A General Upper Bound for the Runtime of a Coevolutionary Algorithm on Impartial Combinatorial Games. [PDF]
Benford A, Lehre PK.
europepmc +1 more source
We have developed a semi‐automated shear flow platform using bright‐field optics and a machine‐learning analysis algorithm to dissect tumor‐microenvironment interactions. The algorithm quantifies the extent of adhesion at the single‐cell level and delivers consistent results within minutes instead of hours, facilitating high‐throughput analysis ...
Driti Ashok +7 more
wiley +1 more source
SpacerScope: binary-vectorized, genome-wide off-target profiling for RNA-guided nucleases without prior candidate-site bias. [PDF]
Qu Y, Wang Y, Wang Y, Tang H, Chen Q.
europepmc +1 more source
A Zonal‐Meridional Projection Method for Quantifying Global Land‐Ocean Moisture Transport
We present a physically consistent and computationally efficient method to quantify global coastal moisture transport by projecting vertically integrated moisture flux onto signed land–ocean boundary segments. The signed projection naturally distinguishes ocean‐to‐land inflow and land‐to‐ocean outflow without explicit directional classification ...
Chong Zhang +2 more
wiley +1 more source
Execution-bound advisory automation for agentic AI: a reproducible AIBOM-driven CSAF-VEX framework. [PDF]
Radanliev P, Santos O, Maple C, Atefi K.
europepmc +1 more source
Sensitivity of Consecutive‐Dry‐Day Trends to Trace Loss in Matched Precipitation Archives
Loss of trace precipitation information can turn valid dry days into missing observations that interrupt consecutive dry day (CDD) spells. Simulating this loss reduced the median cross‐archive CDD trend discrepancy by 88% across 205 matched Spanish station pairs; a separate global experiment converting documented traces to missing observations changed ...
Marc Sempera +3 more
wiley +1 more source
Toeplitz-Hankel Structured Covariance Reconstruction for DOA Estimation of Coherent Sources with Coprime Arrays Under Nonuniform Noise. [PDF]
Zhao H, Hu Y, Zhang Z, Zhang F.
europepmc +1 more source
Machine Learning‐Based Risk Stratification Tool for Hearing Loss in High‐Risk Neonates
Machine learning models, particularly XGBoost, provide robust risk stratification for neonatal hearing loss by capturing complex interactions among clinical risk factors such as NICU stay duration and family history. To translate these predictive capabilities into routine practice, an open‐access web‐based clinical decision support tool was developed ...
Sevgi Kutlu +4 more
wiley +1 more source
Event-Driven Multimodal Sensing and Computing for Context-Aware Home Monitoring Using Stereo Vision and Dietary Event Anchoring. [PDF]
Tong Z, Ono K, Nakamura M, Chen S.
europepmc +1 more source

