Digital Commons Network^™

Prioritising Children’S Participation In Research: Including Children’S Voices In Updating A National Early Learning Framework, Lennie Barblett, Jennifer Cartmel, Leanne Lavina, Fay Hadley, Susan Irvine, Linda J. Harrison, Francis Bobongie-Harris

Research outputs 2022 to 2026

Involving children as stakeholders and including their voices in updating the Australian Early Years Learning Framework (for children birth to age 5) was a focus of this project design. The design was grounded in participatory approaches with a children’s rights perspective, as the team prioritised seeking children’s views and encouraging their agency on matters that affect them. This three-stage research project across 15 months sought children’s input in each stage. Research methods consisted of everyday playful activities supported by educators in early childhood environments using dialogic drawing, talking circles and discussions using photo elicitation. Educators received information to support their …

Reliability Of Time-Motion Analysis In Striking Combat Sports, L. Rohner, C. R. Abbiss, W. Poon, O. R. Barley

Research outputs 2022 to 2026

Introduction: Time-motion analysis (TMA) is a noninvasive performance analysis technique used in various sports to provide broad insights into the technical, tactical, and physiological demands of competitions by quantifying the mode, frequency, and duration of discrete activities. Objectives: This study aimed to assess the intra- and inter-observer reliability of activities in full-contact kickboxing athletes determined using TMA. Equipment and methods: A total of 29 bouts from the World Association of Kickboxing Organizations World Championships 2019, involving 58 male athletes, were analyzed by two expert analysts in a randomised order to determine the number of actions performed (i.e., punches, kicks, significant …

Suspended Particulate Organic Matter Supports Mesopredatory Fish Across A Tropical Seascape, Molly Moustaka, Tahlia J. Bassett, Leah Beltran, Michael V.W. Cuttler, Richard D. Evans, Daniel Gorman, Camille M. Grimaldi, Renee K. Gruber, Glenn A. Hyndes, Gary A. Kendrick, Natalie Travaglione, Shaun K. Wilson

Research outputs 2022 to 2026

Understanding the sources of primary production supporting marine food webs is important for conserving critical habitats. However, the importance of allochthonous versus autochthonous production is often unclear. We identify the sources of primary production supporting three species of predatory fish (Lutjanus carponotatus, Lutjanus fulviflamma, and Lethrinus punctulatus) in the Dampier Archipelago, Western Australia. The proportions of mangrove, seagrass, macroalgae, and suspended particulate organic matter (SPOM) assimilated by fish of different life-history stages and from different habitats were determined using stable isotopes and Bayesian mixing models. While contributions of sources varied among species and habitats, we found that SPOM was an …

The Australian Frailty Network: Development Of A Consumer-Focussed National Response To Frailty, Natasha Reid, Adrienne Young, Loretta Baldassar, Anja Christoffersen, Tracy Comans, Simon Conroy, Christopher Etherton-Beer, Jason Ferris, Maria Fiatarone Singh, Sarah Fox, Emily H. Gordon, Manonita Ghosh, Chandana Guha, Sarah Hilmer, Lisa Kouladjian O’Donnell, Benignus Logan, Kristiana Ludlow, Michelle Miller, Mark Morgan, Alison Mudge, John Muscedere, Donna Reidlinger, Kenneth Rockwood, Rosemary Saunders, David Ward, Paul Yates

Research outputs 2022 to 2026

Frailty is an important concept in the care of older adults. Over the past two decades, significant advances have been made in measuring frailty. While it is now well-recognised that frailty status is an important determinant of outcomes from medical illnesses or surgical interventions, frailty measurement is not currently routinely integrated into clinical practice. In the community setting, it is uncommon for general practitioners to deliver frailty-optimised care. In hospitals, there is substantial variability in how people living with frailty are managed. This variability is notable between and even within disciplines. Furthermore, gains from understanding frailty mechanisms and risk factors …

Variations In The Germinal Center Response Revealed By Genetically Diverse Mouse Strains, Anne Marie Aubin, Daria Vdovenko, Roxanne Collin, Lois Balmer, Lise Coderre, Grant Morahan, Félix Lombard-Vadnais, Sylvie Lesage

Research outputs 2022 to 2026

The humoral response is complex and involves multiple cellular populations and signaling pathways. Bacterial and viral infections, as well as immunization regimens, can trigger this type of response, promoting the formation of microanatomical cellular structures called germinal centers (GCs). GCs formed in secondary lymphoid organs support the differentiation of high-affinity plasma cells and memory B cells. There is growing evidence that the quality of the humoral response is influenced by genetic variants. Using 12 genetically divergent mouse strains, we assessed the impact of genetics on GC cellular traits. At steady state, in the spleen, lymph nodes and Peyer's patches, we …

Density And Abundance Estimation Of West Indian Manatee, Trichechus Manatus, Between The States Of Ceará And Piauí, Northeast Brazil, Using Active Acoustics, Katherine Fiedler Choi Lima, Denis Moledo De Sousa Abessa, Daniel Gonzalez-Socoloske, Renata Sousa-Lima, Ana Carolina Oliveira De Meirelles, Cristine Pereira Negrão Silva

Faculty Publications

The West Indian manatee is one of the most threatened species in Brazil. The species has currently a patchy distribution from the state of Alagoas to the state of Amapá. The difficulty of observing manatees, especially in estuarine waters, is a challenge for conservation. Therefore, it is necessary to use new methodologies and technologies to solve manatee detection problems in their natural habitats. The goal of this study was to use an active acoustic method of detection to estimate manatee density and abundance in the estuarine complex of the Timonha and Ubatuba rivers, between the states of Ceará and Piauí, …

Extending Natural Mates In Euclidean 3-Space And Applications To Bertrand Pairs, Yun Myung Oh, Alexander Navarro

Faculty Publications

In Euclidean 3-space, a family of curves, the co-successor, is motivated and then introduced in relation to the natural mate. A complete characterization of co-successors is proved, followed by an application of the co-successor towards describing Bertrand curves and their mates.

Gender Difference On Internal Equity: Evidence From The Hospitality Industry In Ghana, Patricia Peprah

Faculty Publications

It is a hypothetical position that employees in the hospitality industry in Ghana experience salary disparities based on the gender of the employee. Pay disparities exist because of unconscious biases in areas such as hiring, promotions, performance reviews, and salary decisions. In ensuring equal pay for equal work to fulfill the International Labor Organization (ILO) convention, this study investigated the internal equity pay of the employees in Ghana's hospitality industry based on equal work. This quantitative association study adopted a self-constructed research instrument to measure internal equity pay and randomly selected 350 respondents in the hospitality industry in Ghana to …

Evaluating Chatgpt Performance In Arabic Dialects: A Comparative Study Showing Defects In Responding To Jordanian And Tunisian General Health Prompts, Malik Sallam, Dhia Mousa

Mesopotamian Journal of Artificial Intelligence in Healthcare

Background: The role of artificial intelligence (AI) is increasingly recognized to enhance digital health literacy. There is of particular importance with widespread availability and popularity of AI chatbots such as ChatGPT and its possible impact on health literacy. The involves the need to understand AI models’ performance across different languages, dialects, and cultural contexts. This study aimed to evaluate ChatGPT performance in response to prompting in two different Arabic dialects, namely Tunisian and Jordanian. Methods: This descriptive study followed the METRICS checklist for the design and reporting of AI based studies in healthcare. Ten general health queries were translated into …

Measuring The Effectiveness Of Ai Tools In Clinical Research And Writing: A Case Study In Healthcare, Sani Salisu, Osamah Mohammed Alyasiri, Hussain A. Younis, Thaeer Mueen Sahib, Ahmed Hussein Ali, Ameen A. Noor, Israa M. Hayder

Mesopotamian Journal of Artificial Intelligence in Healthcare

This article investigates the capabilities and limitations of ChatGPT, a natural language processing (NLP) tool, and large language models (LLMs), developed from advanced artificial intelligence (AI). Designed to help computers understand and produce text understandable by humans, ChatGPT is particularly aimed at general scientific writing and healthcare research applications. Our methodology involved searching the Scopus database for ’type 2 diabetes’ and ’T2 diabetes’ articles from reputable journals. After eliminating duplicates, we used ChatGPT to formulate conclusions for each selected article by inputting their structured abstracts, excluding the original conclusions. Additionally, we tested ChatGPT’s response to simple misuse scenarios. Our findings …

Machine Learning Helps In Quickly Diagnosis Cases Of "New Corona", Maad M. Mijwil, Ioannis Adamopoulos, Pramila Pudasaini

Mesopotamian Journal of Artificial Intelligence in Healthcare

Machine learning is considered one of the most significant techniques that play a vital role in diagnosing the Coronavirus. It is a set of advanced algorithms capable of analysing medical data and identifying patterns and behaviours of diseases. It is used to interpret medical images, giving details of each image with high accuracy and efficiency, such as chest X-ray images. These algorithms are trained on a large set of images to recognise patterns that indicate the presence of infection with the Coronavirus (COVID-19). This article will provide a brief overview of the importance of machine learning in diagnosing COVID-19 by …

Examining Ghana's Health Professions Regulatory Bodies Act, 2013 (Act 857) To Determine Its Adequacy In Governing The Use Of Artificial Intelligence In Healthcare Delivery And Medical Negligence Issues, George Benneh Mensah

Mesopotamian Journal of Artificial Intelligence in Healthcare

This analysis examines Ghana’s Health Professions Regulatory Bodies Act, 2013 (Act 857) to assess its fitness to govern the ascent of artificial intelligence (AI) in reshaping healthcare delivery. As advanced algorithms supplement or replace human judgments, dated laws centered on individual practitioner liability struggle to contemplate emerging negligence complexities. Act 857 lacks bespoke provisions for governing this new era beyond outdated assumptions of human-centric care models. With AI projected to transform medicine, proactive reforms appear vital to enable innovation gains while upholding accountability. Through an IRAC legal analysis lens supplemented by case law spanning from the United States to Ghana, …

Evaluating If Ghana's Health Institutions And Facilities Act 2011 (Act 829) Sufficiently Addresses Medical Negligence Risks From Integration Of Artificial Intelligence Systems, George Benneh Mensah, Pushan Kumar Dutta

Mesopotamian Journal of Artificial Intelligence in Healthcare

With artificial intelligence (AI) integrated increasingly to enhance personalized diagnosis and data-driven treatment recommendations, this analysis examines the legal sufficiency of Ghana’s Health Institutions and Facilities Act 2011 (Act 829) to address medical negligence risks from reliance on AI systems in clinical settings. The CREAC framework structures evaluating gaps where existing health regulations may lack clarity for emerging issues of accountability. Explanation contextualizes the probabilistic nature of AI inferences and how general principles of medical negligence could have ambiguous application currently if erroneous AI contributions result in patient harm. Application to a hypothetical scenario assesses if adequate protections for appropriate …

Darknet-53 Convolutional Neural Network-Based Image Processing For Breast Cancer Detection, R. Rajkumar, S. Gopalakrishnan, K. Praveena, M. Venkatesan, K. Ramamoorthy, J. Jasmine Hephzipah

Mesopotamian Journal of Artificial Intelligence in Healthcare

Breast cancer is a common type of cancer in women, denoted by the uncontrolled growth of cells in breast tissue. Thus, manually detecting breast cancer is time-consuming and necessitates automated systems. Existing breast cancer screening methods often have limited efficacy and may delay detection and complicate the individual treatment planning process. However, early detection of breast cancer can be costly and impact the accuracy of diagnosis. To address this issue, we introduce a Darknet-53 Convolutional Neural Network (darknet-53CNN) approach for classifying breast cancer images and improving precision. Furthermore, we utilise the Contrast-Limited Adaptive Histogram Equalization (CLAHE) technique to pre-process breast …

Benchmarking Generative Ai: A Call For Establishing A Comprehensive Framework And A Generative Aiq Test, Malik Sallam, Roaa Khalil, Mohammed Sallam

Mesopotamian Journal of Artificial Intelligence in Healthcare

The introduction and rapid evolution of generative artificial intelligence (genAI) models necessitates a refined understanding for the concept of “intelligence”. The genAI tools are known for its capability to produce complex, creative, and contextually relevant output. Nevertheless, the deployment of genAI models in healthcare should be accompanied appropriate and rigorous performance evaluation tools. In this rapid communication, we emphasizes the urgent need to develop a “Generative AIQ Test” as a novel tailored tool for comprehensive benchmarking of genAI models against multiple human-like intelligence attributes. A preliminary framework is proposed in this communication. This framework incorporates miscellaneous performance metrics including accuracy, …

Assigning Medical Professionals: Chatgpt's Contributions To Medical Education And Health Prediction, Maad M. Mijwil, Mostafa Abotaleb, Guma Ali, Klodian Dhoska

Mesopotamian Journal of Artificial Intelligence in Healthcare

Artificial intelligence is increasingly present in many applications that help humans accomplish many tasks. It can support improved results, increased productivity, and high efficiency in providing services. Systems developers seek to integrate improved artificial intelligence models into the development of healthcare services and make a significant qualitative shift in the medical field. One recently invented tool is ChatGPT, which deserves extensive advertising space. This tool provides sample answers that help both healthcare workers and patients answer all their questions. It is an important tool in medical education, increasing knowledge in making decisions that can improve the performance of medical professionals. …

Covid-19 Diagnosis Using Deep Learning Approaches: A Systematic Review, Tarza Hasan Abdullah, Berivan Hasan Abdullah

Mesopotamian Journal of Artificial Intelligence in Healthcare

The utilisation of deep learning techniques has witnessed a surge in popularity within the realm of medical image analysis, particularly in the context of identifying COVID-19. Following the occurrence of the COVID-19 pandemic, extensive investigations have been conducted to identify the existence of Sars-Cov-2 through the utilisation of several deep learning algorithms. The objective of this study is to conduct a comprehensive review of deep learning techniques utilised for the detection of COVID-19. "Can deep learning methodologies serve as a viable substitute for radiologists in the diagnostic process of COVID-19?" is the research inquiry. In order to compile research articles …

An Optimized Framework For Kidney Disease Detection And Prediction Using Dl Techniques, El-Sayed M. El-Kenawy, Marwa M. Eid, Ahmed M. Elshewey, Ahmed M. Osman

Mesopotamian Journal of Artificial Intelligence in Healthcare

In recent years, chronic kidney disease (CKD) has become a crucial public health concern and issue, resulting in serious mortality rates. Therefore, we introduce a powerful system for kidney disease diagnosis that develops up-to-date approaches and applications. Our powerful system is meant for early detection, individual patient monitoring, and optimal CKD patient outcomes. The study introduces a CKD detection ecosystem primarily intended for optimized early detection techniques to be able to manage significant weaknesses in current systems and also for proactive treatment. This ecosystem also provides medical practitioners with up-to-date diagnostic technology, incorporating advanced Convolutional Neural Networks (CNN) that guarantee …

Machine Learning Techniques To Predictive In Healthcare: Hepatitis C Diagnosis, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi

Mesopotamian Journal of Artificial Intelligence in Healthcare

The accurate prediction and classification of medical data, such as Hepatitis C, play a significant role in upgrading symptomatic accuracy and treatment planning. This study utilized progressed machine learning algorithms, including RF, SVR, and Gradient Boosting, to analyze features and predict outcomes viably. By coordination robust preprocessing strategies and feature engineering, the models tended to missing values and categorical transformations, enabling exact predictions from complex datasets. The models accomplished high accuracy and unwavering quality in execution, as prove by comparative measurements and validation results. These discoveries highlight the potential of machine learning in increasing clinical decision-making and emphasize the require …

A Comprehensive Review On Cryptographic Techniques For Securing Internet Of Medical Things: A State-Of-The-Art, Applications, Security Attacks, Mitigation Measures, And Future Research Direction, Wamusi Robert, Asiku Denis, Adebo Thomas, Aziku Samuel, Simon Peter Kabiito, Zaward Morish, Guma Ali

Mesopotamian Journal of Artificial Intelligence in Healthcare

As healthcare becomes increasingly dependent on the Internet of Medical Things (IoMT) infrastructure, it is essential to establish a secure system that guarantees the confidentiality and privacy of patient data. This system must also facilitate the secure sharing of healthcare information with other parties within the healthcare ecosystem. However, this increased connectivity also introduces cybersecurity attacks and vulnerabilities. This comprehensive review explores the state-of-the-art in the IoMT, security requirements in the IoMT, cryptographic techniques in the IoMT, application of cryptographic techniques in securing the IoMT, security attacks on cryptographic techniques, mitigation strategies, and future research directions. The study adopts a …

Machine Learning Techniques For Skin Fungal Infection Detection -A Review, Daniah Abdul Qahar Shakir, Eman Turki Mahdi

Mesopotamian Journal of Artificial Intelligence in Healthcare

Skin diseases are the most common than other diseases. Skin diseases may be caused by fungal infection, allergy, bacteria, viruses, etc. Fungal disease affects more than billions people worldwide. The accurately of diagnosing skin fungal infections can be challenging in their early stages or present with symptoms, which mimic other dermatological disorders. The identification and categorization of skin fungal infections could be improved by recent developments in deep learning and artificial intelligence (AI). It offers a more effective and dependable substitute for conventional diagnostic techniques. Here we tried to focus on various methods for identifying fungal skin that rely on …

Do I Sound Anxious? Emotional Arousal Is Linked To Changes In Vocalisations In Domestic Chicks (Gallus Gallus Dom.), Sarah A. Collins, Katherine Herborn, Kenneth J. Sufka, Lucy Asher, Ben Brilot

School of Biological and Marine Sciences

A major goal in animal welfare science is the development of methods that quantify or ‘read-out’ current affective states in freely behaving animals. In mammalian models, changes in acoustic parameters within vocalisations have been linked to differences in emotional arousal, although there are very few studies showing changes in vocalisations that act as indicators of valence (positive or negative affect). Currently, there are very few studies on vocal indicators of emotion in birds. To determine the link between acoustic parameters within vocalisations and emotion in domestic chicks (Gallus gallus dom.), we used a well-validated paradigm that purports to elicit two …

Invasive Macroalgae In Native Seagrass Beds: Vectors Of Spread And Impacts, Louise Firth, Andy Foggo, Thomas Watts, Antony Knights, Stacey Deamicis

School of Biological and Marine Sciences

Background and AimsWorldwide, invasive species are spreading through marine systems at an unprecedented rate with both positive and negative consequences for ecosystems and the biological functioning of organisms. Human activities from shipping to habitat damage and modification are known vectors of spread, although biological interactions including epibiosis are increasingly recognized as potentially important to introduction into susceptible habitats.MethodsWe assessed a novel mechanism of spread – limpets as transporters of an invasive alga, Sargassum muticum, into beds of the seagrass Zostera marina – and the physiological impact of its invasion. The association of S. muticum with three limpet species and other …

“Courtesy, Respect, And Follow Through”: A Mixed Methods Evaluation Of Faculty Members’ Experiences, Needs, And Approaches To Research Collaborations, Daniela B. Friedman Ph.D., Christina Ek, Jean Neils-Strunjas Ph.D, Ccc-Slp, Andrea Tanner Ph.D., James R. Hébert Scd, Lorie Donelle, Sue E. Levkoff, Freda Allyson Hucek, Brooks Yelton Ma, Lmsw, Dwayne E. Porter

Faculty Publications

Introduction: Guided by a communications-focused framework developed by an interdisciplinary team of authors, this paper presents data from a survey of health science faculty members to better understand how research collaborations are established and maintained. Methods: An electronic survey was distributed to faculty in six colleges at a Research 1 institution. Quantitative data were downloaded into Excel and then RStudio for descriptive analysis. Open-ended, qualitative responses were coded and analyzed for themes. Results: Most respondents were in public health (44.0%) or medicine (25.3%); 40.0% were tenured. A grant deadline was the main impetus reported for initiating research collaborations (86.1%). Most …

Reflecting On Partnerships Established And Sustained Over Four Cycles Of A Federally Funded Cancer Prevention And Control Research Program: Lessons Learned For Community-Academic Networks, Swann Arp Adams, Lauren Workman Ph.D., Mayank Sakhuja, Brooks Yelton Ma, Lmsw, Karen E. Wickersham Phd, Rn, Ciaran Fairman, Jan Eberth Ph.D., Sue Heiney Scd, James Hébert Scd, Freda Allyson Hucek, Lauren Schaurer, Daniela B. Friedman Ph.D.

Faculty Publications

Introduction: The Centers for Disease Control and Prevention (CDC) funded Cancer Prevention and Control Research Network (CPCRN) is a national network which aims to accelerate the adoption and implementation of evidence-based cancer prevention and control strategies and interventions in communities, enhance large-scale efforts to reach underserved populations and reduce their cancer-related health disparities, and develop the capacity of the dissemination and implementation work force specifically in cancer prevention and control. Methods: Our site has been a part of the CPCRN since its inception in 2002 with the exception of the 2004–2009 funding cycle. As community-based participatory research is a core …

Two-Group Drift-Flux Model For Dispersed Gas-Liquid Flow In Large-Diameter Pipes, Hossein Barati, Takashi Hibiki, Joshua P. Schlegel, Naofumi Tsukamoto

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

Interfacial Heat and Mass Transfer Are Prevalent in Industrial Processes. the Interfacial Transfer Rate Can Be Obtained by the Product of their Fluxes and Interfacial Area Concentration (IAC) Calculated by the Interfacial Area Transport Equation (IATE). Bubbles Show Different Behavior According to their Sizes. Hence, Bubbles Are Classified into Two Groups. Consequently, Two-Group IATE is Required Causing to Use of Two Gas Momentum Equations Leading to More Complexity. the Present Study Suggests a New Reliable Two-Group Drift-Flux Modeling to Reduce the Two Gas Momentum Equations to One Gas Mixture Momentum Equation for Gas-Liquid Flow in Large-Diameter Pipes. the Model is …

Advanced Manufacturing Of Nanomaterials For Energy Storage And Biomedical Applications, Hiep Pham

Doctoral Dissertations

"Nanomaterials have emerged as an important component to the advancement of many fields, ranging from advanced energy materials in the energy field to highly sophisticated treatment vehicles in the biomedical field. Understanding the physical behavior of nanomaterials is critical to design materials with excellent properties and performance for the many disciplines in which they are utilized and is necessary to master the various manufacturing processes that influence nanomaterial properties and behavior. This research focused on a fundamental study into the behaviors of newly developed nanomaterials under both conventional and new manufacturing processes for high performance lithium-ion batteries and for advanced …

Advancing A Systems Perspective On Innovative Behavior, Stephen Demski

Doctoral Dissertations

"Engineering organizations pursue innovation in strategy, structure, processes, and the services and products offered to remain relevant and competitive. Identifying factors supporting or constraining innovative work behavior and recognizing the complexity of their interactions are vital to sustaining an innovative workforce, yet how factors interact has not been comprehensively studied.

Recognizing innovative work behavior as the output of a complex system of factors guided this study’s literature search that identified over one hundred individual, team, and organizational factors influencing innovative behavior, interviews of engineers to learn what factors are essential in their work environment, and Delphi survey to rank factors, …

Chirality Determination Using Three-Wave Mixing Microwave Spectroscopy, Nicole Taylor Moon

Doctoral Dissertations

"Rotational spectroscopy has established itself as a reliable gas-phase spectroscopic technique for the structural determination of molecules. This reliability has stemmed from both advancements in microwave technology and a willingness from the community to push the boundaries of the field. In this dissertation, the boundaries are tested in both how well the technique can determine the structure of molecules exhibiting large amplitude motion and through chirality determination. The first half of this dissertation explores the use of deep averaging to determine the structure of silicon containing molecules in collaboration with Dr. Guirgis from the College of Charleston. For each of …

Melt Pool Feature Extraction, A State-Space Model And Spatial Layer-To-Layer Control For Powder Bed Fusion, Xin Wang

Doctoral Dissertations

"Powder Bed Fusion (PBF) is an Additive Manufacturing (AM) technique which can reduce material waste and is a fast-prototyping technique for complex geometries. However, the lack of consistent quality is a major problem in industrial applications. An InfraRed (IR) camera is a common tool to monitor a surface temperature field and melt pool morphology in PBF. With melt pool features from camera videos, manufacturing researchers use spatial feature maps to visualize defect locations and control researchers use layer-to-layer control to achieve more uniform melt pools and less defects.

Paper I presents a simulation method to characterize the effect of down-sampling …