NESEP Archive

Abstract: COVID-19 has proven detrimental to the economy and changed the nature of social interactions. Governments at every level have increasingly required the use of face masks in public spaces. Evidence has shown that mandatory mask-wearing policies can effectively control the outbreak of the virus, protecting susceptible populations (i.e., individuals with preexisting conditions, individuals 65 and older). Many communities encourage mask-wearing to reduce the chance of viral transmission. While mandatory mask policies appear to effectively reduce transmission of the virus, their long-term psychological effects are not yet known. In this study, we examine the association between the implementation of face mask mandates and detrimental psychological and social consequences as well as other relevant aspects. Also, this study tries to figure out if the mandatory mask policies are advisable, and if so, how it benefits the public. 

Overall, this paper tried to suggest that short-term and institutional responses can coexist as a response to the issue. In addition, the quarantine policy examined in this paper showed a partial response. It is clear that there is no one policy that can comprehensively respond to the global and social problems brought about by the COVID-19 pandemic. Perhaps the government's policy cannot and does not need to fully respond to all the ills that our society faces. The government may be able to alleviate the problem by only partially responding to the public concerns and leaving the rest to the officials and citizens. In addition, the central government can overcome the issue by withholding judgment and by expressing an active choice by local governments and the media. By reviewing the quarantine policy for the COVID-19 crisis, it will be possible to discuss how a partial response to a policy problem can be improved.

Keywords: COVID-19, Mask Policies, Social Consequence, Anxiety and Stress, Psychological Effects

References

1. Detsky, A. S. and Bogoch, I. I. (2020, August 25). The Canadian Response To COVID-19. Retrieved from https://jamanetwork.com/journals/jama/fullarticle/2769439

2. Duan, L. and Zhu, G. (2020). Psychological interventions for people affected by the COVID-19 epidemic. Lancet. Psych. 7 300–302. 10.1016/s2215-0366(20)30073-0

3. Greenberg, N., Docherty, M., Gnanapragasam, S. and Wessely, S. (2020). Managing mental health challenges faced by healthcare workers during covid-19 pandemic. BMJ 368:m1211. 10.1136/bmj.m1211

4. Liu S., Yang L., Zhang C., Xiang Y. T., Liu Z., Hu S., et al. (2020). Online mental health services in China during the COVID-19 outbreak. Lancet. Psych. 7 E17–E18. 10.1016/S2215-0366(20)30077-8

5. Maheu, M. P., McMenamin, J. and Posen, L. (2012). Future of telepsychology, telehealth, and various technologies in psychological research and practice. Profess. Psychol. Res. Prac. 43 613–621. 10.1037/a0029458

6. Parshley, L. and Zhou, Y. (2020, December 4). Why every state should adopt a mask mandate, in 4 charts. Retrieved from https://www.vox.com/science-and-health/21546014/mask-mandates-coronavirus-covid-19

7. The Economist. (2020, October 14). Tracking covid-19 excess deaths across countries. Retrieved from https://www.economist.com/graphic-detail/coronavirus-excess-deaths-tracker

8. The Economist. (2020, October 11). Covid-19 has led to a sharp increase in depression and anxiety. Retrieved from https://www.economist.com/graphic-detail/2021/10/11/covid-19-has-led-to-a-sharp-increase-in-depression-and-anxiety

9. Wang, C. J., Chun, Y. and Brook, R. H. (2020, April 14). Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing. Retrieved October 18, 2020, from https://jamanetwork.com/journals/jama/fullarticle/2762689

10. Zhou X., Snoswell C. L., Harding L. E. (2020). The Role of Telehealth in Reducing the Mental Health Burden from COVID-19. Telemed. E Health. 26 377–379. 10.1089/tmj.2020.0068

Abstract: Pneumonia, a fatal lung disease, is caused by infection of Streptococcus pneumoniae; it is detected by chest x-rays that reveal inflammation of the alveoli. However, the efficiency by which it is diagnosed can be improved through the use of artificial intelligence. Convolutional neural networks (CNNs), a form of artificial intelligence, have recently demonstrated enhanced accuracy when classifying images. This study used CNNs to analyze chest x-rays and predict the probability the patient has pneumonia. Furthermore, a comprehensive investigation was conducted, examining the function of various components of the CNN, in the context of pneumonia x-rays. This study was able to achieve significantly high performance, making it viable for clinical implementation. Furthermore, the architecture of the proposed model is applicable to various other diseases, and can thus be used to optimize the disease diagnosis industry.

Keywords: artificial intelligence, disease diagnosis, pneumonia, convolutional neural networks, machine learning

References

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Abstract: Extreme weather events are becoming more prevalent with increasing global temperatures. In the Northeastern U.S., spring frost events are destroying forest ecosystems by defoliating newly budded trees. In order to grasp a better understanding of community dynamics and carbon fluxes, it is imperative to understand more about species-specific phenological and physiological responses to these events. This study aimed to investigate the legacy effects of a spring frost event in Black Rock Forest on the specific photosynthetic and intrinsic water use efficiency responses within unaffected red maples and sugar maples alongside defoliated red oaks. A LI-6800 machine conducted gas exchange measurements in the north, south, valley, and headquarter sites for each species. The new flush of red oak leaves portrayed

the greatest amount of photosynthetic productivity and efficiency while red maples and sugar maples retained their original characteristics with increased sensitivities. Hence, the defoliated tree species had a competitive advantage with shifted phenological patterns. Future research can be conducted several growing seasons after the frost event to determine the extent to which these events impact species dynamics, including DBH tree growth. New predicative carbon models can also be formed to create new management for tree implantation’s that maximize sequestration rates.

Keywords: spring frost event, defoliation, photosynthetic productivity, water use efficiency, sequestration

References

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Abstract: The areas of the brain that become active when formulating a lie, or “deceit patterns, are denoted on fMRI scans, yielding results that are more accurate than the polygraph. Using publicly available court records and fMRI results obtained from previous literature, the extent to which fMRI scan evidence influences juror confidence, perceived strength of argument, and verdict counts between participants serving as mock jurors in a mock trial exposed to fMRI scan evidence and those not exposed to it were compared. Analysis of these metrics revealed that a mock juror’s exposure to fMRI evidence increases their perceived strength of the argument for the side consistent with their verdict and drastically changes the distribution of guilty versus not guilty verdicts. The difference in confidence levels between mock jurors in the control and experimental groups was not found to be statistically significant, however future research using a larger sample size may verify the current trend that viewing fMRI evidence increases juror confidence in their verdict. Although fMRI evidence possesses the potential to revolutionize the way juries lend weight to pieces of evidence, because it was found to cause such significant shifts in juror decision making, court judges should caution its admission into evidence or further scrutinize its credibility during evidentiary suppression hearings until it is deemed generally acceptable by the scientific community.

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Abstract: Though sharp-wave ripples have been recorded in the EEG data of the hippocampus of mammals for years, it remains unclear how ripples can contribute to memory for different behaviors.. Sharp wave ripples are one of the most synchronous patterns in the mammalian brain. These waves are most common during non-REM sleep, although they can also be associated with consummatory behaviors. In EEG recordings, these occurrences can be seen as large amplitude negative polarity deflections (40–100 ms) in CA1 stratum radiatum that are associated with a short-lived fast oscillatory pattern of the LFP in the CA1 pyramidal layer, known as “ripples.” The purpose of this study was to investigate the distinction between sleep and awake ripples along with the connection between sharp-wave ripples and specific mammalian behaviors during memory tasks. The hypothesis tested was that SPW-Rs occur when the animal has an experience that will help guide subsequent successful task completion that results in obtaining a desired reward. To conduct the experiment electrophysiological signals were collected from a rat’s hippocampus during various tasks. The data were then analyzed using Neuroscope and compared to a visual recording of the rat’s actions. The data suggest that sharp wave ripples are more likely to occur close to a reward, most often before the reward, and do not have a higher tendency to occur early or late in learning. Future research can further clarify these results and investigate the process by which these ripples occur.

References

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Abstract: Even though Major Depressive Disorder (MDD) is the leading cause of disability worldwide impacting over 300 million individuals, early detection and intervention is hindered by the limited knowledge of its underlying mechanisms. One association found to be significant within MDD is the presence of early life stress (ELS), such as sexual abuse, emotional abuse and family conflict. However, the biological mechanism linking ELS and MDD are unknown.

To properly assess the function consequences of ELS within MDD and address these open questions, we propose an analysis of the metabolism of AMY, ACC, HIP, and DLPFC through FDG PET in addition to a structural MRI in MDD patients with and without ELS. We hypothesize that in MDD patients with prior history of ELS, compared to those without ELS, will have a smaller volume/cortical thickness as measured by MRI and decreased metabolism as measured by PET scans in the bilateral DLPFC, ACC, HIP, and AMY. This study would for the first time, assess both structure and function of critical regions of the HPA axis in MDD, while accounting for the common confounder of ELS.

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