Digital Commons Network^™

Classifying Glaucoma Disease Images Via Deep Neural Network Technique, Maysoon Jaaffar Rahim, Ali Abid Dawood Al-Zuky, Fatin Ezzat Muhy Al-Dean Al-Obaidi

Baghdad Science Journal

A class of eye diseases known as glaucoma refers to a category of eye disease which is often associated with increased intraocular pressure, and can damage the eye by destroying nerve cells in the retina in addition to the eye's optic nerve. The accuracy of diagnosing glaucoma eye disease depends on the knowledge and experience of the ophthalmologist. Therefore, the need for automatic feature extraction from the retinal image is crucial for the diagnosis of glaucoma eye disease. The current article introduces a multi-layer deep neural network model with convolution and classification layers. The originality of the current search focuses …

Sex Differences In The Association Of Vascular Risk And Apoe Genotype With Cognitive Decline And Dementia: Evidence From A U.S. Longitudinal Study, Longjian Liu, Jintong Hou, Saishi Cui, Xiaopeng Zhao, Zuolu Liu, J. Craig Longenecker, Nathalie S May, Jin Jun Luo, Rose Ann Dimaria-Ghalili, Howard J. Eisen

Division of Cardiology Faculty Papers

BACKGROUND: Sex differences in the association between vascular factors and cognitive outcomes remain unclear. We aimed to investigate the associations of blood pressure metrics (hypertension, systolic blood pressure [SBP), pulse pressure, ankle and brachial pressures, and ankle to brachial pressure index [ABI]) with the risk of cognitive decline and dementia.

METHODS: We conducted a population-based longitudinal analysis using data from the Atherosclerosis Risk in Communities (ARIC) study (begun in 1987-1989) in the United States. We analyzed a total of 12,268 participants aged 45-64 years who had validated exposure measurements, cognitive function tests (first administrated 1990-1992), and followed up for incidence …

Psychological Responses To Interval And Continuous Exercise In People Living With Hiv: A Single-Blind, Counterbalanced, Crossover Study., Phelipe Wilde, Victor S. De Queiros, Jason R. Jaggers, Angelo Sabag, Julio M. Alves, Elaine Fernandes, Robert F.C. Rocha, Paulo F. De Almeida-Neto, Ronaldo Vagner Thomatieli-Santos, Paulo Moreira Silva Dantas

Faculty and Staff Scholarship

Abstract
Aim: This study compared acute psychological responses to a single session of low-volume high-intensity interval exercise (HIIE-LV), high-volume highintensity interval exercise (HIIE-HV), and moderate-intensity continuous exercise (MICE) in people living with HIV, and healthy controls using a randomized, counterbalanced crossover design. Methods: The participants (people living with HIV, and healthy controls) completed three exercise sessions in randomized order: HIIE-HV (4  4 min at 80% of maximal power output [Wmax]), HIIE-LV (10  60 s at 90% Wmax), and MICE (30 min at 60% Wmax). Psychological outcomes included affective response assessed by the Feeling Scale, exercise enjoyment and future exercise intention …

Teach-Back Techniques In Telehealth: A Review And Insights For Future Directions, Faith A. Albertson, Waka Alnakhi, Shanikque Barksdale, Shannon Stark Taylor, Shaniece Criss, Daniela B. Friedman Ph.D., Karen A. Kemper, Lorie Donelle Phd, Rn, Fcan, Wanda Thompson, Phyllis Macgilvray, Nabil Natafgi

Publications

Background and objectives: The rapid expansion of telehealth during the COVID-19 pandemic has created new challenges in patient-provider communication due to the absence of in-person interactions and visual cues. Teach-back, a method where patients repeat information to confirm understanding, is a promising tool for improving communication in virtual care. This review evaluates the effectiveness of teach-back techniques in telehealth settings.

Methods: A search of four databases (CINAHL, EMBASE, PsycINFO, PubMed) was conducted, yielding 10 studies that met the inclusion criteria. The article inclusion/exclusion criteria consisted of the following: (1) telehealth services topic; (2) direction provision related to teach-back; and (3) …

Advanced Ni-Co And Sn-Based Alloys Electrodeposition From Aqueous And Deep Eutectic Solvents, Narmin M. Hamadamin, Hassan H. Abdallah

Polytechnic Journal

Electrodeposition is a pivotal technique in materials science, enabling the fabrication of metal and alloy coatings with tailored properties for diverse industrial applications. Traditional aqueous electrolytes, while widely used, present limitations such as narrow electrochemical windows, hydrogen evolution, and environmental concerns. Deep eutectic solvents (DESs) have emerged as promising alternatives, offering broader electrochemical windows, reduced toxicity, and enhanced solubility for metal salts. This review comprehensively examines the principles and advancements in electrodeposition from both aqueous and DES media, focusing on the deposition of Ni-Co and Sn-based alloys, the role of additives, the electrodeposition of metal powders, and surface analysis techniques. …

The Gamification Of Online Dating: Exploring The Intersection Of Play, Choice, And Romance In Digital Spaces, Emma Taylor

School of Law, Humanities and Social Sciences

The rise of online dating platforms has transformed the way individuals approach romantic relationships, with many users increasingly engaging in these platforms as a form of entertainment in addition to finding meaningful connections. Central to this shift is the growing phenomenon of gamification, the incorporation of game-like elements, into non-game contexts. This article proposes to explore the gamification of online dating, examining how these game mechanics shape user behaviours, influence romantic choices, and impact relationship outcomes. By analysing the ways in which dating platforms integrate game-inspired features, this study will also assess the implications of gamified experiences for the nature …

A Social Media-Based Framework For Marketing Architectural Design Firms In Egypt During Global Economic Downturn, Ayman Ahmed Ezzat Othman, Yara Ahmed Maarek

Architectural Engineering

Purpose – The global economic downturn has greatly impacted the construction industry and architectural design firms (ADFs). Social media, however, provides a strategic avenue to enhance the visibility and resilience of ADFs. This paper aims to develop a framework integrating social media as an innovative marketing approach for mitigating the impacts of the global economic downturn on ADFs in Egypt.

Design/methodology/approach – A qualitative and quantitative research approach was designed to accomplish four objectives. The literature review examined the global economic downturn and marketing ADFs. Three case studies investigated the role of social media in marketing ADFs during economic uncertainties. …

Exploring The Therapeutic Potential Of Fermented Apple Juice And Sidr Leaves Powder On Gut Microbiota Modulation And Neuropathy Relief In Diabetic Rats, Bakenam Ali Mohamed, Alyae M.S. Gabal, Gehan M. Morsy

Baghdad Science Journal

Diabetes and its complications, particularly diabetic neuropathy, represent major health risks. This study investigated the potential of natural nutrients and bioactive compounds specifically fresh and fermented apple juice and sidr leaf powder to improve gut microbiota and alleviate neuropathy in diabetic rats. Seventy adult male Sprague–Dawley rats (180 ± 20 g) were assigned to six groups (11 rats each), while the diabetic control group (15 rats). Diabetes was induced by feeding a high-sucrose, high-fat (HSHF) diet and administering streptozotocin (45 mg/kg, intraperitoneally) during the 4^th week. The groups included: healthy control; diabetic control; diabetic rats receiving fresh or fermented …

Nuclear Binding Energy Prediction For Some Odd-Mass Number Nuclei By Artificial Neural Network (Ann), Ruya H. Ibrahim, Akram Mohammed Ali

Baghdad Science Journal

Machine learning models called artificial neural networks (ANNs) are widely used in many fields and real-world applications. The parameter vector that forms the basis of these models needs to be evaluated computationally. We calculated the ground-level binding energy of 146 nuclei with an odd mass number using three different models:the integrated nuclear model,the liquid drop model and the experimental model. The results of these models were compared with our theoretical results calculated by the artificial intelligence network. The mean squared error of the target and output values and how close they are to zero were calculated, and the degree of …

Comprehensive Study For Characterization Of Blending And Heat Treatment Of Organic-Based Polymer Thin Films, Ruaa M. Ali, Atyaf H. Kazem, Khalidah G. Hasan

Baghdad Science Journal

Thin films of Polypyrrole (PPy)/Cupper Phthalocyanine (CuPc) have been prepared by the spin coating technique on glass substrates, Samples were prepared in a blending ratio (50:50) in addition to pure PPy and CuPc at room temperature, these samples were annealed at (473K) and then characterized by X ray diffraction (XRD), Energy Dispersive Spectroscopy (EDX) and Scanning electron microscopy (FESEM) at different magnifications power. XRD patterns reveal that pure polypyr role is amorphous. A wide peak was seen at roughly 2θ= 24° with an average crystallite size of roughly 56 nm and CuPc had a polycrystalline structure. Annealing results …

Generalized Pentagonal Linear And Non-Linear Functions For Solving Fully Fuzzy Linear Programming Problems, Eman Hassan Ouda, Iden Hassan Hussein

Baghdad Science Journal

Fuzzy linear programming problems (FLPP) are advanced approaches for solving linear programming problems (LPP) that involve fuzzy coefficients and variables with constraints on the problem. Numerous applications exist for the pentagonal function and ranking membership in geometry and the sciences, especially mathematics. This study suggests a novel approach for solving fully fuzzy linear programming problems (FFLPP) using the ranking function with pentagonal functions. The project aims to determine the maximum (minimum) solution to the problems where all variables, including the objective function, constraints and the right hand, are pentagonal fuzzy numbers. Additionally, generalizations of both linear and nonlinear pentagonal functions …

On The Systems Of Distinct Representatives For The Family Of Sets Formed By Neighborhoods Of Vertices, Shahistha Hanif, K Arathi Bhat

Baghdad Science Journal

Currently, the theory of systems of distinct representatives is being carefully examined and reworked, often in a more general context. With time, considerable literature has grown, and new theories are proposed that require the system of distinct representatives to possess additional properties. In this article, one such context is considered. A graph is completely defined by the relationship between its vertices, also known as the neighborhood of vertices in graph theoretical context. Several parameters are defined based on the set of all neighborhoods of vertices and are explored. This article delves into the well-known problem of the existence of a …

Hybrid Pre-Trained Models With Machine Learning Classifier For Skin Cancer Classification, Toqa A. Sadoon, Asaad F. Qasim, Mohammed Khalaf, Ali M. Hasan

Baghdad Science Journal

Classification of skin lesions can be challenging because of the subtle variation on the skin surface due to the appearance of these lesions. In the other hand, the digital dermoscopy has been widely used by dermatologist to diagnose cancer. For accurate detection, the clinicians should have a lot of experiences, but human nature is prone to error, forgetfulness, tension, and speed in diagnosis, all of which can affect the accuracy of detection. For these reasons, automated skin lesion classification has been used by many researchers to help dermatologists in making the right and accurate decision during diagnosis. A preprocessing image …

Using Physics-Informed Neural Networks For Solving 2Nd-Order Volterra Integro-Differential Equation By Deepxde Library, Oday Ahmed Jasim, Abdulghafor M. Al-Rozbayani

Baghdad Science Journal

Many disciplines widely use deep learning (DL) as a key tool for investigating the behavior of various systems. Deep learning (DL) has recently been utilized to solve differential equations using physics-based input. Physics-informed neural networks (PINNs) are a novel DL model that excels at solving both inverse and forward non-linear PDE problems. PINNs may be trained as surrogate models for approximation solutions to the VIDE without label data by embedding the physical information outlined by PDEs in feedforward NNs. The objective of this study is to solve the second-order Volterra integral-differential equations (2nd-order VIDEs) for the first time using PINN …

The Dynamic Among The Producer, Consumer, And Predator In The Presence Of Fear, Hunting Cooperation, And Anti-Predator Behavior, Muslim Saad Jabbar, Raid Kamel Naji

Baghdad Science Journal

In general, the dynamic interactions that form the relationships between predators and prey within a food chain depend heavily on fear, hunting cooperation, and anti-predator defenses. These elements support species’ survival in their particular habitats, balance the ecosystem, and control the numbers of predators and prey. Therefore, a three-species food chain system consisting of producer-consumer-predator, which plays a crucial role in ecological dynamics, has been formulated mathematically. The objective is to investigate the influence of fear, hunting cooperation, and anti-predators on the dynamic behavior of the food chain system. Two types of functional responses have been utilized. The characteristics of …

Robust Emergency Dispatch Method Considering Dynamic Frequency Security And N-K Contingency, Tao Huang, Zhi Zhang, Yujie Ding, Yanbo Chen, Jing Wang, Wenqian Zhang

Journal of System Simulation

Abstract: To address the risk of system inertia loss and frequency instability caused by grid integration of high-proportioned new energy and unit failures, an N-k robust emergency dispatch method considering dynamic frequency security constraints was proposed. With the consideration of the frequency response characteristics of variable-speed pumped storage, a dynamic frequency response model incorporating variable-speed pumped storage was constructed, and the nadir frequency constraint was established through second-order cone transformation. Information entropy theory was employed to quantify the uncertainty of unit failures, and an uncertainty set considering N-k unit failures was developed. A twostage robust emergency dispatch model considering N-k …

Scheduling Method For Virtual Power Plants Based On Analysis And Forecasting Of Heterogeneous Load Characteristics, Runzhao Zhang, Yanbo Chen, Tao Huang, Haoxin Tian, Tuben Qiang, Zhi Zhang

Journal of System Simulation

Abstract: To improve the electricity supply-demand situation by rationally utilizing demand response resources, a two-layer optimal scheduling model for virtual power plants (VPPs) based on the analysis and forecasting of heterogeneous load characteristics was proposed. With the differences in response characteristics of multi-type loads considered, a demand response model for multi-type loads was constructed by using a customer baseline load (CBL) curve forecasting method that integrated dynamic scenario generation and K-means++ clustering. A two-layer optimal scheduling model for VPPs that incorporated load aggregators and demand response was established. In this model, the upper layer conducted optimal scheduling targeting maximizing the …

Vibration Control Of Offshore Wind Turbine Towers Based On Eddy Current Nonlinear Energy Sink, Xiangxing Yu, Yandong Zhao, Baolin Zhang

Journal of System Simulation

Abstract: To address the issue of tower vibrations induced by wind loads, which can damage the structure of wind turbines, a vibration control method for monopile offshore wind turbine towers based on an eddy current-nonlinear energy sink (EC-NES) was proposed. The dynamic model of monopile offshore wind turbines based on EC-NES was constructed according to the Euler-Lagrange equation, and based on the output response of FAST software, the unknown parameters of the model and the wind loads were identified in terms of parameters. The optimal parameters of EC-NES stiffness and damping were obtained using PSO. The eddy current damper …

Dual-Channel Supply Chain Network Equilibrium Model Under Retailers’ Risk Aversion, Hongchun Wang, Caifeng Lin, Xinyi He, Haiyue Yin

Journal of System Simulation

Abstract: To study the network equilibrium problem of dual-channel supply chains under the background of retailers' risk aversion, a dual-channel supply chain network equilibrium model including multiple competitive suppliers, manufacturers, retailers, and demand markets was established. The Mean-CVaR method was employed to quantify retailers' risk aversion characteristics, and variational inequalities were utilized to characterize the equilibrium conditions of decision-makers at each tier of the supply chain. The projection contraction algorithm was applied to solve the model and conduct numerical analysis, thereby revealing the impact of retailers' risk aversion behavior on equilibrium outcomes. The simulation results indicate that a higher …

Spatiotemporal Graph Convolution-Based Demand Forecasting And Simulation Analysis For Automotive Parts Supply Chain, Xiaobin Li, Bing Hu, Chao Yin, Bo Li, Jun Ma

Journal of System Simulation

Abstract: To address complex automotive after-sales parts supply network operations with insufficient demand forecasting accuracy, slow response, and low service efficiency, this study proposed a spatiotemporal graph convolution-based method for automotive parts supply chain demand forecasting. Sales network data of the automotive parts sales network was constructed as a heterogeneous graph, integrating node features like parts sales volume and value to build multi-dimensional node dependencies. A node update mechanism of the graph convolutional neural network was designed, combined with long short-term memory neural networks to capture temporal features, using spatiotemporal attention to integrate temporal and spatial features into updated nodes …

A Method Of Heuristic Human-Llm Collaborative Source Search, Yi Chen, Sihang Qiu, Zhengqiu Zhu, Yatai Ji, Yong Zhao, Rusheng Ju

Journal of System Simulation

Abstract: Traditional source search algorithms are prone to local optimization, and source search methods combining crowdsourcing and human-AI collaboration suffer from low cost-efficiency due to human intervention. In this study, we proposed a lightweight human-AI collaboration framework that utilized multi-modal large language models (MLLMs) to achieve visual-language conversion, combined chain-of-thought (CoT) reasoning to optimize decision-making, and constructed a heuristic strategy that incorporated probability distribution filtering and a balance between exploitation and exploration. The effectiveness of the framework was verified by experiments. The human-AI alignment heuristic strategy with large language model adaptation design provides a new idea to reduce manual …

Research On Cooperative Interference Allocation Of Jamming Resources Based On Improved Genetic Algorithm, Zhixia Xu, Rui Wang, Nan Sun, Bing He, Xiaowei Shen, Xiaofei Zhu

Journal of System Simulation

Abstract: To address the cooperative interference allocation of jamming tasks, a cooperative interference allocation method of jamming resources was proposed based on the improved genetic algorithm. In search and tracking modes of the target radar, a threat level assessment was conducted by the technique for order preference by similarity to an ideal solution (TOPSIS) based on the entropy weight method. The factors affecting the jamming effectiveness of jammers were analyzed. A cooperative interference evaluation model of jamming effectiveness was established, and the allocation model of jamming resources was built with the total interference effectiveness of multiple jammers as the …

Seroprevalence And Risk Determinants Of Toxoplasma Gondii Infection In Pregnant Women In Pakistan: A Cross-Sectional Study, Tajul Haram, Kamran Khan

Journal of Bioresource Management

Toxoplasma gondii is a globally important zoonotic parasite, and maternal infection during pregnancy may cause miscarriage, congenital anomalies, or severe neonatal complications. This cross-sectional study was conducted among 367 pregnant women attending hospitals in District Dir Upper, Khyber Pakhtunkhwa, Pakistan, to evaluate the seroprevalence of T. gondii and associated risk factors. Blood samples were analyzed using Immunochromatographic Test (ICT) for initial screening, and positive cases were confirmed by Enzyme-Linked Immunosorbent Assay (ELISA). Overall, 34.6 % (127/367) of women tested positive. While no significant differences were observed across age groups, gestational trimesters, or abortion history, higher prevalence was noted in women …

Isolation And Molecular Characterization Of Shiga Toxin Producing Genes Stx1and Stx2 From The Captive Migratory Birds Of Lahore, Romana Zulfiqar, Hamid Ullah, Bushra Nisar Khan, Muhammad Habib Ur Rehman, Hoor Ul Ain, Alishba Zaheer, Samrah Hussain, Aazba Naeem

Journal of Bioresource Management

A total of 240 cloacal and fecal swabs were collected from 25 avian species, including ducks, swans, geese, pheasants, guinea fowl, parrots, cranes, and crows. Samples were cultured on Sorbitol MacConkey Agar, and presumptive Escherichia coli isolates were confirmed using morphological, biochemical, and molecular methods. Shiga toxin–producing E. coli (STEC) was identified through PCR detection of stx1 and stx2 genes, followed by sequencing. Antibiotic susceptibility testing was performed using the Kirby–Bauer disc diffusion method against streptomycin, ceftriaxone, ciprofloxacin, azithromycin, and tetracycline. Only four STEC isolates were recovered, resulting in an overall prevalence of 1.66 % (4/240). Positive cases were detected …

The Assessment Of Soil Physico-Chemistry And Uptake Of Heavy Metals In Lumbricus Terrestris, Shahzad Anjum, Sidra Kanwal, Rana Manzoor Ahmad, Abdul Majid Khan, Muhammad Imran

Journal of Bioresource Management

Earthworms are considered ecosystem engineers, playing an essential role in soil fertility. Heavy metals are supposed to remain linked to soil for a very long time and can bio-accumulate swiftly in soil microbes, posing a severe threat to the environment. The current study was designed to investigate the bio-accumulation of heavy metals in Lumbricus terrestris and the impact of soil pH and texture on earthworm morphology and densities near industrial areas of the district of Okara, Punjab, Pakistan. The samples were collected from the locations of different industries using the quadrate method and analyzed for heavy metal accumulation by using …

Managing The Uncertainty Of "Precision" While Navigating Goals Of Care: A Framework For Collaborative Interpretation Of Complex Genomic Testing Results In Critically-Ill Neonates, Donnamaria E. Cortezzo, Katharine Press Callahan, Bimal P. Chaudhari, Elliott M. Weiss, Monica Hsiung Wojcik, Krishna Acharya, Amy B. Schlegel, Kevin M. Sullivan, Jessica T. Fry

Department of Pediatrics Faculty Papers

Each year, many neonates are born with genetic diagnoses that carry a range of prognoses. As the types and availability of genetic testing have expanded, neonatal intensive care units (NICUs) have served as "launching points" for their clinical application. Broad genetic testing has both improved diagnostic precision and expanded uncertainty. Genetic information may be explicitly uncertain, as in the case of a variant of unknown significance (VUS). But it is also frequently uncertain whether/how the information relates to a patient's phenotype or what it may mean for a child's future. Even without ambiguity in the diagnosis or prognosis, the significance …

Emotive Immersion: Eeg-Driven Ai Art In Immersive Visual Spaces (Full Dome), Yuming Chen, Gianni Corino

School of Art, Design and Architecture

This paper proposes a rethinking of the “Future Screen” through the integration of affective computing, generative AI, and immersive spatial display. As an advanced screen paradigm, the full dome environment transcends flat, passive interfaces and enables dynamic, multisensory, and emotionally adaptive media experiences (Von Chamier-Waite, 2013). Building on this potential, the research presents Coids, an interactive dome installation. In this work, real-time emotional states are captured using EEG-based emotion recognition. These inputs dynamically shape AI-generated visuals within a shared immersive setting.Drawing on theories of immersion, presence, AI generated visuals and affect, the study explores how physiological data, even from low-resolution …

Volumetric Video With Skateboarders: Creative Opportunities Of Working With An Emerging Screen Technology Beyond The Studio, Dani Landau, Diego Zamora

School of Art, Design and Architecture

Volumetric video is an emerging moving image technology in which each pixel is recorded witha location in three dimensions. Volumetric videos are normally created in studios using rigs made upof multiple cameras with LiDAR sensors and computers that combine the moving images. We tookthis technology out of the studio to explore variations of this technique in public skateparks. We foundthat as the technology is still in developing stages there are creative constraints: the lidar cameras sense at a limited distance to the subject, the image is of a relatively low resolution, and there are often glitches in theimage. In our …

Digital Resistance Against The Lasting Manipulation Of Capitalism: Ai, Luddite Rebellion, And The Haunted Future Of Cyberpunk, James Sweeting

School of Art, Design and Architecture

This paper examines the complex relationship between artificial intelligence, labour, and resistance amidst contemporary capitalism. Big Tech presents AI as revolutionary innovation, yet this narrative obscures its function in maintaining growth and preventing alternative economic forms from emerging. Through the lens of "enshittification," we observe a strategic shift toward AI deployment despite its beta state of development, threatening workers' livelihoods. This tension echoes historical patterns of technological implementation and resistance, exemplified by the Luddite movement whose meaning elites have successfully corrupted over time. The Luddites, organised under the mythical figurehead Ned Ludd (a Robin Hood-esque figure), recognised technological change as …

Estimating Prey Capture Attempts And Activity Costs In Foraging Emperor Penguins (Aptenodytes Forsteri) Using Integrated Biologging Data, Taylor Rose Azizeh

Master's Theses

To forage efficiently in patchy and unpredictable prey landscapes, marine predators must optimize energy intake while minimizing costs. Central place foragers like emperor penguins face greater energetic constraints during demanding periods of high investment like chick-rearing. I used high-resolution tri-axial acceleration, depth, and GPS data from 25 birds from two feeding seasons (2019 and 2022) to quantify prey capture attempts and a proxy for energy expenditure (overall dynamic body acceleration; ODBA) across dive types (epipelagic, mesopelagic, benthic), phases (descent, bottom, ascent), and over time at-sea. While prey capture attempts per minute did not differ when looking across dive types alone, …