Results 201 to 210 of about 751,622 (266)

Oxidized MoS2‐Based Multifunctional Memristive Hardware for Energy‐Efficient mmWave Signal Processing and In‐Memory Matrix Multiplication

Advanced Functional Materials, EarlyView.
Thermally oxidized MoS2‐based radio‐frequency switches enable a multifunctional platform that unifies broadband RF switching and in‐memory computation. The device achieves a cutoff frequency of 33.2 THz with high energy efficiency and supports hardware‐aware signal processing.
Juho Son, Changwoo Pyo, Sungmoon Park, Yoongi Cho, Seungchan Lee, Myungsoo Kim   +5 more
wiley   +1 more source

Topology-aware design of spiking neural networks via modular graph architectures. [PDF]

PLoS One
Motaghian F, Nazari S, Dominguez-Morales JP, Jafari R.   +3 more
europepmc   +1 more source

Multifunctional Gold Nanocluster‐Based PROTAC System for Targeted Degradation of Phosphorylated Tau and Modulation of Neuroinflammation in Alzheimer's Disease

Advanced Functional Materials, EarlyView.
We present a novel proteolysis‐targeting chimera (PROTAC) system conjugated to lipoic acid gold nanoclusters (PLANC), designed to degrade pTau, regulate inflammatory signaling, and effectively traverse the blood‐brain barrier (BBB). PLANC degraded pTau at various phosphorylation sites, with mechanistic studies confirming proteasome‐mediated degradation
Sarah Nevins, Callan D. McLoughlin, Wan‐Kyu Ko, Hye Kyu Choi, Brandon Conklin, Joshua B. Stein, Yannan Hou, Hongwon Kim, Rohan Khulbe, Ki‐Bum Lee   +9 more
wiley   +1 more source

Multilayered microelectrode array for monitoring electrophysiological signals of 3d neural networks in cerebral organoid. [PDF]

Microsyst Nanoeng
Kim N, Kang M, Ji J, Kim H, Kim HN, Choi N, Lee YJ.   +6 more
europepmc   +1 more source

Transparent and Robust LiCl–Organohydrogel Triboelectric Nanogenerator With Deep Learning Assisted Sensing

Advanced Functional Materials, EarlyView.
Develop a LiCl–PEI–PAM hydrogel with 3000% stretchability and excellent optical transparency. Through comparative studies of various salts, confirm that LiCl is the most suitable salt for high TENG output. Achieve excellent freeze‐resistant, dry‐resistant, and rapid self‐healing (10 s) properties even in extreme environments. Balance ionic conductivity,
Hai Anh Thi Le, Thien Trung Luu, Duc‐Manh Dinh, Kyehan Rhee, Kyungwho Choi, Dukhyun Choi, Yong Tae Park   +6 more
wiley   +1 more source

Red fescue (Festuca rubra L.) variety recognition using subset division and neural networks. [PDF]

Theory Biosci
Slebioda L, Zawieja B.
europepmc   +1 more source

Lysosome‐Acidifying Nanoparticles Rescue A30P α‐Synuclein Induced Neuronal Death in Cellular and Drosophila Models of Parkinson's Disease

Advanced Healthcare Materials, EarlyView.
Lysosome‐targeted acidic nanoparticles based on a biodegradable poly(ethylene tetrafluorosuccinate‐co‐succinate) copolymer are engineered to restore impaired lysosomal acidification through pH‐responsive intracellular degradation. Localized acid release enhances autophagic proteolysis, reduces α‐synuclein accumulation, and preserves dopaminergic neuron
Chih Hung Lo, Mengda Ren, Gavin Wen Zhao Loi, Eka Norfaishanty Saipuljumri, Jonathan Indajang, Kah Leong Lim, Jialiu Zeng   +6 more
wiley   +1 more source

Two-Step Ensemble Convolutional Neural Networks for Colonoscopic Biopsy Classification Resembling Pathologists' Process. [PDF]

J Korean Med Sci
Yoon H, Alam MR, Thakur N, Jeong S, Hwang G, Lee EJ, Chong Y.   +6 more
europepmc   +1 more source

Decellularized Extracellular Matrix (dECM) in Tendon Regeneration: A Comprehensive Review

Advanced Healthcare Materials, EarlyView.
Decellularized Extracellular Matrix (dECM) offers a promising solution by replicating the native tendon microenvironment and promoting regeneration. This review highlights advances in the decellularization methods, as well as their integration with emerging technologies and translational progress in tendon tissue engineering.
Kumaresan Sakthiabirami, Yeonwoo Park, Seong Kyeong Jo, Min Hee Kim, Jae Hwang Song   +4 more
wiley   +1 more source

LSTM-attention-guided graph neural networks for integrated genotype-Environment modeling in maize yield prediction. [PDF]

PLoS Comput Biol
Morshedian A, Domaratzki M.
europepmc   +1 more source