bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of Hypertension in Outpatients in East Java, Indonesia
Authors: Makhfudli  , Susanto Joko , Sairozi Ali , Ubudiyah Masunatul
Published: April 2023

Objective: To assess the prevalence of hypertension and to identify the causative factors.
Method: The cross- cross-sectional study was conducted at Dr Soegiri Hospital, Lamongan, Indonesia, from March to July 2019, and comprised outpatients of either gender. Data was collected using a modified World Health Organisation STEPwise approach to surveillance questionnaire to identify the risk factors for hypertension. Data were analysed using the SPSS 16.0 statistical tool and logistic regression test.
Results: Of the 184 subjects, 118(64.1%) were females and 66(35.9%) were males, and 96(52%) were aged <60 years. Overall, 120(65.2%) subjects were hypertensive; 80(66.7%) females and 40(33.3%) males. The two main factors that significantly influenced the incidence of hypertension were body mass index (p=0.001) and consumption of vegetables (p=0.013). After adjusting for confounding factors, only body mass index was found to affect the incidence of hypertension (odds ratio: 5.61; 95% confidence interval: 1.686-18.659).
Conclusion: Body mass index and and dietary patterns affected the incidence of hypertension. After adjusting for confounding factors, only the former was found to have significant association with hypertension.
Keywords: Blood pressure, Body mass, Hypertension, Feeding, Dietary.
Demographic characteristics with compliance on the implementation of health protocol on passenger ship
Authors: Asmoro Candra Panji , Prasetya Robby Bagus , Retno
Published: April 2023

Objective: To analyse the relationship of demographic characteristics with coronavirus disease-2019 protocol compliance among ship passengers.
Method: The descriptive, correlational, cross-sectional study was conducted in May 2022 at the harbour in East Java, Indonesia, after approval from the ethics review committee of Universitas Airlangga, Indonesia, and comprised individuals of either gender aged 18-65 years who had a passenger ship departure ticket and were able to communicate well in the Indonesian language. Data related to demographic characteristics and coronavirus disease-2019 standard protocol compliance. Data was analysed using SPSS 25.
Results: Of the 157 subjects, 71(45.2%) were males, 86(54.8%) were females, 68(43.3%) were aged 26-45 years, 79(50.2%) had studied up to the bachelor’s level,106(66.2%) were employees, 89(56.7%) had earnings below the provincial standard, and 116(73.9%) were married. Health protocol compliance at the harbour had a significant correlation with gender, age, education, occupation and income (p<0.05).
Conclusion: The factors related to the compliance of the coronavirus disease-2019 protocol at the harbour were gender, age, education, occupation and income.
Keywords: COVID-19, Mask, Marital, Ethnicity, Occupations.
The use of digital technology in health learning during the COVID-19 pandemic: a systematic review
Authors: Soares Domingos , Nursalam
Published: April 2023

Objective: To investigate reasons, advantages, disadvantages and obstacles in the use of digital technology media for health learning during the coronavirus disease-2019 pandemic.
Methods: The systematic review was conducted from January to February 2022 and comprised search on Google Scholar, ProQuest, PubMed, ScienceDirect and Scopus databases for articles published from 2020 to March 2022 related to the use of digital technology by medical students, teachers and academics. Key words used for the search included digital technology, health learning, health education, COVID-19, COVID-19 pandemic, and coronavirus disease 2019. Main themes were identified which were then grouped into components using Joanna Briggs Institute guidelines and tools.
Results: Of the 128 articles initially found, 10(7.8%) were subjected to detailed analysis. Reasons identified were lockdown and accessibility of flexible learning materials. Advantages were effective time, better effort, saving money, improving technical skills, health security, feasibility, e-learning standardising, dedicated teaching, interdisciplinary collaboration network, creativity, inclusivity and professional development. Disadvantages were inadequate tools, poor internet connection, lack of technical skills, practical in classes, unclear policies, examinations, distribution of grades and limited online exam time. Obstacles included virtual class etiquette disobedience, inadequate interactions, time limitations, infrastructure, distractions, lack of engagement, stress, technical and limited data plans.
Conclusion: Many universities used digital technology in health learning during the pandemic-led lockdowns as it provided greater advantages.
Keywords: COVID-19, Digital Technology, Pandemics, Communicable disease control.
Developing librarians’ teaching practice: a case study of learning advisors sharing their knowledge
Authors: Harding Rachael , McWilliams Robyn , Bingham Tricia
Published: April 2023

Increasingly, tertiary librarians are required to teach as part of their role. There is recognition that ongoing professional development (PD) is required in teaching and learning as this is not generally provided as part of formal library qualifications. Using an education design-based research approach, this collaboration aimed to enhance the teaching practice of liaison librarians to enable more consistent review, planning, and design of information literacy workshops. As part of a wider PD programme for liaison librarians at Auckland University of Technology (AUT), learning advisors developed and taught three workshops. The learning advisors were chosen by the library leadership due to their teaching expertise and adaptability. They provide embedded, academic literacy support for students tailored to specific assessment guidelines and marking criteria. The aim was to share examples of learner advisor practice underpinned by relevant theory and applied directly to an information literacy context. Liaison librarians were exposed to workshop strategies to develop appropriate learning outcomes, content, and pedagogical approaches for planning ongoing teaching. They had opportunities to assess and evaluate their current knowledge and skills and consider new approaches. These sessions enabled the team to go forward with shared knowledge to guide their workshop design to create more consistent, sustainable, and measurable content. Another outcome was the co-development of workshop design principles which have been applied to the redevelopment of workshops. As this process is replicable, the value of sharing knowledge and expertise between teams such as learning advisors and liaison librarians is worth exploring further.
Ready player one: using Vevox to elicit student participation in lectures
Authors: Greenwood Joe
Published: April 2023

With the pivot back to on-campus teaching, many students find themselves in an unfamiliar learning environment: the lecture theatre. This can result in low rates of participation in lectures, especially with a diverse student demographic, including English as an Additional Language students. This can result in exclusion from learning for these students, as well as many students feeling nervous about participating in a lecture format. This case study looked at using the education technology Vevox to elicit student participation in a lecture format. Vevox was used to embed multiple tasks into a series of lectures with a cohort of third-year Engineering students. Vevox was found to be effective at eliciting high levels of participation, although some tasks had higher participation rates than others. An evaluation survey was also conducted with students where they responded positively to the implementation of Vevox in the lectures. Finally, the case study discusses potential applications and limitations of Vevox, with a recommendation that similar research could be carried out across multiple courses and cohorts to improve efficacy.
Effectiveness of Nutrition Education and Fitness Tracking in a Large Healthcare Wellness Program
Authors: Tyrrell Jessica , Ogan Dana , Englund Timothy , Stendell-Hollis Nicole
Published: April 2023

Purpose: The purpose was to determine the effectiveness of a ten-month multicomponent employee corporate wellness program on two health-related outcomes: weight loss and step count.  
Design: Retrospective medical chart review.  
Setting: Wenatchee Valley Hospital/Clinics. 
Sample: Healthcare employees (n=1210) were evaluated; 74.2% of the initial population. 
Intervention: Employees were assigned to either the Healthy Track (HT) or Body Mass Index (BMI) track based on a Health Risk Visit. 
Measures: Employees in the HT had to achieve a certain step count, while those in the BMI track had to lose a certain number of pounds. 
Analysis: A variety of statistical analyses were performed including: crosstabulation, Chi-Square test, independent samples tests, Levene’s test, and linear regression.  
Results: Data showed that employees in the HT who participated in at least one campaign showed a decrease in BMI percentage (p=.000), with greater losses noted in those participating in the nutrition series (p= 0.03). Analysis showed that there was no relationship between the number of steps taken and decrease in BMI percentage for employees in either track (R2 =.000). 
Conclusion: Corporate wellness programs that offer web-based and in-person support can lead to modest reductions in BMI. This research offers recommendations on how to create a successful corporate wellness program. One noted limitation is that weight was only measured pre- and post-study.
Eve Reimagined: Milton’s Undoing of Misogynistic Traditions
Authors: Granowski Annalyse
Published: April 2023

How might John Milton’s depiction of Eve unintentionally reveal the uniquely feminine struggle for equality in a patriarchal power structure? In the epic poem Paradise Lost (1667), Milton “justifies the ways of God to men” by emphasizing the importance of obedience. However, Eve disregards Adam’s suggestion that they work together in Eden, and this separation results in her falling into temptation. Eve chooses to work independently because of her own desire, but is this decision a form of disobedience? Even though Paradise Lost establishes Eden to be a patriarchal structure, I believe that Eve’s decision might plausibly be interpreted as an attempt to gain equality. In this paper, I wish to claim that Milton attempted to minimize the assumption that Eve’s act was merely a selfish or impulsive one. Instead, he depicts his only female figure as a being who can equally make decisions just like the male figures in the Garden, and her independence allows her to attempt to escape a gendered hierarchy. Instead, the misogynistic environment of Eden may play a larger role than originally thought. While traditionally the interrogation of Eve in Judeo-Christian discourse has revolved around her act of disobedience against God, Milton shifts the narrative to focus on Eve’s interactions with Adam; with this modification, Milton creates the possibility for disrupting misogynistic traditions of interpreting Genesis.
Effects of Different Light Intensities on Growth and Fucoxanthin Concentration of Fistulifera solaris
Authors: Vafaei Naeini Zahra , McCallum Mindy , Ndathe Ruth
Published: April 2023

Biofuel production using algae is believed to have tremendous positive impacts on the environment, and it seems a promising solution for global warming. However, growing algae on a large scale requires many resources making mass production of biofuels not yet economically viable. In this study, an oleaginous diatom, Fistulifera solaris, was cultured in autotrophic conditions under four light intensities for 14 days to determine which conditions allowed for higher cellular growth and higher fucoxanthin concentration, a valuable photosynthetic pigment that can make the process of biofuel production affordable. As a measure of abundance, absorbance values of diatoms in 750 nm wavelength (OD 750) were obtained on days 0, 7, and 14. On day 14, fucoxanthin concentration was measured. Statistical analyses revealed a significant change in the growth of diatoms under the four treatments that may be explained by varying rates of reproduction of the diatoms grown under different light intensities. Specifically, the highest OD 750 and growth were observed in medium-high light intensity, while the highest fucoxanthin concentration was observed in low light intensity. It is suggested that diatoms grown in lower light intensities may be ideal for increased fucoxanthin concentration because the geranyl-geranyl diphosphate synthase (GGPPS) gene, which is responsible for encoding a fucoxanthin precursor, is downregulated in exposure to high light intensities. Considering this data, low light intensity leads to the highest fucoxanthin concentration, and medium-high light intensity leads to the highest OD 750 and maximum growth under autotrophic conditions.
The Effects of L1 Transfers on L2 English Intransitive Errors by Japanese Learners
Authors: Tazaki Yu
Published: April 2023

Second language (L2) learners of various native languages frequently overpassivize one type of intransitive verbs, namely, unaccusatives (e.g., disappeared, arrivedn). Previous studies have attempted to address the culprit of this issue without reaching a general consensus on the cause of such errors. This study investigates whether first language (L1) plays a role in L2 English overpassivization errors with intransitive verbs by Japanese-speaking learners. It utilizes the framework of the Unaccusative Trap Hypothesis (UTH, Oshita, 2001) and hypothesizes that learners ungrammatically passivize unaccusative verbs due to L1 lexicon and morphology. It also predicts that learners generate passive errors with unergatives (e.g., cry, smile) in the same manner as passive unaccusatives. The study examined three types of intransitives: English non-alternating/Japanese alternating unaccusatives (e.g., happen in English and okiru/okosu in Japanese); English/Japanese non-alternating unaccusatives (e.g., arrive in English and tuku in Japanese); unergatives. The study analyzed a Japanese learners’ corpus (JEFLL Corpus), consisting of approximately 70,000 words from Japanese junior high and high school students. The findings in this study are that Japanese EFL learners tend to passivize more English non-alternating/Japanese alternating unaccusatives and unergatives than English/Japanese non-alternating unaccusatives. Given the result, it can be suggested that Japanese learners passivize unaccusatives owing to the influence of their L1 lexicon and morphology.
How Inflation Has Impacted US Citizens Today
Authors: Tsai Tristan
Published: April 2023

The COVID-19 pandemic shut the world down and threw the global economy into a recession. Through stimulus checks and the gradual re-opening of the world, the economy recovered from the recession but flew into a period of increased inflation. Using data on inflation, unemployment, and certain factors such as household income and labor statistics, it is revealed that inflation weakens the labor force while having no clear impact on wealth classes. In addition, it is observed that the presence of COVID has not impacted the labor force or certain wealth classes by any sizable margin, and that the Phillips Curve, a graph depicting the relationship between inflation and unemployment, has been flattening throughout the last several decades.
Analyzing the Extent to which Gender Bias Exists in News Articles Using Natural Language Processing Techniques
Authors: Guda Nihita
Published: April 2023

Prior studies have shown the existence of gender bias in job postings, performance reviews, and letters of recommendation. However, very little research has been done on the presence of gender biases in mainstream news sources and how they vary across publications. Human editing, given the rapid pace of news dissemination, is not effective enough to address biases. Even computer programs that parse the news articles for specific words and references still fall short of identifying and detecting the undertones and implicit references, which is why sophisticated techniques like Artificial Intelligence (AI) are necessary.  In this study, I used Natural Language Processing (NLP) methods, a series of Python-programs to further analyze how biases vary in new information, along the metrics of type, variety, and intensity. I used over 500,000 news articles from 15 publications, spanning over 4 years to build and train my algorithm. Using Word2Vec, a popular NLP method, I was able to conclude that more right leaning publications are more likely to exhibit misogynistic content that is biased against women. However, the method fell short of identifying many forms of objectification like Benevolent Sexism. Similarly, using VADER, a python-code of sentiment analysis tool, I was able to determine that mere metrics of positive, negative, and neutral sentiment are not sufficient to detect occurrences of gender bias. To gauge the breadth of sexist language effectively, I used the LIWC text analysis program which calculates the percentage of words in a given text that fall into one or more of over 80 linguistic, psychological and topical categories indicating various social, cognitive, and affective processes. As a result, with statistical evidence my study was able to conclude the presence of implicit gender bias occurs all across publications but is more prevalent in right-leaning publications.
An Overview of the SPAC Market: Problems, Solutions, and Prospects
Authors: Sun Ada , Wang Wenyu
Published: April 2023

This paper aims to present the current problems, solutions, and prospects of SPACs in the United States. First, the report introduces how SPACs function and merge with private companies. Then, it examines the advantages and disadvantages of the SPAC process, especially when contrasted with traditional IPOs. Finally, moving to more current events, it establishes the decline of SPACs in the past year before concluding with the new rules proposed by the SEC. We will also predict the future of SPACs and how the SEC's reforms will impact the market. The paper provides a bird's-eye view of the current status of SPACs in the United States, serving as a foundation for any expectations regarding SPACs.
Fully Automatic Controlled Environment Agriculture using Machine Learning based Plant Size Estimator
Authors: Yoon Seung wook , Nam Sukyeong
Published: April 2023

Due to climate change, the global food supply crisis has become an urgent international problem. Given the circumstances, a controlled environment that artificially adjusts the climate for agriculture has attracted considerable attention as a solution to the problem. Various kinds of research have been proposed to develop the technology of controlled environments. However, the accuracy and scalability problem of these methods is a burden for the expansion to real-world scenarios. In particular, it is necessary to research and implement the computer vision-based algorithm, which is the key technique that enables the controlled environment system to be fully automatic. To solve the aforementioned problem, I propose a novel controlled environment agriculture system. The proposed system is composed of a plant life cycle regression module and a device control module. The system predicts the actual size of the plants and outputs the life cycle indicator of the plant, which is the growth rate of the plants. Based on the life cycle indicator, the device control module adjusts the essential factors, such as the amount of water and the strength of UV (Ultra Violet) light, for photosynthesis. As the proposed system is aware of the life cycle of plants, it can provide fully automatic controlled environments. I also propose and demonstrate the application machine to show how the proposed method can be applied to the real world. Through the experiments, it is shown that the proposed PLCR outperforms the existing state-of-the-art methods on the COCO dataset.
The Role of Morphology and Heart Rate Variability Features in Detecting Arrhythmias from Short ECGs
Authors: Hu Alice , Ghiasi Shadi
Published: April 2023

Detecting heart arrhythmias from short Electrocardiogram (ECG) recordings remains challenging since recordings are short and contaminated by noise. ECG morphology features and Heart Rate Variability (HRV) time and frequency domain features are widely used for classifying short ECG recordings. Here we investigate the relative roles of ECG morphology features and HRV time and frequency domain features in classifying short ECG recordings provided by the 2017 PhysioNet/Computing in Cardiology Challenge. The classification is performed separately by four machine learning models: Logistic Regression, Decision Tree, K Nearest Neighbors, and Convolutional Neural Network (CNN). Our best classification score is obtained using the deep learning 1-dimensional CNN model trained on HRV time domain features combined with ECG morphology features. It gives an overall F1 score of 0.70 and 0.73 for the cross validation and hidden test respectively when considering the average classification performance over all 4 categories: Atrial Fibrillation (AF), normal, other arrhythmias, and noisy signal. We found that HRV time domain features play an important role in detecting AF, normal, and other classes, whereas ECG morphology features play a key role in detecting the noisy class. When HRV frequency domain features are combined with HRV time domain features, they do not improve and often degrade classifications of short ECG recordings compared to classifications using only HRV time domain features. Combining ECG morphology features with HRV time domain features leads to a better classification performance for short ECG recordings. Feature-based deep learning could serve as a viable and less expensive approach for ECG classifications.
The Contrast Between Depression Now and In the Earlier Generations
Authors: Buyrukbilen Irmak
Published: April 2023

Depression is a mood disorder in which one experiences sadness, hopelessness, a loss of desire to live or to enjoy simple activities. It is a prevalent mental disorder that has historically been seen in all age groups. However, depression rates among adolescents have increased in the past few decades. Given this increase, researchers have increasingly studied this topic. According to some of the studies conducted in the past 20 years the increase in adolescent depression has been found to be associated with factors, including increased use of social media among adolescents, decreased free play among children, and more recent COVID-19-related impacts (e.g., staying locked up in their homes for more than a year, doing everything online, not being able to see their close friends.). This article reviews the aforementioned factors in relation to the significant increase in adolescent depression in recent years.
3D Bioprinting: Manufacturing the Human Heart
Authors: Park Seungbihn , Talbot Johnathon
Published: April 2023

Every day, the organ shortage crisis takes away the lives of 17 patients (Health Resources & Services Administration, 2022). The number of patients who require organ transplants significantly exceeds the number of possible donors, and consequently, most patients pass away while waiting for a matching donor organ. To address this issue, 3D bioprinting was suggested as a method by which patients could receive a functioning replica of their own biocompatible organ. This manuscript will cover in depth the materials—the bioink—and the printing methods that are widely used by various researchers in the bioprinting field. More specifically, this manuscript will analyze and compare natural bioinks—alginate and collagen—and synthetic bioinks—Gelatin methacryloyl and polycaprolactone. It will then introduce the two major bioprinting methods—extrusion-based printing and inkjet-based printing—and analyze the advantages and disadvantages of each method. Finally, the manuscript will highlight the successful applications of 3D bioprinting in cardiology using the aforementioned bioinks and printing methods.
The Implications of Shadow Education on African School Systems
Authors: Kim Christine , Zelcer Brook
Published: April 2023

Shadow education has become a growing practice and a subject of interest in all areas of the world. As the regular education system sometimes finds itself unable to satisfy students fully, they often turn to shadow education. The practice is most commonly seen and studied in competitive areas such as East Asia and North America. As Africa’s education system develops as a continent, trends of shadow education also begin to emerge. However, since the practice is relatively new, there is little information surrounding Africa and shadow education. The research paper will review the practice of shadow education in Africa and the potential situations they could face as it becomes more prominent. The information used involves surveys, statistical reports, and comparisons between countries.
The Unique Stress Treatment of Martial Arts on the Adolescent Demographic
Authors: Lee Elliott , Ihn Jenny
Published: April 2023

In the 21th century, the phenomenon of stress and mental fatigue is ever so common in the age group of adolescents and teens. At a crucial time in their lives and in their transition to adults, the coping strategies and methodology in which these young adults deal with stress is largely unpatterned and inconsistent. With the unique hurdles that adolescents experience in dealing with their future and academic challenges, the need for alternate treatment or therapy in the adolescent demographic is crucial in securing their physical and mental wellbeing. Martial arts can be used to treat this unique stress. The effects of martial arts on the general stress levels and mental states of a small group of experimental adolescents was observed through an experiment of 14 participants before and after a martial arts session in order to evaluate the effectiveness of such treatment based on correlations drawn from subcategories organized by ordered levels of anger management, levels of stress frequency, levels of martial arts experience, and levels of exercise frequency. Main findings of the trial include a general reduction in stress levels across all participants of the martial arts experience and encouragement of martial arts as a stress reducing platform. Further subcategories of the trial revealed additional traits of anger management on mental states and stress levels. Limitations include the experimental nature of the trial, limited exposure to various martial arts, and limited pool of participants or the diversity of the demographic studied.
Implications of Aromatase Inhibitor Therapy in Postmenopausal Breast Cancer
Authors: Makkena Anvitha , Appavu Rajagopal , Kethar Jothsna
Published: April 2023

Aromatase Inhibitor(AI) therapy is a crucial treatment for regulating estrogen production that combats breast cancer in postmenopausal patients. Clinical trials have emphasized its importance, as it has surpassed its prior efficacy through each succeeding generation of AI therapy and surpassed other treatment options like estrogen modulators(Tamoxifen) and Progestin therapy(Megace/Megestrol Acetate). There is a big difference between AI therapy and other therapies, though they all ultimately attempt to stop the proliferation of cancerous cells. AI therapy has been shown to be effective; however, some side effects of its use have been challenging its place in recent studies. Many physicians have noticed and questioned its use, and future research addressing these concerns needs to be executed in order to enhance the quality of life for our breast cancer patients. In this paper, an overview of the current status of breast cancer, the details of breast cancer and its development, the different types of breast cancer, the workings of AI therapy, clinical trials of Aromatase Inhibitor therapy, a comparison of different therapies, Physician input, and future implications of its effectiveness will be discussed in detail.
Highly Skilled Migration Flows: A Case Study of Taiwan
Authors: Kesarwani Shreya , Lincoln William
Published: April 2023

The largest type of international migration is the movement of people from developing to developed countries. This extensive global migration has raised concerns of brain drain, where highly skilled students and professionals leave their home countries and never return. While highly skilled migration may indeed create a brain drain, it simultaneously promotes the development of the home country. This paper uses the case study of Taiwan to demonstrate that the emigration of highly skilled individuals enhances the development of the sending country through return migration, transnational workers, and diaspora networks. To analyze the impacts that migration has had on the development of Taiwan, regression techniques are implemented. The empirical findings of the paper show that once transnational networks were developed, migration outflows led to an increase in the overall output of Taiwan.
Climate Change and The Inflation Reduction Act: Recommendations for Job Seekers in US Energy
Authors: Cowan Connor , Martins Aniket , Dignon Ewan , McGuigan Deborah
Published: April 2023

The onset of the global climate crisis has caused many to consider potential impacts on the United States economy, particularly those on the energy sector. Currently dominated by traditional means of production such as coal and fracking, the sector is set to shift towards more sustainable forms such as solar, wind, hydroelectric, and nuclear as stakeholders seek to keep warming below 1.5℃. Accelerating this shift is the recently passed Inflation Reduction Act (IRA), which promises new green incentives, but also leaves questions unanswered regarding the true scale of US divestment from fossil fuels. This paper seeks to combine data regarding projected employment in carbon-intensive/neutral industries with examination of provisions in the IRA, in order to make recommendations for those considering jobs in the US energy sector.
Unintended Bias in Artificial Intelligence Driven Diagnosis of Melanoma: A Systematic Review
Authors: Ihemelandu Kemka , Albanese Chris
Published: April 2023

Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone have increasingly been recognized as a problem. Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN) models. CNN models are prone to biased output due to biases in the dataset used to train them. Although the incidence of melanoma is lower in patients with darker skin tone, it is associated with a worse prognosis than in Caucasians, underscoring the need for accurate early diagnosis in these patients. Our objective in this systematic review was to assess to what degree race/ethnicity, specifically Black/ African American patient cohort were included in training datasets used in generating machine learning algorithms for automated melanoma diagnosis. Our review documents the fact that there is a remarkable lack of and inconsistent reporting of patient demographics especially race/ethnicity with notable under-representation of patients of color, highlighting a currently unmet critical need of lack of diversity in the publicly available skin image datasets. These publicly available skin image datasets, are an inherently unbalanced unintentionally biased datasets from which AI models created for the diagnosis of melanoma skin cancer have restricted applicability to real life clinical scenarios and limited population representation preventing generalizability to the community as a whole.
To the Farthest Gulf for the Wealth of India: Firsthand Experiences of American Travelers in India
Authors: Raman Nikhil , Sandock Thomas , Melchior Kate
Published: April 2023

My essay analyzes the experiences of Americans in India from the colonial period to the emergence of the United States as a nation in the 18th century and further into the nineteenth century when the nation consolidated its identity through commerce, religion and race discourse. I trace these three moments in the joint history of America and India through the life and travel writings of a few key figures. Through the letters of Nathaniel Higginson, the Salem-born man who eventually became Governor of Madras in 1692, we can trace the social and political dealings of a New England based administrator in the colonial era. In the second period, in the aftermath of the American revolution, there is a great interest in India from a newly formed United States, that can be seen in the exploits of American travelers such as Bartholomew Burges. In the nineteenth century there was a further escalation of the ties between India and America that is seen in the story of Calvin Smith, a civil war veteran who traveled to India and worked in the then popular ice trade, sharing his perspectives and experiences of living in India for five years. Finally, in the mid to late 19th century, evangelical America and the Liberal Christian movement spread Christianity to other nations through missions, reaching India.
Transgenerational development of food allergies and allergic rhinitis
Authors: Thatavarthy Samhitha , Fryer Kelsey
Published: April 2023

Both environmental and genetic factors play a role in allergies. Allergies are influenced by genes and how they control immune cell function. Several studies have examined the occurrence of allergic disease in children and its association with other risk factors, including allergic disease in parents. Specific toxins like CO2 and other health conditions can be related to the diagnosis of allergic rhinitis. The response to food allergies was observed in many studies to conclude that heritability from parents to offspring is one of the leading risk factors for allergic diseases. Several studies have found a significant increase in the prevalence of allergic rhinitis in males than in females. Avoidance of a particular food was associated with an increased risk of developing an allergy to that food. At the molecular level, T cells are found to affect allergy outcomes through their part of the immune response.  Food proteins such as milk, egg, and peanut - common food allergens -  may cause an immune response in allergic individuals. Different therapies include Epicutaneous Immunotherapy (EPIT) and specific infant milk protein formulas. If this formula is taken from infancy, the allergic responses can be prevented/reduced.  As with seasonal allergies, prevention can be mediated by avoiding different pollution environments that may cause additional irritation, temperature control in a given atmosphere/humidity, and therapies of Vitamin C for immunity. With many other seasonal allergy triggers, it is ubiquitous among populations and dependent on the area and season.
The Correlation of Various Economic and Political Variables on Carbon Emissions
Authors: Joshi Anay , Greenberg Clayton
Published: April 2023

With the sea levels and surface temperatures steadily rising, many scientists have warned of an oncoming global climate crisis. Currently, most studies point towards greenhouse gas emissions as being the main contributor for this climate crisis. In this study, we will investigate the correlation between various political and economic factors with carbon emissions. We run correlations among GDP and environmental policy stringency with the carbon dioxide emissions per capita to see the way the trends change over the scales of these variables. We also observe the trends of total population and total carbon emissions over time to analyze any occurring patterns. The goal of finding the correlations between these factors is that they may shed light on other potential elements that are commonly overlooked when attempting to minimize the global climate crisis. Our analysis also shows some inconsistencies between the intended and actual effects of the policy.
A Graph Algorithm to Eliminate Hunger and Food Waste by Matching Excess Food to Demand
Authors: Makur Neil , Mathews Maya
Published: April 2023

Millions of tons of food from grocery stores go to waste every year in the US, while many people consistently depend on community food banks. Having a plan to transport food surplus to the needy will eliminate both food waste and hunger at the same time. This problem is modeled as a bipartite graph with one set of vertices representing food donors with certain excess food of various types, and the other set representing food banks with demand of different types of food, and a cost of transportation on each edge. We create four heuristic algorithms to find low-cost transportation plans that satisfy all food needs, and compare them in terms of plan cost and runtime. We find that the basic greedy algorithm does the best in both aspects.
The Dymaxion Dwelling Machine: R. Buckminster Fuller’s Vision to House All of Humanity
Authors: Lee Blake
Published: April 2023

Traditional housing is, and has for many centuries, been uniquely made for their individual clients, making houses difficult to mass-produce and, sometimes, too expensive to provide for those who need it most. R. Buckminster Fuller, an architect who believed that we had an obligation to provide adequate housing, attempted to address this challenge almost a century ago through his creation, the Dymaxion Dwelling Machine. The Dymaxion (a portmanteau of Fuller’s favorite words: dynamic, maximum, and tension) Dwelling Machine was a dome-shaped home optimized for mass-production, and it maintained a higher rate of efficiency and sustainability than the standard cube-shaped home. This paper will analyze several methods and facets that Fuller implemented within this atypical house, such as the Dymaxion Bathroom, Fog Gun, tensegrity, cooling/heating, autonomy, affordability, materials, maintenance, and construction, that inspired sustainable, versatile, and affordable solutions that have contributed to addressing the climate and inadequate housing crises of today. 

 

“You never change things by fighting the existing reality. 

To change something, build a new model that makes the existing model obsolete.”
Statistical Analysis of Titanium Alloy Surface Processing on Aerospace Components Strength
Authors: Zeng Wesley , Buckley Donald
Published: April 2023

In the aerospace and space industry, Titanium alloys such as Ti-6Al-4V and their surface processing are widely used due to their excellent strength and lightweight characteristics such as their high strength-to-weight ratio, excellent corrosion resistance, and many factors. It is well known that the tested strength of aerospace components, such as fasteners, depends on both intrinsic material properties and surface processing. However, no detailed research has been done on the aerospace Ti-6Al-4V component tensile and double shear strength variation due to conducted surface processing on the component. Thus, the objective of this evaluation is to systematically evaluate the effect of various surface processings on the typical aerospace component, Ti-6Al-4V, including its fastener’s mechanical properties of both tensile and double shear strength. The three most common fastener surface processings were selected, including bare, aluminum organic coating, and dry film lubrication. Detailed statistical analyses, including Tukey’s HSD (honestly significant difference), were conducted to identify the relationship between the surface interactions and tested strength. Experimental results confirmed that fastener tested tensile and shear values dropped when surface processing was applied by up to 3.7%. This reduction was likely due to an elimination of localized seizing or galling from the additional lubrication instead of the intrinsic material degradation due to surface processing.
Stellar Classification based on Various Star Characteristics using Machine Learning Algorithms
Authors: Tamez Villarreal Jesus , Barton Sophia
Published: April 2023

The task of stellar classification can be tedious and lengthy when done manually. One can expedite stellar classification by creating an artificial intelligence model to automate the process. As we as a species continue to explore the frontier of the observable universe, we should seek to automate time-intensive problems like stellar classification. The current stellar classification model serves to effectively categorize stars for research purposes regarding their distribution around the universe, so automating the development of this resource would allow professionals to allocate more time to explore the bounds of our current understanding of space and the universe. After finding and analyzing a dataset containing numerical and categorical features, a supervised learning approach was then used to train and test different models on their ability to classify the stars. A Decision Tree Classifier, Random Forest Classifier, Ridge Classifier, and Support Vector Classifier were trained and tested. The most successful models were the Decision Tree Classifier and Random Forest Classifier, each with about a 94 percent prediction accuracy across different accuracy metrics on the test data. Despite some drawbacks in regard to the availability of usable data, four models were trained and two were proven to be consistently and successfully accurate. Any future attempts at developing models for stellar classification should concentrate more on gathering data as to have a more thoroughly trained set of models.
Use of Kolmogorov-Zurbenko Filter Technique to Evaluate PM2.5 Air Quality Trends in New Jersey
Authors: Kim Myoungwoo , Cha Ethan
Published: April 2023

This study examined the long-term trends of PM2.5 in the three counties, Camden, Bergen, and Middlesex in New Jersey between 2000 and 2022 using three different averaging methods: USEPA's 3-year average of highest annual average (TYAHAA), simple annual average, and KZ filter rolling average technique. As results, winter and summer had higher PM2.5 levels than spring and fall, which could be attributed to weather patterns and emission changes. For Camden County, an industrialized area, the KZ (-43%) and the TYAHAA (-41%) had a robust agreement. This suggests both KZ and the TYAHAA method could be used to evaluate long term trends for industrialized areas. As to Bergen County, an urban residential area with intensive transportation sources, the KZ (-29%) showed a disagreement with the TYAHAA (-41%) but correlated with the simple annual average (-25%). This suggests that the KZ is better at capturing transportation-related short-term fluctuations than the TYAHAA. However, the KZ average (+9%) had a significant discrepancy from the TYAHAA (-41%) for a suburban site. These discrepancies may be due to various factors, including differences in emission sources, meteorological conditions, emission control measures, and the time period analyzed. In conclusion, the KZ method can be useful for identifying and removing short-term fluctuations in data to reveal underlying long-term trends in PM2.5 air quality. However, the choice of method should be based on the specific objectives of the study and the nature of the data. Using the three methods may provide a more comprehensive assessment of air quality trends.
The Retina: A Different Perspective into Alzheimer’s Disease Screening
Authors: Avadhanam Advaith , Kim Ally
Published: April 2023

The field of identifying retinal biomarkers of Alzheimer’s Disease has seen tremendous growth in recent years. The retina has great potential for being used in screening for Alzheimer’s disease (AD); it is the only part of the CNS not shielded by bone, and AD patients have several visual complaints. A number of major biomarkers in the retina have been found, including retinal nerve fiber layer (RNFL) thinning, retinovascular changes, pericyte loss and blood-retinal barrier (BRB) weakening, β-Amyloid (Aβ) deposits, Hyperphosphorylated tau and neurofibrillary tangles (NFTs), and gliosis/inflammation. All of these parallel brain biomarkers. Furthermore, new ocular biomarkers have been found (the efficacy of which is not yet fully proven) - Aβ in the lens, choroid thinning, and visual symptoms. Amyloid biomarkers probably have the most potential among these for screening; however, a multivariable model will be more effective. In the future, the Atlas of Retinal Imaging in Alzheimer’s Study (ARIAS) study, which has already commenced, will search for a wide range of retinal biomarkers in many patients in varying stages of AD and risk levels of AD; it will also explore the interrelationships between those biomarkers to find a potential multivariate screening test for AD. Also, tear fluid could be a potential future biomarker that will be relatively easy to screen. Overall, this field has made great strides in recent years, and has great potential for groundbreaking advances in the near future.  The promise of course is to enable simple, inexpensive, widespread and regular screening for AD using retinal biomarkers.
From Combinatory Categorial Grammar to the Calculus of Constructions: A Review of ccg2lambda.
Authors: Jung Yeonho , Briggs Daniel
Published: April 2023

The following is an overview of the concepts and systems necessary to build an understanding of the framework from ccg2lambda: A Compositional Semantics System, which produces logical semantic representations of natural language sentences. These representations are used in tandem with a theorem prover to conduct inferences. But, to the reader unfamiliar with the various tools within computer science, linguistics, and mathematics that were used to construct ccg2lambda and its dependencies, it can be difficult to understand the inner workings of the framework. Thus, an explication of these concepts could be useful for fostering further development. Concepts such as mathematical logic, combinatory categorial grammar, the calculus of constructions, and interactive theorem provers are covered, as well as the two systems C&C and ccg2lambda. A functional version of the ccg2lambda framework can be found at https://github.com/ajung202/ccg2lambda.
Targeting Gastric Cancer Cells using Nanoparticles to Improve Diagnosis and Treatment Outcomes while Minimizing Off-Target Toxicity
Authors: Pathare Dhroov , Haddad Salame
Published: April 2023

Conventional treatments for metastatic and unresectable gastric cancer (GC) involves chemotherapy and immunotherapy, but these methods have limitations and may cause toxicity and damage to healthy cells. This review focuses on the use of nanoparticles to overcome these challenges. Researchers have reported using nanoparticles for improving imaging techniques, such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and Single-photon emission computed tomography (SPECT) by eliminating limitations like adverse reactions, low pharmacokinetics, rapid clearance, and non-specific distribution. Nanoparticles have also been used in chemotherapy to target specific cancerous cells, minimize side effects, improve drug effectiveness, protect therapeutic compounds from the body's harsh environment, and deliver multiple diagnostic and therapeutic agents simultaneously. Nanoparticles have also shown promise as a delivery platform for gene therapy in the treatment of GC, specifically using small interfering RNAs (siRNA) to inhibit the expression of specific genes driving the growth and proliferation of cancer cells using plasmid DNA to express specific proteins. The use of nanoparticles in oxidation therapy to deliver reactive oxygen species agents (ROS) has shown promise as a means of selectively targeting cancer cells while minimizing the toxicity to normal cells. Nanoparticles have also shown similar promise in the delivery of phytochemicals such epigallocatechin gallate (EGCG) in cancer treatment. The biostability of nanoparticles, and their ability to precisely target cancer cells has provided a method for stable systemic delivery of drugs, improved the effectiveness of GC diagnosis, treatment modalities, and prognosis, and has shown tremendous potential to further improve outcomes for patients with GC.