Digital Commons Network^™

A Systematic Review And Network Meta-Analysis Of Empirical Antibiotics For Complicated Urinary Tract Infections, Lior Cohen-Yatziv, Emily Gilbert, Ruiwen Zhou, Maria Cristina Vazquez Guillamet

2020-Current year OA Pubs

BACKGROUND: Empiric antibiotic selection for complicated urinary tract infections (cUTIs) is increasingly complex due to the rising prevalence of multidrug-resistant organisms. We conducted a network meta-analysis (NMA) to compare clinical efficacy and safety among existing empiric treatment options.

METHODS: We performed a frequentist random-effects NMA of randomized controlled trials evaluating single-agent empiric regimens for adults with cUTIs. The primary endpoints were clinical response (CR), microbiological response, and serious adverse events (AEs). Ceftriaxone served as the common comparator.

RESULTS: Forty-seven trials were identified through a systematic search. In the primary analysis of 17 studies published after the year 2000, evaluating agents …

Tennessee Archives Month Proclamation, 2026, Tennessee. Office Of The Governor

Tennessee Archives Month proclamations

Proclamation issued by the Governor designating October 2026 as Tennessee Archives Month.

Marie Taylor Barton And Southern Modernism, Cynthia Fowler

Art Inquiries

This paper examines the efforts by Southern artist Marie Taylor Barton (1904-1992) of Nashville, Tennessee to spread the principles of modern art to her community through her art practice and her advocacy for modern art. Barton emerged as an artist in the first half of the twentieth century. She studied with New York modern artist Ralph Pearson (1883-1958), an underrecognized but highly influential art teacher, at his summer school in Gloucester, Massachusetts. While in Gloucester, she also heard lectures by artist Hans Hofmann and visited Dartmouth College to see José Clemente Orozco’s mural The Epic of American Civilization (1932-34) that …

Noise Characterization And Mitigation In Intermediate-Scale Quantum Systems, Muhammad Qasim Khan

Dartmouth College Ph.D Dissertations

Current quantum processors, at the intermediate scale of tens to hundreds of qubits, remain error-limited. This thesis studies two related sources of error. The first is environmental noise, which may have temporal and spatial correlations and nonclassical components. The second is state-preparation and measurement (SPAM) error, which arises in the operations used to characterize this noise, a prerequisite for boosting operational fidelities. Neither can be characterized alone. Noise spectroscopy techniques use imperfect preparation and readout, while SPAM characterization is affected by qubit decoherence. Our methods vary measurement depth, drive duration, or sequence repetition so each source changes the measured signal …

Compiling Code Llms Into Lightweight Executables, Jieke Shi, Junda He, Zhou Yang, Chengran Yang, Mykhailo Klymenko, Thong (James) Hoang, Sherry (Xiwei) Xu, Zhenchang Xing, David Lo

Research Collection School Of Computing and Information Systems

The demand for better prediction accuracy and higher execution performance in neural networks continues to grow. The emergence and success of Large Language Models (LLMs) have produced many cloud-based tools for software engineering tasks such as code suggestion. Although effective, cloud deployment raises concerns over privacy, latency, and reliance on network connectivity. Running LLMs locally on personal devices such as laptops would address these issues, because it enables offline use and reduces response time. However, local deployment is challenging, since commodity devices lack high-performance accelerators such as GPUs and are constrained by limited memory and compute capacity, which makes it …

Are We Stuck? Modeling And Detecting Deadlocks In Multi-Autonomous Vehicle Systems, Mingfei Cheng, Xiaofei Xie, Lili Quan, Yuan Zhou

Research Collection School Of Computing and Information Systems

Autonomous driving system (ADS) testing is essential to ensure the safety and reliability of autonomous vehicles (AVs) prior to deployment. As ADSs are increasingly deployed in multi-AV traffic environments, it becomes crucial to assess their cooperative performance, particularly with respect to deadlock, a fundamental liveness issue in concurrent systems that can lead to traffic congestion and prolonged stalling. However, the analysis and testing of ADSs’ cooperative capabilities with respect to deadlock remain largely underexplored. In this work, we present the first systematic study of deadlock in multi-AV systems. We formalize deadlock in autonomous driving using a time-indexed wait-for relation grounded …

Rent-A-Rag: Embedding-Space Watermarks For Auditing Third-Party Rag, Alexandr Goultiaev Tolstokorov, Kyriakos Mouratidis, Javad Dogani, Nikolaos Laoutaris

Research Collection School Of Computing and Information Systems

Third-party retrieval-augmented generation (RAG) marketplaces create a new auditing problem: data providers may license corpora to a RAG operator, yet later have no visibility into whether their documents are being reused without compensation. Auditing this misuse is difficult because the operator is non-cooperative, answers are paraphrased by the generator, and one response may combine evidence from many providers. We propose DirBucket, a provider-side semantic watermarking and black-box auditing framework for document-level reuse in multi-provider RAG. DirBucket watermarks documents by meaningpreserving paraphrases whose embeddings are biased toward provider-bucket secret directions, enabling detection from black-box answers while preserving retrieval utility. On a …

Characterizing And Repairing Obsolete Android Gui Tests Under Ui Evolution, Shiwen Song, Yiheng Xiong, Wenbo Guo, Manqi Sun, Jiaolong Kong, Xiaofei Xie

Research Collection School Of Computing and Information Systems

Graphical user interface (GUI) tests are widely used in regression testing of mobile applications (apps) tovalidate app behavior from the user’s perspective. However, frequent app evolution, such as UI redesignsand feature updates, often renders existing GUI tests obsolete, even when underlying functionality remainsunchanged. Automatically repairing such tests is critical for maintaining test suites and reducing substantialmanual effort. Despite the practical importance, there is still a lack of a systematic understanding of thecharacteristics of obsolete GUI tests and a publicly available benchmark to support their study. To fill thisgap, we construct a benchmark comprising 736 obsolete GUI tests collected from 36 …

Arabic Clinical Mental Health Named Entity Recognition Via Distant Supervision: Recurrent Vs. Transformer-Based Architectures, Ali A. Jalil, Rabih Sbera

Polytechnic Journal

Arabic Natural Language Processing (NLP) has made great strides, but the accurate extraction of mental state and physiological symptoms from patient-generated clinical consultations in dialectal Arabic, which is plagued with significant morphological complexity, colloquial noise and an extremely limited number of manually annotated clinical benchmarks, remains a significant challenge. In this work, we propose an end-to-end token-level symptom extraction system that is systematic and grounded in distant supervision paradigm and a strict gold standard evaluation with human verification to ensure real-world clinical generalization. A large weakly labelled corpus of 46,873 Arabic patient questions was created based on a clinical lexicon …

Beyond The Poster Session: Turning A Scientific Poster Into A Publishable Manuscript, Scott R. Beason

The Compass: Earth Science Journal of Sigma Gamma Epsilon

Scientific posters are often treated as the final product of an undergraduate research project. After months of fieldwork, laboratory analysis, data processing, and interpretation, a student prepares a poster, presents the work at a departmental symposium or professional meeting, rolls up the poster, and moves on to the next stage of their career. The research, however, does not necessarily need to end with the poster session. A well-developed scientific poster already contains many of the fundamental elements of a scientific manuscript: a research question, scientific context, methods, results, figures, interpretation, discussion, and conclusions. Converting a poster into a manuscript therefore …

In Memoriam: Dr. Don C. Steinker (1936-2026), Paleobiologist, Teacher, Editor, And Mentor, Margaret M. Yacobucci, Susan T. Goldstein, Ronald E. Martin

The Compass: Earth Science Journal of Sigma Gamma Epsilon

Dr. Don C. Steinker, Professor Emeritus of Geology and Paleobiology, died at the age of 89 in Bowling Green, Ohio, on February 5, 2026. During his remarkable 43-year career at Bowling Green State University (BGSU), Don played a pivotal role in developing the Paleobiology specialization within the Geology undergraduate degree program, mentored generations of students, and served as advisor for the Beta Upsilon chapter of Sigma Gamma Epsilon (SGE) from 1969 until his retirement in 2010. In this brief memorial, we will highlight some of Don’s most important contributions to BGSU’s geology program, the field of foraminiferal paleobiology, geoscience education, …

A Tribute To Frank Delno Holland, Jr. (1924-2023), Sigma Gamma Epsilon National President (1970-1975), Paleontologist, And Friend, John M. Erickson

The Compass: Earth Science Journal of Sigma Gamma Epsilon

Frank Delno Holland, Jr., was born in Leavenworth, Kansas, on March 6, 1924. All family and friends, including his students and professional acquaintances, knew him as Bud. His parents were Frank D. Holland and Francys Bell Holland. His paternal grandparents, O.B. and Laura Holland were North Dakotans who had homesteaded in Sargent County during the 1880s, but had relocated to Kansas in 1903. Bud had a rural upbringing on the outskirts of Leavenworth, graduating in 1942 from Leavenworth High school. It seemed natural that he would follow in his father’s footsteps by attending the University of Kansas (KU) so Bud …

The Compass - Volume 95 Issue 2 - Complete Issue, Scott R. Beason

The Compass: Earth Science Journal of Sigma Gamma Epsilon

No abstract provided.

Training Apart, Together: Team Dynamics In Individual Sports And Surgical Residency, W. Jack Palmer, Dylan Bertoni, Elizabeth E. Cottrill, Colin T. Huntley

Department of Otolaryngology - Head and Neck Surgery Faculty Papers

Surgeons in training share notable parallels with competitive athletes, including rigorous training, skill specialization, and functioning under pressure. Surgical educators have leveraged this comparison, incorporating techniques from sports psychology, such as mental imagery and mindfulness, to improve trainees' individual performance and well-being. Surgical trainees and athletes both rely on effective teamwork for optimal outcomes, suggesting that residency leaders can glean valuable team-level insights from sports psychology. This article examines how the structure of surgical residency influences team dynamics, using concepts from sports psychology to identify evidence-based strategies for improving program cohesion and resident well-being. The surgical literature typically conceptualizes surgery …

Eating Disorders & Meat Consumption: A Meta-Analytic Review, Urska Dobersek, Laurel Standiford-Reyes, Tyler Robinson, Alex Antony Edwin, Sarah Siebers

Midwest Social Sciences Journal

In this meta-analytic review, we examined the current evidence on eating disorders in relation to meat consumption and meat abstention. We systematically searched six online databases in December 2025 for primary research on eating disorder-related variables in meat consumers and meat abstainers. Fifty-one studies with 55,984 participants (n_{meat consumers} = 44,282, n_{meat abstainers} = 9,751) met the inclusion/exclusion criteria. The outcomes were eating disorders and orthorexia nervosa. Meat consumption was associated with lower eating disorder (g = 0.20, 95% CI [0.08, 0.32], p = .001) and orthorexia nervosa symptomology (g = 0.47, 95% CI [0.33, …

Experience Of Working And Studying In Nursing School: A Qualitative Study, Fatimah O. Azeez

Undergraduate Honors Theses

It is hypothesized that some student nurses enrolled in a higher education degree program face academic challenges when retaining employment while attending school. This study aims to explore the various experiences of working students compared to non-working students. Specifically, to quantify and correlate the effects of working while studying in nursing school. The Cognitive Load Theory will be used to guide the research and implementation of the effects of working while simultaneously attending nursing schools on nursing students. Cognitive Load Theory suggests that the human brain has a limited capacity to process information and overloading it with too many tasks …

Intersections Of Religion, Race, And Feminism With A Progressive Politic, Amanda D. Hernandez, Tess Starman Phd

Sociology: Faculty Publications

Public perceptions of feminism often posit religion as antithetical to the movement, despite many Christian women who identify as feminist. Previous scholarship has studied the ways that race and ethnicity have shaped how individuals conceptualize feminism. This study brings religious affiliation into the equation, specifically among Christian women in the United States. Do women who identify as Christian feminists have more “progressive” stances on social issues than Christian women who do not identify as feminist? Through a quantitative analysis of the 2021 Values and Beliefs of the American Public Survey, this study shows the differential moderating effect of two variables: …

State: The Magazine Of Illinois State University, Fall 2026, Illinois State University, University Marketing And Communications

State: The Magazine of Illinois State University (1999-present)

Illinois State University alumni magazine

Iot-Enabled Smart Durian Harvesting: An Integrated Platform For Real-Time Orchard Monitoring And Sustainable Harvest Management, Norisan Abd Karim, Nur Carmilla Abdullah Muhammad Shafiq, Nur’Aina Daud, Syibrah Naim, Syaheerah Lebai Lutfi

Malaysian Journal of Computing (MJoC)

Durian harvesting requires timely monitoring to ensure that fallen fruits are collected promptly, thereby reducing quality deterioration and potential economic losses. Traditional orchard monitoring relies heavily on manual inspection, making the process time-consuming, labour-intensive, and inefficient, particularly in large orchards. The Internet of Things (IoT) technology has been widely used in smart agriculture to manage orchards, but there are very few existing systems that combine real-time durian fall detection with a mobile application that sends immediate notifications, automatic image capture of fall events, and orchard management functions. This study develops an Integrated IoT-Based Smart Orchard Platform for real-time durian harvest …

Benefit-Cost Analysis: A Practitioner’S Guide, Hue Vuong, Amir Abadi Ghadim, Paul Mattingley, Ross Kingwell, Vilaphonh Xayavong, Tafesse Estifanos, Dipesh Maharjan, Nicholas Thorsager, Christophe D'Abbadie, Johnny Machon, Sud Kharel

Farm Systems and Economics published reports

This guide provides government agency staff with a comprehensive, practical and nationally aligned framework for conducting Benefit-Cost Analysis (BCA) of public investments. BCA is a systematic approach to comparing the full range of expected costs and benefits of a proposed investment, expressed in monetary terms where possible. It helps determine whether an investment is likely to deliver net benefits to society and whether public resources are being directed towards initiatives that generate the greatest overall value. BCA is one of the primary and most widely recommended economic appraisal approaches used across Australian governments when assessing major public investments.

Center For Biomedical Research At The Population Council, Population Council

Fact Sheets

No abstract provided.

Factors Influencing Enterprise Adoption Of Ai-Enabled Computers: An Expert Judgment Quantification Approach Across Multiple Sectors, Yu Shan Su, Tugrul Daim, Chia-Hao Hung, Leong Chan, Dana Bakry

Engineering and Technology Management Faculty Publications and Presentations

This study examines the key factors influencing the adoption of Artificial Intelligence Personal Computers (AIPCs) by enterprises, exploring both the benefits and challenges of their business applications. As enterprises increasingly require real-time computing, autonomous decision-making, and improved cybersecurity, AIPC—combining artificial intelligence and edge computing—has become a strategic technology for boosting competitiveness. Particularly in scenarios with less reliance on cloud services, businesses are more likely to adopt devices with local processing and standalone AI capabilities to meet the dual needs of operational efficiency and data privacy. Through an extensive review of the literature, this study identifies four main dimensions and sixteen …

The Effects Of Pluss: Adapting An Evidence-Based Reading Intervention For Multilingual Learners, Amanda K. Sanford, Christopher J. Pinkney, Sheldon Loman, Julie Esparza Brown, Theresa Just, Kendall Flori, Camila Swift, Holly Ramstead

Educator Licensure Faculty Publications and Presentations

The effects of an evidence-based literacy intervention with and without added supports to address the unique needs of multilingual learners (MLs) were assessed through an ABAB single-case withdrawal design. The dual dependent variables were reading fluency/accuracy and performance on the workbook that included spelling, vocabulary, and reading comprehension tasks. Three students (one each in second, third, and fourth grades) who qualified for English language development services and exhibited low reading performance (second and third graders) or were identified with a reading disability (fourth grader) participated. From the initial baseline phase (A1) to the final intervention phase (B2), adding supports specific …

Line Of Sight Lighting Effect In Dark Environment And Its Impact On Interactive Horror Game Experience, Hamzah Asyrani Sulaiman, Fuyen Heng

Malaysian Journal of Computing (MJoC)

Lighting effects in dark environments represent a fundamental psychological mechanism in horror game design, directly shaping player immersion, emotional tension, and the quality of interactive experience. Although Line of Sight (LoS) technology has been widely adopted across many game genres, empirical investigations examining how LoS-based dynamic lighting specifically affects player engagement, usability, and visual aesthetic perception within single-player horror puzzle contexts remain scarce. This paper presents the design, development, and user evaluation of “No One Left”, a three-dimensional top-down horror puzzle game developed using Unreal Engine 4, which systematically employs LoS-based lighting mechanics within a dark environment to restrict player …

Vision Transformer-Based Classification Of Cervical Cancer Images, Muhammad Daniel Alif Jumairi, Itaza Afiani Mohtar, Suraya Masrom, Masurah Mohamad, Lathifah Alfat

Malaysian Journal of Computing (MJoC)

Cervical cancer is a significant health concern as it is one of the most fatal causes of cancer deaths in women. Detection at an early stage is vital, but conventional diagnostic procedures via Pap smears relies heavily on manual cytopathology inspection, a process prone to human fatigue, diagnostic subjectivity, and severe practitioner shortages in low-resource medical environments. To address these challenges, this study presents an automated cervical cancer image classification framework utilizing advanced Vision Transformer (ViT) architectures. Three ViT variants: Data-efficient Image Transformer (DeiT), Swin Transformer, and Cross-Attention Multi-Scale Vision Transformer (CrossViT) were fine-tuned and evaluated on the benchmark SIPaKMeD …

Comparative Machine Learning Prediction Of Carbon Monoxide Levels And Contributing Factors In Shah Alam, Farzana Zubaidi, Norshahida Shaadan, Septia Devi Prihastuti Yasmirullah

Malaysian Journal of Computing (MJoC)

Carbon monoxide (CO) pollution is a major environmental and public health concern because it is colourless and odourless and is produced mainly by incomplete combustion from vehicles, industries, and household sources. Accurate prediction of CO levels and identification of key contributing factors can support early warning and targeted mitigation strategies. This study compared eight machine-learning regression models—Support Vector Regression (SVR), Random Forest Regression (RFR), Decision Tree Regression (DTR), K-Nearest Neighbours (KNN), CatBoost, XGBoost, LightGBM, and Neural Network Regression (NNR)—using daily air-quality data from the Department of Environment Malaysia for 2018–2023. The dataset comprised 42 input features representing air pollutants, meteorological …

A Data Envelopment Analysis Approach To Benchmarking The Efficiency In Selected Malaysian Food Manufacturing Companies, Zuraida Alwadood, Natasya Syafiah Marlis Elias, Norlenda Mohd Noor, Bekzodjon Fayziev

Malaysian Journal of Computing (MJoC)

Food industry, which includes every stage of the production process, from farming and manufacturing to distribution, retail and services, is one of the biggest and most significant sectors in the global economy. The relative efficiency of Malaysian food manufacturing companies is still unclear since many of them lack benchmarking tools and struggle to allocate labor, energy and raw materials optimally. This study applies the Data Envelopment Analysis (DEA) method to examine the relative efficiency of Malaysian food manufacturing companies. Relative efficiency refers to the ratio of the weighted sum of the outputs to the weighted sum of the inputs. The …

Machine Learning-Based Mental Health Risk Prediction And Behavioural Clustering Among Malaysian Undergraduates, Norsyela Muhammad Noor Mathivanan, Debbie Yong Xi Foo, Gerard Soon Lee Chong, Siti Fazilah Shamsudin, Marizkays P. Jamison

Malaysian Journal of Computing (MJoC)

Mental health issues among undergraduate students have become increasingly prevalent, affecting emotional well-being, academic performance, and overall quality of life. The growing number of students experiencing stress, anxiety, and depression highlights the need for effective predictive models to support early risk identification and personalized intervention strategies. This study investigates the performance of several machine learning approaches, including Logistic Regression (LR), Random Forest (RF), Gradient Boosting, LightGBM, Extra Trees, XGBoost, Support Vector Classifier (SVC), and a stacked ensemble model for predicting mental health risk among Malaysian undergraduate students. The study utilizes a dataset comprising demographic, academic, lifestyle, and psychological assessment attributes …

Malaysia Tech Stock Forecasting Using Arima: A Comparative Analysis With Kalman Filter Noise Optimization, Sarah Nadirah Mohd Johari, Ahmad Irfan Mohd Sukeri, Restu Ananda Putra, Ahmad Nur Azam Ahmad Ridzuan

Malaysian Journal of Computing (MJoC)

Forecasting stock prices in Malaysia's technology sector is difficult due to market noise. To mimic market behavior, many models have been developed and gradually improved with new algorithms and machine learning techniques. Relying on a single model often has drawbacks, so hybrid models were introduced to improve prediction stability. This study used a time series method, Autoregressive Integrated Moving Average (ARIMA) that has been proven to be reliable in forecasting various types of data. However, the ARIMA model often struggles with handling nonlinear and noisy data; thus, hybrid integration of the Kalman Filter was introduced to help reduce noise. The …

Turning Ontologies Into Vectors: Embedding Malay Ontological Knowledge For Smarter Machine Learning, Zayanah Zafirah Zulkipli, Ruhaila Maskat, Noor Hasimah Ibrahim Teo, Jie Zhang

Malaysian Journal of Computing (MJoC)

This conceptual study proposes a three-layer methodological framework for representing Malay ontological knowledge in continuous vector spaces and integrating ontology-derived representations with machine-learning models. The framework comprises an Ontology Layer, an Embedding Layer, and an Integration Layer. Its contribution is not a new ontology-embedding algorithm rather, it provides a Malay-oriented methodological organization that links ontology construction, embedding-method selection, symbolic-subsymbolic fusion, ontology-guided consistency checking, and downstream evaluation. In the present study, the ontology layer is represented through a prototype Malay linguistic ontology and its class hierarchy and knowledge graph, whereas the embedding, integration, consistency-checking, and downstream evaluation stages are proposed components …