on 21-Sep-2018 (Fri)

The part in the viewport changes color (to green on my system) indicating it has been assigned a section.

The Mesh item in the model tree no longer has the words (Empty) next to it.

Name it CantileverBeamJob. Notice that there are no spaces in the name.

Putting a space in the job name can cause problems because Abaqus uses the job name as part of the name of some of the output files such as the output database (.odb) file.

Abaqus/CAE (CAE stands for Complete Abaqus Environment), and a postprocessor that helps you visualize the results from the output database - AbaqusNiewer.

In short, the Abaqus/CAE GUI is the easy-to-use interface between you, the user, and the kernel, and the GUI and kernel communicate using Python commands.

.4~.1 : Run . tli e ~ript from the command line without the GUI ~----~~------- Type the command to run the script without the Abaqus/CAE GUI. The exact command varies depending on the version of Abaqus. In the commercial version of Abaqus you would type abaqus cae noGUI = "cantilever_beam.py" In the student edition (SE) version 6.9-2 you would type abq692se cae noGUI="cantilever_beam.py" In the student edition (SE) version 6.10-2 you would type abq6102se cae noGUI="cantilever_beam.py"

While the script is running, you will notice that the cursor is busy and you cannot type in any other commands at the prompt. This is because we have used the built in method waitForComp]etion() in the script which prevents the user from executing other DOS commands while the simulation is running. We will take a look at this statement again a little later, just be aware that if we did not include the waitForCompletion() command in the script, the prompt would continue to remain active even while the simulation is being run. And if you find yourself running batch files, or linking your simulations with optimization software such as !Sight or Mode1Center, this knowledge will come in handy.

2~5 Runn~g a scriJ> l!! om tb~ c-ommand Ji:Oe interface (c;LI) The kernel command line interface is the area below the viewport in Abaqus/CAE. Chances are the message area is currently displayed her e. If you click the box with '>>> ' on it you will be able to type in commands. We will use this to test a few diff erent Python commands in th e next chapter. For now l wish to mak e you aware that it is possible to run a script from here using the execfile() command. Type in Execfile('cantilev e r_beam . py ') Th e file you've passed as an argument to ex ec file() needs to be present in the current work directory for Abaqus, otherwise you need to spell out the full path such as: Execfile('C;\U ser s\Gau ta m\De skt op\ Boo k\ca ntilever _ beam.py') By default the work directory is C:\Temp although you can change it using File > Set Work Directory ..

Python is written in the form of code statements as are other languages.

Python do not need to put a semi-colon at the end of each statement

What the Python interpreter looks for are carriage returns (that's when you press the ENTER key on the keyboard). As long as you hit ENTER after each statement so that the next one is on a new line, the Python interpreter can tell where one statement ends and the other begins.

Python statements within a code block need to be indented, such as statements inside a FOR loop.

Within a statement you can decid~ how ~uch whitespace you wish to leave. So a=b+c can be written as a = b + c (notice the spaces between each character)

sufficient knowledge to identify hypotheses and relevant variables and to know when the ground beneath an organization is shifting

Your job as a data consumer—to generate hypotheses and determine whether results and recommendations make sense in a changing business environment—is therefore critically important.

As the famous statistician George Box noted, “All models are wrong, but some are useful.” In other words, models intentionally simplify our complex world

effective quantitative decisions “are not about the math; they’re about the relationships.” What he means is that quants and the consumers of their data get much better results if they form deep, trusting ties that allow them to exchange information and ideas freely.

direct reports to use analytics to make better decisions—for example, about which branches to open or close, how to reduce cus- tomer wait times, what incentives lead to multichannel interactions, and why some salespeople are more productive than others

Framing a problem—identifying it and understanding how others might have solved it in the past—is the most important stage of the analytical process

ROI story: How will the new decision-making model increase conversions, revenue, or profitability?

No matter how much you trust your quants, don’t stop asking them tough questions.

He also believes it’s vital to admit when you don’t understand something: “I know I am not the smartest person in the room in my meetings with these people. I’m always pushing for greater clarity [because] if I can’t articulate it, I can’t defend it to others.”

explicit goal should be to find the truth

encourages his subordinates to put forth data and analysis, rather than opinions, and reveals his own faulty hypotheses, conclusions, and decisions.

combine the science of analytics with the art of intuition

Be a manager who knows the geeks, understands their formulas, helps improve their analytic processes, effectively interprets and com- municates the findings to others, and makes better decisions as a result.

If anyone at a management meeting suggests a new direction, he or she is pressed for

using analytics is not without its challenges. These can be grouped into three primary areas: credibility, variety and complexity

However Python is n~t strongly typed. This means you don't state what type of data the variable holds, you simply give it a name.

So if you were to create an integer variable x in Python and assign it a value of 5 you would simply write: X=5

Python is also able to recognize String variables, and concatenates them if you add them. So a statement like greeting = 'h' + 'ello' stores the value 'hello' in the variable 'greeting'.

1 .n a, list y.ou..stor.e . multiple .elements or ~a~'.:\ vatues ~nd can refer to them with the name of · . .. ~ the list vru:ia,bfe- ~ f ollowed by an index. in square 'brackets []. T_be lowest index is 0. Note that you ·can store all kinds of data:types, such as · integer s~ float~, Strings, all in the same list. This is different from languages such as C, C++ and Java where all array members , must be of the same data type. Lists have many built-in functions, some of which are: • I en() - returns the number of elements in the list • append(x)- adds x to the end of the list making it the last element

• remove(y) - removes the first occurrence of y in the list • pop(i) - removes the element at index [i] in the list, also returns it as the return value

Dictionaries-are-sets of.key ; ~alue .pairs.

To remove a: key:vatue pair, you '.!Se the del :. ~ommciD.##BAD TAG##·a1Hfie key:value pairs, you use the clear command.

focus is to “model” real-world systems, such as refineries, financial portfolios or workers’ schedules. The four key ways that models may be represented are as an operational exercise, a game, a simulation or an optimization model.

1. Goals set out the purpose and vision for analytics within the firm. This may include sustained competitive advantage, incremental revenue opportunities or cost reduction.

2. Use cases identify the potential short- and long-term uses of analytics to drive the goals. They will be used to: a. Understand the overall business case and show the different types of value that can be derived from analytics b. Define holistic requirements within the firm for the types of analytics that will be required and the associated information management to support them c. Understand the user groups and business processes that may be impacted and whether the usage will be a one-time process or an ongoing operational process

3. Quantitative methods define the different types of analytics that will be required over time to support the different use cases

4. Architecture encompasses the technology components and platforms that will be used to support analytics. It covers information gathering, storage and processing, analytics modeling, visualization, user experience and history maintenance.

5. Data readiness defines the strategy that will enable firms to ensure that all relevant data is available with the appropriate quality and timeliness. This may include activities such as data quality assessment and remediation, data lifecycle governance, etc

6. Organizational capability establishes the organizational architecture required to leverage analytics. This includes decisions around structure (e.g., should analytics reside within one group, be embedded in business groups or maintain a community of practice?), the processes to sustain the analytics lifecycle and the necessary group capability.

7. Governance defines the structure and processes required to sustain the analytics capability and strategy. It will determine owners, standards, value measurement, project approval and prioritization, etc. Governance will also define the research agenda in terms of market analysis, competitive assessment and vendor assessment.

Operational exercises represent a model by executing experiments with the real-world system and leveraging the results to make decisions about how to operate in the future.

Gaming represents a model by creating a simplified response to various scenarios or strategies.

the 'models' object works similar to a dictionary object

Also in Abaqus these enhanced dictionaries are referred to as 'repositories'. You will hear me use this word a lot when we start dissecting scripts.

Simulation is similar to gaming, but in it the decision makers are augmented with quantitative models.

Optimization represents a model completely in mathematical terms, usually by setting an objective that needs to be maximized or minimized under different constraints

Tuples are similar to lists, except once a tuple is created it cannot be edited.

A tuple called random_items is created which contains integers, floats and Strings. Note that you use arcs for parentheses

You often create an "instance" of a. class and then ~ aooe&S · the built-in .metheds which belong to the class or assign properties using'it.

For the uninitiated, a class is a sort of container.

You define properties (variables) and methods (functions) for this class, and the class itself becomes a sort of data type, just Jike integer and String are data types. When you create a variable whose data type is the class you've defined, you end up creating what is called an object or an ins~ce of the class. The best way to understan~ this.iS:thr.ough.an-examp!e -.

What's with the word ' self'? In Python, every method in a class receives ' self as the first argument, that's a rule.

In object oriented languages like C++ and Java you do not pass self as an argument, this is a feature unique to tlre Pythons syntax and might even be a little annoying at first.

When we create 'Gary' as an instance of the 'Person' class, self.weight translates to Gary.weight and self.hair_co/or translates to Gary.hair _color.

In fact it is possible for the coder of the original class to make some of the variables private, meaning that they can only be changed by calling a method. This is known as "abstraction'\ or basically hiding the internal workings of the class.

Overview of Tuberculosis Chemotherapy
• The goals of therapy include cure and prevention of transmission of Mycobacterium tuberculosis.
• Effective treatment of tuberculosis requires a substantial amount of time (usually months and in some cases years).
• Mycobacteria grow slowly and can also be dormant. The lipid-rich mycobacterial cell wall is impermeable to may agent and organisms residing within macrophages are inaccessible to many drugs.
• Combination therapy is used to effectively kill mycobacteria and prevent emergence of drug resistance.

Learning Objectives
• Identify and differentiate microbes commonly causing respiratory infections by structural, growth, and biochemical characteristics.
• Describe common symptoms, pathophysiology, etiology, epidemiology, and diagnosis of pertussis
• Describe and differentiate common symptoms, pathophysiology, etiology, epidemiology, and diagnosis of infectious pneumonias

Bordetella pertussis: Causative agent of whooping cough
• Fastidious – requires nicotinamide, grows on Bordet-Gengou agar. PCR test available

Pathophysiology
• Tracheitis and bronchitis with accumulation of mucus, inflammatory cells, bacteria, and dead epithelial cells
• Valsalva Maneuver. When a person forcefully expires (coughs) against a closed glottis, changes occur in intrathoracic pressure that dramatically affect venous return, cardiac output, arterial pressure, and heart rate - sometimes causing hemorrhages in conjunctiva and brain
• Leukocytosis – predominance of lymphocytes
• Infection rarely extends to lung (to cause pneumonia) or to ear (to cause otitis media), never cause bacteremia

The Whoop
• Series of short expiratory coughing bursts working to expel mucus
• Inspiratory gasp with whoop as air passes turbulently through mucus
• Sometimes vomiting and cyanosis after coughing spells. Cough may produce thick mucus plugs.
• Paroxysms may occur up to 30 times a day, more at night. Child may appear normal and sleep between them.

Epidemiology of Bordatella Pertussis
• Vaccine preventable, but over 8,000 cases reported in 2002 in USA. In 2014, 32,971 cases.
• Highly contagious – attack rates 50-100% in non-immune persons after exposure due to respiratory aerosol droplets during cough
• In pre-vaccine era most children 1-5 yr old infected, protection by maternal antibody in 1 st yr of life
• Vaccine effective for about 12 yr, thus, adults not protected and no maternal antibody passage to protect infants
• Infants before vaccine doses given are susceptible
• Thus, 20-30% of adults with prolonged cough have this
• Indicates need for adult booster vaccine
• Seizures in 3%, death in 1%

Pertussis vaccine and treatment
• Acellular (no whole bacteria) pertussis (aP) always combined with Diphtheria and Tetanus, e.g. DTaP
• Contains: pertussis toxoid filamentous hemagglutinin some with fimbriae or pertactin
• DTaP at 2, 4, 6, 15-18 mo, booster 4-6 y
• At 11-12 y, Tdap
• To protect infants before they finish series, give pregnant women vaccine (Tdap) after 20 th week
• Treatment: erythromycin

Pneumonia
• Infection of the lung parenchyma resulting in
• Consolidation of the affected part and a filling of the alveolar air spaces with exudate, inflammatory cells, and fibrin
• Inflammation of alveoli or lung interstitium resulting in radiographic infiltrate
• Infection by bacteria or viruses is the most common
• Infection by other micro-organisms may occur
• Acute – recent/sudden onset
• Chronic – developing over weeks or months

Pulmonary defense mechanisms . Abrupt changes in direction of airflow in the nasal passages can trap potential pathogens. The epiglottis and cough reflex prevent introduction of particulate matter in the lower airway. The ciliated respiratory epithelium propels the overlying mucous layer (right) upward toward the mouth. In the alveoli, cell-mediated immunity, humoral factors, and the inflammatory response defend against lower respiratory tract infections. (C, complement.) Adopted from Schaechter.

Defenses in Alveolar Lining Fluid
• Alveolar macrophages – ingest particles
• Fibronectin – adhesin involved in cell-cell adhesion, by attaching to both bacteria and PMNs promotes phagocytic function
• Pulmonary surfactant – family of collagenous carbohydrate- binding proteins, bind to bacteria, fungi, viruses – act as opsonins

Pathophysiology of pneumonias
• Bacteria from the upper airways via aspiration or, less commonly, from other sites via hematogenous spread, find their way to the lung parenchyma
• Once there, combination of host and bacterial factors may lead to pneumonia
• Depending on pathogen, the resultant immune response will be predominantly Th17 (most extracellular pathogens) or Th1 (most intracellular pathogens)
• Th17: acute inflammation resulting in the migration of neutrophils out of capillaries and into the air spaces; exudate, dead cells/debris result in alveolar filling and pus
• Th1: acute inflammation bringing NK, CD8, macrophages to alveolar septae, resulting in thickening (no migration into alveoli necessary, no significant exudate)

Pneumonias can be roughly differentiated by symptoms
• “Typical pneumonia” - patient usually very ill
• Fever, cough productive of purulent (pus – yellow or green) and/or rusty sputum (red blood cells), dyspnea, pleuritic pain, lobar pattern of consolidation by x-ray
• S. pneumoniae, H. influenzae, M. catarrhalis

• “Atypical pneumonia” - illness may be mild
• "Walking pneumonia"
• Fever, dry (non-productive) cough, interstitial pattern of fibronodular or patchy infiltrates by x-ray (may be a surprise to physician!)
• Sputum (if present) scanty, thin or white
• Less likely to have pleuritic pain or pleural effusion
• M. pneumoniae, C. pneumoniae, Legionella sp., viruses

Pneumonias are also commonly classified by likely source
• Community-acquired pneumonias (CAP)
• Healthcare-acquired pneumonias
• Hospitals, nursing homes, etc.
• Ventilator-associated pneumonia (VAP)
• Prevalent pathogens differ between these groups
• No parallel to typical/atypical symptomatic presentations
• e.g. CAP may be caused by Streptococcus pneumoniae (typical presentation), influenza (atypical presentation), Legionella (usually atypical but may be typical)

Ventilator-Associated Pneumonia(VAP)
• The leading cause of death in nosocomial infection in USA (Mirseidi et al. Clin Infect Dis 2009;49:72)
• Sample of 178 patients with 28 deaths (16%) during 14- day study period
• Mean age 58 years, 65% male
• Leading bacterial causes:
• Pseudomonas aeruginosa • Acinetobacter baumannii • Klebsiella pneumoniae, Enterobacter aerogenes, and other Gram-negatives • Staphylococcus aureus
• Often antibiotic resistant
• New appreciation for viral involvement!

Community acquired pneumonia (CAP)
• Over 3 million cases per year in the USA
• 1.1 million hospitalized, over 50 000 deaths
• Median age: 55-68 years old
• Risk factors include: COPD (smoking-related), disorders that impair airway clearance, heart failure, dementia, seizures, stroke, alcoholism, kidney failure, diabetes, immunodeficiency
• Viral URI – peaks in winter
• 7 th most common cause of death
• Predictors of mortality: Age > 65, chronic lung disease, low blood pressure, RR > 30/min

CAP: Common causes Smokers Hacking Cough Vibrations
• Streptococcus pneumoniae
• Haemophilus influenzae
• Moraxella catarrhalis
• Mycoplasma pneumoniae
• Legionella pneumophila
• Chlamydophila pneumoniae
• Viruses:
• Influenza A and B
•Adenoviruses
• RSV, parainfluenzaviruses

CAP diagnosis
• Sputum for Gram stain and culture
• Blood culture
• Urinary antigen for S. pneumoniae and Legionella sp.
• Serology for Mycoplasma, Chlamydophila
• PCR • MALDI-TOF (matrix assisted laser desorption ionization time of flight mass spectrometry)

Oxidoreductases catalyze oxidation–reduction reactions

They transfer electrons between biological molecules

They often have a cofactor that acts as an electron carrier, such as NAD⁺ or NADP⁺ .

In reactions catalyzed by oxidoreductases, the electron donor is known as the reductant, and the electron acceptor is known as the oxidant.

Enzymes with dehydrogenase or reductase in their names are usually oxidoreductases.

Enzymes in which oxygen is the final elec- tron acceptor often include oxidase in their names.

rom abaqus import * imports the abaqus module and creates references to aB puhlic~oots . ..defined by that module.