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Wastewater Surveillance of SARS-CoV-2 Genomic Populations on a Country-wide Scale Through Targeted Sequencing
Get PDFSARS-CoV-2 surveillance of viral populations in wastewater samples is recognized as a useful tool for monitoring epidemic waves and boosting health preparedness. Next generation sequencing of viral RNA isolated from wastewater is a convenient and cost-effective strategy to understand the molecular epidemiology of SARS-CoV-2 and provide insights on the population dynamics of viral variants at the community level. However, in low- and middle-income countries, isolated groups have performed wastewater monitoring and data has not been extensively shared in the scientific community. Here we report the results of monitoring the co-circulation and abundance of variants of concern (VOCs) of SARS-CoV-2 in Uruguay, a small country in Latin America, between November 2020—July 2021 using wastewater surveillance. RNA isolated from wastewater was characterized by targeted sequencing of the Receptor Binding Domain region within the spike gene. Two computational approaches were used to track the viral variants. The results of the wastewater analysis showed the transition in the overall predominance of viral variants in wastewater from No-VOCs to successive VOCs, in agreement with clinical surveillance from sequencing of nasal swabs. The mutations K417T, E484K and N501Y, that characterize the Gamma VOC, were detected as early as December 2020, several weeks before the first clinical case was reported. Interestingly, a non-synonymous mutation described in the Delta VOC, L452R, was detected at a very low frequency since April 2021 when using a recently described sequence analysis tool (SAM Refiner). Wastewater NGS-based surveillance of SARS-CoV-2 is a reliable and complementary tool for monitoring the introduction and prevalence of VOCs at a community level allowing early public health decisions. This approach allows the tracking of symptomatic and asymptomatic individuals, who are generally under-reported in countries with limited clinical testing capacity. Our results suggests that wastewater-based epidemiology can contribute to improving public health responses in low- and middle-income countries
Trashed: A Review of Anthropogenic Litter in an Urban Watershed
Get PDFUrban creeks, streams and rivers have become an unfortunate destination for trash pollution. Within an urban watershed trash pollution is harmful to fish, wildlife, public health, contributes to microplastic proliferation, and aesthetically tarnishes an otherwise unscathed ecosystem. With lots of attention focused on trash in marine and coastal ecosystems, this study aims to contribute to the growing research on inland urban watersheds and their involvement. This study highlights issues associated with trash pollution, and investigates the associated vectors, origins, behaviors, and contributing factors that create trash ladened urban watersheds. Datasets and site surveys from repeated trash cleanups in three creekside sites along the Salado Creek Watershed (US-1, MS-2, and LS-3) in Central Texas were analyzed to quantify volumes of specific trash categories and determine their likely origins. This analysis showed that quantitatively, plastic (i.e., bottles, toys, single use items, packaging and miscellaneous scrap) made up a majority (30%) of the trash found throughout the sites. Visual analysis of the Salado Creek Watershed sites yielded four main origins: intentional dumping, encampments, pedestrian/motorist right-of-way, and construction. Given the sites’ proximity to the creek, stormwater flows and past flood events were the main vector. Additionally, with the frequency of encampments throughout the area of study, encampments were also considered a vector. This study also collected surveys and interviews with the general public to assess awareness of trash pollution and shine a light on behaviors that contribute to its spread
The Effects of Anthropogenic Sensory Pollution on Arthropod Diversity and Pollinator Behavior
Get PDFPollinators provide a key ecological function in terrestrial ecosystems, yet in recent years, they have encountered unprecedented declines, likely due to anthropogenic change. Light and noise pollution, which can interfere with the visual and auditory systems of animals that regulate daily behaviors, are important factors to consider when communities are encroached by human development. While many researchers have looked at how vertebrate species behaviorally react to human caused habitat degradation and sensory pollution, little is known about how invertebrates, including arthropod pollinators, are affected, and whether there is a negative cascading effect on the plants that they pollinate. This research investigates threats to arthropod biodiversity and pollination services from light pollution and noise pollution with field observations and experiments. This research is unique and is an important first step to understanding why arthropods and arthropod pollinators are in decline and will inform land managers in important conservation action
Social Justice Mathematics: Classroom Practices that Give Students Rigor While Building Agency
Get PDFThe purpose of this study is to examine the impact of a social justice approach to mathematics instruction. While many students have math aversion, students in low socioeconomic communities exhibit this to a higher degree putting them at a disadvantage as they progress through their educational career. More than 3.4 million K-12 students in the United States come from families that earn less than the median income yet achieve scores in the top percentile (Wyner et al., 2007). This raises the question of why so many students in low-socioeconomic settings are not given rigorous content that will keep them competitive on the national stage. Because the study draws from a population of low-socioeconomic status, all participants are from a district of low-socioeconomic status (94% are designated by the state as economically disadvanted), therefore demonstrating a need for this study. Teaching math using social justice not only provides grade level appropriate and rigorous content, but it also helps them be informed of the injustices’ students in low-socioeconomic settings are facing that they may not notice. In most research done on social justice math, the discussion focuses on the impact of student performance and not the actual teaching methods. Of the research done on the topic, it is frequently pointed out that there are very few methods to teach social justice math that are known (Leonard, J., Brooks, W., Barnes-Johnson, J., & Berry, R. Q., 2010). Therefore, it is imperative to research what methods are successful for the implementation of social justice in a math classroom
Journey into Adulthood: Understanding the Changing Landscape of Transition Planning
Get PDFTransition to adulthood is an important milestone for all students. Transition planning for students with disabilities (SWD) is legally mandated to prepare them for adult life. However, researchers report that teachers do not feel adequately prepared when it comes to transition. With globalization in the 21st century, U.S schools become more culturally, ethnically, and linguistically diverse. As a result, it is important for teachers to be prepared to work with students from diverse backgrounds. Therefore, we discussed recommendations for embedding culturally responsive practices in transition planning as they have the potential to benefit students preparing to enter adult life. Equally important are personal cultural values that lay the foundation for implementing culturally responsive transition planning (Suk, Martin, et al., 2020). The goal of this article is to provide teachers with critical transition information and resources that could be used to prepare SWD from diverse backgrounds for post-school environments and the achievement of aspired goals
Behavioral Consultation in Inclusive Preschool Classrooms
No full textThe purpose of this report is to describe a behavior consultation model that has been successfully tested in early childhood classrooms. A behavior consultant can assist in a teachers’ use of behavior analytic techniques, which have proven successful in classroom settings when applied. Recommendations for choosing a behavior consultant and successful behavior strategies are presented
Detecting AI Generated Text Using Neural Networks
Get PDFSince the creation of the perceptron in the late 1950’s, neural networks have been used as a theoretical model for machine learning but have been limited by the computational proficiency of our machines. Over the past three decades, increasing computational power has allowed neural network research to flourish at an unprecedented rate. For this research, we explore the topic of detecting machine generated text by using a neural network that learns how to read language. Particularly, we took a pre-trained model, RoBERTa, and used it to distinguish between human, mutation, and synthetic text. The topic of machine generated detection has been scarcely researched, making the detection of AI (e.g. Chat-GPT) a very hot topic in academia
The Importance of Faculty Mentorship in Higher Education
Get PDFFaculty mentorship can have an impact on a student\u27s academic performance and career exploration in higher education. Several studies have highlighted the stressors that can hinder students from pursuing higher education, including the gap between themselves and their peers. However, data has supported that many of these concerns are not only addressed by faculty support but oftentimes are resolved by the increased opportunities these mentorships provide. Faculty mentoring programs, such as the Faculty Advising Program, offer students the consistent guidance and resources needed to thrive during their time in college. The data presented for our poster is from our own program here at Texas A&M University-San Antonio and includes over 4 years of survey data that allows us to make a thorough analysis and provide consistent results. Therefore, the question we wish to answer is, what is the extent, importance, and impact of faculty mentorship on college students
Detecting AI generated text using neural networks
Get PDFFor humans, distinguishing machine generated text from human written text is men- tally taxing and slow. NLP models have been created to do this more effectively and faster. But, what if some adversarial changes have been added to the machine generated text? This thesis discusses this issue and text detectors in general. The primary goal of this thesis is to describe the current state of text detectors in research and to discuss a key adversarial issue in modern NLP transformers. To describe the current state of text detectors a Systematic Literature Review was done on 50 relevant papers to machine-centric detection in chapter 2. As for the key ad- versarial issue, chapter 3 describes an experiment where RoBERTa was used to test transformers against simple mutations which cause mislabelling. The state of the literature was written at length in the 2nd chapter, showing how viable text detection as a subject has become. Lastly, RoBERTa was shown to be vulnerable to mutation attacks. The solution was found to be fine-tuning it to some heuristics, as long as the mutations can be predicted the model can be fine tuned to detect them
ANALYZING THE SYSTEM FEATURES, USABILITY, AND PERFORMANCE OF A CONTAINERIZED APPLICATION ON CLOUD COMPUTING SYSTEMS
Get PDFThis study analyzed the system features, usability, and performance of three serverless cloud computing platforms: Google Cloud’s Cloud Run, Amazon Web Service’s App Runner, and Microsoft Azure’s Container Apps. The analysis was conducted on a containerized mobile application designed to track real-time bus locations for San Antonio public buses on specific routes and provide estimated arrival times for selected bus stops. The study evaluated various system-related features, including service configuration, pricing, and memory & CPU capacity, along with performance metrics such as container latency, Distance Matrix API response time, and CPU utilization for each service. Easy-to-use usability was also evaluated by assessing the quality of documentation, a learning curve for be- ginner users, and a scale-to-zero factor. The results of the analysis revealed that Google’s Cloud Run demonstrated better performance and usability when com- pared to AWS’s App Runner and Microsoft Azure’s Container Apps. Cloud Run exhibited lower latency and faster response time for distance matrix queries. These findings provide valuable insights for selecting an appropriate serverless cloud ser- vice for similar containerized web applications