# on 04-Mar-2017 (Sat)

#### Annotation 1479867239692

#deeplearning #neuralnetworks
The transp ose of a matrix pro duct has a simple form: $$(AB)^{T} = B^{T}A^{T}$$ . (2.9) This allo ws us to demonstrate equation , b y exploiting the fact that the v alue 2.8 of suc h a pro duct is a scalar and therefore equal to its o wn transp ose:$$x^Ty = (x^Ty)^T = y^T x$$

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#### Annotation 1479876414732

#deeplearning #neuralnetworks
W e can now solve equation Ax = b by the following steps:
1. A-1Ax = A−1b
2. Inx = A−1b

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#### Annotation 1480139345164

#bayes #programming #r #statistics
The “evidence” for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value

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#### Annotation 1481188969740

#matlab #programming
The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3)2 , as small as possible.

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#### Annotation 1481235369228

#bayes #programming #r #statistics
The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values.

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#### Annotation 1481343896844

#deeplearning #neuralnetworks
The L 1 norm is commonly used in machine learning when the diﬀerence b etw een zero and nonzero elements is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 by $$\epsilon$$, the L 1 norm increases b y $$\epsilon$$.

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#### Annotation 1481354906892

#deeplearning #neuralnetworks
T o compute diag(v)x , we only need to scale each element xi b y vi . In other w ords, diag(v)x = $$x\cdot y$$

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#### Annotation 1481364344076

#deeplearning #neuralnetworks
A unit vector is a vector with unit norm ||x||2 = 1

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#### Annotation 1481365916940

#deeplearning #neuralnetworks
A vector x and a vector y are orthogonal to each other if xTy = 0 .

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#### Annotation 1481373781260

#deeplearning #neuralnetworks
An eigenvector of a square matrix A is a non-zero vector v suc h that m ulti- plication b y A alters only the scale of v: Av = λv

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#### Annotation 1481375354124

#deeplearning #neuralnetworks
Av= λv
The scalar λ is kno wn as the eigen v alue corresp onding to this eigenv ector. (One can also ﬁnd a left eigen v ector suc h that v A = λ v , but we are usually concerned with righ t eigenv ectors

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#### Annotation 1481405238540

#deeplearning #neuralnetworks
SVD of A = UVDT

The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of V are kno wn as as the right-singular v ectors

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#### Annotation 1481406811404

#deeplearning #neuralnetworks
W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AAT . The righ t-singular v ectors of A are the eigen vectors of ATA . The non-zero singular v alues of A are the square ro ots of the eigen v alues of ATA . The same is true for AAT

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#### Annotation 1481720859916

#bayes #programming #r #statistics
In other words, the normalizer for the beta distribution is the beta function $$B(a,b) = \int d\theta \space \theta^{a-1}(1-\theta)^{b-1}$$

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#### Annotation 1481722432780

#bayes #programming #r #statistics
In R, beta(θ|a, b) is dbeta(θ,a,b),and B(a, b) is beta(a,b)

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#### Annotation 1481746025740

#bayes #programming #r #statistics
The standard deviation of the beta distribution is $$\sqrt{μ(1 − μ)/(a + b +1)}$$. Notice that the standard deviation gets smaller when the concentration κ = a + b gets larger.

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Article 1482331131148

This may be [...]

#### Annotation 1482334801164

Waste management or Waste disposal is all the activities and actions required to manage waste from its inception to its final disposal.[1] This includes amongst other things, collection, transport, treatment and disposal of waste together with monitoring and regulation. It also encompasses the legal and regulatory framework that relates to waste management encompassing guidance on recycling etc.

Waste management - Wikipedia
s. Unsourced material may be challenged and removed. (May 2011) (Learn how and when to remove this template message) [imagelink] Waste management in Kathmandu, Nepal [imagelink] Waste management in Stockholm, Sweden <span>Waste management or Waste disposal is all the activities and actions required to manage waste from its inception to its final disposal. [1] This includes amongst other things, collection, transport, treatment and disposal of waste together with monitoring and regulation. It also encompasses the legal and regulatory framework that relates to waste management encompassing guidance on recycling etc. The term normally relates to all kinds of waste, whether generated during the extraction of raw materials, the processing of raw materials into intermediate and final products, the co

#### Flashcard 1483106028812

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#deeplearning #neuralnetworks
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An [...] is the com bination of an enco der function that con v erts the input data into a diﬀeren t representation, and a deco der function that conv erts the new representation back into the original format
autoenco der

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An autoenco der is the com bination of an enco der function that con v erts the input data into a diﬀeren t representation, and a deco der function that conv erts the new representation back into the o

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#### Flashcard 1483107601676

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#deeplearning #neuralnetworks
Question
An autoenco der is the com bination of an [...], and a deco der function that conv erts the new representation back into the original format
enco der function that con v erts the input data into a diﬀeren t representation

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An autoenco der is the com bination of an enco der function that con v erts the input data into a diﬀeren t representation, and a deco der function that conv erts the new representation back into the original format

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#### Flashcard 1483109174540

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#deeplearning #neuralnetworks
Question
An autoenco der is the com bination of an enco der function that con v erts the input data into a diﬀeren t representation, and a [...]
deco der function that conv erts the new representation back into the original format

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An autoenco der is the com bination of an enco der function that con v erts the input data into a diﬀeren t representation, and a deco der function that conv erts the new representation back into the original format

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#### Flashcard 1483110747404

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#matlab #programming
Question
[...] determinant.
det

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det determinant.

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#### Flashcard 1483112320268

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#matlab #programming
Question
det [...]
determinant.

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det determinant.

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#### Flashcard 1483113893132

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#matlab #programming
Question
[...] eigenvalue decomposition
eig

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eig eigenvalue decomposition

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#### Flashcard 1483115465996

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#matlab #programming
Question
eig [...]
eigenvalue decomposition

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eig eigenvalue decomposition

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#### Flashcard 1483117038860

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#matlab #programming
Question
[...] singular value decomposition
svd

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svd singular value decomposition

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#### Flashcard 1483118611724

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#matlab #programming
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svd [...]
singular value decomposition

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svd singular value decomposition

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#### Flashcard 1483120184588

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#biochem #biology #cell
Question
The piecing together of the complete [...] pathway in the 1930s was a major triumph of biochemistry
glycolytic

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The piecing together of the complete glycolytic pathway in the 1930s was a major triumph of biochemistry

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#### Flashcard 1483121757452

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#biochem #biology #cell
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The piecing together of the complete glycolytic pathway in the [...] was a major triumph of biochemistry
1930s

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The piecing together of the complete glycolytic pathway in the 1930s was a major triumph of biochemistry

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#### Flashcard 1483123330316

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#biochem #biology #cell
Question
Two central reactions in glycolysis (steps 6 and 7) convert the [...] into 3-phosphoglycerate (a carboxylic acid; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.
three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde)

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Two central reactions in glycolysis (steps 6 and 7) convert the three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde) into 3-phosphoglycerate (a carboxylic acid; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.

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#### Flashcard 1483124903180

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#biochem #biology #cell
Question
Two central reactions in glycolysis (steps 6 and 7) convert the three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde) into [...]; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.
3-phosphoglycerate (a carboxylic acid

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Two central reactions in glycolysis (steps 6 and 7) convert the three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde) into 3-phosphoglycerate (a carboxylic acid; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.

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#### Flashcard 1483126476044

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#biochem #biology #cell
Question
In step 6, the enzyme [...] couples the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond. At the same time, it enables energy to be stored in NADH. The formation of the high-energy phosphate bond is driven by the oxidation reaction, and the enzyme thereby acts like the “paddle wheel” coupler
glyceraldehyde 3-phosphate dehydrogenase

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In step 6, the enzyme glyceraldehyde 3-phosphate dehydrogenase couples the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond. At the same time, it enables energy to be s

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#### Flashcard 1483128048908

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#biochem #biology #cell
Question
In step 6, the enzyme glyceraldehyde 3-phosphate dehydrogenase couples [...]. At the same time, it enables energy to be stored in NADH. The formation of the high-energy phosphate bond is driven by the oxidation reaction, and the enzyme thereby acts like the “paddle wheel” coupler
the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond

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In step 6, the enzyme glyceraldehyde 3-phosphate dehydrogenase couples the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond. At the same time, it enables energy to be stored in NADH. The formation of the high-energy phosphate bond is driven by the oxidation reaction, and the enzyme thereby acts like the

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#### Flashcard 1483129621772

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#deeplearning #neuralnetworks
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W e use the [...] sign to index the complement of a set.

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W e use the sign to index the complement of a set. F or example x − 1 is the v ector con taining all elemen ts of x except for x 1 , and x − S is the v ector con taining all of the elements of exce

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#### Annotation 1483131981068

#deeplearning #neuralnetworks
W e can identi fy all of the n um b ers with v ertical co ordinate i b y writing a “ ” for the horizontal

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W e can identi fy all of the n um b ers with v ertical co ordinate i b y writing a “ ” for the horizontal : co ordinate. F or example, A i, : denotes the horizon tal cross section of A with v ertical co ordinate i

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#### Flashcard 1483133553932

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#deeplearning #neuralnetworks
Question
The transp ose of a matrix is [...]
the mirror image of the matrix across a diagonal line, called the main diagonal , running do wn and to the righ t, starting from its upp er left corner.

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The transp ose of a matrix is the mirror image of the matrix across a diagonal line, called the main diagonal , running do wn and to the righ t, starting from its upp er left corner.

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#### Flashcard 1483137223948

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#deeplearning #neuralnetworks
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Note that the standard pro duct of tw o matrices is just a matrix con taining not the pro duct of the individual elements. Suc h an op eration exists and is called the [...] , and is denoted as . A
elemen t-wise pro duct Hadamard pro duct or

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Note that the standard pro duct of tw o matrices is just a matrix con taining not the pro duct of the individual elements. Suc h an op eration exists and is called the elemen t-wise pro duct Hadamard pro duct or , and is denoted as . A

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#### Flashcard 1483138796812

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#deeplearning #neuralnetworks
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Is the dot pro duct b etw een tw o v ectors comm utativ e?
Yes

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the dot pro duct b etw een tw o v ectors is comm utativ e: x y y = x

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#### Flashcard 1483144826124

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#deeplearning #neuralnetworks
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The transp ose of a matrix pro duct has a simple form [...] (2.9) This allo ws us to demonstrate equation , b y exploiting the fact that the v alue 2.8 of suc h a pro duct is a scalar and therefore equal to its o wn transp ose:$$x^Ty = (x^Ty)^T = y^T x$$
simple form: $$(AB)^{T} = B^{T}A^{T}$$ .

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The transp ose of a matrix pro duct has a simple form: $$(AB)^{T} = B^{T}A^{T}$$ . (2.9) This allo ws us to demonstrate equation , b y exploiting the fact that the v alue 2.8 of suc h a pro duct is a scalar and therefore equal to its o wn transp ose:$$x^Ty = (x^Ty)^T #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483147185420 Tags #deeplearning #neuralnetworks Question W e can now solve equation Ax = b by the following steps: [...] Answer 1. A-1Ax = A−1b 2. Inx = A−1b status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it W e can now solve equation Ax = b by the following steps: 1. A -1 Ax = A −1 b 2. I n x = A −1 b #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483148758284 Tags #biochem #biology #cell Question fatty acids enter the bloodstream, where they bind to the abundant blood protein, [...] Answer serum albumin. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it fatty acids enter the bloodstream, where they bind to the abundant blood protein, serum albumin. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483150331148 Tags #biochem #biology #cell Question In addition to three molecules of NADH, each turn of the cycle also produces one molecule of [...] from FAD (see Figure 2–39), and one mol- ecule of the ribonucleoside triphosphate GTP from GDP Answer FADH 2 (reduced flavin adenine dinucleotide) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it In addition to three molecules of NADH, each turn of the cycle also produces one molecule of FADH 2 (reduced flavin adenine dinucleotide) from FAD (see Figure 2–39), and one mol- ecule of the ribonucleoside triphosphate GTP from GDP #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483151904012 Tags #biochem #biology #cell Question In addition to three molecules of NADH, each turn of the cycle also produces one molecule of FADH 2 (reduced flavin adenine dinucleotide) from FAD (see Figure 2–39), and one mol- ecule of the [...] Answer ribonucleoside triphosphate GTP from GDP status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it In addition to three molecules of NADH, each turn of the cycle also produces one molecule of FADH 2 (reduced flavin adenine dinucleotide) from FAD (see Figure 2–39), and one mol- ecule of the ribonucleoside triphosphate GTP from GDP #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483153476876 Tags #biochem #biology #cell Question n total, the complete oxidation of a molecule of glucose to H 2 O and CO 2 is used by the cell to produce about [...] molecules of ATP. Answer 30 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it n total, the complete oxidation of a molecule of glucose to H 2 O and CO 2 is used by the cell to produce about 30 molecules of ATP. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483155049740 Tags #biochem #biology #cell Question All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from [...] Answer glucose. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it pan>All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose.<span><body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483156622604 Tags #biochem #biology #cell Question All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino [...], whereas the ribose and deoxyribose sugars are derived from glucose. Answer acids glutamine, aspartic acid, and glycine status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483158195468 Tags #biochem #biology #cell Question All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the [...] are derived from glucose. Answer ribose and deoxyribose sugars status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483159768332 Tags #biochem #biology #cell Question All of the [...] (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose. Answer nitrogens in the purine and pyrimidine bases status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose.< #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483161341196 Tags #biochem #biology #cell Question Sulfur is abundant on Earth in its most oxidized form, [...]. Answer sulfate (SO 4 2– ) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Sulfur is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the amino ac #### Original toplevel document (pdf) cannot see any pdfs #### Annotation 1483162914060 #biochem #biology #cell To be useful for life, sulfate must be reduced to sulfide (S 2– ) status not read #### Parent (intermediate) annotation Open it Sulfur is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the amino acids methionine and cysteine, coenzyme A (see Figure 2–39), and the i #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483164486924 Tags #biochem #biology #cell Question Sulfur is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the [...] (see Figure 14–16) Answer amino acids methionine and cysteine, coenzyme A (see Figure 2–39), and the iron-sulfur centers essential for electron transport status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the <span>amino acids methionine and cysteine, coenzyme A (see Figure 2–39), and the iron-sulfur centers essential for electron transport (see Figure 14–16)<span><body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483169205516 Question [default - edit me] Answer The pressure in the pipe is nearest (A) 843 Pa (B) 981 Pa (C) 1270 P status measured difficulty not learned 37% [default] 0 #### pdf cannot see any pdfs #### Flashcard 1483508419852 Tags #biochem #biology #cell Question Humans and other animals cannot [...] and must therefore acquire the sulfur they need for their metabolism in the food that they eat Answer reduce sulfate status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Humans and other animals cannot reduce sulfate and must therefore acquire the sulfur they need for their metabolism in the food that they eat #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483512089868 Tags #biochem #biology #cell Question Humans and other animals cannot reduce sulfate and must therefore [...] Answer acquire the sulfur they need for their metabolism in the food that they eat status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Humans and other animals cannot reduce sulfate and must therefore acquire the sulfur they need for their metabolism in the food that they eat #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483558751500 Tags #biochem #biology #cell Question The characteristic “size” for each atom is specified by [...]. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii Answer a unique van der Waals radius status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483563470092 Tags #biochem #biology #cell Question The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the [...] Answer sum of their van der Waals radii status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483568188684 Tags #biochem #biology #cell Question The characteristic “size” for each atom is specified by a unique van der Waals radius. The [...] is the sum of their van der Waals radii Answer contact distance between any two noncovalently bonded atoms status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483658890508 Tags #matlab #programming Question [...] can also be done with the reshape function Answer Reshaping status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Reshaping can also be done with the reshape function #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483663609100 Tags #matlab #programming Question Reshaping can also be done with the [...] function Answer reshape status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Reshaping can also be done with the reshape function #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483673570572 Tags #matlab #programming Question On the right-hand side of an assignment, [...] gives all the elements of a strung out by columns in one long column vector Answer a(:) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it On the right-hand side of an assignment, a(:) gives all the elements of a strung out by columns in one long column vector #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483679337740 Tags #matlab #programming Question On the right-hand side of an assignment, a(:) gives [...] Answer all the elements of a strung out by columns in one long column vector status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it On the right-hand side of an assignment, a(:) gives all the elements of a strung out by columns in one long column vector #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483693493516 Tags #matlab #programming Question As a special case, [...] may be used to replace all the elements of a matrix with a scalar, e.g., a(:) = -1 Answer a single colon subscript status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it As a special case, a single colon subscript may be used to replace all the elements of a matrix with a scalar, e.g., a(:) = -1 #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483699260684 Tags #matlab #programming Question As a special case, a single colon subscript may be used to [...], e.g., a(:) = -1 Answer replace all the elements of a matrix with a scalar status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it As a special case, a single colon subscript may be used to replace all the elements of a matrix with a scalar, e.g., a(:) = -1 #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483706076428 Tags #matlab #programming Question You can’t delete a single element from a matrix while keeping it a matrix, so a statement like [...] results in an error Answer a(1,2) = [ ] status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it You can’t delete a single element from a matrix while keeping it a matrix, so a statement like a(1,2) = [ ] results in an error #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483723377932 Tags #deeplearning #neuralnetworks Question T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying [...] (the p oin t sp eciﬁed b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp eciﬁes ho w far we should trav el in eac h of these directions, with x i sp ecifying how far to mo v e in the direction of column : Answer diﬀerent directions we can tra v el from the origin status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying diﬀerent directions we can tra v el from the origin (the p oin t sp eciﬁed b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp eciﬁes ho w far we should trav el in ea #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483731242252 Tags #deeplearning #neuralnetworks Question T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying diﬀerent directions we can tra v el from the origin (the p oin t sp eciﬁed b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x [...], with x i sp ecifying how far to mo v e in the direction of column i: Answer sp eciﬁes ho w far we should trav el in eac h of these directions status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it we can think of the columns of A as sp ecifying diﬀerent directions we can tra v el from the origin (the p oin t sp eciﬁed b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x <span>sp eciﬁes ho w far we should trav el in eac h of these directions, with x i sp ecifying how far to mo v e in the direction of column :<span><body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483737009420 Tags #deeplearning #neuralnetworks Question T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying diﬀerent directions we can tra v el from the origin (the p oin t sp eciﬁed b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp eciﬁes ho w far we should trav el in eac h of these directions, with x i [...]n : Answer sp ecifying how far to mo v e in the direction of colum status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it ra v el from the origin (the p oin t sp eciﬁed b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp eciﬁes ho w far we should trav el in eac h of these directions, with x i <span>sp ecifying how far to mo v e in the direction of column :<span><body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483786292492 Tags #bayes #programming #r #statistics Question The “evidence” for the model, p(D), is [...] Answer the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The “evidence” for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483789962508 Tags #bayes #programming #r #statistics Question The [...] for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value Answer “evidence” status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The “evidence” for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in th #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483800972556 Tags #bayes #programming #r #statistics Question In many models, the probability of data, p(D|θ), does not depend in any way on other data. That is, the joint probability p(D, D |θ) equals p(D|θ)·p(D |θ). In other words, in this sort of model, the data probabilities are [...]. Under this condition, then the order of updating has no effect of the final posterior Answer independent (recall that independence was defined in Section 4.4.2) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it body>In many models, the probability of data, p(D|θ), does not depend in any way on other data. That is, the joint probability p(D, D |θ) equals p(D|θ)·p(D |θ). In other words, in this sort of model, the data probabilities are independent (recall that independence was defined in Section 4.4.2). Under this condition, then the order of updating has no effect of the final posterior<body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483813031180 Tags #bayes #programming #r #statistics Question a general phenomenon in Bayesian inference: The posterior is a compromise [...]. Answer between the prior distribution and the likelihood function status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it a general phenomenon in Bayesian inference: The posterior is a compromise between the prior distribution and the likelihood function. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483824041228 Tags #bayes #programming #r #statistics Question The compromise favors the prior to the extent that [...]. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many. Answer the prior distribution is sharply peaked and the data are few status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483828759820 Tags #bayes #programming #r #statistics Question The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that [...] Answer the prior distribution is flat and the data are many. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483834526988 Tags #bayes #programming #r #statistics Question The compromise favors the [...] to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many. Answer prior status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distributio #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483838197004 Tags #bayes #programming #r #statistics Question The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the [...] to the extent that the prior distribution is flat and the data are many. Answer likelihood function (i.e., the data) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483850255628 Tags #bayes #programming #r #statistics Question the mode of the posterior distribution is between [...], but the posterior mode is closer to the likelihood mode for larger sample sizes Answer the mode of the prior distribution and the mode of the likelihood function status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the mode of the posterior distribution is between the mode of the prior distribution and the mode of the likelihood function, but the posterior mode is closer to the likelihood mode for larger sample sizes #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483858119948 Tags #bayes #programming #r #statistics Question the mode of the posterior distribution is between the mode of the prior distribution and the mode of the likelihood function, but the posterior mode is closer to [...] for larger sample sizes Answer the likelihood mode status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the mode of the posterior distribution is between the mode of the prior distribution and the mode of the likelihood function, but the posterior mode is closer to the likelihood mode for larger sample sizes #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483870178572 Tags #matlab #programming Question the functions [...] generate matrices of 1s, 0s and random numbers, respectively. With a single argument n, they generate n × n (square) matrices. With two arguments n and m they generate n × m ma- trices. Answer zeros, ones and rand status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the functions zeros, ones and rand generate matrices of 1s, 0s and random numbers, respectively. With a single argument n, they generate n × n (square) matrices. With two arguments n and m they generate n × m ma- trices. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483875945740 Tags #matlab #programming Question The function [...] generates an n × n identity matrix, i.e., a matrix with 1s on the main ‘diagonal’, and 0s everywhere else Answer eye(n) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The function eye(n) generates an n × n identity matrix, i.e., a matrix with 1s on the main ‘diagonal’, and 0s everywhere else #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483882761484 Tags #matlab #programming Question [...] extracts or creates a diagonal Answer diag status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it diag extracts or creates a diagonal #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483886431500 Tags #matlab #programming Question diag [...] Answer extracts or creates a diagonal status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it diag extracts or creates a diagonal #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483891150092 Tags #matlab #programming Question [...] extracts the upper triangular part Answer triu status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it triu extracts the upper triangular part #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483895868684 Tags #matlab #programming Question triu [...] Answer extracts the upper triangular part status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it triu extracts the upper triangular part #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483907927308 Tags #biochem #biology #cell Question although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than [...] ago from studies of hair and silk Answer 60 years status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than 60 years ago from studies of hair and silk #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483910548748 Tags #biochem #biology #cell Question although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than 60 years ago from studies of [...] Answer hair and silk status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than 60 years ago from studies of hair and silk #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483919461644 Tags #biochem #biology #cell Question Within [...] of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids Answer a year status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly comm #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483924180236 Tags #biochem #biology #cell Question Within a year of the discovery of the α helix, a second folded structure, called a [...], was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids Answer β sheet status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483926801676 Tags #biochem #biology #cell Question Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein [...], the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids Answer fibroin status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, with #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483931520268 Tags #biochem #biology #cell Question Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of [...]. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids Answer silk status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains o #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483938336012 Tags #biochem #biology #cell Question Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because [...] Answer they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it l>Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids<html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483944103180 Tags #matlab #programming Question [...] inverse. Answer inv status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it inv inverse. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483947773196 Tags #matlab #programming Question inv [...] Answer inverse. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it inv inverse. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483955637516 Tags #matlab #programming Question [...] orthogonal factorization Answer qr status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it qr orthogonal factorization #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483957210380 Tags #matlab #programming Question qr [...] Answer orthogonal factorization status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it qr orthogonal factorization #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483970317580 Tags #matlab #programming Question To see how MATLAB solves this system, first recall that the left division operator \ may be used on scalars, i.e., a\bis the same as b/aif a and b are scalars. However, it can also be used on vectors and matrices, in order to [...] Answer solve linear equations status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it body>To see how MATLAB solves this system, first recall that the left division operator \ may be used on scalars, i.e., a\bis the same as b/aif a and b are scalars. However, it can also be used on vectors and matrices, in order to solve linear equations<body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483976084748 Tags #matlab #programming Question When we have more equations than unknowns, the system is called [...] Answer over- determined status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it When we have more equations than unknowns, the system is called over- determined #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1483982900492 Tags #matlab #programming Question When we [...], the system is called over- determined Answer have more equations than unknowns status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it When we have more equations than unknowns, the system is called over- determined #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484063116556 Tags #matlab #programming Question The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the [...]. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3)2 , as small as possible. Answer least squares best fit status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3) 2 , as small as possible. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484073078028 Tags #matlab #programming Question The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which [...] Answer makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3)2 , as small as possible. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3) 2 , as small as possible. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484080942348 Tags #matlab #programming Question If there are fewer equations than unknowns, the system is called [...]. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns. Answer under- determined status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484086709516 Tags #matlab #programming Question If there are fewer equations than unknowns, the system is called under- determined. In this case there are an [...] number of solutions; MATLAB will find one which has zeros for some of the unknowns. Answer infinite status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484092476684 Tags #matlab #programming Question If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will [...] Answer find one which has zeros for some of the unknowns. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484100341004 Tags #matlab #programming Question A system like this is called [...] meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning Answer ill-conditioned, status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning</s #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484106108172 Tags #matlab #programming Question A system like this is called ill-conditioned, meaning that a [...]. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning Answer small change in the co- efficients leads to a large change in the solution status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484108729612 Tags #matlab #programming Question A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function [...] returns the condition estimator, which tests for ill conditioning Answer rcond status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484113448204 Tags #matlab #programming Question A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the [...] Answer condition estimator, which tests for ill conditioning status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484119215372 Tags #matlab #programming Question The function [...] provides a neat visualization of sparse matrices. Answer spy status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The function spy provides a neat visualization of sparse matrices. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484121836812 Tags #matlab #programming Question The function spy provides a [...] Answer neat visualization of sparse matrices. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The function spy provides a neat visualization of sparse matrices. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484131798284 Tags #bayes #programming #r #statistics Question The space of possibilities is the j[...]. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values. Answer oint parameter space involving all combinations of parameter values status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484147789068 Tags #bayes #programming #r #statistics Question The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are [...] of parameter values. Answer 1,000 P combinations status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484166139148 Tags #biochem #biology #cell Question Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a [...] to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge ( Answer polarity status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge ( #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484168760588 Tags #biochem #biology #cell Question Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a [...] and the N-terminus a partial positive charge ( Answer partial negative status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge ( #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484173479180 Tags #biochem #biology #cell Question Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a [...] charge ( Answer partial positive status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it y>Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge (<body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484186586380 Tags #biochem #biology #cell Question The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in [...] directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand alternately project above and below the plane of the sheet Answer opposite (antiparallel) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484193402124 Tags #biochem #biology #cell Question The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand [...] Answer alternately project above and below the plane of the sheet status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it nt peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand <span>alternately project above and below the plane of the sheet<span><body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484194974988 Tags #biochem #biology #cell Question The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. [...] between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand alternately project above and below the plane of the sheet Answer Hydrogen-bonding status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand alternately project a #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484196547852 Tags #biochem #biology #cell Question An [...] is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every 3.6 amino acids. Answer α helix status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484198120716 Tags #biochem #biology #cell Question An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every [...] peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every 3.6 amino acids. Answer fourth status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every 3.6 amino acids. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484199693580 Tags #biochem #biology #cell Question An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every [...] amino acids. Answer 3.6 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every <span>3.6 amino acids.<span><body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484201266444 Tags #biochem #biology #cell Question α helices wrap around each other to form a particularly sta- ble structure, known as a [...] This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward Answer coiled-coil. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484202839308 Tags #biochem #biology #cell Question [...] wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward Answer α helices status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484204412172 Tags #biochem #biology #cell Question α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when [...] Answer the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484205985036 Tags #biochem #biology #cell Question This is the protein domain, [...] Answer a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it This is the protein domain, a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484207557900 Tags #biochem #biology #cell Question This is the [...], a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure. Answer protein domain status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it This is the protein domain, a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure. </ #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484209130764 Tags #biochem #biology #cell Question A domain usually contains between [...] amino acids, and it is the modular unit from which many larger proteins are constructed Answer 40 and 350 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it A domain usually contains between 40 and 350 amino acids, and it is the modular unit from which many larger proteins are constructed #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484210703628 Tags #biochem #biology #cell Question the [...], which functions in signaling pathways inside vertebrate cells Answer Src protein kinase status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the Src protein kinase, which functions in signaling pathways inside vertebrate cells #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484212276492 Tags #biochem #biology #cell Question the Src protein kinase, which functions in [...] inside vertebrate cells Answer signaling pathways status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the Src protein kinase, which functions in signaling pathways inside vertebrate cells #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484213849356 Tags #biochem #biology #cell Question The smallest protein molecules contain only [...] domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains. Answer a single status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexibl #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484215422220 Tags #biochem #biology #cell Question The smallest protein molecules contain only a single domain, whereas larger proteins can contain [...] domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains. Answer several dozen status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484216995084 Tags #biochem #biology #cell Question The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by [...] Answer short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484218567948 Tags #biochem #biology #cell Question Since each of the 20 amino acids is chemically distinct and each can, in princi- ple, occur at any position in a protein chain, there are [...] different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids, a cell could theoretically make more than 10 390 (20 300 ) different polypeptide chains Answer 20 × 20 × 20 × 20 = 160,000 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Since each of the 20 amino acids is chemically distinct and each can, in princi- ple, occur at any position in a protein chain, there are 20 × 20 × 20 × 20 = 160,000 different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484220140812 Tags #biochem #biology #cell Question Since each of the 20 amino acids is chemically distinct and each can, in princi- ple, occur at any position in a protein chain, there are 20 × 20 × 20 × 20 = 160,000 different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids, a cell could theoretically make more than [...] different polypeptide chains Answer 10 390 (20 300 ) status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it 20 = 160,000 different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids, a cell could theoretically make more than <span>10 390 (20 300 ) different polypeptide chains<span><body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484221713676 Tags #biochem #biology #cell Question Many similar examples show that two pro- teins with more than [...] identity in their amino acid sequences usually share the same overall structure Answer 25% status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Many similar examples show that two pro- teins with more than 25% identity in their amino acid sequences usually share the same overall structure #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484223286540 Tags #biochem #biology #cell Question Many similar examples show that two pro- teins with more than 25% identity in their amino acid sequences usually [...] Answer share the same overall structure status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Many similar examples show that two pro- teins with more than 25% identity in their amino acid sequences usually share the same overall structure #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484224859404 Tags #biochem #biology #cell Question there are a limited number of ways in which protein domains fold up in nature—maybe as few as [...], if we consider all organisms. For most of these so-called protein folds, representative structures have been determined. Answer 2000 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it there are a limited number of ways in which protein domains fold up in nature—maybe as few as 2000, if we consider all organisms. For most of these so-called protein folds, representative structures have been determined. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484226432268 Tags #biochem #biology #cell Question The present database of known protein sequences contains more than [...] entries Answer twenty million status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The present database of known protein sequences contains more than twenty million entries #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484228005132 Tags #biochem #biology #cell Question The encoded polypeptides range widely in size, from [...] amino acids to a gigantic pro- tein of 33,000 amino acids. Answer 6 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The encoded polypeptides range widely in size, from 6 amino acids to a gigantic pro- tein of 33,000 amino acids. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484229577996 Tags #biochem #biology #cell Question The encoded polypeptides range widely in size, from 6 amino acids to a gigantic pro- tein of [...] amino acids. Answer 33,000 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The encoded polypeptides range widely in size, from 6 amino acids to a gigantic pro- tein of 33,000 amino acids. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484231150860 Tags #biochem #biology #cell Question most proteins are composed of a series of protein domains, in which different regions of the polypeptide chain fold independently to form compact structures. Such multidomain proteins are believed to have originated from the [process] , cre- ating a new gene. Answer accidental joining of the DNA sequences that encode each domain status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it dy>most proteins are composed of a series of protein domains, in which different regions of the polypeptide chain fold independently to form compact structures. Such multidomain proteins are believed to have originated from the accidental joining of the DNA sequences that encode each domain, cre- ating a new gene.<body><html> #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484232723724 Tags #biochem #biology #cell Question In an evolutionary process called [...], many large proteins have evolved through the joining of preexisting domains in new com- binations (Figure 3–14). Novel binding surfaces have often been created at the juxtaposition of domains, and many of the functional sites where proteins bind to small molecules are found to be located there. Answer domain shuffling status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it In an evolutionary process called domain shuffling, many large proteins have evolved through the joining of preexisting domains in new com- binations (Figure 3–14). Novel binding surfaces have often been created at the juxtaposition o #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484234296588 Tags #biochem #biology #cell Question β-sheet-based domains may have achieved their evolutionary success because [...] Answer they provide a convenient framework for the generation of new binding sites for ligands, requiring only small changes to their protruding loops status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it β-sheet-based domains may have achieved their evolutionary success because they provide a convenient framework for the generation of new binding sites for ligands, requiring only small changes to their protruding loops #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484235869452 Tags #biochem #biology #cell Question Stiff extended structures composed of a series of domains are especially common in [...] and in the extracellular portions of cell-surface receptor proteins. Answer extracellular matrix molecules status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484237442316 Tags #biochem #biology #cell Question Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the [...] Answer extracellular portions of cell-surface receptor proteins. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484239015180 Tags #biochem #biology #cell Question [...] composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins. Answer Stiff extended structures status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484241636620 Tags #biochem #biology #cell Question N- and C-terminal ends at opposite poles of the domain. When the DNA encoding such a domain undergoes [...], which is not unusual in the evolution of genomes (discussed in Chapter 4), the duplicated domains with this “in-line” arrangement can be readily linked in series to form extended structures—either with themselves or with other in-line domains Answer tandem duplica- tion status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it N- and C-terminal ends at opposite poles of the domain. When the DNA encoding such a domain undergoes tandem duplica- tion, which is not unusual in the evolution of genomes (discussed in Chapter 4), the duplicated domains with this “in-line” arrangement can be readily linked in series to form extended str #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484243209484 Tags #biochem #biology #cell Question [...] of all domain families are common to archaea, bacteria, and eukaryotes, only about 5% of the two-domain combi- nations are similarly shared. Answer half status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it half of all domain families are common to archaea, bacteria, and eukaryotes, only about 5% of the two-domain combi- nations are similarly shared. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484244782348 Tags #biochem #biology #cell Question half of all domain families are common to archaea, bacteria, and eukaryotes, only about [...] of the two-domain combi- nations are similarly shared. Answer 5% status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it half of all domain families are common to archaea, bacteria, and eukaryotes, only about 5% of the two-domain combi- nations are similarly shared. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484246355212 Tags #biochem #biology #cell Question most proteins containing especially useful two-domain combinations arose through [...] rel- atively late in evolution Answer domain shuffling status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it most proteins containing especially useful two-domain combinations arose through domain shuffling rel- atively late in evolution #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484247928076 Tags #biochem #biology #cell Question most proteins containing especially useful two-domain combinations arose through domain shuffling rel- atively [...] in evolution Answer late status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it most proteins containing especially useful two-domain combinations arose through domain shuffling rel- atively late in evolution #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484249500940 Tags #biochem #biology #cell Question we currently lack even the tiniest hint of what the function might be for more than [...] of the proteins that have thus far been identified through examining the human genome Answer 10,000 status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it we currently lack even the tiniest hint of what the function might be for more than 10,000 of the proteins that have thus far been identified through examining the human genome #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484251073804 Tags #biochem #biology #cell Question combinations of protein domains, with the result that there are nearly [...] as many combinations of domains found in human proteins as in a worm or a fly. Answer twice status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it combinations of protein domains, with the result that there are nearly twice as many combinations of domains found in human proteins as in a worm or a fly. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484252646668 Tags #deeplearning #neuralnetworks Question Determining whether Ax = b has a solution th us amounts to testing whether [...] . This particular span is known as the column space range or the of . A Answer b is in the span of the columns of A status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Determining whether Ax = b has a solution th us amounts to testing whether b is in the span of the columns of A . This particular span is known as the column space range or the of . A #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484255005964 Tags #deeplearning #neuralnetworks Question Determining whether Ax = b has a solution th us amounts to testing whether b is in the span of the columns of A . This particular span is known as the [...] Answer column space range or the of . A status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Determining whether Ax = b has a solution th us amounts to testing whether b is in the span of the columns of A . This particular span is known as the column space range or the of . A #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484257103116 Tags #deeplearning #neuralnetworks Question Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a suﬃcien t condition, b ecause [...] Answer it is p ossible for some of the columns to b e redundan t. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a suﬃcien t condition, b ecause it is p ossible for some of the columns to b e redundan t. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484258675980 Tags #deeplearning #neuralnetworks Question Ha ving [...] is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a suﬃcien t condition, b ecause it is p ossible for some of the columns to b e redundan t. Answer n m ≥ status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a suﬃcien t condition, b ecause it is p ossible for some of the columns to b e redundan t.< #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484260248844 Tags #deeplearning #neuralnetworks Question Ha ving n m ≥ is only a necessary condition for [...] It is not a suﬃcien t condition, b ecause it is p ossible for some of the columns to b e redundan t. Answer ev ery p oin t to ha ve a solution. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a suﬃcien t condition, b ecause it is p ossible for some of the columns to b e redundan t. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484261821708 Tags #deeplearning #neuralnetworks Question F ormally , this kind of redundancy is kno wn as [...] . A set of v ectors is linearly indep enden t if no v ector in the set is a linear combination of the other vectors. Answer linear dep endence status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it F ormally , this kind of redundancy is kno wn as linear dep endence . A set of v ectors is linearly indep enden t if no v ector in the set is a linear combination of the other vectors. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484263394572 Tags #deeplearning #neuralnetworks Question F ormally , this kind of redundancy is kno wn as linear dep endence . A set of v ectors is linearly indep enden t if [...] Answer no v ector in the set is a linear combination of the other vectors. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it F ormally , this kind of redundancy is kno wn as linear dep endence . A set of v ectors is linearly indep enden t if no v ector in the set is a linear combination of the other vectors. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484264967436 Tags #deeplearning #neuralnetworks Question the deriv ativ es of the [...] with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector Answer squared L 2 norm status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector</b #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484266540300 Tags #deeplearning #neuralnetworks Question the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on [...] , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector Answer the corresp onding elemen t of x status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484268113164 Tags #deeplearning #neuralnetworks Question the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on [...] Answer the en tire vector status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484269686028 Tags #deeplearning #neuralnetworks Question The [...] is commonly used in machine learning when the diﬀerence b etw een zero and nonzero elements is v ery imp ortan t. Answer L 1 norm status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The L 1 norm is commonly used in machine learning when the diﬀerence b etw een zero and nonzero elements is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 b y , the L 1 norm #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484271258892 Tags #deeplearning #neuralnetworks Question The L 1 norm is commonly used in machine learning when [...] is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 b y , the L 1 norm increases b y . Answer the diﬀerence b etw een zero and nonzero elements status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it The L 1 norm is commonly used in machine learning when the diﬀerence b etw een zero and nonzero elements is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 b y , the L 1 norm increases b y . #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484273618188 Tags #deeplearning #neuralnetworks Question Diagonal matrices are of interest in part b ecause [...] Answer multiplying by a diagonal matrix is very computationally eﬃcien t. status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Diagonal matrices are of interest in part b ecause multiplying by a diagonal matrix is very computationally eﬃcien t. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484275191052 Tags #deeplearning #neuralnetworks Question [...] matrices are of interest in part b ecause multiplying by a diagonal matrix is very computationally eﬃcien t. Answer Diagonal status measured difficulty not learned 37% [default] 0 #### Parent (intermediate) annotation Open it Diagonal matrices are of interest in part b ecause multiplying by a diagonal matrix is very computationally eﬃcien t. #### Original toplevel document (pdf) cannot see any pdfs #### Flashcard 1484278336780 Tags #deeplearning #neuralnetworks Question T o compute [...] , we only need to scale each element xi b y vi . In other w ords, diag(v)x = \(x\cdot y$$
diag(v)x

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T o compute diag(v)x , we only need to scale each element x i b y v i . In other w ords, diag(v)x = x⋅yx⋅y

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T o compute diag(v)x , we only need to [...] . In other w ords, diag(v)x = $$x\cdot y$$
scale each element xi b y vi

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T o compute diag(v)x , we only need to scale each element x i b y v i . In other w ords, diag(v)x = x⋅yx⋅y

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There are the 3 "A" core expressions the are used to protect the attacment relationship, and lead to the 5 different survival styles, What are these 3 core expressions? (each start with the letter A)
Anger, Aggression, Authenticitcy

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1. When core needs are not met by children of rel trauma, what 4 negative experiences (3 start w/D and 1 w/ i) that the adaptive stratagies are trying to help deal with.
2. What are the key parts of self does NARM empahsize to help develp a healthy regulatroy system?
1. Disconnection, Dysregulation, Disorganisation and Issolation.
2. Organized, Coherent, and Functional

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What is the goal of the Pride Based Counter Indenfication?
Pride based counter identifications reflect how we would liek to see ourselves or others see us, the paroix is the more energy a person invest in these defensive the stronger the shame based id becomes.

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What are the 12 steps of the NARM healing cycle?
1. INCREASING AWARENESS OF ADAPTIVE SURVIVAL SYTLES
2. Inquiry into identiy
3. Disidentification from shame and pride based identifications
4. Self hatred self rejection and jugements diminished
5. Reconnection with core needs and capacities
6. Resoriaton of connection and aliveness
7. INCREASING CAPCITY FOR SOMATIC AWARENESS
8. Somatic Mindfulness
9. Discharge of shoke states
10. increasing regulation and presence
11. Increasing contact with the body
12. Greater capacity for self regulations
(Rinse and repeat)

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What is the difference between psychodynamic and esoteric approaches to ego?
What are the pros/cons to these different approaches?
Psychodynamic work to sokidify the sense of identify and strengthen the ego, where as esoteric orientations hold that egow is an illusion and separates us fro Being and keeps us from experiencing teh spaciousness, fulidity, and fullness of our essential nature.
Both perspectives are important, Esoteric approaches address the limitations of what they call Ego, but generally do not incorarate the clinical awareness of the importance of attachement adn developmental trauma in creation of the sense of self.

Brief answer: psychodynmic focus on Strengthen ego vs Esoteric focus on release ego. Psychodynamic supports impact on ego caused by rel trauma while esoteric supports learning how to better regulate and re-wire the adaptive stratagies developed by the truama.

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What is the paradox of change?
The more we try to change ourselves, the more we prevent change from ocurring, on the other hand, the more we allow ourselves to fully experience who we are, the greater the possibility of change.
Brief: More we resist the more we persist.

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Name a core NARM principle that defines emotional health.
The capacity for connection with self and others defines emotional health.

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Elaborate on the 5 adaptive styles in terms of Survial Adaptions (disclousre) and Stratagy Used to PRotect the Attachement Relationship.
 Core Need Survival Adaption Stratagey USed to Protect The Attach Rel Connection Foreclousing Connection, Disconnect from body and social engagement Children gife up their very sense of existence, discounnect and attempt to become invisible. Attunemet Foreclosing the awareness and expression of personal needs Chidrent give up thier own need in order to focus on the needs of others, particularly the needs of the parents Trust Forclosing trust and healthy interdependence Children give up their quthenticity in order to be who the parents want them to be: best friend, sport star, confidante, etc. Autonomy Foreclosing authentic expression, responding with what they think is expected of them Children give up direct expression of independence in oreder not to feel abandoned or crushed Love-Sexuality Foreclosing love and heart connection, foreclosing sexuality, Forclosing integration of love and sexuality Children try to avoid rejection by perfecting themselves, hoping that they can win love through looks or performance.

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What does each adaptive style develop around to help make sense of the broad spectrum of symptoms often seen in developmental trauam?
Connection: develops around teh need for the conact and the fear of connection
Attunement: Develops around the conflict between having personal needs and the rejection of them.
Trust: develops around both the desire for and the fear of setting limits and expressing independence.
Love-Sexuality: Develops around wanting to love and be loved and the fear of vulnrability. It also develops aroudn the splitting of love and sexuality.

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[...] matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply
Non-square diagonal

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Non-square diagonal matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply

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Non-square diagonal matrices do not hav e [...] but it is still p ossible to multiply by them cheaply
inv erses

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Non-square diagonal matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply

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Non-square diagonal matrices do not hav e inv erses but it is still p ossible [...]
to multiply by them cheaply

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Non-square diagonal matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply

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A [...] is a vector with unit norm ||x||2 = 1
unit vector

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A unit vector is a vector with unit norm ||x|| 2 = 1

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A unit vector is a vector with unit norm [...]
||x||2 = 1

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A unit vector is a vector with unit norm ||x|| 2 = 1

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A vector x and a vector y are [...] to each other if xTy = 0 .
orthogonal

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A vector x and a vector y are orthogonal to each other if x y = 0 .

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A vector x and a vector y are orthogonal to each other if [...]
xTy = 0 .

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A vector x and a vector y are orthogonal to each other if x T y = 0 .

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In R n , at most [...] v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them orthonormal
n

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In R n , at most n v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them orthonormal

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In R n , at most n v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them [...]
orthonormal

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In R n , at most n v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them orthonormal

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An [...] of a square matrix A is a non-zero vector v suc h that m ulti- plication b y A alters only the scale of v : Av = vλ
eigen v ector

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An eigen v ector of a square matrix A is a non-zero vector v suc h that m ulti- plication b y alters only the scale of : A v Av v = λ

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An eigenvector of a square matrix A is a [...]
non-zero vector v suc h that m ulti- plication b y A alters only the scale of v: Av = λv

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An eigenvector of a square matrix A is a non-zero vector v suc h that m ulti- plication b y A alters only the scale of v: Av = λv

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Av = vλ . (2.39) The scalar λ is kno wn as the [...] corresp onding to this eigenv ector. (One can also ﬁnd a left eigen v ector suc h that v A = λ v , but we are usually concerned with righ t eigenv ectors
eigen v alue

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Av v = λ . (2.39) The scalar λ is kno wn as the eigen v alue corresp onding to this eigenv ector. (One can also ﬁnd a left eigen v ector suc h that v A = λ v , but we are usually concerned with righ t eigenv ectors

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Av v = λ . (2.39) The scalar [...] is kno wn as the eigen v alue corresp onding to this eigenv ector. (One can also ﬁnd a left eigen v ector suc h that v A = λ v , but we are usually concerned with righ t eigenv ectors
λ

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Av v = λ . (2.39) The scalar λ is kno wn as the eigen v alue corresp onding to this eigenv ector. (One can also ﬁnd a left eigen v ector suc h that v A = λ v , but we are usually concerned with righ t eigenv ecto

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[...] matrices often arise when the entries are generated by some function of t w o argumen ts that do es not dep end on the order of the arguments
Symmetric

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Symmetric matrices often arise when the entries are generated by some function of t w o argumen ts that do es not dep end on the order of the arguments

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Symmetric matrices often arise when [...]
the entries are generated by some function of t w o argumen ts that do es not dep end on the order of the arguments

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Symmetric matrices often arise when the entries are generated by some function of t w o argumen ts that do es not dep end on the order of the arguments

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A matrix whose eigen v alues are all p ositive or zero-v alued is called [...]
p ositiv e semideﬁ- nite

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A matrix whose eigen v alues are all p ositive or zero-v alued is called p ositiv e semideﬁ- nite

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A matrix whose [...] is called p ositiv e semideﬁ- nite
eigen v alues are all p ositive or zero-v alued

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A matrix whose eigen v alues are all p ositive or zero-v alued is called p ositiv e semideﬁ- nite

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The [...] provides another wa y to factorize a matrix, into singular vectors and singular v alues
singular v alue decomp osition (SVD)

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The singular v alue decomp osition (SVD) provides another wa y to factorize a matrix, into singular vectors and singular v alues

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The singular v alue decomp osition (SVD) provides another wa y to [...]
factorize a matrix, into singular vectors and singular v alues

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The singular v alue decomp osition (SVD) provides another wa y to factorize a matrix, into singular vectors and singular v alues

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if a matrix is [...], the eigendecomp osition is not deﬁned, and w e m ust use a singular v alue decomp osition instead
not square

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if a matrix is not square, the eigendecomp osition is not deﬁned, and w e m ust use a singular v alue decomp osition instead

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if a matrix is not square, the eigendecomp osition is not deﬁned, and w e m ust use a [...] instead
singular v alue decomp osition

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if a matrix is not square, the eigendecomp osition is not deﬁned, and w e m ust use a singular v alue decomp osition instead

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if a matrix is not square, the [...] is not deﬁned, and w e m ust use a singular v alue decomp osition instead
eigendecomp osition

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if a matrix is not square, the eigendecomp osition is not deﬁned, and w e m ust use a singular v alue decomp osition instead

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The elemen ts along the diagonal of D are kno wn as the [...] of the matrix A . The columns of U are known as the left-singular v ectors . The columns of are kno wn as as the V right-singular v ectors
singular v alues

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The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of are kno wn as as the V right-singular v ectors

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The [...] are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of are kno wn as as the V right-singular v ectors
elemen ts along the diagonal of D

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The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of are kno wn as as the V right-singular v ectors</spa

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The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the [...] . The columns of are kno wn as as the V right-singular v ectors
left-singular v ectors

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The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of are kno wn as as the V right-singular v ectors

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The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The [...] are known as the left-singular v ectors . The columns of are kno wn as as the V right-singular v ectors
columns of U

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The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of are kno wn as as the V right-singular v ectors

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SVD of A = UVDT

The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of V are kno wn as as the [...]
right-singular v ectors

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><head>SVD of A = UVD T The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of V are kno wn as as the right-singular v ectors<html>

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SVD of A = UVDT

The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The [...] are kno wn as as the right-singular v ectors
columns of V

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SVD of A = UVD T The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of V are kno wn as as the right-singular v ectors

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W e can actually interpret the singular v alue decomp osition of A in terms of the [...] . The left-singular v ectors of A are the eigen v ectors of AA . The righ t-singular v ectors of A are the eigen vectors of A A . The non-zero singular v alues of A are the square ro ots of the eigen v alues of A A . The same is true for AA
eigendecomposition of functions of A

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AA . The righ t-singular v ectors of A are the eigen vectors of A A . The non-zero singular v alues of A are the square r

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the [...] . The righ t-singular v ectors of A are the eigen vectors of ATA . The non-zero singular v alues of A are the square ro ots of the eigen v alues of ATA . The same is true for AAT
eigen v ectors of AAT

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AA T . The righ t-singular v ectors of A are the eigen vectors of A T A . The non-zero singular v alues of A are the square ro ots of the eigen v alues of A T A . The same is true for AA T<

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The [...] of A are the eigen v ectors of AAT . The righ t-singular v ectors of A are the eigen vectors of ATA . The non-zero singular v alues of A are the square ro ots of the eigen v alues of ATA . The same is true for AAT
left-singular v ectors

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AA T . The righ t-singular v ectors of A are the eigen vectors of A T A . The non-zero singular v alues of A are the square ro ots of the eigen v alues o

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AAT . The [...] of A are the eigen vectors of ATA . The non-zero singular v alues of A are the square ro ots of the eigen v alues of ATA . The same is true for AAT
righ t-singular v ectors

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AA T . The righ t-singular v ectors of A are the eigen vectors of A T A . The non-zero singular v alues of A are the square ro ots of the eigen v alues of A T A . The same is true for AA T

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AAT . The righ t-singular v ectors of A are the eigen vectors of [...] . The non-zero singular v alues of A are the square ro ots of the eigen v alues of ATA . The same is true for AAT
ATA

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can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AA T . The righ t-singular v ectors of A are the eigen vectors of <span>A T A . The non-zero singular v alues of A are the square ro ots of the eigen v alues of A T A . The same is true for AA T<span><body><html>

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AAT . The righ t-singular v ectors of A are the eigen vectors of ATA . The [...] of A are the square ro ots of the eigen v alues of ATA . The same is true for AAT
non-zero singular v alues

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interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AA T . The righ t-singular v ectors of A are the eigen vectors of A T A . The <span>non-zero singular v alues of A are the square ro ots of the eigen v alues of A T A . The same is true for AA T<span><body><html>

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#### Flashcard 1484364582156

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W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AAT . The righ t-singular v ectors of A are the eigen vectors of ATA . The non-zero singular v alues of A are the [...] . The same is true for AAT
square ro ots of the eigen v alues of ATA

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sition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AA T . The righ t-singular v ectors of A are the eigen vectors of A T A . The non-zero singular v alues of A are the <span>square ro ots of the eigen v alues of A T A . The same is true for AA T<span><body><html>

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#### Flashcard 1484366155020

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The function [...] returns 1 if A is global, and 0 otherwise
isglobal(A)

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The function isglobal(A) returns 1 if A is global, and 0 otherwise

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A variable in a function may be declared persistent. Local variables nor- mally cease to exist when a function returns. Persistent variables, however, remain in existence between function calls. A persistent variable is initial- ized to the [...]
empty array

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n>A variable in a function may be declared persistent. Local variables nor- mally cease to exist when a function returns. Persistent variables, however, remain in existence between function calls. A persistent variable is initial- ized to the <span>empty array<span><body><html>

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The function [...] inside an M-file p revents the M-file from being cleared. A locked M-file is unlocked with munlock. The function mislocked indi- cates whether an M-file can be cleared or not.
mlock

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The function mlock inside an M-file p revents the M-file from being cleared. A locked M-file is unlocked with munlock. The function mislocked indi- cates whether an M-file can be cleared or not.</s

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The function mlock inside an M-file [...]. A locked M-file is unlocked with munlock. The function mislocked indi- cates whether an M-file can be cleared or not.
p revents the M-file from being cleared

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The function mlock inside an M-file p revents the M-file from being cleared. A locked M-file is unlocked with munlock. The function mislocked indi- cates whether an M-file can be cleared or not.

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The function mlock inside an M-file p revents the M-file from being cleared. A locked M-file is unlocked with [...]. The function mislocked indi- cates whether an M-file can be cleared or not.
munlock

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The function mlock inside an M-file p revents the M-file from being cleared. A locked M-file is unlocked with munlock. The function mislocked indi- cates whether an M-file can be cleared or not.

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The function mlock inside an M-file p revents the M-file from being cleared. A locked M-file is unlocked with munlock. The function [...] indi- cates whether an M-file can be cleared or not.
mislocked

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The function mlock inside an M-file p revents the M-file from being cleared. A locked M-file is unlocked with munlock. The function mislocked indi- cates whether an M-file can be cleared or not.

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ou might want to write a function that doesn’t return values (such func- tions are called [...] in languages like Pascal and Fortran, and void in C++ and Java
procedures or subroutines

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ou might want to write a function that doesn’t return values (such func- tions are called procedures or subroutines in languages like Pascal and Fortran, and void in C++ and Java

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ou might want to write a function that doesn’t return values (such func- tions are called procedures or subroutines in languages like Pascal and Fortran, and [...] in C++ and Java
void

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ou might want to write a function that doesn’t return values (such func- tions are called procedures or subroutines in languages like Pascal and Fortran, and void in C++ and Java

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#### Flashcard 1484378737932

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the functions [...] can be used to determine the number of actual input and output arguments.
nargin and nargout

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the functions nargin and nargout can be used to determine the number of actual input and output arguments.

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the functions nargin and nargout can be used to [...]
determine the number of actual input and output arguments.

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the functions nargin and nargout can be used to determine the number of actual input and output arguments.

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#### Flashcard 1484381883660

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A function M-file may contain the code for more than one function. The first function in a file is the primary function, and is the one invoked with the M-file name. Additional functions in the file are called [...], and are visible only to the primary function and to other subfunctions.
subfunctions

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l>A function M-file may contain the code for more than one function. The first function in a file is the primary function, and is the one invoked with the M-file name. Additional functions in the file are called subfunctions, and are visible only to the primary function and to other subfunctions.<html>

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#### Flashcard 1484383456524

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A function M-file may contain the code for more than one function. The first function in a file is the primary function, and is the one invoked with the M-file name. Additional functions in the file are called subfunctions, and are visible only to [...]
the primary function and to other subfunctions.

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ction M-file may contain the code for more than one function. The first function in a file is the primary function, and is the one invoked with the M-file name. Additional functions in the file are called subfunctions, and are visible only to <span>the primary function and to other subfunctions.<span><body><html>

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You can use the [...] function to save the parsed version of an M-file for use in later MATLAB sessions, or by users from whom you want to hide your algorithms.
pcode

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You can use the pcode function to save the parsed version of an M-file for use in later MATLAB sessions, or by users from whom you want to hide your algorithms.

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You can use the pcode function to [...] for use in later MATLAB sessions, or by users from whom you want to hide your algorithms.
save the parsed version of an M-file

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You can use the pcode function to save the parsed version of an M-file for use in later MATLAB sessions, or by users from whom you want to hide your algorithms.

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The [...] enables you to see where the bottlenecks in your pro- grams are, e.g., which functions are consuming most of the time. With this information you can often redesign programs to be more efficient. To find out more about this utility open the MATLAB Help documentation via the ‘?’ at the top of the desktop and type “Profiler” in the search space. You should be at the document titled “The Profiler Utility
MATLAB Profiler

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The MATLAB Profiler enables you to see where the bottlenecks in your pro- grams are, e.g., which functions are consuming most of the time. With this information you can often redesign programs to be more e

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#### Flashcard 1484389747980

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Because there are two nominal values, we refer to this sort of data as “[...],” or “nominal with two levels,” or “binomial.”
dichotomous

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Because there are two nominal values, we refer to this sort of data as “dichotomous,” or “nominal with two levels,” or “binomial.”

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Because there are two nominal values, we refer to this sort of data as “dichotomous,” or “[...],” or “binomial.”
nominal with two levels

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Because there are two nominal values, we refer to this sort of data as “dichotomous,” or “nominal with two levels,” or “binomial.”

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#### Flashcard 1484392893708

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Because there are two nominal values, we refer to this sort of data as “dichotomous,” or “nominal with two levels,” or “[...].”
binomial

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Because there are two nominal values, we refer to this sort of data as “dichotomous,” or “nominal with two levels,” or “binomial.”

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#### Flashcard 1484394466572

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Question
Because [...], we refer to this sort of data as “dichotomous,” or “nominal with two levels,” or “binomial.”
there are two nominal values

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Because there are two nominal values, we refer to this sort of data as “dichotomous,” or “nominal with two levels,” or “binomial.”

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The [...] function, although it specifies a probability at each value of θ,isnot a probability distribution. In particular, it does not integrate to 1
likelihood

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The likelihood function, although it specifies a probability at each value of θ,isnot a probability distribution. In particular, it does not integrate to 1

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In other words, the normalizer for the beta distribution is the [equation]
beta function $$B(a,b) = \int d\theta \space \theta^{a-1}(1-\theta)^{b-1}$$

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In other words, the normalizer for the beta distribution is the beta function $$B(a,b) = \int d\theta \space \theta^{a-1}(1-\theta)^{b-1}$$

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In R, beta(θ|a, b) is [...],and B(a, b) is beta(a,b)
dbeta(θ,a,b)

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In R, beta(θ|a, b) is dbeta(θ,a,b),and B(a, b) is beta(a,b)

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In R, beta(θ|a, b) is dbeta(θ,a,b),and B(a, b) is [...]
beta(a,b)

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In R, beta(θ|a, b) is dbeta(θ,a,b),and B(a, b) is beta(a,b)

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Our goal is to convert a prior belief expressed in terms of central tendency and sample size into [...]
equivalent values of a and b in the beta distribution

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Our goal is to convert a prior belief expressed in terms of central tendency and sample size into equivalent values of a and b in the beta distribution

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It turns out that the mean of the beta(θ|a, b) distribution is [...] and the mode is ω = (a − 1)/(a + b − 2) for a > 1and b > 1(μ is Greek letter mu and ω is Greek letter omega)
μ = a/(a + b)

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It turns out that the mean of the beta(θ|a, b) distribution is μ = a/(a + b) and the mode is ω = (a − 1)/(a + b − 2) for a > 1and b > 1(μ is Greek letter mu and ω is Greek letter omega)

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#### Flashcard 1484411243788

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It turns out that the mean of the beta(θ|a, b) distribution is μ = a/(a + b) and the mode is [...] for a > 1and b > 1(μ is Greek letter mu and ω is Greek letter omega)
ω = (a − 1)/(a + b − 2)

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It turns out that the mean of the beta(θ|a, b) distribution is μ = a/(a + b) and the mode is ω = (a − 1)/(a + b − 2) for a > 1and b > 1(μ is Greek letter mu and ω is Greek letter omega)

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#### Flashcard 1484416486668

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The spread of the beta distribution is related to the “concentration” [...]
κ = a +b (κ is Greek letter kappa)

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The spread of the beta distribution is related to the “concentration” κ = a +b (κ is Greek letter kappa)

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a beta(θ|12, 12) distribution has a standard deviation of [...]
0.1

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a beta(θ|12, 12) distribution has a standard deviation of 0.1

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a [...] distribution has a standard deviation of 0.1
beta(θ|12, 12)

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a beta(θ|12, 12) distribution has a standard deviation of 0.1

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The standard deviation of the beta distribution is √ μ(1 − μ)/(a + b +1). Notice that the standard deviation gets smaller [...]
when the concentration κ = a + b gets larger.

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The standard deviation of the beta distribution is √ μ(1 − μ)/(a + b +1). Notice that the standard deviation gets smaller when the concentration κ = a + b gets larger.

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Question
The standard deviation of the beta distribution is [...] . Notice that the standard deviation gets smaller when the concentration κ = a + b gets larger.
$$\sqrt{μ(1 − μ)/(a + b +1)}$$

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The standard deviation of the beta distribution is μ(1−μ)/(a+b+1)−−−−−−−−−−−−−−−−√μ(1−μ)/(a+b+1). Notice that the standard deviation gets smaller when the concentration κ = a + b gets larger.

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#### Flashcard 1484431428876

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If the prior distribution is beta(θ|a, b), and the data have z heads in N flips, then the posterior distribution is [...]
beta(θ|z + a, N − z + b)

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If the prior distribution is beta(θ|a, b), and the data have z heads in N flips, then the posterior distribution is beta(θ|z + a, N − z + b)

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#### Flashcard 1484433001740

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If the initial prior is a beta distribution, then the posterior distribution is always a [...]
beta distribution

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If the initial prior is a beta distribution, then the posterior distribution is always a beta distribution

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#### Flashcard 1484434574604

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#biochem #biology #cell
Question
In the simplest case, two identical folded polypeptide chains bind to each other in a “[...]” arrangement, forming a symmetric complex of two protein subunits (a dimer) held together by interactions between two identical binding sites.

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In the simplest case, two identical folded polypeptide chains bind to each other in a “head-to-head” arrangement, forming a symmetric complex of two protein subunits (a dimer) held together by interactions between two identical binding sites.

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#### Flashcard 1484436147468

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#biochem #biology #cell
Question
Why is a helix such a common structure in biology? [...]
As we have seen, biological structures are often formed by linking similar subunits into long, repetitive chains. If all the subunits are identical, the neighboring subunits in the chain can often fit together in only one way, adjusting their relative positions to minimize the free energy of the con- tact between them. As a result, each subunit is positioned in exactly the same way in relation to the next, so that subunit 3 fits onto subunit 2 in the same way that subunit 2 fits onto subunit 1, and so on. Because it is very rare for subunits to join up in a straight line, this arrangement generally results in a helix

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Why is a helix such a common structure in biology? As we have seen, biological structures are often formed by linking similar subunits into long, repetitive chains. If all the subunits are identical, the neighboring subunits in the chain can often fit together in only one way, adjusting their relative positions to minimize the free energy of the con- tact between them. As a result, each subunit is positioned in exactly the same way in relation to the next, so that subunit 3 fits onto subunit 2 in the same way that subunit 2 fits onto subunit 1, and so on. Because it is very rare for subunits to join up in a straight line, this arrangement generally results in a helix

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Handedness is [...] by turning the helix upside down, but it is reversed if the helix is reflected in the mirror
not affected

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Handedness is not affected by turning the helix upside down, but it is reversed if the helix is reflected in the mirror

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Question
Collagen is a [...] formed by three extended protein chains that wrap around one another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form unextendable collagen fibrils (top) that have the tensile strength of steel. The striping on the collagen fibril is caused by the regular repeating arrangement of the collagen molecules within the fibril
triple helix

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Collagen is a triple helix formed by three extended protein chains that wrap around one another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form unextendable

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#biochem #biology #cell
Question
Collagen is a triple helix formed by three extended protein chains that wrap around one another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form [...] (top) that have the tensile strength of steel. The striping on the collagen fibril is caused by the regular repeating arrangement of the collagen molecules within the fibril
unextendable collagen fibrils

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Collagen is a triple helix formed by three extended protein chains that wrap around one another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form unextendable collagen fibrils (top) that have the tensile strength of steel. The striping on the collagen fibril is caused by the regular repeating arrangement of the collagen molecules within the fibril</sp

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#### Flashcard 1484444011788

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Question
Collagen is a triple helix formed by three extended protein chains that wrap around one another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form unextendable collagen fibrils (top) that have the tensile strength of [...]. The striping on the collagen fibril is caused by the regular repeating arrangement of the collagen molecules within the fibril
steel

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ormed by three extended protein chains that wrap around one another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form unextendable collagen fibrils (top) that have the tensile strength of <span>steel. The striping on the collagen fibril is caused by the regular repeating arrangement of the collagen molecules within the fibril<span><body><html>

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#### Flashcard 1484445584652

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Question
Collagen is a triple helix formed by three extended protein chains that wrap around one another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form unextendable collagen fibrils (top) that have the tensile strength of steel. The striping on the collagen fibril is caused by the [...]
regular repeating arrangement of the collagen molecules within the fibril

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another (bottom). Many rodlike collagen molecules are cross-linked together in the extracellular space to form unextendable collagen fibrils (top) that have the tensile strength of steel. The striping on the collagen fibril is caused by the <span>regular repeating arrangement of the collagen molecules within the fibril<span><body><html>

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Question
Elastin polypeptide chains are cross-linked together in the extracellular space to form [...]. Each elastin molecule uncoils into a more extended conformation when the fiber is stretched and recoils spontaneously as soon as the stretching force is relaxed. The cross-linking in the extracellular space mentioned creates covalent linkages between lysine side chains, but the chemistry is different for collagen and elastin.
rubberlike, elastic fibers

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Elastin polypeptide chains are cross-linked together in the extracellular space to form rubberlike, elastic fibers. Each elastin molecule uncoils into a more extended conformation when the fiber is stretched and recoils spontaneously as soon as the stretching force is relaxed. The cross-linking in

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#### Flashcard 1484448730380

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Elastin polypeptide chains are cross-linked together in the extracellular space to form rubberlike, elastic fibers. Each elastin molecule uncoils into a more extended conformation when the fiber is stretched and recoils spontaneously as soon as the stretching force is relaxed. The cross-linking in the extracellular space mentioned creates [...], but the chemistry is different for collagen and elastin.
covalent linkages between lysine side chains

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elastic fibers. Each elastin molecule uncoils into a more extended conformation when the fiber is stretched and recoils spontaneously as soon as the stretching force is relaxed. The cross-linking in the extracellular space mentioned creates <span>covalent linkages between lysine side chains, but the chemistry is different for collagen and elastin.<span><body><html>

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#### Flashcard 1484450303244

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Many proteins were also known to have intrinsically disordered tails at one or the other end of a structured domain (see, for example, the histones in Figure 4–24). But the extent of such disordered structure only became clear when genomes were sequenced. This allowed bio- informatic methods to be used to analyze the amino acid sequences that genes encode, searching for disordered regions based on their unusually [...]
low hydropho- bicity and relatively high net charge.

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ent of such disordered structure only became clear when genomes were sequenced. This allowed bio- informatic methods to be used to analyze the amino acid sequences that genes encode, searching for disordered regions based on their unusually <span>low hydropho- bicity and relatively high net charge.<span><body><html>

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#### Flashcard 1484451876108

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Many proteins were also known to have [...] at one or the other end of a structured domain (see, for example, the histones in Figure 4–24). But the extent of such disordered structure only became clear when genomes were sequenced. This allowed bio- informatic methods to be used to analyze the amino acid sequences that genes encode, searching for disordered regions based on their unusually low hydropho- bicity and relatively high net charge.