Results 121 to 130 of about 1,862 (208)
Patient‐derived xenograft (PDX) tumor models initiated in avian chorioallantoic membranes (CAM) are under investigation to evaluate the effectiveness of therapeutic options with the objective of personalizing treatments. CAM PDXs paired with ultra‐high frequency ultrasound (UHFUS) imaging could potentially constitute prospective high throughput assays ...
Sara Mar +5 more
wiley +1 more source
ABSTRACT Real‐time flood control operation of multi‐reservoir systems is affected by multiple sources of hydrological and operational uncertainties, which increase the complexity of risk propagation and decision‐making processes. Therefore, effective risk assessment and diagnosis are essential for supporting risk‐informed flood control operation.
Juan Chen +5 more
wiley +1 more source
This review details a three‐stage paradigm shift for tumor‐reactive CD8+ T‐cell identification: decoding transcriptomic states, deciphering clonal functional efficacy, and molecular‐level therapeutic TCR design. Addressing translational hurdles and generative AI “scientific blind spots”—such as missing catch bonds—we present a visionary roadmap.
Chao Yang +4 more
wiley +1 more source
An integrated framework combining high‐throughput CG‐MD simulations, automated image‐based feature extraction, and supervised machine learning enables efficient, interpretable, and data‐driven prediction of block copolymer morphological behaviors.
Lan Xu, Zhaofan Li, Wenjie Xia
wiley +1 more source
We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie +3 more
wiley +1 more source
Epistemic and aleatoric uncertainty quantification in weather and climate models
Aleatoric and epistemic uncertainties over time on weather and climate time‐scales, estimated through ensembles that sample aleatoric and epistemic uncertainty using Bayesian neural networks for parameterisations in the Lorenz 1996 model. The spread shows the 16th and 84th percentiles.
Laura A. Mansfield +1 more
wiley +1 more source
Not All Missing Data are Equal: Choosing the Right Imputation Method for Binary Datasets
ABSTRACT Missing binary predictors are common in reliability, quality control, and industrial decision systems, yet imputation methods are often chosen by convenience rather than evidence. We conduct a Monte Carlo study comparing mode substitution, sequential hot‐deck, missForest, MICE, and KNN with three neighbourhood sizes under MCAR, MAR, and MNAR ...
Manuel Delfino, Fabio Rapallo
wiley +1 more source
ABSTRACT Drone light shows (DLShows) represent a rapidly growing application of swarm robotics, creating captivating aerial displays through the synchronized flight of hundreds or thousands of unmanned aerial vehicles (UAVs) as environmentally friendly and reusable alternatives to traditional pyrotechnics.
Yunes Alqudsi
wiley +1 more source
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen +8 more
wiley +1 more source
Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo +2 more
wiley +1 more source

