Results 121 to 130 of about 331,059 (292)
Whole‐genome analysis of 1,054 chickens reveals three ancestral sources (NWC, SYA, and SHF) with distinct temporal entry patterns into the Tibetan Plateau. Route‐specific selection scans, calibrated against a demographic null, suggest complementary functional enrichments—vascular homeostasis (NWC), calcium signaling and cardiac adaptation (SYA), and ...
Zongyi Zhao +7 more
wiley +1 more source
This study outlines the developmental pipeline of a multiplexed nanozyme‐based lateral flow immunoassay for the purpose of ovarian germ cell tumor detection. It demonstrates the application of a design of experiments optimization approach for nanozyme probe conjugate development.
Aida Abdelwahed +10 more
wiley +1 more source
Knightian Forecasting: Mathematical Models of Ambiguity and the Limits of Probabilistic Prediction
ABSTRACT This paper develops a theoretical framework for forecasting under Knightian uncertainty, where probabilities are not uniquely defined, and ambiguity fundamentally constrains predictive inference. Traditional forecasting relies on single‐model probabilistic structures, yet such approaches are often fragile in environments ...
openaire +1 more source
ABSTRACTWith their many therapeutic functions, mesenchymal stem cells (MSCs) are promising sources for regenerative medicine. However, in the manufacture of MSCs, without a method for exploring the effects of long‐term passage on cell proliferation potentials, the design of passage culture processes is challenging.
Keita Hirono +4 more
openaire +2 more sources
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
MATHEMATICAL MODEL OF OPTIMAL PROJECT PORTFOLIO FORMING BASED ON RANDOM FACTORS
Purpose. To identify the ways of perspective development for railway transport one should solve the problem of forming the investment project portfolio.
I. A. Korkhina
doaj
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv +11 more
wiley +1 more source
MATHEMATICAL MODEL OF INTELLIGENT UAV FLIGHT PATH PLANNING
The object of study is the process of planning the UAV flight path. The subject of the study is a mathematical model of intelligent UAV flight path planning.
Serhii Semenov +4 more
doaj +1 more source
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng +17 more
wiley +1 more source

