Results 111 to 120 of about 6,131,436 (285)
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
PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su +7 more
wiley +1 more source
Distinct Biotypes of Visual Perception in Major Depressive Disorder
In a discover dataset (272 acute MDD patients), this work identifies a novel depression biotype characterized by impaired visual motion perception, using machine learning clustering. An independent dataset confirms the robustness of this biotype through cross‐validation and demonstrates its generalizability.
Zhuoran Cai +13 more
wiley +1 more source
The study of Physical characteristics of agricultural materials is necessary for the design of processes and machines for food production. Length, width, thickness, sphericity, unit mass, and aspect ratio were the physical characteristics of ultrasound pretreated Dialium guineense whole fruits subjected to Neural network modeling.
Mfrekemfon Akpan +2 more
wiley +1 more source
Import Wheat Tenders and the Effects of the Russian Invasion
ABSTRACT Risk and volatility for many commodities escalated sharply following the Russian invasion of Ukraine, creating numerous uncertainties for trading firms and importers. The purpose of this study is to analyze the bidding behavior in Egyptian wheat import tenders in the pre‐ and post‐invasion periods.
William W. Wilson +2 more
wiley +1 more source
Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren +6 more
wiley +1 more source
A Qualitative Study of Senior Residents’ Strategies to Prepare for Unsupervised Practice
Introduction: As emergency medicine (EM) residents prepare for the transition into unsupervised practice, their focus shifts from demonstrating competencies within familiar training environments to anticipating their new roles and responsibilities as ...
Max Griffith +5 more
doaj +1 more source
A multimodal fusion pipeline predicts high‐resolution ion distributions in imaging mass spectrometry by integrating Fourier transform ion cyclotron resonance, time‐of‐flight matrix‐assisted laser desorption/ionization, and time‐of‐flight secondary ion mass spectrometry data.
Md Inzamam Ul Haque +7 more
wiley +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Unsupervised Learning of Morphology
Harald Hammarström, Lars Borin
doaj +1 more source

