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Investigating the diagnostic performance and interpretation of the Tritrichomonas foetus direct reverse transcriptase real time quantitative polymerase chain reaction
No full textTritrichomonas foetus, an extracellular protozoan parasite, causes reproductive inefficiency in cow-calf herds when transmitted from the asymptomatic bull host to the cow during coitus. The potential economic impact of T. foetus on the beef cattle industry has led many states to adopt regulations regarding testing, movement, and the culling of infected bulls. A RT-rtPCR offers advantages over other diagnostic modalities, including: 1) it can be performed utilizing smegma samples collected in phosphate buffered saline (PBS) without culture enrichment, 2) has reported improved diagnostic sensitivity and specificity, and 3) has a reported lower limit of detection (LOD). However, veterinarians do not regularly stock PBS. This work aims to determine if 0.9% physiologic saline, a fluid media readily available to veterinarians, is noninferior to PBS as a collection and transport media for T. foetus RT-rtPCR. Further, this work investigates the clinical interpretation and performance of the RT-rtPCR near the LOD
Advancing wood chip moisture content prediction using advanced generative AI techniques
No full textIn this study we propose a deep learning method to optimize the classification of wood chip moisture content levels using the Vision Transformer and then ultimately increase the classification performance by creating synthetic images using the diffusion transformer model. In the first chapter of our study, we complete a detailed explanation of how the moisture content levels of 10 different wood chips were gathered ranging from 2 to 50. This chapter serves as a foundation for subsequent sections, illustrating the challenges associated with the current data collection process, which is both time-consuming and inefficient. Accurately determining moisture content for wood chips is significant in different industries such as pellet mills, bio refineries, and paper mills, and for that reason, in the second chapter of our study, we concentrate on developing an advanced computer vision model named MoistViT. To achieve the MoistViT, we complete an extensive evaluation of fourteen different Vision Transformer models and supplement them with the Bayesian Optimization Hyperband method to achieve superior performance when classifying moisture content levels. In our third chapter, we concentrate on creating high-definition synthetic wood chip images while using the computational limitations faced by many researchers when training advanced models. The importance of creating the generated wood chip images comes from the fact that current data-driven methods used to measure the moisture content of wood chips need a large amount of data to train the models to eventually achieve state-of-the-art results and the current method used to create the wood chip images is destructive and time-consuming. Therefore, we propose a diffusion transformer that is used to generate images in a fraction of the time needed by current methods. The diffusion model obtains strong results, achieving high-quality synthetic images that are then used to augment existing smaller datasets to train computer vision classification models for real-time industrial applications. Finally, the last two chapters present a detailed analysis of the results achieved by both proposed models, along with a comprehensive explanation of their development. With these explanations, we aim to improve model interpretability, mitigating the black box nature often associated with deep learning methods
From tree rings to streamflow: reconstructing the hydroclimatic history of the Mississippi River Basin over the past millennia
No full textThe Mississippi River Basin (MRB), the largest watershed in the United States, plays a central role in shaping regional hydroclimate. This study reconstructs streamflow variability in the MRB from the year 1200 to 2005 by applying principal component regression to streamflow data from 51 gauges and the North American Drought Atlas (NADA), a tree-ring-based reconstruction of the summer self-calibrating Palmer Drought Severity Index. Verification statistics indicated strong predictive skill across the domain. These findings provide critical insight into long-term hydroclimatic variability in the MRB and underscore the value of paleoclimate records for improving water resource assessments
The relationship between internal coherence and student learning in high achieving middle schools: A Mississippi study
No full textIn order to determine ways in which Mississippi is improving in education, a quantitative research study was designed and conducted to examine ten high achieving middle schools in the state. The 10 schools had to obtain an A ranking or B ranking for the 2021-2022 school year and/or 2022 – 2023 school year from the MDE. The purpose of the study was to determine if relationships existed between the student achievement scores (Reading Proficiency, Reading Growth, Math Proficiency, and Math Growth) assigned by the state to each school and levels of Internal Coherence of the administrators and staff employed in the schools. The instrument used for the study was a quantitative survey, the Internal Coherence Assessment Protocol. The data were collected and analyzed for the 10 high-achieving middle schools (Reading Proficiency, Reading Growth, Math Proficiency, and Math Growth scores) and 310 administrators and staff using the Internal Coherence Assessment Protocol. The findings from the study revealed there were no statistically significant differences in the responses on the Internal Coherence Assessment Protocol between administrators and staff. The findings showed statistically significant relationships existed between the students’ achievement scores, mostly with Math Growth and/or Math Proficiency and the administrators and staffs’ levels of Internal Coherence. The researcher provides general recommendations for policymakers and practitioners as well as recommendations for future research
Application of PU learning in detection of DDoS attacks
No full textThe gcore radar 2024 says, the number of DDoS attacks has been increased by 46% in 12 months. Supervised and unsupervised techniques struggle detecting DDoS attacks due to the scarcity of labeled attack samples and an overwhelming presence of benign traffic. In contrast PU- Learning offers a promising solutions by dividing the data into positive and unlabeled data. This study explores the effectiveness of PU-learning in detecting DDoS attacks by comparing it with unsupervised methods. This method employs PU Bagging, Two Step method and auto-encoder based models to extract meaningful patters from network traffic data, utilizing CICDDoS2017 dataset for evaluation. Proposed approach aims to improve generalizability and robustness of DDoS detection system, practically into real world scenarios where labeled data is scare. Experimental results demonstrate PU-learning can achieve competitive detection accuracy while reducing reliance on labeled negative samples. Our findings suggest PU-learning enhances adaptability to evolving attack patters, can be integrated into existing security infrastructure for more efficient DDoS mitigatio
Assessing the kinematics and kinetics about the knee with an isokinetic dynamometer and force plates during field-based and lab-based trials.
No full textThe incidence rate in knee injuries has increased over the last 20 years, with women at a 2-8 times higher incidence rate compared to men. This is likely a result of lower neuromuscular control of the trunk, generating less hip muscle activation, and more reliance on the quadriceps, alongside reduced hip, knee, and dorsiflexion angles, paired with increased knee valgus angles, ground reaction forces (GRF), hip adduction, and knee rotation upon landing from jumps. The focus of this study is to determine if knee kinetics and kinematics during field- and lab-based trials are associated with knee injury predictors. Theoretically, if someone has low hamstrings- to-quadriceps ratio (HTQ), their GRF will be low, and their range of motion will be poor. This would influence their ability to execute athletic movements and potentially truncate their maximal force production during isometric and isokinetic tasks – implying a predisposition to a knee injury in the future
Design and evaluation of a 5G testbed: Analyzing security solutions, IQ sample management, and performance visualization
No full textThe evolution of 5G networks has introduced new opportunities for high-speed, low-latency wireless communication, supporting a wide range of applications from industrial automation to secure data transmission. However, as 5G networks become more complex, ensuring security and maintaining optimal performance present significant challenges. This thesis explores the development of a 5G testbed using Software-Defined Radios (SDRs) and open-source platforms to analyze signal behavior, security implementations, and performance. The testbed, built with the open source srsRAN software library and widely available SDR hardware, serves as a controlled environment for studying 5G communications security features and innovations. To evaluate transmission characteristics, in-phase/quadrature (IQ) samples and key performance indicators such as power distribution, spectral efficiency, and transmission behavior are analyzed using Keysight’s WaveJudge software and visualization features. Through extensive experimentation, this research provides insights into how different security implementations and transmission techniques influence network behavior. The findings contribute to a deeper understanding of secure communication in next-generation wireless networks and offer a flexible framework for testing future 5G security enhancements
Identification of novel activities of LysR-type Transcriptional regulators in virulence of Listeria monocytogenes
No full textListeria monocytogenes is a facultative intracellular pathogen responsible for listeriosis, a severe disease in humans and animals. The bacterium\u27s ability to survive and transition between environmental and host conditions is governed by a complex network of transcriptional regulators. This dissertation investigates the roles of LysR-type transcriptional regulators (LTTRs), including catabolite control protein C (CcpC) and glutamate synthase gene (GltC) and uncharacterized LTTRs in L. monocytogenes physiology, metabolic adaptation, virulence, and stress responses. Deletion of ccpC resulted in impaired phospholipase activity, reduced expression of the cholesterol-dependent cytolysin listeriolysin O (LLO), and diminished bacterial burden in murine liver and spleen. Transcriptomic analysis revealed that ccpC deletion led to the upregulation of DNA repair, stress response, and peptidoglycan biosynthesis genes while downregulating virulence and metabolic genes. Metabolomic profiling further demonstrated shifts in intracellular metabolites, indicating a significant role for ccpC in regulating nitrogen metabolism and bacterial competitiveness. In contrast, the deletion of gltC has a limited impact on phospholipase activity and cell-to-cell spread and intracellular replication. Furthermore, gltC deletion increased bacterial survival under oxidative stress and enhanced virulence in a murine model, suggesting that gltC may function as a negative regulator of virulence genes. Transcriptomic analysis of the gltC mutant revealed significant upregulation of genes involved in virulence, nitrogen metabolism, and oxidative stress response. Additionally, this study examined six uncharacterized LTTRs (LMOf2365_2178, LMOf2365_2322, LMOf2365_2266, LMOf2365_0315(315), LMOf2365_0518(518), and LMOf2365_0446 (446), demonstrating their involvement in phospholipase activity, LLO expression, and PrfA-mediated virulence regulation. Collectively, these findings highlight the crucial roles of LTTRs in modulating L. monocytogenes metabolism, virulence, and stress adaptation. Understanding these regulatory networks enhances our knowledge of L. monocytogenes pathophysiology and may inform the development of targeted interventions to mitigate its pathogenicity
Closing Chapter: A Stratum VIB Reconstruction of Areas I7, I8, J7, and J8 at Tell Halif
No full textThe 1992 and 1993 seasons at Tell Halif resulted in the excavation of Field IV, which has since spawned research on several of the houses found there. Units I7, I8, J7, and J8 have yet to be studied, reconstructed, and published. By analyzing the artifacts found primarily on the floors of the units relating to Stratum VIA and VIB (late 8th century B.C.E. destruction layer), I am determining the architecture that once stood there and its relation to the houses around it, such as the K8 house, through spatial analysis. By comparing the assemblages of units I7, I8, J7, and J8 to those in H7, H8, K7, and K8, I can reasonably reconstruct the building(s) that once stood there. Through my research, I have also assessed the dating of Strata VIA and VIB and their associated artifacts. This project aims to reconstruct the missing architecture of Stratum VIB in these units
Associations Between Parental Depression and Child Internalizing Behaviors: The Role of Gender
Get PDFThe present study is a cross-sectional examination of associations between mother and father depression as it relates to child internalizing symptoms and anxious and depressed symptomatology. The study builds on the literature that underscores the importance of parental mental health for child outcomes, particularly anxiety and depression symptoms, by examining the role of gender in the link between parental depression and child internalizing symptoms. This study included 256 children (M age = 9.53 years; SD = 29.97 months; 123 males) and their mothers, fathers, and teachers. The measures included the Symptom Checklist-90-Revised, the Child Behavior Checklist, and the Teacher Report Form. The results showed that maternal and paternal mental health indicators were associated with child internalizing symptoms, even after controlling for the role of SES, child age, and child sex. Mothers’ depression was more strongly correlated with child outcomes than fathers. Results indicated that child sex did not moderate the association between either mother or father depression on child depression symptoms. Findings can be used to inform prevention and intervention services and policy