Results 111 to 120 of about 4,909,083 (351)

Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re‐Usability: A Position Paper From the Nanosafety Community

Advanced Sustainable Systems, EarlyView.
Nanosafety data provide a guiding example for establishing best practices in data management, aligning with FAIR principles and quality criteria. This review explores existing quality assessment approaches for reliability, relevance, and completeness, emphasizing the need for harmonization and adaptation to nanomaterials and advanced materials. The aim
Verónica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile‐Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli Sánchez Jiménez, Janeck J. Scott‐Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, Iseult Lynch   +43 more
wiley   +1 more source

VDLIN: A Deep Learning‐Based Platform for Methylcobalamin‐Inspired Immunomodulatory Compound Screening

Advanced Science, EarlyView.
Using the convolutional neural network model VDLIN, Co7 is identified as a promising therapeutic candidate. Co7 demonstrates distinct advantages over MCB by effectively balancing anti‐inflammatory and immune‐stimulatory functions, making it a potential novel approach for immune modulation.
Xuefei Guo, Yang Zhao, Xianle Rong, Chenxi Niu, Shiyu Hu, Qiang Liu, Fuping You   +6 more
wiley   +1 more source

Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization

Geoscience Frontiers, 2021
Wengang Zhang, Chongzhi Wu, Haiyi Zhong, Yongqin Li, Lin Wang   +4 more
semanticscholar   +1 more source

Construction of a Multitissue Cell Atlas Reveals Cell‐Type‐Specific Regulation of Molecular and Complex Phenotypes in Pigs

Advanced Science, EarlyView.
This research conducts an in‐depth investigation of cell‐type‐specific regulatory mechanisms underlying molecular and complex phenotypes through integrative analysis of multitissue single‐nucleus RNA sequencing, bulk RNA‐seq, and genome‐wide association study (GWAS) data in pigs.
Lijuan Chen, Houcheng Li, Jinyan Teng, Zhen Wang, Xiaolu Qu, Zhe Chen, Xiaodian Cai, Haonan Zeng, Zhonghao Bai, Jinghui Li, Xiangchun Pan, Leyan Yan, Fei Wang, Lin Lin, Yonglun Luo, Goutam Sahana, Mogens Sandø Lund, Maria Ballester, Daniel Crespo‐Piazuelo, Peter Karlskov‐Mortensen, Merete Fredholm, Alex Clop, Marcel Amills, Crystal Loving, Christopher K. Tuggle, Ole Madsen, Jiaqi Li, Zhe Zhang, George E. Liu, Jicai Jiang, Lingzhao Fang, Guoqiang Yi   +31 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

Cost-Informed Bayesian Reaction Optimization

Digital Discovery
Bayesian optimization (BO) is an increasingly popular method for optimization and development of chemical reactions. Although effective in guiding experimental design, BO does not account for experimentation costs: testing readily available reagents under different conditions might be more cost and time-effective than synthesizing or buying additional ...
Alexandre A. Schoepfer, Jan Weinreich, Ruben Laplaza, Jerome Waser, Clemence Corminboeuf   +4 more
openaire   +2 more sources

Formation of Condition‐Dependent Alpha‐Synuclein Fibril Strain in Artificial Cerebrospinal Fluid

Advanced Science, EarlyView.
α‐synuclein aggregation in artificial cerebrospinal fluid (aCSF) leads to a distinct conformation with an electron density pocket motif found in aggregates from PD and MSA patients. Such fibrils has low stability outside the reaction conditions, hinting about the influence of cerebrospinal fluid components not only on the formation, but also on the ...
Rūta Sniečkutė, Darius Šulskis, Arūnė Jocytė, Urtė Venclovaitė, Rimgailė Tamulytė, Mantas Žiaunys, Vytautas Smirnovas, Andrius Sakalauskas   +7 more
wiley   +1 more source

Bayesian Optimization Augmented with Actively Elicited Expert Knowledge [PDF]

, 2022
Daolang Huang, Louis Filstroff, Petrus Mikkola, Runkai Zheng, Samuel Kaski   +4 more
openalex   +1 more source

Reliable AI Platform for Monitoring BCI Caused Brain Injury and Providing Real‐Time Protection

Advanced Science, EarlyView.
BrainGuard enables real‐time and interpretable assessment of brain injury caused by brain computer interface (BCI). Using feature‐based Gaussian process (GP) emulators trained on limited biomechanical data, it efficiently predicts full‐field strain and constructs patient‐specific digital brain twins to support clinical diagnosis and long‐term BCI ...
Chufan He, Yanjun Ding, Timon Rabczuk, Chensen Ding   +3 more
wiley   +1 more source

Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior

, 2018
Bayesian optimization usually assumes that a Bayesian prior is given. However, the strong theoretical guarantees in Bayesian optimization are often regrettably compromised in practice because of unknown parameters in the prior.
Kaelbling, Leslie Pack, Kim, Beomjoon, Wang, Zi   +2 more
core