OBJECTIVES LEARNING After studying chapter 15 and listening to class lecture,you should be able to: 1. Identify the six key elements that define an organization’s structure. 2. Explain the characteristics of a bureaucracy. 3. Describe a matrix organization. 4. Explain the characteristics of a virtual organization. 5. Summarize why managers want to create boundaryless organizations. 6. Contrast mechanistic and organic structural models. 7. List the factors that favor different organizational structures. 8. Why do structures differ?
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1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. Describe each of the five types of neuroglial cells. Describe the groupings of neurons by structural differences and by functional differences. Compare and contrast resting potential and action potential. How does a nerve impulse travel the length of a nerve? How is this process different in myelenated fibers vs unmyelinated fibers? Describe the process of synaptic transmission. Compare and contrast exitatory and inhibitory actions by neurons. What are neurotransmitters? Where are they synthesized and stored? How do they act? Compare and contrast facilitatation, convergence, and divergence. What is a reflex arc? List the steps involved. What are meninges? Describe the three types found in the skull. Compare and contrast white matter and gray matter. Describe each of the functional divisions of the brain. What is hemisphere dominance? What functions are performed by the dominant hemisphere? by the nondominant hemisphere? Compare and contrast the sympathetic and parasympathetic nervous systems. List the 5 general types of receptors and state what each detects. What is sensory adaptation and why is it important? What is referred pain and why does it occur? Compare and contrast acute and chronic pain. Compare and contrast the olfactory and taste senses. Describe the process of hearing a sound beginning with the sound entering the external auditory meatus. Compare and contrast static and dynamic equilibrium. Compare and contrast rods and cones. Compare and contrast steroid and non-steroid hormones. Give a detailed example of a negative feedback mechanism involving hormones. Describe the three basic types of blood cells. What is hemoglobin? How is it broken down? What are the 5 types of leukocytes and how are they characterized? Describe blood plasma and list its major constituents. Describe the stages of hemostasis. Why is AB blood the universal acceptor? Why is O blood the universal donor? What would happen if AB type blood were transfused into a patient with type O blood? (be specific) Compare and contrast the pulmonary circuit and systemic circuit. Explain the steps of the cardiac cycle. What is an electrocardiogram and what does each point in the graph represent? Compare and contrast arteries, capillaries, and veins. Describe the exchange of substances between capillaries and surrounding tissues. 195 Describe the factors that effect arterial blood pressure.
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Chapter Objectives Identify and describe four characteristics common to all organizations and distinguish between line and staff positions. Describe a business organization in terms of the open-system model and explain the term learning organization. Describe the time dimension of organizational effectiveness. Explain the concept of contingency organization design and distinguish between mechanistic and organic organizations. Identify and briefly describe the five basic departmentalization formats. Describe how a highly centralized organization differs from a highly decentralized one. Define the term delegation and list at least five common barriers to delegation. Explain how the traditional pyramid organization is being reshaped. Describe at least three characteristics of organizational cultures and explain the cultural significance of stories. © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. 2
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BACKGROUND AND SIGNIFICANCE Persistent pathogens pose a great threat to public health. We will develop and use bioinformatics tools to help understand the structural and mechanistic basis of pathogen persistence. In molecular biology, there is an urgent need for tools that can identify binding sites on proteins, which consist of residues at the interface of the interactions. These residues contribute to the affinity of the interactions and provide target for drug design. We propose to develop novel computational methods that can automatically predict binding sites on the protein structure and that can help gain insights on the mechanistic basis of the interactions. We will use these novel methods to help elucidate the function of proteins. We will focus on the binding sites that correspond to protein-protein interactions and protein-nucleic acid interactions. We will refer to this type of binding sites as macromolecule-binding sites, since both proteins and nucleic acids are macromolecules. Unlike ligand-binding sites that often occur in pockets on the protein surface, macromolecule-binding sites usually locate at large planar surfaces. Thus, although numerous pocket-based methods have been developed for ligand-binding site identification, the prediction of macromoleculebinding sites cannot take the same approach. The binding site prediction problem is also different from hot-spot prediction, in which only residues with high contribution to the binding affinity are of interest, or catalytic site residues prediction, in which only residues that directly perform the catalytic activity are predicted. Many methods have been developed for macromolecule-binding site prediction. At one level, they can be divided into two groups: those rely on structural templates and those use automatic methods to analyze various features on the binding sites to discover predicting patterns. The first group of methods derives consensus structural templates of binding sites from a set of protein structures that have the same function. Then, new protein structures are scanned to search for the occurrences of the templates1-9. In some studies, structural templates are used in combination with other features such as electrostatic potentials10 and sequence profiles11,12. This group cannot apply to orphan proteins with no homologs available. The main drawback is the difficulty in deriving structural templates. Some derive structural templates by multiple alignment of protein structures6,10. This approach is hard to automate to produce objective results. Altho common patterns can be generated automatically from protein structure alignment at fold and topology levels13,14, generating structural templates reflecting local structural similarities still requires manual adjustments i.e., setting the anchor point of the multiple alignment. To date, there is no automated objective method for deriving structural templates of binding sites using multiple alignment of protein structures. Others identified structural templates by detecting recurring subgraphs15-18. However, these methods can only be used to find small templates, typically less than 6 residues, due to demanding computation requirement in generating all possible subgraphs in all protein structures. These methods usually report too many patterns. Enormous efforts by experts are needed to identify biologically significant patterns. The second group of methods uses machine-learning to analyze various features on binding sites to discover predicting patterns19-35. A wide range of features, including amino acid identity, sequence profile, evolutionary conservation, solvent accessibility, structural curvature, pocket size, electrostatic potentials and predicted secondary structure, have been analyzed. In these studies, the features of a surface patch are represented as a vector of values and inputted to a machine-learning method. This group of methods has the advantages that: (1) they can automatically discover sophisticated attribute-function relationships; (2) they also consider many features other than geometry that are important for the interactions; and (3) they can capture weak relationships that do not necessarily exist in every protein. However, as of today, this group of methods still suffer low accuracy36. The low accuracy is mainly due to the use of vectors to represent surface patches. When the features of a surface patch are encoded using a vector, the information of how these features distribute on the structure is lost.
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REFLECTIVE JOURNALING TOOLS Reflective J ournalingTools LEARNING: • How is practice different from theory? Did this exercise help you to understand your theory and the application of theory better? How? Why? • Did you learn anything that helped you to better understand a theory, the use of a test that you were taught in lectures/labs? • What did you learn that were not taught in lectures (e.g. communication with patients), and how did you cope or learn more about this to improve your performance? Or how can this be incorporated into lectures? • Did this exercise help you to remember or recall later other aspects of previous experiences that you have forgotten? • Did this exercise help you identify areas that need to be changed, improved etc. in yourself/peers/staff/clinical training etc. Why and how? • What actions did you take you take and what are the results (what did you learn)? SELF ASSESSMENT: • Did you identify areas/issues that you were unclear of, or disagreed with your supervisors/peers, or different from what you have learned in your past lectures? Justify the actions taken. Did this help you in your learning? How? • Have you been open to share with others and to listen what others have to say? • Have you paid attention to both your strong and weak points? Can you identify them? What are you going to do about them? • How did faculty supervision/RW help you in your clinical experiences in relation to your professional growth? (eg. did it encourage you to be more independent, to become more confident in professional activities and behaviors etc) • What have you noted about yourself, your learning altitude, your relationship with peers/supervisors etc. that has changed from doing this exercise? COMMUNICATION: • What have you learned from interacting with others (peers/supervisors/staff etc)? • Did your peers gain anything from YOUR involvement in this exercise and vice versa? • Did this exercise encourage and facilitate communication? • Did you clarify with your supervisors/peers about problematic issues identified? Why (not)? What are the results? • How could you/your peers/staff help you overcome negative emotions arising from your work? Did your show empathy for your peers? PROFESSIONALISM: • Did you learn that different situations call for different strategies in management? • What are the good and bad practices that you have identified? How would you suggest to handle the bad/poor practices identified (if any)? • Did you learn to accept and use constructive criticism? • Did you accept responsibility for your own actions? • Did you try to maintain high standard of performance? • Did you display a generally positive altitude and demonstrate self-confidence? • Did you demonstrate knowledge of the legal boundaries and ethics of contact lens practice? EMOTION & PERSONAL GROWTH: • Did you reflect on your feelings when dealing with the case/peers/supervisor (eg. frustration, embarrassment, fear) for this exercise? If not, why not? If yes, who should be responsible — you, your patient or your supervisor? Why? • Did you find reflection (as required for this exercise) helpful, challenging, and enjoyable, change the way you learn? How? Why (not)? • How and what did you do to handle negative emotions arising from doing this subject? How could these feelings be minimized? • Did you try to find out if your feelings were different from your peers? Why? What did you do to help your peers? • Did you reflect on your learning altitude? How was it? Is there room for improvement? How? Why (not)? • What did you learn about your relationship with your peers/supervisors? What did you learn about working with others? Ideas for Reflective Journaling Writing Contributor(s): Dr. Michael Ying and Dr. Pauline Cho
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Operating Modes C Examples  C – programming msp430x14x.h /************************ * STATUS REGISTER BITS ************************/ #define #define #define #define #define #define #define #define #define C Z N V GIE CPUOFF OSCOFF SCG0 SCG1 0x0001 0x0002 0x0004 0x0100 0x0008 0x0010 0x0020 0x0040 0x0080 /* Low Power Modes coded with Bits 4-7 in SR */ /* Begin #defines for assembler */ #ifndef __IAR_SYSTEMS_ICC #define LPM0 CPUOFF #define LPM1 SCG0+CPUOFF #define LPM2 SCG1+CPUOFF #define LPM3 SCG1+SCG0+CPUOFF #define LPM4 SCG1+SCG0+OSCOFF+CPUOFF /* End #defines for assembler */ #else /* Begin #defines for C */ #define LPM0_bits CPUOFF #define LPM1_bits SCG0+CPUOFF #define LPM2_bits SCG1+CPUOFF #define LPM3_bits SCG1+SCG0+CPUOFF #define LPM4_bits SCG1+SCG0+OSCOFF+CPUOFF  … #include "In430.h“ #define LPM0 _BIS_SR(LPM0_bits) #define LPM0_EXIT _BIC_SR(LPM0_bits) #define LPM1 _BIS_SR(LPM1_bits) #define LPM1_EXIT _BIC_SR(LPM1_bits) #define LPM2 _BIS_SR(LPM2_bits) #define LPM2_EXIT _BIC_SR(LPM2_bits) #define LPM3 _BIS_SR(LPM3_bits) #define LPM3_EXIT _BIC_SR(LPM3_bits) #define LPM4 _BIS_SR(LPM4_bits) #define LPM4_EXIT _BIC_SR(LPM4_bits) #endif /* End #defines for C */ /* /* /* /* /* /* /* /* /* /* Enter LP Mode 0 */ Exit LP Mode 0 */ Enter LP Mode 1 */ Exit LP Mode 1 */ Enter LP Mode 2 */ Exit LP Mode 2 */ Enter LP Mode 3 */ Exit LP Mode 3 */ Enter LP Mode 4 */ Exit LP Mode 4 */ /* - in430.h Intrinsic functions for the MSP430 */ unsigned short _BIS_SR(unsigned short); unsigned short _BIC_SR(unsigned short); CPE 323 23
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From Idea to Solution for (int i = 0; i < list.length; i++) { select the smallest element in list[i..listSize-1]; swap the smallest with list[i], if necessary; // list[i] is in its correct position. // The next iteration apply on list[i..listSize-1] } list[0] list[1] list[2] list[3] ... list[10] list[0] list[1] list[2] list[3] ... list[10] list[0] list[1] list[2] list[3] ... list[10] list[0] list[1] list[2] list[3] ... list[10] list[0] list[1] list[2] list[3] ... list[10] ... list[0] list[1] list[2] list[3] ... list[10]
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To predict binding sites on a protein is to identify the residues at the interface of the interactions. In practice, many researchers look for binding sites by searching for occurrences of sequence or structural motifs or by transferring binding sites information from homologous proteins using sequence or structural alignment. Altho these have achieved success in many apps, they cannot apply to orphan proteins, which have no homologs available. Constructing structural motifs relies on structural multiple alignment, needing manual interference and is hard to automate. In the past, researchers have tried to develop automatic methods using machine-learning for binding site prediction. However, only limited success has been achieved. The first challenge is in the data representation of the protein structure. The protein structure is a 3-dimensional (3D) object, which no current machine-learning methods can directly deal with. Thus, the 3D structures must be reduced to 2D objects, e.g. graphs, or 1D objects, e.g. vectors. The challenge here is that the reduction operation must not discard structural information necessary for the interactions. In other words, the 2D (or 1D) rep. models much contain sufficient structural information to enable binding site prediction. The graph models are designed to maintain structural info for binding site prediction, incl. spatial arrangement of residue side chains, local structure environment of residues, and spatial distribution of multiple physical chemical properties. The model represents the spatial arrangement of a pair of residue side chains using three angles and a distance. Another obstacle in the data representation of proteins is the flexibility of protein structures. Proteins may undergo confirmation change in binding so structure flexibility must be considered in predicting binding sites. However, due to technical difficulties, no previous graph model has addressed the protein flexibility problem. The proposed work is also innovative in that the proposed graph models take into account protein flexibility. The side-chain arrangement, local structural environment, and contacting relationship between residues are defined depending on the protein flexibility. The second challenge for automatic binding site prediction lies in the machine-learning methods. he machine-learning methods must have the ability to fully exploit the information in the data models to discover complex relationships. In the proposed work, the data are graphs labeled with multiple continuous features. Current machine-learning methods are not sufficient to handle this type of data. The innovation of the proposed work also resides in the new graph kernels that we propose to develop. The new graph kernels use innovative ideas to solve the tottering problem and other weaknesses of current methods. The proposed work is innovative because we use an innovative approach to investigate the modular organization of binding sites and discover characteristic patterns associated with modules and different types of binding sites. Currently no effective methods are available for tackling these problems. The graph models and graph kernel methods develop in this work make it feasible to perform the analyses.
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Figure 4: Logic Model for the Quality Enhancement Plan Figure 6. Logic M odel for the Q uality Enhancement Plan Ra tionale Inputs Activities Outputs Outcome Why is this important? What are we doing now? What will we do? What products, events, & services will lead to program outcomes? What learning outcomes will be achieved? • Students must be C urriculum • Global learning content in general education (core) courses • Global learning content in selected academic majors representing each academic college • Collaboration with community resources with global focus to support course assignments • Study abroad program prepared to compete in a global market • Students must understand their role within an international community • Students need to be prepared to engage in increasingly diverse communities C o-Curricular • Global learning/engagement activities sponsored by student organizations • Freshman common read program • International learning community in residence hall Budget to support QEP activities • $1,153,233 budgeted over five year implementation period C urriculum • Incorporate global learning/engagement content/activities in general education (core) discipline courses • Conduct curriculum mapping for coursework in selected majors to enhance global learning/engagement C ampus Initiatives • Increase service learning opportunities within Study Abroad program • Coordinate student recognition and curriculum development activities with the Service Learning program C o-Curricular • Expand global learning/engagement activities sponsored by Student organizations • Increase international interactions C ommunity • Increase collaborative work with community organizations to support global learning/engagement activities • Increase collaborative work with international organizations to support global learning/engagement activities Curriculum E nhance ment • Number of general education (core) courses modified to include global learning/engagement activities • Number of courses in academic majors modified to include global learning/engagement activities • Number of students by college participating in global learning/engagement courses • Number and type of faculty participating in professional development activities and learning communities Co-Curricular • Number of student organizations sponsoring global learning/engagement activities • Number and demographics of students participating in global learning/engagement activities Community • Number of community organizations supporting global learning/engagement activities • Number of international organizations supporting global learning/engagement activities Knowledge • Students identify, describe, and explain global and intercultural conditions and interdependencies. • Students make informed critical assessments of global events, processes, trends and issues and convey the interconnectedness of political, economic and environmental systems. Skills • Students analyze, interpret, and evaluate global and intercultural issues via engagement strategies including the use of information technologies. • Students demonstrate an ability to communicate and interact effectively with members of other cultures. Attitude s • Students reflect upon and integrate global learning and engagement experiences. • Students recognize and appreciate cultural diversity and multiple world views.
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Important Legal Information for Adolescents and Parents According to Iowa law, a minor (an individual younger than 18 years) may seek medical care for the following without the permission or knowledge of his parents: • Substance abuse treatment; • Sexually Transmitted Infection(STI) testing and treatment; • HIV testing – if test is positive, Iowa law requires parent notification; • Contraceptive care and counseling, including emergency contraception; and Even though teenagers young • Blood donation if 17and years of age or adults can receive these treatments older. without their parent’s knowledge, it is important to remember parents are a key part of all aspects of your life. We encourage parents and teens to be open and honest with each other when it comes to health care decisions. It is important for teens to know that if they are covered by their parents’ medical insurance and want it to cover their treatment, they will need to consent to their medical records being shared – possibly even with parents. A minor may also consent for evaluation and treatment in a medical emergency or following a sexual assault. However, treatment information can not be kept confidential from parents. Bill of Rights for Teens and Young Adults • The things you tell us in confidence will be kept private. • We will speak and write respectfully about your teen and family. • We will honor your privacy. YOU HAVE THE RIGHT TO: Emotional Support • Care that respects your teen’s growth and development. • We will consider all of your teen’s interests and needs, not just those related to illness or disability. Respect and Personal Dignity • You are important. We want to get to know you. • We will tell you who we are, and we will call you by your name. We will take time to listen to you. • We will honor your privacy. Care that Supports You and Your Family • All teens are different. We want to learn what is important to you and your family. Information You Can Understand • We will explain things to you. We will speak in ways you can understand. You can ask about what is happening to you and why. Care that Respects Your Need to Grow and Learn • We will consider all your interests and needs, not just those related to your illness or disability. Make Choices and Decisions • Your ideas and feelings about how you want to be cared for are important. • You can tell us how we can help you feel more comfortable. • You can tell us how you want to take part in your care. • You can make choices whenever possible like when and where you YOU HAVE THE RIGHT TO: receive your treatments. Bill of Rights for Parents Respect and Personal Dignity • You and your teen will be treated with courtesy and respect. Make Decisions About Your Teen’s Care • We will work in partnership with you and your teen to make decisions about his care. • You can ask for a second opinion from another healthcare provider. Family Responsibilities YOU HAVE THE RESPONSIBILITY TO: Provide Information • You have important information about your teen’s health. We need to know about symptoms, treatments, medicines, and other illnesses. • You should tell us what you want for your child. It is important for you to tell us how you want to take part in your teen’s care. • You should tell us if you don’t understand something about your teen’s care. • If you are not satisfied with your teen’s care, please tell us. Provide Appropriate Care • You and the other members of the health care team work together to plan your teen’s care. • You are responsible for doing the things you agreed to do in this plan
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Tools are needed that can identify binding sites on proteins, which consist of residues at the interface of the interactions. The plan is to develop computational methods that can automatically predict binding sites on the protein structure and that can help to gain insights on the mechanistic basis of the interactions. The focus is on binding sites corresponding to protein-protein interactions and protein-nucleic acid interactions. We will refer to these binding sites as macromolecule-binding sites, since both proteins and nucleic acids are macromolecules. In practice, many researchers predict binding sites by searching for occurrences of conserved sequence or structural motifs or transferring binding site information from homologous proteins using sequence or structural alignment. Altho this has been success in many applications, they cannot apply to orphan proteins, which have no homologs available. Furthermore, the development of biologically significant structural motifs usually requires extensive interference from experts and is hard to automate. Consequently, there are only a few structural motifs available today. The guiding hypothesis for this project is that stable interactions between macromolecules require the binding sites to possess favorable binding conditions in multiple aspects, including geometric complementarities, evolutionary conservation, hydrophobic force, electrostatic force and other physical and chemical forces. A solution must assess multiple features covering different aspects of the protein surface in order to predict binding sites. The overal goal of this project is to develop data models and computational methods for binding site prediction and analysis. Specific Aim 1: Develop expressive graph models for proteins. Proteins fold into a three-dimensional (3D) structure in cells, which is pivotal for proteins to perform their function. Graph models will be developed for representing crucial structural information and the spatial distribution of multiple features on the protein structure. Residues will be represented as graph vertices. Sequence and structural motifs, evolutionary profiles, physical and chemical properties will be encoded w vertex labels The spatial arrangement of residue side chains will be represented using three angles and one distance value that uniquely define the spatial relationship between two side chains. These angles and distance value will be shown as edge labels on the graphs. The flexibility of the protein structure will also be encoded into the graphs. Specific Aim 2: Develop new graph kernel methods for binding site prediction. Graph comparison is computationally intensive. In the proposed graph models, vertices and edges are labeled with real numbers, which adds difficulty. We will use a new type of graph kernel to exploit the rich info encoded in the graph models for binding site prediction. The new graph kernels resolve the tottering problem and other weaknesses associated with current graph kernels. The graph kernels will be embedded in machine-learning methods to learn complex relationships for binding site predictions. Specific Aim 3: Knowledge discovery in binding sites. Evidence shows macromolecule-binding sites have a modular org. Kernel clustering will be used to discover modules in the binding sites and investigate how modules evolve in the evolution and how they interact with each other. Kernel principle component analysis to identify characteristic patterns associated with different modules and different
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First “Project”Assignment (Preview) assignment (due WEEK 3 in lab): Team assignment In lab your team will specify, design, implement, and test a (java) program consisting of at least one component built by each team member. Use this mini-project to explore the planning and management concepts which you will apply to the quarter project. Based on your experiences with this mini-project, fill in DETAILED answers to the questions below. This will be CHAPTER 1, RESOURCES AND PLANNING, for your quarter project report. RESOURCES: •List all personnel and skills of each (Java experience, software project experience, good writing skills, etc.) •List the number of hours each team member has available to devote to the project over the quarter. •List all hardware and software resources that will be used for development. PLANNING: •Describe the team organization. •List who will be assigned to oversee each of the following: documentation; testing; version control and backups; productivity; overall management (number of managers depends on team organization chosen). •Describe how the team members will communicate and coordinate their work. •Give the time and place of weekly team meetings (at least one meeting per week is required). •Describe completely the process model you will follow and explain why this model is appropriate for the project and for your available resources. •Describe completely how you will handle version control and backups. •Give the formulas you will use for calculating productivity (you must measure individual and team time spent and you must measure how much you have produced—weekly and overall)—see update on next slide •Describe your plan for testing. As we will discuss later, it is important that each component be tested by someone who is not the author. It is also important that you follow an incremental plan for integrating components into your system, testing the whole system each time a new component is integrated. As you develop components, you should also be building up a set of test cases which can be run each time a change is made to the system. •Provide a RISK TABLE for your project (see lecture notes) •Provide both a GANTT CHART and TRACKING DOCUMENT for your project (see lecture notes). You can build the Gantt chart using the project development schedule given on the web page for 495. •Describe the CODING STANDARDS you will use (see lecture notes). 3 •Describe how you will produce up-to-date documentation (content and form—online?) in parallel with the project.
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