Digital Commons Network^™

A057: Research On High-Quality Development Path Of Sports Tourism Boutique Projects In The Yellow River Basin, Yan Wang, Jinsheng Liu

International Journal of Physical Activity and Health

Background/Purposes: The boutique sports tourism initiative in the Yellow River Basin constitutes a comprehensive regional development strategy that integrates competitive events, scenic attractions, and travel itineraries across nine provincial administrations. The study aims to reveal the spatial distribution characteristics and explore the path of high-quality development of sports tourism boutique projects in the Yellow River Basin. (1) Through using the methods of mathematical statistics, 129 projects were selected for analysis, categorized under “scenic spot”, “line”, “event”, and “destination” of sports tourism boutique projects. The data sourced from the “China Sports Tourism Boutique Project” announced by the State Sports General Administration, …

A061: Analysis Of The Current Situation Of Table Tennis Players' Burnout, Rongqing Yu

International Journal of Physical Activity and Health

Burnout is a significant issue among athletes, especially those undergoing high-intensity training and facing competitive pressures. Table tennis players, due to the demands of their sport, are particularly vulnerable. Burnout can impair performance, mental health, and lead to training interruptions or early career termination. This study investigates the prevalence of burnout among table tennis players, examining differences based on gender, age, sports grade, and training duration, to inform targeted interventions. Method: The study utilized a comprehensive approach to data collection and analysis. Firstly, a literature review was conducted to establish a theoretical framework for understanding athlete burnout. Subsequently, a questionnaire …

A210: The Influence Of Applications Of Digital Technology On The Effect Of Competitive Aerobics Training, Guangqi Yang, Fuzhou Zhang, Jiawen Ding

International Journal of Physical Activity and Health

In recent years, with the development of information technology, the application of digital means in the field of sports has become increasingly extensive and deep. Competitive aerobics, as a traditional advantage project in the high-level university sports team, the innovation of its training methods is of great significance for improving athletic performance. However, the traditional training methods still have problems, such as inefficient and insufficient pertinence, which makes it difficult to meet the needs of modern training. Therefore, this paper designs the training method of university competitive aerobics from a digital background, obtains a scientific training strategy of university competitive …

Influence Of Rotation And An Inclined Magnetic Field For The Peristaltic Flow Of Viscoplastic Fluid Through A Porous Medium, Khalid Khaleefah Jassim, Mohammed Salim Ramadhan

Baghdad Science Journal

This research deals with the influencing of rotation and an inclined magnetic field on the analysis of blended convection heat transfer within a viscoelastic fluid that flows peristaltically through an inclined tapered asymmetric channel, that traversing in a porous media. The foundational equations of continuity, momentum, and energy were established in Cartesian coordinates. Furthermore, a range of dimensionless numbers, including Reynolds number, Brandt number, and Froude number, were introduced to regulate the governing equations in their imensionless forms. The governing equations were further simplified under the presumption of long wave lengths and small Reynolds numbers. The perturbation method was utilized …

Robust Qr Code Counterfeit Detection By Integrating Vgg19 Neural Embedding And Triplet Loss, Gede Putra Kusuma, Yulianto Yulianto, Renaldy Fredyan, Hendi Chandi, Jeffry William Tan, Philip Kwan, Muhammad Dafa Syukur

Baghdad Science Journal

Detecting counterfeit Quick Response codes plays a critical role in protecting the integrity of products and documents. This paper presents a novel methodology to increase the reliability of QR code counterfeit detection by integrating neural embedding VGG19 and triplet loss. The approach uses deep neural networks. Specifically, the modification of the VGG19 architecture is used to extract unique features from QR codes. These features are embedded in a multi-dimensional space using neural embedding methods. The use of the triplet loss function aims to increase the discriminative power of the embeddings, ensuring the discriminative power of the embeddings, and ensuring that …

Bioinformatics-Inspired Secure Video Encryption Using Chaotic Maps And Light Streaming Algorithms, Rajaa K. Hasoun, Rasha S. Ali, Ahmed G. Hameed, Ghassan H. Abdul-Majeed

Baghdad Science Journal

The Traditional encryption methods, such as AES, can be too slow for large video files, necessitating the development of faster and more efficient solutions for real-time video security. This research aims to enhance video security during transmission by developing a novel video encryption algorithm that is both fast and robust, specifically designed to handle large video datasets efficiently. The proposed video encryption algorithm integrates lightweight streaming algorithms for enhanced speed, modern cryptographic techniques, and chaotic maps for heightened security. The encryption process involves three key steps: Dividing the video into frames and scrambling/encrypting each frame, employing three innovative techniques: vertical …

Protocol For The Development Of The Who Gestational Weight Gain Charts, Thais Rangel Bousquet Carrilho, Olufemi Taiwo Oladapo, Jennifer A. Hutcheon, Giovanna Gatica-Domínquez, Kathleen M. Rasmussen, Monica C. Flores-Urrutia, Richard Kumapley, Ӧzge Tunçalp, Dang Bahya-Batinda, Amel A. Fayed, Annick Bogaerts, Aris T. Papageorghiou, Cinthya Muñoz-Manrique, Dayana Rodrigues Farias, Eric Ohuma, Harshpal Sachdev, Hayfaa A. Wahabi, Helena J. Teede, Molin Wang, Nandita Perumal Phd

Faculty Publications

Introduction Gestational weight gain (GWG) is an important indicator of maternal nutrition to be monitored during pregnancy. However, there is no evidence-based tool that can be used to monitor it across all geographic locations and pre-pregnancy body mass index (BMI) categories. The WHO is undertaking a project to develop GWG charts by pre-pregnancy BMI category, and to identify GWG ranges associated with the lowest risks of adverse maternal and infant outcomes. This protocol describes all the steps that will be used to accomplish the development of these GWG charts.

Methods and analysis This project will involve the analysis of individual …

Codazzi Normalized Null Hypersurfaces, Théophile Kemajou Mbiakop, Cyriaque Atindogbe, Ferdinand Ngakeu

Turkish Journal of Mathematics

We introduce a class of null hypersurfaces of Lorentzian manifolds, namely Codazzi normalized null hyper surfaces, whose (screen) shape operator associated with the rigged vector field is a Codazzi tensor. Several examples are given to support our study. Moreover, we investigate conditions implying that the induced Riemannian screen structure on a Codazzi-type normalized null hypersurface of a Lorentzian space is locally a nontrivial warped product.

Advancing The Rights Of Nature: Lessons From Sauk-Suiattle V. City Of Seattle, Harry S. Katz

American Indian Law Journal

Advocates for the “rights of nature” seek recognition of legal rights for natural elements such as mountains, rivers, and non-human species as a means of protecting the environment. In the United States, Tribal Nations have been at the forefront of this nascent movement. In a 2022 Washington state case, the Sauk-Suiattle Indian Tribe sued the City of Seattle, alleging that the City’s hydroelectric dams on the Skagit River infringe upon the rights of salmon. Those rights, they claim, include the salmon’s rights to exist, flourish, regenerate, and evolve. The case, known as Sauk-Suiattle Indian Tribe v. City of Seattle, …

A Neutrosophic Homological-Gröbner Framework For Ai-Driven Media Education Evaluation, Mona Gharib, Hafiz Muhammad Athar Farid, José M. Merigó, Muhammad Riaz

Sustainable Machine Intelligence Journal

The integration of artificial intelligence (AI) with media technologies has transformed teaching in Journalism and Communication, introducing new challenges for quality evaluation. Traditional assessment methods fail to capture the uncertainty, inconsistency, and incompleteness inherent in modern educational data. This paper proposes a Neutrosophic Homological–Gröbner Framework, which unifies three perspectives: neutrosophic sets to encode uncertain evidence, homological algebra to analyze structural coherence, and Gröbner bases to systematically simplify interdependent evaluation rules.

Within this framework, diverse evidence is encoded into neutrosophic triplets, daggregate into course-level indicators, and organized into neutrosophic chain complexes, where Betti indices reveal coherence and fragmentation. Educational policies are …

High-Performance Deep Learning Techniques For Plant Disease Detection: Performance Analysis, Validation, And Applications, Doaa El-Shahat, Ahmed Elmasry

Sustainable Machine Intelligence Journal

The early detection of plant diseases is an indispensable task to improve crop yields and production quality. Crop disease observations by experienced pathologists are difficult and might take a long time. Therefore, deep learning (DL) techniques have been utilized to present an automated detection technique that could accurately and timely detect plant diseases. Several DL models in the literature were proposed, but no paper conducted a comparative study between those models to determine which of them was the best alternative for this task. Therefore, twenty-one DL models are compared in this review paper to show which of them could achieve …

Rf-Et-Ann: Hybrid Machine Learning Model For Forecasting Short-Term Photovoltaic Power Production, Walid Abdullah, Ahmed Ismail Ebada, Mohamed Abouhawwash

Sustainable Machine Intelligence Journal

Accurately forecasting photovoltaic (PV) power generation is a challenging problem due to the non-linear and highly variable characteristics of solar data, which is strongly influenced by several interdependent factors, such as environmental conditions, system characteristics, and technical aspects. In this study, a newly proposed machine learning (ML) technique based on integrating random forest (RF), extra trees (ET), and artificial neural networks (ANN) is presented to tackle this problem with better predictive accuracy, ensuring that solar energy is used more consistently, effectively, and economically; this model is dubbed RF-ET-ANN for short. Hybridization of these three models will help capture non-linear aspects …

Gnmsa: An Accurate Parameter Estimation Of Semi-Empirical Proton Exchange Membrane Fuel Cells Model Using A Hybrid Artificial Intelligence–Based Optimization Approach, Dina Atef, Doaa El-Shahat, Hafiz Burhan Ul Haq, Zaka Ur Rehman, Muhammad Nauman Irshad

Sustainable Machine Intelligence Journal

The PEMFC parameter estimation problem has recently piqued the interest of several researchers due to its significance in reaching better PEMFC modeling. However, existing PEMFC parameter estimation algorithms encounter significant difficulty in solving this problem because of its complex and highly nonlinear nature. Therefore, this paper presents a new hybrid approach, termed GNMSA, for addressing this problem more accurately. This hybrid approach combines the exploration operator of the generalized normal distribution optimization with the exploitation operator of the mantis search optimization (MSA), resulting in this strong variant that has high abilities to alleviate stagnation in local optima and expedite convergence …

An Enhanced Optimization Algorithm For Estimating Pem Fuel Cells Parameters: Performance Comparison And Real-World Applicability, Ibrahim Alrashdi, Karam M. Sallam

Sustainable Machine Intelligence Journal

Accurate modeling is critical for the efficient design, control, and optimization of a proton exchange membrane (PEM) fuel cell. This problem is regarded as a multi-modal, multi-variate, non-linear optimization problem, and several methods in the literature have been presented to tackle it. However, those methods still suffer from either being stuck into local optima or a slow convergence rate. To solve this problem more accurately in terms of final results and convergence speed, this study proposes a hybrid optimization algorithm based on enhancing the recently proposed crested porcupine optimizer (CPO) using two new optimization methods, namely ranking-based optimization and exploration-exploitation …

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

The Bg News January 14, 2026, Bowling Green State University

BG News (Student Newspaper)

The BGSU campus student newspaper. January 14, 2026. Volume 105-Issue 13.

Reproducible Semantic Data Management Workflow For Materials Data Science: Generating Knowledge Graphs With Robust Fairifcation Pipelines, Kyle R. Henrikson, Van D. Tran, Meredith Francis, Isabella Giammattei, Quynh D. Tran, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

Combining data from multiple sources is crucial for efficient knowledge aggregation in materials data science. FAIR data from ontology and Linked Data principles enable this. Semantic data management streamlines data exchange and aggregation, ensuring information is available and extractable. FAIRLinked and GraphDB provide solutions for consolidating, hosting, and extracting meaningful insight from multimodal data.

Determination Of Sample Size In Vaccine Trials, Meghna Bose

Doctoral Theses

Sample size determination is an important as well as delicate problem in clinical trials. Often, prior information available before the beginning of the trial is used to estimate the sample size. Hence, it is of importance to quantify the prior information available in terms of an Effective Sample Size (ESS). The problem of finding Effective Sample Size (ESS) in Phase II clinical trials, where toxicity and efficacy are the two components of the treatment response vector, is considered. In particular, one of the components is assumed to be binary, and the other is assumed to be continuous. Theoretical expressions for …

High Thermoelectric Power Conversion Efficiency Of An Earth-Abundant Janus Silicon Oxy-Sulfide Monolayer: A First-Principles Study, Zakariae Darhi, Mounaim Bencheikh, Ravindra Pandey, Larbi El Farh

Michigan Tech Publications

The tunable properties of Janus monolayers, along with advances in their synthesis, make these low-symmetry materials excellent candidates for thermoelectric power generation. In this study, we systematically investigate the electronic and thermal properties of the Janus silicon oxy-sulfide monolayer. The results based on density functional theory reveal that the monolayer is stable. It exhibits a tunable direct band gap and strong covalent bonding. Its ultralow lattice thermal conductivity (< 0.38 W mK⁻¹ at 300 K) is attributed to the broken phonon selection rule for phonon–phonon scattering and a high level of anharmonicity, as reflected in the large Grüneisen parameter. Furthermore, the inclusion …

Africa's Global Influence, Faez Al-Haq - Abidemi Salami

Masters Theses

This thesis believes in the design and production of an interactive kids' coloring book on Africa's extensive influence on world cultures, history, economies, and artistic heritage. In a bid to reverse centuries of misrepresentation and large-scale miseducation regarding Africa within early childhood textbooks, this work aims to design an interactive, kid-friendly guide that informs young readers about the central role Africa plays in today's world. Informed by thorough literature review and referencing case studies of successful education and culture intervention, the proposal positions Africa's global reach, spanning from its precolonial trading networks, philosophic structures, diaspora contributions, art heritage, and cultural …

Algorithmic Editors: Section 230, Big Tech, And The Need For Clarity, Richard Gruters

Seton Hall Law Review

No abstract provided.

Improving Mathematical Problem-Solving Performance Through The Use Of Reading Comprehension Strategies, Rebecca Yonan

Masters Projects

Research shows that math problem solving relies on more than arithmetic computation. Word problem solving is a combination of text comprehension and word memory. Being able to successfully solve word problems at the elementary level helps prepare students for algebra, and higher academics. Learning to solve word problems teaches students problem solving techniques that can be applied in their adult lives. This project creates an instructional routine where lessons are built around teaching primarily through word problem solving. Students will receive instruction on text comprehension, math vocabulary building, word memory, and arithmetic computation in order to simultaneously increase their math …

Butte Medical Monitoring Working Group Meeting, Mike Mcanulty, Eric Hassler

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Proposed Cryptographic Algorithm Based On Three-Pass Protocol And The Elliptic Curve Cryptography, Rifaat Z. Khalaf, Hamza B. Habib

Baghdad Science Journal

The internet lately has become an integral part of people’s lifestyles. It impacts various aspects of their daily lives, including education, communication, etc. Hence, the need for efficient and fast cryptography algorithms has increased. In this paper, a new cryptographic algorithm is proposed using the authenticated Three-Pass Protocol (TPP) and the Elliptic Curve Cryptography (ECC). In the proposed algorithm, the ECC is used to encrypt and decrypt data (a text of size 128 bits), and the TPP is used for transmitting this data without sharing the keys. In the standard ECC, the receiver publishes the elliptic curve (EC) equation, the …

Improving Energy And Capacity-Awareness Of Effective Satellite Communication In 6g Heterogeneous Internet Of Things, Ahmed Mahdi Jubair, Khitam Abdulbasit Mohammed, Fouad H. Awad

Baghdad Science Journal

The spreading of Sixth Generation (6G) communication within the Internet of Things (IoT) is one of the recent innovations in networking services. As the number of devices becomes increasingly connected through extensive communication network connectivity, energy efficiency has become a significant concern with the widespread use of massive IoT devices. While general lack of energy optimization can lead to several issues, including data loss, link failure, and high-power utilization, directly affect the communication quality of the network. To address these challenges, it is crucial to develop a model that combines effective optimization and resource allocation, based on both Quality of …

Methods For Radiation-Sparing Navigation In Endovascular And Spine Surgery, William Ross Warner

Dartmouth College Ph.D Dissertations

Modern surgical navigation systems improve procedural accuracy, limit complications, and can reduce reliance on intraoperative ionizing radiation, yet their adoption remains uneven across surgical domains. Informed by clinical immersion, this thesis identifies and addresses two unmet needs revealed through contrasting image-guidance practices in endovascular and spine surgery, where existing guidance techniques are costly, intermittent, or fundamentally limited. Specifically, these needs include (1) the absence of radiation-sparing navigation techniques for endovascular procedures, which rely heavily on 2D x-ray angiography, and (2) the need for dynamic registration methods in open spine surgery, where navigation accuracy can degrade after initial registration and intraoperative …

Design Of Nanomaterial-Based Sensors For Enhanced Halogen Bonding, Ben H. Edelman, Charles W. Sheppard, Lucas A. Chuidian, Arielle Vinnikov, Felix Bevc, Lillian B. Hughes, Carol A. Parish, Michael C. Leopold

Chemistry Faculty Publications

Halogen bonding is a highly directional, noncovalent, intermolecular interaction which has been harnessed for a variety of applications, including sensor design. A halogen bond (XB) is formed between a region of positive electrostatic potential on a halogen atom (X) and electron rich portions of target molecules. The strength of XB interactions relies on shorter XB bond distances and more linear R–X···B bond angles, which facilitate stronger, more negative binding energies. While prior studies have sought to maximize interactions, few have explored or experimentally demonstrated how geometries and bond angles can enhance XB interactions. Herein, fundamental studies are conducted at self-assembled …

The Relationship Between The Health Science Reasoning Test And Successful Completion Of An Associate Degree Nursing Program: A Retrospective Predictive Study, Joyce A.Ajkuce Kucerovy

Doctoral Dissertations and Projects

The purpose of this study was to retrospectively identify whether the addition of an entrance exam such as the Health Science Reasoning Test (HSRT) to the current admission criteria of an associate degree nursing (ADN) education program would aid in selecting students with the highest chance of successfully completing the program and entering the workforce. A nonexperimental, retrospective, quantitative, predictive correlational study design was used. A retrospective convenience sample of 320 first-year nursing students in an ADN education program was obtained. The G* power analysis showed a minimum sample size of 107 students was needed. Statistical analysis involved a multiple …

Truncated Exponentiated Ailamujia Exponential Distribution: Properties And Applications, Samer Abdulqader Salih, Dabya Mahmood Ali, Hind Khaled Kolaib, Alaa Abdulrahman Khalaf

Baghdad Science Journal

Probability distribution has shown its practicality in almost every area of human effort. This paper introduces a novel family of distributions called the [0, 1] Truncated Exponentiated Ailamujia-G family. The [0, 1] Truncated Exponentiated Ailamujia Exponential ([0, 1]TEAE) distribution, which is a sub-model of the recently created family, is completely constructed. The [0, 1]TEAE distribution is created by merging the [0, 1] Truncated and Exponentiated Ailamujia distributions. the mathematical features of the [0, 1]TEAE distribution, including moments, skewness, kurtosis, incomplete moments, renyi entropy, quantile function, and probability-weighted moments, are extensively examined. The quantiles for the chosen parameter values are clearly …

Distributed Model Predictive Control-Based Power Management Scheme For Grid-Integrated Microgrids, Sergio Escareno, Sijo Augustine, Liang Sun, Sathishkumar J. Ranade, Olga Lavrava, Enrico Pontelli, John Hedengren

Faculty Publications

Transitioning from traditional electrical grids to smart grids is currently an ongoing process that many nations are striving for due to their access to renewable resources. Energy management is one of the key parameters that decides the performance of such complex systems. Distributed Model Predictive Control (DMPC) is a promising technique that can be used to improve the energy management of grid-connected systems. This paper analyzes a grid-connected inverter system with DMPC that exchanges key operating parameters with the grid to optimize coordinated power sharing between its respective loads. The state-space model for the inverter is derived and verified to …