Digital Commons Network^™

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 …

Development Of A Competency-Based Curriculum Through Co-Creation Mechanism To Build High-Skilled Labor Force: Case Studies Of Thailand, Singapore, Germany And South Korea, Panisa Harnpathananun, Somboon Sirisunhirun

Journal of Education Studies

Thailand’s time-based education system still faces limitations in developing 21st Century skills and misalignment with labor market demands. This article analyzes the development of a competency-based curriculum (CBC) through case studies of Thailand, Singapore, Germany, and South Korea, aiming to propose guidelines for enhancing high-skilled labor that corresponds to the needs of the industrial sectors. The study reveals that Thailand has CBC pilot projects such as Work-integrated Learning (WiL), Skill-Mapping, and Higher Education Sandbox. However, it also has key weaknesses, for example, weak tripartite cooperation (government, private sectors, educational institutions), insufficient financial support, inflexible curricula that do not focus on …

Development Of A Learning Activity Package With Integrated Reading Strategies To Promote Reading Literacy Among Lower Secondary School Students, Tasanee Satthaphong, Thassanant Unnanantn

Journal of Education Studies

The objectives of this study were to: 1) develop learning activity packages incorporating integrated reading strategies among lower secondary school students, with a targeted efficiency of 80/80, and 2) examine differences in students’ reading literacy performance before and after the implementation of the learning activity packages. The sample comprised 30 grade 9 students, through multi-stage random sampling, who were enrolled in the first semester of the 2024 academic year at a public secondary school in Bangkok. The intervention was conducted over a period of eight weeks, encompassing a total of 16 instructional periods. The research instruments consisted of 1) four …

The Effects Of Contemplative Facilitation On The Enhancement Of Self-Awareness Among The Elderly: A Case Study Of The Social Welfare Development Center For Older Persons, Chanokporn Suwittayapan, Proetphan Daensilp, Jiraporn Kespichayawattana

Journal of Education Studies

This action research aims to examine a contemplative facilitation process that fosters self-awareness among the elderly. The participants were 10 elderly people from a Social Welfare Development Center for Older Persons in Phra Nakhon Si Ayutthaya Province. Qualitative data were collected through participant observation and in-depth interviews, and data were analyzed using thematic analysis. The results revealed that the developed contemplative facilitation process, grounded in mindfulness cultivation, observation of the body, emotions, and thoughts, and deep listening, comprised eight activity sessions incorporating art-based activities and nature-connected practices. This process led to the development of self-awareness in four main areas: 1) …

Visualizing The Effect Of Process Pause On Virus Entrapment During Constant Flux Virus Filtration, Wenbo Xu, Xianghong Qian, Hironobu Shirataki, Daniel Straus, Sumith Ranil Wickramasinghe

Biomedical Engineering Faculty Publications and Presentations

Virus filtration is an essential unit operation used to validate clearance of adventitious virus during the manufacture of biopharmaceutical products such as monoclonal antibodies. Obtaining at least a 10,000-fold reduction in virus particles in the permeate is challenging as monoclonal antibodies are about half the size of the virus particles. Minute virus of mice, FDA-recommended model adventitious virus, was labeled with a fluorescent dye. Laser scanning confocal microscopy was used to determine the location of virus entrapment within the virus filtration membrane. Three different hollow fiber membranes made of regenerated cellulose and polyvinylidene fluoride were tested. Feed streams consisted of …

Distinct Populations Of Lung Capillary Endothelial Cells And Their Functional Significance, Joel James, Dan Yi, Zhiyu Dai, Et Al.

2020-Current year OA Pubs

The role of the lung's microcirculation and capillary endothelial cells in normal physiology and the pathobiology of pulmonary diseases is obviously vital. The recent discovery of molecularly distinct aerocytes and general capillary (gCaps) endothelial cells by single-cell transcriptomics (scRNAseq) advanced the field in understanding microcirculatory milieu and cellular communications. However, increasing evidence from different groups indicated the possibility of a more heterogeneous nature of lung capillaries. Therefore, we investigated enriched lung endothelial cells by scRNAseq and identified five novel populations of gCaps with distinct molecular signatures and roles. Our analysis suggests that two major populations of gCaps that express Scn7a(Na

Jupiter Mass Binary Objects Show A Minimum Acceleration, Mike Mcculloch

School of Engineering, Computing and Mathematics

Forty-two Jupiter Mass Binary Objects (JuMBOs) have been discovered in the Trapezium Cluster: either brown dwarf stars or planets mutually orbiting in pairs. Here it is shown that, just as in galaxies and wide binaries, the mutual orbits of the objects in each of these twin systems deviate from the Newtonian and level off around a mutual acceleration of 2��2/Θ=2×10−10 m/s2 supporting the minimum acceleration predicted by Quantised Inertia (QI), a theory that attributes inertial mass to an interaction between information horizons and quantum fields and predicts galaxy rotation without the need for dark matter. QI further predicts that the …

Hospital–Medicare Advantage Vertical Integration And Cardiopulmonary Care In Integrated Hospitals, Geronimo Bejarano, Meehir N. Dixit, Alexander P. Philips, Karen E. Joynt Maddox, Meredith B. Rosenthal, Amal Trivedi, David J. Meyers

2020-Current year OA Pubs

No abstract provided.

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 …

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 …

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 …

Allfromair™ Ires (Gen 3) – System Architecture, Process Physics & Compliance Verification, Vesa Olavi Lius

Defensive Publications Series

This disclosure describes the ALLFROMAIR™ IRES (Gen 3), a unified thermodynamic platform integrating heating, cooling, ventilation, and atmospheric water generation (AWG) into a single hardware unit. The system utilizes an ”Anticubic” U-channel geometry with airflow velocities <2.5 m/s to minimize fan power according to the Cube Law. Key innovations include a ”Three-Stage Rocket” thermodynamic process and a ”Turbo Effect” where regenerative pre-cooling reduces compressor temperature lift (\Delta T \approx 5K), enabling practical COPs >30.

The disclosure specifically details a pressure-modulated spray nozzle matrix capable of switching between ”Flash Evaporation” (<300 µm droplets) and ”Film Wetting” modes to maximize latent heat transfer on Heresite P-413/Hydrophilic coated exchangers. The system solves historical displacement ventilation stratification (”The Bahco Problem”) via a scavenger heat exchanger (HX4) coupled to a hydronic floor loop. An integrated ”Water Ring” harvests and purifies condensate to EU Directive 2020/2184 standards, enabling decentralized potable water production for residential, commercial, and tropical applications.

Keywords:

Integrated Regenerative Energy System (IRES), ALLFROMAIR, Anticubic U-Channel, Low Lift Heat Pump, Atmospheric Water Generator (AWG), Pressure Modulated Spray Matrix, Flash Evaporation, Thermodynamic Up-Gearing, Heresite P-413, Hydrophilic Topcoat, Radiant-Assisted Displacement Ventilation, Twin-Leg Air Separation, EU Directive 2020/2184, Three-Stage Rocket Process.

Power-Efficient Speech Detection And Transcription Utilizing Cascaded Visual Triggers And Sensor Fusion, Jon Hurwitz, Yaaseen Mahomed

Defensive Publications Series

Voice interaction is often the primary input modality for wearable electronic devices, such as augmented reality (AR) glasses. However, effective interaction via a voice interface can be difficult in certain common scenarios such as noisy environments, quiet environments where the wearer cannot provide audible spoken input, etc. This disclosure describes techniques that enable adaptive, multi-modal speech-to-text transcription on smart glasses using sensor fusion. The smart glasses include microphones (e.g., a microphone array), a vibration sensor (e.g., in the nose bridge), and low-power cameras that have the wearer’s lips in the field of view. Data streams from these sensors are combined …

Correcting Display Deformations Using A Thermoelectric Cooler Matrix, Kunwoo Park, Sean Terbeek, Yusuf Mohsinally, Harrison Pham

Defensive Publications Series

Temperature variations in the context in which a lenticular display is deployed can result in non-uniform expansion across the display, leading to visual distortion. This disclosure describes techniques to counter non-uniform thermal expansion of a lenticular display due to temperature gradients or other environmental factors. Per the techniques, individual elements of the display are each coupled to a strain gauge and a thermoelectric cooler (TEC). Strains (thermally induced displacements) across the display are provided as input to a microcontroller unit (MCU). The MCU coordinates the matrix of TECs such that individual TECs heat or cool their regions of the display …

Policy-Compliant Generative Artificial Intelligence Deployment Using A Multimodal Critic, Xingyu Federico Xu, Khyatti Gupta, Ágoston Weisz, Felipe Tiengo Ferreira, Anca Dragan, Adilet Zhaxybay, Igor Petrovski

Defensive Publications Series

Generative AI service providers provide access to image generation tools under contractual terms and conditions that require that such tools are used in a compliant way. GenAI service providers can implement guardrails and safety mechanisms to ensure compliance with their terms and conditions, and applicable regulations. However, it is possible for users to bypass such mechanisms and cause a genAI model to generate images that violate the policies of the service provider and/or applicable regulations. This disclosure describes a vision language model (VLM) that detects AI-generated images that violate specified policies. Using preamble-based policy guidelines, the VLM analyzes a generated …

Rack Thermal Topography Gans, N/A

Defensive Publications Series

The technology relates to a framework for designing the thermal layout of compute resource racks to proactively mitigate heat concentration zones and optimize cooling efficiency. The framework utilizes an artificial intelligence (AI) model, specifically a generative adversarial network (GAN), to automate the layout design process. The generative network is configured to ingest physical and operational constraints and produce a simulated layout. The initial layout estimation is then verified by a discriminator network, which acts as a neural network approximation of fluid dynamics, providing a closed-loop feedback mechanism to refine the generated result. The framework allows for the exploration of a …

Deterministic Workflow Generation From Ai-Generated Prototypes, Wai Tai

Defensive Publications Series

Generative artificial intelligence (AI) tools can accelerate workflow prototyping but remain inherently unreliable — the same prompt can yield inconsistent, incomplete, or broken outputs. Proposed herein is an innovation that bridges the gap between AI prototyping and production-grade automation by capturing validated “golden outputs,” extracting them into reusable briefs ("golden briefs"), and regenerating workflows deterministically through template-aware automation. Layered validation, including schema compliance, simulation with golden inputs, and regression testing ensures that every workflow produced is correct, reproducible, and ready for production deployment.

Automated Multi-Modal System For Generating Product Recommendations For Video Advertisements, Satish Shreenivasa, Morgan Brenner, Leigh Purcell Blossom, Xi Li, Briana Wallace

Defensive Publications Series

A system and method for automatically generating a highly relevant list of candidate products from an advertiser’s product catalog to feature alongside a video advertisement are provided herein. The manual process currently used for selecting products is often time-consuming, unscalable, and results in sub-optimal product relevance. The solution provided herein uses an automated, AI-powered approach to identify products featured in a video and then utilizes a two-stage similarity ranking process involving text and image data to find the most contextually and visually similar items in a potentially massive product catalog. This multi-modal approach enhances relevance compared to simple text-based searches …

Process For The Preparation Of 2-{4-[(3s)-Piperidin-3-Yl]Phenyl}-2h-Indazole 7-Carboxamide 4-Methylbenzenesulfonate And Intermediates Thereof

Defensive Publications Series

The present invention provides a process for the preparation of 2-{4-[(3S)-piperidin-3-yl]phenyl}-2H-indazole 7-carboxamide 4-methylbenzenesulfonate represented by the following structural formula-1a and intermediates thereof.

Formula-1a

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 …