Results 181 to 190 of about 3,188,697 (327)

90% F1 Score in Relational Triple Extraction: Is it Real ?

, 2023
Pratik Saini, Tapas R. Nayak, Samiran Pal, Indrajit Bhattacharya   +3 more
openalex   +2 more sources

Topology‐Optimized Bound States in the Continuum with High‐Q Acoustic Field Enhancement

Advanced Science, EarlyView.
This study presents a topology optimization method for acoustic metamaterials, achieving high‐Q resonances by redesigning a single unit cell within a periodic array. The design enables precise pressure confinement and energy trapping, validated through experiments.
Weibai Li, Kazem Ghabraie, Xiaodong Huang   +2 more
wiley   +1 more source

Iterative Tuning of Tree-Ensemble-Based Models' parameters Using Bayesian Optimization for Breast Cancer Prediction

Информатика и автоматизация
The study presents a method for iterative parameter tuning of tree ensemble-based models using Bayesian hyperparameter tuning for states prediction, using breast cancer as an example.
Ayman Alsabry, Malek Algabri
doaj   +1 more source

CXCL13 Damages Blood Spinal Cord Barrier by Promoting RNF6/Sqstm1‐Ubiquitination Induced Autophagy in Experimental Allergic Encephalomyelitis

Advanced Science, EarlyView.
In multiple sclerosis, the disruption of the blood‐spinal cord barrier (BSCB) induced by CXCL13 facilitates the infiltration of inflammatory cells into the central nervous system, resulting in demyelination and neuronal injury. Mechanistically, the deleterious impact of CXCL13 on the BSCB is associated with a reduction in tight junction protein ...
Jingjing Han, Rui Hong, Cong Cao, Wanhua Feng, Wei Zhuang, Gui Wang, Jingchao Tang, Ya Yang, Chu Zhang, Aihua Zhou, Xuebin Qu   +10 more
wiley   +1 more source

An Exploratory Study on Automatic Identification of Assumptions in the Development of Deep Learning Frameworks [PDF]

arXiv
Stakeholders constantly make assumptions in the development of deep learning (DL) frameworks. These assumptions are related to various types of software artifacts (e.g., requirements, design decisions, and technical debt) and can turn out to be invalid, leading to system failures.
arxiv  

ProteoSeeker: A Feature‐Rich Metagenomic Analysis Tool for Accessible and Comprehensive Metagenomic Exploration

Advanced Science, EarlyView.
ProteoSeeker is a new metagenomic analysis tool that accelerates protein discovery. By automating key steps, it reduces computational complexity and enables comprehensive dataset analysis, performing protein identification, screening based on user‐defined protein families, and taxonomic analysis.
Georgios Filis, Dimitra Bezantakou, Konstantinos Rigkos, Despina Noti, Pavlos Saridis, Dimitra Zarafeta, Georgios Skretas   +6 more
wiley   +1 more source

Label-efficient multi-organ segmentation with a diffusion model [PDF]

arXiv
Accurate segmentation of multiple organs in Computed Tomography (CT) images plays a vital role in computer-aided diagnosis systems. While various supervised learning approaches have been proposed recently, these methods heavily depend on a large amount of high-quality labeled data, which are expensive to obtain in practice.
arxiv  

Figure 8: ICA-feature-based classification using a 5-fold validation method, where the accuracy, precision, recall, and F1-score are shown.

, 2021

openalex   +1 more source

Deciphering the Metabolic Impact and Clinical Relevance of N‐Glycosylation in Colorectal Cancer through Comprehensive Glycoproteomic Profiling

Advanced Science, EarlyView.
The comprehensive proteomic and N‐glycoproteomic analyses of 45 colorectal cancer tissues with matched normal adjacent tissues identified 7125 intact N‐glycopeptides from 704 glycoproteins. A glycosylation site‐protein function network revealing metabolic dysregulation is constructed and a model differentiating tumors from normal tissues is developed ...
Guobin Liu, Lu Chen, Jingxiang Zhao, Yue Jiang, Yarong Guo, Xiang Mao, Xuelian Ren, Kun Liu, Qi Mei, Qunyi Li, He Huang   +10 more
wiley   +1 more source

Introducing the Biomechanics-Function Relationship in Glaucoma: Improved Visual Field Loss Predictions from intraocular pressure-induced Neural Tissue Strains [PDF]

arXiv
Objective. (1) To assess whether neural tissue structure and biomechanics could predict functional loss in glaucoma; (2) To evaluate the importance of biomechanics in making such predictions. Design, Setting and Participants. We recruited 238 glaucoma subjects.
arxiv