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Tracking selection of gadolinium-based contrast agent targets by aptamers through SELEX
No full textTo develop a more efficient and safe MRI contrast agent out of existing gadolinium-based contrast agents (GBCAs), an aptamer-based approach was developed. Existing GBCAs consist of chelated Gd(III) ions. Greater efficiency of contrast agents has been observed by increasing the size and polarity of the molecule. However, available chelating agents do not have a feasible way of achieving these goals. For this reason, an aptamer (a single-stranded DNA of 72 nucleotides) based approach was proposed, providing both a larger structure and increased polarity with the ultimate goal of lowering dosages of contrast agents. An aptamer library of sequences of approximately 21,000 g molecular weight were selected for binding to a Gd-DOTA complex and processed using SELEX (Systematic Evolution of Ligands by Exponential Enrichment). 15 total iterations of SELEX were completed, qualitatively assessing binding affinity by gel electrophoresis, and quantitatively verifying concentration of isolated aptamers by UV-Vis spectroscopy, tracking the overall progress towards a high affinity product that can select for low concentrations of Gd-DOTA complex. After 15 iterations, the SELEX cycle yielded concentrations of aptamer at 40.6 ng/µL. Gel electrophoresis qualitative assessment showed an apparent reduction in the amount of aptamers that bind to the target
A Kernel-type regression estimator for MNAR response variables with applications to classification and their convergence properties in Lp norms
Get PDFWe deal with the problem of nonparametric estimation of a regression function when the response variable may be missing according to a missing not at random (MNAR) setup. To evaluate the theoretical performance of our estimators, we study their strong convergence properties in Lp norms, and evaluate their rates of convergence. In doing so, we derive exponential bounds on their performance. We also study applications of our results to the problem of statistical classification in semi-supervised learning. We finish with simulation studies that exhibit the finite-sample performance of our proposed estimator, and compare its error rates with the na´ıve complete case setup, as well as the case in which data is not missing
Fake News Detection Using LSTM Method
Get PDFThe spread of misinformation and fake news has become a major challenge in today's society. Detecting and countering such news is crucial to preserve the integrity and reliability of the details. In recent years, deep learning techniques have been applied to the problem of fake news detection, with promising results. This report focuses on using the Long Short-Term Memory (LSTM) algorithm to detect fake news. We collected a dataset of news articles from different sources and manually labeled them as either fake or real. We preprocessed cleaning and tokenizing the data and the text, and then used an LSTM neural network to model the sequence of words in the news articles. The model was trained on a subset of the data and then evaluated on a held-out test set. We experimented with different hyperparameters and regularization techniques to optimize the performance of the model
Comparative Architecture of Cryptographic Algorithms using Verilog
Get PDFApplications of cryptography range over secure communications and storage. The cryptographic algorithms have found their place in the implementation of Advanced Encryption Standard, which has emerged as a widely adopted standard for its robustness and efficiency. This report begins with a comparative study regarding the architectural issues of the AES cryptographic algorithm implementation using Verilog, which is a hardware description language. This paper only focuses on the simulation of two different modes of encryption under AES, namely Cipher Block Chaining mode and Electronic Codebook mode. While simulating, the study probes into minute details of architecture for each cryptographic mode and brings out relative strengths, weaknesses, and performance characteristics. The Verilog-based simulations establish how each mode would carry out its operations at the hardware level and hence help study efficiencies and complexities. This comparative analysis is supposed to enable judgment on the trade-offs CBC and ECB modes represent in considerations like speed, resource utilization, and security. This work shall serve as a foundation for the further enhancement and optimization of AES implementations, enabling development in secure data transit and storage systems. Drawing on the conclusions of side arguments, this report lays the foundation for an investigation into the architectural intricacies of cryptographic algorithms and serves as a building block toward taking on further research in hardware-based cryptography
Threshold Voltage for SiC MESFET with a Recoil-implanted Channel Profile.
Get PDFThe demand for high-power and high-frequency devices has driven research into Silicon Carbide (SiC) Metal-Semiconductor Field Effect Transistors (MESFETs) due to their superior electrical properties. This study focuses on the threshold voltage characteristics of SiC MESFETs with a recoil-implanted channel profile, leveraging SiC's wide bandgap, high thermal conductivity, and strong breakdown voltage. These properties make SiC ideal for efficient power management and high-temperature applications. The analytical model developed evaluates the impact of recoil implantation on threshold voltage. By controlling the doping concentration through recoil implantation, a uniform doping profile is achieved, minimizing crystal defects and improving channel control and efficiency. Key results from MATLAB simulations show that threshold voltage decreases with increasing ion implant dose and moderated by substrate concentration. This tunability is required for optimizing SiC MESFET performance for specific applications. Additionally, I-V characteristics and transconductance studies of 4H-SiC MESFETs demonstrate effective operational control through variations in gate-to-source and drain-to-source voltages, making them acceptable for microwave and RF amplifier circuits. This research highlights SiC MESFETs as promising candidates for high-performance power devices
Tomorrow We Might Be Dead: Writing With, From, and About Buffy the Vampire Slayer
No full text[ABSTRACT ONLY; NO FULL TEXT] This multidisciplinary text explores the intersections of loving, critiquing, and responding to a piece of media through the forms of poetry, race criticism, and memoir. Buffy the Vampire Slayer, an American television show that first aired in 1997, has impacted my life in many ways and has become a touchstone for the way that I look at and think about my own writing, and this text is the physical manifestation of that relationship. Tomorrow We Might Be Dead consists of erasure poetry derived from every Buffy episode script, footnotes exploring the handling of race throughout the show, and essays discussing topics ranging from the queering of the horror genre, chosen family, prison abolition, the cathartic power of hate, and more. Ultimately, this text is an autoethnographic love/hate/love letter to a show, to myself, and to the world around me
Obesity in Latinx children in Southern Sonoma County
No full text[ABSTRACT ONLY; NO FULL TEXT] Blue Zones Project Petaluma is a health and longevity expert, located in Petaluma, California, whose mission is to empower everyone, everywhere to live better, longer. They offer health education and interventions in the areas of healthy eating and lifestyle management, to empower community members to develop healthy behaviors. In light of these programs, the most appropriate program planning model is the Transtheoretical Model. Childhood obesity is at epidemic proportions in the United States, with 20% of children up to age 17, obese and 33%, overweight or obese, and Latinx children are the most affected in Southern Sonoma County. Studies show that Latinx children tend to have less healthy diets, with cultural foods that are carbohydrate-dense and tend to be less active. Guided by the construct of consciousness raising, a goal was established to reduce the incidence of obesity in Latinx children, and four objectives were developed to ensure that this goal is achieved. This goal and these objectives are foundational, in guiding the creative strategy for increasing the nutrition education of Latinx children. Suitable evaluation methods to determine how effective the innovative strategy is are discussed. A pilot study of this strategy will be implemented for two years, and if it shows a favorable outcome, it can be integrated as a part of Blue Zones Project Petaluma's nutrition education programs
A Strategy for Growth at The Center for Social and Technology Entrepreneurship (C-STE)
No full textWe produced this report for The Center for Social and Technological Entrepreneurship (C-STE), an organization under the David Nazarian College of Business and Economics. C-STE offers students a unique curriculum with a specialization of technology and social entrepreneurship which is a newly emerging and quickly growing area of entrepreneurship. C-STE's reason for seeking consultation was to receive recommendations on a growth plan which included an increase in student engagement into their entrepreneurship programs. To help with our project, C-STE provided internal information and documentation that included financial information, and current marketing methods. Secondary research included using CSUN and C-STE websites, C-STE's business charter and overview, websites from other CSU's and UC's, U.S. Small Business Administration, and U.S. Economic Development Administration. Primary research included surveys and interviews from students, alumni, existing donors, and other universities. Our research indicated that C-STE is susceptible to macro-external factors such as political, economical, social, technological, environmental, and legal that have an impact on its operations. For macro-external factors, we utilized the PESTEL analysis to understand the threats and recommended actions to avoid or minimize their impact. We utilized the SWOT analysis to understand strengths and opportunities that can be leveraged to contribute to C-STE's growth. The 3C analysis was utilized to analyze the three key elements, Customers, Company and Competition to identify opportunities that will leverage C-STE's strengths, address student needs, circumvent competitors and ultimately leading to an effective marketing strategy. For the internal and external analysis, I was responsible for creating the outline and incorporating the analysis tools, PESTLE, SWOT and 3C, and adding context to the PESTLE, 3Cs, threats and opportunities portion of the SWOT. For the Research Instruments, I was responsible for formulating the questions for universities and other institutions to benchmark their entrepreneurship programs which helped our team make recommendations on how C-STE can improve their respective programs. I also contributed to formulating questions for existing donors and potential donors, and coming up with the idea of conducting observations by attending C-STE events to get a first-hand understanding of the student participation and experiential learning experience. For the recommendations, I was responsible for including the Marketing Funnel method which takes potential participants through the journey of being unaware of C-STE to becoming participants. I recommended and demonstrated how C-STE can use this model to engage potential participants in their future marketing initiatives. Additionally, I was responsible for recommending that C-STE enhance their marketing materials to help solidify their brand and increase engagement. Furthermore, I recommended benchmarking the best practices of other universities' entrepreneurship programs to identify gaps and opportunities for C-STE to improve. This recommendation included C-STE making a business practice of collaborating with other universities to help improve their processes. Finally, I was responsible for recommending KGIs to measure the strategic goals that are critical to C-STE's growth, and the respective KPIs to track the processes that are linked to the KGIs. Recommending these metrics is also a way for C-STE to unify the team in achieving similar goals
Light Rail in Los Angeles 1980-2020
No full text[ABSTRACT ONLY; NO FULL TEXT] Los Angeles has become a city known to be dependent on the automobile for travel along with a vast freeway infrastructure system built to take the automobile and its occupants to places in a fast and timely manner. As congestion and traffic heavily arose post World War II, the city has struggled to adopt a meaningful and strategic way to combat the growing number of automobiles on the road. The 1980s put the city aboard a rail revival mentality to address pollution and to get residents to adhere a new way to travel in the basin
Combating fare evasion: Innovative strategies and technologies for bus systems
No full textFare evasion is a persistent challenge facing public transportation systems, particularly in bus networks, where open boarding and limited enforcement often make fare compliance difficult to monitor and maintain. This paper examines fare evasion through an interdisciplinary lens, combining insights from economic, behavioral, and equity perspectives to analyze current strategies and propose innovative approaches. The study investigates fare evasion patterns and their socioeconomic implications, with an emphasis on how enforcement disproportionately impacts low-income and minority populations. Using a qualitative analysis of secondary data, the research systematically reviews academic literature and industry reports to identify key drivers of fare evasion and evaluate strategies aimed at reducing non-compliance. Key findings reveal that traditional enforcement methods, such as random fare inspections and monetary fines, often fail to address the root causes of fare evasion and may exacerbate social inequities. Technological solutions, including mobile payment platforms and predictive analytics, show promise for enhancing fare compliance by making payment systems more accessible and targeting enforcement resources more effectively. However, these innovations must be implemented with attention to equity, ensuring that all passengers have equal access to fare payment options. This paper proposes a conceptual framework that integrates Rational Choice Theory, the Theory of Planned Behavior, and Transportation Equity Theory to guide the development of policies that balance enforcement efficiency with social fairness. The recommendations put forth aim to help transit agencies deploy data-driven and equitable fare evasion strategies that promote both financial sustainability and inclusivity in urban transit systems