Texas A&M University–Kingsville is a public research university in Kingsville, Texas. It is part of the Texas A&M University System. The university has programs in engineering, agriculture, wildlife, music, and the sciences. It also developed the nation's first doctoral degree in bilingual education. It is classified among "R2: Doctoral Universities – High research activity".Texas A&M University–Kingsville is the oldest continuously operating public institution of higher learning in South Texas. The school was chartered as the South Texas Normal School in 1917; however, the opening of the school was delayed due to World War I. Founded in 1925 as South Texas State Teachers College, the university's name changed in 1929 to Texas College of Arts and Industries, or Texas A&I for short, signaled the broadening of its mission. A 1967 name change to Texas A&I University marked another transition. The university became a member of the Texas A&M University System in 1989 and changed its name to Texas A&M University–Kingsville in 1993.The school has been continuously accredited by the Southern Association of Colleges and Schools (SACS) since 1928.
Live capturing of wildlife is important for research and conservation, but is rife with challenges including animal welfare concerns, resource commitments (e.g., time and effort), and low capture success rates. Such challenges may be especially apparent for species listed under the Endangered Species Act and species whose ecology impacts capture success. Thus, it is important to investigate and implement strategies that can improve the capture success of endangered carnivores while reducing human effort and risk to animals. In the United States, ocelots (Leopardus pardalis) are a federally endangered species. To minimize risk to ocelots, capture efforts for research in Texas are limited to box trapping, but capture success is generally low. We tested whether visual and scent lures can increase capture success of ocelots and other co-occurring mesocarnivores with box traps baited with a live bird on a private ranch in the Texas-Tamaulipan thornscrub ecosystem. From December 2023 through April 2024, we used a randomized design and placed visual (hanging compact disc [CD] or shiny ribbon) and scent (civet musk or ocelot urine) lures at a total of 20 box traps and established 5 control traps across 3 temporally and geographically discrete trapping sessions for 75 trapping locations. We used linear regression to assess 2,900 trap nights and found that none of the lures (scent nor visual) impacted capture success of ocelots, bobcats (Lynx rufus), or coyotes (Canis latrans). Further, lures did not increase or decrease capture of non-target animals. Based on our findings, we cannot recommend the use of CDs, ribbon, civet musk, or ocelot urine as lures to increase ocelot box trapping success, as they did not increase capture success of ocelots or other target carnivores nor decrease captures of non-target species. We suggest that researchers prioritize other strategies to increase capture success (e.g., setting additional traps) rather than the addition of lures we tested.
The debate over the H-1B visa (a temporary, non-immigrant visa that allows U.S. employers to hire foreign workers in speciality occupations) in the United States has been longstanding and often contentious. This study finds a positive impact of artificial intelligence (AI) investment on firms' H-1B visa applications, suggesting that firms investing in AI are more likely to hire highly skilled foreign workers. To address potential endogeneity concerns, we employ two identification strategies: propensity score matching and instrumental variable analysis. We further observe that higher R&D expenditure, stronger sales growth, and greater capital investments are associated with increased demand for H-1B visas, particularly among firms with higher AI investment. Additional analyses show that H-1B petitions are linked to enhanced firm performance and innovation outcomes. By connecting AI investment with foreign labour demand, this study offers valuable insights for business leaders and policymakers navigating the evolving intersection of technological advancement and workforce composition.
Objective: This meta-analysis explored the relationship between burnout and psychological distress across different academic disciplines, measurement tools, institutional contexts, and the pandemic. Method: We synthesized 76 effect sizes from 29 studies involving 20,037 students, residents, and fellows in the United States. Results: The correlation between burnout and psychological distress was (r = 0.44), with stress showing the strongest correlation (r = 0.48). Notably, the correlations were higher during the pandemic (r = 0.46) compared to pre-pandemic (r = 0.44). Our subgroup analysis indicated that medical students exhibited a stronger association (r = 0.5) than fellows and residents. Additionally, samples from a multiple organization yielded higher correlations (r = 0.46). Conclusions: Among the dimensions of burnout, emotional exhaustion demonstrated a stronger correlation with psychological distress. Meta-regression confirmed that the students' disciplines, sample locations, and COVID-19 moderated the overall effect size. Findings highlight the urgent need for targeted interventions to address environmental stressors within medical training.
Patterns of resource selection are driven by the decision-making processes of animals occurring at multiple scales from where to establish a home range (i.e., second order selection) to which resource patches to use within the home range (i.e., third order selection). Elk (Cervus canadensis) were reintroduced to southwestern Virginia, USA, from 2012 to 2014 following successful translocations onto reclaimed surface coal mines in the region. We sought to understand how elk have acclimated following their translocation using location data from GPS-collared adult female elk (n = 33) collected from 2019 to 2022 along with remotely sensed terrain and land cover data. We utilized continuous-time movement models paired with generalized linear mixed-effects modeling to describe seasonal resource selection at second and third orders. At both scales of selection and throughout the year, female elk selected reclaimed surface mines, conifer forests, ridgetops, and areas with lower terrain roughness, while avoiding mixed hardwood and oak (Quercus spp.) forests. Unmined open land was only selected at the third order during periods of forage scarcity (i.e., winter) and increased metabolic requirements (i.e., late gestation). Although surface coal mining leaves legacy environmental impacts on the landscape, management of these sites provides benefits to elk and maintains open habitat that is otherwise limited.
Water oxidation catalysts (WOCs) based on first-row transition metal complexes have attracted a greater attention in recent years. Among those, copper-based catalysts have garnered a special interest due to their low cost and high tunability through rational ligand design. In this work, a new series of penta-coordinated mixed ligand Cu(II) polypyridine complexes containing hydrazone ligands (1-6) and tetra-coordinated Cu(II) bipyridine complexes containing thioamide ligands (7-9) with different substituents have been synthesized and characterized. Molecular structures of complexes 1, 4 and 5 were determined by single crystal X-ray crystallography. All the complexes were evaluated as electrocatalysts for oxygen evolution reaction (OER) under alkaline condition. At a current density of 10 mA cm-2, Cu(II) complexes 6 and 9 with methoxy substituted ligand showed minimal overpotentials of 328 and 297 mV (V versus RHE), respectively, and Tafel slopes of 85 and 57 mV dec-1, respectively. Their electrocatalytic activity was compared with that of the commercially available RuO2. The improved OER performance was attributed to high conductivity and surface area of Vulcan carbon, which enhanced charge transport and active site accessibility. The long-term durability test was performed for the best catalyst for 10 h. This study demonstrated that integrating mixed ligand Cu(II) complexes with conducting carbon support was a promising approach towards electrocatalytic OER.
