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University of Texas - BIO - 326R
Chapter 32: HW MCQ: 1) Substances that are recognized as foreign and provoke immune responses are called A. antibodies B. antigens C. infective agents D. inducers 2) Which of the following is a physical barrier in the nonspecific defense of a mammalian ho
University of Texas - BIO - 326R
Chapter 33: HW answer key MCQ: 1) A 2) D 3) B 4) A 5) D 6) A 7) B 8) A 9) A 10) D 11) B 12) A 13) A 14) C 15) D True/ False: 1) F 2) T 3) F 4) F 5) T 6) F 7) F
University of Texas - BIO - 326R
Chapter 33: HW MCQ: 1) The immune system normally discriminates between _ antigens. A. self and nonself B. B and T cells C. humoral and cell-mediated D. primary and secondary response 2) T cells attack A. host cells that have been parasitized by microorga
University of Texas - BIO - 326R
Chapter 35: HW answer key MCQ: 1) D 2) D 3) A 4) B 5) A 6) A 7) D 8) C 9) C 10) C True/ False: 1) T 2) F 3) F 4) T 5) F
University of Texas - BIO - 326R
Chapter 35: HW MCQ: 1) The clinical microbiology laboratory can provide preliminary identification of microorganisms based on A. microscopic examination of specimens. B. growth or biochemical characteristics. C. immunologic techniques that detect microbia
University of Texas - BIO - 326R
Chapter 34 Antimicrobial Chemotherapy1Chemotherapeutic Agentschemical agents used to treat disease destroy pathogenic microbes or inhibit their growth within host most are antibioticsmicrobial products or their derivatives that kill susceptible microb
University of Texas - BIO - 326R
Chapter 37Human Diseases Caused by Viruses and Prions1Airborne Diseaseswhen human is source, airborne viruses are propelled from respiratory tract by coughing, sneezing, or vocalizing2Chickenpox (Varicella) and Shingles (Herpes Zoster) DNA virus, m
University of Texas - BIO - 326R
Chapter 38Human Diseases Caused by Bacteria1Airborne Diseasesmost involve the respiratory system some are skin diseases2Diphtheria caused by Corynebacterium diphtheriae airborne transmission by grampositive lysogenized strains produce an exotox
University of Texas - BIO - 326R
Chapter 39Human Diseases Caused by Fungi and Protists1Pathogenic Fungi and Protistsfungi are eukaryotic saprophytes ~50 produce mycoses in humans five groups depending on route of infection superficial, cutaneous, subcutaneous are all direct contac
University of Texas - BIO - 326R
Chapter 34 HW answer key MCQ: 1) D 2) C 3) C 4) A 5) D 6) D 7) B 8) D 9) B 10) D True / False: 1) T 2) F 3) T 4) F 5) F Match A and B: 1) D 2) B 3) F 4) C 5) H 6) E 7) I8) G 9) J 10) A
University of Texas - BIO - 326R
Chapter 34: HW MCQ: 1) Consider an antibacterial drug. In which of the following cases would the action of the drug be considered primarily bacteriostatic? A. The minimal lethal concentration (MLC) is equal to the minimal inhibitory concentration (MIC). B
University of Texas - BIO - 326R
Chapter 37: HW answer key MCQ: 1) D 2) D 3) B 4) B 5) D 6) D 7) D 8) A 9) D 10) A 11) A 12) C 13) A 14) A 15) D 16) C 17) C True/ False: 1) F; herpes simplex 2) T 3) F 4) T 5) F; paramyxovirus 6) T7) T 8) F; young children 9) T 10) TCase studies: 1) Shi
University of Texas - BIO - 326R
Chapter 37: HW MCQ: 1) In influenza virus, antigenic shift A. results from reassortment of genomes when two different strains of flu viruses infect the same cell. B. results from the accumulation of mutations in HA and NA in a single strain of flu virus.
University of Texas - BIO - 326R
Chapter 38: HW answer key MCQ: 1) D 2) A 3) D 4) C 5) D 6) A 7) B 8) D 9) D 10) A 11) C 12) C 13) B 14) D 15) B T/F: 1) F 2) T 3) F 4) T 5) F 6) F 7) T 8) F 9) T 10) T Case studies: 1) Meningitis by N.meningitidis, vaccination and antibiotics 2) Mantoux t
University of Texas - BIO - 326R
Chapter 38: HW MCQ: 1) The exotoxin produced by Corynebacterium diphtheriae A. causes an inflammatory response. B. causes the formation of a pseudomembrane on the respiratory mucosa. C. may destroy cardiac and kidney tissue. D. all of the choices 2) Dipht
University of Texas - BIO - 326R
Chapter 39: HW answer key MCQ: 1) B 2) C 3) C 4) B 5) B 6) C 7) D 8) B 9) B 10) D True / False: 1) True 2) False, cryptococcosis 3) T 4) T 5) False, T.cruzi 6) False, hands 7) T 8) T 9) False, immunocompromised 10) T Case Studies: 1) Malaria, Plasmodium;
University of Texas - BIO - 326R
Chapter 39: HW MCQ: 1. Most systemic mycoses are acquired from A. puncture wounds. B. inhaling spores. C. insect vectors. D. all of the choices 2. Dried pigeon droppings are a potential source of infection with A. Coccidioides immitis. B. Blastomyces derm
Dalton State - MATH - 023
Section 5.1BTHE NATURAL LOGARITHMIC FUNCTION: DIFFERENTIATION Objectives: 1) Develop and use properties of the natural logarithmic function 2) Understand the definition of the number e 3) Find derivatives of functions involving the natural logarithmic f
Amherst - PHIL - 110
Lecture 1INTRO LOGICDAY 011PHILOSOPHY 110INTRO LOGICWELCOME21Lecture 1INSTRUCTOR INFORMATIONInstructor Gary Hardegree Office 363 Bartlett Hall Office Hours Tu Th 11:00-1:00, 2:30-4:00 Phone 545-5788 EMail gmh@philos.umass.eduPersonal Web Page
Amherst - PHIL - 110
INTRO LOGICDAY 021Schedule for Unit 1Day 1 Intro Day 2 Chapter 1 Day 3 Chapter 2 Day 4 Chapter 3 Day 5 Chapter 4 Day 6 Chapter 4 Day 7 Chapter 4 Day 8 EXAM #12warm-up 40% of Exam 1 60% of Exam 11Chapter 1 Basic Concepts3What is logic?Logic is t
Amherst - PHIL - 110
INTRO LOGICDAY 031Schedule for Unit 1 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Intro Chapter 1 warm-up Chapter 2 Chapter 3 Chapter 4 Chapter 4 Chapter 4 EXAM #1240% of Exam 1 60% of Exam 11Chapter 2Sentential Logic3ReviewAn argument is
Amherst - PHIL - 110
INTRO LOGICDAY 041Schedule for Unit 1 Day 1 Intro Day 2 Chapter 1 Day 3 Chapter 2 Day 4 Chapter 3 Day 5 Chapter 4 Day 6 Chapter 4 Day 7 Chapter 4 Day 8 EXAM #12warm-up 40% of Exam 1 60% of Exam 11CHAPTER 3VALIDITY IN SENTENTIAL LOGIC3Validity i
Amherst - PHIL - 110
INTRO LOGICDAY 051Schedule for Unit 1 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Intro Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 4 Chapter 4 EXAM #1240% of Exam 60% of Exam8 arguments 5 pts each 12 translations 5 pts each1CHAPTER 4TRA
Amherst - PHIL - 110
INTRO LOGICDAY 06TRANSLATIONS IN SENTENTIAL LOGIC 21Schedule for Unit 1 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Intro Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 4 Chapter 4 EXAM #1240% of Exam 60% of Exam8 arguments 5 pts each 12 tran
Amherst - PHIL - 110
INTRO LOGICDAY 071EXAM #1 Thursday, in classOffice Hours: Wed 1:00 3:00 Thu 11:00 12:40 363 Bartlett 1. Validity and Invalidity 8 argument forms 5 points each 2. Translations in SL 12 translations5 points each21INTRO LOGIC EXAM 1 ID # :NAME: Exam
Amherst - PHIL - 110
INTRO LOGICDAY 091UNIT 2DERIVATIONS INSENTENTIAL LOGIC21Basic IdeaWe start with a few argument forms, which we presume are valid, and we use these to demonstrate that other argument forms are valid. We demonstrate that a given argument form is va
Amherst - PHIL - 110
INTRO LOGICDAY 101DERIVATIONS INSENTENTIAL LOGIC2nd day21ReviewWe demonstrate (show) that an argument is valid by deriving (deducing) its conclusion from its premises using a few fundamental modes of reasoning.3Initial Modes of ReasoningModus
Amherst - PHIL - 110
INTRO LOGICDAY 11Derivations in SL 31ReviewWe demonstrate (show) that an argument is valid by deriving (deducing) its conclusion from its premises using a few fundamental modes of reasoning.21Rule Sheetprovided on exams available on course web pa
Amherst - PHIL - 110
INTRO LOGICDAY 12Derivations in SL 41Schedule Day 09 Introductory Material Day 10 Direct Derivation (DD) Conditional Derivation (CD) Negation Derivation (D) Indirect Derivation Day 12 show: atomic show: disjunction Day 11 Day 13 show: conjunction Day
Amherst - PHIL - 110
INTRO LOGICDAY 13Derivations in SL 51EXAM #2 Tuesday, October 26 in classOffice Hours Mon 12:30 2:30 Tue 11:00 12:40 363 Bartlett21Exam 2 Format 6 argument forms, 15 points each, plus 10 free points Symbolic argument forms (no translations) For e
Amherst - PHIL - 110
INTRO LOGICDAY 151UNIT 3Predicate LogicTranslations21OverviewExam 1: Exam 2: Exam 3: Exam 4: Exam 5: Exam 6: Sentential Logic Sentential Logic Predicate Logic Predicate Logic (finals week*) (finals week*) Translations (+) Derivations Translations
Amherst - PHIL - 110
INTRO LOGICDAY 16Translations in PL 21Overview+ + + + Exam 1: Exam 2: Exam 3: Exam 4: Exam 5: Exam 6: Sentential Logic Sentential Logic Predicate Logic Predicate Logic (finals week) (finals week) Translations (+) Derivations Translations Derivations
Amherst - PHIL - 110
INTRO LOGICDAY 17Translations in PL 31Overview+ + + + Exam 1: Exam 2: Exam 3: Exam 4: Exam 5: Exam 6: Sentential Logic Sentential Logic Predicate Logic Predicate Logic (finals week) (finals week) Translations (+) Derivations Translations Derivations
Amherst - PHIL - 110
INTRO LOGICDAY 18Translations in PL 41EXAM #3 Tuesday, in class 25 translations from English into Predicate Logic 4 points each Only final formula is graded. Do intermediate work on scratch paper.21Chapter 7 Polyadic Predicate Logic3Examples of
Amherst - PHIL - 110
INTRO LOGICDAY 19Translations in PL 51EXAM #3 Tuesday, in classOffice Hours: Mon 12:30 2:30 Tue 11:00 12:45 363 Bartlett 25 translations from English into Predicate Logic 4 points each Only final formula is graded. Do intermediate work on scratch pap
Amherst - PHIL - 110
INTRO LOGICDAY 211UNIT 4 Derivations in Predicate Logic21OverviewExam 1: Exam 2: Exam 3: Exam 4: Exam 5: Exam 6: Sentential Logic Sentential Logic Predicate Logic Predicate Logic (finals week) (finals week) Translations (+) Derivations Translations
Amherst - PHIL - 110
INTRO LOGICDAY 22Derivations in PL 21OverviewExam 1 Exam 2 Exam 3 Exam 4 6 derivations Exam 5 Exam 6 Sentential Logic Translations (+) Sentential Logic Derivations Predicate Logic Translations Predicate Logic Derivations @ 15 points + 10 free points
Amherst - PHIL - 110
INTRO LOGICDAY 23Derivations in PL 31OverviewExam 1 Exam 2 Exam 3 Exam 4 6 derivations Exam 5 Exam 6 Sentential Logic Translations (+) Sentential Logic Derivations Predicate Logic Translations Predicate Logic Derivations @ 15 points + 10 free points
Amherst - PHIL - 110
INTRO LOGICDAY 24Derivations in PL 41EXAM #4 Tuesday, in classExam 4 to be returned Thursday in class Office Hours: Mon 12:30 2:30 Tue 11:00 12:45 363 Bartlett Exams 5, 6 Thu, Dec 15, 8:00-10:00, Mahar Exams are scheduled concurrently; you have two h
UMass (Amherst) - CHE - 446
Cascade Control1. 2. 3. 4. 5.Introduction Process examples Closed-loop analysis Controller design Simulink exampleIntroductionqFeedback control Corrective action taken regardless of disturbance source Corrective action not taken until after the outp
Phoenix - HRA - week
HCA 240 HIV/AIDS: An Overview Axia College of University of Phoenix.HIV and AIDS a virus that was first detected in the early 1980's, is a virus that has triggered a lot of fear and denial among people and it is considered a worldwide epidemic. HIV and
UMass (Amherst) - CHE - 446
Closed-Loop Response1. 2. 3. 4. 5. 6. 7.Introduction Liquid level control system Proportional control for setpoint change Proportional control for disturbance change PI control for disturbance change PI control for integrating process Simulink exampleI
UMass (Amherst) - CHE - 446
Closed-Loop Stability1. 2. 3. 4. 5. 6.Motivating example General stability criterion Routh stability criterion Direct substitution method Summary Simulink exampleMotivating ExampleqTransfer functionsGc = K c 1 1 1 G p = Gd = Gv = Gm = 5s + 1 2s + 1
UMass (Amherst) - CHE - 446
Closed-Loop Transfer Functions1. 2. 3. 4. 5.Introduction Stirred tank heating system Closed-loop block diagrams Closed-loop transfer functions Simulink exampleIntroductionqBlock diagrams Convenient tool to represent closed-loop systems Also used to
UMass (Amherst) - CHE - 446
Control Loop Interactions1. 2. 3. 4. 5.Introduction Multivariable systems Controller interactions Multivariable closed-loop stability Simulink exampleIntroductionqWe have focused on singleinput, single-output (SISO) control problems Most real control
UMass (Amherst) - CHE - 446
Empirical Modeling1. 2. 3. 4. 5. 6.Introduction Regression models First-order transfer function models Second-order transfer function models Integrating models Matlab System Identification ToolboxMotivationqFundamental models Derived from conservati
UMass (Amherst) - CHE - 446
Feedback Controllers1. 2. 3. 4.Introduction Basic control modes Typical closed-loop responses Simulink exampleIntroductionqFeedback controller Objective: maintain measured output (ym) at setpoint (ysp) by adjusting output signal (p) sent to process
UMass (Amherst) - CHE - 446
Feedforward Control1. 2. 3.Introduction Ratio control Controller design based on steadystate models Controller design based on dynamic models Feedback-feedforward control Simulink example4.5. 6.Feedback ControlqAdvantages Corrective action taken r
UMass (Amherst) - CHE - 446
Control System Instrumentation1. 2. 3. 4.Introduction Sensors, transmitters and transducers Control valves Measurement accuracyIntroductionqStirred tank heating system Measured liquid temperature with thermocouple Transmit signal to controller Perfo
UMass (Amherst) - CHE - 446
Introduction1. 2. 3. 4. 5. 6.Motivation Stirred tank blending system Classification of control strategies Distillation column Control system design Overview of the courseMotivation for Process ControlqThe technological environment More complex and i
UMass (Amherst) - CHE - 446
Transfer Functions1. 2. 3. 4.The Laplace transform Solution of linear differential equations Transient response example Simulink exampleThe Laplace TransformqDefinitionF ( s ) = L[ f (t )] = f (t )e - st dt0 Time (t) is replaced by a new independ
UMass (Amherst) - CHE - 446
Model-Based Controller Design1. 2. 3. 4. 5.Introduction Direct synthesis method Internal model control (IMC) IMC derived PID tuning rules Simulink exampleModel-Based ControlqPID controller tuning Restrict controller to PID form Seek "best" tuning pa
UMass (Amherst) - CHE - 446
Multiloop Control Systems1. 2. 3. 4. 5. 6.Introduction The relative gain array (RGA) Pairing input-output variables Dynamic considerations Multiloop controller tuning Reducing control loop interactionsIntroductionqMultiloop control approach Pair inp
UMass (Amherst) - CHE - 446
Observer Design and Output Feedback1. 2. 3. 4. 5. 6.Review of state feedback control State estimation Illustrative example Chemical reactor example Separation principle Simulink exampleState Feedback ControlqLinear state-space model x1 x x = 2 Rn xn
UMass (Amherst) - CHE - 446
PID Controller Tuning1. 2. 3. 4. 5.Introduction Model-based PID tuning methods Two degree of freedom controllers On-line PID controller tuning PID tuning guidelines and troubleshooting Simulink example6.IntroductionqPID control law 1 p (t ) = p + K
UMass (Amherst) - CHE - 446
Dynamic Process Models1. 2. 3. 4. 5.Conversion between model types Nonlinear model linearization State-space models Transfer function models Matlab/Simulink examplesConversion Between Model TypesNonlinearFirst Principles ModelLinearization Laplace t
UMass (Amherst) - CHE - 446
Process Unit Control System Design1. 2. 3. 4. 5.Introduction Influence of process design Control degrees of freedom Selection of control system variables Process safetyIntroductionqControl system requirements Safe operation Satisfy environmental reg
UMass (Amherst) - CHE - 446
Simulink Closed-Loop Simulation1. 2.Simulating feedback control systems Biochemical reactor exampleFeedback Control Systems in SimulinkSetpoint To Workspace2 0 Bias Input To Workspace1 Setpoint AddPID PID Controller Add 1bioreactor _basic ProcessO
UMass (Amherst) - CHE - 446
Matlab Controller Design1. 2. 3. 4.Control system toolbox Functions for model analysis Linear system simulation Biochemical reactor linearizationControl System ToolboxqqqqqqqProvides industry-standard algorithms and tools for systematically ana
UMass (Amherst) - CHE - 446
Matlab Controller Design1. 2. 3.Control system toolbox State feedback and observer design Biochemical reactor exampleControl System ToolboxqqqqqqqProvides industry-standard algorithms and tools for systematically analyzing, designing and tuning
UMass (Amherst) - CHE - 446
Simulink: A Crash CourseChE 446MATLABMATLAB is an interpreted language and interactive environment that enables you to input and perform computationally intensive tasks with less (human) effort than compiled programming languages such as C, C+, and For