Individuals experience various mood states or emotions at varying times every day, both subtle changes and obvious changes, that can result in attitude alternations with both negative and positive effects and impair or facilitate performance. The connections in the brain between emotion and memory have been particularly interesting to researchers given that neural networks that are activated by mood states are linked with neural networks that process basic perceptual functions such as word processing. Dr. Siebert has conducted a number of research experiments inducing various mood states through the use of music and then studying the effects of mood on lexical processing. (Dr. Pennie S. Siebert)

Previous research has shown that mood effects can be found in brain function at the level of lexical access. According to the associative network model of memory and emotion, emotions are represented in networks of nodes, as are words. Stimulation of emotion nodes activates networks that prime the retrieval of word nodes, creating mood-related effects on word retrieval such that positive emotions are associated with faster retrieval of positive words and negative moods are associated with faster retrieval of negative words. However, the speed of word retrieval may vary by type of mood, indicating stronger mood-related effects for some emotions compared to others. To assess differences in the speed of word retrieval under the influence of various mood states, researchers randomly assigned participants to happy, sad or neutral mood conditions and then tested their lexical retrieval of emotion-laden words.Participants were randomly assigned to listen to 30 minutes of happy, sad, or neutral music. They were then given a Reicher test which briefly presents a short string of letters that may or may not form a word. Participants were tasked with deciding whether or not the letters represented a word. Reaction time on the Reicher test was recorded for the three groups. Lower reaction time scores indicate greater mood effects on memory.

Research Question: Is there a difference in word recall among individuals who listen to happy, sad and neutral music?

Sad: 384.82, 380.26, 324.24, 314.68, 336.74, 380.26, 404.62, 331.46, 338.04, 418.28 [T=3613.98; M=361.40]

Neutral: 466.32, 430.94, 332.28, 338.04, 418.28, 597.08, 482.74, 436.74, 442.28, 580.34 [T=4525.04; M=452.50]   

Happy: 397.08, 482.74, 332.60, 397.92, 418.94, 519.54, 387.74, 442.62, 376.50, 360.34 [T=4116.08; M=411.61]

1. Write null and alternative hypotheses (in words and notation) appropriate for this research scenario.

2. Explain the concepts of SS_between, SS_within, SS_total, MS_between, and MS_within. With respect to this specific dataset, interpret what are those numbers are telling you?

3. Using the ANOVA Formula Worksheet, compute an ANOVA to test the hypotheses at an α = .05.

4. Compute the η² and interpret it. What might be variables that would influence mood other than listening to certain types of music?

United States / China

Long-Term Care Today

Demographics and epidemiological transitions result in dramatic changes in the health needs of individuals throughout the globe. In recent times, there has been increase in the prevalence of long-term disability in the population—causing increasing need for long-term care services. In addition, the present developing world is experiencing an increase in the demand for long-term care services at a cost much lower than industrialized countries.

·      Who are the institutional and non-institutional caregivers in both the countries? Support your answer with relevant examples. Explain the factors that affect care giving in each country.

·      Is there any difference in the status of quality of care of the elderly consumers in the United States as compared to the developing country?

·      Is there any difference in the health care cost provided in the United States as compared to the developing country? Define any social support that may exist to cover health care in both countries.

Provide guidance on how a firm could mitigate the impact of currency exchange changes: EUR/AED (Euros / United Arab Emirates Dirham)

- How should the firm approach transaction, translation, and/or operating exposure in the UAE (United Arab Emirates)

Scenario:

You are operating a German manufacturing firm in the UAE.

How do the two articles below address the dividend discount model and show changes from original estimations to later estimations based on first quarter results? Any analysis of these two articles would be greatly appreciated so I may better understand the DDM.

The first article was written in April of 2018 and the second was written in July 2018.

April 2018 Article: https://seekingalpha.com/article/4166249-mcdonalds-corporation-target-price-147-according-dividend-discount-model

July 2018 Article: https://seekingalpha.com/article/4189029-mcdonalds-current-valuation-view?page=2

Describe the four key bond valuation relationships. Explain why bond prices move inversely to changes in interest rates after watching the YouTube video "Relationship between bond prices and interest rates | Finance & Capital Markets | Khan Academy", hosted by Khan

1.) Name one psychological change and two physiological changes that can occur in older adults

2.) Describe the difference between Dementia and DeliriumOlder Adult Case Study:

Mrs. K is an 81-yr old female patient that has been admitted for a mechanical fall that resulted in a right hip fracture. Mrs. K had to undergo emergency hip repair surgery yesterday. She has a past medical history of Hypertension, Hypothyroidism and Anxiety. She takes Hydrochlorothiazide and Levothyroxine. Her past surgical history includes bilateral knee replacements 25 years ago. She is a retired book-keeper and a widow that lives alone. Her husband passed away 10 years ago. Mrs. K is usually very active with her social circle of friends and her church community. She plays cards weekly and attends religious services twice per week. She wears glasses, has cataracts bilaterally and walks with a 1-point cane. It is post-operative day #1 (day after surgery occurred) and RN Susie has been assigned to care for Mrs. K. Per the off-going RN from night shift Mrs. K has been experiencing a lot of post-surgical pain in her right hip (ranging from 5-8); and has been taking Oxycodone every 4-6 hours PRN for breakthrough pain. She is receiving continuous IV fluids to help hydrate her after surgery. Mrs. K also has an indwelling urinary catheter. RN Susie received report/nurse handoff from night shift nurse who lets her know Mrs. K has been restless all night, didn’t sleep much, and that they had to put on the bed alarm last night as well as checking on her every 30 minutes as Mrs. K kept trying to climb out of bed during the night.

Upon morning assessment RN Susie observes Mrs. K “picking at the air”, with her right hand, mumbling incoherently to herself as she is sitting up in bed with her breakfast table in front of her, and continually spooning “something” into her mouth with an empty spoon in her left hand (there is nothing on her tray table). She is not wearing her glasses either (RN Susie is not able to find her glasses in the room after looking for 10 minutes). RN Susie assesses Mrs. Ks’ level of consciousness and finds she is A/O x 1 (alert to self only) as she can tell only RN Susie her name when asked. As RN Susie proceeds further through the shift she becomes concerned that Mrs. K might be exhibiting symptoms of delirium and is unsure how to proceed.Case Study Questions:

1.) Identify pertinent assessment data gathered on Mrs. K that points toward a diagnosis of Delirium.

2.) Create two nursing diagnoses for this new secondary diagnosis of Delirium and ensure your diagnoses are directly related to your assessment information (1x Problem-Focused and 1x Risk For nursing diagnosis)

3.) Indicate 2 nursing interventions based on your 2 nursing diagnoses. Write 1x goal statement and 2x expected outcomes that are connected with your nursing interventions.

Q3: Pharmaceutical industry firms have been trying to counter the changes below through M&A and strategic alliance activity. Please categorize them according to Porter’s Five Forces.

Porter’s Five Forces:
-Threat of substitutes (SUBST)
-Threat of new entrants (NEWE)
-Threats of supplier leverage (SUPPL)
-Threat of buyer leverage (BUYER)
-Threat of rivalry (RIVAL)

Adapted from Schon, H. 2015. Pharmaceuticals M&A versus alliances and its underlying value drivers.
1. ________ Government austerity measures like the 2010 Affordable Care Act have lowered prices.
2. ________ Generics constituted 22% of pharmaceutical sales in 2006, 40% in 2016.
3. ________ Biologics (biotechnology) accounted for 16% of pharmaceutical sales in 2006, 22% in 2016.
4. ________ R&D productivity in terms of new FDA-approved small and large molecules has remained essentially unchanged since 1998, perhaps contributing to slowing industry sales at large firms.

Analysis:

1. Consider your galaxy rotation curves. Describe how rotational velocity changes as a function of distance from galaxy center. Do all the galaxies show similar behavior?
2. Now compare the galaxy rotation curves to the curve you plotted for the solar system planets. How do they differ?
3. We know that most of the mass (>99%) of the solar system is in the Sun. Is this consistent with the masses you calculated in the first table, and the solar system rotation curve? Explain your answer.

4. What pattern do you notice about the masses calculated in the galaxy tables? How does this pattern differ from that of the solar system table?

5. Explain how your results imply the existence of dark matter in the halos of galaxy? (You may need to do additional research to make this connection.)