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Navigating Stigma and Privacy: Health-Related Communication Among Bangladeshi Women
No full textWomen in Bangladesh often silently bear the burden of stigma tied to their bodies, minds, and societal roles. This study examines the coping strategies women use to manage health-related stigma and their privacy while facing issues like reproductive health, mental health, and postpartum challenges. The study was conducted by utilizing in-depth interviews with 17 Bangladeshi women. Stigma Management Communication Theory (SMC) and Communication Privacy Management Theory (CPM) are the two frameworks that guided the study. The findings of the study reveal that stigma often silences women and threatens their social identities, and women feel that having a health problem means they have failed in some way. Therefore, strategies such as, avoiding conversations, distancing themselves from stigma, concealing their struggles, and relying on their own resilience were adopted by women. On the other hand, privacy, closely connected to their stigmatized identity, becomes an emotional labor. The process of choosing people to share private information is not straightforward. It is a risky decision influenced by trust, social judgment, and the need to maintain dignity. This study highlights women\u27s voices and adds to health, stigma, and privacy research in the Global South. It shows how communication can support or challenge stigma
Farmers’ Perceptions About Drivers of Poverty: A Case Study of Cocoa Farmers in Ghana
No full textCocoa farmers in Ghana face numerous challenges that undermine their incomes and living standards, including high labor costs, fluctuating cocoa prices, high cost and limited access to inputs, lack of credit, illegal mining, weather risks, small farm sizes, outdated farming and drying technologies, and inadequate extension services. These issues reduce productivity, lower incomes, and perpetuate poverty. This study examined farmers’ perceptions about the importance of these challenges and assessed possible differences across regions and farm households’ socioeconomic status. In the summer of 2024, data were collected from 400 cocoa farmers in major cocoa-producing areas of Ghana’s Eastern and Ashanti regions. The Best-Worst Scaling (BWS) approach was used to rank the challenges and, thus, identify key poverty drivers. The analysis revealed that farmers perceive labor cost, low cocoa prices, high cost and limited access to inputs, lack of credit, and illegal mining as the top five drivers of poverty. Differences in the ranking of poverty drivers were observed across regions and farm sizes
The Market for Local Beef and Local Beef Processing Investment in Arkansas.
No full textThe COVID-19 pandemic exposed vulnerabilities in the U.S. food supply chain, particularly in the beef sector, where processing bottlenecks and labor shortages disrupted meat production and the market. In response, several policies were implemented to strengthen food system resilience, and significant funding was allocated to expand independent meat processing capacity nationwide. However, the long-term viability of expanding regional processing capacity remains uncertain, notably in Arkansas, a net exporter of live cattle. This study evaluates whether consumer demand supports the expansion of local beef processing in Arkansas. Using a dichotomous choice survey, we estimate market shares for beef labeled “Arkansas Grown” and examine how factors like freezer storage availability influence bulk beef purchasing decisions. By comparing demand estimates to the state’s limited processing capacity, the study helps determine if infrastructure investments align with market interest. The findings provide practical guidance for policymakers and industry leaders seeking to enhance regional food systems
Coastal Consumption: Diet and Social Organization at Four Postclassic Sites in the Yucatán Peninsula
No full textThis research examines Postclassic Maya food practices during CE 1200–1600 to understand how eating behaviors reflect systems of social hierarchy, political economy, and cultural identity. The investigation focuses on four archaeological sites in the northern Yucatán Peninsula—Tulum, El Rey, El Meco, and San Miguelito—to examine dietary behaviors through dental microwear texture analysis (DMTA), oral pathology, and stable isotope data within a biocultural framework. The research aims to identify whether elite and non-elite individuals exhibited notable variations in food texture consumption, access to resources, and nutritional health. High-resolution 3D surface metrology enabled DMTA to assess the mechanical properties of consumed foods, revealing short-term dietary fluctuations. Long-term nutritional stress was evaluated by analyzing dental caries and enamel hypoplasia. Carbon and nitrogen isotope analysis provided insights into protein sources from marine versus terrestrial environments, as well as distinctions between C₄ and C₃ plant consumption. Burial positioning, associated artifacts, and site-level data on political control and trade access were used to contextualize the biological indicators. This multi-proxy approach facilitated a detailed understanding of how diet functioned both biologically and symbolically within complex Maya social systems. The analysis reveals subtle but meaningful differences between elite and non-elite diets, despite minimal statistically significant distinctions. Higher-status individuals may have consumed foods that required different preparation techniques or had access to more nutritionally diverse options, as indicated by microwear texture and pathology data. Lower-status individuals exhibited slight indicators of increased physiological stress. These differences demonstrate how political control, trade connections, and household-level food availability shaped daily life and reinforced social inequality. This research contributes to ongoing debates in bioarcheology and Mesoamerican archaeology by showing how small-scale dietary differences, when interpreted in context, can reveal broader patterns of social differentiation and survival strategies. Food functioned as both a material necessity and a symbolic medium through which political-economic systems were maintained and, at times, contested. The integration of new microwear data with existing isotopic and archaeological evidence provides a more refined understanding of how ancient Maya societies negotiated status, identity, and subsistence through practices of consumption
Optimal & Robust control of a Bidirectional DC-DC Converter in EV Systems
No full textThis paper analyzes the performance of PI, LQR, and H∞ controllers for the regulation of a bidirectional buck boost converter in electric vehicle systems. To get the system state space equations, a continuous conduction average model is linearized. For analysis a PI controller will be used as baseline, the LQR controller will be used to improve transient response, and the H∞ controller will be used for the system robustness and disturbance rejection. The simulation results show that the advanced controllers surpass the PI controller in terms of overshoot, settling time, and voltage ripple, with the H∞ controller offering the best robustness to system variations and load disturbances
The Kids Aren’t Alright
No full textIt is not new that students struggle in law school. Research has shown for decades that, while students generally begin law school with healthy well-being, the competitive nature of law school combined with the stress of the Bar and securing post-Bar employment causes increased anxiety, depression, isolation, and related symptoms among students, especially women and underrepresented groups. What is new is the sheer number of law students struggling with serious mental health challenges today—a number that has reached crisis proportions.
This Article is divided into four parts. In Part I, I explore the mental health landscape for high school, college, and law students as well as practicing attorneys. In Part II, I explore some notable takeaways from the mental health literature, including that more women and underrepresented groups are suffering, and few students are seeking treatment In Part III, I explore research on Gen Z. Finally, in Part IV, I explore research on why law school causes elevated mental health symptoms among students and propose steps law schools and professors can take to improve students’ well-being
Morphology of Smallmouth Bass (Micropterus dolomieu) in Arkansas
No full textThe Smallmouth Bass, Micropterus dolomieu, is one of the most important game fishes in Arkansas. Three distinct lineages are recognized from different river basins: the Northern, Neosho, and Ouachita Smallmouth Bass. Understanding the biodiversity within this species complex inhabiting different water bodies in Arkansas is important for effective management of the fisheries resource and to guide conservation efforts. But current data on distribution of distinct forms are insufficient to guide management. The primary goals of the study presented here was to quantify morphological characteristics to identify distinct lineages of Smallmouth Bass, and to determine their specific locations within Arkansas streams and basins. Meristic counts of lateral line scales collected from 268 individual fish revealed significant differences among basins (Kruskal Wallace Rank Sum test H = 109.183, p \u3c 0.00001). These findings can be applied to identify and distinguish distinct lineages of Smallmouth Bass in Arkansas, and thus are important for guiding conservation strategies
Usage of Natural Language Processing and Deep-Learning Techniques on Thematic Apperception Tests to Predict Big Five Personality Traits
Get PDFThe usage of personality as a method of behavioral prediction and outcomes of success has grown considerably over the last few decades. This project explores predicting user personality profiles via the Big Five personality index through the integration of advanced natural language processing techniques as well as neural networks. Using a dataset provided by Dr. James W. Pennebaker, participants analyze an image—formally referred to as a thematic apperception test—and write a thorough paragraph describing the details. This free-form text, along with their personality test results, is captured in a structured dataset. Many deep-learning and machine learning models have been used in the field of psycholinguistics before, but the usage of the Big Five personality model has been relatively scarce, despite it having the highest validity and reliability amongst modern personality indexes. The proposed model extracts personality using word embeddings while incorporating sentiment concentration, typo density, and other linguistic features to capture meaningful insights from participant responses. These features enable the neural network to identify complex linguistic patterns linked to personality traits, presenting a novel approach that leverages many advancements made in the fields of language analysis, psycholinguistics, and modern applications of machine learning. The model’s performance is evaluated by measuring the Mean Squared Error (MSE) between the predicted Big Five traits and the actual traits obtained from the user’s given quiz results. While there is improvement to be made in expanding the scope and accuracy of the model, this project contributes toward advancing accurate computational approaches to personality assessment in the field of computer science
