Racialized Masculinities In The Sexual Field: A Latent Profile Analysis Of Gay Community Stressors

While intra-group discrimination is commonly experienced among men in the LGBT community, little is known about the intersection of multiple forms of discrimination. This study used a latent class analysis (LCA) to visualize the intersections of different forms of perceived discrimination and to evaluate to what degree LCA membership is associated with depression, anxiety, and somatization among a sample of racially and ethnically diverse men who have sex with men (MSM). The data was sourced from the Gay Community Stress Scale (GCSS) wherein participants were asked to what degree their perception of the mainstream gay community’s racism, racial objectification, masculinity consciousness, classism, and tribe consciousness caused them stress. Participants also completed the Brief Symptom Inventory (BSI), a validated measure of psychological distress and psychiatric disorders based on self-report. A total of 937 (66.5 %) MSM were included in the LCA analytic sample (10.7 % Black, 25.1 % Hispanic, 73.4 % Gay). The LCA resulted in a 5-class solution that had a compelling relative and absolute fit. These 5 classes were defined as: Masculinity Stress (11%); Low Stress (47.1 %); Moderate Stress (10.2 %); High Stress (12.2%); Racism Stress (19.5%). Multivariate models revealed that, compared to the Low Stress class, individuals in the High Stress, Moderate Stress class, and the Masculinity Stress class had higher odds of endorsing symptoms of depression, anxiety, and somatization. Interaction effects between race and masculinity were observed in likelihood of latent class membership, with all forms of racialized masculinity/ femininity displaying lower odds of occupying the Low Stress class than masculine White men. Future research should consider the co-occurrence of multiple forms of intra-group discrimination and its impact on the mental health of MSM who occupy the intersection of marginalized racial masculinity and femininity

Design and Implementation of a Vehicle Tracking Mechanism using Wireless Network Infrastructure

This study presents the design and implementation of a vehicle tracking system with the goal of assisting victims of road accidents in obtaining prompt assistance from the rescue team. This is accomplished by sending tracking data to the rescue team's mobile equipment. The system was developed utilising available electronics components, installed in a vehicle. Accident situations were recreated by dropping loads of different sizes from a height and loads linked to a rope to shatter the glass on the automobile in order to determine the minimal impart energy necessary to break the glass and the likelihood of a catastrophic accident. If an accident occurs, the GPS engine sends the coordinates of the crash site to the rescue team's mobile equipment through the SIM900 module's GSM engine over a GSM frequency for tracking. The system's tracking accuracy was determined using a standard GPS device, the GERMIN GPSMAP78s, to get the GPS coordinates of the scene and tracking them using the Google map API. When tracked using Google map, the tracking information obtained, when compared with the GARMIN GPSMAP78s, were exact, indicating that proposed device is capable of transmitting accurate tracking information in a short period of time, thereby saving lives

Design and implementation of a fingerprint-based biometric access control system

Security systems are often penetrated by sophisticated criminals, thus there is always a need for new solutions to be devised to give sufficient security to houses and other locations. The goal of this project is to build and deploy a fingerprint-based biometric access control system. The fingerprint is a pattern of ridges and valleys on the surface of a fingertip. Among various biometrics, fingerprint recognition is the most extensively and internationally accepted biometric because of its uniqueness, accuracy, cost-effectiveness, non-transferability, and ease of use. Presented is the system architecture for the system development that demonstrates component augmentation, detail extraction, and matching methodologies. MATLAB and the programming language C were used to develop a software application that was used to build algorithms for improvement, minutiae extraction, and matching processing. The software works by extracting meaningful features known as minutiae points from the person’s fingerprint, then records and stores these minutiae points to verify the person’s identity in the future.  The resulting minutiae information is used to find matching fingerprints and to register these fingerprints in the system database. Finally, a verification system and identification system were realized. The proposed automatic door access control system was implemented using the Arduino Atmega 328p microcontroller. The proposed system was tried-out in real-time, and its performance was deemed adequate

Effects of Pharmaceutical Effluents on Soil Microbiome and Physicochemical Parameters

Soil contamination from pharmaceuticals is an evolving issue, consequently measurable data on their microbial effects are deficient. Thus, this study investigated the effects of pharmaceutical effluents on soil microbiome and the physicochemical parameters of soil samples obtained from Ugbowo, Benin City, Nigeria using standard procedures. The experiment which lasted for four weeks consists of four treatments of soil samples with pharmaceutical effluents of different percentages and one soil sample without pharmaceutical effluents (control). These include: soil treated with 250 ml of pharmaceutical effluents (25%); soil treated with 500 ml of pharmaceutical effluents (50%); soil treated with 750 ml of pharmaceutical effluents (75%), soil treated with 1000 ml of pharmaceutical effluents (100%) and soil treated without pharmaceutical effluents (0%). There was significant increase in the soil microbial counts in all effluent treatments compared to the control soil. A total of 16 isolates were identified. Ten were isolates belonging to the genera Bacillus, Arthrobacter, Proteus, Pseudomonas, Staphylococcus, Escherichia, Klebsiella, Enterobacter, Streptococcus, and Chromobacterium, while Fusarium sp., Mucor sp., Saccharomyces sp., Aspergillus niger, Rhizopus sp. and Penicillium sp. were the observed fungal isolates. The mean values of the soil physicochemical properties were all significantly higher in the treated groups compared to the control. This study revealed that pharmaceutical effluents altered the soil microbiological and physicochemical properties. The possibility of these alterations was due to the high nutrient content of the effluent which enriched the soil with additional nutrients needed for microbial growth

Optimal sizing of a hybrid photovoltaic/fuel cell grid-connected power system including hydrogen storage

The global energy demand is enormous, yet nonrenewable resources such as fossil fuels, and nuclear power are insufficient to satisfy it. Renewable energy will eventually be the better option. This study investigates the design and optimization of a hybrid photovoltaic / fuel cell (PV/FC) energy system with an H2 tank linked to the grid. The primary objective of this research is to design and size a PV/FC energy system with an H2 storage tank to supply the energy needs of a university ICT center that is connected to an inconsistent grid. HOMER's energy-balance algorithms were used to determine the best design architecture. Using mean solar radiation data (22 years) obtained for the University of Benin ICT Center, hourly simulations were performed to determine the optimum configuration in terms of size, cost, and performance of the energy system. Findings revealed that a hybrid PV/FC power system with a 400 kW solar array, a 250 kW FC, a 240 kW inverter, and a 150 kW electrolyzer with an H2 tank of 700 kg will reliably supplement the inconsistent grid with a high proportion (92%) of renewable resources at $0.1052/kWh. An energy cost reduction of approximately 88 percent and a return on investment of 200 percent with a present value of$98,251,110 could be obtained in less than 2 years over the traditional grid/diesel systems. Using an ideally sized PV/FC hybrid system will alleviate Nigeria's electrical challenges, impeding the country's economic growth. Furthermore, hybrid PV/FC power systems can reduce CO2 emissions, resulting in a more environmentally friendly and sustainable environment

Optimal sizing of a hybrid photovoltaic/fuel cell grid-connected power system including hydrogen storage

The global energy demand is enormous, yet nonrenewable resources such as fossil fuels, and nuclear power are insufficient to satisfy it. Renewable energy will eventually be the better option. This study investigates the design and optimization of a hybrid photovoltaic / fuel cell (PV/FC) energy system with an H2 tank linked to the grid. The primary objective of this research is to design and size a PV/FC energy system with an H2 storage tank to supply the energy needs of a university ICT center that is connected to an inconsistent grid. HOMER's energy-balance algorithms were used to determine the best design architecture. Using mean solar radiation data (22 years) obtained for the University of Benin ICT Center, hourly simulations were performed to determine the optimum configuration in terms of size, cost, and performance of the energy system. Findings revealed that a hybrid PV/FC power system with a 400 kW solar array, a 250 kW FC, a 240 kW inverter, and a 150 kW electrolyzer with an H2 tank of 700 kg will reliably supplement the inconsistent grid with a high proportion (92%) of renewable resources at $0.1052/kWh. An energy cost reduction of approximately 88 percent and a return on investment of 200 percent with a present value of$98,251,110 could be obtained in less than 2 years over the traditional grid/diesel systems. Using an ideally sized PV/FC hybrid system will alleviate Nigeria's electrical challenges, impeding the country's economic growth. Furthermore, hybrid PV/FC power systems can reduce CO2 emissions, resulting in a more environmentally friendly and sustainable environment

Monitoring and Mapping of Atmospheric Concentration of Carbon Monoxide, Sulphur Dioxide, and Nitrogen Dioxide from 2019 - 2022 in Benin City, Southern Nigeria

This study presents a comprehensive monitoring and mapping assessment of the atmospheric concentrations of carbon monoxide (CO), sulphur dioxide (SO2), and nitrogen dioxide (NO2) from 2019 - 2022 in Benin City, Southern Nigeria using Google Earth Engine (GEE) and Sentinel 5P (S5P) TROPOMI satellite data. To extract the pollution map, all satellite datasets were imported into GEE, and pollutant results were obtained through JavaScript coding. The spatial map showed that the highest annual concentration of CO was recorded in 2020 as 0.0554 mol/m2, the highest annual concentration of SO2 was recorded in 2020 as 0.0000866 mol/m2, and the highest annual concentration of NO2 was recorded in 2021 as 0.0000797 mol/m2. For CO, a paired sample t-test revealed that there was a significant difference in 2019 compared to 2020, but not in 2020 compared to 2021. The years 2021 and 2022 did not significantly differ from one another either. There was no significant difference in SO2 across the years. For NO2, there was a significant difference between 2019 and 2020, and also a significant difference between 2020 and 2021, but no significant difference between 2021 and 2022. This study finds that the COVID-19 lockdown protocol was loosely implemented in Benin City, as the results from this study did not effectively correlate with those of other studies. The study also finds the efficacy of S5P in monitoring and mapping the concentrations of CO, SO2, and NO2 in Benin City, laying the groundwork for future research using Sentinel 5

Production of Biodiesel from the Transesterification of Waste Cooking Oil using Biobased Sulphonated Catalyst prepared from Coconut Shells

This study investigated the effects of transesterification process factors on biodiesel yield from waste cooking oil using a biobased sulphonated catalyst made from waste coconut shells. The catalyst was characterized in terms of surface structure, elemental compositions, surface area, pore volume and pore size. Reaction duration was varied from 30 to 180 minutes, catalyst loading varied from 1 to 6 wt%, and reaction temperature varied from 45 to 65°C are among the transesterification process variables studied. The Box Behnken design (BBD) of response surface methods was used to design the transesterification reaction. The catalyst surface morphology revealed that it has an uneven pore structure while elemental composition revealed that it is mainly composed of CaO (17.32%), SiO2 (21.40%), SO3 (21.04%), and Al2O3 (13.68%). The catalyst surface area, pore volume, and pore size were determined to be 474.4 m2.g-1, 0.295 cm3.g-1, and 2.144 nm, respectively. Reaction time and temperature had significant effect on the biodiesel yield while the influence of catalyst dosage was minimal. After a reaction time of 147.73 minutes and a catalyst dosage of 2.18 wt % at a reaction temperature of 65°C, a maximum yield of 96.22 percent of biodiesel was produced. The predicted R2 (0.9541) and actual R2 (0.7705) values were found to be in good agreement. Due to the high output of biodiesel, waste cooking oil could be a low-cost biobased feedstock for biodiesel formulations. The characteristics of biodiesel made from waste cooking oil were comparable to those of conventional biodiesel

Factors Impacting COVID-19 Vaccine Hesitancy and Resistance Among College Students in Northwest Ohio

Background: Vaccination is a critical strategy for controlling the transmission of COVID-19 and for returning to normalcy on college campuses; however, vaccine hesitancy and resistance persist as a significant barrier. This study utilized the integrated behavior model (IBM) and the precaution adoption process model (PAPM) to identify factors predictive of COVID-19 vaccine willingness (receptive, hesitant, and resistant) among college students. Methods: A sample of 1248 students at 2 universities in northwest Ohio were surveyed online in 2021. Stata/SE, version 17 (StataCorp) software was used to conduct stepwise logistic regression to investigate the association of theoretical constructs with vaccine willingness, after controlling for COVID-19 related factors and sociodemographic factors. Results: Most students (82.5%) were vaccine receptive, 6.9% were vaccine hesitant, and 10.6% were vaccine resistant. Vaccine hesitancy was higher among students aged 18 to 22 years (9.3%), undergraduates (16.5%), and students who identified as Black (13%) or Middle Eastern (14.3%). Lower vaccine hesitance was significantly predicted by IBM constructs of positive attitudes, high self-efficacy, and high salience. Not getting an influenza vaccine in the past 3 years and viewing vaccination as a personal choice were significantly associated with higher vaccine hesitancy. Lower odds of vaccine resistance were predicted by higher subjective norms. Descriptive norms, not getting an influenza vaccine in the past 3 years, agreeing with conspiracies, and viewing vaccination as a personal choice were strongly predictive of higher vaccine resistance. Conclusion: Identifying the factors that predict vaccine hesitancy and resistance among college students is critical for college administrators, and for those who are designing health communication campaigns, to increase vaccination among this priority population

Soil Adjusted Vegetation Index, Normalize Difference Buildup Index, and Land Surface Temperature between 1987 and 2023 in Abuja Municipal Area Council, Nigeria

Abuja Municipal Area Council (AMAC) is experiencing rapid urban expansion, which is expected to impact land surface temperatures (LST). This paper evaluates the trends in soil adjusted vegetation index (SAVI), normalize difference buildup index (NDBI), and land surface temperature (LST) between 1987 and 2023 in AMAC using Landsat 4 Thematic Mapper and Landsat 8 Operational Land Imager/Thermal Infrared Sensor imagery, respectively. Results show that in 1987, SAVI ranged from -0.126 to 0.477, NDBI from -0.186 to 0.678, and LST from 27.18 to 46.4 oC. In 2023, SAVI ranged from -0.253 to 0.71, NDBI from -0.308 to 0.619, and LST from 23.89 to 46.57 oC. Analysis showed an increase in vegetation in 2023 compared to 1987. Built-up and bareland areas became more concentrated in the northeast in 2023 compared to 1987, and temperature reductions were observed in areas with increased vegetation, notably in the south and southwest. Correlation analysis indicated a strong negative relationship (-0.772) between SAVI and LST in 1987, weakening in 2023 (-0.389). NDBI and LST remained moderately positively correlated (0.645 in 1987, 0.621 in 2023). Significant differences (P<0.01) were observed between 1987 and 2023 SAVI, NDBI, and LST values. These findings have important implications for environmental monitoring, and urban planning in rapidly urbanizing areas such as AMA