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Racial (Dis)Empowerment and Racial Consciousness of Black Student-Athletes: A Phenomenological Study
No full textBlack College Student-Athletes (BCSA) have spent their time generating millions of dollars in revenue for their respective collegiate athletic programs and intuitions. In 2021 the Name, Image, and Likeness (NIL) ruling (NCAA, 2021) shifted scales of power towards student-athletes (SA) to reap benefits for their NIL, yet many are still left feeling unsupported. Although, SAs have more autonomy over their NIL now, Donnor (2005) notes, “student athlete’s physical talent and ability are the property of the institution” (p. 54) which still rings true today and can be a disempowering experience for BCSAs. BCSAs who transition from being SA (with/without a degree) often feel exploited for their athletic abilities (Cooper, 2019). Additionally, BCSAs are and historically been subjected to racial discrimination in the same Predominantly White Institutions (PWI) where they are essentially employees in contrast to Historically Black College and Universities (HBCU) that are designed to be a welcoming environment of learning and solace for Black college students in general, since their inception. This study hoped to inform and compel college student-athletes’ stakeholders to create more empowering and racially conscious environments for their BCSAs to thrive. Black college student-athletes in the study shared their experiences with racial (dis)empowerment and racial conscious at their current HBCU in contrast to their high school experiences. Results showed that many BCSAs experienced stress related to being a racial minority in PWIs. A common theme to mitigate this was the connectedness through Blackness that was empowering, supportive, and safe for BCSAs, experienced at HBCUs
Enhancing Growth and Lignocellulosic-Biomass Yield Through the Use of Naturally Occurring Growth-Promoting Microbial Endophytes in Sorghum
No full textCurrently, ~2.5% of the world’s transportation fuels are produced from crop plants including maize, sugarcane, and vegetable oils. However, extensive use of both maize and sugarcane as biofuel feedstock will pose a threat to food security, as they will compete with other food crops for irrigation and arable land resources. For this reason, in the United States of America (USA), Sweet Sorghum [Sorghum bicolor (L.) Moench], is considered a leading candidate for lignocellulosic biofuel feedstock, partly because of its high biomass production, wide adaptation, low agronomic input requirements, and accumulation of sugars in its stalks. Other agronomic traits, like the short life cycle of about four months, low cost of cultivation, and C4 photosynthesis are especially helpful for its adoption as a biofuel feedstock; however, sorghum itself is recalcitrant to genetic manipulation and is threatened by various diseases, limiting its growth. To address these issues, we used naturally-occurring, growth-promoting rhizobacteria—Biological Control Agents (BCAs) to enhance sorghum growth and its biomass traits. Four BCAs will be investigated: Bacillus thuringiencis (IMC8), Bacillus subtilis (PRT), Bacillus vallismortis (PS), and Bacillus amyloliquefaciens (PSL). Specifically, we investigated the biochemical mechanisms that underlie the beneficial interactions between BCAs and sorghum by evaluating BCAs’ impacts on two varieties of sorghum: Dale and Topper 76-6, well known to be cultivated in the state of Tennessee through three objectives: (i) Evaluation of the effects of BCAs in sorghum seed germination and growth. (ii) Phenotypical characterization of BCA-host sorghum plants interaction (iii) Evaluation of biochemical mechanisms underlying BCA-host sorghum plants interaction. Results show that none of the BCAs were harmful to sorghum plants, and they all promote germination and overall growth. However, these BCAs may provide other benefits that are subject to further analyses. Overall, our studies indicate that BCAs naturally and safely promote sorghum growth, suggesting that they can be used as a replacement of chemical products that are harmful for plants or humans
Modeling, Simulation, Fabrication, and Defect Analysis of Polyvinylidene Fluoride (PVDF) Acoustic Sensors
No full textInfrastructural damage to military vehicles due to corrosion remains costly and is a major concern for the Navy. To minimize the future risk of excessive damage to vehicles, it is imperative that efficient and reliable sensors are developed to track the progression of corrosion. One such sensor is a surface acoustic wave (SAW) sensor which is a class of micro-electrical mechanical sensors (MEMS). In this research, we developed a systematic approach to model, simulate, fabricate, and analyze a PVDF-based SAW sensor. The system consisted of three primary components 1) model and simulate the PVDF-based SAW sensor 2) fabricate the PVDF-based SAW sensor using the photolithographic processes and use optical microscopy to image the sensors 3) detect and classify the presence of defects within the PVDF-based SAW sensor. Following the system engineering approach, the proposed system was composed into two subsystems: SAW Sensor Design subsystem, and Defect Detection Model subsystem. All subsystems were developed, integrated, verified, and validated in this dissertation. To evaluate the proposed system, deep learning was employed to develop an autoencoder convolutional neural network to classify features with the optical image data. The efficacy of the autoencoder was validated using statistical analysis that evaluated classification accuracy
Magnetic Nanoparticles Enhanced Surface Plasmon Resonance Biosensor for Rapid Detection of Salmonella Typhimurium in Romaine Lettuce
Get PDFSalmonella is one of the major foodborne pathogens responsible for many cases of illnesses, hospitalizations and deaths worldwide. Although different methods are available to timely detect Salmonella in foods, surface plasmon resonance (SPR) has the benefit of real-time detection with a high sensitivity and specificity. The purpose of this study was to develop an SPR method in conjunction with magnetic nanoparticles (MNPs) for the rapid detection of Salmonella Typhimurium. The assay utilizes a pair of well-characterized, flagellin-specific monoclonal antibodies; one is immobilized on the sensor surface and the other is coupled to the MNPs. Samples of romaine lettuce contaminated with Salmonella Typhimurium were washed with deionized water, and bacterial cells were captured on a filter membrane by vacuum filtration. SPR assays were compared in three different formats—direct assay, sequential two-step sandwich assay, and preincubation one-step sandwich assay. The interaction of flagellin and MNPs with the antibody-immobilized sensor surface were analyzed. SPR signals from a sequential two-step sandwich assay and preincubation one-step sandwich assay were 7.5 times and 14.0 times higher than the direct assay. The detection limits of the assay were 4.7 log cfu/mL in the buffer and 5.2 log cfu/g in romaine lettuce samples
Conversion of Food Waste into 2,3-Butanediol via Thermophilic Fermentation: Effects of Carbohydrate Content and Nutrient Supplementation
Get PDFFermentation of food waste into 2,3-butanediol (2,3-BDO), a high-value chemical, is environmentally sustainable and an inexpensive method to recycle waste. Compared to traditional mesophilic fermentation, thermophilic fermentation can inhibit the growth of contaminant bacteria, thereby improving the success of food waste fermentation. However, the effects of sugar and nutrient concentrations in thermophilic food waste fermentations are currently unclear. Here, we investigated the effects of sugar and nutrients (yeast extract (YE) and peptone) concentrations on 2,3-BDO production from fermenting glucose and food waste media using the newly isolated thermophilic Bacillus licheniformis YNP5-TSU. When glucose media was used, fermentation was greatly affected by sugar and nutrient concentrations: excessive glucose (\u3e70 g/L) slowed down the fermentation and low nutrients (2 g/L YE and 1 g/L peptone) caused fermentation failure. However, when food waste media were used with low nutrient addition, the bacteria consumed all 57.8 g/L sugars within 24 h and produced 24.2 g/L 2,3-BDO, equivalent to a fermentation yield of 0.42 g/g. An increase in initial sugar content (72.9 g/L) led to a higher 2,3-BDO titer of 36.7 g/L with a nearly theoretical yield of 0.47 g/g. These findings may provide fundamental knowledge for designing cost-effective food waste fermentation to produce 2,3-BDO
Evaluation of Selected Bacteria and Yeast for Probiotic Potential in Poultry Production
Get PDFPerformance and efficiency of feed utilization in poultry is highly influenced by gut health, which is dependent on intestinal microbial balance. Probiotics are live microbial feed supplements or viable microorganisms that beneficially affect the host animal by improving its gastrointestinal tract (GIT) microbial balance. However, their mode of action and suitable GIT environment favoring their colonization of the GIT is obscure. The probiotic properties of Lactobacillus plantarum, Bifidobacterium longum, and Saccharomyces boulardii were evaluated. These microbes were tested in vitro against gastrointestinal conditions for survivability and their ability to attach to the intestinal mucosa. The ability of the microbes to tolerate and survive varying pH levels and bile concentrations was assessed. The microbes were challenged with a pH of 2 to 7 for 5 h and bile concentrations of 1 to 3% for 6 hrs. The microbes were sampled hourly to evaluate growth or decline in colony-forming units (CFU). B. longum, L. Plantarum, and S. boulardii exhibited significantly higher CFU (p \u3c 0.05) at a pH range of 5 to 7, 4 to 7, and 2 to 7, respectively, when compared with other pH levels. L. plantarum had much higher colony-forming units per mL within each pH level, except at pH 2 where S. boulardii was the only microbe to survive over time. While L. plantarum and S. boulardii were able to tolerate the various bile concentrations, B. longum and L. plantarum showed remarkable ability to attach to the intestinal mucosa and to inhibit pathogenic microbes
A Complete Process of Text Classification System Using State-of-the-Art NLP Models
Get PDFWith the rapid advancement of information technology, online information has been exponentially growing day by day, especially in the form of text documents such as news events, company reports, reviews on products, stocks-related reports, medical reports, tweets, and so on. Due to this, online monitoring and text mining has become a prominent task. During the past decade, significant efforts have been made on mining text documents using machine and deep learning models such as supervised, semisupervised, and unsupervised. Our area of the discussion covers state-of-the-art learning models for text mining or solving various challenging NLP (natural language processing) problems using the classification of texts. This paper summarizes several machine learning and deep learning algorithms used in text classification with their advantages and shortcomings. This paper would also help the readers understand various subtasks, along with old and recent literature, required during the process of text classification. We believe that readers would be able to find scope for further improvements in the area of text classification or to propose new techniques of text classification applicable in any domain of their interest