bluuebunny/crossref_metadata_2025 huggingface dataset:
Stem cells in cardiac diseases
Authors: Huang Yadan , Yang Jinglin
Published: March 2023

Heart diseases is one of the most common diseases that people are facing currently, including coronary artery disease, arrhythmia, cardiomyopathy, and heart failure. Heart disease is responsible for most of the death globally, causing about 1 in 4 deaths, since heart is one of most important organs in organisms. There already have been several ways dealing with the heart diseases, such as medical treatment, operations, regulation in daily diet, coronary artery bypass graft, heart transplantation and so on. A entirely new approach, which is called stem cell therapy tßechnique was also developed and gradually introduced to the public. Stem cells are able to differentiate into the different type of cells needed for the treatment. Whenever the therapies take place or what ever the organs needed, stem cells can always fulfill the requirement. As an always-new material, stem cells have broad prospects since it can help figure out some diseases that have no treatment now as it provides a entirely new approach of thinking.
Effect of Pranayama Yoga Breathing Exercises on High School Swimmers
Authors: Gunin Adrika , Lohman Matthew , Gormley Jenny
Published: March 2023

The overall purpose of this study was to determine the effect of regular pranayama yoga breathing on high school swimmers. This study used experimental and survey research methods to collect the data and answer the research question. Experimental data was collected before and after the intervention group went through five weeks of pranayama yoga breathing. Survey data was also collected before and after the intervention. The data collected in this study showed that pranayama yoga breathing is useful in decreasing high school swimmers' race time because the intervention group had a 10.07% decrease, while the control group only had a 6.97% decrease. After analyzing these results, it was concluded that the hypothesis was correct in claiming that regular pranayama yoga breathing would have a positive effect on high school swimmers' race times.
Testing a Choline Diet in Neuroligin-Deficient C. elegans to Reduce Repetitive Behavior in Autism
Authors: Balasingam Sasha , Messenger Cathy
Published: March 2023

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by  obsessive adherence to repetitive motion and behavior. Previously my research tested whether neuroligin, a brain molecule and potential determinant of behavioral traits in autism, could be used in neuroligin-deficient C.elegans (strain NLG-1) to model autism. The experiment studied the sensitivity of neuroligin-deficient C. elegan to sensory stimuli, a core symptom of autism, and the results led to the conclusion that NLG-1 C. elegans could be used as a potential model for autism in worms. This project is a continuation study from last year that tested whether choline supplementation reduced repetitive locomotion in neuroligin-deficient C. elegans. Since people with neurological disorders are often deficient in the neurotransmitter acetylcholine, it was hypothesized that increasing the amount of choline, a building block of acetylcholine, would reduce repetitive behaviors. The C. elegans were age-synched to test three different age groups of worms, and over a 1-minute period, and the repetitive movement of the worms exposed to choline was compared to worms without choline using microscope camera software. The results showed the addition of choline in the diet significantly reduced the amount of repetitive locomotion in NLG-1 C. elegans in all 3 age groups. This study suggests that for people with ASD, adding choline to the diet in their daily schedule may help them reduce repetitive behavior. On a larger scale, scientists can use NLG-1 C. elegans to target neurochemical systems to develop early treatments, and ultimately reduce the significant deficits of autism.
Creating the Perfect Final Tribal – An Analysis of Survivor’s 5 Unanimous Winners
Authors: Carneiro Fernanda
Published: March 2023

A show that has maintained popularity over two decades, Survivor essentially represents a microchasm of society through its social dynamics. This paper analyzes the five unanimous winners of the show to determine what characteristics make a unanimous Sole Survivor. The unanimous winners were chosen for analysis due to it being such a rare occurrence in a show that has lasted over forty seasons. The study was a content analysis of the five Survivor seasons with unanimous winners, with qualitative and quantitative components that analyzed the winners as well as season-specific factors, as well as a winner comparison through the use of a quantitative frequency scale created to analyze traits of various unanimous and not unanimous Survivor winners. Results illustrate the necessity for further research into gender roles and bias on Survivor. However, this study developed a new understanding about shared characteristics among all unanimous winners of the show and gave a deeper understanding on common characteristics among unanimous winners and some not unanimous winners of the show.
How efficient is Machine Learning in detecting financial fraud using mobile transaction metadata?
Authors: Shah Vedant
Published: March 2023

Global data has shown that each day the number of fraudulent transactions is exponentially increasing.  As digital fraud continues to increase, machine learning and AI are being used to curb this increase. This paper will focus on the development and analysis of a machine learning model used to detect financial fraud in mobile money transactions.  The aim of this paper is to discuss how effective a machine learning model can be in detecting fraud. This algorithm makes use of the Naïve Bayes model to detect fraud. To prove this, the results have been provided by using a confusion matrix, precision and recall which indicate the effectiveness of the model. The accuracy of the developed model is 0.996 with a precision and recall of both above 0.99. This work explores and develops a solution to one of the biggest breaches in digital security.
A Qualitative Content Analysis of Colorism in Black Sitcoms
Authors: Dunlap Danae , Park Soo
Published: March 2023

This paper examines colorism in twenty Black American sitcoms ranging from the 1960s until the 2010s. Although previous researchers have looked at how colorism has presented itself in various forms of mainstream and Black media, not many have looked at the Black sitcom genre as a whole. Through the use of qualitative content analysis, this research suggests that Black American sitcoms tend to spread colorist messages in how characters are portrayed in the areas of romance, aggressiveness, criminality, and class status. Under the cultivation analysis theory, this research argues that because of this Black sitcoms have been used as a tool to spread colorist messages which plays a part in real world discrimination typically felt by darker skinned Black people. This study could be used by both audiences and content makers to acknowledge and fight against the biases present within previous and future forms of media.
Machine Learning in Alzheimer’s Disease: Prognostic Prediction via Neuroimaging and Numerical Data
Authors: Phetchrungruengphol Ydathip , Thanitkul Phasit , Arunkunarax Chavakorn , Wongtharua Thanapol , Sumpunwetchakul Kunapas , Kongsirirungruang Jetnipat , Janavatara Niracha , Sittisirinukul Witawin , Kanchana-art Chutikarn , Krutdumrongchai Pingpan , Praditphonlert Tansiri , Pitayakornpakdee Kanokkorn
Published: March 2023

Alzheimer's disease (AD) is often detected too late or inaccurately in clinical practice. Therefore, improvement in the current methods of AD detection will provide opportunities for early intervention, symptomatic treatment, and, overall, better quality of patients’ and their caregivers’ lives. The paper is an in-depth study of how functional brain imaging and support vector machine (SVM) could be utilized to detect the risk for AD which works by assessing and plotting data into multi-dimensional graphs for various results. It aims to identify patients in presymptomatic stages for early treatment to delay or prevent progressive cognitive decline and disease. With knowledge of machine learning, our medical tool is a breakthrough in the methodology of AD detection. The future of our tool requires a substantive amount of brain scan data for the machine learning algorithm to produce reliable results, so further research in this field of study is crucial and strongly encouraged.
Saving Sexuality From Stigma: A Perception Study On LGBT Bullying In Korean International Schools
Authors: Kim Grace , Stallings Bethany
Published: March 2023

Teens who identify as lesbian, gay, bisexual, or transgender (LGBT) often experience bullying and are at increased risk of suffering from mental health issues. Research, especially in the West, has shown that such bullying can decline if schools actively implement programs that raise awareness and educate students to promote a safer and more tolerant environment. However, in South Korea, schools currently either lack such programs or have ineffective programs. On the other hand, International Schools in Korea (ISK), which enroll more diverse students and teach western curricula, seem more liberal about LGBT issues, and tolerant towards such individuals. However, the fact that many ISK are affiliated with Christianity, and that Christian tenets are not entirely amicable towards LGBT individuals, raises an intriguing question: Despite Christian beliefs about LGBT individuals and the conservative attitude of Korea, have ISK actually created a culture that reflect the schools’ stated policies of tolerance and inclusivity, or is there a disparity of opinions between LGBT students and staff that needs to be addressed? In order to find an answer, I conducted anonymous surveys and interviews with both students and staff from six different ISK. The results show that the opinions of the LGBT students differ in both experience and perception from those of the staff and non-LGBT students, but are similar to those of non–LGBT students. Ultimately, by analyzing data from my study, I determined perceptions on LGBT in ISK and proposed necessary plans of action to increase support of LGBT in these communities.
The Artificial Synthesis of Raphide
Authors: Matsushima Shoki , Morimoto Yuko
Published: March 2023

Have you ever had an itchy mouth after eating yam? This is because the calcium oxalate needle shaped crystals, known as raphide, is contained in the plant that irritate the skin. raphide has been studied in various fields such as medicine and agriculture because of their characteristic effects. Although previous studies have reported useful effects, no successful artificial synthesis of raphide crystals has yet been reported. Therefore, I researched for factors that affect the synthesis of raphide. First, I conducted targeted experiments on drop rate, rotation speed, and concentration. As a result, it was found that the drop rate and rotation speed are factors that change the crystal structure. When these crystals were analyzed by X-ray crystallography, it was confirmed that they were calcium oxalate crystals. However, they were not raphide, so I attempted to synthesize them using a catalyst. For the catalyst, I decided to use the cell fluid part of aloe vera and an aqueous solution of amino acids. When the synthesized crystals were observed under a microscope, there were few raphide could be seen. Furthermore, since the extracted crystals may be the catalytic amino acid, ninhydrin reaction was performed on the filtrate and crystals, and no reaction was observed in both. Since it reacted in the solution before the experiment, I can say that it is calcium oxalate crystal. Therefore, it can be said that the synthesis of raphide was successful and the purpose of the research was achieved.
The Attenuation of Alcohol and Nicotine Induced Behaviors in Drosophila melanogaster by Sinomenine
Authors: Federici Jacob
Published: March 2023

The purpose of this experiment is to determine the efficacy of Sinomenine, an opioid receptor antagonist, in attenuating ethanol and nicotine induced behaviors in Drosophila melanogaster. While ethanol and nicotine are quite different in their direct mechanism of action, current research suggests that opiate reward, CREB-mediated transcription, and long-term potentiation are common pathways implicated in the development of various addictions. Due to its ability to antagonize the mu-opioid receptor, Sinomenine prevents endorphin binding, drug-induced CREB transcription, and consequent increase in dopamine production by tyrosine hydroxylase that leads to euphoria and addiction. Sinomenine may be particularly promising over other opioid receptor antagonists for sedative addictions due to its opioid-receptor independent anxiolytic effects.  In a CAFE assay performed to measure preference through consumption of ethanol or nicotine, Sinomenine reverses both naive and conditioned preference for ethanol, as well as conditioned nicotine aversion. Measuring locomotion, Sinomenine attenuated both the ethanol and nicotine induced decreases in negative geotaxis exhibition in Drosophila melanogaster. Quantifying olfactory preference, Sinomenine reversed conditioned odor preference in a Y-maze, but not naive preference. Reflecting its effects on the CREB pathway, Sinomenine inhibited a nicotine-induced increase in cAMP, but did not significantly affect cAMP levels in ethanol treated Drosophila. According to these results, Sinomenine is particularly effective in attenuating conditioned ethanol or nicotine-induced behavior, and produces mixed results in terms of naive exposure. The natural chemosensory preferences or aversion of ethanol and nicotine may be independent of the CREB pathway, while developed preference may be directly dependent on it.
Effective Methods for Mitigating Maternal Mortality in Developing Countries
Authors: Ayaz Lamia
Published: March 2023

Ninety-nine percent of maternal mortality occurs in developing countries; this is a global crisis, yet efforts to improve mortality rates in the short term have been largely uncoordinated and dispersed (Latt et al., 2019). Two promising options to reduce maternal mortality are improving access to contraception and distributing misoprostol, but to maximize investment potential the better method must be identified. This study examined the idea that increasing contraceptive access is the better short-term method to reduce maternal mortality in developing countries. The analysis centered on three studies on the effects of misoprostol and a single scoping projection on the effect of contraceptive distribution. The first study found that in transitioning from no misoprostol coverage to high misoprostol coverage, there could be a 25.49% reduction in maternal mortality. By contrast, a second study found that distributing misoprostol increased risk of maternal mortality because of increased hyperpyrexia, or elevated body temperature (Prata et al., 2014; Hofymeyr et al., 2013). A third study reported that misoprostol is unlikely to be misused and does not affect facility delivery rates (Tiruneh et al., 2019). By satisfying unmet need for contraception, there could be a 29% reduction globally in maternal mortality (Ahmed et al., 2012). Because there are limited studies available, it is difficult to draw a conclusion over which method is most effective. Based on current data, contraception distribution appears to be slightly more effective, but further research into both methods is necessary to guide resource distribution.
Disruptive Innovations and Deep Market Penetration with Respect to Timing
Authors: Tiku Sarvesh
Published: March 2023

This research analyses the impact of ‘timing’ on the success of disruptive technologies and deep market penetration. The essential components to view a firm as a disruptive innovation, as well as aspects associated with it, are the main subjects of this study. This paper also includes the definition of the term 'timing'; in relation to disruptive innovations. This study focuses on such examples of disruptive innovations in distinct markets: 1) Tesla and 2) Urban Company. Both of these will serve as a depiction of the real-life situations on how ‘timing’ aided them in breaking into their respective sectors. Finally, the research examines the many underlying variables that aided each disruptive company's establishment.
Applying adversarial networks to increase the data efficiency and reliability of Self-Driving Cars
Authors: Kumar Aakash , Kim Joe
Published: March 2023

Convolutional Neural Networks (CNNs) are vulnerable to misclassifying images when small perturbations are present. With the increasing prevalence of CNNs in self-driving cars, it is vital to ensure these algorithms are robust to prevent collisions from occurring due to failure in recognizing a situation. In the Adversarial Self-Driving framework, a Generative Adversarial Network is implemented to generate realistic perturbations in an image that cause a classifier CNN to misclassify data. This perturbed data is then used to train the classifier CNN further. The Adversarial Self-driving framework is applied to an image classification algorithm to improve the classification accuracy on perturbed images and is later applied to train a self-driving car to drive in a simulation. A small-scale self-driving car is also built to drive around a track and classify signs. The Adversarial Self-driving framework produces perturbed images through learning a dataset, as a result removing the need to train on significant amounts of data.  Experiments demonstrate that the Adversarial Self-Driving framework identifies situations where CNNs are vulnerable to perturbations and generates new examples of these situations for the CNN to train on. The additional data generated by the Adversarial Self-driving framework provides sufficient data for the CNN to generalize to the environment. Therefore, it is a viable tool to increase the resilience of CNNs to perturbations. Particularly, in the real-world self-driving car, the application of the Adversarial Self-Driving framework resulted in an 18 % increase in accuracy, and the simulated self-driving model had no collisions in 30 minutes of driving.
Lucas-Kanade Optical Flow Machine Learning Implementations
Authors: Gaur Vedant
Published: March 2023

Optical flow is an effective measurement to gauge motion in a scene, which allows for the computation of pixel-by-pixel motion in a frame pair. This paper aims to address the ambiguity with determining how to gain optical flow results for a given sequence. Due to varying speeds and nuances of a sequence, where it’s set, how fast it’s moving, a different amount of blur radius, i.e., the extent to which the image is blurred, may have to be applied to gain realistic flow maps. Furthermore, this paper touches on the many variables that can impact the efficacy of the flow outputted by an optical flow algorithm. Thus, we aim to determine whether the composition of results obtained through different blur values provides for more ground-truth flow outputs.
Galleria Mellonella as a model for drug screening of topical steroids against Malassezia Furfur
Authors: Subhash Aadhya , Farrar Cathy
Published: March 2023

The process of drug development is a long and laborious system where almost 90% of clinical drug trials end up failing. Therefore, drug screening in the preclinical stage is imperative to ensuring a higher success rate of the newly developed drug. One of the recently proposed model organisms for testing has been the larvae Galleria Mellonella mainly due to its technical and biological advantages. This study investigates the larvae as a potential model for specifically topical treatments against the fungal pathogen Malassezia Furfur. Using an application method, the larvae pre infected with M.Furfur showed recovery when treated with an antifungal topical treatment. Through this study the G.Mellonella has proven to be an effective model for topical drug testing to conduct an efficient and cost effective testing on a large scale for future pre clinical research.
Profitability and Polarization: TikTok's Dominance of the Attention Economy
Authors: Jain Aditya , Hussenet Allison
Published: March 2023

With increased access to technology, our dependency on Internet platforms for information has increased. The COVID-19 pandemic-related lockdown measures, such as stay-at-home orders and quarantines, seem to have accelerated the natural drift towards greater technological usage. One Internet platform that individuals use to consume online content is TikTok, a rapidly growing entertainment source that uses algorithms to curate and prioritize user preferences. Increasing technological dependence, however, may be tied to rising concerns about polarization associated with online content. This research explores if and in what way users perceive that Tikok benefits from polarizing content in terms of increasing user engagement and profits. This study of high school TikTok users found that these consumers believe engagement and profits thrive because of the algorithm’s increased frequency of displaying divisive content to active users, increasing their use of TikTok.
Alternative Treatment Options to Levodopa and Carbidopa for Parkinson’s Disease Patients
Authors: Kwon Destany , Wang Jing , Sharbaugh Janine
Published: March 2023

The most commonly used treatment for Parkinson’s Disease (PD) is levodopa used in conjunction with carbidopa. Despite being able to alleviate the motor symptoms of PD, it is unable to slow down the progression of the disease or give neuroprotective effects. There is no effective cure for PD or any treatment that is able to prevent the advancement of Parkinson’s pathology. The purpose of this research was to examine different combinations of treatments and medications that provide best results for patients and investigate novel research that is conducted in order to target the causes of PD, rather than its effects and symptoms. Interviews of doctors were conducted in order to determine the most commonly used treatments and what they have had success with when treating patients. The results revealed that levodopa still remains the most effective treatment, but its effects can be improved by adjunctive medications or therapies. Recent research also suggests that drugs that target other factors of PD pathology separate from dopaminergic neurons provide more neuroprotective effects and may be able to prevent the progression of the disease.
The Immediate Effects of Short-term Exercise on Diaphragmatic Breathing over Wind Instruments
Authors: Yu Lyn , Spigner Michelle
Published: March 2023

A strong diaphragm is critical to wind musicians because it helps produce a steady airstream needed for playing wind instruments. To strengthen the diaphragm, musicians use various methods. One method is exercise because it increases the breathing rate, forces the diaphragm to expand and contract, and allows for longer sustainment of breaths and greater endurance. This raises the question of whether exercise can affect the diaphragmatic breathing rate over wind instruments for wind musicians. The purpose of this research was to draw conclusions that could help rising and professional musicians improve their endurance through alternative means. The initial hypothesis was that as the duration of cardio exercise increases, there would be an increase in breath sustainment because the exercise would impel the diaphragm to expand and, subsequently, allow the lungs to fill to higher capacity. To determine this, human participants were gathered for three trials: no exercise, five minutes of exercise, and ten minutes of exercise. Each participant performed cardio exercises, after which they breathed into a breath builder. The amount of time they could sustain the ball in the air was measured as were the average times for each of the three groups of participants. The results of the ANOVA test demonstrated that F(2, 5.07) = 0.0081, p<0.05, indicating that the null hypothesis­­—that the mean durations of breath sustainment for the three trials were equivalent—could be rejected. The results demonstrated that exercise did not have the hypothesized immediate effect of increasing breath sustainment and diaphragmatic breathing.
How Experimental Reproducibility Affects Our Effort to Combat Climate Change
Authors: Baek Minjae , Kim Younmi
Published: March 2023

I present the comparison of CO2 adsorption data on ZIF-8 to show the differences in the data measured by different researchers. I used an isotherm model to fit the collected adsorption data using a simple Least Squares method using Microsoft Excel solver function. The model describes the adsorption data very well and the collected data show quite a large spread with outliers. The heat of adsorption calculated from the adsorption data also shows a very large spread. This level of spread in experimental data can lead to incorrect calculations when these data are used in large scale applications, such as gas separations or gas capture where adsorption is widely studied for uses. Through this work, I highlight the importance of producing reproducible experimental measurements that compare well with the data measured by other researchers.
Review of Chronic Kidney Disease and Comparison Between Humans, Dogs, and Cats
Authors: Hahn Layla , Callaband Celeste
Published: March 2023

The kidney is the body’s filter and when it is damaged, the body no longer functions the way it should. When enough damage has occurred to the kidney, the kidneys will slowly start to fail resulting in chronic kidney disease (CKD). There is no cure for CKD and it gets progressively worse over time. CKD affects a wide variety of animal species, including humans, dogs, and cats. We will be comparing CKD prevalence, symptoms, risk factors, and treatment modalities. There are many similarities in disease diagnosis, monitoring, and treatment between the species. There are also key differences in each species' physiology that results in different diagnostic and monitoring parameters as well as differences in the treatment options available. We compare CKD treatment options that include kidney transplantation, dialysis, hypertension, and nutrition. As part of the One Health movement, understanding these similarities and differences will help us better understand the disease process and hopefully improve treatment outcomes across species.
The Effects of Genetics and Psychosocial Stress on War-Affected Youth
Authors: Brinson Zaila
Published: March 2023

The atrocities of war have a negative impact on those who must witness them. Syrian refugees have gone to Jordan to escape the civil war in their home country. The genetics of the youngest among the refugees plays a role in the development of mental illnesses. The importance of studying the effect of psychosocial stress and genetics on war-affected youth can be seen today when many children are being uprooted from their homes in Ukraine. This study was done using a case-control study. To get DNA, a gender-balanced group of 417 Syrian refugees and 306 Jodanian non-refugees provided buccal samples to the researchers. The male participants were exposed to more traumatic events, but the female participants had higher rates of perceived stress, insecurity, depression and anxiety, and post-traumatic stress disorder symptoms. The serotonin transporter  5-HTTLPR and the protein-coding gene COMT were found to play a role in the response to trauma. 5-HTTLPR was found to be associated with human insecurity and perceived stress. COMT was found to be associated with CRIES-8, also known as PTSD. The results of this study can be used in many ways. They can be used to know which mental health resources should be allocated to those uprooted by wars and the results can be used to advance the study of human behavior.
How Acculturative Stress Impacts Vietnamese American (Aged 30-60) Access To Quality Treatment And The Healthcare System In St Mary’s County MD.
Authors: Vo Devon
Published: March 2023

Vietnamese Americans often face difficulties receiving quality care from the healthcare system due to acculturative barriers. These barriers can include misunderstanding of language, culture, and lack of social connections. These difficulties affect the health quality of Vietnamese Americans compared to other ethnicities in the U.S. Therefore, Vietnamese Americans were examined to see how the process of acculturation affected the Vietnamese community and its impact on access and quality of treatment from the healthcare system. Upon giving 26 Viet participants a survey many of them responded that they were satisfied with their care. However, cultural stigma played a huge role in dissuading them from accessing additional resources and participants cited language as a significant barrier. Overall, my project showed that Vietnamese Americans (ages 30-60) found their care satisfactory. Future work should investigate cultural stigma in order to get more Vietnamese Americans to access the medical care they need.
Analyzing Gender Differences in the FIRST® Robotics Challenge by FIRST® Robotics
Authors: Rajpal Ria , Sample Kate , Torraca Eileen
Published: March 2023

Technological innovation has grown over the years, so there has been a greater demand for the STEM workforce. Thus, many initiatives have been taken to meet this demand. One of these many initiatives is robotics. Over the years, many robotics leagues have been created, the most notable being FIRST Robotics and Vex Robotics. While these initiatives are implemented to bring change, marginalized groups like women have been known to be undermined in the activity. This paper aims to address this issue by studying gender differences, specifically in the FIRST Robotics Challenge (FRC) by FIRST robotics. The study was conducted through online surveys taken by participants of FRC that utilized both quantitative and qualitative data. This data was analyzed to discover how males felt about aspects of the activity versus females. This study finds that females have had a net negative experience within FIRST as they faced less encouragement, more discrimination, comments doubting ability, etc., compared to their male counterparts. With this understanding, more effort should be taken to retain and encourage the future involvement of females in robotics. Future research is needed to address this issue in other male-dominated activities to allow society to meet demands in the STEM workforce and provide equal opportunity to those entering the field.
The Role of Social Organizations in the Rescue of Abducted Women in China
Authors: Nie Xin , Pan Jintang
Published: March 2023

Gradual enhancement of the law system and modernization do not prevent human trafficking crime away from Chinese people’s lives. The considerably large buyer's market due to the imbalance of economic and cultural development, the difficulty of cross-regional criminal investigation, and the deficiencies of legislation related to human trafficking incentivize criminals to take risks for economic benefits. When discussing the ways to “activate” each link on the chain of the social system that eventually results in crimes, the role of social organizations, especially the Women’s Federation is often neglected. This paper will first focus on the empowerment of social organizations in the process of settling down victims and offering mental therapy and re-employment training. This part will also examine the challenges of empowerment and the potential solutions. The Women's Federation is at the front line of contact with women victims of abduction and has abundant information at its disposal; therefore, legal improvement and aid assistance are also what social organizations can provide. Then the paper will emphasize the approaches for social organizations to utilize their resources and connections to assist local governments, law institutions, and police officers in facilitating the work of preventing human trafficking. After investigating the specific functions social organizations can execute after rescuing the victims, the paper will highlight how they play a role in preventing crimes from taking place by educating the most vulnerable group of people. A combination of precaution and remediation measures is necessary and complementary in keeping people safe from human trafficking.
Can we rely on AI or Deep Learning to read or detect brain tumors using MRI scan and images?
Authors: Jindal Rayna
Published: March 2023

The brain is one of the complex and most significant organs in the human body. It controls every process that regulates our body and affects how we think, feel, act and is indispensable to living a happy and balanced life. Due to the current lifestyle, depression, stress, and anxiety have risen to an extreme, especially during COVID. Researchers have found that people with mental disorders are more prone to brain tumors and develop cancers early than people without mental illness. Therefore, it is worthwhile to invest time and research to improve our ability to diagnose brain tumor in early stage. This research aims to use the Deep Learning model to detect brain tumors. The dataset used for this research project is the Brain MRI segmentation dataset (LGG lower-grade gliomas) taken from The Cancer Imaging Archive (TCIA). This dataset is open source and available on Kaggle. Using the Keras library, I used the Convolutional Neural Network (CNN) for tumor detection to get concrete results. I got approximately a 90% accuracy which shows us it is very promising that Deep Learning can help with brain tumor predictions, thereby making the diagnosis easy, correct, and prompt, which allows early diagnosis and reduces the mortality rate.
How does the Italian High Renaissance Artist Raphael Sanzio connect the past, present, and future of the art community?
Authors: Xie Tianyi
Published: March 2023

The artist Raphael Sanzio is one of the most renowned artists in the history of art, praised of his ideal of perfection, beauty, and harmony that prompted the Italian High Renaissance to its very peak. Conventionally, investigation on Raphael’s influence as a master would center around his major art creations during the High Renaissance. This essay would also explore Raphael’s main achievements in the artistic sphere (including education, techniques, compositions, and aesthetic theories) and his social life during the High Renaissance as his present but would at the same time discuss the connection of his present to the past and future of the art community. In terms of the past during the Early Renaissance, this essay would elaborate on how past events of commercialization of economy triggers the dignified status of artists, compared to the status of craftsmen during the Middle Ages. Moreover, in terms of the future, this essay would depict Raphael’s influence and contribution to artistic movements surrounding the Academia and the modernists during the Early Modern period.
Eye as a window to the brain: Review of retinal changes in Alzheimer’s dementia
Authors: Sastry Dhruv , Keshavamurthy Ravi
Published: March 2023

Alzheimer's disease (AD) is the most common neurodegenerative disease causing significant morbidity and mortality in the elderly, affecting million worldwide. Diagnosis of AD is mainly by clinical symptoms, use of tests to detect loss of higher mental functions, and confirmed by neuroimaging studies such as magnetic resonance imaging and positron emission tomography. Current research in AD aims at early detection of pathological changes in the brain and development of disease-modifying drugs. Testing the effectiveness of these drugs requires the development of a noninvasive and cost-effective screening tool. Retinal changes in patients with AD mirror those found in the brain and offers a window for early detection of AD before cognitive changes set it. This article reviews the pathological correlation between retinal changes and AD and the current advances in retinal imaging to detect AD.
Social Entrepreneurs in the Pharmaceutical Industry: The Catalyst That Finally Drives Down Price?
Authors: Hsu Ryan
Published: March 2023

The cost of healthcare in the United States is notoriously expensive. In recent years, social enterprises and nonprofit organisations have begun flooding into the market to try and stem the rising costs. I perform a case study on two prominent social enterprises and analyse the challenges they’re facing and the implications of their work. I requested an interview from a key figure within each respective organisation to gain a better understanding of their perspective. The companies are at polar ends when it comes to company growth, with one being a startup company that is just beginning to grow into its name and the other an already well-established firm. I provide overviews on each respective firm and compare their challenges and company goals. A better understanding of the pharmaceutical market led to suggestions of potential solutions to the problem of high healthcare prices in the form of patent reform and negotiation committees.
Does U.S. Aid Improve Human Rights Conditions of Aid-Recipient Countries?
Authors: Choi Yoonjung , Park Seongkyu
Published: March 2023

This paper examines whether U.S. aid improves the human rights conditions in aid-recipient countries. Using the cross-sectional time series data for more than 100 countries from 2007 to 2018, the multivariate regression model shows a significant positive relationship between U.S. aid receipts and human rights improvement. When the U.S. increases its foreign aid amount over the recipient country's GDP by 1% point, the level of human rights conditions in aid-recipient countries subsequently improves by 0.5%. This paper contributes to the literature in three dimensions. First, it compares the annual change in U.S. aid and the subsequent annual change in human rights instead of the absolute amount of U.S. aid and the absolute level of human rights that are used in the literature. Second, it uses the Fragile States Index as a measure of human rights which reflects the human rights conditions more comprehensively than the measures used by literature. Third, it uses the actual disbursement amount of U.S. aid rather than the obligation amount used by the literature. This paper provides evidence that U.S. foreign aid enhances human rights conditions in aid-recipient countries which is the desired outcome.
A Prospective Treatment for Selective Mutism through an Analysis of Social Anxiety Disorder
Authors: Patel Riya , Kirk Lauren
Published: March 2023

Selective mutism (SM) is a rare pediatric anxiety disorder in which a child fails to speak in specific social situations. Due to its classification as a rare disorder that affects less than 1% of the world’s population, research on this disorder is limited, inhibiting available treatment options for SM patients. Thus, it is critical to research more on this relatively unexplored disorder. Social anxiety disorder (SAD) is a prevalent anxiety disorder characterized by the fear, self-consciousness, and embarrassment in social situations in which a person may be judged or evaluated negatively. SM is known to present with other anxiety disorders, primarily SAD. The main treatment for SM is cognitive-behavioral therapy (CBT), followed by pharmacological interventions such as selective serotonin reuptake inhibitors (SSRIs). With limited knowledge of this rare disorder, this paper attempts to suggest a potential novel treatment for SM, serotonin-norepinephrine reuptake inhibitors (SNRIs). SNRIs are a class of antidepressants used to increase both an individual’s serotonin and norepinephrine levels in the brain. Previous case studies of SM and research on these specific antidepressants used commonly to treat comorbid SAD elucidate the antidepressant’s potential on SM. With its strong usage in the treatment of SAD, SNRIs may also be effective as a treatment for SM, a disorder that has similar clinical presentations and therapeutic approaches to SAD. In conclusion, this review paper calls to attention the lack of research on SM and identifies a novel alternative approach for its effective treatment.
Brain, Memory, and Amnesia
Authors: Zhang Ryan , Andl Thomas
Published: March 2023

Amnesia is a large-scale and long-term memory loss. Complications of amnesia, including the inability to create new memories and learn new things, severely reduce the quality of an individual's life. In the last three centuries, many famous clinical studies, including the one involving Henry Molaison (H.M), have been completed, furthering our understanding of the brain’s memory system and amnesia. Especially, a variety of psychological and neurological causes of amnesia have been identified. Different treatments are available for different types of amnesia; however, due to the extensive causes of amnesia, finding a common cure has proven to be difficult. This review will focus on our current understanding of the memory system and history of amnesia as well as the types, causes, preventive measures, and potential treatment strategies of amnesia.
Predicting the Danger of Particulate Matter Pollution from Wildfires Using Classification Models
Authors: Lai William
Published: March 2023

Due to a mix of climate change and California’s mega-drought, California’s wildfire seasons have overall gotten progressively longer, more destructive, and more expensive. In 2020 alone, around 9,900 wildfires burned about 4.3 million acres, costing the state over $12 billion. (Kerlin, 2022) Larger and more numerous wildfires pollute billions of harmful particles into the atmosphere, including PM2.5. This study aims to use features of a wildfire and other factors to predict whether a wildfire pollutes enough PM2.5 particles to be detrimental to human health. The 8 features used in the model are the acres burned, the length in days of the fire, available green space within a 15-mile radius of the fire, the highest population density within a 15-mile radius of the fire, electricity usage, median income, temperature, and precipitation. A Gradient Boosting Classifier (GBC) was applied to the dataset to predict whether a wildfire’s emissions necessitated an evacuation. The GBC results achieved a high accuracy of 0.931 as well as a great Area Under the Curve (AUC) of 0.911. By far the most important feature in the GBC is Length, with a feature importance score of 0.109 +/- 0.009.
Analyzing the Use of 5XFAD Model Mice in Determining Late-Stage Alzheimer’s Disease Treatment
Authors: Mellacheruvu Anika , Bondoc Maria , Torraca Eileen
Published: March 2023

Nationally, Alzheimer’s Disease (AD) is growing in numbers across an elderly demographic. While treatments exist to mitigate degeneration, they usually are targeted towards early-stage Alzheimer’s and tend to neglect more severe stages of the disease. In these severe stages, beta-amyloid plaques and neurofibrillary tangles, two neurological indicators of AD, tend to aggregate more acutely than in previous stages. To help develop treatments, mouse models are utilized, typically. In order to test what type of model mouse could potentially be used to explore further treatment, the 5XFAD model mouse, one that produces an abundance of beta-amyloid plaques in its brain, was chosen. This paper intends to compare 5XFAD mice to the human brain in its severe stages of Alzheimer’s through a qualitative comparative analysis to juxtapose the neurological factors of both brains. It also utilizes interviews in order to compare severe AD patients and 5XFAD mice phenotypically, and in terms of their cognitive and behavioral deficits. The author finds that the 5XFAD model is very limited as a medium to discover new treatments, and can only be used to a certain extent. Due to AD being defined by both the aggregation of beta-amyloid plaques and neurofibrillary tangles, but only beta-amyloid plaques being present in 5XFAD mice brains, treatments that target the beta-amyloids in the brain can be discovered due to the highly-occurring similarities between the two, neurologically and behaviorally. However, a treatment that encompasses both contributing factors to Alzheimer’s Disease will not be able to be found.
Does the Stock Market Anticipate Economic Growth? Empirical Evidence Based on the U.S. Stock Market
Authors: Sreenivasan Vishnu , Kolli Harish , Sialm Clemens
Published: March 2023

It is essential to understand the relationship between stock market returns and economic growth. We investigate whether the stock market is a leading indicator, a lagging indicator, or it has no relation to economic growth. Identifying this can help households plan their investments for business cycle contractions and expansions, as well as provide legislators and federal government agencies with the information they could use to maximize the effectiveness of their policies. Through our research, we identified the relationship between stock market returns and the changes in the percentage of gross domestic product (GDP) growth in the prior and the year following the market returns. By running a regression analysis of GDP percent change on the prior-year S&P 500 annual return, we find a significance level of 0.00159, which is highly statistically significant. Therefore, we conclude that the stock market is a leading indicator of a recession, which further allows us to better understand how policymakers can make optimal decisions.
Examining Machine Learning Models That Predict sgRNA Cleavage Efficiencies
Authors: Kawle Krish , Kethar Jothsna , Appavu Rajagopal
Published: March 2023

Ever since its discovery, CRISPR-Cas9 has taken over the world in gene editing. By providing a single guide RNA to the cas9 enzyme, CRISPR-Cas9 can immediately pinpoint the target gene location in the genome and slice it. Scientists discovered a revolutionary way to use this method for gene editing. Yet, the challenge is that the CRISPR-Cas9 system is lenient with the matching precision of the guide RNA to the target sequence As a result, the CRISPR-cas9 system may also cleave certain healthy sequences that are almost identical to the target sequence. This paper aims to find the best model that uses machine learning to predict an optimal sgRNA design.
Effects of Sleep Deprivation and Early School Start Times on Adolescent Health
Authors: Toprak Teoman , Karan Maira
Published: March 2023

As sleep deprivation is a general public health issue reported by the Center for Disease Control, it becomes an even more detrimental problem in adolescent years with potential consequences of physical, mental, and academic impairments leading to chronic health issues such as obesity, metabolic dysfunction, and increased cardiovascular morbidity into adulthood. The reasons behind the epidemic of insufficient sleep during adolescence are complex and multifactorial which include the biological and central changes in sleep regulation in teenage years as well as early high school start times (SST) determined by state legislation and local school districts. This important public health issue of sleep loss in adolescents has led increased research and policy changes about the ideal SST. Studies have shown that later SSTs are associated with positive student outcomes, including improved academic performance, mental health, and physical health, along with increased public safety and long-term economic gains. In light of this scientific evidence, the average teenager is best suited to wake at 8:00 AM or later. In this review article, we aim to summarize the literature and raise awareness on long-term effects of insufficient sleep in teenagers, school start times (and its potential delay), as well as general health recommendations.