Results 111 to 120 of about 25,519 (265)

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

Research on Overburdened Rock Structures and Support Resistance of Shallow Buried Large Mining Heights Based on Sheet Gangs

Applied Sciences
In the mining of shallow coal seams, the increase in mining height will lead to a sharp increase in the probability and degree of coal wall spalling. Rib spalling will affect the normal production of coal mines and may also threaten the safety of miners.
Pei Zhang, Yang Chen, Yibo Wei, Zhuo Li, Liqiang Dong   +4 more
doaj   +1 more source

Rib Spalling 3D Model for Soft Coal Seam Faces with Large Mining Height in Protective Seam Mining: Theoretical and Numerical Analyses

, 2020
Fully-mechanized mining of coal face with a large cutting height is generally jeopardized by rib spalling disaster in the working face. Preventive measures based on undisturbed coal seam conditions fail to provide safe predictions, as large-scale ...
Shuai Liu, Tong Zhang, Ke Yang, Chunan Tang   +3 more
core   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Coal‐wall spalling prevention mechanism using advance‐grooving pressure relief in the large‐mining‐height working face of a shallow coal seam

Energy Science & Engineering
In mining, the roof structure of a working face with a large mining height in a shallow‐buried coal seam is prone to cutting instability in front of the support, which causes support crushing and coal‐wall spalling. This study analyzes 2201 working faces
Wang Hongwei, Feng Li, Zhao Zhouyan, Li Yanjun, Cao Peipei, Jiao Jianqiang, Jiang Baolin, Liu Yong   +7 more
doaj   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs

Advanced Intelligent Discovery, EarlyView.
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley   +1 more source

Early Effects of the Serious Accidents Punishment Act on Occupational Health Outcomes in Korea: A Nationwide Difference‐in‐Differences Study (2017–2023)

American Journal of Industrial Medicine, EarlyView.
ABSTRACT Background Work‐related injury and occupational disease remain major public health challenges worldwide; South Korea continues to report comparatively high industrial accident rates among OECD countries. To strengthen managerial accountability for worker safety, the Korean government enacted the Serious Accidents Punishment Act (SAPA) in 2021,
Hyewon Park, Misong Woo, Wanhyung Lee
wiley   +1 more source

Per‐ and Polyfluoroalkyl Substances (PFAS) Exposure Profiles and Their Predictors in a Study of US Volunteer Firefighters

American Journal of Industrial Medicine, EarlyView.
ABSTRACT Introduction Firefighters may experience occupational exposure to per‐ and polyfluoroalkyl substances (PFAS). Volunteer firefighters make up 65% of the US fire service, but their serum PFAS profiles have not been well characterized. This study aims to (1) describe PFAS serum profiles among US volunteer firefighters from 9 states enrolled in ...
Katherine A. Lubina, Zorimar Rivera‐Núñez, Miriam M. Calkins, Robert Laumbach, Shou‐En Lu, Jefferey L. Burgess, Elena Austin, Derrick L. Edwards, Maria D. H. Koeppel, Jaclyn M. Goodrich, Zhihua (Tina) Fan, Chang Ho Yu, Kaleigh M. Hinton, Casey C. Grant, Brian Kubiel, Daniel Roy, Judith M. Graber   +16 more
wiley   +1 more source