Results 91 to 100 of about 53,402 (265)

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Times Series Averaging and Denoising from a Probabilistic Perspective on Time–Elastic Kernels

International Journal of Applied Mathematics and Computer Science, 2019
In the light of regularized dynamic time warping kernels, this paper re-considers the concept of a time elastic centroid for a set of time series. We derive a new algorithm based on a probabilistic interpretation of kernel alignment matrices.
Marteau Pierre-Francois
doaj   +1 more source

Learning Moisture‐Induced Damage From Vision: Diffusion Models for Real‐Time Monitoring of Additive Manufacturing Processes

Advanced Science, EarlyView.
We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung, Yuna Yoo, Dharneedar Ravichandran, Dahyun Daniel Lim, Grace X. Gu   +4 more
wiley   +1 more source

Denoising random forests

CoRR, 2017
This paper proposes a novel type of random forests called a denoising random forests that are robust against noises contained in test samples. Such noise-corrupted samples cause serious damage to the estimation performances of random forests, since unexpected child nodes are often selected and the leaf nodes that the input sample reaches are sometimes ...
Masaya Hibino, Akisato Kimura, Takayoshi Yamashita, Yuji Yamauchi, Hironobu Fujiyoshi   +4 more
openaire   +3 more sources

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

Advanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li, Jin Ning, An Wang, Minxi Shi, Yuanze Chen, Guoliang Liu, Shiquan Sun   +6 more
wiley   +1 more source

Distribution Conditional Denoising: A Flexible Discriminative Image Denoiser

CoRR, 2020
A flexible discriminative image denoiser is introduced in which multi-task learning methods are applied to a densoising FCN based on U-Net. The activations of the U-Net model are modified by affine transforms that are a learned function of conditioning inputs.
openaire   +3 more sources

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source

Multispinning for Image Denoising

Journal of Intelligent Systems, 2012
Abstract. The problem of reconstructing digital images from degraded measurements is regarded as a problem of importance in various fields of engineering and imaging science. The main goal of denoising is to restore a noisy image to produce a visually high quality image.
B. N. Aravind, K. V. Suresh 0001
openaire   +3 more sources

Single‐cell Transcriptome Profiling Reveals Gene Regulatory Networks and Key Genes in the Root Epidermis and Cortical Cells Associated with Early Nodulation in Glycine Max

Advanced Science, EarlyView.
Single‐cell transcriptomics of soybean roots soon after rhizobial inoculation reveals epidermal and cortical cell‐specific programs and gene‐regulatory networks acting in symbiosis establishment. We identify an ethylene‐driven regulatory circuit involving WRKY6.3/6.4 transcription factors targeting select Nod19 genes that promotes infection‐thread ...
Yongbin Zhuang, Yu Geng, Xinyu Guo, Chen Wang, Yongjing Sun, Luqi Liu, Li Liu, QianQian Gao, XinFang Zhu, Hongxiang Cao, Gengshuo Zhang, Yunxia Liu, Guobin Zhang, Baoyin Chen, Jinfei Zhang, Xin Hou, Xiaoming Li, Dajian Zhang   +17 more
wiley   +1 more source

PolyG Fibrils Coalesce Into Nuclear Ribbons That Engage Proteostasis Machinery in Neuronal Intranuclear Inclusion Disease

Advanced Science, EarlyView.
In NIID, expanded NOTCH2NLC repeats give rise to nuclear polyG inclusions. Tracer‐guided in situ cryo‐electron tomography enables cross‐scale structural analysis from mouse brain to native neuronal nuclei, revealing dense‐core/peripheral‐halo inclusions built from compact polyG ribbons.
Hui Dong, Yongcheng Pan, Zhiyao Tang, Yuxuan Yao, Guicong Zhang, Junpu Wang, Haonan Xiao, Yun Tian, Beisha Tang, Dan Li, Qiang Guo, Ruijun Tian, Qiong Liu, Cong Liu   +13 more
wiley   +1 more source