As younger consumers increasingly favor experiences over products,“curator”-led cafes and boutiques have emerged across China.Yet with growing pushback against overpriced,underwhelming offerings,is this fad already ...As younger consumers increasingly favor experiences over products,“curator”-led cafes and boutiques have emerged across China.Yet with growing pushback against overpriced,underwhelming offerings,is this fad already losing its appeal?展开更多
cFos is one of the most widely-studied genes in the field of neuroscience.Currently,there is no systematic database focusing on cFos in neuroscience.We developed a curated database-cFos-ANAB-a cFos-based web tool for ...cFos is one of the most widely-studied genes in the field of neuroscience.Currently,there is no systematic database focusing on cFos in neuroscience.We developed a curated database-cFos-ANAB-a cFos-based web tool for exploring activated neurons and associated behaviors in rats and mice,comprising 398 brain nuclei and sub-nuclei,and five associated behaviors:pain,fear,feeding,aggression,and sexual behavior.Direct relationships among behaviors and nuclei(even cell types)under specific stimulating conditions were constructed based on cFos expression profiles extracted from original publications.Moreover,overlapping nuclei and sub-nuclei with potentially complex functions among different associated behaviors were emphasized,leading to results serving as important clues to the development of valid hypotheses for exploring as yet unknown circuits.Using the analysis function of cFos-ANAB,multi-layered pictures of networks and their relationships can quickly be explored depending on users’purposes.These features provide a useful tool and good reference for early exploration in neuroscience.The cFos-ANAB database is available at www.cfos-db.net.展开更多
Characterized by self-monitoring and agile adaptation to fast changing dynamics in complex production environments,smart manufacturing as envisioned under Industry 4.0 aims to improve the throughput and reliability of...Characterized by self-monitoring and agile adaptation to fast changing dynamics in complex production environments,smart manufacturing as envisioned under Industry 4.0 aims to improve the throughput and reliability of production beyond the state-of-the-art.While the widespread application of deep learning(DL)has opened up new opportunities to accomplish the goal,data quality and model interpretability have continued to present a roadblock for the widespread acceptance of DL for real-world applications.This has motivated research on two fronts:data curation,which aims to provide quality data as input for meaningful DL-based analysis,and model interpretation,which intends to reveal the physical reasoning underlying DL model outputs and promote trust from the users.This paper summarizes several key techniques in data curation where breakthroughs in data denoising,outlier detection,imputation,balancing,and semantic annotation have demonstrated the effectiveness in information extraction from noisy,incomplete,insufficient,and/or unannotated data.Also highlighted are model interpretation methods that address the“black-box”nature of DL towards model transparency.展开更多
Since its launch in 2011, the Materials Genome Initiative（MGI） has drawn the attention of researchers from academia,government, and industry worldwide. As one of the three tools of the MGI, the use of materials data...Since its launch in 2011, the Materials Genome Initiative（MGI） has drawn the attention of researchers from academia,government, and industry worldwide. As one of the three tools of the MGI, the use of materials data, for the first time, has emerged as an extremely significant approach in materials discovery. Data science has been applied in different disciplines as an interdisciplinary field to extract knowledge from data. The concept of materials data science has been utilized to demonstrate its application in materials science. To explore its potential as an active research branch in the big data era, a three-tier system has been put forward to define the infrastructure for the classification, curation and knowledge extraction of materials data.展开更多
文摘As younger consumers increasingly favor experiences over products,“curator”-led cafes and boutiques have emerged across China.Yet with growing pushback against overpriced,underwhelming offerings,is this fad already losing its appeal?
基金by the National Natural Science Foundation of China(71974167 and 71573225).
文摘cFos is one of the most widely-studied genes in the field of neuroscience.Currently,there is no systematic database focusing on cFos in neuroscience.We developed a curated database-cFos-ANAB-a cFos-based web tool for exploring activated neurons and associated behaviors in rats and mice,comprising 398 brain nuclei and sub-nuclei,and five associated behaviors:pain,fear,feeding,aggression,and sexual behavior.Direct relationships among behaviors and nuclei(even cell types)under specific stimulating conditions were constructed based on cFos expression profiles extracted from original publications.Moreover,overlapping nuclei and sub-nuclei with potentially complex functions among different associated behaviors were emphasized,leading to results serving as important clues to the development of valid hypotheses for exploring as yet unknown circuits.Using the analysis function of cFos-ANAB,multi-layered pictures of networks and their relationships can quickly be explored depending on users’purposes.These features provide a useful tool and good reference for early exploration in neuroscience.The cFos-ANAB database is available at www.cfos-db.net.
文摘Characterized by self-monitoring and agile adaptation to fast changing dynamics in complex production environments,smart manufacturing as envisioned under Industry 4.0 aims to improve the throughput and reliability of production beyond the state-of-the-art.While the widespread application of deep learning(DL)has opened up new opportunities to accomplish the goal,data quality and model interpretability have continued to present a roadblock for the widespread acceptance of DL for real-world applications.This has motivated research on two fronts:data curation,which aims to provide quality data as input for meaningful DL-based analysis,and model interpretation,which intends to reveal the physical reasoning underlying DL model outputs and promote trust from the users.This paper summarizes several key techniques in data curation where breakthroughs in data denoising,outlier detection,imputation,balancing,and semantic annotation have demonstrated the effectiveness in information extraction from noisy,incomplete,insufficient,and/or unannotated data.Also highlighted are model interpretation methods that address the“black-box”nature of DL towards model transparency.
基金Project supported by the National Key R&D Program of China(Grant No.2016YFB0700503)the National High Technology Research and Development Program of China(Grant No.2015AA03420)+2 种基金Beijing Municipal Science and Technology Project,China(Grant No.D161100002416001)the National Natural Science Foundation of China(Grant No.51172018)Kennametal Inc
文摘Since its launch in 2011, the Materials Genome Initiative（MGI） has drawn the attention of researchers from academia,government, and industry worldwide. As one of the three tools of the MGI, the use of materials data, for the first time, has emerged as an extremely significant approach in materials discovery. Data science has been applied in different disciplines as an interdisciplinary field to extract knowledge from data. The concept of materials data science has been utilized to demonstrate its application in materials science. To explore its potential as an active research branch in the big data era, a three-tier system has been put forward to define the infrastructure for the classification, curation and knowledge extraction of materials data.
