Engineering Commons^™

Modulation Of Prussian Blue Redox Signaling By Molecular Imprinting For Reagent-Free Electrochemical Detection Of Emtricitabine, Abdellatif Ait Lahcen, Gymama Slaughter

Center for Bioelectronics Publications

Reagent-free electrochemical sensors offer significant benefits for rapid, affordable point-of-care drug testing. In this study, we introduce a novel, reagent-free electrochemical sensor based on a molecularly imprinted polymer (MIP) specifically designed for the selective detection of Emtricitabine (FTC), a common antiretroviral used in HIV therapy. The sensor uses laser-induced graphene (LIG) electrodes, renowned for their high conductivity and porosity, ideal for electrochemical sensing. To enable reagent-free operation, the LIG surface was electrochemically coated with Prussian Blue, serving as a redox-active layer. Next, an MIP-PPy film was electropolymerized onto the Prussian Blue surface in the presence of FTC as a template, …

Senescent Fibroblasts In Aging And Pulmonary Fibrosis, Sara B. Palega, Aiwei Y. Borengasser, Yan Y. Sanders

Department of Biomedical and Translational Sciences Faculty Publications

Aging is a major risk factor for many chronic lung diseases, including Idiopathic Pulmonary Fibrosis (IPF), a fatal and incurable disease characterized by progressive fibrotic remodeling. Age-associated structural alterations, impaired regenerative capacity, and dysregulated cellular signaling collectively create a pro-fibrotic microenvironment. A central driver of this pathological shift is the accumulation of senescent cells, which undergo irreversible growth arrest and develop a robust pro-inflammatory senescence-associated secretory phenotype (SASP). Emerging evidence identifies senescent lung fibroblasts as critical mediators of IPF pathogenesis. These cells promote excessive extracellular matrix deposition, myofibroblast differentiation, and tissue stiffening, while simultaneously impairing epithelial regeneration. Together, these effects …

First-Job Contract Review Cheat Sheet, Johanna Jones-Morris, Ashlee Martellacci

Teaching and Learning Resources

This cheat sheet helps first-time employees understand what to review before signing an employment contract. It highlights job duties, compensation, scheduling, employment terms, benefits, restrictive clauses, worker classification, and common red flags so that individuals can ask informed questions and recognize potentially unfair or unclear terms.

Hyperglycemia Detection From Sigle - Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract
Hyperglycemia Detection from Single-Lead ECG using a Hybrid CNN & Transformer Model
Adam Ogunjembola

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes …

Nanosecond Pulsed Electric Fields For Extracellular Vesicle Engineering: From Electro-Exocytosis To Cargo Modulation, Art Neal, Teresa Graham, Mohamadmahdi Samandari, Arash Ghorbannia, Anca Dobrian, Stephen J. Beebe, Ruben M. L. Colunga-Biancatelli

Bioelectrics Publications

Extracellular vesicles (EVs), including small extracellular vesicles (sEVs) and medium/large extracellular vesicles (MVs), have emerged as promising therapeutic vectors and diagnostic biomarkers across various branches of biomedicine. However, the clinical translation of EV-based technologies remains constrained by persistent challenges in manufacturing: insufficient yield from primary cell sources, limited control over cargo composition, and the absence of scalable, standardized production platforms. Nanosecond pulsed electric fields (nsPEF) represent an emerging biophysical approach that can address several of these limitations. Unlike conventional electroporation, which targets the plasma membrane using microsecond-to-millisecond pulses, nsPEF delivers ultrashort (1–300 ns), high-amplitude (10–300 kV/cm) pulses that penetrate intracellularly …

Preventing G-J Tube Dislodgement - A Device And Communication Innovation, Sarah Clark

2026

Abstract

The Problem: G/J tube dislodgement is a frequent complication in pediatric patients.

Leads to:

• Emergency department visits
• Hospital admissions
• Delays in nutrition/medication

Impact on Patients & Families:

• IV placement (traumatic)
• Radiation exposure
• Overnight hospital stays

Impact on Nurses & System:

• Increased workload (admissions, coordination)
• Occupied inpatient beds for stable patients
• Inefficient care processes

Aims/Objectives Aim: Reduce unplanned G/J tube dislodgements and related hospital utilization.

Objectives: Develop a breakaway connector prototype

Implementation and Evaluation:
Setting: Pediatric inpatient & outpatient system
Participants: Nurses (bedside, GI, IR), caregiver, innovation team
Process: Roundtable discussions → identified workflow gaps Communication/workflow audit Developed …

Gaze Transition Entropy And Automation Trust In Multitasking Workspace, Yusuke Yamani, Austin Jackson, Tetsuya Sato, Feyishola Ashimi, Michael S. Politowicz, Eric T. Chancey, Makoto Itoh

Psychology Faculty Publications

Safe flight operation requires visual scanning across multiple displays in a cockpit, which collectively represent the state of the aircraft and supporting automation. Trust is a crucial factor that drives human-automation interaction, and recent work has suggested a relationship between an operator's visual attention and automation trust. One index that captures predictability of eye movements between different areas of interest is gaze transition entropy. The current work reanalyzed data from Sato et al., which examined eye movement patterns and trust in automation associated with the system monitoring task of the Multi-Attribute Task Battery. Results showed credible positive correlations between the …

A Portable Potentiostat Integrated With A Pt/Zno/Lig Electrode For Non-Enzymatic Glucose Detection, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Continuous glucose monitoring is critical for effective diabetes management; however, conventional benchtop potentiostats are bulky, costly, and unsuitable for decentralized point-of-care (PoC) applications. To address these limitations, this work presents a miniaturized, low-cost electrochemical sensing platform integrating a non-enzymatic glucose sensor with a portable potentiostat. The sensing electrode is based on laser-induced graphene modified with zinc oxide and platinum nanostructures via electrodeposition to enable sensitive glucose detection under physiological conditions. A custom-designed portable potentiostat was developed to control electrode potentials and perform electrochemical measurements, and its performance was experimentally validated against a commercial Metrohm system. Glucose detection was evaluated using …

Nanofibrous Materials And Nanoparticles For Combating Antimicrobial Resistance: Synthesis, Integration, And Translational Perspectives, Rewati Raman Ujjwal, Ashish Dilip Sutar, Rahul Shukla, Gymama Slaughter

Center for Bioelectronics Publications

Antimicrobial resistance (AMR) is a major global health challenge driven by mechanisms such as biofilm formation, efflux pumps, and genetic mutations. Nanoparticulate and fibrous materials have emerged as promising strategies to overcome these limitations through multimodal antimicrobial action and controlled drug delivery. This review highlights recent advances in electrospun nanofibrous systems, including natural and synthetic polymer-based scaffolds, stimuli-responsive nanofibers, and functionalized patches. Nanoparticle-loaded nanofiber systems demonstrate enhanced performance, including bacterial eradication, sustained drug release, and significant biofilm disruption. Multifunctional systems combining antimicrobial, antioxidant, and immunomodulatory properties further show synergism. Emerging innovations, such as piezoelectric and smart sensing systems, enable self-powered …

Osmotic Dilators Vs. Foley Balloons: Bayesian Secondary Analyses Of The Dilafol Trial, Antonio F. Saad, Elenir B. C. Avritscher, Claudia Pedroza, Xiao Han, George R. Saade

Department of Obstetrics & Gynecology Faculty Publications

Background: Dilapan-S, a synthetic osmotic dilator used for pre-induction cervical ripening, has proven to be as effective as the Foley balloon in terms of vaginal versus cesarean delivery and has been associated with increased patient satisfaction. Nevertheless, its ability to lower cesarean rates and its cost-effectiveness remain poorly studied.

Objectives: To estimate the likelihood that synthetic osmotic dilators reduce cesarean deliveries and to evaluate their health system costs (2026 US$) and incremental cost-effectiveness compared to the Foley balloon during cervical ripening.

Study Design: Secondary Bayesian analyses were conducted using data from the single-center DILAFOL randomized controlled trial, which enrolled 419 …

Circulating Biomarker Results From A Phase 2 Study Of Seralutinib In Pulmonary Arterial Hypertension, Robin Osterhout, Athénaïs Boucly, Raymond L. Benza, Richard N. Channick, Kelly M. Chin, Robert P. Frantz, Anna R. Hemnes, Luke S. Howard, Vallerie V. Mclaughlin, Olivier Sitbon, Jean-Luc Vachiéry, Rotham T. Zamanian, Richard Aranda, Matt Cravets, Zhaoqing Ding, Thao Duong-Verlé, David Mattola, Robert F. Roscigno, Ravikumar Sitapara, Lawrence S. Zisman, Jean-Marie Bruey, Hossein-Ardeschir Ghofrani

Department of Medicine Faculty Publications

[Introduction] To the Editor: Pulmonary arterial hypertension (PAH) is a progressive disease characterized by obstructive pulmonary arterial remodeling (1). Seralutinib, an investigational inhaled tyrosine kinase inhibitor, potently and selectively targets kinases relevant to PAH pathobiology including platelet-derived growth factor receptors (PDGFR) α and β, colony stimulating factor 1 receptor (CSF1R), and mast/stem cell growth factor receptor kit (c-KIT) (2). In preclinical models, seralutinib improved cardiopulmonary hemodynamics, reversed pulmonary vascular pathology and decreased right ventricular hypertrophy (3). In TORREY, a phase 2, multicenter, double-blind, randomized, placebo-controlled trial in PAH, seralutinib significantly reduced pulmonary vascular resistance (PVR) after 24 weeks with good …

Micro- And Nanoplastics: A Paradigm Shift In The Pathogenesis Of Inflammatory Bowel Disease, Michael Saadeh, Priyata Dutta, Gordon Hong, Edward Oldfield, David A. Johnson

Department of Medicine Faculty Publications

Micro- and nanoplastics (MNPs) are pervasive environmental contaminants with growing recognition as potential contributors to human disease. Widespread human exposure occurs primarily through ingestion of contaminated food and water, and MNPs have been detected in multiple human tissues, including the gastrointestinal tract. Experimental evidence provides a plausible biological basis for disease associations, including impairment of intestinal barrier integrity, activation of mucosal immune pathways, and alteration of gut microbial communities caused by MNP exposure. Although human data remain limited, early studies demonstrate MNP detection in stool and suggest potential correlations with inflammatory biomarkers such as fecal calprotectin. These findings, together with …

Recent Insight And Perspective Of Marine-Inspired Biopolymers For Wound Healing Applications - A Review, Muhammad Umar Aslam Khan, Saiqa Yousaf, Abdalla Abdal-Hay, Mohd Faizal Bin Abdullah, Sahar Madani, Muhammad Shahzad Zafar, Goran M. Stojanović, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

There is an increasing necessity for advanced, sustainable, and biocompatible materials for wound healing as therapeutic and diagnostic products. Marine environments, characterized by high biodiversity, offer an underutilized source of natural resources with enormous potential for creating novel materials for dressings. This review highlights the revolutionary nature of polymeric biomaterials of marine origin, with a focus on polysaccharides, like alginate, chitosan, and carrageenan; proteins, such as collagen and gelatin. These biopolymers are outstanding in their physicochemical properties, such as biodegradability, bioactivity, and modifiable mechanical strength, which enable their use in wound-healing systems. Besides, these biomaterials may be easily chemically and …

Pin-Plane Electrical Discharge Driven By A Mosfet Dc Current Source, Myles Perry, Sidmar Holoman, Daniel Wozniak, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

The generation of atmospheric pressure nonequilibrium plasma using electrical discharges is an active area of research due to its significance in a wide spectrum of applications including medicine, combustion, and manufacturing. In our attempt to create a helium plasma jet in a pin-plane discharge with a constant current source, we observed self-pulsating behavior. We present the results of the electrical, optical, and spectroscopic measurements carried out to characterize the discharge. The duration of the discharge is a few tens of nanoseconds, and the repetition rate is in the few tens of kHz. The effect of the gap distance and gas …

Healthcare Digital Twins: A Methodological Literature Review On Integrating Iot And Ai For Personalized Medicine And Predictive Care, Sara Shahnazinia, Mahsa Tavasoli, Abdolhossein Sarrafzadeh, Ali Karimoddini

Electrical & Computer Engineering Faculty Publications

Digital Twin (DT) technology has the potential to revolutionize healthcare delivery and enhance patient outcomes through personalized and precision medicine, simulation models for operations and interventions, and drug discovery. However, successful implementation of DTs in Internet of Things (IoT) and artificial intelligence (AI) healthcare is contingent upon addressing key challenges such as privacy, ethics, and robust data security. This paper presents a methodological literature review of DT applications in healthcare, systematically analyzing the current state of research, key enabling technologies, and implementation challenges. The review summarizes DT categorization approaches (application-based, technology-based, and real-time function-based); delineates core DT components such as …

Application Of A Hyaluronic Acid-Based Lotions Containing Hydroxyapatite Nano-Particles Approach For Treatment Of Initial Dental Caries, Zahra Gharavi, Zahra Namazi, Fatemehsadat Pishbin, Helia Givian, Maryam Torshabi, Farhood Najafi, Parisa Amdjadi

Electrical & Computer Engineering Faculty Publications

This study evaluated the remineralization potential of a ceramic–polyelectrolyte system, based on a novel combination of hydroxyapatite nanoparticles (HAp NPs) and a hyaluronic acid (HY) matrix, for dental enamel, a tissue that remains challenging to repair in clinical dentistry. Nano-Hydroxyapatite (nanoHAp) powder was synthesized and characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FE-SEM), dynamic light scattering (DLS), and zeta potential analysis to confirm their crystalline structure, functional groups, morphology, particle size distribution, and colloidal stability. HY-based suspensions (remineralizing lotions) containing 5, 10, and 12 wt% of the synthesized nanoHAp particles were formulated via a …

Beyond The Square Pulse: Waveform Shape, Eeg Correlates, And The Pursuit Of Natural Sensation In Tens, Jason Whitson

Honors Undergraduate Theses

This study investigates the relationship between electrical stimulus characteristics of shape and charge on evoked sensations and electroencephalogram (EEG) data during multi-waveform transcutaneous electrical nerve stimulation (TENS) of the median nerve. Neuromodulation methods have traditionally had little control over the location and quality of their associated evoked sensation (e.g., electric, vibration, touch). This experiment utilized five unique stimulus waveforms during TENS stimulation. EEG data were collected concurrently to provide an introductory objective measure of the neural responses underlying these sensory changes. Eleven participants completed three tasks (thresholding, super-threshold stimulation, two-alternative forced choice) using a two-electrode TENS approach. Stimulus waveforms were …

A Chicken Model For Non-Invasive Diagnosis Of Infant Developmental Dysplasia Of The Hip (Ddh) Using Acoustic Transmission Measurements, Aliza Shah

Honors Undergraduate Theses

Developmental dysplasia of the hip (DDH) is a condition characterized by abnormal development and stability of the hip joint. In a healthy infant, the femoral head (ball) fits securely within the acetabulum (socket of the pelvis), allowing for proper joint function. In DDH, the relationship is disrupted, ranging from mild acetabular dysplasia to partial (subluxation) or complete dislocation of the femoral head. This condition represents a range of structural abnormalities that develop during early growth. The integrity of the hip joint is essential for physical mobility, and disruption of this structure can lead to significant functional impairment. DDH may result …

Preventing G/J Tube Dislodgement: A Device And Communication Innovation, Sarah Clark

2026

The Problem
G/J tube dislodgement is a frequent complication in pediatric patients
Leads to:

• Emergency department visits
• Hospital admissions
• Delays in nutrition/medication

Impact on Patients & Families:

• IV placement (traumatic)
• Radiation exposure
• Overnight hospital stays

Impact on Nurses & System:

• Increased workload (admissions, coordination)
• Occupied inpatient beds for stable patients
• Inefficient care processes

Aims/Objectives
Aim: Reduce unplanned G/J tube dislodgements and related hospital utilization.
Objectives: Develop a breakaway connector prototype

Implementation and Evaluation
Setting: Pediatric inpatient & outpatient system
Participants: Nurses (bedside, GI, IR), caregiver, innovation team
Process:
Roundtable discussions → identified workflow gaps
Communication/workflow audit
Developed device …

Privacy-Preserving Federated Learning With Optimized Ensemble Weighting And Knowledge Distillation For Covid-19 Detection From Non-Iid Medical Imaging Data, Richard Annan, Hong Qin, Robert Newman, Madhuri Siddula, Letu Qingge

Computer Science Faculty Publications

Medical imaging enables rapid and accurate diagnosis of COVID-19, with CT scans proving especially effective. However, data privacy concerns limit collaborative model development across hospitals. To address this issue, we introduce a novel federated learning framework. It is referred to as Independent Knowledge Distillation with post-Ensemble Federated Learning (IKDEFL). Differential Privacy (DP) is integrated into the framework to improve privacy guarantees. Three DP mechanisms are evaluated. These include Fixed Gaussian, Gaussian Adaptive, and Tree Adaptive. The evaluation has been conducted on heterogeneous and Non-Independent and Identically Distributed (Non-IID) datasets. These datasets reflect real-world hospital scenarios. Results show that IKDEFL significantly …

A Comparative Analysis Of Explainable Ai (Xai) Techniques For Transparent And Reliable Image Classification, Sovon Chakraborty, Shakib Mahmud Dipto, Kevin R. Pilkiewicz, Michael L. Mayo, Pratip Rana

Computer Science Faculty Publications

Evaluating the trustworthiness of black-box machine learning models remains a significant methodological challenge. Their lack of transparency and interpretability limits applicability, because stakeholders often seek transparency before trusting the results of black-box machine learning models. Explainable AI (XAI) methods provide for human-understandable justifications and informed decision-making of these black-box architectures. Therefore, it is imperative to select the proper XAI model tailored to specific tasks. In this research, we focus on examining four XAI techniques: PEEK, LRP, GRAD-CAM, and LIME to understand how they perform against each other for image classification tasks. We evaluate the performance, robustness, generalizability, noise stability, and …

Isotropic Shrinkage Of Patterned Vacancies Enables Three-Dimensional Nanoprecise Metastructures For Visible Light Applications, Quansan Yang, Gaojie Yang, Takahiro Nambara, Hiroyuki Kusaka, Yuichiro Kunai, Alex C. Matlock, Corban Swain, Brett Pryor, Yannick Salamin, Daniel Oran, Hasindu Kariyawasam, Ramith Hettiarachchi, Dushan Wadduwage, Marin Soljačić, Peter T. C. Soflaei, Edward S. Boyden

Computer Science Faculty Publications

Three-dimensional metastructures with nanoscale feature sizes exhibit unique properties compared with structures with larger feature sizes, but are difficult to fabricate. Here we introduce implosion carving (ImpCarv), a method for photopatterning vacancies of complex geometry throughout materials, followed by isotropic shrinkage (>10-fold). ImpCarv works by photoactivating sensitizers to generate reactive oxygen species that cleave a swollen hydrogel at defined points, followed by controlled shrinkage via dehydration. ImpCarv creates three-dimensional metastructures where the refractive index of each point throughout a material can be specified with nanoscale precision via material presence or absence. By leveraging refractive index programmability for precise phase …

Adaptive Self-Attention For Enhanced Segmentation Of Adult Gliomas In Multi-Modal Mri, Evan P. Savaria, Jiangwen Sun

Computer Science Faculty Publications

Every year there are an estimated 80,000–90,000 new glioma cases, highlighting the need for reliable imaging-based decision support. Although deep learning has improved tumor sub-region segmentation, many state-of-the-art models fail to fully capture complementary information across T1, T1Gd, T2, and FLAIR MRI modalities and often operate as “black boxes,” limiting physician trust when precise delineation is critical for surgical planning, radiation targeting, and treatment monitoring. To address these limitations, we propose AIMS, an Adaptive Integrated Multi-Modal Segmentation framework that maintains modality-specific feature streams and employs adaptive self-attention within a hierarchical CNN-Transformer architecture to prioritize and fuse multi-modal MRI features. We …

Designing Narrative-Based Ai Assistance For Sensemaking In Collaborative Environments: Case Studies In Education And Dementia Care, Dylan Edward Moore

Dartmouth College Ph.D Dissertations

This thesis addresses a gap in the human-computer interaction literature regarding the design, development, and evaluation of narrative-based AI assistance for collaborative, complex problem solving. I explore this design space through three case studies across the domains of education and dementia care. This work encompasses multi-year industry partnerships and longitudinal fieldwork, user-centered design, dataset curation, model training, and system evaluation.

Specifically, the first case study considers a story-based web platform for teaching AI literacy through peer-generated, personalized narrative scaffolding. Learners on the platform showed significant knowledge gains and other learning-related outcomes. To describe the novel design of this system, I …

Cognitive Load Classification Using Functional Near-Infrared Spectroscopy, Pratham Shah

Theses and Dissertations (Comprehensive)

This thesis investigates the classification of cognitive load using functional near-infrared spectroscopy (fNIRS) signals recorded during an N-back working memory task. The study introduces a novel short-channel correction layer designed to suppress superficial physiological noise adaptively, addressing limitations of traditional General Linear Model (GLM) based regression. A single participant dataset comprising 69 validated sessions was analyzed using both conventional machine learning and deep learning approaches. Traditional classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Random Forests, and Gradient Boosting were first evaluated using statistical features (mean, variance, peak, and slope). Among these, Gradient Boosting achieved the highest accuracy (55.6%), …

Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra

Theses and Dissertations (Comprehensive)

Effective and interpretable classification of medical images remains a critical challenge in computer-aided diagnosis, particularly in data-scarce and resource-constrained clinical settings where traditional deep learning models prove impractical. This study addresses the fundamental barrier to Vision Transformer adoption in medical imaging—massive parameter counts and data requirements—through a systematic two-phase methodology. Phase 1 evaluates three spline-based Kolmogorov–Arnold Network (KAN) variants to identify the optimal nonlinear approximation function for parameter-efficient medical image classification: SBTAYLOR-KAN (B-splines with Taylor series), SBRBF-KAN (B-splines with Radial Basis Functions), and SBWAVELET-KAN (B-splines with Morlet wavelets). Comprehensive experiments across brain MRI, chest X-rays, and tuberculosis datasets—without any image …

Health Risk Assessment (Hra) In Home-Based Ironing Businesses: Risk Identification, Intervention, And Evaluation In Johar Baru District, Central Jakarta, Heru Alfares, Irawadi Darmaputra, Marsen Isbayuputra, Muhammad Ilyas

Occupational and Environmental Medicine Journal of Indonesia

Background Home-based ironing businesses in Johar Baru District, Central Jakarta, are part of the informal sector, vulnerable to health risks due to suboptimal working conditions. This study aims to identify, assess, and control health risks through a Health Risk Assessment (HRA) approach.

Methods Research methods include direct observation, interviews, environmental measurements, health screenings, and ergonomic surveys using the BRIEF (Baseline Risk Identification of Ergonomic Factor) instrument.

Results The results indicate that the temperature in the ironing area reaches 33°C, exceeding the comfort standard, and that 80% of workers have dark yellow urine, indicating a high risk of dehydration. Risk assessment …

A Study Of Perceptions, Readiness, Benefits, And Barriers Related To Exoskeleton Adoption In New Jersey’S Warehousing Sector, Terry Asante

Theses

The warehousing industry in New Jersey remains a vital component of the region's logistics network, employing more than 200,000 workers who routinely engage in lifting, bending, overhead reaching, and other physically demanding activities. These exposures contribute to musculoskeletal disorder (MSD) rates that exceed national averages, particularly affecting the low back and shoulders. Nationally, MSDs account for an estimated $420 billion in combined direct and indirect costs each year, underscoring the need for interventions that can effectively reduce biomechanical strain. Industrial exoskeletons have emerged as a potential solution, with prior research demonstrating reductions in muscle activation, perceived exertion, and fatigue during …

Uji Kelayakan Teknis Dan Performa Auvest: Rompi Pendingin Otomatis Berbasis Wearable Thermoelectric Cooler Untuk Mitigasi Risiko Heat Stress, Muchammad Adam Wildan, Amelia Avril Rayhana, Nadia Hanifan Nabila, Bian Shabri Putri Irwanto

National Journal of Occupational Health and Safety

Heat stress is a serious threat to construction workers that can reduce productivity and even threaten lives. Existing cooling vest innovations still have limitations, such as weight, manual systems, and the risk of leakage. This study aims to analyze the effectiveness of the Automatic Vest (AUVEST), an automatic cooling vest based on Wearable Thermoelectric Cooler and the Internet of Things (IoT), in preventing the risk of heat stress. The method used is experimental with trials on one construction worker in indoor and outdoor environments. AUVEST is equipped with temperature sensors (DS18B20, TMP102) and humidity (DHT11), whose data is processed by …

Using Machine Learning To Predict Women At Risk Having A Child With Congenital Heart Defects, Amany M. Abdo Prof., Asmaa M. Mosallam Ms., Laila M. Abdelhamid Assoc.Prof.

Information Systems

Congenital heart defects (CHD) are heart malformations present at birth, affecting heart function and circulation, and are a leading cause of infant mortality. CHD can result from genetic, environmental, and maternal health factors, making early detection essential. Early diagnosis allows for timely intervention, reducing risks like heart failure or stroke. In countries like Egypt, CHD often remains undiagnosed due to limited healthcare resources. Artificial intelligence (AI) can improve early detection by analyzing risk factors. This study presents a predictive model for CHD using maternal and paternal health factors. Data was collected from 571 families: 260 with a CHD-affected child and …