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The Danger of a Single Story: Affrilachian Experiences in West Virginia Policy, Economy, and Resilience
Full text linkThis research project sought to understand the various issues facing Black communities in West Virginia and the efforts being made by Affrilachian (African Americans in Appalachia) people and communities to address the issues that they face and to build spaces and initiatives that support Affrilachian communities to survive and thrive. The contributions of Black West Virginians to the region have often gone ignored in mainstream histories and continue to be ignored by mainstream media. However, this project seeks highlight the significant organizing that is being done by Affrilachians, illustrating that although Black people only make up 3.8% of West Virginia’s population, the stories of Black communities in West Virginia stories need to be told
Return to Me
No full textIn Rita Mae’s green-thumbed world, anything with roots can grow—including the teeth she steals from lascivious men, which she grows into potted, sadomasochistic creatures called “sweetings.” By day, Rita Mae works a corporate job in Chicago, where she meticulously flirts with a married coworker and subscribes to her boss’s OnlyFans account for future blackmail. By night, Rita Mae mothers her sweetings, bathing them in mouthwash and toothpaste and pruning their limbs to keep them from growing feet and leaving her. But when she isn’t preoccupied with her sweetings, Rita Mae moonlights as a sex-fiend and seduces random men for their teeth—while she struggles with her own loneliness and continues to harbor an unhealthy obsession and lust for her estranged twin brother. As Rita Mae’s new life in Chicago straddles the line between fantasy and reality, danger and normalcy become synonymous when Rita Mae’s fragile hold over her job, sweetings, and world shatters when a homegrown, nightmarish version of her twin returns to claim what was once his, threatening her with the horrors and heartbreak of her past she desperately fled from a year ago in rural Kentucky. While Rita Mae’s grip over her reality spirals out of control, her orchestrated identities dissolve in the face of her own mistakes, threatening every connection she has in her life, human or not. Rita Mae must reckon with the consequences of what can and should grow from the dark, and whether or not she can return to a life made for herself, or if she belongs in the same dark where her own roots grow… and rot. Return to Me is a modern-day gothic tale cast against a backdrop of obsession, possession, fractured self-identity, and misplaced love, about a mentally disturbed young woman trying to find herself in the world—with a sweet tooth for revenge
A Multiscale AI Framework for Forest and Agriculture Health Monitoring: Drone-Based Object Recognition and Segmentation for Automated Ecological Assessment
No full textForest and agricultural ecosystems are increasingly at risk due to invasive species, pests, and diseases, necessitating scalable, automated, and intelligent monitoring solutions. Traditional field based forest and agriculture health assessments are limited by cost, time, and spatial coverage. This dissertation presents a multiscale deep learning framework that automates forest and agriculture health monitoring using drone imagery and computer vision techniques. The system operates across three spatial levels: forest level, tree level, and leaf level, combining object detection, segmentation, and classification models to support large scale ecological assessment.
At the forest level, high-altitude drone imagery is processed using object detection and segmentation models, leveraging the state-of-the-art Mask2former architecture to detect and map large-scale ecological threats, such as invasive species and pest infestations. At the tree level, two complementary approaches are employed: a semi-supervised learning pipeline using a novel Gaussian Mixture Model (GMM) for limited labeled data, and a deep learning segmentation model optimized for large datasets to provide fine-grained spatial mapping of invasive species presence. Our semi-supervised GMM combines supervised and unsupervised learning, incorporating user input for manual region selection and data augmentation to enhance model robustness. At the leaf level, a classification model based on transformer architectures is used to differentiate invasive species, enabling species-level identification based on visual patterns.
Our framework integrates deep learning, semi-supervised learning, and efficient data handling to enable large-scale ecological surveillance. By combining supervised and semi-supervised learning, it adapts to varying data availability, providing accurate monitoring of forest and agriculture health. This scalable system enhances automated ecological surveillance, offering valuable insights for forest conservation and ecosystem resilience
Skeletal and Dental Effects of the Carriere Motion Appliance™ in Non-Growing Class II Patients: A Cephalometric Study
No full textBackground and Objectives: Dental and skeletal Class II discrepancies are commonly associated with orofacial disharmony, and therefore appear in orthodontic clinics frequently. Class II correction for adults is generally limited to camouflage treatment with extractions, Class II elastics, Class II correctors, distalization, or orthognathic surgery in severe cases. The orthodontic field is constantly innovating to find efficient and effective means to correct class II malocclusions. The Carriere Motion Appliance TM was introduced in 2004 as an effective “distalizing” appliance to be used as a non-extraction approach to Class II correction for adolescent and adult patients. Recent clinical evidence suggests that most of the effects are dentoalveolar, and that some of the effects of the CMA can relapse after removal of the appliance and completion of comprehensive orthodontic treatment. The objective of this retrospective study was to evaluate and quantify the skeletal and dental effects of Class II correction with the CMA followed by comprehensive orthodontic treatment of Chinese adult patients with Class II malocclusions. Experimental Design and Methods: This retrospective study evaluated twenty-five post-pubertal patients with class II malocclusions treated with the CMA followed by either fixed appliances (five patients) or clear aligners (twenty patients). Orthodontic records were obtained from Dr. S.L.’s practice in Hong Kong. All patients had a full permanent dentition at the beginning of treatment. All patients were post-pubertal with a cervical vertebral maturation stage of either 5 or 6. Lateral cephalograms were taken before treatment (T1), immediately following class II correction and removal of the CMA (T2), and immediately following completion of comprehensive orthodontic treatment and removal of all appliances (T3). Angular and vertical skeletal changes were evaluated using the Dolphin imaging software; sagittal linear changes were measured by hand on T1, T2 and T3 digitally traced radiographs printed 1:1. Data were analyzed using a matched-pair t-test Wilcoxon signed rank test for the skeletal and dental changes across three timepoints. Two-sided p-values of ≤ 0.05 were considered statistically significant. Test-retest intra-rater reliability was assessed for two investigators using Pearson correlation coefficients (PCCs). Inter-rater reliability was assessed between two investigators using Intra-class correlation coefficients (ICCs). ICCs and PCCs ≥ 0.5 indicated moderate-excellent reliability. Results: Class II correction with the CMA took an average of 6.28 ± 1.9 months. Average total comprehensive treatment time for our patient sample was 32.2 ± 6.5 months. Overjet and molar relationship were significantly improved after Class II correction with the CMA. Treatment effects were primarily dentoalveolar, with no clinically significant skeletal effects; maxillary molars distalized, mandibular molars mesialized and extruded, mandibular incisors proclined, overbite was reduced, and the occlusal plane angle steepened. The mandibular plane angle increased slightly. After removal of the CMA and completion of comprehensive orthodontic treatment, molar correction relapsed somewhat due to slight mesialization of the maxillary molars. Overjet was further reduced. Overbite reduction, steepening of the mandibular plane angle, and proclination of lower incisors were somewhat recovered after removal of the CMA. Maxillary incisors were significantly retracted and retroclined. Lower anterior facial height did not change throughout the course of treatment. Conclusions: The CMA effectively improved molar relationships and reduced overjet in our sample of Class II adult Chinese patients. Molar correction relapsed slightly after removal of the CMA, however. Treatment effects of the CMA appliance were predominantly dentoalveolar. While some statistically significant skeletal changes were observed after Class II correction with the CMA and after completion of comprehensive treatment (decrease in SNB, increase in ANB, increase in mandibular plane angle), changes were minor and clinically insignificant. Lower facial height did not change over the course of treatment
Do Demographics and Social Determinants of Health Relate to Current and Anticipated Caregiving Roles?
No full textIn 2021-22, approximately 37.1 million Americans provided care to family or friends who had an illness or disability (U.S. Bureau of Labor, 2024). These informal caregivers experience poorer mental health (Dahlrup et al., 2015) and physical health (Pinquart & Sorensen, 2003) influencing their overall well-being. Experiences in caregiving may differ across age, gender, race (Young et al., 2019). Given the effects of Social Determinants of Health (SDOH), such as financial stability, health care, and food resources (Duran & Perez-Stable, 2019), some adults may experience additional threats to health and quality of life before entering into the caregiver role. Little is known about those who anticipate becoming a caregiver. Knowing key information about anticipated caregivers would allow better programs and policies for future caregivers. The current study includes 97,914 participants (Mean age = 55.56, 45.8% female, 81.6% white non-hispanic) who completed the 2022 BRFSS. Approximately 20.1% were current caregivers, 10.47% anticipated becoming a caregiver in the next two years, 5.3% were unsure, and 64.11% did not anticipate becoming a caregiver. One-way analysis of variance examined group differences in emotional and physical well-being. Overall, current caregivers reported poorer emotional well-being compared to the other three groups. Those who were unsure in the caregiving role reported poorer physical health than all other groups. Anticipated caregivers were better off physically but they were not far behind current caregivers with emotional well-being. Additionally, multinomial logistic regressions examined the contributions of key demographic characteristics and economic SDOH to predicting group membership. Compared to current caregivers, anticipated caregivers were more likely to be younger (OR = .99), male (OR = 1.2), and unemployed (OR = .81). Challenges related to eSDOH were higher for current than for anticipated (OR = .89), unsure (OR = .76), and those not anticipating becoming a caregiver (OR = .73). Additional post hoc analyses compared anticipated caregivers to unsure and not anticipating. More resources should be available for those prior to becoming a caregiver to alleviate future caregiver burden