1. What is the role of wireless technologies in smart-metering sys-
tems?

2. Describe the potential disadvantages of smart-metering systems.

3. Discuss the advantages of smart meters to utility companies.

4. Discuss the advantages of smart meters to the customers of utility
companies.

ONLINE APPENDIX

Three concerns with this study are that estimated relationships between diagnosis and future school behaviors may be artifacts of (1) the cut-point used to differentiate children with less severe versus more severe pre-diagnosis behaviors, (2) modeling strategy, or (3) stable unobserved differences between the teachers/classrooms of diagnosed and undiagnosed children. One reason results may be idiosyncratic to use of a 25th percentile cut-point is if, for example, diagnosed children are clustered around the 25th percentile cut-point. Resulting estimates may be upwardly biased for children with less severe pre-diagnosis behaviors and downwardly biased for children with more severe pre-diagnosis behaviors. However, estimates using cut-points ranging from the 10th to the 60th percentiles of the aggregate measure of pre-diagnosis ADHD-related behaviors are roughly stable, especially between the 15th and 50th percentile severity cut-points for children with less severe pre-diagnosis behavior problems (see Appendix Figure A.1; note that externalizing problems are reverse-coded so scales are comparable across outcomes). This indicates that results are not driven by choice of idiosyncratic cut-point. To assess whether PSM estimates are driven by modeling strategy, OLS estimates from the 25th percentile cut-point can be compared to the PSM estimates in the main text. Although estimates from the controlled OLS models tend to be larger in absolute values due to lesser sample balance, the general pattern of differences by severity group remains similar.

To examine whether results are driven by stable unobserved differences between the teachers/classrooms of diagnosed versus undiagnosed children (e.g., differences in class sizes or instructional practices that lead to differing constraints/supports or tolerance of behavioral issues), estimates are generated for diagnosed and undiagnosed children with the same teachers in 5th grade (Appendix Tables A.3 and A.4). Estimated effects of diagnosis are roughly twice as large, likely reflecting poorer sample balance given that only 15 percent of sample students have at least one diagnosed sample student in class. (However, these fixed-effects estimates are smaller, on average, than comparable estimates from the clustered subsample without fixed effects, as would be expected.) Nonetheless, patterns of difference between children with less severe versus more severe pre-diagnosis ADHD-related behaviors are consistent: diagnosed and medicated children with less severe pre-diagnosis ADHD-related behaviors fare worse than children with more severe behaviors.

A final question pertains to the visibility of the diagnosis by teachers. Analysis to this point has assumed—but not tested—that the differing effects of an ADHD diagnosis by pre-diagnosis behavioral severity may result, in part, from teachers contributing to children’s psychological processing of their diagnosis (i.e., not only from the diagnosed child’s internalization of negative stereotypes or stigma). To explicitly examine this possibility, supplemental matching analyses examine special education/educational accommodations receipt as another moderator of the relationship between diagnosis and future school behaviors. It is reasonable to assume teachers are aware of a diagnosis if the child is receiving special education. Because the same matching techniques continue to be used to pair children who are diagnosed and receiving special education with undiagnosed matches with the same pre-diagnosis behaviors, cognitive skills, and other characteristics, matching minimizes the effects of differential selection into special education from driving the estimated effects of “diagnosis with special education/accommodations” on observed outcomes relative to undiagnosed matches. Estimated differences are instead attributed to teachers’ explicit knowledge of the diagnosis/service-use apart from the underlying behaviors or other observed characteristics, with all caveats about risk of omitted variables bias.

Because so few children in this sample are diagnosed and receive special education services or educational accommodations (“special education” for short) without medication, I separately estimated the effects of diagnosis within each severity group for three subgroups, each relative to their undiagnosed matches: (1) diagnosed and unmedicated, no special education; (2) diagnosed and medicated, no special education; and (3) diagnosed and medicated, receiving special education. This analysis reveals that the net negative marginal effects of diagnosis appear for all three groups. However, the magnitudes are descriptively (but not statistically significantly) larger for diagnosed children receiving special education. This suggests that teachers’ increased likelihood of knowledge of a child’s diagnosis/service-use (the “external” label) does increase the negative effects of diagnosis, but only descriptively.

Design six-pulse rectifiers with LC filters to meet three different specifications. The input is threephase AC with a line-to-line RMS voltage of 208 V and a frequency of 60 Hz. The variable load
can be modeled as a resistance that can vary between 100 Ω and 500 Ω.
Design 1: Inexpensive Design
• Total component cost < $47
• Efficiency > 98% for all load conditions
• Load voltage ripple < 1% (peak-to-peak/average) for all load conditions
• AC source power factor > 0.89 for all load conditions
Design 2: High Performance Design
• Total component cost < $75
• Efficiency > 98.5% for all load conditions
• Load voltage ripple < 0.25% (peak-to-peak/average) for all load conditions
• AC source power factor > 0.93 for all load conditions
Design 3: Aircraft Design
For this design, assume that the AC source has a frequency of 400 Hz.
• Total component cost < $50
• Efficiency > 98.8% for all load conditions
• Load voltage ripple < 0.1% (peak-to-peak/average) for all load conditions
• AC source power factor > 0.945 for all load conditions
Selecting Components
Use Digikey or Mouser to find components and get their prices. You may use the prices for bulk
purchases. Include the site you found the component and its part number in your submission.
Make sure that you select components with adequate current and voltage ratings for all operating
points. Use the datasheets to check the specifications and ratings. You just need to select
components; you do not need to purchase components or build a prototype. You may use some of
the same components for multiple designs. For example, you might use the same capacitor for
Designs 1 and 3 or the same inductor for Designs 2 and 3.
Diodes
Use Digikey part number RFN5BM3SFHTLTR-ND. Assume Vf = 0.74 V and rd = 80 mΩ. This
diode has a peak voltage rating of 350 V, an average current rating of 5A, and a peak current rating
of 50 A. These values must not be exceeded. The diodes can be purchased for $0.80 each. (When
calculating the total component cost, remember that multiple diodes are required.)
Inductors
Use a fixed inductor, NOT a common mode choke. Make sure that the inductor is rated for
adequate current. Since the frequencies that we are dealing with are relatively low, you can use
the inductor’s DC current rating as the limit for your RMS inductor current. You may combine
multiple inductors in parallel or series, if needed. If you cannot find the DCR or current rating for
an inductor in its datasheet, do not use that inductor.
Capacitors
Make sure that the capacitor is rated for adequate voltage and RMS ripple current. You may
combine multiple capacitors in parallel or series, if needed. Since the frequencies that we are
dealing with are relatively low, if the capacitor has the ESR or ripple current specified for two
different frequencies, use the lower frequency (either 100 Hz or 120 Hz). If you cannot find the
ESR, current rating, or voltage rating for a capacitor in its datasheet, do not use that capacitor.
Submission Requirements
Submit both your code and a summary of the designs. Your code should take the following inputs:
• Diode forward voltage
• Diode resistance
• Diode average current rating
• Diode peak current rating
• Diode reverse voltage rating
• Inductor inductance
• Inductor DCR
• Inductor RMS current rating
• Capacitor capacitance
• Capacitor ESR
• Capacitor voltage rating
• Capacitor RMS current rating
If you use Matlab, use the code posted on eLearning as the first lines of your code so that I can
easily copy in my test cases to see whether your code works. You can change the values of the
different variables to reflect your design, but do not change the names of the variables.
Your code should do the following:
• Calculate the range of efficiencies across the range of loads
• Calculate the range of power factors across the range of loads
• Calculate the range of load voltage ripples (as the peak-to-peak ripple divided by the
average load voltage) across the range of loads
• Verify that no current or voltage ratings are exceeded across the range of loads
• Verify any assumptions about continuous or discontinuous current
Your summary of the designs should include the following for each design:
• Part numbers for each component and where you found each component (Digikey or
Mouser)
• Ratings and specification for each component
• Cost for each component
• Total component cost
• Graph* of efficiency versus load resistance
• Graph* of power factor versus load resistance
• Graph* of load voltage ripple (peak-to-peak as a percentage of average load voltage)
*For the graphs, use enough points that the curves look smooth. I should not be able to count the
number of points that you used. Also, make sure that axes are labeled and units are shown.

follow up on the posts of your classmates and faculty and responses to your own posts. The grading rubric calls for you to post a total of 3 times per week (1 initial post +  2 discussion participation posts).

– Add new information or viewpoints

– Provide context by example, inference, explanation, or comparison

– Critically evaluate discussion content

– Challenge, question, or refute discussion content or accepted knowledge

The development of early computerized billing systems was modeled after the electronic data interchange systems started by the steamship and railroad industries as described in the article by Reza et al (2020). From 1960 to 1980, these systems were rudimentary to say the least. They were not connected even in the same hospital as outlined in Wager (2022). I will illustrate an example of how fragmented the process was early in my career. The different hospital departments acted like separate units with different programs and even hardware. All of this was independent from the paper charting done at bedside by nurses and doctors. In the mid-nineties, as a resident I would handwrite orders. The chart would then be handed to the unit secretary. That person would have to tell the charge nurse to read it. If it were a nursing commination order such as “give a stool softener,”  the charge would then tell the bedside nurse. If it were a blood draw order, the unit secretary would input it on an old-fashioned IBM computer. The lab would then print the order and manually input it into another system. Then they would send someone to draw the blood from the patient’s arm. The next day at the printer, I would collect those paper results. This process was error prone, time consuming, inefficient, and costly. What I saw and experienced on the ground was reaffirmed by the second Institute of Medicine report To err is Human: Building a safer health care system (Kohn, Corrigan, & Donaldson, 2000) as cited in Wagner (2020).

Now I can dictate on my EPIC driven electronic health platform, order a test and send a copy of my note to the patient portal and to the family clinician. Then I can bill for the encounter, all from my iPhone. There were various laws and acts by the government to drive us to this point. Three to four fundamental pieces of US (United States) government legislation really impacted me as a clinician. First in 1996 was the passage of the Health Insurance Portability and Accountability Act (HIPPA) setting the standards for privacy and codifying them. Next was the passage of Health Information Technology for Economic and Clinical Health Act in 2009 that gave monies in incentives to Medicaid providers and hospitals as per Reza et al. (2020). The Affordable Care Act and 21st Century Cures Act are the other two subsequent pieces of legislation that took us to the next level, Wagner (2020). I believe that the last two really propelled us to wider adoption of equipment, platforms, programs that now are the norm.

In this journey I have had to develop various levels of health literacy and data literacy. I can only imagine what other consumers such as patients have had to do to assimilate the massive amounts of information now available. There are many other players that have a role in this process certainly not everyone has the same background or experience. I will focus on the physician – patient role. As the TEDx Morrow (2019) video discusses, I certainly had to develop a skill set of how to read, work, analyze, and argue/decipher information just to get through my EPIC electronic workflow every day. It is certainly different from when I started back as a medical student. That process took time, but it was more in physical terms. Now I must sift through layers of windows to get the right information. It is still not easy but certainly light years advanced than before. For patients, the central hub of dissemination of information was the physician. They had to trust the doctor, period. He or she was the central gospel of information. To many individuals this is still true. Now with Goggle and MedlinePlus any person has near complete access to up-to-date health information. This may “level the playing field ” to a point. It may also lead them to life saving treatment that their physician may not even know about. The outcome of their health depends on the level of health literacy. They must develop a robust skill set to dig through the information explosion. The better people can understand and manage their health information the healthier they can become, Netemeyer et al. (2020).

References 

Dixon B., Rahurkar S., Apathy N.C. (2020). Interoperability and health information exchange for public health. In Magnuson J.A., Dixon B. (Ed), Public health informatics and information systems. (3rd ed., pp. 307-321). Switzerland: Springer Nature.

Hersh W. (2020). Public health informatics in the larger context of biomedical and health informatics. In Magnuson J.A., Dixon B. (Ed), Public health informatics and information systems. (3rd ed., pp. 31- 41). Switzerland: Springer Nature.

Netemeyer, Dobolyi, D. G., Abbasi, A., Clifford, G., & Taylor, H. (2020). Health literacy, health numeracy, and trust in doctor: Effects on key patient health outcomes. The Journal of Consumer Affairs, 54(1), 3–42.  https://doi.org/10.1111/joca.12267

Reza F., Prieto J.T, Julien S.P. (2020). Electronic health records: Origination, adoption, and progression. In Magnuson J.A., Dixon B. (Ed), Public health informatics and information systems. (3rd ed., pp. 183-200). Switzerland: Springer Nature.

TEDx Talks Morrow J. (2019, June 3rd) Why everyone should be data literate [Video File]. YouTube https://youtu.be/8ovyQZ_Z8Xs

Wager, K. A., Glaser, J., & Lee, F. W. (2022). Evolution of health care information systems in the United States. In Wager, K. A., Glaser, J., & Lee, F. W. (Ed.), Health care information systems a practical approach for health care management (5th ed., pp 3-38.). San Francisco: Jossey-Bass

Types, Purpose and Use of HIS

Health information systems provide various uses depending on the stakeholders involved: this can range from the healthcare professional, patients and the administration staff who work tirelessly behind the scenes. In a generalized sense the purpose of health information systems is to reduce costs, manage populations, and improve quality care and outcomes (Wagner et al., 2022). Examples of healthcare information systems (HCIS) are electronic health records (EHR), personal health record (PHR), and telehealth and telemedicine systems.

Health systems within the last decades have shifted their focus to become more patient-centered. This has proven to be the exemplary model of care. When holding patients at the center of all decision and treatment plans it allows for optimal outcomes at reduced costs. Use of applications such as patient portals allow patients to feel more involved in their care which promotes compliance as they feel as though they are being heard and become empowered to make decisions and then are more likely to follow through with care as they were involved in the decision-making process (Jung, 2016). Telehealth medicine has exploded over the last few years with the progression of the Covid pandemic. Consumers of telemedicine were able to have the ease and convenience of these visits providing an immense advantage to those struggling with mobility, financial burden of leaving the home or mental health disabilities that prove it difficult to interact with large populations. Remote monitoring for consumers allows trained professionals to view vital signs and weight and assist with disease monitoring or decompensation.

The foundation of HIS is the EHR. Healthcare professionals and administration staff all with various needs ranging from scheduling, billing, orders, or prescribing medications can be completed within the EHR system. Key functions of the EHR are health information and data, results management, order entry, decision support, communication, patient support, administrative process, and reporting for population health management (Wagner, 2022). Interoperability within the EHR works cohesively with the health data to be collected and transcribed and transferred from provider to payee or to the patient themselves. Results management collects diagnostic data and houses this for all patients applying analytics, trends, and algorithms regarding value ranges for additional patient safety and tracking. Order entry and decision support coincide jointly for the best patient outcomes. Order entry houses a location for historical tracking if multiple specialists are involved, prevents medication errors by alerting of possible allergies or interactions, and improves workflows as standardization is created. Clinical support tools assist to prevent medication errors from integrated algorithms. They remind providers of upcoming or overdue prevention screenings and predict disease process in certain populations. (Wagner, 2022). Communication with the EHR allows the interdisciplinary care team to collaborate amongst themselves through visibility into other discipline’s documentation. Communication within the platform also provides secure formatting complying with HIPPA regulations. Administrative process for billing and prior insurance authorization can be submitted and obtained with EHR systems. Other administrative personnel can also schedule appointments for other specialists or testing within the facility as ordered. Alerts can then be forwarded to the patient to ensure compliance with the plan of care. Reporting data within the EHR allows for monitoring and transmission of data at state and federal levels to comply with reportable infections or report increases in disease processes among a certain population.

The various capabilities of the EHR system are profound within the healthcare practice. They range from assisting the patient and provider relationship to a high level of reporting to assist the entire nation with disease management outcomes. This focus on prevention and minimization of error not only ensures the optimal outcome but also decreases the overall healthcare cost.

Resources

Jung, M. (2016). Consumer health informatics. The Health Care Manager, 35 (4), 312-320. https://doi.org/10.1097/HCM.0000000000000130

Wager, K. A., Glaser, J., & Lee, F. W. (2022). Health care information systems (5^th ed.).  Jossey-Bass.

You work for a company as a digital marketing manager and you’ve been asked to prepare a comprehensive digital marketing campaign. The campaign will run for the duration of one year, starting January until December 2023.

Important note:

You can choose any company to work with as long as:

• It is a local company.
• It is a startup that was established in the last (3 – 6) years, 2014 onwards.
• It can belong to any industry sector.

Requirements

Part 1, around (1500) words: Due week 8, on 22/10/2022. (Refer to the Textbook Chapters 2, 3, 4, 5,&6 and apply the following in the context of your company)

• Investigate the micro-environment as part of the situation analysis for your company.
• Summaries the macro-environment variable your company needs to monitor when operating the digital marketing campaign. (two or three variables for each force are sufficient)
  • Technological forces.
  • Legal forces.
  • Economic forces.
  • Political forces.
  • Social forces.
• Devise a digital marketing strategy for your campaign. (refer to figure 4.5, page 147 or ch4, slide 9)
  • Where are you now? (situation analysis)
  • Where do you want to be? (business objectives)
  • How are you going to get there? (strategy)
  • How exactly do you get there? (tactics)
  • Who does what and when? (actions)
  • How do you monitor performance? (control)
• Summaries the marketing mix best suitable for your campaign. (refer to ch5)
  • Product variables
  • Price variables
  • Place variables
  • Promotion variables
  • Process variables
• How can you implement relationship marketing for your campaign? (refer to ch6)
  • Could you create a virtual community? And how does it help the relationship marketing.
  • Could you use digital media to support customers’ advocacy? And how?
• How can you implement relationship marketing for your campaign? (refer to ch6)
  • Could you create a virtual community? And how does it help the relationship marketing.
  • Could you use digital media to support customers’ advocacy? And how?

• Competitors analysis
• Suppliers and/or Digital Marketing intermediaries.
• Customers’ persona.

End of Part 1!

Part 2, around (1000) words: Due week 11-12 on 19/11/2022. (Refer to the Textbook Chapters 7, 8, 9 &10) – For legal reasons, you will not actually create business profiles and launch a campaign on different platforms. You will merely write the proposed plan and the expected results and accumulated costs, using real facts from the chosen used platforms. So, do the proper research and choose wisely..

Create a campaign for your company to launch, starting January 2021 till December, that will be active for 12 months. Marketing budget: SR 450,000 to spend on digital advertising media over the next 12 months. The budget also includes up to SR 340,500 for advertising creative and content development, and for the company to manage the program.

End of Part 2!

Part 3, Instructors will manage the date and time for presentation during week 11&12.

Make a power-point presentation of your Project work mentioning all the above contents and present in the class. There must be minimum 10 slides in the presentation with a good background design, readable font size and style with appropriate color.

End of Part 3!

Important instructions and Notes

• This is a group work.
• You will submit online through blackboard.
• A cover page is required for each submission, one mark will be deducted if there is no cover page.
• The submitted document needs to be structured as follow: a cover page, assignments’ requirements’, then your answers. without these instructions.
• The assignments parts will be each submitted on a different date. However, part 2 needs to contain part one.
• The reference list, a minimum number of 10 references and citations is required, and you must use APA referencing style.
  • Quotations must be cited to its resources.
• The paper styles:
  • The format of the paper needs to be introduction, main body and conclusion.
  • Your work needs to be consistent in terms of style, tone and appearance.
  • Font size: 12.
  • Font type: Times New Roman,
  • Page are numbered.
  • 1.5 spacing between lines and paragraphs.
  • Left alignment.
• Entire project word count, around 2500 words.
• You must check the spelling and grammar mistakes before submitting the assignment. You can ask someone to proofread your work or use online tools.
• Up to 20% of the total grade will be deducted for providing a poor structure of assignment. Structure includes these elements: paper style, free of spelling and grammar errors.

In case of any questions, please refer to your instructor

Successful marketing requires effective relationship marketing, integrated marketing, internal marketing, and performance marketing. In this chapter, we consider the societal impact of a company’s marketing activities and examine the key dimensions of corporate social responsibility. A company must also choose what countries to enter based on the product and factors such as geography, income, population, and political climate. Competitive considerations come into play, too. It may make sense to go into markets where competitors have already entered to force them to defend their market share, as well as to learn how they are marketing in that environment.

One of the problems that some large multinational corporations, such as Nike, Hershey, and H&M, to name just a few, have had is bad press as a result of not being socially responsible toward the people they employ in other countries. The use of child labor in third-world countries is a huge concern and one that every company doing business there must be aware of. Regardless of what is practiced in third-world countries, American businesses conducting business overseas must follow American employment laws.

Conduct research on the use of child labor overseas and locate a USA-based company that has gotten into international trouble for hiring underage children for a mere pittance of what American workers earn for the same jobs or to do dangerous jobs. Then, review the company’s social responsibility policy on their website and discuss the following: The situation found overseas by the company or its contractors or representatives. According to what you read on the Internet, is the company following its own social responsibility policy regarding the hiring of children overseas? What should the company do differently if anything? Does the prospect of a company hiring underage children as laborers make you think twice about purchasing any of their products?

Be sure to include a reference list after your initial post.

Be sure to include a reference list after your initial post.At least 2 references including Kotler, P., Keller, K. L., & Chernev. A. (2022). Marketing management (16th ed.). Pearson.

Angmering Raceway Car Jumping Simulation with Graphical User Interface (GUI)
Angmering Raceway is a motor racing circuit on the outskirts of Angmering, West Sussex in the
United Kingdom. Here is the Angmering Raceway website. Angmering Raceway – Oval Raceway at
Angmering, West Sussex
One of the Angmering Raceway Car Jumping Competitions is in the following YouTube Video.

The objective of the car jump competition is to drive over a 7 m long (horizontally) and 1.5 m high
(vertically) jump ramp and jump over 9 cars parked tightly side-by-side, approximately 1.8 m x 9 =
16.2 m long distance.
Car jumps utilize the slop of the ramp and fast speed to create a catapult effect that launch the car
into the air at an angle like a catapult. Since the slop of the ramp is fixed, the distance of the jump
will be determined by the velocity of the car when it jumps off the ramp.
Car repairs can be time consuming and expensive. Write a MATLAB App Designer app using
Graphical User Interface (GUI) to help the race driver to visualize the jump and simulate the result.
Add an Axes to show a picture of the race car in GUI when the app starts [2 pt]
.
Add another Axes in GUI to plot the jump ramp and parked cars in GUI when the app starts [2 pt]
.
1. The jump ramp is 7 meters long (measured horizontally) and 1.5 meters tall (measured
vertically). Create a new variable to store the jump ramp x-direction coordinates, 0 and 7
[1pt]. Create another new variable to store the jump ramp y-direction coordinates, 0 and 1.5
[1pt]
.
2. The tightly parked cars (for the race drivers to jump over) are 16.2 meters long and 1.5
meters high. Create a new variable to store the parked cars x-direction coordinates, 7, 7,
(7+16.2), and (7+16.2) [1 pt]. Create another variable to store the parked cars y-direction
coordinates, 0, 1.5, 1.5, and 0 [1 pt]
.
3. Plot the jump ramp [2 pt] and the tightly parked cars [2 pt]
.
4. Set XLim to [0 35] [1 pt]. Set YLim to [0 25] [1 pt]
.
5. Add plot title [2 pt]
, x-axis label [1 pt]
, y-axis label [1 pt], and legend [2 pt]to the plot.
Add a Label in GUI to show the race driver the current car speed in MPH [2 pt]
. The label should show
0 MPH when the app starts [2 pt]
.
Add a speedometer Gauge in GUI to show the race car in MPH [2 pt]
. The gauge should point to 0
MPH when the app starts [2 pt]
.
Add a start Button in GUI [2 pt] for the race driver to click to start the simulation and to start speeding
up the car. When this start Button is clicked, the app should:
1. Modify the picture of the race car to show another picture [2 pt]
.
2. Increment the text shown in the car speed label by 1 MPH every 0.2 seconds (200
milliseconds) [2 pt]
.
3. Increment the gauge value by 1 MPH every 0.2 seconds (200 milliseconds) [2 pt]
.
Add a Jump Button in GUI [2 pt] for the race drive to click when the car reaches the desired jump
speed. When this Jump Button is clicked, the app should:
1. Stop the car speed increment of the text shown in the car speed Label [2 pt]
.
2. Stop the increment of the Gauge value [2 pt]
.
3. Take the current car speed value in MPH from the Gauge and use the value for the simulation
computation [2 pt]
.
4. Convert the car speed from miles per hour (mph) to meters per second (m/s) [2 pt]
.
5. Compute the jump ramp incline angle [2 pt]
.
6. Compute the initial velocity of the car in the x [2 pt] and y [2 pt] directions (vx0 and vy0).
7. Compute the time it takes for the car to reach the maximum height (vy = 0) using vy = vy0 + ay t
[2 pt]
.
8. Compute the maximum height [2 pt] using y = y0 + vy0t + ½ ay t
2
.
9. Compute the time it takes for the car to free-fall (with zero initial velocity) from the
maximum height to the ground [2 pt]
, using y = y0 + vy0t + ½ ay t
2
.
10. Compute the total flight time of the projectile [2 pt], the time it takes for the car to reach the
maximum height plus the time it takes for the car to free-fall from the maximum height to the
ground.
11. Use the MATLAB linspace function to generate a large array of time that starts at 0 and ends
at the total fly time with 100 equally spaced time points [2 pt]
.
12. Compute a large array of x
[2 pt] and another large array of y
[2 pt] values by applying elementby-element computation to the large array of time.
13. The jump ramp is 7 meters long (measured horizontally) and 1.5 meters tall (measured
vertically). Create a new variable to store the jump ramp x-direction coordinates, 0 and 7
[1pt]. Create another new variable to store the jump ramp y-direction coordinates, 0 and 1.5
[1pt]
.
14. The tightly parked cars (for the race drivers to jump over) are 16.2 meters long and 1.5
meters high. Create a new variable to store the parked cars x-direction coordinates, 7, 7,
(7+16.2), and (7+16.2) [1 pt]. Create another variable to store the parked cars y-direction
coordinates, 0, 1.5, 1.5, and 0 [1 pt]
.
15. Use element-by-element addition to add the length of the jump ramp (7 m) to every value in
the large array of x projectile motion coordinates [2 pt]
.
16. Now we are ready to prepare the coordinates for the top of the race car. The race car is 1.5
meters tall. The x-direction coordinates for the top of the race car can be obtained from
combining the jump ramp x-direction coordinates and the new x-direction projectile
coordinates together into a new array [2 pt]
. The y-direction coordinates for the top of the
race car can be obtained from combining the jump ramp y-direction coordinates + 1.5 and
the y-direction projectile coordinates + 1.5 together into a new array [2 pt]
.
17. Plot the jump ramp [2 pt]
, the tightly parked cars [2 pt]
, the bottom of the race car projectile
motion [2 pt] and the top of the race car projectile motion [2 pt] in the same figure.
18. Set XLim to [0 35] [1 pt]. Set YLim to [0 25] [1 pt]
.
19. Add plot title [2 pt]
, x-axis label [1 pt]
, y-axis label [1 pt], and legend [2 pt] to the plot.
20. Multiply the time it takes for the car to reach the maximum height by 2 to obtain the time
the race car flies above 1.5 m [2 pt]
.
21. Compute the horizontal distance the race car flies above 1.5 m using x = x0 + vx0t + ½ ax t
2
.
Recall that ax = 0 [2 pt]
.
22. If the horizontal distance the race car flies above 1.5 m value is greater than 16.2 [2 pt]:
a. Modify the picture of the race car to show a successful picture [2 pt]
.
23. Else:
a. Modify the picture of the race car to show a crash picture [2 pt]
.
24. End.
Additional components are always welcome!
(Here is an example display when the program starts.)
(Here is an example display after clicking the START+SPEED button. Note that the speed goes up
automatically.)
(Here is an example display showing the speed automatically goes up.)
(Here is an example clicking the JUMP button at 56 MPH.)
(Another example for clicking the JUMP button at 39 MPH.)
Ensure your hw1 folder contains all files.
Include all the pictures used in hw1 GUI in the same folder.
Zip the entire hw1 folder.
Rename the hw1.zip to LastName_FirstName_ME106_hw1.zip
Submit the .zip file to Moodle.

The client is a 46-year-old white male who works as a welder at a local steel fabrication factory. He presents today after being referred by his PCP after a trip to the emergency room in which he felt he was having a heart attack. He stated that he felt chest tightness, shortness of breath, and feeling of impending doom. He does have some mild hypertension (which is treated with low sodium diet) and is about 15 lbs. overweight. He had his tonsils removed when he was 8 years old, but his medical history since that time has been unremarkable. Myocardial infarction was ruled out in the ER and his EKG was normal. Remainder of physical exam was WNL.

He admits that he still has problems with tightness in the chest and episodes of shortness of breath- he now terms these “anxiety attacks.” He will also report occasional feelings of impending doom, and the need to “run” or “escape” from wherever he is at.

In your office, he confesses to occasional use of ETOH to combat worries about work. He admits to consuming about 3-4 beers/night. Although he is single, he is attempting to care for aging parents in his home. He reports that the management at his place of employment is harsh, and he fears for his job. You administer the HAM-A, which yields a score of 26.

Client has never been on any type of psychotropic medication.

MENTAL STATUS EXAM

The client is alert, oriented to person, place, time, and event. He is appropriately dressed. Speech is clear, coherent, and goal-directed. Client’s self-reported mood is “bleh” and he does endorse feeling “nervous”. Affect is somewhat blunted, but does brighten several times throughout the clinical interview. Affect broad. Client denies visual or auditory hallucinations, no overt delusional or paranoid thought processes readily apparent. Judgment is grossly intact, as is insight. He denies suicidal or homicidal ideation.

You administers the Hamilton Anxiety Rating Scale (HAM-A) which yields a score of 26.

Diagnosis: Generalized anxiety disorder

Decision Point One

Select what you should do:

Begin Zoloft 50 mg po daily

Begin Imipramine 25 mg po BID

Begin Buspirone 10 mg po BID

Decision Point One

Begin Zoloft 50 mg orally daily

RESULTS OF DECISION POINT ONE

• Client returns to clinic in four weeks
• Client informs you that he has no tightness in chest, or shortness of breath
• Client states that he noticed decreased worries about work over the past 4 or 5 days
• HAM-A score has decreased to 18 (partial response)

Decision Point Two

Select what you should do next:

Increase dose to 75 mg orally daily

Increase dose to 100 mg orally daily

No change in drug/dose at this time

Decision Point Two

Increase dose to 75 mg orally daily

RESULTS OF DECISION POINT TWO

• Client returns to clinic in four weeks
• Client reports an even further reduction in his symptoms
• HAM-A score has now decreased to 10. At this point- continue current dose (61% reduction in symptoms)

Decision Point Three

Select what you should do next:

Maintain current dose

Increase current dose of medication to 100 mg orally daily

Add augmentation agent such as BuSpar (buspirone)

Decision Point Three

Maintain current dose

Guidance to Student
At this point, it may be appropriate to continue client at the current dose. It is clear that the client is having a good response (as evidenced by greater than a 50% reduction in symptoms) and the client is currently not experiencing any side effects, the current dose can be maintained for 12 weeks to evaluate full effect of drug. Increasing drug at this point may yield a further decrease in symptoms, but may also increase the risk of side effects. This is a decision that you should discuss with the client. Nothing in the client’s case tells us that we should consider adding an augmentation agent at this point as the client is demonstrating response to the drug. Avoid polypharmacy unless symptoms cannot be managed by a single drug.

For discussion, you will review this week’s interactive media pieces and select one to focus on for this discussion.

You will reflect on the decision steps in the interactive media pieces and consider the potential impacts from the administration of the associated pharmacotherapeutics based on the patient’s pathophysiology.

Post a discussion of pharmacokinetics and pharmacodynamics related to anxiolytic medications used to treat GAD. In your discussion, utilizing the discussion highlights, compare and contrast different treatment options that can be used.

Supported by at least three current, peer reviewed scholarly work credible sources. DO NOT USE PATIENT -ORIENTED PUBLICATIONS AS YOUR CITATIONS.