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Green materials in semiconductors: perspective from the IRDS Beyond-CMOS roadmap.
Nanotechnology
January 2025
IBM research, 650 Harry Road, San Jose, California, 95120, UNITED STATES.
Environmental, Safety, Health, and Sustainability (ESHS) have become an indispensable issue in the semiconductor industry. The "Beyond CMOS" chapter of the International Roadmap for Devices and Systems(IRDS) roadmap introduces the concept of "Green materials", emphasizing their importance for maintaining sustainability in semiconductor manufacturing. We discuss the current trends of emerging architectures and devices in the perspective of "Green materials".
View Article and Find Full Text PDFDesigning Health Recommender Systems to Promote Health Equity: A Socioecological Perspective.
J Med Internet Res
January 2025
Department High-Tech Business and Entrepreneurship Section, Industrial Engineering and Business Information Systems, University of Twente, Enschede, Overijssel, Netherlands.
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities.
View Article and Find Full Text PDFHigh Areal Loading Silicon Nanoparticle-Based Lithium-Ion Batteries.
ACS Appl Mater Interfaces
January 2025
Electrical & Computer Engineering Department, Montana State University, Bozeman, Montana 59717, United States.
Interfacial mechanical stability between silicon (Si) and the current collector is crucial when high areal-loading of Si is demanded as intense stress develops at the interface due to its extreme volume alteration during the lithiation-delithiation process. Therefore, we propose using a thin, rough, porous, and highly conductive carbon nanotube network (CNT-N) as a buffer layer between the Si and current collector that provides abundant anchor sites for Si nanoparticles. The strong and elastic CNT-N, which is not involved directly in the lithiation process, reduces stress at interfaces between the Si and CNT-N and the CNT-N and current collector.
View Article and Find Full Text PDFReconstructing Covert Consciousness: Neural Decoding as a Novel Consciousness Assessment.
Neurology
February 2025
Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Determining the level of consciousness in patients with brain injury-and more fundamentally, establishing what they can experience-is ethically and clinically impactful. Patient behaviors may unreliably reflect their level of consciousness: a subset of unresponsive patients demonstrate covert consciousness by willfully modulating their brain activity to commands through fMRI or EEG. However, current paradigms for assessing covert consciousness remain fundamentally limited because they are insensitive, rely on imperfect assumptions of functional neuroanatomy, and do not reflect the spectrum of conscious experience.
View Article and Find Full Text PDFState-Level Influenza Hospitalization Burden in the United States, 2022-2023.
Am J Public Health
January 2025
Alexia Couture, A. Danielle Iuliano, Ryan Threlkel, Matthew Gilmer, Alissa O'Halloran, Dawud Ujamaa, Matthew Biggerstaff, and Carrie Reed are with the National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA. Howard H. Chang is with the Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
To develop a method leveraging hospital-based surveillance to estimate influenza-related hospitalizations by state, age, and month as a means of enhancing current US influenza burden estimation efforts. Using data from the Influenza Hospitalization Surveillance Network (FluSurv-NET), we extrapolated monthly FluSurv-NET hospitalization rates after adjusting for testing practices and diagnostic test sensitivities to non-FluSurv-NET states. We used a Poisson zero-inflated model with an overdispersion parameter within the Bayesian hierarchical framework and accounted for uncertainty and variability between states and across time.
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