Results 141 to 150 of about 1,265 (217)

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

Higher plant seed container germination success predicted by smart farming optical RGB approach. [PDF]

Sci Rep
Novikova TP, Tylek P, Petrishchev EP, Novikov AI.   +3 more
europepmc   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Millets for food and nutritional security in semi-arid Bundelkhand, India: historical, scientific, and socio-economic perspectives. [PDF]

Front Nutr
Khan R, Sahoo S, Yadav S, Tiwari JK, Rout AK, Kumar N, Singh MK, Joshi DC, Reddy PS.   +8 more
europepmc   +1 more source

Prediction‐Guided Two‐Step Solid‐State Exploration of Unknown Pseudo‐Ternary Oxides

Advanced Intelligent Discovery, EarlyView.
Prediction‐guided selection combined with two‐step solid‐state exploration enables efficient search of unknown pseudo‐ternary oxides. Broad robotic slurry screening followed by manual single‐phase isolation leads to the discovery of a new oxide, Ba5SnV6O22, showing how data‐guided experiments connect unexplored composition regions to new materials ...
Hiroyuki Hayashi
wiley   +1 more source

Landscape Structure and Breeding Site Conditions Shape the Urban Distribution of the Two Frog Species, <i>Dryophytes japonica</i> and <i>Rhacophorus schlegelii</i>. [PDF]

Ecol Evol
Osawa T, Sato N, Nagaoka H.
europepmc   +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

Deforestation-focused policies do not reduce degradation in the Brazilian Amazon. [PDF]

Proc Natl Acad Sci U S A
Cammelli F, Gibbs HK, Gollnow F, Levy SA, Stigler M, Garrett RD.   +5 more
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Spatiotemporal patterns and optimization of dominant and recessive morphology of cultivated land use in the Ili River Valley. [PDF]

iScience
Zhou C, Fu L, Xiang H.
europepmc   +1 more source