Results 101 to 110 of about 4,433,930 (229)

Tree-Packing Revisited: Faster Fully Dynamic Min-Cut and Arboricity. [PDF]

Algorithmica
de Vos T, Christiansen A.
europepmc   +1 more source

A linear programming approach to increasing the weight of all minimum spanning trees [PDF]

Dans cet article nous étudions le problème qui consiste à augmenter au moindre coût le poids de tous les arbres couvrants de poids minimum. Nous considérons le cas où le coût d'augmenter le poids d'une arête du graphe est une fonction linéaire par ...
Fancisco Barahona, Mourad Baïou
core  

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Phosphatase Activities of a Highly Stable High-Molecular-Mass Multiprotein Complex Isolated from Different Organs of the Sea Cucumber <i>Paracaudina chilensis</i>. [PDF]

Int J Mol Sci
Soboleva SE, Maltseva NA, Dmitrenok PS, Nevinsky GA.   +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

Comparative Evaluation of Machine Learning Algorithms for Fault Diagnosis in Automotive Press Lines. [PDF]

Sensors (Basel)
Oner AE, Bayraktar M.
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

Theoretical derivation and experimental validation of tree detection rate in TLS-based forest plot surveys. [PDF]

Front Plant Sci
Sun J, Zhang Y, Zhao M, Xie J, Gao Y, Wang P.   +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

Mitochondrial genomic variation, evolutionary dynamics, and phylogeny of forest-associated <i>Phytophthora</i> species in the Qinling Mountains of China. [PDF]

IMA Fungus
Sun Y, Chen X, Wang W, Li Y, Qian Z, Ma X, Hieno A, Kageyama K, Li M.   +8 more
europepmc   +1 more source