Nonlinear Wave Transformation Using Modified Dispersive Shoaling Models

This study is to compare and validate two models for random wave transformation with experimental data. Both models are based on frequency domain KdV equation. First model is a modified version of KdV equation which was derived to provide shoaling and dispersion relation of each frequency mode. Second model is a dispersive nonlinear shoaling model including shallow water limits and dissipation terms. Results expected are as follows 1) Second model is expected to overestimate the results in higher frequencies but can predict satisfactorily close in the lower and intermediate frequency zones of the energy spectrums. 2) First model is expected to predict the transformation better than that of the second because of the fully dispersive nature. Energy spectrum plots from models are expected to match close to the experimental plots in the lower frequencies and the first model is expected to be much closer to the experimental data than that of the second model. The validation plots of both the models are expected to be as close as they can be in the Infra gravity and Swell regions of the spectrum; the second model is expected to do better in the Sea wave region of the spectrum

Generating fast and accurate compliance reports for various data rates

As the demands on the industry data rates have increased there is a need for interoperable interfaces to function flawlessly. Added to this complexity, the number of I/O data lines are also increasing making it more time consuming to design and test. This in general leads to creating of compliance standards to which interfaces must adhere. The goal of this theses is to aid the Signal Integrity Engineers with a better and fast way of rendering a full picture of the interface compliance parameters. Three different interfaces at various data rates were chosen. They are: 25Gbps Very Short Reach (VSR) based on Optical Internetworking Forum (OIF), Mobile Industry Processer Interface (MIPI) particularly for camera based on MIPI Alliance organization upto 1.5Gbps and for a passive Universal Serial Bus (USB) Type-C cable based on USB organization particularly for generation-I with data rate of 10Gbps. After a full understanding of each of the interfaces, a complete end-to-end reports for each of the interfaces were developed with an easy to use user interface. A standard one-to-one comparison is done with commercially available software tools for the above mentioned interfaces. The tools were developed in MATLAB and Python. Data was usually obtained by probing at interconnect, from either an oscilloscope or vector network analyzer --Abstract, page iii

Nonlinear Wave Transformation Using Modified Dispersive Shoaling Models

This study is to compare and validate two models for random wave transformation with experimental data. Both models are based on frequency domain KdV equation. First model is a modified version of KdV equation which was derived to provide shoaling and dispersion relation of each frequency mode. Second model is a dispersive nonlinear shoaling model including shallow water limits and dissipation terms. Results expected are as follows 1) Second model is expected to overestimate the results in higher frequencies but can predict satisfactorily close in the lower and intermediate frequency zones of the energy spectrums. 2) First model is expected to predict the transformation better than that of the second because of the fully dispersive nature. Energy spectrum plots from models are expected to match close to the experimental plots in the lower frequencies and the first model is expected to be much closer to the experimental data than that of the second model. The validation plots of both the models are expected to be as close as they can be in the Infra gravity and Swell regions of the spectrum; the second model is expected to do better in the Sea wave region of the spectrum

Ambulatory biopotential measurement

Biopotential signals measure the electrical activity of different parts of the body. Conventional bedside monitors only provide information about the body under restricted conditions. Observation and documentation of biopotential signal during daily activities and the relation to patient symptoms may be important factors for clinical decision-making. Ambulatory monitoring helps to monitor the biopotential signal of a patient in the natural environment. The effective ambulatory system can help a physician to diagnose the patient\u27s abnormality. In this project, a low cost and flexible ambulatory biopotential system, compared to the commercially available systems, was designed and tested. Concurrently a software program was developed for data acquisition and analysis with a Personal Data Assistant (PDA). The data was analyzed in real time using the Lab VIEW PDA. Pilot data was collected using the developed hardware during different normal activities to confirm the accuracy and reliability of the developed hardware and data was collected simultaneously from both a standard ECU machine and the developed system. It was shown that during some activities the system performed as designed, however under extreme conditions where there was more motion artifact, the number of missing R waves increased. The quality of raw ECU from the developed system was as good as the standard ECU during low motion artifact. It has been demonstrated that this newly developed biopotential system is less expensive, flexible, accurate, and more reliable than the commercially available systems and could be used in different clinical and research studies

Cardiac MRI in Infiltrative Disorders: A Concise Review

Cardiac MR imaging is an effective method for noninvasive imaging of the heart. The technology has been limited in the past because of imaging difficulties associated with cardiac motion. In recent years, however, cardiac MR imaging has broadened its spectrum of applications in cardiovascular disease with impressive advances in spatial and temporal resolution and increased imaging speeds. This review presents the current clinical applications of cardiac MR imaging for evaluation of cardiac disease in infiltrative disorders such as amyloidosis, hemochromatosis, and sarcoidosis

A Detailed Review on Plant Leaf Disease Detection and Classification Methodologies using Deep Learning Techniques

The rapid emergence and evolution of deep learning methodologies in the field of plant disease classification and detection has resulted in significant progress. Their application has revolutionized the way agriculture is done. This paper provides an overview of the advancements in utilizing deep learning models to address the crucial task of identifying and categorizing plant diseases. By harnessing the power of deep convolutional neural networks (CNNs) and transfer learning, researchers have achieved remarkable accuracy in disease classification, often surpassing traditional methods. This study also delves into the challenges that persist in this field, such as the scarcity of labeled data and potential biases in models. To address these concerns, the integration of visualization techniques is explored, allowing for better model interpretation and transparency. The collaborative efforts of agricultural experts and machine learning researchers are deemed crucial for overcoming these challenges and driving the future direction of research. Looking ahead, the interdisciplinary approach is anticipated to play a pivotal role in refining deep learning models for plant disease detection. A seamless collaboration between domain-specific professionals, machine learning experts, and agricultural practitioners is essential to foster innovation, enhance the reliability of models, and create a sustainable agricultural ecosystem. With the integration of cutting-edge architectures, emerging technologies like edge computing, and broader datasets, the field is poised to bring about transformative changes in agricultural practices, bolstering crop health and productivity

Nonlinear Wave Transformation Using Modified Dispersive Shoaling Models

This study is to compare and validate two models for random wave transformation with experimental data. Both models are based on frequency domain KdV equation. First model is a modified version of KdV equation which was derived to provide shoaling and dispersion relation of each frequency mode. Second model is a dispersive nonlinear shoaling model including shallow water limits and dissipation terms. Results expected are as follows 1) Second model is expected to overestimate the results in higher frequencies but can predict satisfactorily close in the lower and intermediate frequency zones of the energy spectrums. 2) First model is expected to predict the transformation better than that of the second because of the fully dispersive nature. Energy spectrum plots from models are expected to match close to the experimental plots in the lower frequencies and the first model is expected to be much closer to the experimental data than that of the second model. The validation plots of both the models are expected to be as close as they can be in the Infra gravity and Swell regions of the spectrum; the second model is expected to do better in the Sea wave region of the spectrum

Effects of chronic green tea flavonoid supplementation on features of metabolic syndrome, biomarkers of oxidative stress and inflammation and plasma catechin levels in subjects with metabolic syndrome

Green tea, rich in anti-oxidants, particularly epigallocatechin gallate (EGCG), is inversely associated with cardio vascular disease (CVD). Metabolic syndrome (MeS) is linked with increased oxidative stress & inflammation and subsequent risk for CVD. The main objectives of the study are to examine the effects of green tea beverage and green tea extract supplementation on features of MeS, biomarkers of oxidative stress and inflammation and plasma catechin levels. Obesity has parallel association with metabolic syndrome and Oklahoma is the sixth most obese state with 30.3 % prevalence of obesity. Hence, green tea supplementation study will address this problem. 28 subjects with MeS were randomly assigned to control, green tea beverage (4 cups/day, 440 mg EGCG) or green tea extract (2 capsules/day, 460 mg EGCG) groups for 2 months. Chronic green tea supplementation for 8 weeks showed significant weight loss in green tea beverage group (-2.3 kg, p<0.05) vs control. This study found no significant difference in markers of oxidative stress and inflammation. However, there is a decreasing trend in Ox-LDL (- 19.7%, p<0.1), nitric oxide (- 31.2 %, p<0.1) levels and increasing trend in HDL cholesterol in beverage group vs control after 8 weeks of supplementation. Green tea catechins were found in plasma samples collected after over-night fast. This indicates that catechins may present in the system for longer periods of time. Green tea supplementation with higher doses for longer periods is necessary to explore the findings of our study.Department of Nutritional Science

Effect of Saw Palmetto Supplements on Androgen-Sensitive LNCaP Human Prostate Cancer Cell Number and Syrian Hamster Flank Organ Growth

Citation: Opoku-Acheampong, A. B., Penugonda, K., & Lindshield, B. L. (2016). Effect of Saw Palmetto Supplements on Androgen-Sensitive LNCaP Human Prostate Cancer Cell Number and Syrian Hamster Flank Organ Growth. Evidence-Based Complementary and Alternative Medicine, 10. doi:10.1155/2016/8135135Saw palmetto supplements (SPS) are commonly consumed by men with prostate cancer. We investigated whether SPS fatty acids and phytosterols concentrations determine their growth-inhibitory action in androgen-sensitive LNCaP cells and hamster flank organs. High long-chain fatty acids-low phytosterols (HLLP) SPS >= 750 nM with testosterone significantly increased and >= 500 nM with dihydrotestosterone significantly decreased LNCaP cell number. High long-chain fatty acids-high phytosterols (HLHP) SPS >= 500 nM with dihydrotestosterone and high medium-chain fatty acids-low phytosterols (HMLP) SPS >= 750 nM or with androgens significantly decreased LNCaP cell number (n = 3; p < 0.05). Five-to six-week-old, castrated male Syrian hamsters were randomized to control (n = 4), HLLP, HLHP, and HMLP SPS (n = 6) groups. Testosterone or dihydrotestosterone was applied topically daily for 21 days to the right flank organ; the left flank organ was treated with ethanol and served as the control. Thirty minutes later, SPS or ethanol was applied to each flank organ in treatment and control groups, respectively. SPS treatments caused a notable but nonsignificant reduction in the difference between left and right flank organ growth in testosterone-treated SPS groups compared to the control. The same level of inhibition was not seen in dihydrotestosterone-treated SPS groups (p < 0.05). Results may suggest that SPS inhibit 5 alpha-reductase thereby preventing hamster flank organ growth

Plasma Pharmacokinetics and Tissue Disposition of Novel Dextran- Methylprednisolone Conjugates with Peptide Linkers in Rats

The plasma and tissue disposition of two novel dextran prodrugs of methylprednisolone (MP) containing one (DMP-1) or five (DMP-5) amino acids as linkers were studied in rats. Single 5-mg/kg doses (MP equivalent) of each prodrug or MP were administered intravenously, and blood and tissue samples were collected. Prodrug and drug concentrations were quantitated using HPLC, and noncompartmental pharmacokinetic parameters were estimated. Whereas conjugation of MP with dextran in both prodrugs substantially decreased the clearance of the drug by ∼200-fold, the accumulations of the drug in the liver, spleen, and kidneys were significantly increased by conjugation. However, the extent of accumulation of DMP-1 in these tissues was substantially greater than that for DMP-5. Substantial amounts of MP were regenerated from both prodrugs in the liver and spleen, with the rate of release from DMP-5 being twice as fast as that from DMP-1. However, the AUCs of MP regenerated from DMP-1 in the liver and spleen were substantially higher than those after DMP-5. In contrast, in the kidneys, the AUC of MP regenerated from DMP-5 was higher than that after DMP-1 administration. These data suggest that DMP-1 may be more suitable than DMP-5 for targeting immunosuppression to the liver and spleen