Results 61 to 70 of about 175,179 (256)

Komadu: A Capture and Visualization System for Scientific Data Provenance

Journal of Open Research Software, 2015
Data provenance captured from scientific applications is a critical precursor to data sharing and reuse. For researchers wanting to repurpose data, it is a source of information about the lineage and attribution of the data and this is needed in order to
Isuru Suriarachchi, Quan Zhou, Beth Plale   +2 more
doaj   +1 more source

ORBIT‐AMD: Ordinal Risk, Bilateral Imaging, and Trajectory Learning for Age‐Related Macular Degeneration in Multi‐Cohorts

Advanced Science, EarlyView.
Eligibility flow and real‐world AMD burden in the UKB retinal imaging cohort and TMUEH external‐validation cohort. Overview of the ORBIT‐AMD architecture, integrating retinal representation pretraining, bilateral eye‐graph modeling and concept bottleneck learning to support ordered risk, bilateral context, interpretable lesion concepts, longitudinal ...
Xuehao Cui, Dejia Wen, Patrick Yu‐Wai‐Man, Xiaorong Li   +3 more
wiley   +1 more source

Tamper-Evident Data and Model Provenance for IoT-Based Machine Learning Using Blockchain and Off-Chain Storage

Information
Machine learning models increasingly rely on continuously generated sensor data for automated decision-making in Internet of Things (IoT) environments.
Sangheethaa Sukumaran, Arun Korath, Gowri Arun Menon   +2 more
doaj   +1 more source

A Sustainable Bio‐Based Epoxy Thermoset as a High‐Performance Alternative to BPA‐Based Resins

Advanced Science, EarlyView.
A rigid–flexible bio‐based epoxy network integrates soybean oil, lignin, and maleic anhydride to overcome the strength–toughness–sustainability trade‐off of conventional BPA epoxy. The thermoset delivers excellent performance as both a structural adhesive and a matrix for glass‐fabric composites, while enabling pH‐responsive degradation, environmental ...
Jiyun Qi, Xinyi Hui, Xipeng Zhang, Jia‐Long Wen, Tong‐Qi Yuan   +4 more
wiley   +1 more source

Data Foundations for Medical AI: Provenance, Reliability and Limitations of Russian Clinical NLP Resources

Informatics
Russian-language resources for medical natural language processing (NLP) are expanding rapidly; however, their fragmentation, uneven curation, and limited clinical reliability hinder the development of safe machine learning systems for prognosis ...
Arsenii Litvinov, Lev Malishevskii, Evgeny Karpulevich, Iaroslav Bespalov, Yaroslav Nedumov, Sergey Zhdanov, Ivan Oseledets, Evgeniy Shlyakhto, Arutyun Avetisyan   +8 more
doaj   +1 more source

Overcoming Interfacial Hurdles in Solid‐State Aluminum Batteries for Safe and Energy‐Dense Storage

Advanced Science, EarlyView.
Solid‐state aluminum batteries (SSABs) promise high energy density and intrinsic safety but face severe solid–solid interfacial challenges. This review reveals the three core hurdles—anode passivation, cathode contact loss, and electrolyte grain boundary resistance and discusses strategies including artificial interphases, alloying, and composite ...
Yunlei Wang, Xiaogang Zhang, Mingguang Wang, Yifan Wu, Shitao Dou, Taibin Wu   +5 more
wiley   +1 more source

Green and Low‐Carbon Synthesis of Lithium Sulfide (Li2S): From Fundamental Mechanisms to Scalable Manufacturing for Next‐Generation Energy Storage

Advanced Science, EarlyView.
This review focuses on green synthesis routes for lithium sulfide (Li2S)—a key material for lithium–sulfur batteries and sulfide solid electrolytes, whose traditional carbothermal reduction remains energy‐intensive and unsustainable. Specifically examined routes include low‐temperature solid‐state reactions, magnesiothermal reduction, and solution ...
Aiping Peng, Xingtao Qi, Lingfeng Zhu, Ningrui Zhan, Yaohui Qu, Hui Li, Hai Zhang, Fan Wang, Ze Zhang, Xuewen Wang, Zhenyu Yang, Tianyi Ma   +11 more
wiley   +1 more source

Data Isotopes for Data Provenance in DNNs

Proceedings on Privacy Enhancing Technologies
Today, creators of data-hungry deep neural networks (DNNs) scour the Internet for training fodder, leaving users with little control over or knowledge of when their data, and in particular their images, are used to train models. To empower users to counteract unwanted use of their images, we design, implement and evaluate a practical system that ...
Emily Wenger, Xiuyu Li, Ben Y. Zhao, Vitaly Shmatikov   +3 more
openaire   +3 more sources

TSTScope Unifies Single‐Cell Multi‐Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Advanced Science, EarlyView.
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao, Jinyu Cheng, Feng‐ao Wang, Chenxin Yi, Jiajun Chen, Keyue Wang, Lulu Liu, Junwei Liu, Yixue Li   +8 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source