Physical Sciences and Mathematics Commons^™

Pappus Of Alexandria, Book Viii Of The Mathematical Collection, Pappus Of Alexandria, John B. Little

Holy Cross Bookshelf

John B. Little is the translator.

This is a Greek-to-English translation of one section or chapter of a larger ancient Greek work called the Mathematical Collectionby Pappus of Alexandria (ca. 290 - 350 CE). Specifically, this is “Book VIII”' of that work. To date and to the translator’s knowledge, no complete English translation of Book VIII has been published.

Pappus was very influential as a bridge between the knowledge that had been preserved from ancient mathematics and European mathematicians in the Renaissance. This specific part of Pappus' work deals with applications of geometry to questions in mechanics.

The format …

Experimental Data Supporting Co2 Enhanced Oil Recovery And Storage Potential In The Bakken Petroleum System (Bps), University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet on CO₂ enhanced oil recovery (EOR) in the Bakken petroleum system. Highlights experimental data concerning CO₂’s role in oil recovery in the region.

Upgraded Carbon Ores To Products, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet on the Energy & Environmental Research Center (EERC) project to develop domestic battery materials from upgraded carbon ores. Includes information on upgraded carbon ores to products (UCOP) technology and a timeline for development.

Geneseo Solar Eclipse Website, Anne Pellerin, Aaron Steinhauer, Sherry Larson-Rhodes, Leah Root

Myth and Science, 2023-24

The Geneseo Solar Eclipse website is a collaboration by Faculty from the SUNY Geneseo Physics & Astronomy Department and the Staff of Fraser Hall Library, highlighting Geneseo campus and local eclipse-related events, and demonstrating the science behind solar eclipses. Learn about the differences between partial and total solar eclipses, how eclipses are used to find new worlds, and find resources and Geneseo campus events celebrating the eclipses of Oct 14, 2023 and April 8, 2024!

This archived copy of eclipse.geneseo.edu, captured on July 16, 2024, can be viewed using The Internet Archive, Conifer, or by loading the WARC …

Separation Of Zr From Complex Matrices For Isotope Harvesting Applications, Jake A. Bence

Dissertations, Theses, and Capstone Projects

Zr isotopes have various applications in nuclear science, such as ⁸⁶Zr and ⁸⁹Zr in nuclear medicine, ⁸⁸Zr as a diagnostic isotope relevant to stockpile stewardship, and the fission product ⁹⁵Zr useful as an s-process branch nucleus for study in astrophysics. To access these isotopes of interest, dedicated production methods and subsequent processing chemistry are required. Direct production routes can be technically challenging and difficult to obtain enough activity to meet demand. The processing chemistry of Zr isotopes is tedious due to the tendency for Zr to hydrolyze in solution without highly acidic conditions or a strong …

On The Second Case Of Fermat's Last Theorem Over Cyclotomic Fields, Owen Sweeney

Dissertations, Theses, and Capstone Projects

We obtain a new simpler sufficient condition for Kolyvagin's criteria, regarding the second case of Fermat's last theorem with prime exponent p over the p-th cyclotomic field, to hold. It covers cases when the existing simpler sufficient conditions do not hold and is important for the theoretical study of the criteria.

Dataset: Marsh Migration Methodology Development For Wetland Restoration Targeting, Molly Mitchell, Karinna Nunez, Christine Tombleson, Julie Herman

Data

Coastal marsh loss is a significant issue globally, due in part to rising sea levels and high levels of coastal human activity. Marshes have natural mechanisms to allow them to adapt to rising sea levels, however, migration across the landscape is one of those mechanisms and is frequently in conflict with human use of the shoreline. Ensuring the persistence of marshes into the future requires an understanding of where marshes are likely to migrate under sea level rise and targeting those areas for conservation and preservation activities. The goal of this project was to 1) compile existing datasets and information …

Synthesis Of Shoreline, Sea Level Rise, And Marsh Migration Data For Wetland Restoration Targeting Final Report, Molly Mitchell, Karinna Nunez, Christine Tombleson, Julie Herman

Data

Coastal marsh loss is a significant issue globally, due in part to rising sea levels and high levels of coastal human activity. Marshes have natural mechanisms to allow them to adapt to rising sea levels, however, migration across the landscape is one of those mechanisms and is frequently in conflict with human use of the shoreline. Ensuring the persistence of marshes into the future requires an understanding of where marshes are likely to migrate under sea level rise and targeting those areas for conservation and preservation activities. The goal of this project was to 1) compile existing datasets and information …

Singlet Oxygen-Mediated Conformational Flexibility, Antioxidant, And Isomerization Studies In Chemistry And Biochemistry, Oliver Turque

Dissertations, Theses, and Capstone Projects

Three chapters are included in this dissertation, each of which describes non-oxidative reactions, with peroxy intermediates formed between singlet oxygen (¹O₂) and substrate. (1) Novel discoveries related to the intermediate formed by ¹O₂ and dimethyl disulfane are explored. (2) A new mechanism is proposed, wherein the dihedral angle CS–SC (θ) determines the pro- or antioxidant activity of an organic disulfide. (3) A review of ¹O₂'s ability to facilitate the geometric isomerization of alkenes and polyenes is presented in Chapter 3.

Chapter 1 investigates the role of singlet oxygen potentially …

Explaining Students’ Attitudes Towards A Sustainable Future: Evidence From Sea-Plm 2019 Data, Syeda Kashfee Ahmed, Petra Lietz

Global education monitoring

This report, published by the Global Education Monitoring (GEM) Centre, discusses how students’ attitudes towards global issues are now crucial more than ever to build a sustainable world for future generations. The first section describes why students’ attitudes towards school and learning are important and how they are linked to the Educational Prosperity Framework (Willms & Tramonte, 2015). The second section highlights the literature about the key factors which can influence students’ attitudes towards school and learning and how they are related to students’ attitudes towards sustainable development. The third section discusses the methods used for analysing the relationships between …

2023 September - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

On Predicting Esg Ratings Using Dynamic Company Networks, Gary Ang, Zhiling Guo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Environmental, social and governance (ESG) considerations play an increasingly important role due to the growing focus on sustainability globally. Entities, such as banks and investors, utilize ESG ratings of companies issued by specialized rating agencies to evaluate ESG risks of companies. The process of assigning ESG ratings by human analysts is however laborious and time intensive. Developing methods to predict ESG ratings could alleviate such challenges, allow ESG ratings to be generated in a more timely manner, cover more companies, and be more accessible. Most works study the effects of ESG ratings on target variables such as stock prices or …

Experimental Comparison Of Features, Analyses, And Classifiers For Android Malware Detection, Lwin Khin Shar, Biniam Fisseha Demissie, Mariano Ceccato, Naing Tun Yan, David Lo, Lingxiao Jiang, Christoph Bienert

Research Collection School Of Computing and Information Systems

Android malware detection has been an active area of research. In the past decade, several machine learning-based approaches based on different types of features that may characterize Android malware behaviors have been proposed. The usually-analyzed features include API usages and sequences at various abstraction levels (e.g., class and package), extracted using static or dynamic analysis. Additionally, features that characterize permission uses, native API calls and reflection have also been analyzed. Initial works used conventional classifiers such as Random Forest to learn on those features. In recent years, deep learning-based classifiers such as Recurrent Neural Network have been explored. Considering various …

Automated Question Title Reformulation By Mining Modifcation Logs From Stack Overflow, Ke Liu, Xiang Chen, Chunyang Chen, Xiaofei Xie, Zhanqi Cui

Research Collection School Of Computing and Information Systems

In Stack Overflow, developers may not clarify and summarize the critical problems in the question titles due to a lack of domain knowledge or poor writing skills. Previous studies mainly focused on automatically generating the question titles by analyzing the posts’ problem descriptions and code snippets. In this study, we aim to improve title quality from the perspective of question title reformulation and propose a novel approach QETRA motivated by the findings of our formative study. Specifically, by mining modification logs from Stack Overflow, we first extract title reformulation pairs containing the original title and the reformulated title. Then we …

Uncertainty-Adjusted Inductive Matrix Completion With Graph Neural Networks, Petr Kasalicky, Antoine Ledent, Rodrigo Alves

Research Collection School Of Computing and Information Systems

We propose a robust recommender systems model which performs matrix completion and a ratings-wise uncertainty estimation jointly. Whilst the prediction module is purely based on an implicit low-rank assumption imposed via nuclear norm regularization, our loss function is augmented by an uncertainty estimation module which learns an anomaly score for each individual rating via a Graph Neural Network: data points deemed more anomalous by the GNN are downregulated in the loss function used to train the low-rank module. The whole model is trained in an end-to-end fashion, allowing the anomaly detection module to tap on the supervised information available in …

Edge Distraction-Aware Salient Object Detection, Sucheng Ren, Wenxi Liu, Jianbo Jiao, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Integrating low-level edge features has been proven to be effective in preserving clear boundaries of salient objects. However, the locality of edge features makes it difficult to capture globally salient edges, leading to distraction in the final predictions. To address this problem, we propose to produce distraction-free edge features by incorporating cross-scale holistic interdependencies between high-level features. In particular, we first formulate our edge features extraction process as a boundary-filling problem. In this way, we enforce edge features to focus on closed boundaries instead of those disconnected background edges. Second, we propose to explore cross-scale holistic contextual connections between every …

Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The digital economy has brought significant advancements in electronic devices, increasing convenience and comfort in people’s lives. However, this progress has also led to a shorter life cycle for these devices due to rapid advancements in hardware and software technology. As a result, e-waste collection and recycling have become vital for protecting the environment and people’s health. From the operations research perspective, the e-waste collection problem can be modeled as the Heterogeneous Vehicle Routing Problem with Multiple Time Windows (HVRP-MTW). This study proposes a metaheuristic based on the Greedy Randomized Adaptive Search Procedure complemented by Path Relinking (GRASP-PR) to solve …

Fine-Grained In-Context Permission Classification For Android Apps Using Control-Flow Graph Embedding, Vikas Kumar Malviya, Naing Tun Yan, Chee Wei Leow, Ailys Xynyn Tee, Lwin Khin Shar, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Android is the most popular operating system for mobile devices nowadays. Permissions are a very important part of Android security architecture. Apps frequently need the users’ permission, but many of them only ask for it once—when the user uses the app for the first time—and then they keep and abuse the given permissions. Longing to enhance Android permission security and users’ private data protection is the driving factor behind our approach to explore fine-grained contextsensitive permission usage analysis and thereby identify misuses in Android apps. In this work, we propose an approach for classifying the fine-grained permission uses for each …

Hercules: Boosting The Performance Of Privacy-Preserving Federated Learning, Guowen Xu, Xingshuo Han, Shengmin Xu, Tianwei Zhang, Hongwei Li, Xinyi Huang, Robert H. Deng

Research Collection School Of Computing and Information Systems

In this paper, we address the problem of privacy-preserving federated neural network training with N users. We present Hercules, an efficient and high-precision training framework that can tolerate collusion of up to N−1 users. Hercules follows the POSEIDON framework proposed by Sav et al. (NDSS’21), but makes a qualitative leap in performance with the following contributions: (i) we design a novel parallel homomorphic computation method for matrix operations, which enables fast Single Instruction and Multiple Data (SIMD) operations over ciphertexts. For the multiplication of two h×h dimensional matrices, our method reduces the computation complexity from O(h3) to O(h) . This …

Graph-Level Anomaly Detection Via Hierarchical Memory Networks, Chaoxi Niu, Guansong Pang, Ling Chen

Research Collection School Of Computing and Information Systems

Graph-level anomaly detection aims to identify abnormal graphs that exhibit deviant structures and node attributes compared to the majority in a graph set. One primary challenge is to learn normal patterns manifested in both fine-grained and holistic views of graphs for identifying graphs that are abnormal in part or in whole. To tackle this challenge, we propose a novel approach called Hierarchical Memory Networks (HimNet), which learns hierarchical memory modules---node and graph memory modules---via a graph autoencoder network architecture. The node-level memory module is trained to model fine-grained, internal graph interactions among nodes for detecting locally abnormal graphs, while the …

Are We Ready To Embrace Generative Ai For Software Q&A?, Bowen Xu, Thanh-Dat Nguyen, Thanh Le-Cong, Thong Hoang, Jiakun Liu, Kisub Kim, Chen Gong, Changan Niu, Chenyu Wang, David Lo, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Overflow after only 6 days from its release. The main reason provided by the official Stack Overflow is that the answers generated by ChatGPT are of low quality. To verify this, we conduct a comparative evaluation of human-written and ChatGPT-generated answers. Our methodology employs both automatic comparison and a manual study. Our results suggest that human-written and ChatGPT-generated answers are semantically similar, however, human-written answers outperform ChatGPT-generated ones consistently across multiple aspects, …

Quantifying Taxi Drivers' Behaviors With Behavioral Game Theory, Mengyu Ji, Yuhong Xu, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

With their flexibility and convenience, taxis play a vital role in urban transportation systems. Understanding how human drivers make decisions in a context of uncertainty and competition is crucial for taxi fleets that depend on drivers to provide their services. As part of this paper, we propose modeling taxi drivers’ behaviors based on behavioral game theory. Based on real-world data, we demonstrate that the behavioral game theory model we select is superior to state-of-the-art baselines. These results provide a solid foundation for improving taxi fleet efficiency in the future.

The Devil Is In The Tails: How Long-Tailed Code Distributions Impact Large Language Models, Xin Zhou, Kisub Kim, Bowen Xu, Jiakun Liu, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Learning-based techniques, especially advanced Large Language Models (LLMs) for code, have gained considerable popularity in various software engineering (SE) tasks. However, most existing works focus on designing better learning-based models and pay less attention to the properties of datasets. Learning-based models, including popular LLMs for code, heavily rely on data, and the data's properties (e.g., data distribution) could significantly affect their behavior. We conducted an exploratory study on the distribution of SE data and found that such data usually follows a skewed distribution (i.e., long-tailed distribution) where a small number of classes have an extensive collection of samples, while a …

Are We Ready To Embrace Generative Ai For Software Q&A?, Bowen Xu, Thanh-Dat Nguyen, Thanh Le Cong, Thong Hoang, Jiakun Liu, Kisub Kim, Chen Gong, Changan Niu, Chenyu Wang, Xuan-Bach Dinh Le, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Overflow after only 6 days from its release. The main reason provided by the official Stack Overflow is that the answers generated by ChatGPT are of low quality. To verify this, we conduct a comparative evaluation of human-written and ChatGPT-generated answers. Our methodology employs both automatic comparison and a manual study. Our results suggest that human-written and ChatGPT-generated answers are semantically similar, however, human-written answers outperform ChatGPT-generated ones consistently across multiple aspects, …

Butte Priority Soils Operable Unit (Bpsou) Final Unreclaimed Sites – Field Sampling Plan (Fsp) Ur 43 – Area Near Missoula Gulch Ballfield, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2023, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2023, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) Final Unreclaimed Sites – Field Sampling Plan (Fsp) Ur 42 – Area Near Walkerville Playground, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Advances And Perspectives Of Using Stable Isotope Probing (Sip)-Based Technologies In Contaminant Biodegradation, Jinha Kim, Myung Hwangbo, Chih-Hsuan Shih, Kung-Hui Chu

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Highlights

• Advances of SIP-based techniques/applications are comprehensively reviewed.

• Varying stable isotopes types/numbers/ positions reinforce biodegradation studies.

• SIP identifies microbes capable of co-metabolic degradation of contaminants.

• Single-cell SIP.and qSIP are promising to overcome cross-feeding effects.

Abstract

Stable isotope probing (SIP) is a powerful tool to study microbial community structure and function in both nature and engineered environments. Coupling with advanced genomics and other techniques, SIP studies have generated substantial information to allow researchers to draw a clearer picture of what is occurring in complex microbial ecosystems. This review provides an overview of the advances of SIP-based technologies over time, summarizes the …

Impact Of Thermal Water On Environment: Case Study Of Mila And Guelma Region, Algeria, Rima Kifouche, Foued Bouaicha, Oualid Bouteraa

Bulletin of the Mineral Research and Exploration

A hydrochemical characterization of the waters of the study region (North-East Algeria) was carried out following samples taken at 36 thermal springs and their effluents during May 2022. The analysis of the waters allowed to establish the chemical facies and their classification according to the Stuyfzand’s method and to deduce the aptitude of these waters for irrigation and the risks of salinity. The results revealed physico-chemical characteristics, relatively, variable. Q-mode cluster analysis was applied to the thermal water, generated four (4) groups clusters. Group1 represent a group of waters with low salinity dominated by Na-HCO3; Stuyfzand’s classification indicated that the …