Knoxville College

Abstract Understanding the weather and climate of Mesoamerica and the Caribbean remains challenging due to complex hydroclimate interactions, limited observations, and poor representation of regional processes in global models. We introduce the Mesoamerica Affinity Group (MAAG), a National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and community initiative that fosters research collaboration to advance weather and climate science, develop convection-permitting datasets, and promote knowledge exchange. MAAG’s first major contribution is a 2-week convection-permitting simulation of Hurricane Maria (2017) using Model for Prediction Across Scales–Atmosphere (MPAS-A), featuring a novel regional 15- to 3-km variable-resolution mesh over the region. Initial evaluation shows that MPAS-A captures key features like precipitation patterns, the intertropical convergence zone, and low-level jets. Some biases remain, particularly in enhanced land convection and slight deviations in Maria’s track. This novel dataset, now publicly available through NCAR’s Data Archive, supports studies of other extreme events and mesoscale convective systems active during the same period. It offers a valuable resource for the research community. MAAG is a new but rapidly growing initiative achieving notable milestones in a short time. It serves as a collaborative platform for codesigning high-resolution modeling experiments aimed at producing actionable weather and climate information. We invite the community to join MAAG, explore this initial dataset, and advance regional weather and climate research. Significance Statement The Mesoamerica Affinity Group (MAAG), a National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and community initiative, aims at addressing the complex challenges of understanding weather and climate in Mesoamerica and the Caribbean. MAAG’s first major achievement is a 2-week convection-permitting simulation of Hurricane Maria (2017) using a novel 15- to 3-km variable-resolution mesh. This dataset accurately captures key regional features and is publicly available through NCAR’s Data Archive. By fostering collaboration through data production and sharing, monthly group meetings that serve as a platform for networking and knowledge exchange, and the development of advanced high-resolution datasets, MAAG provides a vital resource for advancing regional weather and climate science. The initiative is rapidly growing, serving as a platform for codesigned modeling experiments aimed at producing actionable climate information for academia and different sectors. We invite the scientific community to join MAAG and advance research in this critical region.

The electronic energy loss spectra of ceria (CeO2) irradiated with swift heavy ions (27 MeV Xe and 946 MeV Au) in the electronic slowing down regime were measured for bulk sintered samples and nanoparticles by using a double Cs-corrected transmission electron microscope. The low-loss region as well as the core-loss region, including the oxygen K-edge and cerium M4, 5 white lines, were recorded. No strong lattice disorder was found in the low-loss peaks for both types of samples showing the same bulk oxygen plasmon loss peak at about 15 eV. However, there is a clear evidence of cerium reduction to the trivalent oxidation state after irradiation for the sintered samples as shown by the K-edge shape of oxygen and decrease of the Ce M4/M5 intensity ratio. A similar change of the M4/M5 intensity ratio was observed for the irradiated nanoparticles with respect to the virgin sample owing to the high energy input inside the nanograin. The effect of radiation damage on electron energy loss spectroscopy data is analyzed for both types of samples and irradiation conditions.

Bull breeding soundness examination (BBSE) is critical for identifying subfertile bulls and preventing reproductive and economic losses in cow/calf systems. This retrospective study evaluated intrinsic and extrinsic factors associated with BBSE failure in bulls. Data from 1,375 BBSE records (2008-2018) included age, breed, body condition, scrotal circumference (SC), semen quality traits, physical and reproductive findings, examining veterinarian, season, and prior BBSE history. Outcomes were classified as pass or fail. Among failures, sperm morphologic abnormalities were the predominant reason (73.3%), followed by inadequate SC (8.6%), penile abnormalities (5.5%), no ejaculate produced (4.6%), and lameness (3.1%). Bulls that previously failed BBSE were likely to fail again (> 6 times) with abnormal morphology accounting for 93% of repeat failures. Significant intrinsic predictors of failure included SC, sperm morphology, progressive motility, primary and secondary defects, gross motility, breed, and body condition score. Significant extrinsic predictors included examining veterinarian, year, quarter, and prior BBSE status. A significant downward trend (p = 0.0299) in failure prevalence was observed. In the multivariable model, previous BBSE, year of examination, and examination quarter remained independently associated with failure. Results highlighted the multifactorial nature of BBSE outcomes and emphasized the importance of considering prior evaluation history, seasonal timing, and persistent morphology abnormalities when interpreting results and managing herd reproductive performance.

Breastfeeding enhances maternal-newborn bonding, supports newborn nutritional requirements, and is recommended in mothers undergoing medication-assisted treatment (MAT) for opioid use disorder (OUD). Breastfeeding decision-making is complex and may be influenced by implicit biases among healthcare providers, negatively impacting maternal quality of care and breastfeeding outcomes in mothers with OUD. This integrative review aimed to synthesize current evidence on how healthcare professionals' implicit bias affects breastfeeding initiation, support, and continuation among women with OUD. Included studies focused on women with OUD, specifically those on MAT, and examined bias in relation to breastfeeding. Studies were excluded if they did not involve pregnant or postpartum women on MAT, focused solely on polysubstance use, or addressed only racial bias. A total of 117 articles underwent title and abstract review. Of the 117 articles initially identified through the database search, only 28met the preestablished inclusion and exclusion criteria and were ultimately included in this integrative review. Key themes emerged: stigma and discrimination, lack of social and institutional support, provider knowledge gaps, and maternal fears related to recovery. Studies included qualitative, quantitative, and mixed methods research. Educating healthcare providers with accurate, evidence-based information can reduce bias and better support women with OUD in achieving their breastfeeding goals. Future studies should examine how implicit bias impacts breastfeeding in this population to inform provider training and resource development.

ABSTRACT Lithium‐ion battery performance degrades over time due to complex aging mechanisms, including lithium inventory loss, structural changes in electrode materials, and increases in contact resistance. Understanding these processes is essential for improving battery performance and extending cycle life. This work presents a combined electrochemical impedance spectroscopy and distribution of relaxation times approach using a three‐electrode configuration to investigate aging and state‐of‐charge (SOC)‐dependent internal resistances in NMC811│graphite Li‐ion cells. By simultaneously probing the cathode, anode, and full‐cell responses and deconvoluting overlapping impedance features using DRT, we identify distinct contributions from particle‐particle resistance, SEI resistance, intercalation (charge‐transfer) kinetics, and solid‐state diffusion. Our results show that cathode processes dominate impedance growth at high SOC due to structural degradation and surface reconstruction, whereas anode contributions arise mainly at low SOC through increasing intercalation‐kinetic limitations. SEI‐related resistance stabilizes after the initial cycles, while contact resistance and diffusion impedances grow steadily with aging. These trends correlate closely with SEM, XRD, and Raman evidence of particle cracking, lattice strain, and structural disorder, establishing strong links between electrochemical signatures and physical degradation. Overall, this methodology provides a quantitative, component‐resolved framework for diagnosing electrode‐specific failure modes and guiding materials or interface‐engineering strategies to enhance the lifetime of lithium‐ion cells.