Digital Commons Network^™

Leveraging Ai And Big Data In Low-Resource Healthcare Settings, Ahmed Hussein Ali, Saad Ahmed Dheyab, Abdullah Hussein Alamoodi, Aws Abed Al Raheem Magableh, Yuantong Gu

Mesopotamian Journal of Big Data

Big data and artificial intelligence are game-changing technologies for the underdeveloped healthcare industry because they help optimize the entire supply chain and deliver more exact patient outcome information. Machine learning approaches that have recently seen more growing popularity include deep learning models that have brought revolution within the healthcare system in the previous years due to more complicated data compared to previous years . Machine learning is an essential data analysis procedure to describe efficient and effective methods to extract hidden information from large amounts of data that it would take logical analytics too long to manage. Recent years have …

Agent-Interacted Big Data-Driven Dynamic Cartoon Video Generator, Yasmin Makki Mohialden, Abbas Akram Khorsheed, Nadia Mahmood Hussien

Mesopotamian Journal of Big Data

This study presents a novel method for animating videos using three Kaggle cartoon faces data sets. Dynamic interactions between cartoon agents and random backgrounds, as well as Gaussian blur, rotation, and noise addition, make cartoon visuals look better. This approach also evaluates video quality and animation design by calculating the backdrop colour's average and standard deviation, ensuring visually appealing material. This technology uses massive datasets to generate attractive animated videos for entertainment, teaching, and marketing.

Generalized Time Domain Prediction Model For Motor Imagery-Based Wheelchair Movement Control, Z. T. Al-Qaysi, M. S. Suzani, Nazre Bin Abdul Rashid, Reem D. Ismail, M. A. Ahmed, Rasha A. Aljanabi, Veronica Gil-Costa

Mesopotamian Journal of Big Data

Brain-computer interface (BCI-MI)-based wheelchair control is, in principle, an appropriate method for completely paralyzed people with a healthy brain. In a BCI-based wheelchair control system, pattern recognition in terms of preprocessing, feature extraction, and classification plays a significant role in avoiding recognition errors, which can lead to the initiation of the wrong command that will put the user in unsafe condition. Therefore, this research's goal is to create a time-domain generic pattern recognition model (GPRM) of two-class EEG-MI signals for use in a wheelchair control system. This GPRM has the advantage of having a model that is applicable to unknown …

Mlp And Rbf Algorithms In Finance: Predicting And Classifying Stock Prices Amidst Economic Policy Uncertainty, Bushra Ali, Khder Alakkari, Mostafa Abotaleb, Maad M. Mijwil, Klodian Dhoska

Mesopotamian Journal of Big Data

In the realm of stock market prediction and classification, the use of machine learning algorithms has gained significant attention. In this study, we explore the application of Multilayer Perceptron (MLP) and Radial Basis Function (RBF) algorithms in predicting and classifying stock prices, specifically amidst economic policy uncertainty. Stock market fluctuations are greatly influenced by economic policies implemented by governments and central banks. These policies can create uncertainty and volatility, which in turn makes accurate predictions and classifications of stock prices more challenging. By leveraging MLP and RBF algorithms, we aim to develop models that can effectively navigate these uncertainties and …

Advanced Machine Learning Approaches For Enhanced Gdp Nowcasting In Syria Through Comprehensive Analysis Of Regularization Techniques, Khder Alakkari, Bushra Ali, Mostafa Abotaleb, Rana Ali Abttan, Pushan Kumar Dutta

Mesopotamian Journal of Big Data

This study addresses the challenge of nowcasting Gross Domestic Product (GDP) in data-scarce environments, with a focus on Syria, a country facing significant economic and political instability. Utilizing a dataset from 2010 to 2022, three machine learning algorithms Elastic Net, Ridge, and Lasso were applied to model GDP dynamics based on macroeconomic indicators, commodity prices, and high-frequency internet search data from Google Trends. Among these, the Lasso regression model, noted for its variable selection and sparsity promotion, proved most effective in capturing Syria's complex economic realities, achieving the lowest Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). …

Hybrid Model For Forecasting Temperature In Khartoum Based On Cru Data, Hussein Alkattan, Alhumaima Ali Subhi, Laith Farhan, Ghazwan Al-Mashhadani

Mesopotamian Journal of Big Data

This consider leverages verifiable climatic data from the Climatic Research Unit (CRU), traversing from 1901 to 2022, to create progressed temperature forecasting models for Khartoum, Sudan. By applying state-of-the-art machine learning techniques, including Hybrid model, we aim to progress the precision of temperature forecasts in a semi-arid climate. The integration of long-term CRU data permits for the recognizable proof of climate patterns and patterns, upgrading the unwavering quality of short- and long-term forecasts. Moved forward temperature forecasting can altogether advantage basic segments empowering way better adjustment to climatic changes and extraordinary climate occasions. Our approach illustrates the potential of combining …

Deep Learning Approaches For Gender Classification From Facial Images, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Reem D. Ismail, Z. T. Al-Qaysi, Fatimah N. Ameen

Mesopotamian Journal of Big Data

Gender recognition on the facial level is considered one of the most important technologies that finds use in such fields as a personalized marketing plan, safe systems of authentication, and effective human-computer interfaces. However, it has the following challenges; variation of lighting, facial movement, and ethnic/age face images. AI and DL has been improving on the effectiveness, flexibility, and speed of the gender classification system. AI enables complex and automatic feature learning in Data, while DL is tailored for handle variants in vision-based data. In this paper, we evaluated several architectures including Efficient Net_B2, ResNet50, ResNet18, and Lightning whilst determining …

Automated Water Quality Assessment Using Big Data Analytics, Yasmin Makki Mohialden, Nadia Mahmood Hussien, Saba Abdulbaqi Salman

Mesopotamian Journal of Big Data

Water is one of the world's most precious resources, essential to life. Industrial waste, agricultural runoff, and urban discharge degrade water, rendering it unfit for consumption. Water quality monitoring and evaluation are more important than ever. Big Data analytics is used to examine water quality utilizing enormous datasets of pH, hardness, solids concentration, chloramine, sulfate, conductivity, organic carbon, trihalomethanes, and turbidity. This work classifies water potability, which is vital for human consumption, using strong machine learning on massive datasets. Classifiers were Random Forest, Gradient Boosting, and Support Vector Machine on 3,276 water bodies. The Random Forest classifier obtained the highest …

Anomaly-Based Ids (Intrusion Detection System) For Cyber-Physical Systems, Ahmad Muter Awaad, Khattab M. Alheeti, Abdul Kream A.H. Najem

Mesopotamian Journal of Big Data

Cyber-physical systems (CPS) are critical infrastructures that integrate physical processes with computational components. The security of CPS is paramount, as any breach can lead to severe consequences. Anomaly-based intrusion detection systems (IDS) have emerged as a promising approach to safeguard CPS against cyber threats. This paper presents an anomaly-based IDS designed specifically for CPS, leveraging machine learning techniques to establish a baseline of normal system behaviour and promptly detect deviations indicative of malicious activities. The proposed system incorporates multiple classification techniques, including KNeighbors, RandomForest, XGB, DecisionTree, SGD, SVM, LGBM, AdaBoost, Bagging, and MLP Classifier, to enhance detection accuracy and robustness. …

Using Data Anonymization In Big Data Analytics Security And Privacy, Abdulatif Ali Hussain, Ismael Khaleel, Tahsien Al-Quraishi

Mesopotamian Journal of Big Data

Big Data and Analytics mean an enormous and complex collection of very diverse information, which is processed with various technologies and methods to produce and deliver useful and valuable insights. Analytics is the science of using data, or information to extract useful and actionable insights, facts and knowledge from a collection of data it could be stated that Big Data Analytics is the best thing since every commercial data system ever built, although everybody with a more optimistic vision of technology would like to take note that there is a fine line where Everything Data crosses the boundary to something …

Integrating Body Dysmorphic Disorder Screening Into Aesthetic Medicine Clinics, Michelle Andrus

Doctor of Nursing Practice Projects

As rates of elective cosmetic and dermatological procedures increase, it remains imperative for

aesthetic medicine providers to adequately screen potential patients for body dysmorphic

disorder (BDD). A psychiatric disorder, BDD presents when persons perceive flaws that are not

apparent to others, perform repetitive actions to examine and groom themselves which hinders

daily living activities, and require constant reassurance regarding their appearance. Literature

notes those with BDD seek elective cosmetic surgery at higher rates than the general population

resulting in poor satisfaction and outcomes. Cosmetic Procedure Screening (COPS) is a validated

screening tool for BDD and this quality improvement project sought …

Health Sciences Students’ Career Commitment, Mental Health, And Physical Activity During The Covid-19 Pandemic, David Wrucke, Marie K. Hoeger Bement, April L. Harkins, Sandra K. Hunter, Stacy Stolzman, Astrida S. Kaugars

Physical Therapy Faculty Research and Publications

Objective: To understand the biopsychosocial dimensions of university health sciences students’ experiences during the COVID-19 pandemic.

Participants: Health sciences students (n = 297) from two universities in July and August 2020.

Methods: Participants completed a Web-based survey asking about depression, anxiety, physical activity, coronavirus threat, and career commitment.

Results: Moderate or severe depression and anxiety were reported by 28.6% and 31.3% of respondents, respectively. Depression and anxiety were positively correlated with perceived coronavirus threat and negatively correlated with career commitment and strenuous physical activity. A change in career commitment interests during the COVID-19 pandemic was reported by 11% of …

Activity Levels Across The Intensity Spectrum In Athletes: A Systematic Review Protocol, Jacob J. Capin, Jena Heck Street, Alissa V. Fial, Nicola D. Ridgers, Grant R. Tomkinson

Physical Therapy Faculty Research and Publications

Physical activity (PA) promotes better cardiometabolic health, physical function, brain health and longevity. In contrast, prolonged sedentary behaviour (SB) is a risk factor for many chronic diseases and poor health. Limited research has evaluated or synthesised how competitive sports participation influences PA across the lifespan. Some evidence suggests, ironically, that former competitive athletes may be insufficiently active and current athletes may be highly sedentary away from sport. This study describes the protocol for a systematic review and meta-analysis on activity levels across the intensity spectrum in athletes, addressing the primary research question: is sports participation significantly associated with PA and/or …

Midlife Health Crisis Of Former Competitive Athletes: Dissecting Their Experiences Via Qualitative Study, Jacob J. Capin, Taylor Wolf, Jena Heck Street, Carolyn S. Smith, Shannon L. Lennon, William B. Farquhar, Sandra K. Hunter, Linda B. Piacentine

Physical Therapy Faculty Research and Publications

Sports participation confers many health benefits yet greatly increases injury risk. Long-term health outcomes in former athletes and transition to life after competitive sports are understudied. Ending a sport may pose physical and psychosocial challenges. The purpose was to determine the lived experiences of former competitive athletes and how their sports participation impacted their long-term health and well-being. Former college varsity athletes participated in semistructured interviews focusing on their experiences, including past and current health, the impact of injuries, activity, exercise, diet and transition to life after competitive sport. Thematic analysis was completed using a collaborative, iterative process. Thirty-one (16 …

Age-Related Development Of Bilateral Coordination Of The Upper Limbs In Children And Adolescents, Samuel Nemanich, Sheila M. Schindler-Ivens

Physical Therapy Faculty Research and Publications

Bilateral coordination of the upper limbs (UL) is important for activities of daily living and physical activities. Motor coordination improves from childhood through adolescence. However, age-coordination trajectories for bilateral UL movements are not well-established, and it is unclear if bimanual coordination develops slower than unilateral coordination. In this study we examined age-related changes in UL coordination from childhood to late adolescence. Typically-developing children (N = 29, aged 7–17 years) performed unilateral and bilateral, antiphase cycling tasks with their ULs. Variations in cycling velocity and interlimb phase errors were computed as measures of coordination. Linear regression was used to examine …

The Effects Of Attentional Focus Instructions On Approach Jump Performance, Hanwen Liu, Scott Arnett, Dano Tolusso, Kaylee Woodard

Physical Therapy Faculty Research and Publications

Introduction

Attentional focus has been shown to significantly influence motor learning and performance, with external focus instructions enhancing performance compared to internal focus instructions. Research has also demonstrated that novice performance is improved when instructed to focus on skill execution processes rather than outcomes. However, this effect remains untested in complex jumping skills crucial to numerous sports.

Purpose

This study aimed to investigate the effect of internally and externally directed process and outcome focus instructions on approach jump height and approach speed in novice participants.

Methods

Twelve individuals aged 18 to 22 participated across three sessions: Familiarization, Test Session 1, …

Making The Most Of Sushi In Alma: Tips For Smooth Maintenance And Reporting, Marie Day, Laura Beane

Faculty Articles

SUSHI is a widely used protocol in academic libraries. This article discusses maintaining SUSHI vendor accounts in Alma, troubleshooting irregularities, and finding technical support. This article also includes sample analyses for the ACRL survey 60B Digital/Electronic Circulation or Usage and 63 E-serials Usage using COUNTER 5 reports.

Empirically Assessing 510(K) Device Safety, George Horvath

Akron Law Faculty Publications

Innovations in medical device technology hold the potential to improve health outcomes across the populace. Nearly half of all medical devices that enter the U.S. market each year are regulated by the Food and Drug Administration (FDA) under the 510(k) pathway. If FDA regulation of 510(k) devices stifles innovation, health outcomes will suffer over time because beneficial devices would not reach patients; on the other hand, if regulation facilitates innovation, health outcomes could improve. Most discussions of innovation under the 510(k) pathway have been either excessively reductionist (such as claims that the pathway stifles innovation) or wholly pessimistic (notably, the …

The Patent Law Origins Of Science Fiction, Camilla Hrdy, Daniel H. Brean

Akron Law Faculty Publications

This Article reveals the surprising role of patent law in shaping the literary genre of science fiction. Drawing on previously unpublished sources, the Article shows that Hugo Gernsback—the so-called “father” of science fiction who started the first all-science-fiction magazine in 1926—believed that works of science fiction are analogous to patents. Like patents, science fiction stories can disclose useful information to the public about new inventions. Like patents, science fiction stories can influence future inventors and drive innovation. Gernsback went even further, positing that some of the inventions depicted in science fiction should themselves be patentable. In 1952, he urged Congress …

Gut Pathobiont Enrichment Observed In A Population Predisposed To Dementia, Type 2 Diabetics Of Mexican Descent Living In South Texas, Lisa M Matz, Nisarg S Shah, Laura Porterfield, Olivia M Stuyck, Michael D Jochum, Rakez Kayed, Giulio Taglialatela, Randall J Urban, Shelly A Buffington

Faculty, Staff and Students Publications

Type 2 diabetes (T2D) is a common forerunner of neurodegeneration and accompanying dementia, including Alzheimer's Disease (AD), yet the mechanisms underlying this comorbidity remain unresolved. Individuals of Mexican descent living in South Texas have increased prevalence of comorbid T2D and early onset AD, despite low incidence of the APOE-ε4 risk variant among the population and an absence of a similar predisposition among relatives residing in Mexico - suggesting a role for environmental factors in coincident T2D and AD susceptibility. We therefore sought to test if differences in gut community structure could be observed in this population prior to any AD …

Posttransplantation Late Complications Increase Over Time For Patients With Scid: A Primary Immune Deficiency Treatment Consortium (Pidtc) Landmark Study, Hesham Eissa, Monica S Thakar, Ami J Shah, Brent R Logan, Linda M Griffith, Huaying Dong, Roberta E Parrott, Richard J O'Reilly, Jasmeen Dara, Neena Kapoor, Lisa Forbes Satter, Sharat Chandra, Malika Kapadia, Shanmuganathan Chandrakasan, Alan Knutsen, Soma C Jyonouchi, Lyndsay Molinari, Ahmad Rayes, Christen L Ebens, Pierre Teira, Blachy J Dávila Saldaña, Lauri M Burroughs, Sonali Chaudhury, Deepak Chellapandian, Alfred P Gillio, Fredrick Goldman, Harry L Malech, Kenneth Desantes, Geoff D E Cuvelier, Jacob Rozmus, Ralph Quinones, Lolie C Yu, Larisa Broglie, Victor Aquino, Evan Shereck, Theodore B Moore, Mark T Vander Lugt, Talal I Mousallem, Joeseph H Oved, Morna Dorsey, Hisham Abdel-Azim, Caridad Martinez, Jacob H Bleesing, Susan Prockop, Donald B Kohn, Jeffrey J Bednarski, Jennifer Leiding, Rebecca A Marsh, Troy Torgerson, Luigi D Notarangelo, Sung-Yun Pai, Michael A Pulsipher, Jennifer M Puck, Christopher C Dvorak, Elie Haddad, Rebecca H Buckley, Morton J Cowan, Jennifer Heimall

Faculty, Staff and Students Publications

Background: The Primary Immune Deficiency Treatment Consortium (PIDTC) enrolled children in the United States and Canada onto a retrospective multicenter natural history study of hematopoietic cell transplantation (HCT).

Objective: We investigated outcomes of HCT for severe combined immunodeficiency (SCID).

Methods: We evaluated the chronic and late effects (CLE) after HCT for SCID in 399 patients transplanted from 1982 to 2012 at 32 PIDTC centers. Eligibility criteria included survival to at least 2 years after HCT without need for subsequent cellular therapy. CLE were defined as either conditions present at any time before 2 years from HCT that remained unresolved (chronic), …

Cutting Edge Of Genetically Modified Pigs Targeting Complement Activation For Xenotransplantation, Qin Sun, Si-Yuan Song, Jiabao Ma, Danni Li, Yiping Wang, Zhengteng Yang, Yi Wang

Faculty, Staff and Students Publications

In the quest to address the critical shortage of donor organs for transplantation, xenotransplantation stands out as a promising solution, offering a more abundant supply of donor organs. Yet, its widespread clinical adoption remains hindered by significant challenges, chief among them being immunological rejection. Central to this issue is the role of the complement system, an essential component of innate immunity that frequently triggers acute and chronic rejection through hyperacute immune responses. Such responses can rapidly lead to transplant embolism, compromising the function of the transplanted organ and ultimately causing graft failure. This review delves into three key areas of …

Fam20a: A Potential Diagnostic Biomarker For Lung Squamous Cell Carcinoma, Yalin Zhang, Qin Sun, Yangbo Liang, Xian Yang, Hailian Wang, Siyuan Song, Yi Wang, Yong Feng

Faculty, Staff and Students Publications

Background: Lung squamous cell carcinoma (LUSC) ranks among the carcinomas with the highest incidence and dismal survival rates, suffering from a lack of effective therapeutic strategies. Consequently, biomarkers facilitating early diagnosis of LUSC could significantly enhance patient survival. This study aims to identify novel biomarkers for LUSC.

Methods: Utilizing the TCGA, GTEx, and CGGA databases, we focused on the gene encoding Family with Sequence Similarity 20, Member A (FAM20A) across various cancers. We then corroborated these bioinformatic predictions with clinical samples. A range of analytical tools, including Kaplan-Meier, MethSurv database, Wilcoxon rank-sum, Kruskal-Wallis tests, Gene Set Enrichment Analysis, …

Liver Directed Adeno-Associated Viral Vectors To Treat Metabolic Disease, Marcel A Chuecos, William R Lagor

Faculty, Staff and Students Publications

The liver is the metabolic center of the body and an ideal target for gene therapy of inherited metabolic disorders (IMDs). Adeno-associated viral (AAV) vectors can deliver transgenes to the liver with high efficiency and specificity and a favorable safety profile. Recombinant AAV vectors contain only the transgene cassette, and their payload is converted to non-integrating circular double-stranded DNA episomes, which can provide stable expression from months to years. Insights from cellular studies and preclinical animal models have provided valuable information about AAV capsid serotypes with a high liver tropism. These vectors have been applied successfully in the clinic, particularly …

Editorial: Epilepsy And Alzheimer’S Disease: Shared Pathology, Clinical Presentations, And Targets For Treatment, Beth Leeman-Markowski, Jeannie Chin, Dominique Leitner, Keith Vossel

Faculty, Staff and Students Publications

No abstract provided.

Editorial: Symmetry As A Guiding Principle In Artificial And Brain Neural Networks, Volume Ii, Fabio Anselmi, Ankit B Patel

Faculty, Staff and Students Publications

No abstract provided.

It Is Time To Screen For Homozygous Familial Hypercholesterolemia In The United States, Samuel S Gidding, Christie M Ballantyne, Marina Cuchel, Sarah De Ferranti, Lisa Hudgins, Allison Jamison, Mary P Mcgowan, Amy L Peterson, Robert D Steiner, Melissa K Uveges, Yunshu Wang

Faculty, Staff and Students Publications

Homozygous familial hypercholesterolemia (HoFH) is an ultra-rare inherited condition that affects approximately one in 300,000 people. The disorder is characterized by extremely high, life-threatening levels of low-density lipoprotein (LDL) cholesterol from birth, leading to significant premature cardiovascular morbidity and mortality, if left untreated.

Homozygous familial hypercholesterolemia is severely underdiagnosed and undertreated in the United States (US), despite guidelines recommendations for universal pediatric lipid screening in children aged 9–11. Early diagnosis and adequate treatment are critical in averting premature cardiovascular disease in individuals affected by HoFH. Yet, an unacceptably high number of people living with HoFH remain undiagnosed, misdiagnosed, and/or receive …

Editorial: Sex Differences In Cancer Incidence, Mortality, And Survival: Methodological Perspectives, Syed Ahsan Raza, Wilson Luiz Da Costa, Aaron P Thrift

Faculty, Staff and Students Publications

No abstract provided.

Adolescent/Young Adult Self-Management And Independence Self-Report Scale: Preliminary Psychometric Findings, Monique M Ridosh, Zoe Smith, William Adams, Timothy J Brei, Ellen Fremion, Grayson N Holmbeck, Audrey J Roach, Kathleen J Sawin, Eileen Sherburne

Faculty, Staff and Students Publications

Purpose: This study examined preliminary psychometrics of the Adolescent/Young Adult Self-Management and Independence Self-Report Scale (AMIS II SR).

Methods: Adolescents and adults (N = 159; 13-38 years old) with spina bifida from two clinics and one community sample completed the AMIS II SR. The majority (83%) had myelomeningocele, and about half were female (51.6%). The sample included 44.7% White, 11.3% Black and over one-third Hispanic/Latino (38.4%) participants. Descriptive analyses and reliability were assessed; a confirmatory factor analysis (CFA) was conducted.

Results: Item-to-total correlations support the AMIS II SR total scale (r = .38-.79) and its two subscales: condition (r = …

Triiodothyronine Acts On Dao To Regulate Pulmonary Fibrosis Progression By Facilitating Cell Senescence Through The P53/P21 Signaling Pathway, Xiaoshu Guo, Kai Xu, Lan Wang, Linke Ding, Wenwen Li, Xinsheng Zhang, Weiming Zhao, Ningdan Wang, Gaiping Wang, Wenyu Zhao, Ivan Rosas, Guoying Yu

Faculty, Staff and Students Publications

Background: Idiopathic pulmonary fibrosis (IPF) is the result of multiple cycles of epithelial cell injury and fibroblast activation; currently, there is no clear etiology. Increasing evidence suggests that protein metabolism and amino acids play a crucial role in IPF, but the role of D-amino acids is not yet clear. The aim of this study was to identify novel mediators in order to test the hypothesis that D-amino acid oxidase (DAO) plays a significant role in the pathogenesis of IPF.

Methods: We analyzed DAO gene expression in patients with IPF and mice with bleomycin (BLM)-induced lung fibrosis. We performed in vitro …