Digital Commons Network^™

Design, Optimization, And Techno-Economic Analysis Of A Standalone Pv-Wind-Battery Microgrid For A Remote Load In Kurdistan Region Of Iraq, Harwan Mohammed Taha, Laith Akram Mohammed

Mansoura Engineering Journal

Standalone microgrids play a crucial role in rural areas where grid electricity delivery is difficult and expensive. This research verifies the effectiveness of a standalone microgrid in a rugged area, Pers Mountain in Akre district, Duhok governorate, Iraqi Kurdistan. A first hybrid renewable energy system (HRES)-based standalone microgrid is presented to supply a remote load. Solar and wind energy are employed for their reliability, sustainability, and abundance, with battery storage ensuring continuous power when solar and wind are unavailable. Simulation results demonstrate reliable power supply during summer months (loss of power supply probability < 5%), with the system operating across three modes — PV-dominant daytime, combined wind-battery evening, and battery-discharge nighttime. The inverter achieved minimum total harmonic distortion of 1.53% for both current and voltage outputs, below the IEEE 519 limit. A full-year hourly particle swarm optimization (PSO) sizing analysis assessed annual reliability and each source's economic contribution: the original fixed sizing yields an annual loss of power supply probability (LPSP) of 26.80% (expected energy not served ~1,471 kWh/year), motivating a PSO-optimized PV-battery configuration achieving annual LPSP of 5% (~274 kWh/year unserved) at comparable cost. The site's wind resource is reasonable (13.8% capacity factor), but the fixed tower and controller cost outweighs its contribution at this small scale. The proposed HRES totals $11,960–$16,317 depending on configuration, approximately 28–38 times lower than grid extension ($455,600) to the site, while producing zero CO₂ emissions and avoiding approximately 4,189 kg/year versus an equivalent HOMER Pro-simulated diesel generator.

Reconfiguring Environmental Design Thinking: Artificial Intelligence As A Cognitive Partner In Sustainable Architecture – A Novel Hybrid Framework And Empirical Validation Study, Walaa Hussein Hussein Hanafi

Mansoura Engineering Journal

This study develops and empirically validates a Hybrid Cognitive Design Framework (HCDF) that integrates artificial intelligence, parametric design, and environmental simulation as a cognitive partnership system for sustainable architectural design. The research addresses a gap in existing studies, which have largely focused on the functional benefits of AI while giving limited attention to its influence on designers’ cognitive and ethical decision-making. A quasi-experimental study was conducted with 30 architecture students divided into two groups: an HCDF-assisted group and a traditional design group. Participants were tasked with designing a self-sufficient residential neighbourhood in Toshka, Egypt. Data were collected using Think-Aloud Protocol …

Harmonic Mitigation And Reactive Power Support Using Dpfc And Upfc In Grid‑Connected Solar Pv Systems: A Comparative Performance Evaluation, Abhishek Vashistha, Dharmbir Prasad, Rudra Pratap Singh

Mansoura Engineering Journal

Harmonic distortion, reactive power imbalance, and voltage instability represent major challenges regarding the power quality of grid-connected solar photovoltaic (PV) systems. Various recently developed flexible AC transmission system (FACTS) devices such as the unified power flow controller (UPFC) and distributed power flow controller (DPFC), however, have made them possible solutions but still do not provide a quantitative comparison in similar dynamic conditions. In this paper, comparative performance analysis of UPFC and DPFC in 3 MW grid connected solar PV system using Matlab Simulink is presented. The two controllers are affected by same disturbances, namely irradiance step change at t = …

Performance Enhancement Of A Fully Integrated Solar Still Using Flat Plate Collector, Reflector, And Evaporative Cooling System, Joe Patrick Gnanaraj Sundararaj, Vanthana Jeyasingh

Mansoura Engineering Journal

Water scarcity has become a major global concern due to increasing population growth, industrialization, and depletion of freshwater resources. Solar desalination is considered an eco-friendly and sustainable solution, especially for rural and off-grid regions where conventional water treatment facilities are limited. However, conventional solar stills suffer from low productivity, which restricts their practical application. In this study, a fully integrated solar still system was designed and fabricated by incorporating a flat plate collector, front-wall reflector, and passive evaporative cooling arrangement. The system was experimentally tested under natural climatic conditions over seven consecutive days to evaluate temperature variation, distillate yield, and …

A Hybrid Geoid Model For The Perlis Region, Malaysia Based On Cadastral Reference Marks And A Geometric Approach, Muhammad Aiman Haiqal Abdul Malek, Muhammad Faiz Pa’Suya, Ramazan Alpay Abbak, Ami Hassan Md Din, Noorfatekah Talib

Mansoura Engineering Journal

This study presents the development of a high-resolution local geoid model for the Perlis region, Malaysia, using a geometric approach that integrates GNSS-levelling benchmarks with Cadastral Reference Mark (CRM) data. A total of 38 GNSS-levelling benchmarks were used as reference points, while 3,725 CRMs were incorporated to significantly enhance spatial coverage for geoid modelling. Orthometric heights at the CRM points were first determined by transferring heights from the reference benchmarks using gravimetric geoid information. Subsequently, geometric geoid heights were computed from the differences between ellipsoidal and orthometric heights. Five interpolation techniques were evaluated to generate the geometric geoid surface, namely …

Secondhand Books Industry Between Extinction And Challenges Of The New Millennium: Insights Urban And Architectural Considerations From Al-Azbakeya Book Market., Ahmed M. Selim, Heba M. Gaber, Nehal M. Elmahdy

Mansoura Engineering Journal

At the beginning of the 21st century, the printed and secondhand book industry has faced enormous challenges, particularly after the COVID-19 pandemic, when book consumers sought to engage directly with e-books. The Azbakeya Book Market in Egypt is one of the markets that confronts this challenge, while maintaining its distinctive historical character. This study aims to rehabilitate the secondhand book market in Al-Azbakeya district as a model that simulates the potential urban and sustainable architectural design strategies for reviving this industry. The study framework was comprised into four sections. First, "desk-based research" was conducted to discuss the secondhand book industry …

Comparative Finite Element Method-Based Optimisation Of Coir Fibre Laminates: Aluminium Skins Versus Carbon Cloth Skins, Muhamed Swaleh Ahmed, Bernard Wamuti Ikua, Abel Nyakundi Mayaka

Mansoura Engineering Journal

Natural fibre composites offer a sustainable alternative to conventional composite materials. Their mechanical efficiency is influenced by laminate structure and skin material selection. This study presents a comparative finite element analysis and optimisation of coir fibre-reinforced laminates employing either aluminium skins or carbon cloth skins. COMSOL Multiphysics was used to determine their mechanical response. Optimisation was performed using the BOBYQA algorithm to enhance load sharing between the coir core and skin materials. Results indicated that aluminium-skinned laminates achieve superior compressive and flexural performance, achieving a peak compressive strength of 210 MPa and sustaining a flexural load of 0.65 kN at …

An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare

Mansoura Engineering Journal

The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …

Framing Inclusive Heritage Urbanism Reconfiguring Publicness In Mosque-Centered Precincts In Historic Cairo, Ghada Sayed Ghazala

Mansoura Engineering Journal

Mosque-centered precincts in historical cities face a continuous tension between touristic-led redevelopments, security management policies and urban life of commons. Recently in Historic Cairo state-led interventions occur in major mosque-centered settings with upgrading intent by enhancing visual order, crowd control and visitors’ experience, yet socio-spatial inclusivity stayed insufficiently incorporated in those implications. This study discourses this gap by initiating the Heritage Socio-spatial Inclusivity Framework (HSIF) to assess inclusivity across major mosque-centered realms – AL-Hussein Mosque & Al-Sayida Zeinab Mosque precincts -

HSIF synthesized urban design & heritage conservation concepts through indicators covering aspects like communal livability, users experience, governance & …

Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy

Mansoura Engineering Journal

Concrete is essential for construction due to its high strength and durability. It supports most modern infrastructure globally. Cement production is a major source of CO₂ emissions, posing serious environmental concerns. Additionally, the rising demand for concrete is straining the limited supply of essential raw materials, such as aggregates. Researchers are examining alternative materials to improve Sustainability while maintaining structural strength to address these issues. This research aims to improve concrete performance by enhancing cement durability with nano-silica. Coconut shell, an agricultural by-product, functions as an eco-friendly alternative to conventional coarse aggregates, alleviating their scarcity. Microbiologically induced calcium carbonate precipitation …

A Machine Learning–Based Framework For Traffic Classification And Threshold-Based Load Management In 5g Network Slicing, Safi Ibrahim, Younis S. Younis, Kamal S. Hamza, Mohamed M. Ashour

Mansoura Engineering Journal

This study proposes a machine learning–based framework that applies machine learning techniques to improve the efficiency of 5G network slicing through automated traffic classification and threshold-based load management . The proposed model optimizes resource allocation among the three standardized 5G slice types: enhanced Mobile Broadband (eMBB), ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC). Two supervised learning algorithms—K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)—are trained using Quality of Service (QoS) parameters such as packet delay, loss rate, and Quality Class Identifier (QCI). Experimental evaluations were conducted on two large-scale datasets containing over 400,000 traffic instances, demonstrating that the …

A Dual-Domain Face Forgery And Deepfake Detection Framework, Neha Pradyumna Bora, Pradyumna Mulchand Bora, Rushikesh Sanjay Kumavat, Raunak Manoj Gangwal, Prit Sandesh Jain, Hardik Vijay Ostwal

Mansoura Engineering Journal

Concerns about media authenticity, privacy, and information security arising from rapid advances in deepfake technology have made it increasingly important to detect manipulated facial content reliably. The primary goal of our work was to develop a deepfake detection model with high generalization across multiple datasets. To achieve this, we developed a hybrid detection approach that combines spatial visual texture analysis and frequency-domain analysis to detect manipulated facial images. Our approach includes convolutional spatial feature extraction from facial images and frequency—domain representations of the same images obtained by applying the fast Fourier transform. To help alleviate concerns about overreliance on frequency—domain …

Advancing Ultrahigh Carbon Steel Characterization: A Metaheuristic-Tuned Deep Learning Approach, Walaa Omar El-Farouk Badr, Hossam El-Din Mostafa, Rania Elbana

Mansoura Engineering Journal

Accurate classification of ultrahigh carbon steel (UHCS) microstructures is essential for elucidating processing-structure-property relationships and enhancing material performance. While convolutional neural networks (CNNs) offer powerful automated classification, navigating their complex, high-dimensional hyperparameter spaces present a significant computational bottleneck. To advance automated materials characterization, this study proposes a metaheuristic-tuned deep learning approach for robust and efficient microstructure classification. Two architectures, VGG16 and MobileNetV2, were evaluated under both pretrained and fine-tuned configurations, with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Ant Colony Optimization (ACO) applied for systematic hyperparameter tuning. Results show that GA substantially improves the performance of fine-tuned VGG16, achieving …

Edge Guided Channel Attention In Fsrcnn: A Novel Approach For Depth Super Resolution, Yagneshkumar Jayantilal Parmar, Paresh M. Dholakia

Mansoura Engineering Journal

Depth images from low-cost sensors often suffer from blurred edges and structural distortions when processed with standard super-resolution models. While FSRCNN is efficient for RGB images, it struggles to handle the unique geometric requirements of depth maps. To solve this, we propose the Edge Guided Channel Attention FSRCNN (EGCA FSRCNN). This method incorporates an edge-guided modulation mechanism to preserve object boundaries and a Squeeze and Excitation (SE) block to focus on critical structural features. A major benefit of this framework is the use of frozen, pretrained FSRCNN weights, which bypasses the requirement for retraining. Our evaluation on the UTKinect, Middlebury, …

Multi-Method Energy Optimization: Linear Programming, Hmm Modeling And Arduino-Based Simulations, A.E. El-Alfy, Eman Elayat, M. A. E. Sheta

Mansoura Engineering Journal

This paper presents the simulation and optimization of hybrid energy systems integrating renewable energy and storage technologies. Linear Programming (LP) is utilized to minimize operational costs, while a Hidden Markov Model (HMM) improves reliability by accurately predicting energy flow. Hardware-in-the-loop simulation in Proteus demonstrates efficient energy trading, significantly reducing dependence on conventional sources. The results from a 24-hour analysis show that the system achieves an 87.14% load factor, indicating high efficiency in utilizing the system's rated capacity, 26.23 system reliability, and a 20% improvement in cost efficiency and enhanced sustainability, providing a robust and practical framework for hybrid energy solutions …

Trident-Bladder: A Resolution-Aware Multimodal System For Robust, Calibrated Bladder Cancer Diagnosis Across Endoscopy, Histopathology, And Liquid Biopsy, K. Sankar, S. Venkata Lakshmi, Gummadi Reshma, V. Gokula Krishnan, M. Ganesan, V. Vijayaraja

Mansoura Engineering Journal

Bladder cancer diagnosis demands the integration of cystoscopy, histopathology, and biomarker testing, yet the majority of AI systems continue to be modality, specific and sensitive to acquisition variations. TRIDENT, Bladder is a resolution, aware multimodal framework that we have developed to address this issue. The method combines cystoscopic lesion segmentation, whole, slide image (WSI) molecular subtype prediction, and urine miRNAclinical data through reliability, weighted fusion and a utility, aware decision policy. The endoscopic branch features a quality, gated super, resolution component, resulting in mDice 87.5, sensitivity 92.1%, precision 91.4%, boundary, F1 85.3%, and ECE 0.023 at 32 FPS. mDice on …

Development Of Enhanced Dingo Optimization Algorithm For Distribution Network Reconfiguration, Samson Oladayo Ayanlade, Ignatius Kema Okakwu, Richard Oladayo Olarewaju, Ayodeji Akinsoji Okubanjo, Joseph Bukola Samson, Oluwadare Adepeju Adebisi, Emmanuel Idowu Ogunwole, Oluwadare Olatunde Akinrogunde

Mansoura Engineering Journal

This paper presents the Enhanced Dingo Optimization Algorithm (EDOA) to reconfigure the radial distribution network with the long-standing problem of active power loss minimization while maintaining a stable and acceptable voltage profile. EDOA enhances the standard Dingo Optimization Algorithm (DOA) through the integration of adaptive search control, elite-guided local refinement, and crossover-based diversity preservation mechanisms tailored for distribution network reconfiguration problems. The proposed method has been tested on two test systems: the IEEE 33-bus standard as well as the real-world Ayepe 34-bus distribution feeder in Ibadan, Nigeria. In the IEEE 33-bus test system, EDOA reduces active power loss by 56.00%; …

Evaluating The Effectiveness Of Hard Coastal Protection Structures For Long-Term Erosion Mitigation, Case Study: Eastern Rosetta Shoreline, Nile Delta, Egypt, Basma Sayed, Ayman Sabry Koraim, Tarek Hemdan Nassrallah, Ahmed Abouelfetouh Abdelaziz, Nada Mansour, Fahmy Salah Fahmy Abdelhaleem

Mansoura Engineering Journal

Coastal erosion threatens densely populated shorelines worldwide. At the Rosetta Promontory (Nile Delta), shoreline retreat has accelerated since the construction of the Aswan High Dam due to reduced fluvial sediment supply. This case study numerically evaluates shoreline response to six hard-protection scenarios along the eastern promontory, combining groins and detached breakwaters, over a 20-year forecast (2022–2042). Offshore wave conditions were transformed to nearshore hydrodynamics using MIKE21 Spectral Wave, and long-term shoreline evolution was simulated with DHI-LITPACK. The numerical models were forced using a 40-year wave dataset derived from the ECMWF ERA5 reanalysis. Results indicate that the configuration with eight detached …

Green Hydrogen-Based Decarbonization Approach For Steel Industry With Hybrid Renewable Energy Sources, Raju Kumar Maurya, Dharmbir Prasad, Rudra Pratap Singh

Mansoura Engineering Journal

This work provides a micro-pilot techno-economic and environmental assessment of a green hydrogen-driven decarbonization scenario for low-carbon steel production at the capacity of 1 ton steel produced (i.e., requiring 50 kg of green hydrogen). In this work an integrated renewable energy (RE) scenario for the steel production site at Jamuria, West Bengal, India is planned to utilize solar photovoltaic (PV), wind turbines (WTs), battery storage and a diesel backup generator to meet the hydrogen production load from an electrolyzer using HOMER Pro software. The results show that the proposed micro-pilot system produces excess electricity with respect to the plant's operating …

From Classroom To Career: Use Of Digital Collaboration Tools To Bridge Theory & Practice, Della Clark, Kristina Kaufman, Sphurti Sewak, Peter Kaufman, Rick Valentin, Hulda Black

Faculty Publications – Marketing

Teamwork and project management skills, from in-person to remote interactions, remain central to marketing graduates’ career readiness, yet students often complete team projects with limited guidance on how to organize work, especially in hybrid and technology‑mediated environments. This study explores a pilot of integrating Miro, a widely used digital collaboration whiteboard, into classroom student projects. A pre- and post-survey design was implemented across two undergraduate marketing courses at a large Midwestern U.S. university to explore if Miro can improve students’ team‑project experience and perceived preparedness for working with emerging technologies. Students completed a questionnaire at the beginning of the semester …

Conceptualizing The Receipt Of Unfair School Discipline Through A Betrayal Trauma Lens, Charles Bell, Alexia Angton, Sarah Franklin, Michayla Mack, Pavel Ahmed

Faculty Publications - Criminal Justice Sciences

We contribute to the literature on school discipline by investigating why some Black students, parents, and advocates perceived particular punishments as unfair. Using Betrayal Trauma Theory (BTT) as a framework, we conducted qualitative interviews with twelve Black parents and five community activists who assisted Black children throughout the school discipline process and perceived such punishments as unfair. We also interviewed four Black children who received punishments at school that they perceived as unfair. Participants reported that instances of unfair school punishment created barriers to graduation, criminalized Black students, and permitted victimization to occur on school grounds.

Course Revision To Enhance Preservice Student Knowledge Of And Engagement Within Collaborative Learning Communities, Emily M. Jones, Oscar Nunez Enriquez, Zack Beddoes, Dan Phelps, Deborah Garrahy

Faculty Publications - Kinesiology and Recreation

This article shares a collaborative approach to refining an upper-level physical education teacher education seminar course. The primary goal of this refinement was to thoughtfully consider the existing course structure, content, and relevance to the evolving needs of schools. The approved course content focused on sociopolitical issues in education, strategies to navigate the complexities of professional roles in schools, and the transition into the teaching workforce. Through this process, the use of professional learning communities (PLCs) was considered as a viable approach to support preservice teachers’ learning and engagement in course content. Furthermore, by embedding PLCs into the course, the …

A Practical Approach To The Management Of Percutaneous Coronary Intervention Complications, Tanawat Attachaipanich, Hafeez Ul Hassan Virk, Muzamil Khawaja, Mahboob Alam, Ravi S Hira, Jacob A Doll, Chayakrit Krittanawong

Faculty, Staff and Students Publications

Introduction: Despite advances in stent design, pharmacotherapy, and procedural techniques that have improved percutaneous coronary intervention (PCI) outcomes and reduced PCI-related complications, these events still occur and are associated with adverse outcomes. Moreover, complex PCI procedures, which predispose to increased risk of complications, are increasingly performed. Understanding risk factors, underlying mechanisms, evidence-based management, and preventive strategies are essential to optimize procedural outcomes. This review aims to summarize current evidence and highlight gaps in knowledge related to PCI-associated complications.

Methods: This narrative review used a focused PubMed search through October 2025, prioritizing randomized trials, large observational studies, guidelines, and consensus statements. …

Investigating Food-Related Behaviors In Smith-Magenis Syndrome: Tailoring A Questionnaire For A Rare Disease, Citrine Elatrash, Theresa A Wilson, Alexis C Wood, Sarah H Elsea, Stephanie Sisley

Faculty, Staff and Students Publications

Purpose: Accurate measurement is essential for tracking changes in clinical outcomes. Individuals with Smith-Magenis syndrome (SMS) exhibit challenging and unique food-related behaviors. We sought to determine the best tool to capture their unique food-related behaviors.

Methods: We conducted focus groups with caregivers of individuals with SMS to evaluate two commonly used questionnaires for food-related behaviors- the Food Related Problems Questionnaire (FRPQ) and the Hyperphagia Questionnaire for Clinical Trials (HQ-CT). Based on caregiver input and clinical expertise, we adapted these existing measures into a new tool: the SMS-FRPQ. We then validated this instrument for internal consistency and concurrent validity using online …

Reframing Trauma-Informed Care For Refugee And (Im)Migrant Health Systems: From Interpersonal Practice To Structurally Embedded Care, Hyojin Im, Sophia Banu, Aisha Koroma, Sarmaya Mustafayeva

Faculty, Staff and Students Publications

No abstract provided.

Overcoming The Challenges Faced By Leaders Of Purpose-Led Medium-Sized Businesses: The Role Of Corporate Communication And Its Interplay With Corporate Reputation And Organisational Identity, Taofeeq Ibn-Mohammed, Suranga Herath, Nicholas Swallow, Charlie Gower, Adriana P. Montes, Dawn Brooks, Andres P. Garcia, Angus Morrison-Saunders

Research outputs 2022 to 2026

Induced by worsening environmental conditions, pursuing purpose, not solely profit, now constitutes an ethical obligation for leaders of business organisations, towards future generations. Consequently, increasing numbers of businesses seek to become purpose-led (PLBs), but challenges exist. Despite the significant growth in PLB research since the turn of the millennium, attention has mainly focussed on multinational companies, although small- and medium-sized businesses (MSBs) hugely impact any economy. This research sets out to better understand the challenges faced by leaders of companies undergoing purpose-led MSB transitioning. Thematic analysis of the interview data from founders and leaders of B-Corp certified purpose-led MSBs revealed …

Cancer Survivor Preferences For Breast Cancer Follow-Up Care: A Discrete Choice Experiment, Sameera Senanayake, Sanjeewa Kularatna, Fiona Crawford-Williams, David Brain, Michelle Allen, Ruvini M. Hettiarachchi, Nicolas H. Hart, Bogda Koczwara, Carolyn Ee, Raymond J. Chan

Research outputs 2022 to 2026

Purpose: To identify the key attributes of breast cancer follow-up care models preferred by cancer survivors in Australia. Methods: A discrete choice experiment (DCE) was conducted to elicit preferences for attributes of breast cancer follow-up care. Respondents were presented with two hypothetical scenarios, known as choice sets, and asked to select a preference. Respondents were individuals living in Australia who were diagnosed with breast cancer within the past five years prior to survey completion and were recruited through the Breast Cancer Network of Australia and other community or consumer networks. Latent class modelling (LCM) approach under a random utility framework …

Retrenchment, Segregation, And Public Education: A Five-Year Analysis Of State Exclusionary School Discipline Legislation, Thalia Gonzalez, Will Martel

Faculty Scholarship

Notwithstanding the decision in Brown v. Board of Education formally ending educational segregation and more than two decades of state reform, the legislative landscape protecting minoritized children from the structural violence of exclusionary school discipline has dramatically shifted in less than five years. From the passage of state “Teacher’s Bills of Rights” to mandatory expulsions, rescissions of prior protections, and new categories of removal, a retrenchment of anti-inclusion legislation—and its corollary, educational carcerality— has occurred. While studies of other forms of legislative retrenchment in K–12 public schools, such as anti-Critical Race Theory and Don’t Say Gay laws, literacy bans, and …

Open Secrets, Robin C. Feldman, Vaughn Goehrig

Faculty Scholarship

Patents and trade secrets were never intended to meet, but in the world of biologic drugs, they've become as thick as thieves. Patent law's disclosure requirement has demanded far too little of biologics manufacturers-allowing them to keep vital manufacturing details under trade secret lock and key. This intellectual property patchwork has been devastating for drug affordability: Because the most critical manufacturing information remains hidden, makers of follow-on biologics (called biosimilars) are often stuck reinventing the wheel, even after the original patents have expired.

This Article makes two principal contributions to illuminating this problem. First, it presents, for the first time …

Medical Device Dangers: Choosing Ignorance In The Courts And At The Fda, George Horvath

Faculty Scholarship

Medical devices save lives and improve well-being but have caused as many as 83,000 deaths and 1.7 million injuries in a recent decade. Decisions of critical importance—patients’ decisions whether to have a device implanted, doctors’ decisions about which device to use, insurers’ decisions whether to reimburse for those devices—depend on information about risk that is provided by manufacturers. But producing this information is costly. Injured patients, through private lawsuits under state products liability theories, can incentivize device manufacturers to incur these costs and to produce and disclose information about device risk. Unfortunately, courts are making it increasingly unlikely that this …