Results 71 to 80 of about 9,721 (245)
The inherent high dimensionality of hyperspectral imagery presents both opportunities and challenges for agricultural crop classification. This study offers a rigorous comparative evaluation of three U-Net-based architectures, i.e., U-Net, U-Net++, and ...
Georgios Dimitrios Gkologkinas +3 more
doaj +1 more source
The hyperactivation of PI3K/AKT signaling in PTEN wild‐type triple‐negative breast cancer represents a clinical paradox. We delineate a novel post‐translational regulatory axis wherein the oncogene TSPYL5 competitively antagonizes the deubiquitinase USP10.
Jiaying Shi +8 more
wiley +1 more source
Structure-Preserved and Weakly Redundant Band Selection for Hyperspectral Imagery
In recent years, sparse self-representation has achieved remarkable success in hyperspectral band selection. However, the traditional sparse self-representation-based band selection methods tend to neglect the spatial distribution differences and ...
Baijia Fu +4 more
doaj +1 more source
Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang +14 more
wiley +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Autologous tumor‐infiltrating lymphocyte (TIL) therapy shows promising efficacy in acral melanoma, yet determinants of durable response remain unclear. By integrating single‐cell transcriptomics and TCR sequencing, this study reveals that TIL products enriched for T follicular helper and intermediate exhausted T cells establish persistent clonal ...
Chao Zhang +12 more
wiley +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Producing MSCs on rigid culture substrates induces a scar‐making phenotype, jeapordizing therapeutic success. ‘Tissue‐soft’ surfaces prevent MSC fibrogenesis and preserve regenerative traits. An epigenetic network, driven by HOXA11 and SALL1, maintains ‘soft memory’ by keeping chromatin open in relaxed MSCs, promoting anti‐fibrotic programs.
Fereshteh Sadat Younesi +7 more
wiley +1 more source
BioSenSRRF is an open‐source workflow that combines conventional FRET biosensors with SRRF reconstruction to generate sub‐diffraction FRET index maps on standard microscopes. The pipeline integrates automated image registration, SRRF reconstruction, quantitative FRET index calculation, and random line‐based hotspot analysis to uncover AURKA‐dependent ...
Nicolas Y. Jolivet +5 more
wiley +1 more source

