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E-waste is a global concern due to its environmental and health risks, and India, as a top producer, generates 3.23 million tonnes annually(Sengupta et al., 2023). India is adopting circular economy principles, influenced by the 4R paradigm, to address this issue. The goal of the circular economy is to achieve zero waste and to not waste any materials of a product- in this case, an electronic product at its end-of-life stage. The circular economy approach has the potential to be advantageous in multiple aspects including providing economic, environmental, and health benefits. Unfortunately, India has not been able to realize this potential due to its large informal sector, a sector that is unregulated by the government and processes almost all of the e-waste generated in India in a crude manner. Through a comprehensive literature review, the transition to a circular economy in the electronic waste sector is explored in India. First, key definitions and context on circular economy and e-waste is introduced, then context on India’s e-waste sector is discussed, benefits to formalizing the informal sector is analyzed, circular economy applications under the 4R paradigm in India is explored, and finally solutions to promote circular economy and recommendations on formalizing are given. The findings suggest that the primary challenge to shifting to a circular economy lies in the prominence of the informal sector, which is inefficient in resource recovery, unsafe and difficult to trace, and that solutions lie in incentivizing producer responsibility for waste, changing regulations around urban mining practices, raising awareness for consumers, and integrating the informal and formal sector.

Environmental Economics, Energy Modelling, Environmental Policy, Climate and Energy Transition, Energy Modeling, International Affairs, Carbon Footprinting, Net Zero, Literature Reviews, Applying behavioural economics to environmental issues

Literature Review of Application of CE to India’s E-Waste Problem, Using the 4R Paradigm to Identify Challenges and Opportunities

Previous research claims business firms should be innovative because innovative firms will be able to gain market advantage and become the market leader. Innovation is both a positioning and differentiation strategy that gives firms a unique position in the consumers’ minds, attracting their attention and separating them from the rest of the firms (Carpenter 1994). This increased attention has positive effects on perceptions of the company and on purchase intentions (Bae 2016). Earlier research has focused on how innovation impacts individual firms and how innovation impacts performances against market leaders. This research, however, focuses on how innovation impacts industries as a whole. Industries may naturally differ in how innovative they appear because of differentials in progress in the technologies or products that comprise each industry (Fuerst 2017). It was hypothesized that more innovative markets are likely to experience volatility than non-innovative markets. Greater sales from innovation can come from new consumers or from existing consumers from other companies. If the latter were true, a rise in market share from an innovative company would come at the expense of other companies, creating greater changes in market share. Data analyzing the frequency of change in market share among the top five companies in both innovative and non-innovative industries shows that there is a more frequent change in market share in innovative industries. Therefore, the findings indicate that innovativeness has a weak point because innovative industries are more volatile in terms of market share than non-innovative industries. Innovative markets are harder to dominate than non-innovative markets, meaning firms in more innovative industries need to innovate consistently and constantly to maintain a high position in consumers’ minds.

Marketing, Consumer Psychology, Social Psychology, Prosocial Behavior, Respect and Consumer Dignity, Emotions, Identity, Branding

Innovation Creates Volatility: The Disadvantage of Innovation

Former president Donald Trump endorsed over
200 candidates during the 2022 election cycle; in total, he has endorsed 551 candidates
since he took office. Facilitated by the convenience of social media, other
major political figures, including Bernie Sanders and Barack Obama, have
endorsed similar numbers of candidates. Though such endorsements ostensibly
advance a certain political cause and support a candidate’s viability, it is
uncertain what effects they actually have on the political landscape of the
United States today. In this project, we want to determine how much of a
measurable effect these endorsements have on midterm elections in the United
States and the political makeup of Congress as a whole. In order to quantify
the effect of an endorsement on an election, we hope to perform a regression,
with several fundamental factors, including endorsements, state and district
demographics (race, income and age distribution), and political leanings by
state. Data on these factors can be obtained from several sources, including
Nate Silver's 538 sites, Ballotpedia, and the US Census Bureau. Once we obtain
our data, we will perform a statistical analysis and construct a predictive
model for the election outcome based on the fundamental variables.

 

We can use multiple statistical methods to
make predictions based on our data, including linear regression, multiple
regression, and random forests. We will also assess the robustness and
predictive power of our model through “leave-one-out” cross-validation methods
and applying election results of previously unseen candidates endorsed by major
political figures. Through evaluating the endorsement impact of major political
figures in the US, we hope to ascertain whether or not former presidents such
as Trump or Obama still retain lingering influence over their party, as well as
the “kingmakers” of Congressional elections today. Finally, we will apply our
model to the ongoing 2022 midterm elections (featuring many candidates for
which Biden, Sanders, Trump etc. have already staked their claim) and attempt
to forecast each endorsed candidate’s victory margin through fundamental
factors, state political leanings, and endorsement impacts.

Computer Science theory, particularly complexity theory or algorithms. Also interested in game theory, especially applications of computational methods to microeconomic theory and political science.

Who controls U.S. politics? An analysis of major political endorsements in U.S. midterm elections

Sammi will be writing an 8-10 page research essay on _Pride and Prejudice_. Her research will involve searching academic journal databases, selecting and summarizing the arguments of other scholars and critics, and incorporating their arguments within her own analysis. She might also conduct research on the novel's historical context and/or literary theory related to Austen. A description of her specific topic is forthcoming.

Comparative Literature; Film Studies; Literary Analysis; Cultural Studies; Francophone, Anglophone and Arabophone Literature & Cinema; Postcolonial Theory

Research essay on Austen's _Pride and Prejudice_

While there are many root causes for mass migration from Central America to the United States, the COVID-19 pandemic and climate change have particularly exacerbated this problem. In recent years, Central American countries, such as Guatemala, El Salvador, and Honduras, have suffered from an increase in economic inequalities, natural disasters, and even civil wars. Since 2020, the number of Central American migrants entering the United States has risen at an extreme rate, as more people seek asylum. In the summer of 2021, the Biden-Harris Administration launched the “U.S. Strategy for Addressing the Root Causes of Migration in Central America”, or more commonly known as the Root Causes Strategy. This paper serves to examine this novel approach by the Biden Administration to Central American immigration and the recent influx of refugees in the United States, eventually determining whether or not the policy will be successful. It will examine past United States policies, whether successful or not, in relation to the new Biden Administration strategy. Additionally, it will evaluate past foreign aid programs, such as those of the United States Agency for International Development (USAID), and the current relationships with those Central Americans countries. While the United States has engaged in a series of foreign aid programs in the past, even with these countries, none of these policies or programs have attempted to address the Central American migration crisis and its root issues. This new policy shifts away from those of the past which focused on immigrants’ rights in the United States, instead of getting to the “root cause” of the immigration problem: immigration itself.

Humanities, Social Sciences, Multiculturalism, Human Rights, Globalization, Sociology, Public Policy, Political Science, International Relations, Public Health, Ethnography, Religious Studies, Linguistics, Middle Eastern Studies, South Asian Studies, Human Migration

What is the effectiveness of the new Biden-Harris Administration strategy on the root causes of Central American migration? (main)Do the listed policy objectives align with the current issues of the migration crisis? (subquestion)How is this strategy different from those of the past in addressing Central American migration? (subquestion)Has the Administration followed through on their strategy? (subquestion)

Effective wound healing depends on several factors including on the presence of bacteria and other potentially pathogenic organisms. Controlling their growth in the wound is central to a favorable prognosis. There are several commerciallly available wound dressings that contain silver as an antiseptic. The purpose of the study will be to assess the ability of these different dressings to limit bacterial growth. The student hypothesizes that one ore more of the dressings will be most effective at controlling bacterial growth. To test this hypothesis the student will perform bacterial growth assays. Results are expected to show that one (or more) of the dressings will outperform the others. 

Biology (cell and molecular biology, neuroscience, genetics)

Effect of silver-containing wound dressings on the growth of bacteria

I remember the walks home from my middle school. At 3:00 PM, on the dot, hoards of middle schoolers poured out of classrooms, crowding the streets daily with their bikes, band instruments, and roller backpacks. For us, the commute home was a time of relief, a comforting ritual almost, to chat and laugh with each other on the way home after a long day at school. I remembered these walks home as I read the report from Citizens Advisory Committee on Enrollment that listed my middle school to close in a plan for budget cuts due to declining enrollment in four of the six scenarios presented. It seemed almost impossible to me as I recounted the full classrooms, seemingly endless lunch lines, and crowds of children congregating in the campus quad. In the end, the school board decided to close two elementary schools, consolidate another, and leave my middle school on the table after seeing enrollment trends in the years after. Children, current and future, who were previously intending on attending these schools would miss out on their walks home from school. My experience is not unique, though. Birth rates around the U.S. have been declining ever since the Great Recession from 2007-2009, translating into lowering public school enrollment. Moreover, public school enrollment has similarly faced dwindling numbers in recent years due to the COVID-19 pandemic. This paper aims to provide evidence towards answering how current and potential birth rate trends could change public school enrollment by 2060. This paper uses secondary data analysis, sources from the Center of Disease and Control (CDC) and United States Census Data, compiled and organized by the Integrated Public Use Microdata Series (IPUMS). The data used from the CDC is out of the National Vital Statistics System (NVSS) which is collected through birth and death certificates of infants. Potential confounding is presented when considering not all data is complete or accurate due to changes made to legal records after the data is collected. The data used from the U.S. Census is collected from the American Community Survey (ACS), an annually conducted demographic survey which uses random sampling. Non-response sampling bias is addressed through offering multiple methods of conducting the survey (phone, mail-in, or a Census Bureau representative visit), imposing fines for non-response, and data weighting to correct the non-response bias. Since the ACS uses sampling, it still is subject to sampling bias, a factor important to note for when we manipulate data. We will use scenario-probability analysis to forecast the different outcomes of birth rate trends and subsequent school enrollment rates, demonstrating the effect of of these outcomes by estimating the human impact: the number of school closures, school district closures, and approximate change in school density (ie. how much larger would a school zone be?). Through this paper, I hope to inform policymakers and school districts of the potential scenarios, whether negative or positive, that could result from enrollment patterns.

Computing Education, Human-Computer Interaction, Psychology

Based on the current trajectory of birth rates and potential events affecting birth rates, how will public school enrollment in the United States change by 2060?

The cost of living in Silicon Valley, California, has risen steadily over the past decade, seemingly while enrollment in public schools and birth rates in the area have been dropping. While analyzing how the change in the cost of living in Silicon Valley affects the economic growth of the area, a few assumptions must be asserted: The inverse relationship between the cost of living and birth rates, and the correlation between birth rates and enrollment in public school, and the direct relationship between birth rates and school enrollment with the economic growth of an area. While causation does not equal correlation, there are multiple pathways through which the increasing cost of living could impact economic growth, two of which will be analyzed in the following paper: 1. The rising cost of living causes more residents to have to move out and fewer residents wanting to move in, and consequently declining birth rates and school enrollment. This causes smaller school budgets and more school closures, then consequently the property value of the area decreases, and diminishes the attraction to live in the area. 2. The rising cost of living still causes residents to have to move out and fewer residents to want to move in, and the decline in school enrollment and consequent school budgets and closers cause the quality of schooling and education to go down. In the long run, this would cause more of the population to be less educated, negatively impacting the aggregate income, and consequently economic growth.

Economics, Statistics, Data Science, Natural Language Processing, Labor Economics, Industrial Organization, Antitrust, Economics of Education,  AI/ML, Text Analysis, Macroeconomics

How did the change in the cost of living in Silicon Valley, California in the past decade affect the economic growth of the area?

This project will compile various metadata on Covid 19 to explain what governs Covid 19 deaths. We will look at data from various Covid patients with different disease outcomes and perform a clustering analysis to determine which particular factors contribute to Covid in different regions in the US. We will look at both rural and urban parts of the US and see if covid outcomes cluster based on region, diet, weight, preexisting health conditions and so forth. Based on the results, we will suggest what measures people can potentially take to minimize Covid disease outcomes. 

Microbial genetics | Microbial genomics | Computational biology| Microbial role in human health and disease | Genetic engineering | Molecular and Cellular biology

Analysis of Covid metadata

Aziza is still picking between two topics: 1) The first case of COVID-19, the novel disease caused by retrovirus SARS-Cov-2, was reported in Wuhan, China in November 2019. Since the first outbreak of coronavirus, 6.33 million people have been recorded to date. The fast rate of new COVID-19 occurrences and accompanying mortality have sparked significant worries around the globe. Early detection of viral infection certainly enables rapid intervention, illness management, and significant limitation of the disease's fast spread. Additionally, we showcase cutting-edge CRISPR-based COVID-19 diagnostic and therapeutic technologies. Due to the requirement for advanced laboratory equipment and qualified staff, the widely used diagnostic technology, RT-qPCR, is only available in centralized laboratories. There is also relatively high chance of results turning out to be false negative or uncertain. Utilizing CRISPR-Cas systems, novel techniques for pathogen diagnostics and nucleic acid detection have recently been created. These techniques offer quick, affordable diagnostic platforms with excellent sensitivity and specificity without the use of intricate gear. It is conceivable to expand the number of daily tests performed in current laboratories and lower the rates of false negative or uncertain results obtained with RT-qPCR by using CRISPR-based SARS-CoV-2 detection technologies. It enables SARS-Cov-2 testing in resource-constrained environments or in emergency situations when RT-qPCR is not practical. This study will also discuss the benefits and drawbacks of utilizing CRISPR-Cas9 for the diagnosis and treatment of SARS-Cos-2. 2) With the advent of CRISPR-Cas9 technology, many opportunities have opened up in the field of genetic engineering, including genetic drives. The development of driving systems that can both propagate through communities to have the desired influence and be recalled in the case of unintended repercussions or public unfavor is necessary. CRISPR-based gene-drive elements would offer novel approaches to tackle ecological issues by modifying the features of wild creatures if they could spread in wild populations, however the possibility of uncontrolled spread greatly complicates their ethical development and usage. This paper  describse a self-exhausting CRISPR-based drive system made up of genetic components connected in a daisy chain, with each component driving the one before it. The ability of "daisy-drive" systems to spread is constrained by the continued loss of non-driving parts from one end of the chain. Daisy-drive systems may locally replicate any impact possible by utilizing an equivalent self-propagating drive mechanism. A valuable genetic factor can be almost fixed locally for a variety of organisms by releasing daisy-drive organisms, which make up a small portion of the local wild population. This paper will also adress ethical issues that might arise if technologies that limit the duration time of gene drives will be not applied. 

Genomics, CRISPR-gene editing, genome architecture, social justice in STEM, Art in STEM, creative writing (poetry/short stories)

Aziza is still picking between two topics: 1) CRISPR-Cas9 systems: the recent approach for diagnostics and therapeutics of COVID-19 disease. 2) Possible use of daisy chain gene drives to address the ethical problems of using gene drives.

This project is a review article about the overall evolution of schizophrenia. In my research, I reviewed literature about schizophrenia as a whole as well as its portrayal in the media, the various symptoms, and the medical diagnoses over time. While reading through this literature, I observed achievements in the medical field in treating schizophrenia as well the changes in society's viewpoint of schizophrenia and mental health as a whole. I found historical portrayals of mental illnesses similar to schizophrenia through classic literature, historical accounts, and experiments conducted by medical professionals. I also explored the idea of stigmatization of mental illnesses and how over time, the creation of outlets like social media has impacted the public's perspective on such illnesses as well as the ways it can help fix this issue through accurately educating those who misunderstand the importance of mental health. Along with these ideas, I looked into new studies that could potentially change the medical standpoint of the treatment of mentally ill people as well as ways to avoid developing such ailments by reaching out to medical professionals for help. The observations made by medical professionals using MRI and PET scans in the brain were also part of my research as they helped showcase the neurological changes that occur due to the development of schizophrenia and similar mental conditions. Through this combination of physical as well as emotional accounts, I was able to map the overall evolution of schizophrenia from its first historical account to its portrayal in today's society.

Neuroscience, data science

Schizophrenia in Modern Times

Biomechanical errors in running form have increasingly been linked to the development of musculoskeletal injuries, precluding runners from the physical and mental benefits of long-distance running. Existing works on biomechanical analysis of running form utilize expensive equipment and focus on understanding injury causes instead of predicting injury risk. In this paper, we present a novel dataset and three deep learning models for video analysis of running biomechanics using 2-dimensional pose estimation. Our approach predicts scores corresponding to the severity of injurious biomechanical errors, enabling runners to improve their form based on these predictions. We collect training examples through web-scraping and supplemental recordings, to which we apply BlazePose, a pre-trained pose estimation model, to obtain spatiotemporal data series. We explore three deep learning models for time series analysis, of which a Residual Neural Network (which we term gAIt) performs best, and all models achieve greater accuracy than baseline K-Nearest Neighbors with Dynamic Time Warping. Our gAIt model and future work with this dataset may provide recreational runners with an accessible and accurate tool to improve their running form in order to stay injury-free.

Machine Learning/AI, Neural Architecture Search and Design, Image / Signal Processing, Computer Graphics

gAIt: Deep Learning Based Evaluation of Injurious RunningBiomechanics Using 2-Dimensional Pose Estimation

Type 2 diabetes and stroke are some of the most common illness-related causes of deaths in America. Type 2 diabetes, because it is caused by insulin tolerance, can increase blood sugar and cholesterol levels, leading to increasing build up of foam cells and plaque in the arteries, which causes endothelial damage. Type 2 diabetes is very debilitating with many of the treatments just slowing down the process rather than curing the disease. Unfortunately, it is also one of the most common illnesses in America, with almost half of all senior citizens suffering from it. Because of the nature of the sickness, it can place many people at increased risk of other illnesses, one of the main ones being stroke. A stroke is caused by the blockage of a cerebral artery due to endothelial damage. It is one of the most fatal conditions, usually causing death or paralysis, even with the boost of modern technology. While working on cures for stroke is essential, it is also very important to understand how they can be prevented, especially for people who are already at risk because of conditions like diabetes. Certain treatments for diabetes, such as SGLT2 inhibitors as well as PCSK9 inhibitors, are able to prevent macrovascular diseases, like strokes, which makes them unique compared to other diabetes medications. My goal is to understand why these therapies can help with stroke prevention as well as how they can be modified to help patients who have had prior ischemic incidents to both improve neurological recovery and reduce the risk of subsequent ischemic episodes.

Neuroscience, Neuroanatomy, Microbiology, Cellular Biology, Genetics and Genomics, Cancer Biology, Medicine

The Effects of Diabetes on Patients with Stroke

Before Roe v. Wade, women would resort to unsafe practices to terminate their pregnancy; as a result, this soon became illegal, causing distress for women with unwanted pregnancies. 
To begin with, Jane Roe sued Texas district attorney Henry Wade in 1970, arguing that the state's abortion legislation violated the First, Fifth, Fourth, Ninth, and Fourteenth Amendments and was unconstitutional. When the court overturned Roe, it gave the states the ultimate decision on whether abortion should be banned. Some states made it harder for women to access an abortion within a specific time range because of cultural and religious ideals. Religion, especially Christianity, seemed to overpower the court and influence legislators while making such decisions For example, the Supreme Court has six conservative justices: four, are conservative Christian white men, one Christian African American man, and one white conservative Christian woman. CNN states that Conservative Supreme Court justices have indicated they are willing to overturn abortion rights. Many Christians believe having an abortion would be immoral because they think life begins at conception and goes against God's teachings. With these restrictions implemented by the government, many women and children face repercussions such as life-threatening risks, racial stigmatization, and limited information about sex education. In conclusion, there must be a supreme court system that acknowledges the effects of bodily autonomy restrictions and more financial support for women's clinics, planned parenthood, and other fundraisers.

Health law and policy; general law; mental health law and psychology; bioethics and the practice of medicine; clinical research ethics; health disparities; public health; ethics of using new biotechnologies such as CRISPR and use of AI in medical care; the history of eugenics; creative writing; novel, chapter book and picture book writing.

The logistical breakdown of Abortion restrictions and their impact on women’s bodily autonomy rights.

Recently, several highly globalized countries have experienced electoral victories for anti-globalization candidates and parties. Studies find that globalization creates distinct patterns of political behavior in winners and losers caused by different types of voter participation. Technological progress has made prosperity for humankind, yet it has always created winners and losers in the labor market. Groups in the labor market that have lost to technological change are more likely to opt for radical political change. This paper examines the effects of the economy, demography, and globalization on political behavior and voting patterns while looking specifically at the robust evidence in the 2016 US election cycle.

Economics, Macroeconomics, Finance, Business, Economic Policy, Applied Math, Statistics, Econometrics, Data Analysis, Algorithms, Optimization

How do job losses and demographic/cultural change due to automation and globalization affect political behavior and voting patterns in the U.S.?

Face detection is a growing field of image recognition research with applications ranging from security to biometrics. It is especially useful for the concept of “tagging” people in photos, which can make searching for said person more streamlined. In this project, the two problems that I am trying to solve are to create a network that detects one or more faces from an image and then trying to correctly label these faces if they are playing in the NBA. This project is both interesting and challenging because it involves detecting a single person from our database from images that often contain multiple people. To overcome this challenge, Ishaan will use neural networks with various convolutional architectures.

Data Science, Machine Learning, Data Engineering, Analytics, Electroencephalography (neuroscience)

Detecting NBA players from images

At this point in time, the amount of carbon (C) produced by humans every year is higher than it has ever been. There are two main solutions to fix this problem: reduce the amount of C produced and remove some of it directly from the air. The methods for removing C from the air involve new developments in technology, both industrial and agricultural. Along with these advancements comes the question, which one is more efficient at removing C? The efficiency of these methods could be defined in many ways, including the amount of C captured or the cost per amount of C captured. I am going to focus on the amount of C captured in general, as the importance of the cost differs from company to company and nation to nation. To discover the more effective method, I will use a combination of data from sources including the National Energy Technology Laboratory’s Carbon Capture and Storage (CCS) Interactive Database and others that support both the industrial and technological side of carbon capture technology (CCT). With the data from these sites, using the R computing environment, I will compile a dataset that supports the more efficient and effective form of CCT. In the end, I expect the industrial methods will be more efficient as they are faster and more easily mass produced than agricultural methods. Distinguishing the difference in efficiency between these two methods is important because the severity of the situation requires a quick, effective solution and while using both methods at the same time does work, it would be better to focus on the more efficient solution.


Biogeochemistry, geology, environmental science, microbiology, marine biology, ecology, plant ecology, ecosystems ecology

Which form of CCT, natural or industrial, is the most sustainable way of reducing Carbon in the air at an efficient rate?

Over the years, the incidence of Type 2 diabetes has increased in the Asian population. Suspected causes include a rapid change of lifestyle including daily habits and diets in the context of urbanization. Additionally, Asians have a high prevalence of the “Normal Weight Metabotically obese” phenotype in comparison to Caucasians and other ethnicities. This study looks to analyze the current body of research and present recent findings in an approachable platform for the general population.

Medicine, Biomedical Engineering, Nanoparticles, Drug Delivery Systems

Why is it that South and East Asian populations have a higher incidence of type 2 diabetes?

Rheumatoid arthritis is a widespread disease that affects millions of people worldwide. Recent research has pinpointed diet and its impact on the gut microbiome as being a major player in the development of the disease. This project will focus on creating a review article that summarizes the field, what researchers are focused on, and what potential therapeutics will be used to treat the disease.

Meet Polygence Scholars and explore their projects