Results 71 to 80 of about 1,119 (185)

Fabrication of High‐Density Multimodal Neural Probes Based on Heterogeneously Integrated CMOS

Advanced Science, Volume 13, Issue 34, 19 June 2026.
A chiplet‐based methodology democratizes active neural probe development on standard bulk CMOS services. This yields the first probe combining high‐density electrophysiology (416 electrodes) with calcium imaging (832 photodiodes) and complete on‐chip signal processing across 13 shanks.
Ju Hee Mun, Miji Kim, Wooyeon Shin, Yongjun Park, Kanghwan Kim, Il‐Joo Cho, Jae Won Shim, Min Soo Kim, Sunwoo Lee, Jeongjin Kim, Changhyuk Lee   +10 more
wiley   +1 more source

Privacy Protection Optimization Method for Cloud Platforms Based on Federated Learning and Homomorphic Encryption. [PDF]

Sensors (Basel)
Wang J, Wang Y.
europepmc   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

Advanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang, Max Shotbolt, Mostafa Abdel‐Mottaleb, Shawnus Chen, Victoria Andre, Jieyuan Tian, Jonathan Shulgach, Max Murphy, Brian Noga, Ping Liang, Darcy Griffin, Douglas Weber, Marta Pardo, Salvador Pane, Sakhrat Khizroev   +14 more
wiley   +1 more source

Protecting cells at the genetic level and simulating unauthorized access via a biohackathon. [PDF]

Sci Adv
Kim D, Kumar I, Hassan MI, Barraza-Vergara LF, Voigt CA, Wilson CJ.   +5 more
europepmc   +1 more source

MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion

Advanced Science, Volume 13, Issue 34, 19 June 2026.
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong, Ji Ma, Yidan Lu, Jiahui Zhang, Wanyue Li, Yeke Chen, Teng Zhang, Xuechao Chen, Zhangguo Yu, Peng Lu   +9 more
wiley   +1 more source

Resilient and verifiable outsourced attribute-based non-interactive oblivious transfer protocol for tactical edge networks. [PDF]

Sci Rep
Liu W, Fu B, Wang L.
europepmc   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source

Advanced security in fog environments using encryption and adaptive user activity tracking. [PDF]

Sci Rep
Rai HM, Razaque A, Agarwal N, Agarwal S, Abdallah HA, Kant S.   +5 more
europepmc   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

Preferential path attachment model for quantum key distribution networks. [PDF]

Sci Rep
Weiss J, Lucki M, Mařík R, Boháč L.
europepmc   +1 more source