Mason Journals (George Mason Univ.)
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Distributions of Funding Models, Application Types, and Governance Models in Blockchain OSS Projects (2013 - 2024)
No full textBlockchain technology has only recently caught the attention of developers and tech entrepreneurs around the world; its own history dates back about 15 years, with the birth of Bitcoin in 2009. As the field evolved, modern Open-Source Software (OSS) projects within the blockchain field have diversified across various application types, funding strategies, and governance models. Despite this growth, comprehensive data on the distributions of these characteristics remains scarce due to the field's relative youth. This study addresses this gap by running Structured Query Language (SQL) scripts within Google Cloud's BigQuery API to retrieve GitHub development data between 2013 and 2024 from 660 OSS organizations. Next, using Excel, we generated distributions of the three attributes mentioned above and found that 62.5% of the OSS organizations rely on Public Token or Product/Service Sales for funding; 31.4% were Decentralized Apps, leading the other application types by a margin of over 15%; and 45.2% were Private Companies. Additionally, 22.9% of these projects were not centrally organized, remaining in the early, pre-seed stage, thus reflecting the developing nature of the field. These findings reveal prevalent characteristics and trends of OSS projects within the blockchain field, which can guide future investment and development strategies.
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
Investigating how various funding/governance models of OSS projects may impact Github development activities
No full textGithub is a central repository where developers can share code with others. This allows for the development of OSS projects that are used to develop various blockchain models either for crypto or similar usage like NFTs. The impact that various funding and governance models of OSS projects have on Github development activities like commit ratios is currently an area of active research. As a part of a larger effort to understand more about these impacts, data collection and analysis of 20 OSS projects was conducted. Tools such as Google Big Query(GBQ) were used to process over 20 TB of data per project. Much of the data was split and merged as necessary using a python script. The compiled events and attributions of the 20 OSS projects are part of a larger effort of over 600 projects that are ready for further analysis. This will determine whether there is a correlation between the project model and github activities.
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
Investigating How Funding and Governance Models Impact GitHub Development Activities in OSS Projects
No full textOpen Source Softwares (OSS) are softwares in which people can openly access, modify online, and distribute its source code to others for any purpose. Many Blockchain, Cryptocurrency, and Decentralized Finance (DeFi) are OSS Projects, allowing visitors to openly access their GitHub repositories. In the study, our team first analyzed over 500+ different OSS projects, using BigQuery to pull GitHub data for the repository name, dates, actor IDs, actor logins, and 28 different events. Examples of the 28 events include the total number of activities and distinct commits; the data was taken from the years 2013 to present. The second part of our study involved further research on the 500+ projects we analyzed in the first part through visiting its GitHubs, personal websites, and CoinMarketCap page. The three main components our team researched were project type (eg. DApp, token), the funding model (eg. fundraising, token exchange), and the governance mode (eg. DAO, private company). Specifically, the goal was to find trends between different funding and governance models and their respective GitHub Development Activities such as watch/commit ratios. For example, OSS projects which mainly rely on fundraising may have greater watch/commit ratios than projects which rely on public token sales.
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 You Only Look Once Version 5 (YOLOv5) for Object Detection in Thermal Images
No full textThe field of computer vision, has seen exponential growth over the past few years. Within computer vision,object detection is a popular field due to its vast application to real world problems. You Only Look Once(YOLO) is an object detection model trained on the Common Objects in Context (COCO) dataset. YOLOmodels are widely recognized for their performance in object detection with RGB images; however, theiraccuracy sees a substantial falloff when dealing with thermal fused images, due to their distinct characteristics.While prior studies have addressed this limitation, none provide open-source code. Our research aims tofine-tune YOLOv5 for thermal fused images and publish our modifications. YOLOv5 comes pretrained withanchors, a backbone, and a head, all optimized for RGB image utilization. Our study tests numerousmodifications to these components, to develop a model which excels at detecting the distinct features withinthermal images. By sharing our findings and code, we hope to advance the application of YOLOv5 in thermalimaging and facilitate future research into this area
Analyzing the vulnerability of US Power Grids to Climate Change related Stressors
No full textThe importance of the power grid under the energy sector umbrella is difficult to overstate, as it enables the function of nearly all critical infrastructure systems. The interconnected assets within electrical substations enable the function of our society and economy. With such a vast system of interconnected nodes, threats to the stability of this network come in many forms, from natural hazards to malicious threats. To begin quantifying these impacts, our initial study focuses on developing a novel software-based asset survey system utilizing satellite and street view imagery for classifying and geolocating component-level assets within extra high-voltage substations. The ability to accurately differentiate components and spatially plot transmission and distribution assets allows for a more detailed analysis of vulnerabilities and external stressors beyond what is currently available in open-source repositories. To this end, using this surveying system, our research has categorized components of over 1,300 substations in the US alone. Notably, our ability to create classifications of this resolution entirely from publicly accessible data encourages the expansion and application of our methodology beyond a national region of interest. Through refining our research to improve component-level granularity, the ongoing study aims to provide deeper insight into the socioeconomic impacts incurred when power grids suffer degradation. Foundational research already supports precise simulation of performance under scenarios such as extreme weather conditions and prolonged heat waves, informing future strategies aimed at bolstering the resilience of the US power grid against climate-related challenges, ultimately safeguarding the reliability of electrical distribution for all
Presence of bacterial proteins in Human Breast Milk detected through Western Blot Techniques
No full textBreastmilk has always contained a diverse microbiome known as the human milk microbiota (HMM), containing many diverse populations such as bacteria, fungi, parasites, etc. Western blotting is a technique commonly implemented to assist in the detection of antigens or proteins in a sample of interest. The antibodies NTHi 3B9, JLA20, and 15F12F8 are specific for antigens commonly found in bacterial strains including Escherichia coli, Streptococcus pyogenes and staph bacteria. However, the presence of these bacterial proteins in breast milk and evidence behind it are understudied. In order to validate the presence of the specific bacterial proteins in our breast milk samples, we deploy the use of antibodies (NTHi 3B9, JLA20, and 15F12F8) specific to them using the western blot technique. We can report that our bacterial proteins were not detected in control samples using Western Blotting. Consequently, these results show that our antibodies could not be validated for use in breastmilk samples. It is possible that the bacterial proteins were not detected because of the protein concentration of control samples that was added. Future studies should focus on optimizing the protein concentration of samples utilized and overall better precision
Mathematical modeling, analysis and simulation of the spread of smoking in the United States using Optimal Control
No full textIn this work, we consider a mathematical study for assessing the dynamics of smoking and its public health impact in a community. Specifically, a compartmental model for smoking as an infectious disease is considered using a coupled system of ordinary differential equations. The model describes the spread of smoking in the population through six compartments corresponding to different subpopulations. We introduce into this system of coupled equations, the use of public education campaigns aimed at elucidating the health impacts of smoking. Specifically, we introduce a variable corresponding to education as a control which causes a change in behavior resulting in two susceptible classes. We perform stability analysis, derive the basic reproduction number and use optimal control theory to characterize education as a control in order to achieve the goal of minimizing the exposed and infected populations, while maximizing the susceptible populations and minimizing the cost of education. Our numerical results show that education can be used as a regulatory mechanism to mitigate the spread of smoking. We hope that the model created can help provide insights to achieve maximum reduction in smoking prevalence while optimizing cost-effectiveness that will then allow policymakers to determine the optimal allocation of financial resources for such campaigns
Influence of El Niño Southern Oscillation on Indian Summer Monsoon Intraseasonal Circulation and Cluster Dynamics
No full textThe Indian Summer Monsoon (ISM) is a large-scale seasonal event responsible for providing the majority ofannual rainfall to India. However, when the El Niño Southern Oscillation (ENSO), categorized by anomalous sea surfacetemperatures (SST) in the central and eastern Pacific Ocean, is in a warm year (higher SST), the seasonal mean ISMrainfall generally decreases, although the robustness of this relationship has been questioned. Our study focuses on theextent to which the preferred intraseasonal active-break cycle of the ISM defined by five circulation regimes (obtained bycluster analysis in Straus 2021), is independent of the seasonal mean SST of the Pacific Ocean, a current debate amongresearchers. Using the Niño 3.4 Index (average SST over the central-eastern Pacific), we define warm years as those forwhich the summer average anomaly of Nino3.4 exceeds 0.7 degrees K. Cold years have the seasonal mean indexanomaly less than -0.7 degrees K. (All other years are considered neutral.) Following Straus (2021), we compositeprecipitable water (PW) and diabatic heating (Q) anomalies during each of the five circulation regimes to show theirevolution during the active-break cycle. Going beyond this, we composite PW and Q during each regime for warm, coldand neutral ENSO years separately. Differences between the warm and cold ENSO regime composites for each phase ofthe active-break cycle are nearly independent of the phase of the cycle, suggesting (but not proving) that the seasonalmean ENSO effect is not related to the cycle. We pursue this line of enquiry with further research to determine how theprincipal components of u and v-winds at 850 mb (the variables used to define the regimes) are affected by ENSO
Synthesis and crystal structure studies of NdCrTiO5
No full textNdCrTiO5 is a magnetic oxide which exhibits a wide variety of properties, including magnetoelectric coupling and multiferroic behavior, which have potential use in magnetoresistive random-access memory and other energy-based applications. Below its magnetic ordering temperature, the orthorhombic crystal structure changes from non-polar space group Pbam (No. 55) to polar Pba21 (No. 32). The goal of this work is to first synthesize the parent compound NdCrTiO5 and then attempt to introduce other 4d/5d magnetic ions in the crystal structure to achieve polar crystal structure and magnetic ordering at a higher temperature. NdCrTiO5 was synthesized by grinding stoichiometric quantities of Nd2O3, Cr2O3, and TiO2, pressing them into a pellet, and heating at a high temperature. Powder X-ray diffraction pattern indicated that the prepared sample contains the main phase NdCrTiO5 (> 90%). Energy dispersive X-ray confirmed the chemical composition
Analyzing Firework Emissions Across Various Locations and Settings in the United States
No full textIndependence Day celebrations in the United States are often accompanied by large, bright firework performances. These firework celebrations are accompanied by multiple negative effects, including harm to human and wildlife health, increased air pollutant emissions, and contamination of soil and groundwater. Due to the nature of fireworks as combustion reactions, they release particulate matter (PM2.5 & PM10), carbon monoxide (CO), nitrogen oxides (NOx), and others, all of which have respiratory and cardiovascular impacts. Datasets from the EPA’s Air Quality Service for hourly readings of CO, NO, and PM2.5/10 for the month of July in 2021-2023 were processed using RStudio. Hourly concentrations from July 4th, 18 LST to July 5th, 17 LST were compared with hourly averages from July 1st-7th and July 1st-31st, excluding the Independence Day timeframe. Differences in concentrations across urban, suburban, and rural settings were also examined to understand relationships between emissions from fireworks and population density. Preliminary results indicate that all pollutant levels are generally heightened from 18LST to 7LST, and start to return to average levels after that. Differences are generally higher in states with large cities, like New York and District of Columbia. The main goal of the study was to examine locational and population impacts on firework emissions to potentially create a better understanding of an emission source that may not be accurately represented in current models and allow efforts to reduce emissions from fireworks to be targeted in areas with the most impact to more rapidly see results