Mason Journals (George Mason Univ.)
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How Blockchain Open Source Software (OSS) Projects Succeed
No full textBlockchain open-source software (OSS) projects are vital to the decentralized technology landscape, enabling innovation and collaboration in developing distributed ledger technologies. These projects exhibit diverse operational models, which may influence their popularity - a factor measured by the frequency of development activities conducted upon a project on software hosting platforms like GitHub. This study aims to identify the characteristics of a blockchain-utilizing OSS project's operational model that contribute to its success. A project's popularity/success was determined using an SQL script and GH archive, a tool that records the public GitHub timeline and archives it for further analysis. With this, the frequency of a project's development activities (forks, commits, etc.) was determined, which serves as a direct metric of active development and community engagement. Then, its operational model, including a governance mode (private, non-profit, DAO, etc.) and funding model (crowdfunding, VC funding, token sales, etc.) were determined through a web-based search. By conducting a comparative econometric analysis and determining the correlation between the characteristics of over 600 projects’ funding models/governance modes and development activities, this study establishes the operational characteristics of blockchain-utilizing OSS projects that contribute to their success, offering insights into the optimal operational methods that drive innovation and growth in the decentralized technology landscape.
This abstract is part of a collection in which the overarching large project under Dr. Jiasun Li was subdivided into discrete critical tasks that were carried out by multiple individuals or smaller teams. Abstracts in this collection read similarly given the shared project goals, but represent distinct tasks completed by the abstract authors towards finalizing the described analysis
Optimizing Online Interval Scheduling Systems with Data-Driven Analytics for Enhanced Resource Utilization
No full textCurrent scheduling mechanisms struggle to accommodate the diverse constraints of real-world time management, leading to inefficiencies for both clients and administrators. This sector of the project addresses the database integration and analytics required for a multi-machine online interval scheduling system. This online interval scheduling system works by prompting the users for a specific time window they want to make the reservation within rather than booking the exact time. The system uses algorithmic approaches to find the most suitable sector of time in a given window to allocate to the user. A key focus is the development of analytics that enable algorithms to assign reservations to the least popular timeslots within users' specified availability windows, thereby optimizing resource distribution and minimizing congestion. Additionally, efficient queries were developed to provide valuable insights to the reservable space owners, such as peak usage times, utilization rates, and patterns of user preferences. This data-driven approach supports more informed decision-making and enhances the overall efficiency and effectiveness of the reservation system. As a result, this project establishes a foundation for more advanced algorithms, suggesting future integration of factors such as expected travel time. Our goal for the future is to refine these algorithms continually, incorporating additional variables to achieve peak scheduling efficiency. By doing so, we aim to develop a more adaptable and effective scheduling system that meets the diverse needs of real-world users
Analyzing the Impact of Funding and Governance Models on GitHub Development Activities in OSS Projects
No full textOpen Source Software (OSS) projects, which are accessible and modifiable by the public, have experienced significant growth due to the advent of blockchain and other emerging technologies. These projects, typically hosted on platforms like GitHub, utilize various governance models and funding methods that can greatly influence their development activities. The study was split into two main parts. This first part of the study examines data from approximately 600 OSS projects using BigQuery. The data encompasses repository names, dates, actor IDs, actor logins, and 28 different events, including total activities and distinct commits, from 2013 to the present. The second part of the study consisted of taking a deeper dive into the backgrounds of these OSS projects. The funding model, project type, and governance mode were all used to investigate potential correlations with the success of the OSS. Although the data has not been fully realized, the study aims to identify correlation with a specific aspect of an OSS and its success.
This abstract is part of a collection in which the overarching large project under Dr. Jiasun Li was subdivided into discrete critical tasks that were carried out by multiple individuals or smaller teams. Abstracts in this collection read similarly given the shared project goals, but represent distinct tasks completed by the abstract authors towards finalizing the described analysis
The Impact of Funding and Governance on Open-Source Development Activity
No full textOpen-source software (OSS) projects are becoming more prominent, with new funding and governance models emerging. However, the affinity between these models and project development activity is poorly understood. This study looks into the potential relationship between funding/governance systems and GitHub development metrics like commit and watch counts in OSS projects. A dataset of 660 OSS projects was evaluated to provide data on funding strategies (e.g., public token sales, crowdfunding, product sales), governance structures (e.g., decentralized autonomous organizations (DAOs), centralized foundations, private firms), and GitHub activity metrics. Project-level metrics were obtained by querying GitHub Archive data in BigQuery using Structured Query Language (SQL). At the same time, project websites and GitHub repositories were examined to classify funding and governance models and identify project types (e.g., cryptocurrency wallet, decentralized application (DApp), Layer 2 network). By comparing GitHub metrics across different funding and governance categories, this study aims to identify patterns and trends in development activity. The findings will help to further the understanding of the elements that determine OSS project performance, such as the impact of financial resources from public token sales versus traditional product sales on developer activity. Furthermore, this study will demonstrate how governance structures, such as DAOs, which promote community-driven development, differ from centralized private firms in terms of development workflows and project longevity.
This abstract is part of a collection in which the overarching large project under Dr. Jiasun Li was subdivided into discrete critical tasks that were carried out by multiple individuals or smaller teams. Abstracts in this collection read similarly given the shared project goals, but represent distinct tasks completed by the abstract authors towards finalizing the described analysis
Satellite-based NO2-GDP Index Quantifies the Emission Intensity of Economic Development
No full textEconomic activities release a significant amount of air pollution. Reducing the emission intensity of economic activities has been a key objective of the green transition. Some pollutants, such as NO2, have short lifetimes and stay mostly in place, so they can be used as tracers for local economic activity. Previous studies have been able to establish a relationship between satellite NO2 measurements and economic indicators, such as GDP. In this study, we use satellite NO2 products to analyze the relationship between NO2 and GDP measured in real terms, as well as trends in NO2 cost per unit GDP increase. First, we review three different satellite NO2 products, finding substantial differences among them. After comparing with ground observations, we conclude that the OMI NO2 product aligns most closely with NO2 trends observed by EPA AQS ground monitoring stations. We then use satellite NO2 products from 2005-2020 to establish a novel NO2/GDP index on two levels: the contiguous United States and globally. Through correlational and comparative analysis, we classify countries based on their NO2 emissions per unit of GDP and document trends in their NO2/GDP index over time. While most regions have a downward trend, countries such as Libya and Yemen have a positive trend, indicating increased emission intensity per unit GDP. On a national scale, states in the Northwest U.S. often have elevated index values, reaching as high as 17.89. These metrics provide a useful input in discussions of environmental policies and assessments of their global impact
Investigation How Differing Funding/Governance Models May Influence GitHub Development Activities
No full textGitHub, a major software development site, supports an extensive number of projects. This study seeks to understand if there is a link between different funding/governance models and how much activity has occurred on a GitHub project. To achieve this objective, metrics were created such as the count of commits, watches, pull requests, and other relevant information spanning from 2013 to the present, which helped classify the activity on the GitHub project. Overall, six hundred and sixty projects were examined with the factors listed above. The data extraction process for these projects from GitHub Archive involved executing a sequence of SQL (structured query language) queries in Big Query. Afterwards, the website and GitHub of each project were examined to categorize the funding and business strategies of each initiative. For instance, it might refer to a cryptocurrency wallet, a decentralized application (Dapp), a Layer 2 network, or a token. While the full data collection and analysis of the data collected and has not been completed, further development of this study will establish whether there is a connection between differing project models and its GitHub activity.
This abstract is part of a collection in which the overarching large project under Dr. Jiasun Li was subdivided into discrete critical tasks that were carried out by multiple individuals or smaller teams. Abstracts in this collection read similarly given the shared project goals, but represent distinct tasks completed by the abstract authors towards finalizing the described analysis
Secretory mitophagy is a novel pro-survival and pro-growth mechanism for Neurofibromatosis Type 2 cancers
No full textNeurofibromatosis Type 2 (NF2) is a hereditary cancer caused by a chromosomal mutation which induces loss-of-function of the tumor suppressor protein Merlin. The physical effects of the mutation-induced tumors include hearing loss, tinnitus and a loss in balance.Currently, most therapies available are palliative and involve treatments to minimize pain and neurologic dysfunction, rather than destroying the cancer. There is a need to study new mechanisms of tumor growth. A hallmark of cancer is metabolic reprogramming. Under oxidative stress, mitochondria undergo changes (fission or fusion) to support the metabolic needs of the cancer. Autophagy, or self-eating, is a process to recycle damaged or unwanted proteins within a cell to the lysosome to survive. Mitophagy is the removal of damaged mitochondria regulated by mitochondrial fission molecules (FIS1 and PINK). Our team discovered an alternative pathway known as secretory mitophagy, which is the export of damaged mitochondria into extracellular vesicles. We observed Merlin, FIS1, and PINK1 within these vesicles. We hypothesize that secretory mitophagy is a cell survival and pro-growth mechanism used bycancer cells to withstand oxidative stress and export tumor suppressor molecules. Chemically induced oxidative stress and lysosomal blockade of meningioma cancer cells lead to increased cell survival and greater levels of secretory mitophagy. Merlin co-located viaimmunoprecipitation of PINK1+ EVs. A siRNA knock-down of FIS1 with oxidative stress reduced secretory mitophagy and cell survival. Overall, secretory mitophagy is an adaptive pathway used by cancer to endure greater levels of toxicity and export tumor suppressormolecules for unchecked growth
Enhancing Power Grid Resilience: A Novel Labeling System for Assessing Climate Vulnerabilities in US Substations
No full textPower grids are essential infrastructure networks composed of components including transformers, circuit breakers, andsubstations, which guarantee the reliable delivery of electricity throughout the world. Climate change poses significantrisks to these systems through factors, such as increased flood risk and extreme weather events. To address thevulnerability of power grids to these climate impacts, our study develops an innovative system for labeling thecomponents of power substations, enabling a detailed analysis of their exposure to external stressors. Our researchcatalogs over 1300 substations across the United States using this labeling system. In our ongoing research, we aim touse our comprehensive database and intersect it with tropical storm data under various climate scenarios, creating visualrepresentations of our hazard analysis. These visualizations will highlight the specific vulnerabilities within the power gridwhen exposed to different storm conditions, allowing for precise simulations of their performance during extremeweather events. Additionally, our ongoing research aims to provide deeper insights into the long-term degradation andeconomic costs associated with these impacts. Initial results demonstrate the potential of our approach to enhance thepredictive accuracy of climate impact models on power infrastructure. The findings for our study prove to be significant,offering critical information that can inform future strategies to bolster the resilience of the US power grid againstclimate-related challenges, ensuring the reliability and stability of electricity delivery for all across the globe
The Prevalence of the KRAS Mutation in Lung Cancer Based on the Smoking Status
No full textIn today's world, lung cancer is considered one of the leading causes of cancer-related deaths, and the KRAS mutation is one of the most prevalent mutations in lung cancer. The KRAS gene belongs to a class of genes known as oncogenes. When mutated, oncogenes can cause uncontrollable growths which make the normal cells cancerous. Many studies have investigated the prevalence of KRAS mutation in smokers. The goal of this study is to review the prevalence of KRAS mutation in smokers vs. non-smokers, their impact on survival rates, and different gene expression levels. We conducted a literature review on the most recent studies examining the prevalence of the KRAS mutation in relation to smoking status. Overall, the results show that the majority of KRAS mutations were found mainly in heavy smokers, and for nonsmokers, women had the mutation more frequently than males. Additionally, patients who were diagnosed with the KRAS mutation had lower survival rates than patients without it. In conclusion, the findings highlight the KRAS mutation's prevalence in lung cancer patients in correlation with smoking status, aiding in identifying high-risk individuals and informing targeted screening and prevention strategies.
 
The correlation of changing levels of Aerosol Optical Depth and annual tuberculosis incidences in Kenya
No full textAerosol Optical Depth, or AOD is a measurement of how much direct sunlight is blocked from reaching the ground, due to blockage by aerosols. Aerosol is a suspension of microscopic particles in gas. The AOD can be used as an indicator as to the pollution level, with higher AOD values indicating higher pollution levels and vice versa. Due to climate change, public health issues have arisen, one major disease that can be aggravated by air pollution is Tuberculosis. Gases such as Nitrogen Dioxide, Sulfur Dioxide, Carbon, Ozone, and many more can easily increase the severity of incidence and mortality of Tuberculosis. The goal of this project is to analyze and understand the relationship between AOD and the incidence of Tuberculosis in Kenya, a country in the East Africa, using Google Earth Engine based on the AOD data products from MODIS measurements onboard the Terra and Aqua satellites , and the World Bank annual incidence database for incidence of Tuberculosis for the period from 01-01-2001 to 12-31-2020. The analytical results show that there is an almost minute increase in AOD, however Tuberculosis cases number declines over the study period