Results 201 to 210 of about 123,792 (311)

Stretchable Microelectrode Arrays with Microneedles for Reliable Electrophysiological Recording of Human Heart and Brain Organoids

Advanced Science, EarlyView.
A stretchable 3D microelectrode array with microneedles (3D MN‐sMEA) enables stable, minimally destructive electrophysiological monitoring of 3D organoids. The wafer‐level stud‐bump bonding process facilitates high‐fidelity recordings of heart and cerebral organoids.
Eunyoung Jang, Saewoon Shin, Seul‐Gi Lee, Kiup Kim, Yoojeong Kim, Jun Sun, Il‐Joo Cho, Joseph A. Gogos, Jong‐Chan Park, C‐Yoon Kim, Hyunjoo J. Lee   +10 more
wiley   +1 more source

Health and Regulatory Impacts of PM_2.5 From Wildland Fires for 2019-2024 in the US. [PDF]

Geohealth
Jaffe D, Lee H, Magzamen S, Goldberg DL, O'Dell K.   +4 more
europepmc   +1 more source

Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces

Advanced Science, EarlyView.
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo, Jinhong Min, Geumbee Lee, Joohoon Kang, Hyoyoung Jeong, Jae‐Young Yoo, Sang Min Won   +9 more
wiley   +1 more source

Manganese Oxidation during Vegetation Burning. [PDF]

Environ Sci Technol
Mariano SMF, Zeng L, Huang R, Sánchez-García C, Santin C, Neris J, Yang P, Ma L, Kiss A.   +8 more
europepmc   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Urban Conflagrations: Structural Ash and Soil Metal(loid) Contamination after California's Eaton and Palisades Fires. [PDF]

Environ Sci Technol Lett
Dossou SA, Kelly L, Lu PL, Jones R, O'Donnell O, Walsh JSP, Richter DD.   +6 more
europepmc   +1 more source

Extra Climate Benefits From Afforestation Due to Reduced Forest Fragmentation in China

Advanced Science, EarlyView.
Afforestation in China reduced forest fragmentation in 2015, transforming 51.8 M ha of edge forests into interior forests. This enhanced carbon sequestration (1.4±0.2 Pg CO2e, a cooling biogeochemical effect), while reduced albedo (−0.9 Pg CO2e, a warming biophysical effect) partially offset the gain, yielding a net extra climate benefit of ...
Nan Meng, Wei Li, Philippe Ciais, Martin Brandt, Xiaowei Tong, Yanzheng Yang, Guofeng Shen, Wei Du, Lei Zhu, Yi Leng, Minxuan Sun, Mengjie Han, Xuemei Zhang, Jie Zhang, Nan Wang, Dan Tong, Chao Wu, Wenhao Dong, Shu Tao, Bo Pan   +19 more
wiley   +1 more source

Climate impacts from North American boreal forest fires. [PDF]

Nat Geosci
van Gerrevink MJ, Veraverbeke S, Cooperdock S, Potter S, Zhong Q, Moubarak M, Virkkala AM, Goetz SJ, Mack MC, Randerson JT, Schutgens N, Turetsky MR, van der Werf GR, Rogers BM.   +13 more
europepmc   +1 more source

Reconfigurable Selector‐Only Memory (SOM) for Scalable Neuromorphic Computing

Advanced Science, EarlyView.
ABSTRACT Highly scalable reconfigurable neuromorphic devices are critical for addressing continual‐learning challenges in artificial intelligence. However, the scalability of existing reconfigurable devices is severely constrained by limited operating margins and insufficient process maturity.
Jin‐Yu Wen, Chuan‐Qi Yi, Ya‐Ru Zhang, Bin‐Hao Wang, Zi‐Xuan Liu, Chun‐Yu Zhou, Hao Tong, Xiang‐Shui Miao   +7 more
wiley   +1 more source

An intelligent IoT-machine learning framework for wildfire detection and prediction using a hybrid RF-XGB model. [PDF]

Sci Rep
Radhi AA, Ibrahim AA.
europepmc   +1 more source