As Hematopoietic stem cell transplantations (HSCT) are high-risk procedures with a 30-50% likelihood of resulting in Graft Versus Host disease (GVHD), a critical complication that significantly impacts patient outcomes, it is essential to have an effective treatment. However, current efforts to find specific treatments result in low response rates. Understanding the interactions that cause host rejection, GVHD, and a successful transplantation is imperative. This review highlighted innovative therapies such as HLA matching and typing, Antibiotic Prophylaxis, etc. which utilize personalized medicine to increase success rates. Ethical issues such as the risk of adverse reactions due to drugs which were tested in unconventional clinical trials, mishandling of genetic data in commercial genetic testing companies, the wellbeing of an infant produced via preimplantation HSCT typing, and whether the cost of treatment would allow equitable access should all be considered. The challenge of balancing ethical rights with public health interests, especially in the context of genetic testing and research, requires thoughtful consideration. Despite this, the potential of personalized medicine in HSCT is paramount. By implementing some of the following personalized treatment strategies, an increase in success rate along with longer lifespans had been recorded. Nevertheless, fatal side effects such as Cytokine Release Syndrome (CRS) question their integration into mainstream therapies. As precision medicine continues to advance, it is crucial to provide a substantial trial period and find strategies to create a confidential environment. Future research should focus on refining these personalized procedures and exploring their broader applications in the field of HSCT.

The formation and evolution of galaxies are key processes that shaped the heterogeneous universe from a homogeneous state after the Big Bang. The advent of high-resolution space telescopes has provided unprecedented detail in observing distant and faint objects, enabling deeper analysis of galaxy morphology and structure that builds on the foundational classifications established by the Hubble Sequence. Aiming to study the galaxtic evolution in the Southern Massive Cluster Survey (SMACS) 0723 and identify the age of the more complex disk galaxies, this work examined the morphology of galaxies in using data from the James Webb Space Telescope (JWST). The captured high-resolution images provided new insights into galaxy formation and evolution, revealing a larger number of galaxies than previously visible with the Hubble Space Telescope. By applying the Morpheus machine learning model, 755 galaxies were identified and classified into four morphology categories: disk, spheroid, irregular, and point source. With more than 80% of the classified output receiving high confidence scores, this deep learning method was shown to be effective at analyzing JWST's high-resolution images, providing clearer and more detailed insights into galaxy morphology. The distributions of all types of galaxies throughout this cluster were found to be homogeneous, with the majority classified as disk galaxies. Additionally, by aligning JWST data with photometric redshift information from the Reionization Lensing Cluster Survey, this study presented a correlation between galaxy morphology and redshift; a substantial number of disk galaxies, over 50% of all galaxies, were identified at z > 4 for the first time. These findings suggest that disk galaxies have existed for billions of years, challenging previous assumptions about galaxy evolution. This research emphasizes the importance of JWST in advancing understanding of the universe and lays groundwork for future studies on galaxy morphology and evolution.

The prevalence of online newspapers and media sources has been coupled with the growth of accessible retail investing throughout the U.S.. Although there has been an increase in forecasting, there are no conclusive determinations regarding the influence of media on stocks and the broader market. The lack of current literature surrounding this contemporary topic of news media’s relationship with the Market Efficiency Hypothesis necessitates new research. To assess the degree to which the media is able to affect the stock market, articles pertaining to Apple and S&P 500 from 7/28/22 to 2/03/23 were selected from the Wall Street Journal and Barrons. Each article was given a positivity rating, ranging from Extremely Positive to Extremely Negative, and was compared to the change in the corresponding stock’s price. The research revealed a weak correlation with Apple, which had less data, and a mildly strong correlation with S&P 500. Using the correlation coefficient equation and statistical analysis, a 0.75 correlation factor was determined for S&P 500. Thus, these findings refute the Market Efficiency Hypothesis, showing how the stock does not trade at its “fair” value, and how modern factors such as instantaneous news and media influence its price. Overall, as news platforms continue to increase viewership, along with the ubiquity of social media platforms such as X, Reddit, and TikTok which continue to drive investing popularity and regularity, the influence that media has on the market will become paramount as new technology emerges.

One of the many fascinating features of the brain is the ability to form motor habits, known as “motor memory”. Following a revolutionary 1997 study, the topic of motor memory consolidation, or how the engram changes over time, began to garner significant attention, and the field has only grown since. The first objective of this review was providing an overarching synopsis of this topic’s history, mainly the debate on whether motor memory consolidates and current gaps in knowledge. The second goal was to identify and provide evidence for one particular consolidation model, including acquisition and storage sites, believed to be the most well-supported. To conduct the research, Google Scholar was the main database utilized, and most articles before 1997 were eliminated. The first finding was the general mechanism of consolidation: similar to declarative memory, the motor engram after encoding transforms from an initially fragile state to a stronger one resistant to disruption. The second finding was related to the proposed acquisition sites, such as the cerebellum and prefrontal cortex. This paper contended for the former, as the cerebellum’s significance in acquisition has been demonstrated through vestibulo-ocular reflex training and Pavlovian eye conditioning. This paper also identified studies that discuss long-term storage areas, such as the vestibular nuclei. Finally, existing issues like the complexity of the encoding mechanism, effects of sleep fragmentation, and the factor of age were addressed. This review contributes towards a more unified consolidation model to be used in various real-life applications, such as sports science.

Minimally invasive surgery has become standard for many medical operations. However, it comes with its challenges. For one, surgeons aren’t always skilled. While some may be incredibly experienced, operations are still susceptible to human error—especially with rigid instruments. With new advents in soft robotics, soft robots are being explored for optimal surgery, better patient experience, and more effective diagnoses. The surgeons will no longer be responsible for instrumentation with soft robots, they mainly help with robot orientation, diagnoses, and interpretations of data provided by the robot. Soft robots are safer and more human-friendly, with gentler materials as well as fluidity that makes them apt for many circumstances. However, there are some issues in controlling their movement. In this paper, a learning-based kinematic controller was presented as the solution for a generic soft robot through a simulation. This model proved that it is possible to control a soft continuum robot through traditional techniques used for rigid robots. These techniques are optimized for soft robots through modern methods like machine learning by providing it data from motor babble. This discovery can be utilized for future models of soft robots built for minimally invasive surgery or other extensive uses. This will further development in the soft robotics field.

This paper studied the effect of a venture capital (VC) firm’s reputation and social media presence on the portfolio company’s post-IPO long-run performance based in the US between the years 2005 to 2019; The research conducted four different case studies to examine the relationship between these variables, with the use of netnography and financial analysis. According to previous studies, a VC firm's reputation, based on the success of past ventures, has a positive correlation with a portfolio company’s post-IPO long-run performance based in the US, but they don’t consider social media as a factor since it was not prevalent during the time of their study, which is something this paper took into account while examining the relationship between VC reputation and a portfolio company’s post-IPO performance. The research found that VC reputation does have a positive correlation with the post-IPO performance of a company; however, the research also found that a VC firm’s social media activity also has a positive relation to the performance of a portfolio company, mostly in the short run, but also lingers temporarily in the post-IPO long run. The implications of these findings suggested that previous assumptions about VC reputation and a portfolio company’s post-IPO performance have slightly, and ultimately, VC firms could leverage their social media presence to boost the portfolio company’s short-run performance, while also giving entrepreneurs an additional factor to consider when finding the VC firm to back their company.

The field of oncology is rapidly growing in search of various therapies for cancer, which calls for further study of cellular processes and molecules. ROS, or reactive oxygen species, are necessary throughout a cell's metabolic processes; high reactivity at high concentrations could threaten cells, possibly allowing for beneficial use against cancers. Conversely, antioxidants regularly neutralize ROS in cells and manage lipid peroxide. Depleting certain antioxidants may lead to ferroptosis, which may also target cancer cells. It has been found that antioxidants can protect healthy cells from ROS treatment while cancer cells suffer damage. However, antioxidants may also diminish the effects of chemotherapy/ROS treatment, increase the risk of cancer, or have no effect at all, so additional work is needed to understand the balance and specific molecules necessary. The metabolic pathways generating ROS, involvement of ROS in cancer, and interplay among antioxidants, ferroptosis, and reactive oxygen species are evaluated in this review.

The COVID-19 pandemic has significantly impacted society, highlighting the need to understand disease dynamics. This paper explored the Susceptible-Infected-Recovered (SIR) model, which categorizes populations to simulate disease spread. By analyzing the transmission (β) and recovery rates (γ), the model provided insights into epidemic behavior. Using COVID-19 data from South Korea (February-April 2020), the study examined the impact of social distancing on the effective reproduction number (Rt). The findings showed that interventions effectively reduced Rt, demonstrating that the SIR model’s predictions align with observed outcomes in managing outbreaks. The paper concluded that even though the SIR model is valuable for showing basic and simple trends for the disease, incorporating Rt and more complex alternative models provides a more comprehensive understanding and enhances response strategies. This approach is crucial for preparing for future pandemics and developing effective public health policies.

We analyzed earnings reports of mega-cap companies to determine rationality of the stock price reactions with behavioral economics. The objective was to evaluate whether behavioral economics was a viable method for interpreting price action. We compiled the top twenty companies by weight in the S&P 500 and examined their price data after an earnings report was released. The data indicated that price reactions were not always rational and concepts such as negativity bias and herding behavior often affected stock prices negatively. Specifically, the companies we analyzed experienced rational reactions to their earnings reports 40% of the time and most price reactions were irrational to some degree. Furthermore, technology companies showcased clear signs of negativity bias and the outcomes of many of their earnings could not be explained with the Efficient Market Hypothesis.

Homelessness in the US is continuing to get worse despite significant support from local, state, and federal governments. It is not only a significant problem for the individual impacted directly but also has a knock-on effect on society at large. This research paper looks at the major causes of homelessness in the state of California and the role of government policies that impact it, focusing on housing supply and welfare support. The research concludes that shortage in housing supply is the major cause of homelessness in California. The situation is exacerbated because of the negative impact of economic and fiscal policies, and limited impact of welfare policies such as CalWORKS. The paper proposes specific solutions for increasing the housing supply, and identifies areas for further research.

Chess is a classic board game with simple rules but requires complex cognitive strategies. Over the years, it has left a huge mark on scientific interest, particularly in cognitive science. This interest led to the conduction of a literature review to summarize the research findings of chess on brain activity, cognition, and clinical applications. Benefiting from the neuroimaging techniques, researchers have identified several more active brain regions known to play an important role in the processing of strategic planning, attention, memory, decision-making, and other cognitive skills that are critical throughout practice of chess. There is solid evidence demonstrating a positive correlation between chess and cognitive abilities. A multitude of studies have been conducted regarding the value of chess intervention as a type of psychotherapy. A chess instructional program improves math skills and overall school performance in children with learning disabilities. Chess therapy is effective in the management of individuals suffering from attention deficit/hyperactivity disorder (ADHD). Chess can also support children with autism by improving certain cognitive and social skills. Playing board games including chess is associated with a lower risk of dementia. Chess intervention can ameliorate the manifestations and quality of life in patients with Alzheimer’s disease. Playing chess can restore, at least partially, the executive functions of patients with schizophrenia. As an add-on, chess-based cognitive remediation therapy helps improve cognitive recovery from substance abuse during the initial abstinence period. Altogether, chess has a promising role in the management of neurodevelopmental and mental health disorders.

Deforestation not only destroys habitats for many plant and animal species but also releases billions of tons of carbon dioxide annually into the atmosphere. In order to meet our growing demand for timber without worsening deforestation, one solution that has received increasing acceptance over the past two decades has been fast growing trees, which produce timber and sequester carbon faster than most trees. This paper focuses on South-East Asia, which is home to about 15% of the world’s tropical forests and a major timber supplying region. The two most commonly cultivated fast growing trees here are eucalyptus and acacia. However, because both are exotic to most of South-East Asia, as well as to the majority of regions where they are grown for timber, they have invasively disrupted local ecologies.  The damage includes excessive water consumption, suppression of local ground vegetation and lower plant and animal biodiversity. Hence, this paper examined a potential native alternative, the jabon species (Anthocepalus cadamba), and compared its performance as timber producer and carbon capturer with other fast growing trees.  From existing research, the dimensions of three different species at various ages from planting to harvest were obtained, from which the above-ground biomass (a measure of timber produced) and carbon weight were calculated.  This paper found that compared to eucalyptus, jabon was superior in both metrics by the time of its first harvest, while compared to acacia, jabon produced more timber but captured less carbon.  These findings suggest that jabon is a very deserving candidate for sustainable timber in South-East Asia, with the added benefit that it is indigenous and non-invasive.  Two areas of further study are exploring factors other than species that affect productivity and carbon capture, and extending the study to harvests beyond the first.

Chronic Obstructive Pulmonary Disease (COPD) represented a complex respiratory disorder influenced by a combination of genetic and environmental factors. This review highlighted the pivotal role of DNA methylation in the pathogenesis and progression of Chronic Obstructive Pulmonary Disease. By examining the function of DNA methylation, particularly hypermethylation, the authors identified key targets genes involved in lung maturation, inflammation, and oxidative stress, which contributed to the worsening of Chronic Obstructive Pulmonary Disease. The review also explored the significance of DNA methylation in the biomarker field, environmental factors, and treatment methods. Through a com- prehensive analysis, the authors elucidated the impact of hypermethylation on genes such as Interleukin-1 Beta, which was associated with inflammatory processes in Chronic Obstructive Pulmonary Disease lungs. Furthermore, the review discussed emerging therapeutic procedures, including epigenome editing through CRISPR technology and DNA methyltransferase inhibitors, demonstrating their potential in personalized Chronic Obstructive Pulmonary Disease management. The authors proposed that the integration of these novel approaches with conventional pharmacological interventions might offer a more comprehensive treatment plan tailored to each patient’s specific molecular characteristics.

This research aimed to investigate the daily oscillations of pivotal atmospheric parameters—temperature, humidity, and carbon dioxide (CO2) levels. The investigation is significant in comprehending Earth's climate dynamics and their repercussions on environmental processes. This study amalgamated primary data from an experiment with secondary research from diverse sources, employing statistical and analytical techniques to dissect these patterns. The findings revealed the intricate interplay of natural and anthropogenic influences on diurnal atmospheric variations, underscoring the imperative of sustained vigilance and research in this domain. Potential applications of these findings include improvements in weather forecasting, climate modeling, and environmental policy formulation.

Solar power, a promising green technology, is known to have a decrease in its efficiency as temperature increases. While solutions such as nanofluids offer the potential to cool the panels, their practical implementation has challenges. This study aims to analyze the cooling performance of a Titanium Dioxide (TiO2) and Zinc Oxide (ZnO) based sunscreen on photovoltaic panels. The experimental set-up consists of polycrystalline solar panels, water, a DIY sunscreen kit including TiO2 and ZnO, a heat fan, a spray bottle, an Arduino voltage sensor and a current sensor. Sunscreen and water were sprayed 10 to 30 times on the backside or frontside of the photovoltaic panel that is 55℃. Statistical analysis was done using SPSS. A temperature drop ranging from 3.5-11℃ was observed as the fluid was sprayed. Spraying on the back side rather than the front side, an increase in the rate of spraying, and utilizing sunscreen instead of water lead to larger temperature drops. Power and temperature showed significant correlations with a Pearson‘s R coefficient of -0.71 (p<0.001). Linear regression showed a R2 value of 0.505 (p<0.001), with an equation of [Power] =－0.338[Temp] + 44.561. Overall, TiO2-ZnO-based sunscreen showed effectiveness on the cooling performance of photovoltaic panels. For further applications, verification of these results and an outdoor study would be needed.

Attention deficit and hyperactivity disorder (ADHD) is a mental disorder that is characterized by obvious difficulty in concentration, short duration of attention, and hasty action. Traditional diagnosis mainly based on subjective report or questionnaire has the limitation of inconsistency and inaccuracy. Main treatment, pharmacology, is also criticized by irresponsiveness, overuse, side effects, or reluctance from patients. Recently, computerized methods have been developed and applied as diagnostic and treatment tools in various medical fields including psychiatry. This review was to describe computerized methods applying for diagnosis and treatment of ADHD that have been used. For this, articles were selected through extensive search of databases and reviewed with regard to diagnosis using machine learning (ML) and deep learning (DL) with extracted data from structural and functional magnetic resonance image, electroencephalography (EEG), and genetic study as well as treatment by computer games based on EEG feedback or not. Overall, the literatures included in this review stated that ML/DL techniques provided objective and reliable diagnostic tools with improved accuracy and computer games achieved better results in reduction of ADHD related symptoms than other traditional treatment. Computerized methods will be promising strategies to accurately select the patients with ADHD benefitted by treatment and provide the effective treatment method. 

Due to rapid urbanization, noise-related sleep disturbances are particularly prevalent in metropolitan areas. (United Nations Department of Economic and Social Affairs. (n.d.)) sThis study investigates how nocturnal noises in the urbanized city influence sleep quality to provide insights in tackling noise-related sleep disturbances. First, a web-based, cross-sectional survey was conducted with convenience and snowball sampling of 338 residents from five residences in Gongshu District, Hangzhou, China. Later, the objective noise exposure around the periphery of each residence was measured by a decibel meter, the level of nocturnal noise exposure was determined based on the Noise Exposure Questionnaire, and the perceived sleep quality was determined using a combined Pittsburgh Sleep Quality and Insomnia Severity Index questionnaire. Lastly, multiple regression models using stepwise variable selection were fitted to determine associations, adjusting for potential confounders. This study showed a significant negative association between nocturnal noise exposure (measured both objectively via a decibel meter and subjectively through the survey) and sleep quality. In the univariate regression model, participants' perceived level of noise disturbances was significantly negatively associated with perceived sleep quality (β=-0.126, p-value=0.020) in the multiple regression model, participants' perceived level of noise disturbances was significantly negatively associated with perceived sleep quality (β=-0.118, p-value=0.000), adjusted for confounding variables, namely volume of tea intake, time spent on outdoor activities, and other lifestyle factors (cellphone usage, midnight snacks intake) by stepwise method.Volume of tea intake was significantly associated positively with perceived sleep quality (β=0.096 and p-value=0.050). This study provided insights into urban nocturnal noise intervention to ensure qualified sleep. More research is needed to determine how nocturnal noise exposure affects objective sleep quality and threshold noise level.

Previous research has indicated that emotions have an effect on investment behavior. However, this research only encompassed a limited range of emotions. While emotions like fear, anxiety, and anger have been frequently studied for their effects on investor behavior and how they affect the stock market, the effects of other relevant emotions such as sadness, surprise, nostalgia and excitement have not been as extensively studied. Furthermore, only a limited range of investment behaviors have been studied. This paper served as a review for the previous research on emotions and investment behavior, and develops a generalized model following a two dimensioned approach incorporating approach and avoidance motivations as well as appraisal theory. Different emotions significantly affect investor behavior and the stock market and emotions with approach tendencies cause risk prone behavior while avoidance tendencies cause the opposite. Additionally, the more an investor is associated with certainty appraisals the more confident they are that their investment will travel in the intended direction. Through this model, propositions are made linking emotions and investment behavior and stress their nuanced relationship. This paper was formulated through previous literature, previous surveys and experiments as well as established psychological principles. This paper deepened the comprehension of how emotions affect investor behavior and emphasized the essential nature of considering a broad spectrum of emotions when analyzing investment decisions.

Cardiac hypertrophy is a major cause of heart failure and a common symptom of congenital heart disease (CHD). Cardiac hypertrophy has usually been studied through the lens of coding genes, but a promising new field of research has emerged regarding the critical role long non-coding RNA (lncRNA) plays with cardiac hypertrophy. Utilizing next-generation sequencing (NGS), scientists have been able to uncover some of these lncRNAs, such as Chaer, Chast, H19, Lipcar, and Hotair, as well as their newly-established association with cardiac hypertrophy. These lncRNAs have potential for use as epigenetic regulators, biomarkers, or even sponges for microRNAs. With 68.4% of non- syndromic cases of cardiac hypertrophy associated with various lncRNAs, understanding the role they play could transform the landscape of cardiac treatments in acute and chronic illnesses with new treatments with lncRNAs, discovered with NGS, pushing forward the front in the fight against heart failure. Epigenetic regulators can either inhibit or promote cardiac hypertrophy. For example, Mhrt and H19 inhibit hypertrophy while Chaer and Chast promote hypertrophy. Targeting specific lncRNAs for upregulation or downregulation could provide insights into developing new treatments for cardiac hypertrophy. However, effective delivery mechanisms for lncRNAs must be established and human trials must be undergone before lncRNA therapies are considered for clinical use.

This literature review explored the emergence and evolution of hybrid cultures from the rise of the Renaissance and the Scientific Revolution in the 16th century. It examined how European pursuits of exploration and trade, beginning with Portugal's maritime route to India and Spain's exploration of the "New World," propelled Europe into an era of colonization. This review highlighted the economic partnerships and religious opportunities that facilitated cultural exchanges, emphasizing the agency indigenous peoples maintained despite colonial pressures. By analyzing the profound impact of colonialism, including forced conversions, cultural destruction, and resistance, the review revealed how indigenous peoples navigated and negotiated their roles, contributing to the formation of hybrid cultures. These interactions created opportunities for social and political advancement, leaving enduring impacts on language, culture, and music. The study also suggested future research into the religious aspects of hybrid cultures in North America, focusing on conversion efforts and their influence on local hybrid cultures.

This research paper investigated the sources and dispersion of PM2.5 particulate matter in New York City's Morrisania neighborhood from January 2018 to August 2023, using Conditional Probability Function (CPF) analysis alongside detailed meteorological data. The study identified significant local PM2.5 sources, notably transportation emissions from nearby highways and industrial activities from New Jersey, and examined how varying wind patterns affect pollutant dispersion. Key findings revealed that winds from the northwest promoted efficient PM2.5 dispersion, resulting in lower concentration levels, whereas slower winds from the south, southwest, and west led to higher concentrations due to reduced dispersion capabilities. This paper also evaluated the limitations of CPF analysis in distinguishing between local and distant pollution sources, suggesting the incorporation of advanced methodologies like Positive Matrix Factorization (PMF) and Chemical Mass Balance (CMB) models for future research. The results had important implications for air quality management in urban settings, providing a framework for targeted interventions to reduce PM2.5 pollution and improve public health outcomes. The insights gained underscored the necessity of integrating more detailed local data and modeling techniques to enhance the understanding of air pollution dynamics and inform effective policy-making. 

The venture capital industry plays a pivotal role in fostering innovation and driving economic growth by providing required funding to start-ups with long-term growth potential. In this high-risk environment, the choice of pricing mechanisms (whether posted price or auction) for start-up companies can significantly impact investment decisions, allocation of resources, efficiency, and finally success of the ventures. This research paper delves into an in-depth comparison of a first-price sealed-bid auction against a posted price system within the context of the venture capital industry. The goal is to compare their relative advantages, limitations, and overall implications for venture capitalists and entrepreneurs by starting with deriving optimal strategies in a standard posted price and auction model with bid preparation costs. The second part of this paper will focus on maximising the expected utility and the total capital raised by the start-up, while comparing optimal strategies within each model. The analysis shows a negative relationship between bid preparation costs and the total revenue generated, which substantiates the existence of miscoordination due to fear of wasted efforts and predicts the effect of priority on efficiency. However, the extent to which each factor impacts the equilibrium varies greatly with changes in the pricing mechanism.

Minority coalitions have ubiquitous presence across the globe, from the United States to regions in Africa. These ethnic enclaves serve a purpose beyond merely preserving their own culture; they also function as protective shields, almost a sanctuary, against local and regional pressures. As minorities in their respective regions, minority coalition communities have faced significant discrimination, sometimes even targeted by state policies focusing on weakening their influence. Despite these government efforts, minority coalitions have adeptly resisted amalgamation, eventually compelling their host countries to recognise and celebrate their cultural distinctiveness, often transforming these areas into popular tourist destinations. This paper aimed to delve deeper into the underlying reasons among social, political, and economic factors for the formation and development of such ethnic coalitions, arguing that the economic factor is the most important factor out of all. In doing so, out of many minority coalitions, the paper argues that Chinatown serves as an example and a representative that will be mainly discussed when pertaining to minority groups. It explored the intrinsic need for these communities to establish their own communities in response to the challenging social, political, and economic reasons, resulting in the creation of minority coalitions. Especially among these factors, economic reasons were identified to be the driving factor for such dynamics within the minorities. By shifting the discourse away from conventional political and social analyses toward economical factors, the results of the study are anticipated to further enhance our comprehension of social cohesion and identity formation within chinatowns. Furthermore, the results can be further utilised for a better understanding of how those economic factors interact with different social and political factors to shape the dynamics of ethnic enclaves, aiding in policy decisions for immigrating populations.

Music therapy is commonly used to improve people's mental and physical health. However, the role social media plays in this therapeutic practice has not yet been thoroughly explored. One study looked at the benefits of music therapy in 40 Australian adolescents. Another study found how music affects the perception of agency in 44 adolescents. Though these papers reveal the positive effects of music, they do not consider an important factor in their research– how much their subjects are exposed to media. This study seeks to explain research questions such as the extent to which social media usage influences the efficacy of music therapy interventions and how individuals' interaction with social media platforms shapes these musical experiences. To achieve these objectives, the author conducted a comprehensive review of existing literature, analyzing articles and journals related to music therapy and social media. This will provide an understanding of the synergies between music therapy and social media in aiding mental and physical well-being. Our study aims to explore the impact of social media exposure on the efficacy of music therapy interventions, illuminating the interplay between digital environments and therapeutic outcomes to inform and enrich practices tailored to the needs of the digital age.

In this paper, the primary objective is to create and validate a predictive model using neural networks to forecast high school students' likelihood of pursuing higher education to contribute to the body of knowledge in educational planning and policymaking. The foundation of the analysis rests upon a comprehensive dataset, encompassing diverse information about 1000 students. Pertinent factors considered include the nature of the educational institution attended, the institutional quality, gender demographics, and other relevant parameters. This study leverages the robust capabilities of Keras, a widely acclaimed open-source library nested within the TensorFlow framework. The modeling approach adopts a neural network architecture, featuring a sigmoid activation function in the output layer. To mitigate the potential risk of overfitting, this study integrates regularization techniques into the model construction process. The dataset undergoes a partitioning into a training dataset, constituting 75% of the samples, and a validation dataset, comprising the remaining 25%. The training process involves the application of the neural network on the training set, facilitating the refinement of the model's parameters. Subsequently, the validation set is employed to assess the model's generalization performance, affirming its efficacy in extrapolating insights to novel examples. This research not only showcases the utilization of cutting-edge machine learning tools but also emphasizes the significance of thoughtful data preprocessing and model validation methodologies. The results gleaned from this study contribute valuable insights into the predictive factors influencing a student's likelihood of pursuing higher education, thereby fostering a nuanced understanding of educational trajectories.

Classified as hallucinogens, psilocybin is a psychedelic drug that affects our psychological processing. Recent studies highlight the benefits of controlled doses utilized as a medication for depression and other mental health illnesses to exert the positives of synthetic medicines without the side effects that often occur. By regulating mood and through various brain mechanisms the drug modifies, the personalities of individuals can improve. Of the Big Five personalities, patients displayed an increase in extraversion and openness levels- possibly through serotonin uptake. Based on varying dosages and environments upon experiment, individuals present a diversified set of results to analyze. Despite evidence presenting support for the usage of psilocybin, research on this subject is limited as studies are heavily regulated and not often approved for further investigation. Additional analysis should be organized before deciding on the legality of this hallucinogen; in the future, when additional evidence becomes available, public opinion on psychedelic drugs may change depending on scientific authentication of advantages and disadvantages regarding the effects of psilocybin. It’s vital to foster an environment where research can be further conducted to fully understand the therapeutic potential and risk associated with use.

Evolution in technology has shown a noticeable gap between Gen X and Gen Z. Both generations manifest excessive screen time. To understand the market research, the focus was on surveys, focus groups, interviews, observations and field trials. The majority of both generations use cell phones over any other electronics. Cell phones are portable, which indicates the immoderate times of screen time. Screen time has proven to damage both mental and physical health of an individual. After reviewing the response survey from both generations, it proved they are entirely dependent on electronics, making this trend irreversible. There has to be a solution to avoid using gadgets, and increase the amount of face-to-face interactions between both generations.

Since there is no cure for Parkinson’s it’s essential detecting the disease early and accurately. However, it’s extremely challenging because brain MRIs in the early stages looks normal to a human eye. Deep learning convolution neural network models using custom and transfer learning approaches were used to detect and classify Parkinson’s disease. MRI images were collected from Alzheimer's Disease Neuroimaging Initiative datasets for both Parkinson’s and control-normal classes. VGG16, ResNet-50 and DenseNet-169 base models were used for the transfer learning convolution neural network study. Transfer learning models VGG16, ResNet-50 and DenseNet-169 achieved score for accuracy and precision of (68, 77), (63, 64) and (81, 87) respectively but their performance was impacted by fewer number of datasets and class imbalances. Siamese neural networks which work well with fewer number of datasets was used in this study. For Siamese neural network, transfer learning approach was used via ResNet-50 for Parkinson’s disease classification. Siamese neural network model achieved on outstanding score for accuracy and precision of (99,99). Siamese neural network approach also detected and extracted the region of interest as the corpus callosum region.

Gaming disorder, which is often associated with an addiction to video games, is characterized by an increasing prioritization of gaming. This issue affects people of all demographics and inhibits one from performing daily activities, leading to increased anxiety and distress. This study outlined the multitude of factors associated with anxiety levels among video game players and a range of demographic and gaming habit variables. By analyzing demographic factors and gaming habits, this research uncovered potential predictors of anxiety levels among those who play video games in order to contribute to a better understanding of general anxiety among certain demographics of video gamers. This paper studied what variables are associated with game players’ anxiety levels. The dataset used in this study consists of 6 groups of variables collected from 13464 users, including Generalized Anxiety Disorder, satisfaction with life scale, social phobia inventory, single-item narcissism scale, gaming habits, and demographics. Correlation analysis and Chi-square tests were conducted to study the association between these variables with general anxiety. This study suggests that younger people as well as females are more prone to developing Generalized Anxiety Disorder. In addition, players who spend more hours playing video games and those who do not have an education degree tend to be more prone to developing Generalized Anxiety Disorder.

Large-scale scientific instruments generate increasingly large amounts for data analysis. Data compression can reduce the data cost by reducing the size of data saved on disks. This paper explores an extrapolation-based compression algorithm commonly used by many state-of-the-art compressors, investigating its performance. The paper develops two extrapolation schemes in C++, linear and piecewise extrapolation, and evaluates their performance on three real datasets. The key finding of this paper is that extrapolation effectively exposes data redundancy, which means data can be better compressed further. However, the best extrapolation scheme to use depends on data characteristics and needs to be chosen carefully to achieve the best performance.

The complexity of the tumor system presents a formidable challenge in developing an optimal cancer treatment. Mathematical modeling and computer simulation are increasingly being utilized to predict tumor growth and investigate the efficacy of cancer therapeutic strategies, such as chemotherapy, in suppressing its growth. Along with laboratory experiments, this approach has been utilized to develop an optimal treatment for individual patients. This paper presents a system of ordinary differential equations consisting of the Gompertz and exponential decay models that describe the dynamics of tumor growth and chemotherapy drug concentration. A numerical method was utilized to simulate and solve the model and was further used to examine the effectiveness of various treatment schedules and dosages in suppressing overall tumor growth. The results suggested that frequent smaller dosages of the chemotherapy drug are more efficient than less frequent larger dosages. This study illustrates the use of mathematical model as a predictive tool to help guide laboratory experiments in developing an optimal cancer treatment.

This review paper focuses on indigenous tribes who inhabited the northeastern part of United States for over ten thousand years prior to European contact in 1620. Our research, which involved consulting various databases such as government and museum sites, archaeological journals, research papers, articles and books on northeast indigenous tribes, aimed to gain an understanding of how these tribes managed to survive for centuries. These tribes acquired knowledge and skills that allowed them to adapt to the changing climate and environment of the northeastern United States which had been evolving significantly since the post ice-age era, beginning approximately 11,700 years ago. These tribes utilized natural resources including native plants and herbs for medicine and developed unique dwelling techniques in construction of their houses in order to survive harsh winters. They used natural flora and fauna such as wild berries, animals and aquatic life for food and other necessities. They developed farming and gardening methods which supported soil conservation and crop interdependencies. These tribes preserved and stored food for winter by utilization of smoking and drying techniques. This research helps to conclude that the indigenous tribes of the Northeast (Algonquins and Iroquois) were advanced societies. They were self-sufficient, and had an impressive amount of understanding about their surrounding natural environment. The age-old techniques and practices used by these tribes can further benefit modern societies including the development of effective therapeutics and support for climate initiatives.

Since 1981, HIV/AIDS has existed as a prominent global epidemic. Throughout the years, research on the disease has greatly improved and expanded as technology has advanced. Because a latent reservoir of dormant viruses persists in the T cells of HIV patients, eliminating these infected cells is a primary goal and challenge for research on the virus. Over the past 40 years, there has been significant research on a variety of potential solutions, yet a functional cure remains elusive. Current antiretroviral treatments can effectively ensure the inactivation of the latent reservoir, but patients must take these medications for life. Therefore, researchers are actively searching for a cure that can either eliminate dormant viruses or assist the immune system in eradicating them once treatment is stopped. The most promising methods include the “kick and kill” strategy to reveal the latent reservoir and remove it and gene editing methods to create immunity to the virus in patients. However, both of these techniques require further study to improve their effectiveness. Based on an evaluation of the current research, a combination of approaches may lead to more effective results. This review also covered efforts to create HIV/AIDS vaccines and improve treatment methods. Due to ethical concerns around testing experimental cures in human patients, the scope of HIV/AIDS research has been limited. Many trials contain relatively small sample sizes and primarily include Caucasian men as research subjects. A resurgence in research efforts and greater inclusion of women and people of color in research may provide greater insights in finding effective solutions.

This study examined the significance and mechanisms of the roles of the determinant factors play in gaining sustainable competitive advantage. The factors include supply chain resilience, performance, and awareness of potential disruptions. The investigation was conducted within manufacturers in the US in the context of their supply chain operations under disruptions. Employing a linear regression on the four factors, this empirical examination shows that supply chain resilience, performance, and awareness of potential disruptions exert positive effects on the improvement of sustainable competitive advantage. Additionally, this study investigated the role of market volatility, which plays a negative role in building sustainable competitive advantage and the role is marginal. The findings of this study offer practical implications to supply chain managers. Limitations of this study suggest future research directions. First, the regression analysis was based on a dataset with small sample size, which might constrain the generalizability of the findings of the investigation. Further research might include a substantial sample size to better represent the manufacturers in the US. Second, inventory management can impose disruptions on supply chain operations and generate ripple effects in a supply chain. However, it is not considered in the study. Future research is expected to assess its role in building sustainable competitive advantage.

Alzheimer's Disease is a degenerative disorder of the brain that results in the deterioration of memory, language, and behavior. The accumulation of a protein called amyloid beta is responsible for the development of Alzheimer's Disease. This protein forms plaques in the brain, obstructing communication between neurons and playing a crucial role in the progression of the disease. Potential treatments aiming to reduce the presence of beta amyloid plaques include immunotherapy (both active and passive), enzymes that degrade beta amyloid, and inhibitors of beta secretase. Unfortunately, effective treatments for Alzheimer's Disease are currently unavailable due to the severe side effects and limited effectiveness of existing options. As Alzheimer's Disease is influenced by various factors including but not limited to amyloid beta proteins, a comprehensive study that includes clinical trials becomes vital in finding an effective treatment. Clinical trial data suggests that beta amyloid degrading enzymes show the most promise as a future treatment, as they have successfully reduced amyloid beta plaque levels in the brain with minimal side effects compared to the other treatments. This review aims to provide a basic understanding of Alzheimer's Disease by exploring the interactions between neurons, amyloid beta proteins, and other internal factors that contribute to the disease's development. Additionally, it highlights three potential treatments and their approaches to preventing or reducing amyloid beta proteins, supported by relevant clinical trial data. Finally, the review discusses the side effects and limitations of current treatment options while considering the potential of becoming viable future treatments.

Understanding the various stages of sleep is crucial in diagnosing and treating sleep disorders like insomnia and sleep apnea. The current methods used to determine sleep stages involve using a polysomnogram (PSG), a sleep diagnostic tool in healthcare, to examine a patient’s activity throughout their sleep. In a polysomnogram study, an electroencephalogram (EEG) records the brain's electrical activity to determine signal amplitudes at various frequency bands (e.g., alpha, beta, theta, delta). Sleep technicians then examine electroencephalogram data to determine each sleep state during the patient’s sleep. However, this process is labor-intensive. This paper investigated spectral and temporal features of a group of patients' electroencephalogram signals, such as the amount of frequency present and its changes and behaviors over time. It is revealed through the paper’s results that analyzing these features with a classifier would provide experts with a more efficient way to score sleep. Distinguishing corresponding sleep stages from wake/sleep characteristics would give physicians a more accurate and accessible scoring system than existing human performance sleep scoring methods. This research anticipates a transformation in healthcare by increasing productivity in sleep scoring, allowing patients with severe sleep disorders to be diagnosed and treated faster. By creating a classification system that categorizes each sleep stage, this paper provided a way for physicians to move from tedious human sleep scoring to automatic sleep scoring, improving patients’ sleep-based health issues.

Eighty nine children were recruited for the study during the child’s routine asthma clinic visit by their provider. Everyone between 7 and 13 years of age were eligible. Those children and parents who agreed to participate were introduced to the study team waiting in a conference room where the study occurred. Pulmonary Function Tests were collected to provide the biological function of the child’s lungs. In return, the child would receive a $10 Amazon gift card. The child completed the first activity by replicating the Asthma Control Test and the second activity by filling out the new survey tool, the Child Asthma Severity Tool. Results showed that the Asthma Control Test is significantly correlated with aspects of the Pulmonary Function Test but more importantly, it showed that the Child Asthma Severity Tool is significantly correlated with the Pulmonary Function Test.

Cyberbullying on social media platforms recently became a serious social issue with significant psychological impacts on individuals. This study focused on cyberbullying detection on multiple social media platforms. A related dataset was acquired from Hosseinmardi et al., and the research was conducted based on this dataset. The methodology combined both deep learning and traditional machine learning models. Experiments were conducted with various machine learning algorithms, including logistic regression, random forest, support vector machine, and Naive Bayes classifier. The DistilBERT transformer model was tested alongside these machine learning models. In the end, the Naive Bayes classifier outperformed the other models, including the transformer model, with an accuracy of 95.83%. The results indicated that while complex deep learning models like DistilBERT were often superior for natural language processing tasks, probabilistic models like the Naive Bayes classifier could sometimes yield better results. The insights from this study contributed to the broader understanding of cyberbullying detection and paved the way for future research to integrate multimodal data, explore real-time detection systems, and more.

This research paper explores the multifaceted economic impact of chess, spanning its historical foundations, cognitive and educational contributions, and its evolution into a digital and commercial powerhouse. Tracing the game's origins to ancient India, it highlights how chess catalyzed cognitive growth, becoming a solid investment in education. The study meticulously analyzes the economic stimulation generated by chess tournaments, from local events to the prestigious World Chess Championship. The digital disruption is examined through the lens of online platforms, revealing a thriving digital chess economy. The paper also delves into the commercialization of chess through merchandise and intellectual property, citing examples like "The Queen's Gambit." The material and methods section outlines a comprehensive data collection and analysis process, with statistical techniques applied to discern trends. The results present a decade-long upward trajectory in the global chess market, reaching 40.5 million enthusiasts in 2022. The discussion contextualizes these findings, comparing them with other research and emphasizing the consistent growth in chess's influence. The paper concludes by highlighting the implications of chess's economic ascent in a rapidly evolving global economy, emphasizing its role as a valuable educational tool and strategic player shaping industries and minds.

Previous studies have concluded that as individuals get older, they become more prone to experiencing loneliness due to significant economical, social, and cognitive changes in their lives. For instance, older adults are more likely to experience more loss in their social network and become reluctant to initiate new networks. Social isolation and loneliness are two major factors damaging elderly adults’ health. With the population of elders aged 60 years and older increasing, it is important to understand the root cause of detrimental senior health outcomes in order to minimize its effects. Despite this, seniors’ health is often neglected compared to other age groups. Due to lack of sufficient and cohesive data, there is a need for a comprehensive review, to gain a better understanding. The objective of this paper is to analyze the correlation between social isolation of elders and various health issues. Loneliness and social deprivation of elders significantly increased the likelihood of psychological, cognitive, and physical health issues, such as depression, dementia, and cardiovascular diseases.

In the current swimming environment, swimmers are placed in lanes based on the timings they had swum in the preliminaries, with the fastest swimmer traditionally being in the middle lanes (lane 4). It is currently known that there is no physical disadvantage to being in the outside lanes, but the psychological effect is not known. This study will be determining if lane placement does play an effect on collegiate-level swimmers in the United States. This study aims to find deficiencies in the National Collegiate Athletic Association’s (NCAA) running of the national swimming championships and remedy them to make swimming a more equitable sport where every athlete is given an equal chance of performing. It was found that no statistical results could be made with a p-value of 0.21, but other conclusions could impact the NCAA and the audience: maintaining audience expectations for a swimmer’s performance and contributing to the scholarly conversation surrounding swimming and the factors that impact swimmers.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) is a relatively new gene editing technology. It can be used in many ways, including cancer research and treatment. CRISPR and CRISPR associated enzymes (Cas) were discovered as an adaptive immune system in bacteria in 2013, and have already been used in clinical trials. In treatment, it binds to or removes mutated genes, canceling their effects. In research, this is used to test the necessity of the gene for cell survival or drug sensitivity. There are still several difficulties in using it, but it is already far better than previous tools, and will become better as research continues.

Shock impact injuries in ice hockey are common, and they cause major brain injuries. Protective helmets can reduce such risks. The purpose of this study was to explore the effects of two types of helmets (with and without a cage) on shock impact to the head. The secondary purpose was to compare the effectiveness of the four different helmets from popular brands (Nike, Bauer, and Reebok), and see which one of the four helmets receives the least amount of shock impact. To test the shock impact on different helmets, they were put on a mannequin’s head. The shock impact was measured by the Vibrometer App by ExaMobile on an iphone. The phone was placed inside the helmet, by the left ear of the mannequin, on the opposite side of the impact. It was hypothesized and found that the shock impact to head was less when the helmet had a cage as opposed to not. Additionally, out of the two helmets with a cage, the shock impact to head was less when Bauer IMS 5.0 brand helmet was used as compared to the Reebok 3K brand helmet. It was concluded that helmets with cages are critical, and youth ice hockey players should use caged helmets that are manufactured by Reebok and Bauer.

Retail inventory management is a crucial part of many businesses due to the high profit associated with it as well as the uncertainty around it, especially for industries with short production cycles and a complex supply chain. Proper management of retail inventories can lead to decreased inventory costs, prevent spoilage and obsolescence, and improve customer satisfaction, all of which lead to increased profits for the company. In this paper, we first stated a well-known inequality. The inequality involves multiple variables and how the maximum/minimum values of a subset of the numbers compare to the maximum/minimum values of the whole set of numbers. After demonstrating this inequality is true, we further proved generalizations of the inequality. With these, we applied our results to the retail inventory management problem. A model for such problem was taken from Ozbay, 2006. Finally, we provided an upper and lower bound for the cost of inventory management. These results might allow companies to make better long term decisions due to the bounds being rigorously proven. However, more work can be done to further improve the bounds in special cases as well as combining the results with other algorithms.

The amount of usable farmland is decreasing worldwide as a result of an increasing global population as well as pollution. This means that we must search for ways to increase the efficiency of our agricultural systems. Industrial indoor farming has significantly augmented efforts to grow unique variants of crops and crops in places where the outdoor conditions do not permit natural field growth by growing crops with LED and fluorescent lights; however, this overlooks the possibility of applying UV light to indoor farming. The UV spectrum includes UVA (λ = 315-400 nm), UVB (λ = 280-315 nm), and UVC light (λ = 100-280 nm). While the ozone layer blocks UVC light, UVA and UVB have been shown to have significant impacts on the development and morphology of various plant species. Red Malabar spinach (Basella alba) is an important crop in combating food insecurity due to its high nutritional value, high growth rate, and many harvestable parts. This research analyzed the effect of growing Malabar spinach under different UV radiation treatments in an indoor farming setting. Plants were grown for two trials in three chambers: white light (control), white light + UVA, and white light + UVA + UVB (sunlight conditions). For the second trial, the distance between the UV lights and plants was halved. Using an ANOVA and post-hoc Tukey test, statistically significant differences in plant height, leaf surface area, and leaf number were demonstrated between radiation treatments. The results of this experiment demonstrated that the UV treatments outperform the standard LEDs for the aforementioned characteristics with the UVA group showing the most growth. This study highlighted the stimulatory effect of UVA light on Malabar spinach growth and demonstrated the potential for incorporating UVA light into indoor agriculture systems to increase crop yields.

Steven Universe, a children’s cartoon show that piloted in May of 2013, is a science-fantasy series written by Rebecca Sugar that follows the adventures of Steven Universe, a half-human half-gem (i.e. alien) who protects Earth from intergalactic threats alongside his guardians, the Crystal Gems. Throughout each successive season, Steven encounters increasingly dangerous villains, learns to navigate the gem powers passed to him from his mother, and is subsequently villainized for her crimes. The purpose of this study was to conduct a film review of Steven Universe to investigate the accuracy of the portrayal of three mental illnesses (i.e. major depressive disorder, generalized anxiety disorder, and post-traumatic stress disorder), in addition to the presence of mental illness stigma. Episodes were chosen solely from the finale season Steven Universe Future, as it depicts the culmination of the trauma Steven endures in prior seasons. Moreover, the criteria for measuring the frequency of these mental illnesses was based on the 2013 Diagnostic and Statistical Manual of Mental Disorders. To determine the presence of stigma, components of the Mental Illness Stigma Framework were observed, namely the stigmatization mechanisms used against individuals with mental illnesses. The results found that a majority of episodes had relatively accurate depictions of the three investigated mental illnessses and were devoid of mental illness stigma. These findings suggest that it is feasible for television and film outlets to portray constructive depictions of mentally ill characters and that, among modern shows, Steven Universe sets a replicable standard for achieving this.

Over the past seven decades, artificial intelligence (AI), specifically AI based on machine learning (AI/ML), has evolved from a mere concept to a ubiquitous force permeating nearly every facet of modern society. Today, many medical devices leverage AI/ML-based technologies to recommend actions and treatments. Because AI/ML technologies inadvertently inherit discriminatory practices from their creators and from the data used to “train” them, bias has been found in a number of medical systems that rely on AI/ML technologies. This bias has directly resulted in the misalignment of treatment offered to people of different races for the same ailment, resulting in the exacerbation of existing inequalities between racial groups and the further marginalization of vulnerable communities including but not limited to women, low-income families, or persons identifying as LGBTQ+. This paper advocates for a comprehensive set of ethical guidelines for development and use of AI/ML-based systems in the medical space to alleviate the presence of racial bias. This paper further presents a systematic review of prevailing ethical frameworks aimed at mitigating racial bias in medical AI/ML domains while proposing avenues for continuous improvement in ethical practices.

Artisanal and small-scale cobalt miners in the Democratic Republic of Congo (DRC) face numerous human rights abuses, including poor working conditions and child labor exploitation. As the DRC remains a global leader in cobalt production, driven by the increasing demand for lithium-ion batteries, concerns over the health and well-being of these miners have escalated. While previous attempts to address the issue, such as Law No. 007/2002, fell short, this research paper proposed a solution centered around international legislative regulations requiring supply chain due diligence and responsible cobalt standards. This research paper examined the effectiveness of supply chain due diligence through a case study of two artisanal and small-scale mining sites in the DRC. Results revealed that implementing due diligence significantly curtails common human rights violations, such as child labor, by enforcing strict age control systems. Moreover, supply chain due diligence improves health and safety conditions in artisanal and small-scale mines, thus reducing occupational accidents and mitigating health risks associated with elevated cobalt exposure. Despite a counterargument questioning the efficacy of due diligence initiatives, the paper highlighted the adverse welfare impacts of eliminating ar mining, emphasizing the need for sustainable solutions. The proposed implementation involves an international cobalt supply chain management system, promoting ethical and safe standards for cobalt mining. While short-term challenges may arise during the certification process, strict enforcement of supply chain due diligence promises long-term benefits for artisanal and small-scale cobalt miners in the DRC. By safeguarding their human rights and improving working conditions, this solution aims to balance economic demands and social responsibility in the cobalt mining industry.

The purpose of this study is to determine the effects of ethanol (EtOH) on the regeneration and reaction time (RT) of Dugesia tigrina. Studies have shown that ethanol can negatively influence planaria’s brain function and increase regeneration time. Forty, randomly-selected planaria were assigned to four concentrations of ethanol (0%, 0.01%, 0.1%, 1%). The planaria were exposed to their designated concentrations and then decapitated. The planaria’s lengths (head and tail) were measured on Days 0, 4, 8, 12, and 16. Results showed that as the ethanol concentration increased, the length regenerated decreased. However, results were shown to only be statistically significant when ethanol concentration was at its highest (1%) signifying that low and moderate concentrations of ethanol did not affect planaria regeneration. The tail of the planaria generally regenerated slower than its corresponding head. After the initial regeneration experiment, in order to observe ethanol’s effect on planaria reaction time, planaria were placed in a Y-maze with negative (light) and positive (hard-boiled egg yolk) reinforcements. The groups that were exposed to higher ethanol concentrations took a longer time to complete the maze, displaying a decrease in their reaction time and mobility. Results were significant in the 0.1% and 1% groups. Ethanol has been shown to decrease planarian regenerative abilities as well as their reaction time and mobility. Due to the similar central nervous system between humans and planaria as well as planaria stem cells sharing at least one gene with those of humans, findings can support and reveal the harmful effects of alcohol on regenerative processes, motor function, and reaction time within humans.

This study examined if there were associations between poor mental health and vaping behaviors controlling for sex and sexual identity. Given the public health implications, this research study provided insights in identifying potential higher risks youth for planning targeted public health interventions for youth. National data in Youth Risk Behavior Survey High school student survey for 2021 were used to analyze the data. Baseline statistics were carried out and used chi- square to test for differences. Statistical analysis were carried out using Epi Info 7 software. Sexual identity and sex were controlled for in the study and odds ratios were calculated for subgroups. The latest YRBS data was analyzed to explore association between vaping and mental health controlling for sexual identity. Twenty nine percent of youth reported mental health was most of the time or always not good. The prevalence of poor mental health was 29.3%. Forty four percent of gay or lesbian youth reported poor mental health.  Highest reports of ever vaping reported among female youth (41%) and bisexual youth (49%) and current vaping were among females (21%) and bisexual youth (29%). Through analyzing 2021 YRBS data, bisexual youth were more likely to have ever used electronic vapor products than heterosexual youth. The results demonstrated an association between poor mental health and vaping. Statistically significant groups were who were found to have an association between reports of vaping and poor mental health were all youth with other/questioning youth reporting strongest association. These findings point for the need for improved school–based services for mental health and the need for schools to provide vaping cessation services or referral systems to community resources. These findings of association between vaping and mental health were consistent with previous studies.

Previous research has concluded that a correlation exists between stress and burnout within adults in high stress working environments. Stressors such as pressure, performance anxiety, psychological distress, and an intense workload can result in feelings of inadequacy, reduced ideas of accomplishment, and more frequent tendencies to become overwhelmed. However, research is sparse on understanding the relationship between stress and burnout within adolescent student-athletes. As adolescents live majorly different lives than adults, perceived stressors may affect the development of burnout differently than prior research suggests. The current study aimed to investigate the impact of high stress on academic, athletic, and general burnout in student-athletes, and how such burnout can impact overall performance. The current study sought to evaluate the extent to which burnout arises in response to various stressors in student-athletes aged 13-18. Particularly, this study explored the impact that external pressures may contribute to burnout. Adolescent student athletes surveyed (N=11) responded to questions regarding perceived stress and life stress, feelings of inadequacy, varying performance goals, and external pressures. Particularly, this study explored the impact that overworking and external pressures may have on the development of burnout and aims to replicate the association between stress and burnout in adolescents. Findings suggested that increased external stressors, like parental pressure, academic pressure, and athletic pressure, is a significant predictor of academic burnout. Additionally, the study found associations between age and perceived stressors. This work suggested adolescent athletes face unique stressors and more work is needed to understand and intervene to prevent burnout.

The general population has many concerns about Electric Vehicles (EVs), but the concerns are significantly different for various income groups. This paper analyzes the concerns of a specific income group about purchasing a battery-powered electric vehicle. While previous studies have investigated people’s concerns regardless of income, this study offers novel findings on high-income suburban individuals’ sentiment. A 10-question google forms survey was sent out to collect data on EV perception. Based on the results, a T-test was used to see the differences in concern ratings between high-income EV owners and high-income non-owners along with differences in concern ratings in two different suburbs (West Windsor and Plainsboro, NJ, and Frisco, Texas). Interestingly, it suggests that the differences in ratings for apprehensions related to charging and battery efficiency are statistically significant(higher) for EV non-owners compared to owners. In addition, findings also suggest that Initial Cost is a concern for non-owners, but its rating is very similar to that of owners, suggesting that it isn’t the primary reason for non-purchase of an EV. The conclusions of this study can facilitate further research in areas focused on educational and awareness building campaigns to address the key concerns regarding EV adoption along with future studies on EV perception.

Studies indicate that high protein consumption increases risk of cardiovascular disease, while high saturated fat consumption reduces risk. The effects of these diets on left-ventricular hypertrophy remain unknown. This study examined the effects of high protein and high saturated fat diets on left-ventricular hypertrophy in C. elegans. Two experimental groups mutated with left-ventricular hypertrophy (JM311 strain) were fed either high protein or high saturated fat diets, while two control groups of JM311 worms and N2 wildtype worms were fed OP50 diets. It was hypothesized that worms fed high fat diets would have less severe left-ventricular hypertrophy than the worms fed high protein diets. Egg viability assay results showed lower egg counts in JM311 control strains (16.33±0.31 eggs) compared to control N2 worms (34.67±0.92 eggs). The high saturated fat diet groups had higher egg counts (32.33±0.28 eggs) than high protein diet groups (26±0.36 eggs). The number of eggs laid by the high saturated fat worms was significantly higher than those of the high protein worms (p=0.03826). The number of eggs laid by both high saturated fats (p=0.65) and the high protein worms (p=0.1642) did not significantly differ from the N2 wildtype group suggesting that high saturated fat and high protein diets can enhance recovery rates in left-ventricular hypertrophy patients, with high saturated fat diets having a more significant effect on recovery rates. These results provide insights on potentially beneficial dietary approaches to clinicians treating patients with left-ventricular hypertrophy.

In this essay, we traversed the journey of Native American languages from the boarding school era to the present day. We delved into the strategies employed by the U.S. government to steal indigenous voices, the tragic and on-going impact of these policies, and resilience and creativity that has gone into linguistic revival. Looking at the state of indigenous languages today, we explored the varying ways that indigenous communities have endeavored to revive their languages and found cause for hope. Specifically, we looked to the case of the Ojibwe Nation as a model of exemplary language revitalization and examined that its combinations of institution-based support, innovative use of technology, and grassroots movements can serve as a template for further revitalization efforts.

Since recent years have brought popularity to new media platforms, this paper aimed to explore its impact on Parasocial Relationships. Thus, as the ease with which adolescents can access these platforms today influences their likeliness to form parasocial relationships, the research question was asked: To what extent do parasocial relationships grow due to heightened Twitch, TikTok, and Twitter usage? To answer the question, a qualitative data collection method of surveys was utilized. It was concluded that increased social media usage causes the proliferation of parasocial relationships as adolescents increased social media use establishes a sense of intimacy between themselves and media personalities. These platforms allow celebrities to present a candid, “behind-the-scenes” view of their daily life, which provides viewers with the ultimate intimate details of their existence which reinforces the emotional connections and illusions created and then fostered by a parasocial relationship.

Takashi Murakami fundamentally influenced contemporary Japanese art, creating a new art movement called Superflat. This paper explores his artworks through art historical methods of formal analysis to highlight how Murakami not only “infiltrate[d] the manga and anime fan communities with his art, he also managed to throw popular culture into the realms of fine art.” .This assertion is supported by a visual analysis of three Murakami artworks: My Lonesome Cowboy (Sculpture made of oil, acrylic, fiberglass and iron, 100” x 46” x 36”, 1998), Mr. Rainbow Dob (Offset lithograph, 26.8” x 26.8”, 2006) and Superflat my first love flowers (Archival pigment print, 29.5” x 29.5”, 2020). These artworks showcased the incorporation of traditional Nihonga aesthetics for which Murakami is formally trained into which he blends popular culture elements like manga and anime, creating the SuperFlat art form and new Japanese identity through mass merchandizing. The paper concludes that Murakami was a driving force of Japanese contemporary art and identity while providing suggestions for further research.

As cancer cells grow uncontrollably and spread to other parts of the body, partly due to the mutation of the p53 proto- oncogene. The mutated p53 proto-oncogene, also known as the p53 oncogene, can no longer regulate cell cycles, allowing for cells with damaged DNA to proliferate. The p53 oncogene can be inhibited by different extracted concentrations of curcumin on zebrafish embryonic models of cancer, as observed through mutations in developing embryos. Zebrafish embryos are an excellent in-vivo modeling tool because 84 percent of the genes known to be associated with human diseases have a zebrafish counterpart. Zebrafish are useful to understand the dynamics of early- stage cancers, especially since they overexpress the p53 oncogene; when this is suppressed, gross mutations of the embryo result. Data for each concentration of curcumin was graded 72 hours post fertilization (hpf) by the severity of several phenotypes (bent or hook-like tails, spinal column curving, sac mutation (reabsorption), shorter body length, or no mutations). Results of the experiment showed that increased concentrations of curcumin, which acts as an anticancer agent, led to more severe mutations, indicating a higher absorbance of curcumin by cancer cells, thus suppressing the overexpressed p53 oncogene.

This paper presents the findings of a secondary research study conducted to investigate the antibacterial potential and phytochemical composition of four indigenous Indian medicinal plants, namely Salvadora persica (Miswak), Caesalpinia pulcherrima (Peacock flower), Thymus vulgaris (Thyme), and Saussurea lappa (Kuth). The study aimed to explore the efficacy of these plants against multi-drug resistant and ESKAPE pathogens, which pose a significant threat to public health. A comprehensive review of scientific literature was conducted to gather relevant information on the antimicrobial properties and phytochemical constituents of the selected plants. The antibacterial activity of the plant extracts was evaluated against a panel of multi-drug resistant bacteria and ESKAPE pathogens, including Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species. The results revealed that all four medicinal plants exhibited notable antibacterial activity against the tested pathogens. Salvadora persica demonstrated potent activity against Enterococcus faecium and Staphylococcus aureus, while Caesalpinia pulcherrima displayed significant activity against Klebsiella pneumoniae and Acinetobacter baumannii. Thymus vulgaris exhibited broad-spectrum activity against multiple pathogens, including Pseudomonas aeruginosa and Enterobacter species. Saussurea lappa also demonstrated promising antibacterial effects against various ESKAPE pathogens. Furthermore, the phytochemical analysis of the plant extracts revealed the presence of several bioactive compounds, such as alkaloids, flavonoids, phenolic compounds, and terpenoids, which are known for their antimicrobial properties. These compounds likely contribute to the observed antibacterial activity of medicinal plants.

Trihalomethanes (THMs), which are likely to cause cancer in humans, are frequently detected as disinfection by-products (DBPs) in public water systems (PWS). A recent study revealed that regions with higher incomes typically had lower THM levels in New York State, potentially suggesting a socioeconomic disparity concerning the quality of drinking water. Expanding on this crucial discovery, our research sought to lead the development of an Environmental Justice (EJ) Index for evaluating drinking water quality, using THM concentrations as the primary metric. Our hypothesis centers on utilizing THM concentration as an environmental indicator to address issues of environmental justice, given the health risks associated with THMs and their susceptibility to socio-economic and environmental factors in communities. The step-by-step creation and practical application of an EJ Index for THMs has been demonstrated, highlighting the suitability of THMs as an EJ indicator. Through this comprehensive approach, our research aimed to initiate the inclusion of a water-quality related EJ index in the current U.S. EPA’s thirteen EJ indexes which lack adequate representation of water quality in communities.

Parkinson’s Disease is a chronic neurodegenerative disorder that causes uncontrollable movements in the body, including tremors and impaired balance. As of today, there is no cure for Parkinson’s Disease. While there are treatments such as Levodopa that can be used to slow the progression of the disease and control certain symptoms, it may not always be effective. Therefore, early detection of the disease is crucial. However, as the diagnosis of Parkinson’s Disease heavily relies on subjective physician judgment and rarely on clinical tests, detecting Parkinson’s Disease at an early stage is often challenging, inaccurate, and inconclusive. One possible way to detect Parkinson’s Disease both early and accurately is through the detection of abnormal saccadic intrusions – in this case, slow saccades. This study used Dai and colleagues’ algorithm based on the implicit piecewise polynomial approximation model, which includes the nonlinear denoising step and basic velocity-threshold step that helps detect slow saccades with high precision, to prove how it could be used to diagnose Parkinson’s Disease early.

The human immune system consists of a complex network of cells, tissues, organs, and substances that help the body protect itself from infectious diseases. Simultaneously, the immune system cells can recognize and remove damaged or abnormal cells with the potential to become cancerous. Early Greek physicians discovered that maintaining a healthy immune system is crucial to survival and unhealthy food consumption can undernourish the immune system and cause a state of failure. In a weakened state, the body can be infiltrated by several harmful pathogens. Specifically, Asian populations in  Mongolia, Bangladesh, the Maldives, and Japan have higher rates of liver, oral, nasopharyngeal, and stomach cancer cases, which all stem from the body’s digestive system. These cancers can form when a balanced diet is disrupted. Commonly eaten foods in these countries have been proven to impair the immune system’s ability to attack cancer cells. More research is needed to fully understand the relationship between per capita food consumption of commonly consumed foods and cancer rates, and understanding this relationship could allow these populations to avoid overconsumption of harmful ingredients. This research paper examines the correlation between the most consumed foods in these specific countries and the respective high prevalence of cancer. The findings are promising and can be used to spread awareness on this issue in hopes that preventative action is taken to have populations reduce their consumption of such foods.  

To remedy its lack of affordable housing, the state of California has passed legislation aimed at implementing fair housing principles, including rules that require the creation of low-income housing in cities throughout the state. In San Ramon, a new development plan has been approved which will create thousands of housing units, retail developments, parks, a new hotel, and parking amenities. Called CityWalk, the new development projects a vision of a “walkable city,” one in which people can live and work in the same district, never having to commute by car again. The reality, however, is that San Ramon’s housing prices are likely inaccessible for the workers that CityWalk is hoping to attract -- the retail salespeople, restaurant cooks and servers, hotel maids and janitors, among other low-wage employees, who might actually work in the immediate vicinity. Several methods were used to determine whether or not CityWalk will meet the needs of the workers who need housing, gauge the level and possible ramifications of community and stakeholder input into the project, and shed light on the broader question of whether affordability thresholds based on relatively high percentages of area median income make sense in the context of highly polarized, post-industrial economies. American Community Survey data from 2020 was analyzed to profile the incomes, existing housing characteristics, and commute times of both the current residents of San Ramon and the workers who currently commute to the area. That data was juxtaposed with economic data from the state of California describing the median wages in the area for people holding the jobs CityWalk hopes to create. Finally, meeting minutes from San Ramon’s planning meetings were analyzed to measure the degree of stakeholder involvement in the planning process. Approximately 0% of the San Ramon workers eligible for the affordable housing units at all three levels could afford those units when affordability was defined according to the federal definition of ‘rent burden’ (no more than 30% of income spent on rent). Opening the aperture to include workers who might improve their rent burden (by paying less than the Bay area average of 44% of income on rent) while still devoting high proportions of their income to rent still yielded very small slices of the worker population who might benefit: approximately 12%, 16%, and 14% of the work force, depending on the affordability level. Examination of the 351 relevant meetings held by San Ramon from 2019 through 2022 yielded only 44 mentions of the CityWalk project, for an average of one mention every eight meetings. Throughout the process, no more than 103 citizens participated, or less than one person, on average, every three meetings. This study concludes that the affordable housing allocation in the CityWalk project will serve neither the workers who will staff the central business district nor the current residents of San Ramon, a pattern likely to limit the utility of California’s affordable housing rules in any wealthy enclave. Furthermore, San Ramon’s planning process did not successfully gather input from either city residents or commuters the city sought to target. This research accordingly suggests policy makers and citizens alike may need to think deeper about both the execution and impacts of affordable housing in wealthy California towns.