Digital Commons Network^™

Talking About Suffering In The Intensive Care Unit, Brent M Kious, Judith B Vick, Peter A Ubel, Olivia Sutton, Jennifer Blumenthal-Barby, Christopher E Cox, Deepshikha Ashana

Center for Medical Ethics and Health Policy Staff Publications

Background: Some have hypothesized that talk about suffering can be used by clinicians to motivate difficult decisions, especially to argue for reducing treatment at the end of life. We examined how talk about suffering is related to decision-making for critically ill patients, by evaluating transcripts of conversations between clinicians and patients' families.

Methods: We conducted a secondary qualitative content analysis of audio-recorded family meetings from a multicenter trial conducted in the adult intensive care units of five hospitals from 2012-2017 to look at how the term "suffering" and its variants were used. A coding guide was developed by consensus-oriented discussion …

Nanoparticle Contrast Agents For Photon-Counting Computed Tomography: Recent Developments And Future Opportunities, Laxman Devkota, Rohan Bhavane, Cristian T Badea, Eric A Tanifum, Ananth V Annapragada, Ketan B Ghaghada

Faculty, Staff and Students Publications

The clinical availability of photon-counting computed tomography (PCCT) has ushered in a new era of CT imaging. Spectral imaging coupled with superior contrast resolution, and ultrahigh spatial resolution (200 μm) offered by PCCT has the potential to revolutionize value-driven imaging. The potential of multicolor PCCT has generated excitement, and renewed interest, in novel contrast agent development for comprehensive disease interrogation, prediction and monitoring of treatment outcomes. Nanoparticles provide a versatile and powerful platform for the development of next generation contrast agents for spectral PCCT. In this article, we review recent developments and use of nanoparticle contrast agents for PCCT. We …

Recognition And Management Of Persistent Chylomicronemia: A Joint Expert Clinical Consensus By The National Lipid Association And The American Society For Preventive Cardiology, Seyedmohammad Saadatagah, Miriam Larouche, Mohammadreza Naderian, Vijay Nambi, Diane Brisson, Iftikhar J Kullo, P Barton Duell, Erin D Michos, Michael D Shapiro, Gerald F Watts, Daniel Gaudet, Christie M Ballantyne

Faculty, Staff and Students Publications

Extreme hypertriglyceridemia, defined as triglyceride (TG) levels ≥1000 mg/dL, is almost always indicative of chylomicronemia. The current diagnostic approach categorizes individuals with chylomicronemia into familial chylomicronemia syndrome (FCS; prevalence 1-10 per million), caused by the biallelic combination of pathogenic variants that impair the lipolytic action of lipoprotein lipase (LPL), or multifactorial chylomicronemia syndrome (MCS, 1 in 500). A pragmatic framework should emphasize the severity of the phenotype and the risk of complications. Therefore, we endorse the term "persistent chylomicronemia (PC)" defined as TG ≥1000 mg/dL in more than half of the measurements to encompass patients with the highest risk for …

Revisiting Icd Therapy For Primary Prevention In Patients With Heart Failure And Reduced Ejection Fraction., Amin Yehya, Jose L Batista, Andrew J Sauer, Jonathan D Davis, Nasrien E Ibrahim, Roderick Tung, Biykem Bozkurt, Gregg C Fonarow, Sana M Al-Khatib

Faculty, Staff and Students Publications

Implantable cardioverter-defibrillators (ICDs) are recommended to reduce the risk of sudden cardiac death (SCD) in patients with heart failure with reduced ejection fraction (HFrEF). The landmark studies leading to the current guideline recommendations preceded the 4 pillars of guideline-directed medical therapies (GDMTs). Therefore, some have questioned the role of ICDs for primary prevention in current clinical practice. In this paper, the authors provide an overview of the current ICD recommendations, including the instrumental clinical trials, the risk of SCD as observed in clinical trials vs real-world scenarios, disparities in ICD use among different patient populations, the impact of contemporary GDMT …

News Mediated Reporting And Governmental Narratives About The Enforcement Of Elite Criminality: Exploring The Social Construction Of Financial Frauds And Discrepancies In Punishment, Dominic J. Zicari

Theses and Dissertations

This study examines how financial crime enforcement decisions are socially constructed through a qualitative content analysis of news articles and government communications pertaining to two specific cases: the Enron scandal of 2001 and the subprime mortgage crisis of 2008. The study was guided by a theoretical framework that utilizes Barak’s (2017) theory of state-routinized crime control. The rigorous analysis of 394 news articles and government communication documents revealed that the media and the state rarely framed the subprime mortgage crisis as a criminal issue. Although the Enron scandal was frequently described as financial crime, journalists and government communicators were often …

Hostos Community College Academic Bulletin 2025-2026, Hostos Community College

College Bulletins

This is the official college catalog for 2025-2026. It contains course descriptions as well as information on degree programs, college resources and services, financial aid, admissions, and the academic calendar.

Mementos, Zixuan Guo

Theses and Dissertations

Relevance:

Personal Relevance: This project merges my passion for film photography and modern technology, aiming to create a design that bridges traditional and modern practices.

Local Relevance: Richmond’s rich historical context provides an ideal setting to illystrate that traditional arts like analog photography can be preserved while integrating modern digital technology.

Global Relevance: Globally, there is an increasing trend toward combining traditional and modern design approaches, particularly in architecture and interior design. Synthesizing analog and digital means is used to meet the balance between materiality and modern technology (Rose, 2014; Pelizzari & Scrivano, 2011). Designers balance tactile materials like wood …

Challenge Based Learning For Social Entrepreneurship Education, Koen Depryck, Ilse Wambacq

Department of Communication Sciences and Disorders Faculty Scholarship and Creative Works

Challenge Based Learning (CBL) provides a promising educational framework for teaching social entrepreneurship, addressing the persistent gap between theoretical knowledge and practical implementation. Through a comprehensive analysis of existing literature and theoretical frameworks, this paper demonstrates how CBL’s seven key elements-authentic challenges, stakeholder involvement, interdisciplinary approaches, student agency, work and life skills development, entrepreneurial mindset cultivation, and impact focus-directly align with and support core social entrepreneurship competencies. The integration of Kolb’s experiential learning theory, Santos’ social entrepreneurship framework, and Rogers’ innovation diffusion theory provide a basis for understanding how CBL can enhance social entrepreneurship education. Evidence suggests that CBL particularly …

Radical Hope Amid Generational Oppression And Puerto Rican Well-Being, Natalia Gomez Giuliani

Theses and Dissertations

Oppressive systems (e.g., colonialism, racism, capitalism) create a disparate distribution of power that, through various mechanisms, negatively impacts the health and well-being of members of the oppressed group. Boricuas have experienced over 500 years of oppression, with the island currently maintaining a colonial relationship with the United States. As these adverse effects of oppression are identified, the need for protective factors (e.g., hope) has emerged. This study explored how islander Boricuas practice radical hope, understand their history of oppression and resistance, and how they perceived it to impact their overall well-being. Utilizing a phenomenological qualitative approach, I conducted 15 semi-structured …

A Systematic Review Of Reading Comprehension Assessment And Intervention In Minimally And Nonspeaking Autistic Children, Grace T. Clark, Madison Skibicki, Gabriella Pesantes

Department of Communication Sciences and Disorders Faculty Scholarship and Creative Works

Up to 25% of autistic individuals are minimally or nonspeaking and require augmentative and alternative communication (AAC). While literacy instruction for this group is increasing, limited research has examined their reading comprehension. This systematic review examined assessment and intervention practices targeting reading comprehension in autistic children who use AAC. A search of five databases yielded 586 articles, of which 6 studies met inclusion criteria. Studies were included if they featured autistic participants under 18 who were minimally or nonspeaking and addressed reading comprehension beyond single-word decoding. Findings varied widely in participant profiles, comprehension targets, and methodological rigor. There is a …

Swarming Segregation: Leveraging Swarm Intelligence And Regionalization As Instruments For School District Desegregation, Jeffrey Wooten

Theses and Dissertations

Even after Brown led to the South briefly having the most diverse schools in the nation, schools throughout the Northeast have remained the most segregated in the nation for decades. While federal jurisprudence has made compelling desegregation pursuant to the Equal Protection Clause more challenging, New Jersey has a particularly favorable landscape to address severe segregation. With a highly diverse, densely populated public enrollment, favorable state constitutional precedent, and a history of successfully compelling desegregation, New Jersey is fertile ground exploring regional desegregation. Scholars, judges, and even plaintiffs in ongoing litigation (Latino Action Network v. N.J.) have called for New …

Learning To Deceive And Persuade: Predictive Agents With Language And Personality Diversity In Social Deduction Games, Aaron M. Shah

Theses and Dissertations

This thesis presents a novel multi-agent architecture that combines Joint Em bedding Predictive Architectures (JEPA), Free Energy Principle (FEP)–inspired planning, and language-based social interaction. The system is evaluated in a custom Werewolf-style hidden-role game, where agents must coordinate, persuade, or deceive under partial observability. Each agent encodes its belief state into a latent representation, predicts future trajectories under candidate actions, and selects votes or eliminations through a planner trained to minimize prediction error. To enable communication, agents are equipped with trainable mouthpieces. A lightweight SpeakerBandit selects from discrete templates using REINFORCE on judge-derived rewards, while a logit-bias head steers a …

An Overview Of Video Game Biometrics Collection And Considerations For Cyberbiosecurity, Lucas Potter, Christen Westberry, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Over the past fifty years, the global cost of consumer electronics has significantly decreased, leading to greater accessibility to both biosensing systems and interactive entertainment platforms. This increased access has naturally resulted in higher usage of medical and entertainment electronics. However, the intersection of these technologies, combined with invasive data harvesting practices, has raised concerns about the potential misuse of biological signals to manipulate individuals' behavior both within and beyond the video game environment. Currently, biometric data in video games are employed in various ways, such as using Heart Rate Variability (HRV) as a performance metric and integrating eye tracking …

Calvin Theological Seminary Academic Catalog 2025-2026, Calvin Theological Seminary

Seminary Academic Catalogs

No abstract provided.

Urinary Ammonium: A Potential Novel Biomarker For Diarrhea Severity In Patients With Ulcerative Colitis, Jared A Sninsky, L Parker Gregg, Mahbubur Rahman, Adith Ram, Jason K Hou

Faculty, Staff and Students Publications

No abstract provided.

Targeting Bone In Cancer Therapy: Advances And Challenges Of Bisphosphonate-Based Drug Delivery Systems, Fariba Ganji, Mohammadmahdi Eshaghi, Hossein Shaki, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: Bisphosphonates (BPs) are well-known for their strong affinity toward bone mineral matrices and are widely used to inhibit excessive osteoclast activity associated with various bone disorders. Beyond their clinical use, their unique bone-targeting capability has positioned them as promising ligands for drug delivery systems aimed at treating bone-related cancers. Approach: The review analyses published studies on BP-functionalized drug delivery systems, including direct drug conjugates, calcium-based nanomaterials, carbon-based nanostructures, and self-assembling systems such as micelles and liposomes. In vitro assays (e.g. hydroxyapatite binding, cell viability) and in vivo biodistribution studies are discussed to evaluate targeting efficiency and …

Land Target Detection Algorithm In Remote Sensing Images Based On Deep Learning, Wenyi Hu, Xiaomeng Jiang, Jiawei Tian, Shitong Ye, Shan Liu

Electrical & Computer Engineering Faculty Publications

Remote sensing technology plays a crucial role across various sectors, such as meteorological monitoring, city planning, and natural resource exploration. A critical aspect of remote sensing image analysis is land target detection, which involves identifying and classifying land-based objects within satellite or aerial imagery. However, despite advancements in both traditional detection methods and deep-learning-based approaches, detecting land targets remains challenging, especially when dealing with small and rotated objects that are difficult to distinguish. To address these challenges, this study introduces an enhanced model, YOLOv5s-CACSD, which builds upon the YOLOv5s framework. Our model integrates the channel attention (CA) mechanism, CARAFE, and …

Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion, thereby improving …

Analyzing Visual Attention In Virtual Crime Scene Investigations Using Eye-Tracking And Vr: Insights For Cognitive Modeling, Wen-Chao Yang, Chih-Hung Shih, Jiajun Jiang, Sergio Pallas Enguita, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

Understanding human perceptual strategies in high-stakes environments, such as crime scene investigations, is essential for developing cognitive models that reflect expert decision-making. This study presents an immersive experimental framework that utilizes virtual reality (VR) and eye-tracking technologies to capture and analyze visual attention during simulated forensic tasks. A 360° panoramic crime scene, constructed using the Nikon KeyMission 360 camera, was integrated into a VR system with HTC Vive and Tobii Pro eye-tracking components. A total of 46 undergraduate students aged 19 to 24–23, from the National University of Singapore in Singapore and 23 from the Central Police University in Taiwan—participated …

Potential Of Lidar And Hyperspectral Sensing For Overcoming Challenges In Current Maritime Ballast Tank Corrosion Inspection, Sergio Pallas Enguita, Jiajun Jiang, Chung-Hao Chen, Samuel Kovacic, Richard Lebel

Electrical & Computer Engineering Faculty Publications

Corrosion in maritime ballast tanks is a major driver of maintenance costs and operational risks for maritime assets. Inspections are hampered by complex geometries, hazardous conditions, and the limitations of conventional methods, particularly visual assessment, which struggles with subjectivity, accessibility, and early detection, especially under coatings. This paper critically examines these challenges and explores the potential of Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) to form the basis of improved inspection approaches. We discuss LiDAR’s utility for accurate 3D mapping and providing a spatial framework and HSI’s potential for objective material identification and surface characterization based on spectral …

A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of Kalman filtering uses the position …

A Customized Large Single-Piece Bifrontal Implant For Post-Craniectomy Defect Reconstruction: A Case Study, Omid Ghaderzadeh, Ehsan Amirbeyk, Seyed Roholah Ghodsi, Zahra Namazi, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background: Large bifrontal defects pose unique reconstruction challenges due to their complex curvature and mechanical requirements. This case demonstrated how computer-aided design/manufacturing (CAD/CAM) enabled precise single-piece polymethyl methacrylate (PMMA) implant fabrication, thereby overcoming traditional limitations. Case presentation: A 25-year-old male who had undergone bifrontal decompressive craniectomy suffered a severe traumatic brain injury. The autologous bone flap had been temporarily stored in a subcutaneous fat area of the abdomen for 3 months to preserve its viability. A secondary cranioplasty was then performed using titanium miniplates and self-tapping screws for final fixation. After 2 years, the patient developed empyema and a brain …

Leveraging Large Language Models To Create Learner Personas For Training Design, N. Lovett, M. Yang, K. Herman, B. Li, M. Sosonkina, W. Purwanto, P. Jiang, M. H. Wu

Electrical & Computer Engineering Faculty Publications

This case examines the innovative use of Large Language Models (LLMs) to generate learner personas for developing learner-centered cybersecurity training materials when direct access to initial learner data is not available. The team developed a nine-stage iterative process for creating and refining AI-generated personas to address this constraint, integrating ethical review, stakeholder feedback, and action research principles. The process expanded upon Kouprie and Visser’s (2009) empathic design framework to ensure cultural responsiveness and mitigate potential biases in LLM outputs. Through multiple refinement cycles, initial generic personas evolved into detailed, context-rich archetypes which informed the development of effective and context-responsive training …

A Proximal Policy Optimization-Based Controller For Enhanced Power Sharing In Microgrids, Seyedmohammad Hasheminasab, Armin Lotfy, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

This paper introduces a Proximal Policy Optimization (PPO)-based virtual impedance (VI) controller to enhance both power sharing and system response under disturbances in inverter-interfaced microgrids. Traditional droop control methods often face challenges due to variations in feeder impedance, which degrade performance. The proposed controller continuously updates its policy based on changes in the operating environment. The control problem is modeled as a Markov Decision Process (MDP), in which the state and action spaces are explicitly defined, and a carefully designed reward function, satisfying system criteria and constraints, guides the learning process toward achieving the desired transient and steady-state performance. By …

Development Of 2d Microfluidics Surface With Low-Frequency Electric Fields For Cell Separation Applications, Madushan Wickramasinghe, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell separation techniques are widely used in many biomedical and clinical applications for the development of screening, diagnosis and therapeutic tests. Current 3D microfluidics-based cell separation methods have limited applications in part due to low throughput and technical complexity. To address these critical needs, we have developed a 2D microfluidics surface which is the miniaturized version of a 3D microfluids cell separation device. Using low-frequency electric fields (1–10 Vpp and 1 kHz–20 MHz), we have first studied dielectrophoresis, AC electro-osmosis and capillary flow within a sessile drop, and finally utilized the results to develop the 2D cell separation surface. Our …

A Novel Intelligent Thermal Feedback Framework For Electric Motor Protection In Embedded Robotic Systems, Mohamed Shili, Salah Hammedi, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

As robotic systems advance in autonomy and sophistication while being used in uncertain environments, the challenge of building reliable and robust electric motors that are embedded into robotic systems has never been a more important engineering problem. Thermal distress caused by extended operation or excessive loading can negatively affect a motor’s performance and efficiency and lead to catastrophic hardware failure. This paper proposes a novel intelligent control framework that includes real-time thermal feedback for hybrid electric motors that are embedded into robotic systems. The framework relies on adaptive control techniques and lightweight machine learning techniques to estimate internal motor temperatures …

Energy-Aware Sensor Fusion Architecture For Autonomous Channel Robot Navigation In Constrained Environments, Mohamed Shili, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

Navigating autonomous robots in confined channels is inherently challenging due to limited space, dynamic obstacles, and energy constraints. Existing sensor fusion strategies often consume excessive power because all sensors remain active regardless of environmental conditions. This paper presents an energy-aware adaptive sensor fusion framework for channel robots that deploys RGB cameras, laser range finders, and IMU sensors according to environmental complexity. Sensor data are fused using an adaptive Extended Kalman Filter (EKF), which selectively integrates multi-sensor information to maintain high navigation accuracy while minimizing energy consumption. An energy management module dynamically adjusts sensor activation and computational load, enabling significant reductions …

Streamer Discharge Modeling For Plasma-Assisted Combustion, Stuart Reyes, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

Some of the popular and successful atmospheric pressure fuel/air plasma-assisted combustion methods use repetitive ns pulsed discharges and dielectric-barrier discharges. The transient phase in such discharges is dominated by transport under strong space charge from ionization fronts, which is best characterized by the streamer model. The role of the nonthermal plasma in such discharges is to produce radicals, which accelerates the chemical conversion reaction leading to temperature rise and ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to develop a predictive model. We examine the important characteristics of streamers that influence combustion and develop some …

A Worker's Struggle, Sakan Binte Imran, Shadman Mahmood Khan Pathan

Electrical & Computer Engineering Faculty Publications

[Introduction] The casualty department at Sir Salimullah Medical College Mitford Hospital was crowded, as it always was. The air smelled of antiseptics, and hurried footsteps echoed through the narrow corridors. It was another day of internship, and I had just finished checking on a patient when a nurse called me over.

“There’s a new case in Trauma. Factory worker. Severe hand injury.”

I hurried over and found a man sitting on the examination table. His face was pale, and his forehead was glistening with sweat. His right hand was wrapped in a blood-soaked cloth. His left hand trembled as he …

Enhancing Cyber Situational Awareness Through Dynamic Adaptive Symbology: The Dass Framework, Nicholas Macrino, Sergio Pallas Enguita, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The static nature of traditional military symbology, such as MIL-STD-2525D, hinders effective real-time threat detection and response in modern cybersecurity operations. This research introduces the Dynamic Adaptive Symbol System (DASS), a novel framework enhancing cyber situational awareness in military and enterprise environments. The DASS addresses static symbology limitations by employing a modular Python 3.10 architecture that uses machine learning-driven threat detection to dynamically adapt symbol visualization based on threat severity and context. Empirical testing assessed the DASS against a MIL-STD-2525D baseline using active cybersecurity professionals. Results show that the DASS significantly improves threat identification rates by 30% and reduces response …