Digital Commons Network^™

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 …

Fault Diagnosis Method For Photovoltaic Systems Based On Multi-Strategy Fusion, Bin Li, Yuchuo Wang

Journal of System Simulation

Abstract: To address the problem of frequent PV system faults, a multimodal fusion fault diagnosis model based on the optimization of the improved lemming algorithm was proposed. The one-dimensional time series signals of PV currents and voltages were converted into two-dimensional images by Markov transformation field, and the spatial features of the original waveforms were mined by using multiscale CNN (MCCNN); BiGRU was used to extract the temporal dynamic features of the original waveforms, and complementary enhancement of the temporal and spatial features was realized by the feature fusion layer. The improved lemming algorithm was innovatively introduced to adaptively optimize …

Numerical Simulations Of Ship Liquid Tank Sloshing Based On Graph Neural Networks, Wenkang Zhang, Xiaofeng Sun, Yiping Zhong, Yong Yin

Journal of System Simulation

Abstract: To address the high consumption of computational resources in simulating ship liquid tank sloshing using computational fluid dynamics simulation methods, a data-driven numerical simulation model was proposed based on graph neural networks. An encoder-processor-decoder framework was employed in the proposed model. The encoder extracted features of fluid particles from the first five time steps. The processor learnt latent motion patterns of fluid and updated features, and the decoder predicted features of particles at subsequent time steps. The processor incorporated a self-attention mechanism to enable dynamic adjacency weight allocation and emphasize the influence of irregular tank wall regions. Training …

Lightweight Assembly Workpiece Detection Algorithm Based On Improved Yolov8, Shuheng Wu, Yongkui Liu, Lin Zhang, Yingying Xiao, Lihui Wang

Journal of System Simulation

Abstract: To address the issues of low recognition accuracy and slow detection speed with existing deep learning-based object detection algorithms for robotic automatic assembly tasks, a lightweight assembly workpiece object detection algorithm based on YOLOv8 was proposed. The PConv was introduced to improve the C2f module, and a new Faster_C2f module was designed to enhance the detection speed of the model. The SIoU loss function was employed to optimize the location prediction accuracy of the CIoU loss function and improve the localization accuracy of small targets. The high-level screening-feature fusion pyramid networks (HS-FPN) structure was used to improve the Neck …

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) …

How Youth Think About Structural, Individual, And Random Sources Of Wealth Inequality, Amanda R. Burkholder, Riley N. Sims, Melanie Killen

Open Access Fund Publications

This study investigated how youth evaluate wealth inequalities, and whether youth differentiate structural, individual, and random explanations for why such inequalities exist. Understanding these distinctions is necessary for addressing exclusionary attitudes, biases, and discriminatory behaviors that emerge in childhood which have deleterious outcomes for youth. The present study included 262 youth (56.1% female; 27% Black, 49% White, 6.5% Asian American or Pacific Islander, 6% Latine, 6% multiracial, 6% other) who were 9 to 14-years-old, living in the Mid-Atlantic region of the U.S., and from primarily middle to high-middle income backgrounds. Participants evaluated wealth inequalities of different causes, reasoned about their …

Diskursus Kriminalisasi Pemidanaan Terhadap Pemberi Gratifikasi, Muhammad Fatahillah Akbar

Jurnal Hukum & Pembangunan

This article aims to examine the legal basis to prosecute gratifiers in Indonesian Corruption Justice System. Samin Tan as the giver of gratification to Eni Maulani Saragih had been acquitted by the Corruption Court of Jakarta Decision Number 37/Pid.Sus-TPK/2021/PN.Jkt.Pst on 30^th August 2021. Then, the Cassation to Supreme Court had also been rejected by Supreme Court Decision Number 2205 K/Pid.sus/2022 on 9^th June, 2022. Hence, Samin Tan stays acquitted. The decision majorly focuses on the “absence” of law which criminalizes gratifiers or gratification givers. Therefore, this article elaborates how similar cases shall be handled in the future. In …

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 …

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 …

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. …

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 …

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 …

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 …

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 …

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 …

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 …

Anti-Saccade Error Rates Are Associated With Somatic Depressive Symptoms In Cocaine Use Disorder, Constanza De Dios, Heather E Webber, Margaret C Wardle, Jin H Yoon, Michelle A Patriquin, Joy M Schmitz

Faculty, Staff and Student Publications

Background: Inhibitory control deficits are associated with cocaine use disorder (CUD) development and maintenance. Additionally, drug use and inhibitory control can be negatively affected by depressive symptoms, including somatic factors like sleep disturbance and fatigue.

Aim: The current study assessed the relationship between inhibitory control and depressive symptoms among individuals initiating CUD treatment. We examined associations among anti-saccade response inhibition performance, total scores on the Beck Depression Inventory-II (BDI-II), and individual BDI-II items.

Methods: N = 101 patients enrolled in a clinical trial for CUD completed drug-specific anti-saccade and depression (BDI-II) measures prior to treatment. Generalized linear models tested the …

The Impact Of Targeting Traf2 And Nck-Interacting Protein Kinase On Antitumor Effect And Tumor Immune Environment In C-Myc-High Sclc, Azusa Tanimoto, Kavya Ramkumar, C Allison Stewart, Bingnan Zhang, Kyle Concannon, Li Shen, Jing Wang, Carl M Gay, Lauren Averett Byers

Faculty, Staff and Student Publications

Introduction: Wnt/β-catenin signaling pathway activation contributes to tumorigenesis and chemo-resistance in SCLC, yet clinical attempts to target this pathway have been unsuccessful. TRAF2 and NCK-interacting protein kinase (TNIK), an essential nuclear activator of Wnt/β-catenin target genes, has not yet been validated as a viable therapeutic target in SCLC. Here, we validated that TNIK inhibition is a promising approach for personalized anticancer therapy in SCLC.

Methods: We correlated the IC50 values of a TNIK inhibitor, NCB-0846, with proteomic profiling (reverse phase protein array) data across 28 SCLC cell lines. Cytokine array analysis was performed to quantify changes in 105 cytokines after …

Detection Of The Linac Jaw Face Angle Misalignment Using High Energy Electron Beam Symmetry, Song Gao, Andres Cibrian, Jared Ohrt, Peter Balter

Faculty, Staff and Student Publications

Purpose: To demonstrate the usage of a high energy electron beam symmetry measured at different collimator angles to detect jaws face angle misalignments on Varian TrueBeam linear accelerators (linac) during acceptance and commissioning processes.

Methods: During the linac acceptance, all beams were steered to a symmetric shape with the gantry and collimator at 0°. We noted that the symmetries of higher energies electrons (e.g., 16 MeV, 20 MeV) changed over 2% when measured with the collimator at 90° and/or 270° for two linacs commissioned within 5-months of each other. Misaligned applicators were ruled out as the cause of this issue. …

Reduction Of Ground Vibration Dynamic Effects Induced From Mining Blasting On Nearby Structures: Case Study, Ayman M. Ismail, Sherif H. M. Hassnien

HBRC Journal

One of the primary challenges confronting the quarrying industry pertains to the ground vibrations resulting from the blasting activities in cement quarries, as these vibrations have the potential to inflict significant damage upon adjacent structures. Within the context of this scholarly article, an examination is conducted on a residential edifice situated in the 15th of May city in Cairo, Egypt, which has been impacted by the proximate mining blasting. The ground velocity at the foundation of this residential building is assessed, mainly from the peak particle’s velocity prospective. Subsequently, a finite element model (FEM) of the building is formulated and …

Carbon Nanotubes Enhanced Tio2/G-C3N4 As A Potential Nanocomposite Material For Impedance-Type Humidity Sensors, Mohamed Morsy

HBRC Journal

The development of high-performance humidity sensors based on nanotechnology has become critical for different applications. This work focuses on the fabrication and characterization of impedance-type humidity sensors based on graphitic carbon nitride, titanium dioxide, and carbon nanotubes. The prepared materials comprise g-C3N4, g-C3N4/TiO₂, and g-C3N4/TiO₂/CNTs, which have been synthesized through the co-precipitation method. The properties of the nanocomposites have been verified through different characterization techniques that confirm the phase composition and morphology. The humidity-sensing response of the prepared materials was tested within a humidity range of 11%–97% RH at different testing frequencies. The unique structure of …

A Proposed Model For Assessing The Impact Of Sustainable Practices On The Affordability Of Affordable Housing In Egypt Using Ahp, Ayman M Zakaria Eraqi, Omnia Nagy Abd El-Hafez, Amany Nagy Abd El-Hafez

HBRC Journal

Amid rising inflation and a housing crisis in Egypt, this research develops a model to assess the affordability of sustainable housing for low- and middle-income groups by integrating environmental, social, and economic sustainability criteria. The research methodology used Analytic Hierarchy Process (AHP) to evaluate the relative weights of sustainability criteria in housing projects. Based on their impact on construction costs, these criteria were classified by experts into five main groups: Design Criteria (preliminary studies, initial cost, environmental planning), Neighborhood Criteria (location, design, management), Social and Cultural Criteria (privacy and safety), Natural Resource Sustainability (water, energy), Housing Unit Criteria (design and …

Structural Behavior Of Reinforced Concrete Columns Under Eccentric Loads Strengthened By Steel Jackets Filled With Normal And High-Strength Concrete, Mahmoud Ahmed M. Amin, Mahmoud Mostafa El Hawary, Ahmed Shaheen, Ibrahim M. Mashhour

HBRC Journal

Reinforced concrete (RC) columns are essential structural components in buildings and infrastructure, providing vertical load support and stability. However, these columns can be degraded over time due to various factors, such as environmental exposure, seismic events, and increased loading demands. As a result, the need for effective and reliable column-strengthening techniques arises to ensure the safety, durability, and longevity of structures. The main objective of this study is to investigate how fully strengthening damaged columns affects load-bearing capacity and overall structural performance. Moreover, this study tested thirteen reinforced concrete columns during the experimental program. The original dimensions of these columns …

Finite Element Analysis Of Double-Skin Steel-Concrete Composite Shear Walls With Portal Frames Under Monotonic Shear Loading, Islam Salama, Mahmoud M. Elnahla, Hasan Maaly, Ibrahim T. Arafa

Almaaqal Journal of Sustainability and Emerging Technology

This study investigates the structural performance of double-skin profiled steel-concrete composite shear walls (DSPCW) integrated with portal frames under monotonic shear loading using a validated finite element model. The FE framework, developed in ABAQUS, accurately predicts experimental load-displacement behavior, stress distribution, and failure modes, demonstrating its reliability for parametric exploration. A comprehensive analysis evaluates the effects of steel grade, fastener quantity and distribution, panel openings, and comparative performance against traditional vertical bracing systems. Key findings reveal that DSPCW panels with engineered cementitious composite concrete cores exhibit 1.5–2 times higher shear capacity than conventional braced frames at comparable mass, emphasizing their …

A Generalized Convolutional Autoencoder Framework For Seismic Waveform Compression, Emad B. Helal, Mostafa M. Ibrahim, Ali G. Hafez

Almaaqal Journal of Sustainability and Emerging Technology

Effective data compression methods have become crucial as the amounts of seismic data are growing exponentially. Due to extensive surveys and ongoing real-time monitoring, compression not only reduces storage requirements but also optimizes communication bandwidth between remote seismic stations and central processing hubs. In this paper, a generalized autoencoder-based compression framework is proposed.. Its primary innovation is a single, fixed network architecture that delivers robust performance across low, medium, and high compression ratios (CRs). Performance was compared with a dynamic pooling-based model and three wavelet-based methods (db4, sym8, coif3) across CRs from 2 to 100. Experimental results demonstrate that the …

A Review Of Machine Learning Methods In Energy Management System, Mays Sattar Al-Fatllah, Zaipatimah Ali, Aidil Azwin Zainul Abidin

Almaaqal Journal of Sustainability and Emerging Technology

Traditional energy sources are vital for energizing residences and industries. Nonetheless, they meet considerable obstacles, such as deteriorating infrastructure, ecological decline, resource exhaustion, price fluctuations, and a disparity between real-time demand and supply. Conversely, renewable energy sources offer cleaner and more sustainable energy sources. Renewable energy mitigates the pollution caused by carbon and greenhouse gas emissions in traditional power systems. Incorporating renewable energy into a power system needs an efficient management system to keep stability and improve power use. Modern energy management systems (EMS) face a significant challenge in controlling renewable and non-renewable energy sources. The challenges encompass intermittent and …

Multivariate Optimization Of Nonlinear Response Functions Using Central Composite Design, Hussein M. Hussein, Bassma H. Elwakil, Esraa Abdelhamid Moneer, Sara H. Akl, Yahya H. Shahin

Almaaqal Journal of Sustainability and Emerging Technology

This study addresses critical challenges in multivariate optimization by: (1) developing efficient strategies for optimizing nonlinear response functions in high-dimensional parameter spaces, (2) quantifying comparative performance of traditional versus statistical design methodologies, (3) establishing mathematical frameworks for parameter interactions, and (4) validating results through comprehensive statistical analysis. A dual-phase optimization framework combined One-Variable-At-a-Time (OVAT) screening with Central Composite Design-based Response Surface Methodology (CCD-RSM). Five parameters were evaluated using rotatable CCD (α= 2.378) with 50 design points. Statistical analysis included analysis of variance (ANOVA), regression modeling, interaction quantification, and cross-validation. CCD-RSM demonstrated superior performance with model predictability improving from …

Machine Learning Framework For Automatic Classification Of Nano-Seismic Signals Preceding Earthquakes, Ghada Ali, Ali G. Hafez, Sayed Hasaneen, Hamed Nofel, Nabeel Al-Atwan, Ahmed Mohamed

Almaaqal Journal of Sustainability and Emerging Technology

Nano-seismicity preceding earthquakes has many applications in fault prediction, in structure health monitoring, and in enhancing fault and source parameter determination. Not all earthquakes are preceded by these precursors; therefore, there is a need to identify P-wave arrivals that are preceded by these nano signals, which will eliminate errors in P-wave arrival timing. The current work introduces topologies capable of automatically categorizing the arrivals with nano-seismic precursors. The proposed methods are trained on datasets extracted from stations belonging to Egyptian National Seismic Network (ENSN). These records contain both P-wave arrivals preceded by such nano precursors and other records without these …

Optimizing Bioethanol Production Using Design Of Experiments For Sustainable Biofuel Development, Hussein M. Hussein, Yahya H. Shahin, Ihab A. Moneam

Almaaqal Journal of Sustainability and Emerging Technology

This study presents a statistically optimal approach for bioethanol production from sugarcane bagasse (SCB) using alkaline pretreatment, enzymatic hydrolysis, and fermentation processes. To maximize cellulose yield, four extraction parameters—solvent type, concentration, temperature, and time—were optimized using a Taguchi statistical model. The Taguchi-optimized extraction yields 11.3% increased cellulose recovery relative to cellulose recovered via non-optimized extraction methods (i.e., alkaline treatment with 6% NaOH at 90 °C for 3 hours). This yielded 45.20% cellulose (w/w), with 37.80% weight loss (predicted weight loss was 36.94%). Statistical analysis of extraction results verified solvent type (p = 0.0022) and temperature (p = 0.0007) to be …

A Smart City Transformation Survey: Using Intelligent Buildings To Promote Smart Cities, Salma A. Alhashimi, Majid A. Alwan, Ali N. Aliedani

Almaaqal Journal of Sustainability and Emerging Technology

The challenges of urbanization have been greatly aided by the integration of cutting-edge technology into smart buildings and cities. In smart cities and buildings, machine learning and the Internet of Things are essential for boosting sustainability, increasing safety, and optimizing resource use. In order to enable more effective, connected, and comfortable living in urban settings, this work has introduced the relationship between creative technology and buildings. It also discusses the regulatory frameworks for smart cities and emphasizes the importance of standardization in this regard.