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The effect of X-ray irradiation technology on Salmonella spp. and quality parameters of ready-to-bake chocolate chip cookie dough
No full textSalmonella contamination in cookie dough poses a threat to consumers. This study investigated the effect of X-ray irradiation on Salmonella-inoculated ready-to-bake chocolate chip cookie dough and its impact on dough quality. A Salmonella cocktail (~10 log CFU/g) was prepared and inoculated into cookie dough samples (~6.5 log CFU/g) and then treated with X?ray irradiation (0.25, 0.5, and 1 kGy). Salmonella decreased by 1.15, 1.79, and 2.49 log CFU/g, at an exposure of 0.25, 0.5, and 1 kGy, respectively. Quality parameters (pH, aw, and colorimetry) were evaluated for two brands. No statistical difference (P\u3e0.05) in pH was observed for Brand A, while Brand B had a significant decrease (P\u3c 0.05) at 1 kGy from 8.25 to 7.92. At 1 kGy, aw decreased significantly (P\u3c 0.05) for both brands from 0.78 to 0.75 (Brand A) and 0.75 to 0.72 (Brand B). As dosage increased, dough color visually darkened in both brands. To control pathogens in cookie dough, X-ray irradiation can be utilized without impacting dough quality
Investing in your own: How university leaders should aim to invest to retain quality staff in undergraduate recruitment offices
No full textThis quantitative narrative inquiry study examined the experiences of undergraduate recruitment professionals, and the impact institutional investment can influence staff retention of these professionals within higher education. Using Job Embeddedness Theory often applied within private industry and Bolman and Deal’s (2017) human resource theoretical framework, the research question was: To what extent are specific dimensions (support, compensation, professional advancement) of institutional investment related to the retention of undergraduate recruitment professionals within higher education? Data were collected using an anonymous online survey that was shared with potential participants via email. Responses were analyzed through SPSS software using item-level and composite score multiple linear regression models to determine significant between the independent variables, the dimensions of institutional investment, and the dependent variable, self-report influences on retention. Results indicated that undergraduate recruitment professionals place greater emphasis on factors of being supported than anything more. These findings indicate that higher education administrators and leadership should begin focusing attention and additional efforts to better understand how undergraduate recruitment professionals can be supported
Design and evaluation of hollow cross-laminated timber with corrugated cores: a structural perspective
No full textThis study investigates the integration of small-diameter trees (SDT) into cross-laminated timber by developing cellular cross-laminated timber (CCLT) with corrugated panels in the transverse mid-layer. This innovation addresses sustainable building material demands while mitigating forest fire risks associated with SDT. The research progressed through three phases. First, parametric linear finite element modelling (FEM) examined corrugated geometry\u27s influence on CCLT flexural stiffness. Based on these findings and manufacturing constraints, an optimal geometry was designed and fabricated. Experimental testing validated the FEM predictions and demonstrated CCLT\u27s superior normalized modulus of elasticity by density compared to conventional cross-laminated timber (CLT). Second, using modified planar shear tests, various fabrication parameters of the corrugation panel were evaluated. Two optimized parameter combinations yielded remarkable shear strength improvements of 65% and 125% over baseline configurations. Finally, a nonlinear finite element model was developed and validated that assessed the influence of geometric parameters of corrugated panels on CCLT\u27s structural performance under bending and shear loads. Based on these findings, CCLT panels with the optimized design corrugated geometry were fabricated that exceeded ANSI/APA PRG-320 standards for shear strength and bending stiffness for CLT. This research demonstrates the viability of transforming underutilized SDT into high-performance engineered wood products for sustainable construction applications
Removal of harmful algal bloom toxin, Microcystin-LR via graphene coated polymers
No full textThis study investigates a novel 3D-printed graphene-coated polymer (GCP) for the removal of Microcystin-LR (MC-LR), a harmful cyanotoxin produced during harmful algal blooms (HABs). While graphene nanoplatelets (GnPs) exhibit high adsorption capacity, their powdered form limits practical application. To address this, GnPs were coated onto 3D-printed poly(lactic acid) (PLA) substrates, enabling enhanced handling for field deployment. Surface characterization using laser confocal microscopy, Raman spectroscopy, and thermogravimetric analysis confirmed GnP distribution and coating uniformity. Batch adsorption experiments revealed pseudo-second-order kinetics, a maximum adsorption capacity (qmax) of 596 μg/g, and adsorption behavior best described by the Langmuir isotherm. Statistical analysis and comparison of multiple isotherm models supported monolayer adsorption on a relatively homogeneous surface, consistent with the structured nature of the GCP material. Although GCPs showed lower adsorption capacity than pristine GnPs, their scalability and reusability offer practical advantages. Future work will focus on integrating GnPs directly into 3D-printed structures and incorporating TiO₂ for photocatalytic degradation, further enhancing performance for HAB toxin remediation
An overview of global navigation satellite system reflectometry in coastal wetlands
No full textWith rising global temperatures, increasing sea levels, and the accelerated erosion of coastal wetlands, efficient methods for monitoring this vulnerable ecosystem are crucial. Traditional approaches, such as manual surveys, are labor-intensive, hazardous, and invasive to the environment they are attempting to protect, while current remote sensing methods are cost prohibitive and rely on irregular data collection techniques. To address these challenges, a scalable solution is needed for reliable and frequent data collection. This study explores the use of GNSS Reflectometry (GNSS-R) combined with unmanned aerial vehicles (UAVs) to monitor the shifting topology in wetlands with minimal human invasion. By leveraging low-cost, mobile platforms equipped with precise GNSS-R systems, this method offers an accurate and cost-effective method to track changes in vegetation and erosion in wetland environments
Effects of environmental stress and antimicrobials on the health, microbiome, and product shelf-life of channel and hybrid catfish
No full textTwo studies investigated various aspects of channel and hybrid catfish production and processing. The first study examined the effects of ammonia stress (15 mg/L vs. 1 mg/L control) on growth performance and fillet quality. While channel catfish demonstrated superior growth, ammonia stress minimally impacted the sensory profiles of both species. Gut microbiota analysis revealed species-specific differences, with Lactococcus lactis dominating hybrid catfish communities. The second study evaluated buffered vinegar treatment (1.5%) on fillet shelf life during refrigerated storage. Vinegar-treated fillets maintained better microbiological quality, with aerobic plate counts remaining below 7 log cfu/g through day 6, while untreated fillets exceeded this threshold. Notably, hybrid catfish fillets treated with vinegar showed the best sensory qualities by day 9. Together, these findings provide insights for optimizing catfish production and processing methods to enhance product quality and shelf life
Work-life balance and the impact of COVID-19 on faculty at Historically Black Community Colleges (HBCCs)
No full textThis research study was conducted to determine how the COVID-19 pandemic affected the work-life balance of faculty at HBCCs based on their race, gender, age, marital status, and tenure status. The study employed a quantitative research design utilizing Exploratory Factor Analysis (EFA) to conduct time-based activities separately and group perception-based response variables into meaningful categories to uncover patterns. To analyze the differences in race, gender, age, marital status, and tenure status, Regression and Chi-square test analyses were used to evaluate the collected data. Regression analysis explored relationships between time spent on activities and perceptions of stress, productivity, and satisfaction. Chi-square tests examined whether significant time-use patterns varied across demographic groups. EFA created three continuous variables: high, medium, and low. This made comparisons and interpretations more insightful. Gender and race-related stress levels were considerably higher among participants in the low personal engagement category, indicating that a decrease in personal activities was a contributing factor to the elevated stress levels. On the other hand, people in the low domestic participation group reported feeling less stressed, suggesting a connection between less stress and fewer household responsibilities. Key findings highlighted the crucial roles of sleep and personal engagement in promoting faculty well-being and work-life balance. However, significant insights were gained into the impact of stress based on gender and race, faculty productivity balance, and the relationship between satisfaction, time management, and childcare responsibilities. Participants in the low sleep category reported significantly worse work-life balance and productivity than those in the high sleep category, indicating that getting enough sleep is essential for preserving both. Low- and medium-sleep individuals also reported considerably lower personal and family satisfaction levels
Compensation challenges in early childhood education: an analysis of Mississippi’s child care workforce
No full textThe early childhood workforce in the U.S. faces significant challenges, including low wages, high turnover, and inadequate support, affecting the quality of education and care for children. The existing research on early childhood education typically identifies low wages as an issue, but lacks advanced analysis of rural–urban pay disparities and how educational qualifications interact with location to affect compensation. This leaves a significant gap in understanding wage compression across the early childhood education (ECE) field. Utilizing the framework of wage compression, which posits that higher qualifications may not equate to higher pay, this study uses data from the 2023 Mississippi Wages Survey to analyze how job experience, educational attainment, and geographic location impact wages for early childhood educators. The results show that average hourly wages for teachers are approximately 11.66, as compared to 9.95 per hour in rural and small urban areas respectively. Years of experience, educational attainment, and geography show the modest effects on wage differences. Higher education correlates with better pay; however, wage increases remain modest, indicating policies targeting only education may insufficiently address compensation issues. Geographic disparities exist, with urban areas generally offering higher wages than rural ones, but small urban areas report lower pay than expected. These findings underscore systemic undervaluation and necessitate policy interventions, such as wage increases and support for professional development, tailored to local contexts, to enhance workforce stability and childcare quality. Wage reforms and increased funding can contribute to elevating the profession. Future research should include longitudinal studies across multiple states for a comprehensive understanding of these issues
Optimizing a Perfusion-Compression Bioreactor via Python Integration
No full textBioreactors are widely used in tissue engineering to support cell and tissue growth under controlled conditions. Perfusion-compression bioreactors, like the one developed in our lab, can be used to replicate the physiological loading of bone on 3D-printed scaffolds. When seeded with osteogenic cells and subjected to mechanical loading, these scaffolds serve as a model to study osteogenesis. To simulate physiological conditions, the bioreactor must apply 1000 compression cycles at forces up to 200 N, three times daily over 14 days. Upon implementation, validation testing and experimental studies exposed several limitations in the bioreactor’s control code. The system was initially programmed in LabVIEW, which is expensive, closed source, and not readily adaptable to changing research needs. During testing, the LabVIEW code frequently overloaded bone explant samples. To resolve these issues, the objective of this project was to transition the control code to Python, an open-source, non-graphical programming language that offers greater flexibility and customization. Transitioning to Python also allows for a more user-friendly, customizable graphical user interface (GUI) to improve accessibility for future researchers. The transition has been implemented step by step. First, timers were enabled to control the retraction and extension of the NEMA 17 linear actuator, which applies compressive forces. Load cells were verified to ensure the force readings were accurate. The actuator and load cell functions have been integrated so the actuator’s behavior adjusts in real time based on the load cell readings. Next, the Linear Variable Differential Transducer (LVDT) displacement sensor will be incorporated to measure small displacements and calculate the stiffness of the scaffold. Beyond optimizing data handling and visualization, this transition from LabVIEW to Python will ensure the bioreactor remains adaptable to new technologies and applications, improving system performance and sustainability
Predictive modeling of spatial distribution of deep-sea benthic macrofauna at a methane seep site using geophysical data
No full textSeafloor seeps are locations where gas is discharged from marine sediments into the ocean. Methane released from seeps in the deep sea drives a wide range of interconnected biogeochemical processes, resulting in unique chemosynthetic ecosystems with relatively high biodiversity. Due to their remote location, these ecosystems are understudied, and there is a lack of information on benthic species distribution, environmental preferences, and habitat associations. We developed a spatial distribution model for the seep foundation species Bathymodiolus childressi mussels, and Paragorgia spp. corals at the deep-sea Veatch Canyon seep site (Depth: ~1410 m). A presence only maximum entropy (MAXENT) model was used to predict the probability of the presence of mussels and deep-sea corals with acoustic data used as most of the explanatory variables. The predictive model was based upon high-resolution (~1m2) multibeam sonar observations of the seafloor bathymetry and acoustic reflectivity collected with an autonomous underwater vehicle. Validation of the model was conducted with a database of mussel and coral location data generated from mosaiced seafloor imagery collected with the same AUV. The accuracy of the model in predicting species presence was evaluated through ten-fold cross validation. The model predicted the presence of mussels in 1.82% of the study area and had an accuracy of 73.22%. The model predicted the presence of corals in 10.93% of the study area and had an accuracy of 73.97%. Explanatory variables such as distance from seeps, seafloor depth, and acoustic backscatter intensity including its statistical derivatives- like standard deviation, maximum backscatter and minimum backscatter- were strongly related to probability of mussel presence and probability of coral presence. This interdisciplinary approach to species distribution modeling demonstrates the potential value of incorporation of less commonly applied acoustic data sources in deep-sea benthic ecological modeling