Results 51 to 60 of about 1,414,364 (143)
Charting Endocrine Progenitors Across Species and Organs
Endocrine progenitors give rise to the hormone‐producing cells of the pancreas and intestine. Using single‐cell multiomics and proteomics, this study compares these progenitors across species, systems, and organs, mapping the conserved and species‐specific gene regulatory networks that guide their formation.
Changying Jing +21 more
wiley +1 more source
Lactiplantibacillus plantarum GUANKE remodels the indigenous gut microbiota and is associated with microbiota‐dependent restoration of circulating IAA. IAA treatment attenuates JAK3‐STAT3 and Jag1‐Notch4‐Hey1 signaling and reduces CX3CR1+Ly6C− monocytic precursor generation and pulmonary CD11b+ DC accumulation, together with reduced Th2 inflammation ...
Yujia He +10 more
wiley +1 more source
Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale +6 more
wiley +1 more source
The influence of heterogenous porosity on silicon nitride/steel wear in lubricated rolling contact [PDF]
Heterogeneous porosity is detected on the surface and subsurface of hot isostatically pressed (HIPed) silicon nitride spherical rolling elements. The extent of the localised porosity accounts for an area of 6% of the rolling element surface and 4% of the
Kang, J, Hadfield, M
core +2 more sources
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source
Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors
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 +7 more
wiley +1 more source
Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram +4 more
wiley +1 more source
Erosion and rolling contact wear mechanisms in silicon nitride hybrid bearings. [PDF]
One remarkable advantage of hybrid bearings over all steel bearings is the elimination of separate oil lubricant system in applications, such as compressors and pumps in refrigeration and air conditioning units.
Karunamurthy, Balamurugan
core +4 more sources
Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors
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 +4 more
wiley +1 more source

