Tuskegee University

MiR-184 plays a significant regulatory role in immunity during pregnancy. Its dysregulation in toxoplasmosis and rubella infection is strongly associated with increased risk of abortion . Further clinical studies are needed to validate miR-184 as a diagnostic marker and therapeutic target in pregnancy complications. One hundred specimens of blood were taken from the miscarriage ladies, with age ranges between 15 and 50 years, who were complaining of TORCH infections. The findings showed that the age range group (<20-29 years) was the highest at (59.0%), followed by (30-39 years) at (36.0%), and then (40-46 years) 5 (5.0%). Distribution of infections according to residency showed the patients that living in rural areas were higher 59 (59.0%) than those who lived in urban areas (41.0%), while the number and percentage of acute infections with rubella were higher 29 (29%) than toxoplasmosis (4.0%) in aborted women with TORCH infections. However, 4 (4.0%) of Toxoplasmosis was recorded compared to 0 (0.0%) CMV infection. The evaluation of IgM antibodies showed that Rubella IgM levels were higher at 29 (29.0%) in comparison to CMV IgM levels of 0 (0.0%). The number and percentage of rubella IgM levels among the age group (<20-29) were higher (18.0%) than in other age groups, while it was (9.0%) among the age group (30-39) years and 4 (4.0%) among Toxoplasmosis. Out of 100 patients, gene expression of MicroRNA-184 was done on 33 patients, and the results revealed that 10 (27.2%) of the aborted women were carriers of Toxoplasmosis, CMV, and Rubella IgM, and they had positive MicroRNA-184.

The journal retracts the article titled "Malted barley as a potential feed supplementation for the reduction of enteric methane emissions, rumen digestibility, and microbiome community changes in laboratory conditions" [...].

This study presents a comprehensive life-cycle assessment and techno-economic analysis of a 270.665 kWdc solar photovoltaic (PV) system installed at Aswaq Al Salam in Jordan. Using OpenLCA with the Ecoinvent database, greenhouse gas emissions were evaluated across major components including solar panels, steel structures, cables, and inverters. Results show that the total system impact is 232,367.84 kg CO 2 -eq over its 25-year lifetime, with the majority (74.6%) originating from solar panel manufacturing due to an energy-intensive silicon purification process. When compared to grid electricity, which would have produced 7,915,520.10 kg CO 2 over the same period, the PV system achieves a 97.06% reduction in emissions, corresponding to only 15.59 g CO 2 /kWh. An off-grid alternative with a 3 MWh battery storage was also assessed, yielding a higher footprint of 431,929.63 kg CO 2 -eq, primarily due to emissions from lithium-ion battery production. In addition to the environmental assessment, a discounted techno-economic evaluation was performed. The total investment cost was estimated at USD169,200, yielding first-year savings of USD92,891. When accounting for discounting, operation and maintenance costs, and electricity price escalation, the system achieves a net present value of approximately USD979,950 over 25 years and a levelized cost of electricity of USD0.024/kWh, significantly lower than the prevailing grid electricity tariff. The simple payback period remains short at 1.82 years, confirming both the short-term attractiveness and long-term economic robustness of the grid-connected PV system.

SAC (Sn-Ag-Cu) solder joints are frequently exposed to thermal cycling, leading to microstructural evolutions that accelerate thermal fatigue. During thermal cycling, the coarsening of Ag<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub>Sn precipitates and recrystallization occur, impacting the reliability and microstructure of solder joints. To enhance the high-temperature performance of lead-free alloys, dopants such as Bismuth (Bi), Antimony (Sb), and Indium (In) have been proposed by leveraging the solid solution and dispersion-strengthening mechanisms. However, limited studies have investigated the impact of varying paste volumes of third-generation alloys on thermal cycling reliability and the resulting microstructural evolution. This study examines the thermal cycling reliability of three CABGA208 components mounted on a printed circuit board (PCB) using three different paste alloys, namely SAC305, SAC-Bi, and SAC-Bi-Sb, while maintaining fixed 18-mil SAC305 solder balls. Three paste volumes were printed to achieve paste-to-sphere-volume ratios of 0.1, 0.3, and 0.5. The PCB was plated with Electroless Nickel Immersion Gold (ENIG) and Organic Solderability Preservative (OSP) surface finishes. Thermal cycling tests were conducted between -40 °C and +125 °C, with a dwell time of 15 minutes and a ramp rate of 10°C/min. Weibull analysis revealed that doped alloys outperformed SAC305, with SAC-Bi exhibiting the highest reliability. A higher paste-to-sphere volume ratio generally improved reliability, except for SAC-Bi-Sb, where larger voids formed at higher paste volumes. The ENIG surface finish provided better performance than OSP, likely due to the beneficial effect of the Ni layer. Microstructural analysis showed that higher paste volume in SAC-Bi and SAC-Bi-Sb significantly reduced Ag<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub>Sn coarsening. Additionally, increased paste volume resulted in a thinner intermetallic compound (IMC) layer and less evolution.

ABSTRACT This study presents a comprehensive numerical investigation of buoyancy‐driven boundary‐layer flow and heat transfer of viscoelastic (non‐Newtonian) fluids over a horizontal surface subjected to two fundamental thermal boundary conditions: constant surface temperature (CST) and constant heat flux (CHF). Using similarity transformations, the governing nonlinear partial differential equations are reduced to a coupled system of ordinary differential equations and solved to examine the influence of the Prandtl number (0.7 ≤ Pr ≤ 100) and the viscoelastic parameter (0.10 ≤ A ≤ 0.21) on velocity and temperature fields, boundary‐layer thickness, wall shear stress, and the modified Nusselt number. The results show that increasing viscoelasticity suppresses buoyancy‐driven convection, leading to reduced peak velocities, thicker momentum and thermal boundary layers, lower wall shear stress, and reduced heat transfer rates under both CST and CHF conditions. Increasing the Prandtl number from 0.7 to 100 enhances near‐wall temperature gradients, significantly thins the thermal boundary layer, and increases the Nusselt number, with a stronger influence observed under CST conditions. A key finding is that CHF exhibits significantly greater sensitivity to viscoelastic effects than CST due to the dynamic adjustment of wall temperature required to sustain a prescribed heat flux, which amplifies elastic damping and modifies buoyancy forces. The study highlights the coupled roles of fluid elasticity and thermal diffusion and demonstrates that neglecting viscoelastic effects can lead to overestimation of heat transfer performance. The results provide design‐oriented insights for thermal energy storage, electronic cooling, polymer processing, and other applications involving buoyancy‐driven transport of viscoelastic fluids.

Agricultural production remains highly susceptible to water-related risks, such as drought and flooding. Although hydrologic forecasting systems, such as the National Water Model (NWM), have advanced considerably, their outputs are rarely used for real-time agricultural decision-making. This study developed the Agricultural Water Risk Indicator (AWRI), a framework that translates NWM streamflow forecasts into crop-specific risk assessment indicators. The AWRI framework has three key components: (1) the hydrological threat and exposure characterization based on NWM streamflow forecasts (B1); (2) crop sensitivity by growth stage and water needs (B2); and (3) adaptive capacity reflecting the presence of irrigation or drainage infrastructure (B3). The AWRI was evaluated across three NWM reach IDs covering five farm sites in the Black Belt region of Alabama, USA. The results show that the AWRI captured variations in hydrologic conditions, risk, and crop tolerance across the research sites within the one- to four-week forecast range. Crops in the reproductive stage were especially sensitive. Without resilience measures, up to 55% of the crops simulated at some sites had high-risk AWRI categories. Including irrigation or drainage decreased risk scores by one to two levels. The AWRI tool provides farmers and stakeholders with critical information to support proactive agricultural water management.

The Comprehensive Partnerships to Advance Cancer Health Equity (CPACHE) initiative of the National Cancer Institute (NCI) supports long-standing collaborations between an under-resourced institution and NCI-designated Cancer Centers to strengthen cancer research workforce and advance cancer research capacity. One of the longest continuously funded CPACHE programs is the Morehouse School of Medicine/Tuskegee University/University of Alabama at Birmingham O'Neal Comprehensive Cancer Center tri-institutional partnership. A central component of this partnership is training future generations of investigators, which is accomplished through the research education programs that are designed to build cancer research skills, enhance mentorship, and support career development for all levels from high school students to Early-Stage Investigators (ESIs). This paper evaluates the longitudinal impact of a year-long program for ESIs and postdoctoral fellows since its inception in 2007. The data were extracted from the Research Education Core administrative records about the scholars and mentors and utilized publicly accessible databases Scopus and PubMed for publications, and the NIH RePORTER for grants. Among 89 program scholars, nearly 95% had at least one publication since their program start date. Of these, 70% had a first author, and 62% had a senior author publication. Approximately 20% of scholars obtained NIH funding as principal investigators through grants, core leadership, and/or supplements. This tri-institutional program successfully attracted investigators committed to cancer research. The outcomes suggest that structured training, intensive mentorship, and cross-institutional collaboration can meaningfully support their academic careers. These findings provide insights for strengthening similar programs to continue to meet the evolving professional needs for the development of ESIs and postdoctoral fellows, particularly at under-resourced institutions.

In this paper, we develop a secure cell-free massive multiple-input multiple-output (CF-mMIMO) communication system assisted by a passive reconfigurable intelligent surface (RIS). In this model, multiple mobile unmanned aerial vehicle access points (UAV-APs) are tasked with communicating with multiple legitimate users (UEs), while multiple jammers are in charge of sending interference signals to UEs. This work proposes a unique framework to maximize the average sum secrecy rate (ASSR) by jointly optimizing the UAV’s trajectory, total transmit power at UAV-APs, and RIS phase shift. Ensemble global optimization (EGO) is implemented followed by deep learning (DL) techniques for optimization with low computational complexity. In particular, we train a deep neural network offline, to optimize the RIS phase shift, UAV-AP trajectory, and UAV-AP transmission powers online. A real-time optimization capability of the trained model is assessed online with low computational complexity. The numerical results show the performance analysis of the best neural network for real-time optimization. Furthermore, numerical results demonstrate that passive RIS technology and increased UAV-AP speed significantly enhance the performance of the cell-free communication system.

With the advent of the Google Colab, a free, online Jupyter notebook environment, it is now possible for anyone with internet access to use Jupyter notebooks to program in Python without installing any software. In the POGIL-PCL project, Jupyter notebooks have been developed to teach basic notebook use and coding, to analyze data with linear and nonlinear optimization, and to exploit the symbolic math capabilities. A 3-session workshop for instructors to learn Jupyter and its use in teaching Physical Chemistry was developed and run during Spring 2024. In general, the workshop was well-received and sparked discussions about pedagogical uses of programming in chemistry. We will discuss best practices for notebooks in the guided inquiry environment for four main areas: reading code, data analysis and nonlinear optimization, symbolic math manipulation, and writing code.