Results 231 to 240 of about 2,921,645 (302)

Disentangling biotic and abiotic drivers of a neotropical mistletoe. [PDF]

Oecologia
Oliveira EVS, Almeida TS, Oliveira HS, Gouveia SF.   +3 more
europepmc   +1 more source

Yum Yum Tree [PDF]

Yum Yum Tree
core  

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Divergent Temporal Trends in Carbon Assimilation-Growth Coupling Across Global Forests. [PDF]

Glob Chang Biol
Shi H, He R, Friedlingstein P, Sitch S, Dang H, Zhang Q.   +5 more
europepmc   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Suffixient Arrays: A New Efficient Suffix Array Compression Technique. [PDF]

Theory Comput Syst
Cenzato D, Depuydt L, Gagie T, Kim SH, Manzini G, Olivares F, Prezza N.   +6 more
europepmc   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

Advanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu, Fumiaki Iwane, Minsu Zhang, Leonardo G. Cohen, José del R. Millán   +4 more
wiley   +1 more source

Optimizing Symptom Surveys with Machine Learning to Predict PTSD One Year Post-trauma. [PDF]

IEEE Int Conf Connect Health Appl Syst Eng Technol
Prince C, Xie H, Grider S, Wang X, Xu KS.   +4 more
europepmc   +1 more source

Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries

Advanced Science, EarlyView.
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu   +4 more
wiley   +1 more source

DFB-PPGSQ: Dynamic Forward-Private and Epochal Backward-Private Graph Similarity Matching Query over Encrypted Sensor Graph Databases. [PDF]

Sensors (Basel)
Hou H, Ma Y, Zhao Z, Ge X.
europepmc   +1 more source