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    15648 research outputs found

    Designing For The Modern Digital Landscape: A Full-Stack Web Development Project

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    Given the widespread usage of web applications in today’s digital landscape, web design has considerable economic implications. The paper seeks to address various aspects of web design, including information architecture, user interface (UI), user experience (UX), and human-computer interaction (HCI). In this research project, we build a full-stack web development project, called MycroExpense, from scratch to investigate, implement, and illustrate many facets of web design. The web application was created using Django and Python for the server-side; HTML, CSS, Jquery and Bootstrap for the client-side, and SQLite3 for the database. This web application allows users to manage their expenses, subscriptions, and budgets, and displays comprehensive statistics and summaries for their spending. Through this implementation, we cover many essential topics like fundamental design principles, human dimensions (physiology, gendered, and cultural), aesthetics, and user credibility to create a product that ensures a seamless user experience

    The Creation of Black Paradise: Exploring Wealth Accumulation, Racial Politics, and Resilience of Black Neighborhoods In Detroit\u27s East Side Through Archaeological Reconstruction

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    The neighborhoods of Black Bottom and Paradise Valley in Detroit, Michigan, were a cultural, economic, and sociopolitical mecca for the African-American community from the 1920’s to the 1950’s. In a time where racism and segregation limited the acquisition and accumulation of wealth for Black families, this neighborhood in a heavily segregated Detroit served as the first African-American middle class neighborhood in the United States. However, little has been reconstructed of its history since racially influenced housing standards saw it torn down in the 1940’s and 1950’s to make way for a highway into the city and slum clearance, an act for which residents were compensated little to none. Due to both the immediate destruction of the neighborhood and the financial disparity that followed, this act would heavily influence racial tensions that still influence the cultural makeup of Detroit today. Through a stratigraphic mapping of the neighborhood, analysis of cultural artifacts produced and distributed during this time, oral testimonies, and the examination of the policies implemented and their ties to racism in housing policy at the time, we can determine both the invaluable cultural atmosphere that these neighborhoods had, and to what extent the removal of this vital community in Detroit led to contemporary issues in the city today

    Investigation of Splicing Changes in dNab2 Knockdown Drosophila Neurons

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    Putin\u27s Corrective Project : An Examination of State Repression Against Russian Nongovernmental Organizations

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    Since the early 2000s, restrictions against nongovernmental organizations in Russia have drastically increased with some of the oldest organizations in the country being liquidated. Why, in Putin-era Russia, has the Russian state gone to such great lengths to repress NGOs? This study utilizes case study comparisons of NGOs, both independent and state-run, to situate these efforts for repression in the broader context of the Kremlin’s efforts for political control and centralization—specifically as it relates to bolstering nationalistic sentiments, controlling information, and co-opting political engagement. Examining published materials, activities, and state response, this study finds support for the idea that the Russian government uses repression as a means of not only eliminating political threats, but also as a means of controlling historical narratives and centralizing the state in information sharing and avenues of political activity

    Brownfield Meets the Bees\u27 Needs: The William J. Robertson Nature Preserve Provides a Safe Haven for Solitary Native Bees

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    In the last 20 years, public perception of native bees has grown from a bare understanding to recognizing their important role in many ecosystem functions. Brownfield environments are understudied in how they support populations of solitary native bees. One of the key purposes of this research project was to help us understand the role of brownfields as vital safe spaces for these populations to recover. The project begins by providing a history of the scientific research on native bee ecology, social learning, and communicating needs for environmental change through signage. Then, the project breaks into two studies that address the biological and societal impacts of the William J. Robertson Nature Preserve on solitary native bees in Rittman, Ohio. To understand how brownfields contribute to bee conservation, an experiment was run five times from July to October in 2022 to assess the local quality of habitat features on the abundance of solitary native bees. Transects were conducted to validify the designation of high or low flowering, and high or low tree coverage at the sites where pan trapping occurred for specimen collection. Results concluded that solitary and native bees were found most abundant in areas that were high in both floral resources and tree coverage. Five families of bees were cataloged representing 11 different genera of solitary and native bees that have residences within William J. Robertson Nature Preserve. The second study, aimed to create a workshop for members of the community of Rittman to design signage that addressed topics of solitary native bee conservation. Research concerning social learning was reviewed and related to humanities arts based participatory research. The model for a workshop was proposed to increase the public\u27s perception of native bees and suggested that art can be utilized as a tool to enhance lessons on environmental conservation

    The Effects of Interparental Conflict on an Individual’s Expectations Towards Their Romantic Relationships: Attitudes Towards Romantic Relationships

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    This study examined the extent to which expectations towards romantic relationships are affected by interparental conflict (IPC). This study looked at personality and relationship factors, such as attachment anxiety, attachment avoidance, and commitment to determine if they mediated the relationship between IPC and expectations. Participants (n = 102) completed an online survey with measures of these constructs. The results indicate that higher levels of anxiety and avoidance predict lower relationship expectations while higher levels of commitment predict higher relationship expectations. In a mediation analysis, IPC was found to both be a direct predictor of expectations and was also found to be an indirect predictor of expectations when mediated through anxiety. This indicates that higher levels of IPC directly leads to lowered expectations and that higher levels of IPC leads to higher levels of anxiety, which then leads to lowered expectations

    Instating Natural Reward-Induced Conditioned Place Preference in C57BL/6J Mice

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    Reward is a vastly complex process, integrating diverse brain regions and neurotransmitters to modulate higher-order vertebrate behavior. Often studied utilizing unnatural drugs of abuse (cocaine, methamphetamines, alcohol), reward research is relevant to substance abuse disorders and conditions involving dysfunctional reward circuitry (depressive disorders, schizophrenia). The present study, however, aimed to approach reward with a naturally rewarding substance: chocolate. Using five milk chocolate chips as a natural reward, I sought to evaluate the ability of mice to develop conditioned place preference to a context paired with this reward. Subjecting male and female C57BL/6J male mice (n = 16) to a ten-day conditioned place preference paradigm, it was hypothesized that the experimental mice would develop preference for the CS+ conditioning environment. Analyzing the percent preference data, I found no signicant conditioning in any mice, however, I observed sex dierences within the experimental mice. The experimental male mice exhibited increased preference for the CS+ conditioning environment in comparison to the experimental females. Furthermore, the male mice, overall, consumed more of the natural reward than the females during conditioning. My data suggests that conditioning was more successful in the male mice, indicating that sex dierences may underlie natural reward-induced CPP. In follow up research, I would like to further elucidate the identity of active neurons through fluorescent microscopy techniques and assess the role of various reward doses in natural reward

    Forecasting PM2.5 Concentration in Different Cities in Mongolia Using Neural Network Autoregression (NNAR) Model and Seasonal Autoregressive Integrated Moving Average (SARIMA) Model

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    This thesis presents a comparative study of the performances of different machine learning modelsfor forecasting the PM2.5 concentration in several cities in Mongolia. The study aims to developtwo types of forecasting models for PM2.5 concentration, which is a significant environmental andpublic health issue in Mongolia. The first model is a Neural Network model which is used inareas without air quality monitor and past air quality data available to be used for PM2.5 forecastmodel. The second type of model includes the Neural Network Autoregression (NNAR), SeasonalAutoregressive Integrated Moving Average (SARIMA), and Seasonal Auto-Regressive IntegratedMoving Average with Exogenous factors (SARIMAX) models. These models are for cities withhistoric PM2.5 concentration data available to forecast PM2.5.The dataset used for this study includes daily PM2.5 concentration data as well as othermeteorological data collected from air quality monitors and weather stations in Ulaanbaatar, Dornod,Gobi-Altai, Khovd, Selenge, Tuv, Uvs, Uvurkhangai, and Zavkhan cities from September 2021 toMarch 2023. The study first pre-processes the data, including data cleaning, and then implementsthese models on the processed data. The performances of these models are evaluated using variousstatistical metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Thecomparison of different model results shows that the NNAR model performed the best when usingdaily PM2.5 concentration data in Ulaanbaatar, with MAE = 16.55 μg m−3 and RMSE = 23.01 μg m−3.This model also explained 55% of the variability (R = 0.55) in the PM2.5 concentration

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