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Guatemalan Maya Women’s Attitudes Towards Biomedical Contraception After Migrating to the United States
Get PDFMedical providers in the United States who discuss the use of contraceptives with Maya women migrants might discover strong reluctance and complex beliefs about the social and physical benefits of biomedical contraceptive measures. This research report presents information about contraceptive usage among Maya in Guatemala and how usage or attitudes toward contraception might have changed while living in the United States. The research team, during 2024, interviewed six adult female Guatemalan Maya refugees over Zoom to understand their thoughts toward contraceptive use before and after migrating. Discussion points included: lack of sexual education in Guatemala, health concerns arising from using contraception, correlation between acculturation into American culture and openness to contraception, beliefs about contraceptives that originated in Guatemala, and the impact of religion in their decision to use contraception. This research will help organizations tailor their approaches and interventions to consider the concerns of Maya women, fostering a deeper understanding and effective communication
Book Review: Ch’ul Mut: Sacred Bird Messengers of the Chamula Maya
Get PDFby Maruch Méndez Pérez and Diane Rus University of New Mexico Press, 2023 xli + 365 pp., 75 black-and-white photos, 77 color plates, 4 appendixe
Feature Significance and Explainability in Neural Networks
No full textAs deep neural networks grow increasingly powerful, concerns about their opacity and interpretability escalate, hindering their trustworthiness in high-stakes scenarios. eXplainable AI (XAI) methods have emerged to enhance transparency and accountability in neural networks, emphasizing interpretability through global feature significance, which seeks to quantify feature importance at the dataset level (i.e., across the range of possible model inputs), and local feature significance, which seeks to quantify feature importance at the datapoint level (i.e., for an individual prediction). A critical yet overlooked aspect in local feature significance research, as well as local explainability methods more broadly, is the selection of appropriate baselines for attribution methods. This dissertation addresses these dimensions by proposing rigorous methodologies: (1) a permutation-based testing framework for global feature significance, uniquely permuting the target variable to robustly handle nonlinear relationships and multicollinearity without restrictive assumptions; (2) statistical significance tests and confidence intervals for local feature attribution methods, including Integrated Gradients, DeepLIFT, SHAP, and LIME, providing robust validation of individual feature contributions; and (3) a generative contrastive baseline approach, enabling more precise and actionable explanations. Together, these methodologies significantly advance XAI, integrating statistical rigor with practical applicability to promote transparency, accountability, and responsible use of AI models
Quantifying Uncertainty in Image-generative Models
No full textRecent advancements in deep learning, particularly the development of large language models, have generated substantial interest, yet there remains limited evidence that these technologies consistently fulfill their anticipated potential. While uncertainty quantification has been extensively studied in the context of classification and regression tasks, it is comparatively underdeveloped in generative models, and image captioning models in particular. At present, there is limited consensus regarding appropriate methodologies for quantifying uncertainty in these systems. This research examines existing uncertainty quantification approaches and evaluates their suitability for image captioning models. The findings indicate that current methods are generally inadequate for the generative setting, owing to the conditional and recursive nature of language generation. To address this gap, we conduct experiments involving the generation of structured captions and developed a distributional framework to quantify uncertainty based on the predicted probabilities associated with generated tokens. We find the distributional method works for a limited number of tokens generated. Subsequently, the investigation extends to unstructured captions, wherein we introduce a method for constructing prediction sets around parts of speech, thereby providing a specified level of confidence that the true value resides within the set. These prediction sets can be utilized to score captions, facilitating the identification of captions that warrant further review. This approach not only enables the quantification of uncertainty in generated text captions but also supports the formation of word sets that are most relevant to the image
Improving Rail Resources: The Detroit-Chicago Rail Corridor Upgrade
Get PDFThe Detroit-Chicago Rail Corridor was awarded federal high-speed rail designation in October, 1992. This designation was the end result of a 22-year Amtrak/State of Michigan partnership created to improve the corridor\u27s infrastructure and performance. Portions of the corridor are now able to support train speeds of up to 110 mph due to improvements to trackage and safety devices, and the elimination of some grade crossings. Facility improvements along with the infrastructure improvements have been responsible for the nearly 170 percent increase in annual corridor ridership since 1970. The continued commitment of numerous agencies has ensured that the Detroit-Chicago Corridor is poised to take advantage of all opportunities afforded it in the future
Wireless Access: A Barrier to Success?
Get PDFThis study investigates the differences in the speed of the Internet among various libraries in rural and urban counties, as well as how this difference affects KSU students\u27 access to educational materials. The primary purpose was to determine how download and upload speeds compare across libraries and what impact those differences have on academic performance. A sample of libraries in counties with over 500 KSU students was selected, and speed tests were executed at two major libraries per county.
Data analysis by the Kruskal-Wallis test revealed the presence of considerable differences, with rural libraries like Maude P Ragsdale Public Library, Paulding County, having low speeds compared to urban libraries like Adairsville Public Library and Cartersville Public Library aligning with the findings of Kinney, (2010) and Wang et al. (2022). These findings emphasize the need for infrastructure improvements in rural areas and targeted educational policies to bridge the digital divide. Guaranteed access to the internet on equal terms is highly important for allowing and involving all KSU students in the full range of digital learning resources
Terrain Influences on Total Length of Snow-Avalanche Paths in Southern Glacier National Park, Montana
Get PDFThis research was designed to determine the impact of topographic variables on the total length of avalanche chutes in southern Glacier National Park, Montana. Seventy-eight snow avalanche paths were manually interpreted from aerial photographs within the study area, and their outlines were delineated on U.S. Geological Survey topographic maps with a scale of 1 :24,000. Terrain variables were either measured directly from the maps or derived from the original ones. Terrain parameters were first analyzed by using the descriptive statistical method. Total path length was then regressed against the independent variables elevation, orientation, and slope gradient. We found that: (a) the majority of the avalanche chutes are oriented north, south, and southwest; (b) total path length is highly correlated with source area as well as with top elevation but negatively with slope gradient; (c) longitudinal slope gradient is a significant determinant of path length only for north-facing slopes. Sou rce zone area, to a large extent, determines the length of the avalanche path. However, top elevation is of greatest importance in explaining the total length is the specific contribution made by each individual factor is considered