Digital Commons Network^™

Sociosexual Orientation And Dark Triad Personality Traits Impact On Deception In Relationships, Kristin Lena

Murray State Theses and Dissertations

Within the last 10 years, research has suggested that it has become more common for individuals to engage in casual sex. Research has consistently shown that sociosexual orientation, dark triad traits, and deception are all related. This study sought to examine the linear relationship between sociosexual orientation, dark triad personality characteristics, and the use of deception in a relationship. Participants (n = 135) completed this study online and were recruited from a midsize university. Findings did suggest a positive correlation between sociosexuality and deception, as well as a positive correlation between dark triad traits and deception. The findings of …

The Impact Of Instructional Coaching In K-12 Education, Angela Michelle Hickey

Murray State Theses and Dissertations

This study aimed to examine the various aspects of instructional coaching in educational environments and offer a thorough understanding of the impact on teacher growth in a small, rural school district with 90 certified teachers and four district instructional coaches. The study used a quantitative approach that utilizes pre-post assessments to gauge the influence of instructional coaching on many aspects of teacher development, such as high-impact instructional practices, classroom management, and overall pedagogical effectiveness. Statistical studies will identify any significant changes over time and investigate potential links between coaching variables and teacher outcomes. This research aims to comprehensively understand how …

Perceptions Of Benefits From Middle School Agricultural Education Programs, Michael Hunter

Murray State Theses and Dissertations

As agriculture education continues to evolve across the state of Georgia and the country, leaders need to understand the dynamic vision and the importance of this industry. Utilizing P-20 education initiatives and new concepts, leaders can implement agriculture education in more schools to increase diversity and provide students with opportunities to participate in the three-component model of agriculture education. This research aimed to explore the perceived benefits that high school principals, CTAE directors, and agriculture teachers have on middle school agriculture education programs. This research was confined to the Georgia FFA North Region. Findings indicated no significant evidence that middle …

A Comparison Of Student Achievement On Agriculture Mechanics End Of Pathway Assessments Among Agriculture Programs In Georgia, William Burt

Murray State Theses and Dissertations

Agriculture education programs in Georgia are held to the same standards and evaluations regardless of their location, resource availability, and student clientele. For schools with agriculture mechanics programs specifically, students are expected to obtain proficient skills in welding, electrical wiring, woodworking, small engines, concrete, and machinery. Students' are expected to obtain skill sets in these various content areas, yet the equipment and resources available to the educator differs among schools. The experience that a student encounters also differs among schools. For instance, some schools have multiple agriculture pathways for a student to enroll in, while other schools have minimal. The …

Take My Perspective, Please: Perspective Taking’S Impact On Insecure Attachment And Phubbing, Connor Brown

Murray State Theses and Dissertations

Phubbing is defined as the act of ignoring another individual (e.g., significant others, friends) by devoting attention to one's phone (Chotpitayasunondh & Douglas, 2018). Previous literature indicates that insecurely attached (anxious and avoidant) individuals are more likely to phub than others (Sun & Miller, 2023a). This study examined correlations between attachment styles and phubbing, finding that avoidant attachment was not significantly correlated with phubbing, while anxious attachment was. As well as examining the correlation between phubbing and perspective taking, results indicate that there was not a significant correlation. The primary interest of this study sought to investigate perspective taking as …

Assessing The Transformative Influence Of Chatgpt On Research Practices Among Scholars In Pakistan, Nayab Arshad, Mehran Ullah Baber, Adnan Ullah

Mesopotamian Journal of Big Data

This article investigates the transformative impact of ChatGPT on research practices within the scholarly community in Pakistan. ChatGPT, a powerful AI language model, has added significant consideration for its possibility of improving academic research. Survey data was gathered via a structured questionnaire distributed to researchers in Pakistan. A total of 278 questionnaires were distributed for the randomly chosen sample, of which 223 were returned. For calculating descriptive statistics, SPSS was utilized.  Results of the study indicated that 90% of scholars are familiar with the practice of ChatGPT in research activities. 86% of scholars used 3.5 (Basic version) of ChatGPT for …

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 …

Face Morphing Attacks Detection Approaches: A Review, Essa Mokna Namis, Khalid Shakir Jasim, Sufyan Al-Janabi

Mesopotamian Journal of Big Data

Face recognition systems (FRSs) that are applied by real-time applications such as border control are vulnerable to attacks such as face morphing, which blends two or more facial images into a single morphed image. The vulnerability of FRSs to many types of attacks, including both direct and indirect attacks, as well as face-morphing attacks, has garnered significant attention from the biometric field. A morphing attack aims to undermine the security of an FRS at an automated border control (ABC) gate by using an electronic machine-readable travel document (eMRTD) or e-passport that is acquired using a morphed face image. Most countries …

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). …

Harnessing The Potential Of Artificial Intelligence In Managing Viral Hepatitis, Guma Ali, Maad M. Mijwil, Ioannis Adamopoulos, Bosco Apparatus Buruga, Murat Gök, Malik Sallam

Mesopotamian Journal of Big Data

Viral hepatitis continues to be a serious global health concern, impacting millions of people, putting a strain on healthcare systems across the world, and causing significant morbidity and mortality. Traditional diagnostic, prognostic, and therapeutic procedures to address viral hepatitis are successful but have limits in accuracy, speed, and accessibility. Artificial intelligence (AI) advancement provides substantial opportunities to overcome these challenges. This study investigates the role of AI in revolutionizing viral hepatitis care, from early detection to therapy optimization and epidemiological surveillance. A comprehensive literature review was conducted using predefined keywords in the Nature, PLOS ONE, PubMed, Frontiers, Wiley Online Library, …

A Framework For Automated Big Data Analytics In Cybersecurity Threat Detection, Mohamed Ariff Ameedeen, Rula A. Hamid, Theyazn H. Aldhyani, Laith Abdul Khaliq Al-Nassr, Sunday Olusanya Olatunji, Priyavahani Subramanian

Mesopotamian Journal of Big Data

This research presents a novel framework designed to enhance cybersecurity through the integration of Big Data analytics, addressing the critical need for scalable and real-time threat detection in large-scale environments. Utilizing technologies such as Apache Kafka for efficient data ingestion, Apache Flink for stream processing, and advanced machine learning models like LSTM and Autoencoders, the framework offers robust anomaly detection capabilities. It also includes automated response mechanisms using SOAR and XDR systems, significantly improving response times and accuracy in threat mitigation. The proposed solution not only addresses current challenges in handling vast and complex data but also paves the way …

Hybrid Spotted Hyena Based Load Balancing Algorithm (Hshlb), Raed A. Hasan, Mustafa M. Akawee, Enas F. Aziz, Omar A. Hammood, Aws Saad Showket, Husniyah Jasim, Mohammed A. Alkhafaji, Omar K. Ahmed, Khalil Yasin

Mesopotamian Journal of Big Data

In this paper, we delve into the core of our proposed dynamic load balancing mechanism, the Hybrid Spotted Hyena based Load Balancing algorithm (HSHLB). We begin by presenting a comprehensive overview of the Spotted Hyena Optimization Algorithm (SHOA) and the fundamental behaviors it encompasses, namely migration and attacking. We then introduce the Load Balancing Algorithm (LB) and outline its principles, emphasizing its distinct characteristics. Recognizing the strengths and weaknesses of both SHOA and LB, we embark on a journey to hybridize these two optimization techniques, resulting in the potent HSHLB. We elucidate the intricate process of combining these algorithms, elucidating …

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. …

Dna Barcoding Reveals A New Population Of The Threatened Atlantic Forest Frog Sphaenorhynchus Canga, Diego J. Santana, Andre Yves, Elvis A. Pereira, Priscila S. Carvalho, Lucio M. C. Lima, Henrique C. Costa, Don Shepard

Biological Sciences Faculty Publications and Presentations

Species identification plays a significant role in biodiversity conservation. As many species remain unrecognized, particularly in neotropical hotspots like the Brazilian Atlantic Forest (AF), novel molecular techniques are being widely employed to bridge this gap. In this study, we used DNA barcoding and phylogenetic tools to identify a new population of Sphaenorynchus canga in the central region of the Brazilian AF. Our results extend the species’ known distribution by approximately 200 km to the south, encompassing a different mountain range than its type locality (Serra do Espinhaço). This disjunct distribution, while not uncommon among amphibians, suggests a historical connection between …

Non-Invasive Auricular Vagus Nerve Stimulation For Subarachnoid Hemorrhage (Navsah): Protocol For A Prospective, Triple-Blinded, Randomized Controlled Trial, Anna Huguenard, Gansheng Tan, Gabrielle Johnson, Markus Adamek, Andrew Coxon, Terrance Kummer, Joshua Osbun, Ananth Vellimana, David Limbrick, Gregory Zipfel, Peter Brunner, Eric Leuthardt

2020-Current year OA Pubs

BACKGROUND: Inflammation has been implicated in driving the morbidity associated with subarachnoid hemorrhage (SAH). Despite understanding the important role of inflammation in morbidity following SAH, there is no current effective way to modulate this deleterious response. There is a critical need for a novel approach to immunomodulation that can be safely, rapidly, and effectively deployed in SAH patients. Vagus nerve stimulation (VNS) provides a non-pharmacologic approach to immunomodulation, with prior studies demonstrating VNS can reduce systemic inflammatory markers, and VNS has had early success treating inflammatory conditions such as arthritis, sepsis, and inflammatory bowel diseases. The aim of the Non-invasive …

Disruption Of The Nascent Polypeptide-Associated Complex Leads To Reduced Polyglutamine Aggregation And Toxicity, Leeran B. Dublin-Ryan, Ankan K. Bhadra, Heather L. True

2020-Current year OA Pubs

The nascent polypeptide-associate complex (NAC) is a heterodimeric chaperone complex that binds near the ribosome exit tunnel and is the first point of chaperone contact for newly synthesized proteins. Deletion of the NAC induces embryonic lethality in many multi-cellular organisms. Previous work has shown that the deletion of the NAC rescues cells from prion-induced cytotoxicity. This counterintuitive result led us to hypothesize that NAC disruption would improve viability in cells expressing human misfolding proteins. Here, we show that NAC disruption improves viability in cells expressing expanded polyglutamine and also leads to delayed and reduced aggregation of expanded polyglutamine and changes …

Graceful Gait: Virtual Ballet Classes Improve Mobility And Reduce Falls More Than Wellness Classes For Older Women, Elinor C Harrison, Allison M Haussler, Lauren E Tueth, Sidney T Baudendistel, Gammon M Earhart

2020-Current year OA Pubs

INTRODUCTION: Dance is an effective and motivating form of exercise for older women, but few studies have quantified the benefits of virtual dance classes nor, specifically, ballet. This study tested the effectiveness of virtual ballet compared to virtual wellness classes, with the goal of reaching underserved populations. It is among the first to explore the effects of virtual classical ballet on functional gait mobility, balance, and quality of life measures in older women.

METHODS: Older women were recruited in two waves and randomized to two groups: a ballet class modified for older adults and a wellness-based control class. Both groups …

Mapping Of A Hybrid Insulin Peptide In The Inflamed Islet Β-Cells From Nod Mice, Janet M Wenzlau, Orion J Peterson, Anthony N Vomund, James E Dilisio, Anita Hohenstein, Kathryn Haskins, Xiaoxiao Wan

2020-Current year OA Pubs

There is accumulating evidence that pathogenic T cells in T1D recognize epitopes formed by post-translational modifications of β-cell antigens, including hybrid insulin peptides (HIPs). The ligands for several CD4 T-cell clones derived from the NOD mouse are HIPs composed of a fragment of proinsulin joined to peptides from endogenous β-cell granule proteins. The diabetogenic T-cell clone BDC-6.9 reacts to a fragment of C-peptide fused to a cleavage product of pro-islet amyloid polypeptide (6.9HIP). In this study, we used a monoclonal antibody (MAb) to the 6.9HIP to determine when and where HIP antigens are present in NOD islets during disease progression …

Referent Data For Investigations Of Upper Limb Accelerometry: Harmonized Data From Three Cohorts Of Typically-Developing Children, Catherine E Lang, Catherine R Hoyt, Jeffrey D Konrad, Kayla R Bell, Natasha Marrus, Marghuretta D Bland, Keith R Lohse, Allison E Miller

2020-Current year OA Pubs

AIM: The rise of wearable sensing technology shows promise for addressing the challenges of measuring motor behavior in pediatric populations. The current pediatric wearable sensing literature is highly variable with respect to the number of sensors used, sensor placement, wearing time, and how data extracted from the sensors are analyzed. Many studies derive conceptually similar variables via different calculation methods, making it hard to compare across studies and clinical populations. In hopes of moving the field forward, this report provides referent upper limb wearable sensor data from accelerometers on 25 variables in typically-developing children, ages 3-17 years.

METHODS: This is …

An Internet Mantram Repetition Program To Promote Well-Being In Breast Cancer Survivors: A Feasibility Randomized Controlled Trial, Jennifer M Hulett, An-Lin Cheng, Jill E Bormann, Allison B Anbari, Jane M Armer, Brooke M Hartman, B Ann Bettencourt, Leeanne B Sherwin, Edie L Sperling, Natsayakarn Narkthong, Carol Reinero, Hans Rindt, Kathy Schreiber, Lindsay L Peterson, Emily Albright

2020-Current year OA Pubs

No abstract provided.

Perspectives From Public Health Practitioners And Advocates On Community Development For Active Living: What Are The Lasting Impacts?, Natalicio Serrano, Laurel Schmidt, Amy A Eyler, Ross C Brownson

2020-Current year OA Pubs

PURPOSE: Evidence suggests differential impacts of community development, including gentrification and displacement. Public health practitioners and advocates are key stakeholders involved in the community development process related to active living, yet little is known about their perceptions of its impacts. We explored the perspectives of relevant leaders of public health departments and key community and advocacy organizations on community development, gentrification, and displacement.

APPROACH: Purposive key informant interviews.

SETTING: CDC State Physical Activity and Nutrition (SPAN) funding recipients.

PARTICIPANTS: CDC SPAN recipient leadership (n = 10 of 16) and advocacy organizations they partnered with (n = 7 of 16).

METHOD: …

Researching Covid To Enhance Recovery (Recover) Pediatric Study Protocol: Rationale, Objectives And Design, Rachel S Gross, Deanna M. Barch, Andrew C. Heath, Et Al.

2020-Current year OA Pubs

IMPORTANCE: The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or "Long COVID") in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults.

OBSERVATIONS: We describe the protocol for the Pediatric Observational Cohort Study of the NIH's REsearching COVID to Enhance Recovery (RECOVER) Initiative. RECOVER-Pediatrics is an observational meta-cohort study of caregiver-child pairs (birth through 17 years) and young adults (18 through 25 years), recruited from more than 100 sites across the US. This report focuses on two of …

Sillyputty: Improved Clustering By Optimizing The Silhouette Width, Polina Bombina, Dwayne Tally, Zachary B. Abrams, Kevin R. Coombes

2020-Current year OA Pubs

Clustering is an important task in biomedical science, and it is widely believed that different data sets are best clustered using different algorithms. When choosing between clustering algorithms on the same data set, reseachers typically rely on global measures of quality, such as the mean silhouette width, and overlook the fine details of clustering. However, the silhouette width actually computes scores that describe how well each individual element is clustered. Inspired by this observation, we developed a novel clustering method, called SillyPutty. Unlike existing methods, SillyPutty uses the silhouette width for individual elements as a tool to optimize the mean …

Using Information Technology For Comprehensive Analysis And Prediction In Forensic Evidence, Faris Kamil Hasan Mihna, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Yasir Hussein Ali, Yasir Hussein Ali

Mesopotamian Journal of CyberSecurity

With the escalation of cybercriminal activities, the demand for forensic investigations into these crimes has grown significantly. However, the concept of systematic pre-preparation for potential forensic examinations during the software design phase, known as forensic readiness, has only recently gained attention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous and precise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence (AI) technologies. This research amalgamates diverse datasets encompassing crime history, various socio-economic indicators, and geographical locations to attain a comprehensive understanding of how crimes manifest within the city. Leveraging …

Social Relationships, Amyloid Burden, And Dementia: The Aric-Pet Study, Renée C Groechel, Albert C Liu, Chelsea Liu, David S Knopman, Silvia Koton, Anna M Kucharska-Newton, Pamela L Lutsey, Thomas H Mosley, Priya Palta, A Richey Sharrett, Keenan A Walker, Dean F Wong, Rebecca F Gottesman

2020-Current year OA Pubs

INTRODUCTION: This study aimed to assess whether social relationships in mid-life reduce the risk of dementia related to amyloid burden.

METHODS: Participants in the Atherosclerosis Risk in Communities (ARIC) study were assessed for social support and isolation (visit 2; 1990-1992). A composite measure, "social relationships," was generated. Brain amyloid was evaluated with florbetapir positron emission tomography (PET); (visit 5; 2012-2014). Incident dementia cases were identified following visit 5 through 2019 using ongoing surveillance. Relative contributions of mid-life social relationships and elevated brain amyloid to incident dementia were evaluated with Cox regression models.

RESULTS: Among 310 participants without dementia, strong mid-life …

Hippocampal Volumes In Uk Biobank Are Associated With Apoe Only In Older Adults, Ariya Chaloemtoem, Vera Thornton, Yoonhoo Chang, Andrey P Anokhin, Michaël E Belloy, Janine Bijsterbosch, Brian A Gordon, Sarah M Hartz, Laura J Bierut

2020-Current year OA Pubs

INTRODUCTION: The hippocampus atrophies with age and is implicated in neurodegenerative disorders including Alzheimer's disease (AD). We examined the interplay between age and apolipoprotein E (

METHODS: Using neuroimaging data from 37,463 UK Biobank participants, we applied linear regression to quantify the association of age and

RESULTS: Total hippocampal volume declined with age, with significant differences by

DISCUSSION: The association of

HIGHLIGHTS: Apolipoprotein E (

The Risks Of Unconcern: Low Sensitivity To Threat Can Have Unfortunate Consequences, Stephen L Ristvedt

2020-Current year OA Pubs

Each one of us is confronted with warnings of danger or threats to wellbeing in our everyday life, whether in the form of certain road signs, Public Service Announcements, ominous changes in bodily functioning, or cautionary tales heard from family or friends. There is great inter-individual variation in how people respond to such threats, with some people habitually tending to ignore or dismiss them, often to their peril. The first purpose of the present paper is to review several studies showing that individuals-most often men-who score very low on measures of trait anxiety are more likely to engage in behaviors …

Awareness, Use, Motivations And Methods Of Accessing Genetic Testing In 2022 In The United States, Sukh Makhnoon, Minjae Lee, Tanushree Prasad, Alexa Badalamenti, Tami Gurley, Erika A Waters, Celette Sugg Skinner

2020-Current year OA Pubs

INTRODUCTION: Awareness, access, and use of clinical and direct-to-consumer (DTC) genetic tests has increased in recent years with documented disparities in these services. We provide updated data on test awareness and use, and report novel data on motivations and methods for accessing genetic tests.

METHODS: Nationally representative data from the 2022 Health Information National Trends Survey (HINTS 6) were used to assess awareness and use of ancestry, personal trait, specific disease, and carrier testing by sociodemographic characteristics, examine reasons for undergoing tests, and methods of accessing them.

RESULTS: Overall, 81.4% of respondents were aware and 40.0% had undergone testing. Only …