MENTAL HEALTH OUTCOME DISPARITIES IN CHILDREN WITH A HISTORY OF MALTREATMENT: A QUALITATIVE STUDY

Child maltreatment is a widespread social issue that leads to lasting effects that include perpetuating cycles of violence and can lead to long term problems in adulthood. The presented study aims to focus on describing the mental health outcome disparities in children who have experienced child maltreatment. Although existing studies have addressed mental health outcomes, previous work has overlooked the disparities between children who have experienced maltreatment and children who have not. This qualitative study will collect data using interviews and utilize thematic analysis to analyze the collected data. This research will enhance understanding of the impact of child maltreatment and highlight the importance of prevention and intervention strategies in addressing this issue

E-payment Systems Use: The Role of Cybersecurity Risk and The Moderating Effect of Risk Propensity and Technology Readiness

Advances in digitalization have accelerated consumer migrations away from traditional cash- and check-based payment systems towards electronic payment systems worldwide. Yet, many people still remain resistant. This study examined the role of motivational and inhibiting factors and their interaction effects on the use of e-payment systems. The findings suggest that perceived cybersecurity risk, risk propensity, trust in the companies offering the e-payment services, and technology readiness have a significant direct impact on the use of e-payment systems. The findings also suggest that risk propensity and technology readiness have a tempering effect on the negative impact of perceived risk. The study discussed the practical and theoretical implications of the research

SLEEP DISTURBANCES IN PARKINSON’S PATIENTS WITH A HISTORY OF HEAD INJURY

Sleep disturbances are among the most prevalent and burdensome non-motor symptoms of Parkinson’s disease (PD), yet the contribution of prior traumatic brain injury (TBI) to these problems remains poorly understood. The purpose of this study was to examine whether the number and severity of lifetime head injuries predicted sleep disturbances in individuals with PD. Data from 3,055 PD patients enrolled in the Fox Insight study were analyzed, including 1,593 with a history of head injury. Participants completed self-report questionnaires assessing head injury history, motor and cognitive symptoms, and sleep disturbances. Generalized linear mixed models tested whether head injury history and severity indicators (loss of consciousness, hospitalization, and cognitive complaints) predicted five sleep outcomes: insomnia, excessive daytime sleepiness (EDS), restless legs syndrome (RLS), vivid dreams, and dream enactment. Results showed that a greater number of head injuries significantly predicted higher rates of insomnia, while loss of consciousness predicted greater dream enactment. Hospitalization showed no effect, and unexpectedly, fewer cognitive complaints were associated with more frequent sleep disturbances, potentially reflecting anosognosia or symptom underreporting. These findings suggest that TBI contributes selectively to insomnia and dream enactment in PD, underscoring the need for routine screening and targeted interventions to improve quality of life and reduce fall risk in this population

Determinants of Digital Piracy: An Integrated Model

Digital piracy is a form of copyright infringement, and challenges persist in addressing it effectively. Accordingly, understanding why people engage in digital piracy is crucial. Although prior studies have examined digital piracy from multiple perspectives, existing studies on the explanatory factors of digital piracy remain fragmented. To address this research gap, this study develops an integrated model that incorporates key theoretical perspectives, neutralization theory, social learning theory, and the theory of planned behavior (TPB), along with key determinants including gender, age, and the technology factor. Rather than conducting a meta-analysis of previous studies, this study adopts a survey-based approach to examine the effects of these factors on digital piracy. We collected our data through a survey and used t-tests, ANOVA, and logistic regression to analyze it. The results indicate that gender, age, the neutralization factor, and the social learning factor have significant effects on digital piracy. Specifically, gender, the neutralization factor, and the social learning factor play a crucial role in the use of BitTorrent for engaging in digital piracy. In contrast to prior research, this study shows that the technology factor does not have a statistically significant influence on digital piracy. This study advances digital piracy literature by offering an integrated model and a comprehensive analysis of the factors influencing digital piracy, thereby addressing the limitations of prior fragmented research that focused on a narrow set of factors and theoretical perspectives. Practically, by integrating these findings, administrators and policymakers can develop more precise interventions to discourage digital piracy, ultimately reducing digital piracy behaviors

Wings of Perception: Investigating Customer Sentiments in Indian Aviation Sector

India\u27s aviation sector, a key contributor to the nation\u27s economy, has experienced rapid growth, supporting nearly 7.5 million jobs and contributing approximately $30 billion annually to the GDP (Gross Domestic Product). The growth, driven by increased demand for air travel and government incentives, has resulted in more competition among carriers. In the competitive market, it is necessary to understand customer preferences to enhance the quality of service and maintain a competitive edge. The dissemination of customer opinions on social media and review platforms offers airlines the opportunity to access passenger views. However, extracting useful information from this unstructured data is challenging. Previous studies had not accounted for variables such as seasonal fluctuation in opinion and the impact of specific service features on customer satisfaction. This study fills the gaps by employing sentiment analysis tools, including TextBlob and VADER (Valence Aware Dictionary for Sentiment Reasoning), to analyse customer opinions from platforms like X, Skytrax, and TripAdvisor. The study process involves data collection through automated web scraping tools, followed by data cleaning and text analysis to tag sentiments and identify variables influencing customer emotions. Key findings indicate that carriers like IndiGo and Vistara are highly rated by customers for punctuality, service quality, and operational consistency. Conversely, Air India and SpiceJet are faulted for delays and inefficiency. Seasonal patterns further indicate that negative sentiments are greater during peak travel seasons. The study highlights the importance of customer-centric initiatives, operational efficiency, and advanced analytics to boost brand loyalty in a highly competitive market

The Intricate Dance Between Stars and Words: A Review of Customer Reviews in Tourism

Travel and tourism industries rely heavily on customer reviews from past travelers as an invaluable source for informing potential travelers’ decisions. Thanks to the internet, reviews are an invaluable source for both quantitative star ratings as well as qualitative text comments that evaluate travel experiences. In this paper we analyse this complex relationship between text comments and their associated star ratings; using existing literature we highlight their interplay to give an overall picture of customer satisfaction. Factors that influence ratings and comments include both intrinsic (service quality, staff behavior) and extrinsic aspects such as location or price. Sentiment analysis through Natural Language Processing (NLP) helps interpret emotions or opinions expressed through comments to correlate them with star ratings. Review platforms such as TripAdvisor are key resources for travelers; however, they also face issues of biases or fake reviews that require further attention. This review emphasises the significance of taking both quantitative and qualitative aspects of customer reviews into account in tourism, providing valuable insights as well as uncovering gaps that require further exploration - for instance, specific travel styles, deeper qualitative analyses, cultural differences, or language barriers that need further investigation. Future research must extend beyond English reviews into non-English reviews from different travel segments as this could enhance decision-making and customer service in tourism businesses; by filling in gaps this could allow better customer understanding leading to increased satisfaction with services and informed decision-making by businesses. As this review concludes, its significance lies in emphasizing both quantitative and qualitative aspects of customer reviews in the tourism industry is clear. By filling any identified gaps through further research efforts, tourism organizations can deepen their understanding of customer experiences resulting in more informed decision-making processes and enhanced customer satisfaction ratings

A QUALITATIVE METHOD STUDY ON SERIOUS MENTAL ILLNESSES SEEING IN HOMELESSNESS

Homelessness is a serious social problem influenced by various factors, specifically serious mental illnesses (SMI’s). Based on past studies, there is limited research that explains the quality of mental health services for individuals who are unhoused with SMI’s. The purpose of this research was to explore mental health services among the unhoused population who have serious mental illnesses (SMI’s) (from the perspective of social service providers). The study was a qualitative method design which provided a rich in-depth description through interviews. The study answered the following research questions: What is the perception of mental health services among homeless groups in California? What are effective ways to make homeless services accessible for the population? The researcher conducted the study on a single point of time to focus on social service providers and their interactions with the unsheltered population. The researcher recruited five participants for sampling, using snowball sampling, who were licensed clinical social workers and social service providers. Findings were that five major themes were gathered from the interview data which were barriers to access, building trust, stigma around mental health, effectiveness of outreach and flexibility, and comprehensive and collaborative care. The study established a better understanding of the quality of mental health services, specifically by identifying how homeless individuals perceive mental health services and ways to make homeless services accessible to the population. Findings from this research can contribute to positively informing better social work practices when providing support to the unhoused population

NTIER CODE GENERATOR

This project presents a software tool designed to automate the generation of standardized code for all layers of an n-tier architecture, including the Database Layer, Data Access Layer (DAL), and Business Logic Layer (BLL). By employing object-oriented principles and parsing the database structure, the tool ensures modularity, scalability, and maintainability. It efficiently formats code templates for CRUD operations, enhancing development efficiency and consistency, while streamlining database interactions and enforcing business rules. This project presents an innovative software tool designed to automate the generation of standardized code for all layers of an n-tier architecture, including the Database Layer, Data Access Layer (DAL), and Business Logic Layer (BLL). By employing object-oriented principles and parsing the database structure, the tool ensures modularity, scalability, and maintainability of the application. The tool efficiently formats code templates for CRUD operations, which stands for Create, Read, Update, and Delete functionalities, enhancing development efficiency and consistency across various projects. Its ability to streamline database interactions and enforce business rules is particularly noteworthy, as it significantly reduces development time and potential for human error. Moreover, the nTier code generator offers immense value by ensuring that the generated code adheres to best practices and industry standards, thus promoting high-quality software development. By maintaining synchronization across all layers of the application, it provides a robust foundation for future modifications and extensions. The n-tier architecture model itself is a sophisticated design pattern that separates an application into multiple layers, each with a distinct responsibility. Typically, it consists of the Presentation Layer (PL), Business Logic Layer (BLL), Data Access Layer (DAL), and Database Layer. The Presentation Layer is responsible for user interaction, the Business Logic Layer handles core application logic, the Data Access Layer interacts with the database, and the Database Layer stores structured data. By adhering to this architecture, the project not only ensures a well-structured and organized codebase but also facilitates easier maintenance and scalability. The automated code generator represents a significant advancement in software development tools, offering developers a powerful resource to enhance their productivity and the overall quality of their applications

DEGRADATION OF MARTIAN GLACIER-LIKE FORMS IN RELATION TO THE OBSERVED EVOLUTION OF EMMONS GLACIER ON MOUNT RAINIER, WA

This study establishes parallels between the observed degradational evolution of debris-covered glaciers on Mount Rainier, WA and select glacier-like forms (GLFs) by studying the time-varying morphologies of the debris cover. Mount Rainier is home to 28 debris-covered valley glaciers, including Emmons Glacier which has a history of orthoimages taken from 1951 to 2023 and high-resolution Digital Elevation Model (DEM) coverage of 2008, 2021 and 2022. We can observe the degradational evolution of Emmons Glacier through orthorectified black and white imagery collected from an airborne platform and the National Agricultural Imagery Program (NAIP) colored satellite images periodically collected over the last 72 years. GLFs in the Mars mid-latitude areas are indicative of past ice flow based on visual interpretations of their overall forms and from surface textures that are similar to glaciers on Earth. On Mars, GLFs are the smaller flows by area that appear most similar to debris-covered valley glaciers on Earth. Morphological textures discernable in tonal and spatial variation display supraglacial landform evolution of debris-covered glaciers on Earth, including Emmons Glacier on Mount Rainier observable at the meter scale with DEMs. Observations of Emmons Glacier show that these textures—such as crevasses, ridges, and moraines—develop and degrade over time as ice thins and debris accumulates. These evolutionary stages provide a baseline for interpreting similar textural patterns in Martian GLFs, suggesting that these Martian features may represent advanced stages of degradation, potentially analogous to the later stages observed at Mount Rainier

CHALLENGES THE SPORTING INDUSTRY FACED DURING COVID-19 ON FAN ATTENDANCE: THE CASE OF THE NATIONAL BASKETBALL ASSOCIATION

This culminating experience project investigates the challenges the sporting industry faced during the COVID-19 pandemic, with a focused look at the National Basketball Association. The research questions are: (Q1) How did the NBA arena shutdowns impact fan attendance for each team during the COVID-19 pandemic? (Q2) What factors influenced NBA arena attendance before the COVID-19 shutdowns? (Q3) What factors influenced NBA arena attendance after the COVID-19 shutdown? The data collected includes all 30 NBA teams from 2019 through the 2024 seasons. The research questions were analyzed using multilinear regression analysis and comparison of attendance data over 6 seasons including the immediate seasons before and after the COVID-19 pandemic. The findings and conclusions for each question are: (Q1) Involves comparing the seasonal attendance data for each team and the percentage change between each year, highlighting the pivotal 2021 pandemic year. (Q2) A focus on factors that influenced NBA attendance before the shutdowns, with a focus on arena capacity, winning percentage, key performance statistics per game, and revenue. (Q3) A focus on factors after the shutdowns, with statistical analysis of models comparing the NBA with the MLB, MLS, and NFL