Digital Commons Network^™

A Bibliometric Analysis Of The Most Influential And Impactful Plastic Surgery Publications From Saudi Arabia, Hatan Mortada, Abdulaziz Alnufaei, Amal Tuaki Aljuaid, Zainab Ahmed Al Hubail, Waad Nawaf Alanazi, Abdulaziz Suleiman Jasaniah, Sarah Abdullah Ramzi, Amr Youssef Arkoubi

Saudi Medical Journal

Objective: To analyze the most cited plastic surgery articles from Saudi Arabia, focusing on publication trends, leading contributors, collaboration patterns, and thematic areas.

Methods: We conducted a bibliometric analysis using the Web of Science Core Collection (1990–2025). Keywords covering plastic surgery subfields were combined with geographic identifiers (“Saudi Arabia,” “KSA,” “Kingdom of Saudi Arabia”) using Boolean operators. Only English-language original and review articles were included. Citation metrics, authorship networks, and keyword co-occurrence were analyzed with VOSviewer and the bibliometrix R package.

Results: We identified 1,013 Saudi-affiliated plastic surgery publications, receiving 7,929 citations. The top 100 most-cited articles averaged 39.3 citations …

Bridging The Evidence Gap: A Retrospective Lens On Survival And Treatment Patterns In Older Patients With Colorectal Cancer, Emad M. Tashkandi

Saudi Medical Journal

Objectives: To advise evidence-based strategies and healthcare policies to optimize the management of older adults with colorectal cancer (CRC) in the region. Older adults are disproportionately affected by CRC but are underrepresented in clinical trials. Hence, real-world data are crucial in guiding treatment in this population.

Methods: We conducted a retrospective cohort study involving patients aged ≥65 years diagnosed with CRC between 2015 and 2021 at King Abdullah Medical City, Makkah, Saudi Arabia. Clinical data, treatment patterns, and survival outcomes were analyzed.

Results: Among 256 patients (mean age 74.7; 61.7% male), 75% had an Eastern Cooperative Oncology Group performance status …

Biomarkers Of Multiorgan Failure In Covid-19: A Predictive Framework For Disease Severity And Clinical Outcomes, Wesam A. Nasif, Mohammed H. Mukhtar, Mohammad Althubiti, Abeer Shaker El Moursy Ali

Saudi Medical Journal

Objective: To investigate the predictive value of inflammatory, liver, renal, and cardiac biomarkers in relation to the progression of multiorgan failure (MOF) in COVID-19 patients. A primary goal was to identify which of these markers served as the most discriminative predictors of disease severity.

Methods: A retrospective cohort study was carried out between December 2020 and February 2023 to collect data from 1,803 COVID-19 patients from data records in different hospitals in Makkah, Saudi Arabia. The ROC curve analysis evaluated the diagnostic and predictive performance of selected biomarkers.

Results: Inflammatory markers such as CRP and D-dimer were evaluated, but ferritin …

Role Of Artificial Intelligence In Infectious Diseases And Antimicrobial Resistance: A Comprehensive Review On Diagnostic, Treatment, And Prevention Aspects, Naveed Ahmed, Mansoor Alghamdi

Saudi Medical Journal

Artificial intelligence (AI) plays a significant role in managing infectious diseases by enhancing diagnosis, treatment, and preventive measures. AI-assisted tools have predictive analysis ability for incoming outbreaks, including the emergence of antimicrobial resistance (AMR). AI-assisted tools facilitate the treatment methods by tailoring personalized medicine according to the specific disease history of the patient, immune response, and genetics. Advanced vaccine development by various AI-assisted in silico tools is becoming easy, leading to faster vaccine discovery and more efficient vaccine design with a more immunogenic response. Despite huge benefits, a few limitations are also encountered, including biases in algorithms, data privacy, and …

Artificial Intelligence In Radiology: Hidden Fragilities And The Path To Resilience, Mustafa S. Alhasan

Saudi Medical Journal

Radiology artificial intelligence (AI) is advancing however its adoption faces fragile foundations that threaten sustainability. Despite bold promises of efficiency and accuracy, current deployment is undermined by weaknesses in economics, evidence, infrastructure, human factors, regulation, security, and environmental impact. Nearly 90% of radiology AI studies report process metrics rather than patient outcomes, while hidden costs elevate ownership to 400% to 500% of subscription fees. Technical fragilities include 25% or greater performance loss with routine protocol or scanner shifts, compounded by vendor consolidation that has eliminated 63% of companies since 2020, creating migration costs averaging 180,000 dollars per exit. Human factor …

Master Any Language 100x Faster, Yoshihiko Ariizumi

Learning, Teaching, & Researching Optimization

Learn any language 100x faster with this booklet of high-speed acquisition techniques!

Hyaluronan 35 Prevents Endotoxin-Mediated Dysregulated Skeletal Muscle Proteostasis During Ethanol Exposure, Nicole Welch, Pugazhendhi Kannan, Gangarao Davuluri, Annette Bellar, Amy H. Attaway, Saurabh Mishra, Jasmin A. Cunningham, Avinash Kumar, Ryan Musich, Elif G. Ertugral, Vandana Agrawal, Isaac L. Hu, Terri J. Hartford, Noah L. Weisleder, Vidula T. Vachharajani, Chandrasekhar R. Kothapalli

Chemical & Biomedical Engineering Faculty Publications

Sarcopenia in alcohol-related liver disease (ALD) is of high clinical significance, but there are no effective treatments. Hyaluronan 35 kDa (HA35), a glycosaminoglycan polymer, modulates responses to Toll-like receptor 4 (TLR4), a lipopolysaccharide receptor, to improve hepatic and macrophage function in ALD. We evaluated skeletal muscle responses to HA35 in preclinical models of ALD. Responses to ethanol, lipopolysaccharide (LPS), and HA35 were studied in differentiated murine C2C12/human-induced pluripotent stem cell (hiPSC)-derived myotubes, and wild-type/HA receptor CD44 knockout (CD44(-/-)) mouse models of ALD (mALD). Signaling molecules and measures of protein homeostasis (proteostasis) were quantified by immunoblots, mitochondrial oxidative function was determined …

Project Risk Management In Ai-Enabled Systems: Managing Ethical, Privacy, And Governance Risks, Onome Cynthia Anakanire

Harrisburg University Dissertations and Theses

This research examined how Artificial intelligence (AI) has been embedded in project-based work, particularly in finance and software industries, where it enables efficiency and assists in complex decision-making. However, these innovations introduce significant ethical, privacy, and governance risks that traditional project risk management frameworks fail to adequately address. This study investigated how project managers can systematically integrate the management of these emerging risks into AI-enabled projects. Using a qualitative research design, the study drew on semi-structured interviews with project managers, compliance officers, and AI developers in finance, software and related sectors. Supplementary data included internal project documentation and risk registers. …

Schwannomatosis Tumor Modeling: Progress And Prospects For Translational Research, Mackenzie S Madison, Huazhen Xu, Yarelis Gonzalez-Vargas, Marybeth G Yonk, Charee M Thompson, Hurley Haney, Danielle Babbitt, Yuhong Du, Angela C Hirbe, Nicholas M Boulis, Ren-Yuan Bai, Kecheng Lei

2020-Current year OA Pubs

BACKGROUND: Schwannomatosis (SWN) is a rare genetic condition characterized by the development of benign schwannomas along peripheral and spinal nerves, and this tumor development often results in chronic peripheral pain and significant neurological deficits. Despite surgical resection being the current standard of care for SWN-related pain, scientists are searching for accurate preclinical models that can be used for drug efficacy testing, but existing models often fail to fully recapitulate the complex genotypic diversity and tumor-nerve interface pathology seen in patients. MAIN TEXT: This review first summarizes the genotypic and phenotypic characteristics of SWN subtypes resulting from key mutations in NF2, …

Therapeutic Reprogramming Of Tumour-Associated Macrophages In Pancreatic Cancer Using A Cytotoxic Ccr2-Targeted Nanotheranostic, Vikas Kumar Somani, Xiaohui Zhang, Timothy Hung-Po Chen, Ashenafi Bulle, Sapana Bansod, Lin Li, Yutong Geng, Liang-I Kang, Gyu Seong Heo, Hannah Luehmann, Yuena Zhang, Muhammad A Saeed, Kory J Lavine, David G Denardo, Russell K Pachynski, Yongjian Liu, Kian-Huat Lim

2020-Current year OA Pubs

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) exhibits a profoundly immunosuppressive tumour microenvironment (TME) dominated by inflammatory monocytes (IMs) and tumour-associated macrophages (TAMs), which restrict adaptive immunity and drive resistance to immune checkpoint blockade (ICB). Recruitment of CCR2⁺ IMs by tumour-derived CCL2 is a central mechanism underlying TAM accumulation. Conventional gemcitabine (GEM) and small-molecule CCR2 inhibitors provide limited benefit due to poor intratumoural delivery, transient target engagement, and compensatory myeloid recruitment. METHODS: We engineered a CCR2-targeted nanotheranostic by conjugating a CCR2-binding peptide (ECL1i) and GEM onto ultrasmall copper nanoclusters (CuNCs-ECL1i-GEM; C-E-G). Therapeutic efficacy and immune remodelling were evaluated using orthotopic subcutaneous and …

The Impact Of Climate On Solar Panel Performance In Al-Madinah Al-Munawwarah, Mounira Matthas Al-Qahtani

UB Journal for Humanities

This study aims to identify the most important climatic elements that must be considered when designing solar panels in Al-Madinah Al-Munawwarah for the period 1995–2024, as well as the impact of monthly and annual climatic variations on the efficiency of solar panel performance. The study relies on the following climatic elements: annual radiation, temperature, relative humidity, wind, rainfall, and dust, in order to understand the relationship between climatic elements and the performance of solar panels. The study employed an analytical and applied methodology. The results indicate that Al-Madinah Al-Munawwarah enjoys high levels of solar radiation, with an overall average of …

Tailoring Cathode Structure And Materials To Enable Fast Charging And Extended Lifespan In Li-S Batteries, Yuxuan Zhang, Yeongjun Oh, Sunghwan Lee

Purdue Polytechnic Graduate Student Poster Symposium

The practical implementation of Li–S batteries is limited by sluggish sulfur redox kinetics and inefficient ion transport in high-mass-loading cathodes, challenges that are further exacerbated under fast-charging and high-power operation. Conventional electrocatalyst-based strategies can partially suppress electrochemical polarization by lowering reaction energy barriers, yet they do not address concentration and ohmic polarizations, which dominate in thick electrodes. Here, we introduce a coupled material–architecture design that integrates electrocatalysts into a low-tortuosity, correlated dual-gradient electrode fabricated using programmable high-resolution stereolithography and pyrolysis-induced carbonization. By deliberately pairing a microscale pore-size gradient with a corresponding active-material gradient, the electrode synchronizes redox progression across its …

Optimal Anchor Placement For Cable-Driven Parallel Robots On Curved Surfaces, Lei Jin, Dongming Gan, Tarek Taha

Purdue Polytechnic Graduate Student Poster Symposium

Cable-Driven Parallel Robots (CDPRs) are increasingly used for inspection and maintenance on large curved surfaces where traditional planar anchor layouts fail. This work introduces a unified geodesic–optimization framework for determining optimal anchor configurations that ensure both static feasibility and dynamic efficiency. The method first models curved surfaces using local tangent-plane coordinates to compute cable directions accurately, then evaluates anchor candidates through linear-programming tension optimization. Dynamic simulations along representative motion paths—spiral, circular, and zigzag—quantify total cable energy for ranking feasible configurations. Results show that anchors raised above mid-latitude and symmetrically distributed around the workspace minimize both peak tension and total energy …

Modification Of Copper-Based Catalysts With Conductive Polymers For Co2 Conversion With High C2+ Selectivity, Minyoung Kim, Dong Hun Lee, Reilly Eiynck, Meredith Zannacker, Reese Resheske, Sujat Sen, Sunghwan Lee

Purdue Polytechnic Graduate Student Poster Symposium

Carbon Dioxide (CO2) is abundant in our atmosphere, and its conversion to value-added using renewable electricity is currently an active area of investigation at both lab and commercial scale. Previous research has shown that copper-based catalysts can produce a wide range of hydrocarbons through the electrochemical reduction of CO2 under ambient conditions. Herein, we report on the modification of copper-based thin films as composite catalysts by depositing conductive polymers to improve the selectivity of CO2 conversion as well as surface stabilization. The copper layer was thermally evaporated onto PTFE substrates, showing a highly uniform film morphology and thickness with excellent …

Integrated Simulation Of Alloy Composition And Process Parameters For Fluidity Optimization In Hpdc Aluminum Alloys, Xin He, Xiaoming Wang

Purdue Polytechnic Graduate Student Poster Symposium

Fluidity is a critical factor in high-pressure die casting (HPDC) of aluminum alloys, directly influencing mold filling behavior, defect formation, and the mechanical reliability of cast components. This study employs multiphase computational fluid dynamics (CFD) simulations to investigate how alloy composition, process parameters, and die conditions collectively affect molten metal flow and solidification dynamics. Key variables include viscosity, thermal conductivity, solidification range, pouring temperature, injection velocity, die geometry, and preheating temperature. Alloys with a narrow solidification range and lower thermal conductivity exhibit prolonged liquid-phase duration, which enhances flowability and reduces the risk of cold shuts and porosity. In contrast, increased …

Function-Adaptive Hulls: Reconfigurable Building Material For Multipurpose Unmanned Vehicles, Yubing Han, Brittany Newell, Richard Voyles

Purdue Polytechnic Graduate Student Poster Symposium

This research presents a scalable building material for unmanned vehicles, inspired by origami principles and designed for adaptive functionality and stealth. Traditional fixed-shape vehicles face significant limitations in optimizing performance metrics such as velocity, payload capacity, and observability, often resulting in highly specialized designs that increase costs and resource consumption. To address the challenge, we introduce self-folding building material that incorporates pre-constructed creases, embedded actuation mechanisms, and location tags. The system utilizes electric rails organized on multiple levels, enabling switch modules to traverse internal channels and activate folding circuits with precision. A two-step folding process is demonstrated to reduce actuation …

From Outdoor Curiosity To Engineering Learning: Developing An Augmented Reality Module Grounded In Student Experiences, Mohammed Metwaly, Adel Elwakil, Selena Nadjarian, Farid El Breidi

Purdue Polytechnic Graduate Student Poster Symposium

Engineering education often overlooks the formative influence of outdoor experiences in shaping students’ curiosity about how things work. This study examines how such experiences contribute to students’ interest in engineering and demonstrates how those insights can inform experiential learning tools. A mixed-methods survey was administered to 189 Mechanical Engineering Technology undergraduates, yielding 150 complete responses. The instrument combined Likert-scale items and open-ended prompts to capture demographics, nature affinity, formative outdoor activities, and connections between those experiences and engineering interest. Reliability testing confirmed strong internal consistency (α = 0.854; ω = 0.751). Nearly half of respondents (47%) identified outdoor experiences as …

Edge Ai-Enabled Vagus Nerve Analysis For Adaptive Neuromodulation In Diabetes, Saeka Rahman, Reepa Saha, Md Motiur Rahman, Ardavan Vakil, Hope Teng, Muhammad Arafin Khan, Benjamin Larimer, Rita Basu, Andy Basu, Amy Warriner, Miad Faezipour, S. Abdollah Mirbozorgi

Purdue Polytechnic Graduate Student Poster Symposium

Comprehending the neural mechanisms underlying Type 2 Diabetes (T2D) is critical to developing next generation bioelectronic therapies. This work-in-progress presents a novel neural interface that integrates edge artificial intelligence (AI), machine learning (ML), and flexible implantable electronics to record, analyze, and modulate vagus nerve activity in real time for potential diabetes treatment and reversal. The proposed system combines low-power, semi-analog signal processing with embedded AI/ML algorithms capable of performing on-chip feature extraction and classification of neural signals under stringent power and communication constraints. By leveraging edge-based learning, the platform will enable adaptive neuromodulation of vagus nerve activity, providing a closed-loop …

Ai-Powered Pacifier With Intraoral Sound Analysis For Neonatal Pulmonary Monitoring, Shiva Shokouhmand, Md Motiur Rahman, Saeka Rahman, Indya Mooney, Guoliang Zhang, Smriti Bhatt, Namasivayam Ambalavanan, Colm P. Travers, S. Abdollah Mirbozorgi, Miad Faezipour

Purdue Polytechnic Graduate Student Poster Symposium

Respiratory monitoring in neonates remains a clinical challenge due to the limitations of existing pulmonary function assessment tools and the infant’s delicate physiology. This work-in-progress presents an artificial intelligence (AI)-driven framework for intraoral respiratory analysis using a smart pacifier platform that integrates acoustic sensing, embedded electronics, and deep learning. The proposed AI model is based upon a deep convolutional neural network that processes intraoral breathing sound reflections passively, or in presence of active sound stimuli. By learning complex temporal-spectral features from the breathing sound signals, the AI model will estimate key cardiorespiratory measures (e.g., respiratory rate, lung capacity) and the …

Adaptive Droop Control Gain Tuning Of Grid-Forming Inverters For Stability Enhancement Of Diesel-Plus-Battery Islanded Microgrids, Ram Shankar Yallamilli, Xiaonan Lu

Purdue Polytechnic Graduate Student Poster Symposium

This paper presents an adaptive gain tuning approach to enhance frequency stability in islanded microgrids consisting of diesel generators and grid-forming (GFM) inverters. Although GFM inverters provide voltage and frequency regulation capabilities, their interaction with diesel generators can introduce dynamic challenges such as reduced system inertia and frequency deviations during load transients. Existing studies have focused on small-signal modeling and damping methods but often overlook data-driven techniques for improving transient stability under varying diesel-to-GFM power ratios and inverter droop settings. To address this gap, this work investigates frequency stability behavior across different diesel and inverter power rating ratios and analyzes …

Assessing The Information Literacy Skills Of Faculty And Students In Using Open Educational Resources In Nigerian Universities, Adeniran Adetoro

Georgia International Conference on Information Literacy

Access to Open Educational Resources (OERs) by university libraries and through online sources is trending among academics and students in Nigeria, particularly given the emphasis on it by the National Universities commission in recent times. Extant literature points to low level of use of OERs among faculty and students, and there is an urgent need to understand the extent to which their information literacy (IL)skills can explain this and how IL drives OERs practical use for academic purposes. Thus, the paper investigates the perceived information literacy of faculty and graduate students in using open educational resources in federal universities in …

Teaching Ourselves Ai Literacy, Kelly Jones, Chandler Christoffel

Georgia International Conference on Information Literacy

To prepare to teach and support AI literacy, we organized an internal mini-conference for our Academic Engagement department. During each session, librarians taught one another various AI-related modules (e.g., ethics, prompt design, tools) as though leading a real class with students. We encouraged the use of active learning strategies and asked participants to submit session proposals in advance so we could offer feedback. This approach to professional development allowed us to rapidly test and refine our instructional methods and deepen our AI expertise. This mini-conference also helped us generate valuable content—including lessons, slides, assessments, and activities — for an AI …

Sienna Revisited, Sergio Pitol

Creative Nonfiction Magazine

No abstract provided.

Girl, Fighting, Laurie Lynn Drummond

Creative Nonfiction Magazine

No abstract provided.

The Generative Ai Game Is Afoot: A Workshop Series, Denise A. Wetzel, Elliott Rose

Georgia International Conference on Information Literacy

Generative artificial intelligence (AI) is transforming how we create, learn, and solve problems, making it essential for students to engage with these tools both skillfully and ethically. This presentation introduces “The Generative AI Game is Afoot,” a themed workshop series designed to explore generative AI through the lens of detective work inspired by Sherlock Holmes. Using the metaphor of digital sleuths and their trusted partners, the series invites participants to unravel the mysteries of generative AI with curiosity, critical thinking, and practical know-how.

The series consists of four interactive workshops followed by an open forum. The first workshop, "Writing Effective …

Cover To Cover: Reviews Of New Books

Creative Nonfiction Magazine

No abstract provided.

Bibliophilia, Laurie Graham

Creative Nonfiction Magazine

No abstract provided.

And So On And So Forth, Joyce Reiser Kornblatt

Creative Nonfiction Magazine

No abstract provided.

Why I Ride

Creative Nonfiction Magazine

No abstract provided.

Beyond The Buzzwords: Working With Faculty To Create Ai-Informed Personal Information Literacy Frameworks, Scott E. Shumate, Jenny Harris, Stephanie Bandel

Georgia International Conference on Information Literacy

Artificial Intelligence (AI) tools have become increasingly integrated into the classroom, requiring faculty across disciplines to reconsider how critical thinking skills are being impacted by AI. Academic libraries, long the centers of information access and literacy, are well positioned to confront the issues surrounding AI and address its influence on the wider information landscape. Three academic librarians have taken the lead at their university in encouraging faculty to be thoughtful and intentional about their own understanding of information literacy by developing a personal information literacy framework. This reflective process codifies the mental models all users create when interacting with information …