Results 111 to 120 of about 6,445,685 (297)

Study on Positive Temperature Effect of Moderator in TOPAZ-Ⅱ Reactor

Yuanzineng kexue jishu, 2023
TOPAZ-Ⅱ space nuclear reactor power supply adopts thermionic static thermoelectric conversion mode, the output power of the system is 5 kW, and its service life can reach 3 years. It is one of the most advanced space nuclear power supply systems that can
SHI Yunda;SUN Zheng;YANG Rui;HU Binhe;AN Weijian;ZHAO Shouzhi
doaj  

The Association of Amyloid‐β and Tau With Synaptic Dysfunction in Alzheimer's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the relative contributions of amyloid and tau to synaptic dysfunction in Alzheimer's disease (AD). Methods We included 109 cognitively unimpaired and impaired individuals from the Geneva Memory Center with available CSF synaptic biomarkers (neurogranin, SNAP‐25, GAP‐43). Participants were stratified according to amyloid (A)
Fausto Roveta, Augusto J. Mendes, Valentina Garibotto, Cecilia Boccalini, Aurelien Lathuiliere, Innocenzo Rainero, Elisa Rubino, Henrik Zetterberg, Nicholas J. Ashton, Federica Ribaldi, Giovanni B. Frisoni, for the Alzheimer's Disease Neuroimaging Initiative   +11 more
wiley   +1 more source

Separating Curing and Temperature Effects on the Temperature Coefficient of Resistance for a Single-Walled Carbon Nanotube Nanocomposite. [PDF]

Polymers (Basel), 2023
Jafarypouria M, Mahato B, Abaimov SG.
europepmc   +1 more source

A Sub-1 ppm/°C Reference Voltage Source with a Wide Input Range

Micromachines
With the continuous advancement of electronic technology, the application of high-voltage integrated circuits is becoming increasingly prevalent in fields such as power systems, medical devices, and industrial automation.
Yuchi Xiao, Chunlai Wang, Hongyang Hou, Weihua Han   +3 more
doaj   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Tailored Out-of-Oven Energy Efficient Manufacturing of High-Performance Composites with Two-Stage Self-Regulating Heating via a Double Positive Temperature Coefficient Effect. [PDF]

ACS Appl Mater Interfaces, 2023
Yao X, Wang Y, Thorn TDS, Huo S, Papageorgiou DG, Liu Y, Bilotti E, Zhang H.   +7 more
europepmc   +1 more source

Artificial Intelligence‐Driven Extraction of Patient‐Reported Pain Outcomes in Osteoarthritis Using Large Language Models

Arthritis Care &Research, Accepted Article.
Objective Patient‐reported outcome measures (PROMs) are central to assessing symptom burden and treatment response in Osteoarthritis (OA) but are often embedded in unstructured clinical notes. We evaluated whether prompt‐engineered large language models (LLMs) could accurately extract or infer pain scores on a 0‐10 scale from routine OA clinical ...
Jainesh Doshi, Stephen Batter, Yiyuan Wu, William Salerno, Alice Santilli, Sandhya Kannayiram, Susan Goodman, Bella Mehta   +7 more
wiley   +1 more source

Positive/Negative Temperature Coefficient Behaviors of Electron Beam-Irradiated Carbon Blacks-Loaded Polyethylene Nanocomposites. [PDF]

ACS Omega, 2022
Kim CH, Lee SY, Park SJ.
europepmc   +1 more source

Positive temperature coefficient of coercivity in Sm1-xDyx(Co0.695Fe0.2Cu0.08Zr0.025)(7.2) magnets with spin-reorientation-transition cell boundary phases

, 2015
Positive temperature coefficients of coercivity are first obtained in the series of Sm1-xDyx (Co0.695Fe0.2Cu0.08Zr0.025)(7.2) magnets. The temperature range with a positive temperature coefficient of coercivity is gradually moving to higher temperature ...
Lee, Don, Z. Liu, Don Lee, R. J. Chen, J. Liu, Li, W., Liu, L., Liu, Z., M. Li, L. Liu, A. R. Yan, W. Li, Liu, J., Yan, A. R., Li, M., Chen, R. J.   +15 more
core   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source