Virginia State University

The Asian tiger mosquito, Aedes albopictus, is currently the most widespread invasive mosquito species in the world. It poses a significant threat to human health, as it is a vector for several arboviruses. We used a SNP chip to genotype 748 Ae. albopictus mosquitoes from 41 localities across Europe, 28 localities in the native range in Asia, and 4 in the Americas. Using multiple algorithms, we examined population genetic structure and differentiation within Europe and across our global dataset to gain insight into the origin of the invasive European populations. We also compared results from our SNP data to those obtained using genotypes from 11 microsatellite loci (N = 637 mosquitoes from 25 European localities) to explore how sampling effort and the type of genetic marker used may influence conclusions about Ae. albopictus population structure. While some analyses detected more than 20 clusters worldwide, we found mosquitoes could be grouped into 7 distinct genetic clusters, with most European populations originating in East Asia (Japan or China). Interestingly, some populations in Eastern Europe did not share genetic ancestry with any populations from the native range or Americas, indicating that these populations originated from areas not sampled in this study. The SNP and microsatellite datasets found similar patterns of genetic differentiation in Europe, but the microsatellite dataset could not detect the more subtle genetic structure revealed using SNPs. Overall, data from the SNP chip offered a higher resolution for detecting the genetic structure and the potential origins of invasions.

Objectives College students are at elevated risk for both food insecurity and eating disorder (ED) symptoms. Prior literature supports cross‐sectional associations between food insecurity and ED symptoms, including binge eating, purging (e.g., diuretic and laxative misuse, self‐induced vomiting), and dietary restriction. However, less is known about the temporal relation, particularly among college students. Methods We tested associations between food insecurity and cognitive restraint, binge eating, dietary restriction, purging, and excessive exercise across one college semester (three months). College students [ N = 259; mean (SD) age = 19.22 (1.23)] were recruited to complete the Eating Pathology Symptoms Inventory (EPSI) and the 30‐day version of the United States Department of Agriculture Adult Food Security Survey Module in August (baseline) and November (follow‐up). We conducted five multiple regression models to examine baseline food insecurity as a predictor of each EPSI subscale score of interest, adjusting for baseline EPSI score, sociodemographic characteristics, and body mass index. Results Baseline food insecurity significantly predicted greater cognitive restraint ( β = 0.12, p < 0.05), dietary restriction ( β = 0.18, p < 0.001), excessive exercise ( β = 0.15, p < 0.01), and purging ( β = 0.14, p < 0.05) at follow‐up, adjusting for baseline levels, sociodemographic characteristics, and body mass index. Baseline food insecurity did not predict binge eating at follow‐up when the baseline level, body mass index, and sociodemographic characteristics were considered. Discussion Experiencing food insecurity may contribute to the development or exacerbation of excessive exercise, dietary restriction, cognitive restraint, and purging among college students. Findings highlight the potential need for food insecurity interventions to include support for disordered eating.

The serine/threonine kinase, Tank Binding Kinase 1 (TBK1), drives distinct cellular processes like innate immune signaling, selective autophagy, and mitosis. It is suggested that the translocation and activation of TBK1 at different subcellular locations within the cell, downstream of diverse stimuli, are driven by TBK1 adaptor proteins forming a complex directly or indirectly with TBK1. Various TBK1 adaptors and associated proteins like NAP1, TANK, SINTBAD, p62, optineurin (OPTN), TAX1BP1, STING, and NDP52 have been identified in facilitating TBK1 activation and recruitment with varying overlapping redundancy. This review focuses on what is known about these proteins, their interactions with TBK1, and the functional consequences of these associations. We shed light on underexplored areas of research on these TBK1 binding partners while emphasizing how future research is required to understand the function and flexibility of TBK1 signaling and crosstalk or regulation between different biological processes.

In the worldwide context of rising salinity issues in agriculture, it is important to understand crop responses to salinity stress. Currently, standing as the second largest oilseed crop, canola (Brassica napus L.) entices continued research focus on such aspects. Thus, this study investigated the genotypic variation in seedling emergence characters under salinity stress. Two growth chamber experiments were conducted in diverse canola genotypes (10 each of winter and spring types) at six salinity levels (0, 2, 4, 6, 8, and 10 dS m⁻¹ EC). Increasing salinity levels reduced the emergence indices (emergence percentage, emergence rate index, corrected emergence rate index, and emergence velocity) and salt tolerance index (STI). An approximate threshold salinity range of 6–8 dS m⁻¹ ECs was determined. Importantly, salinity at ≥8 dS m⁻¹ EC levels substantially reduced seedling emergence indices and delayed emergence by 3–7 days after seeding. Winter genotypes CP1022WC/Chinook and CP320WRR, and spring genotypes Monarch, PI597352, PI601200, and PI432395 had higher STI and emergence indices. Based on cluster analysis, genotype groups were classified as low (Athena, CP115W, Durola, Impress, and Gem), medium (Amanda, Ericka, CP320WRR, Salut, CP225WRR, Clearwater, and Wester), and high salt‐tolerant types (CP1022WC/Chinook, Monarch, PI597352, and PI432395). All emergence indices showed high broad‐sense heritability (H2 = 0.82–0.94). Between canola types, spring canola consistently showed greater genetic potential for salt tolerance than winter canola. The results of this study provided useful information for canola seedling establishment under salinity and for further genetic improvement of salt tolerance.

Bots (i.e., automated software programs that perform a variety of tasks) and fraudulent responders pose a growing threat to psychological research. Bots and fraudulent responders affect data integrity, and cost researchers and organizations resources (e.g., time and money). Bot and fraud detection tactics (BFDTs) are methods used to identify and eliminate bots and fraudulent responders while simultaneously retaining real and verified human participants. This study describes our team’s experience with bots and fraudulent responders during an online experience sampling study with trauma-exposed sexual minority cisgender women and transgender and/or nonbinary people. We employed and tested an array of BFDTs, as well as the timing and duration of BFDT deployment (i.e., how long we used them to identify bots and fraudulent responders) to create a preliminary protocol for eliminating bots. The baseline survey received 24,053 responses. After applying our BFDT protocols, we eliminated 99.75% of respondents that were likely bots or fraudulent responders. Executing BFDTs generated a final sample size of 59. Analyses showed that some BFDTs seemed to be more effective than others, some BFDTs afforded higher confidence than others, protocols that were changed periodically (i.e., the order of BFDTs) were more effective than protocols that did not change, an bots and fraudulent responders introduced significant bias in the data collected. This study highlights the need for further research to validate the preliminary strategies developed and tested in this pilot, proof-of-concept study aimed at mitigating the impact of bots and fraudulent responders in online psychological research.

Autistic youth experience disproportionately high rates of child maltreatment and a wide range of other traumatic and stressful events, such as peer victimization. Very little empirical work has evaluated trauma-focused supports for Autistic youth, despite high rates of posttraumatic stress disorder (PTSD) and other trauma-related symptoms. The current study is a pilot proof-of-concept evaluation of telehealth-based trauma-focused cognitive behavioral therapy (TF-CBT) for Autistic youth ( N = 17, ages 10–17) and their caregivers. Youth PTSD symptoms significantly declined from the beginning to end of the program across youth self-report, caregiver report, and clinician interview, and effects were maintained at the 1-month follow-up with large effect sizes. Youth self-reported significant declines in anxiety. Caregivers reported significant improvements in all co-occurring youth mental health symptoms and some caregiver-level outcomes. Youth and caregivers rated the program and telehealth delivery favorably overall. Future larger-scale randomized evaluations of TF-CBT for Autistic youth are needed.

A gallium oxide (Ga2O3)–nickel oxide (NiO) merged PiN Schottky (MPS) diode was fabricated using Ga flux plasma-free etch and platinum oxide (PtOx) contacts. The use of a plasma-etch-free process enables the fabrication of Ga2O3 trenches with low surface damage. PtOx acts as both a Schottky contact to n-type Ga2O3 and an Ohmic contact to p-type NiO. Compared to the Ni/NiO contact used in many prior devices, the PtOx/NiO contact exhibits a 100 times lower contact resistance as shown by linear transfer length method measurements. This improved contact resistance boosts the diode’s forward current capacity, as featured by a second turn-on in the current–voltage characteristics with a decreased differential on-resistance. This verifies the concurrent current conduction through both Schottky and PN junctions and thereby the formation of a MPS diode. Furthermore, MPS diodes were subjected to high reverse bias reliability testing. Such a reliability test has been seldom reported in Ga2O3 devices. During an 800 V stress test (80% of the breakdown voltage) for a cumulative time of 2000 s, MPS diodes were periodically switched on, showing no degradation in the dynamic on-state characteristics. This signifies a stable PtOx–Ga2O3 Schottky contact and an improved Ga2O3–NiO heterojunction with minimal sidewall trapping as a result of the plasma-etch-free process.

Spring dead spot is a disease of bermudagrass (Cynodon dactylon L. Pers) caused by Ophiosphaerella spp., of fungi which infect the below ground structures of plants, causing damage to the turf canopy. Previous research suggests that precision management strategies based on manually identified disease within unmanned aerial vehicle (UAV) imagery using GIS software and global navigation satellite systems (GNSS)-equipped sprayers can reduce the fungicide required for spring dead spot management. However, this methodology is time consuming and impractical for golf course superintendents. This paper introduces a novel approach to spring dead spot identification utilizing a custom Python script, the Simple Ophiosphaerella Damage Detector (SODD), to identify and record locations of spring dead spot from UAV imagery using basic feature extraction techniques. Initial tests comparing the outputs from SODD to spring dead spot manually identified by researchers on four fairways, comparisons of K-means cluster maps showed similarities ranging between 71 and 88% although incidence counts were inconsistent. Precision treatment methods based on SODD were evaluated across 16 golf course fairways at three locations in Virginia organized as a randomized complete-block design with four replications and four treatment methods; spot and zonal treatments based on SODD identified incidence and density, respectively, compared against full-coverage and non-treated controls. Applications were made with a Toro Multipro5800 with GeoLink GNSS-equipped sprayer in Fall of 2021. Spot and zonal treatment strategies showed similar control to full-coverage applications (p≤0.001) while reducing the percentage of the fairways treated by 48% and 52%, respectively (p≤0.001). These results highlight the capabilities for SODD as a tool for disease map generation.

Validating the safety of automated driving systems (ADS) demands a thoughtful strategy for constructing appropriate test cases that enable direct and fair comparisons with human drivers. The complexity of driving and the rarity of safety-critical situations pose challenges in creating a reliable and efficient validation framework. This paper addresses these issues by selecting appropriate test cases from the largest-scale naturalistic driving study (NDS). We introduce a novel Kernel Test Case Sampling (KTCS) method, which selects cases satisfying two key criteria: representativeness, ensuring alignment with real-world scenarios, and coverage, capturing high-risk corner cases. By selecting 118 cases, our method effectively captures long-tailed scenarios while approximating the NDS distribution. Additionally, we provide a reliable approach for calculating accident rates, enabling fair comparisons with human drivers. Our method supports standardized and scalable ADS safety validation, facilitating accelerated development and deployment while building public trust and regulatory confidence.

Introduction Approximately 53% of maternal mortality occurs in the postpartum period, a time with little monitoring and health surveillance. The objective of this study was to test the feasibility, usability, appropriateness, and acceptability of remote low‐burden physiologic monitoring of Black postpartum women, using a novel soft wearable patch and home vital sign monitoring for the first 4 weeks postpartum. Methods A prospective longitudinal cohort feasibility study of 20 Black postpartum women was conducted using home monitoring equipment and a wearable patch with physiologic sensors measuring temperature, pulse oximetry, blood pressure, electrocardiogram (ECG), heart rate, and respiration twice daily during the first 4 weeks postpartum. Feasibility, acceptability, appropriateness, and usability were measured at the end of the study with the Feasibility of Intervention Measure, Acceptability of Intervention Measure, Intervention Appropriateness Measure, and System Usability Scale. Results Twenty Black women were recruited and consented to participate in the study. Remote physiologic monitoring using a wearable patch and home monitoring equipment was rated as feasible (93%), acceptable (93%), appropriate (92%), and useable (80%). During the first 2 weeks postpartum, remote home monitoring detected that 60% of the women had blood pressures exceeding 140/90 mm Hg. The wearable patch provided useable data on ECG, heart rate, heart rate variability, pulse oximetry, and temperature. Discussion Our research suggests that remote monitoring in the first 4 weeks postpartum has the potential to identify Black women at risk for postpartum complications.

This chapter reflects on how a social justice partnership began between a University Professor and the Director of Pretty Purposed, a youth-based non-profit organization based in Petersburg, Virginia, designed to help create spaces of justice and creativity for Black girls and girls of color. We discuss our collaborative efforts toward building a mentorship community collective model, by working with local undergraduate college students, to help mentor the girls in her program. An emphasis on how projects centering both wellness and social justice have been transformative is explored. Further, we discuss ongoing barriers and challenges, often experienced by non-profit directors of color, including a lack of structural resources, and funding from state and federal agencies. We discuss how collaborating with relevant and similar non-profit organizations, to build and maintain a larger social justice conglomerate of activists to help foster social justice for the youth, is one practical solution. Rather than relying solely upon theorizing underlying causes of social consequences underserved communities experience, due to ongoing social inequities, we discuss how a community collective model can help build positive interpersonal relationships between Black girls and can positively impact how Black girls shape their perception and identity of Black girlhood.

Mannose-containing glycopolymers display antibacterial properties even in the absence of antimicrobial moieties like cations or antibiotics.

This paper discusses a conceptually simple, computationally efficient, yet very accurate method tailored to the seismic analysis of RC wall components and systems. The method, called the Beam-Truss Model (BTM), has been extensively validated in prior research for various wall configurations under both static and dynamic loads. This paper presents the recent application of the BTM implementation as a shell macroelement to a Blind Prediction Competition hosted by UCLouvain, focused on the flexural and torsional response of two U-shaped walls. The modeling assumptions and blind predictions obtained with the BTM are presented and discussed. Overall, satisfactory response estimations were obtained for the initial stiffness, lateral strength, and deformation capacity of the wall specimens. A post-competition parametric numerical study, aimed to further enhance the accuracy of the method, is also presented. An improved calibration of the confined concrete stress-strain law resulted in a more accurate estimate of the deformation capacity of the wall under flexure. The post-competition analysis successfully captured out-of-plane inelastic buckling of the specimen subjected to flexure load, a failure mode observed for the first time experimentally in a U-shaped wall and captured only from a limited number of finite element studies. Additionally, this paper investigates the influence of torsional stiffness on the flexural and torsional response of BTM-shell models, highlighting its significant impact on the structural behavior predictions. Post-test analyses also revealed that employing a more accurate strain penetration law led to an improved estimation of the energy dissipation of the wall subjected to flexural loading. Finally, a study on the regularization of concrete material softening response was conducted to enhance mesh size objectivity.

The GHA strain of Beauveria bassiana (Balsamo) Vuillemin (Ascomycota: Hypocreales) is known to establish symbiotic relationships with some plant species. The present study was developed to determine whether the foliar application of B. bassiana-GHA and B. bassiana ANT-03, another commercial B. bassiana, results in the successful colonization of cotton, Gossypium hirsutum L., and examine whether the endophyte can influence the survivorship and feeding damage by the corn earworm, Helicoverpa zea Boddie (Lepidoptera: Noctuidae). Using polymerase chain reaction, colonization success by B. bassiana-GHA, 3, 7, 14, and 21 days after inoculation was estimated at 83.3%, 100%, 91.7%, and 83.3%, respectively. The colonization success based on the mycelial outgrowth method was 41.7%, 66.7%, 58.3%, and 50%, 3, 7, 14, and 21 days after inoculation, respectively. Beauveria bassiana ANT-03 did not colonize cotton. Corn earworms preferred untreated plants over the neonicotinoid and B. bassiana-GHA treatments. The B. bassiana ANT-03-treated plants and controls were not distinguished from one another by the corn earworms. The corn earworm survivorship was higher on the control plants, compared to plants treated with B. bassiana ANT-03, B. bassiana-GHA, and the neonicotinoid insecticide. The neonicotinoid insecticide, B. bassiana-GHA, and B. bassiana ANT-03 reduced corn earworm damage compared to the untreated controls. Our results demonstrated the potential for B. bassiana-GHA to be used as a biological control agent against H. zea in cotton.

Terrestrial ecosystems mitigate CO₂ accumulation in the atmosphere by annually absorbing ∼30% of anthropogenic emissions. The degrees to which CO₂ and climate drive this absorption are uncertain, which presents a challenge for future planning around carbon mitigation scenarios. To reduce this knowledge gap, we use a Bayesian model–data integration framework (CARDAMOM) to build and analyze a global terrestrial biosphere reanalysis that optimally reconciles multiple lines of Earth Observations with mechanistic model processes. The Earth observations informing the model dynamics include satellite and inventory-based constraints on distributions and change in terrestrial C storage (e.g., live biomass, soil organic C, and net biosphere exchange of CO₂) and mechanisms of that change (e.g., photosynthesis, deforestation, water storage anomalies, or fire). We find that the impact of 2001–2021’s atmospheric CO₂ increase on terrestrial C storage (+38 PgC) opposes and far outweighs the impact of climate trends over the same period (−8.2 PgC). Globally, CO₂-induced carbon gains occurred primarily in living biomass pools, while climate-induced losses occurred primarily in dead organic C pools, but relative gains and losses vary regionally. The fact that live biomass and dead organic C exhibit distinct and often opposing responses indicates that mechanistically resolving ecosystem function underlying the terrestrial C cycle’s emergent behavior is crucial for estimating the strength and resilience of the land C sink over the coming decades.