2015-12-30 , Volume 1 Issue 4

Cover illustration

  •  

    The cover image shows an example of smart grid wide-area visualizations. In the image the electric load is shown in white and the generation in magenta for a synthetic power flow model of the four major electric grids in North America. See page 468.

    Download cover

  • Select all
    News & Highlights
  • News & Highlights
    Nitroxyl, a New Generation of Positive Inotropic Agent for Heart Failure
    [Author(id=1166055714499256632, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055714646057274, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, authorId=1166055714499256632, language=EN, stringName=Ye Tian, firstName=Ye, middleName=null, lastName=Tian, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Pathophysiology, Harbin Medical University, Harbin 150086, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055714750914875, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, authorId=1166055714499256632, language=CN, stringName=Ye Tian, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Pathophysiology, Harbin Medical University, Harbin 150086, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055714864161085, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055715010961727, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, authorId=1166055714864161085, language=EN, stringName=Nazareno Paolocci, firstName=Nazareno, middleName=null, lastName=Paolocci, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055715120013632, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, authorId=1166055714864161085, language=CN, stringName=Nazareno Paolocci, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055715237454146, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055715384254788, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, authorId=1166055715237454146, language=EN, stringName=Wei Dong Gao, firstName=Wei Dong, middleName=null, lastName=Gao, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=3, address=3  Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055715489112389, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829267393602479, authorId=1166055715237454146, language=CN, stringName=Wei Dong Gao, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=3, address=3  Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)] Ye Tian , Nazareno Paolocci , Wei Dong Gao

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Views & Comments
  • Views & Comments
    Basic Ideas of the Smart Grid
    [Author(id=1166053555879731734, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053556018143768, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, authorId=1166053555879731734, language=EN, stringName=Yixin Yu, firstName=Yixin, middleName=null, lastName=Yu, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053556123001369, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, authorId=1166053555879731734, language=CN, stringName=余贻鑫, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053556223664667, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053556366271005, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, authorId=1166053556223664667, language=EN, stringName=Yanli Liu, firstName=Yanli, middleName=null, lastName=Liu, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053556466934302, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, authorId=1166053556223664667, language=CN, stringName=刘艳丽, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053556575986208, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053556718592546, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, authorId=1166053556575986208, language=EN, stringName=Chao Qin, firstName=Chao, middleName=null, lastName=Qin, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053556823450147, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827409241432627, authorId=1166053556575986208, language=CN, stringName=秦超, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)] Yixin Yu , Yanli Liu , Chao Qin

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Views & Comments
    Fall of the Titans The Demise of Basic Neuroscience Research
    [Author(id=1166053760704372826, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827898859315669, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053760846979164, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827898859315669, authorId=1166053760704372826, language=EN, stringName=Sergio Canavero, firstName=Sergio, middleName=null, lastName=Canavero, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Turin Advanced Neuromodulation Group, Turin 10132, Italy, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053760947642461, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827898859315669, authorId=1166053760704372826, language=CN, stringName=Sergio Canavero, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Turin Advanced Neuromodulation Group, Turin 10132, Italy, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053761048305759, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827898859315669, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053761182523489, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827898859315669, authorId=1166053761048305759, language=EN, stringName=Vincenzo Bonicalzi, firstName=Vincenzo, middleName=null, lastName=Bonicalzi, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Turin Advanced Neuromodulation Group, Turin 10132, Italy, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053761283186786, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827898859315669, authorId=1166053761048305759, language=CN, stringName=Vincenzo Bonicalzi, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Turin Advanced Neuromodulation Group, Turin 10132, Italy, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)] Sergio Canavero , Vincenzo Bonicalzi

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
  • Research
    An Overview of the Smart Grid in Great Britain
    [Author(id=1166055836352176980, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055836507366230, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, authorId=1166055836352176980, language=EN, stringName=Nick Jenkins, firstName=Nick, middleName=null, lastName=Jenkins, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055836616418135, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, authorId=1166055836352176980, language=CN, stringName=Nick Jenkins, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055837593690975, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055837736297315, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, authorId=1166055837593690975, language=EN, stringName=Chao Long, firstName=Chao, middleName=null, lastName=Long, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055837841154917, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, authorId=1166055837593690975, language=CN, stringName=Chao Long, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055837946012521, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055838084424557, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, authorId=1166055837946012521, language=EN, stringName=Jianzhong Wu, firstName=Jianzhong, middleName=null, lastName=Wu, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055838189282159, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829672026497651, authorId=1166055837946012521, language=CN, stringName=Jianzhong Wu, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address= Institute of Energy, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)] Nick Jenkins , Chao Long , Jianzhong Wu

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies
    [Author(id=1166053706568491912, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053706757235596, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053706568491912, language=EN, stringName=David P. Chassin, firstName=David P., middleName=null, lastName=Chassin, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, 3, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada
    3  Pacific Northwest National Laboratory, Richland, WA 99352, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053706853704589, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053706568491912, language=CN, stringName=David P. Chassin, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, 3, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada
    3  Pacific Northwest National Laboratory, Richland, WA 99352, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053706945979279, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053707096974226, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053706945979279, language=EN, stringName=Sahand Behboodi, firstName=Sahand, middleName=null, lastName=Behboodi, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053707193443219, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053706945979279, language=CN, stringName=Sahand Behboodi, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053707285717909, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053707436712856, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053707285717909, language=EN, stringName=Curran Crawford, firstName=Curran, middleName=null, lastName=Crawford, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053707533181849, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053707285717909, language=CN, stringName=Curran Crawford, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053707625456539, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053707810005919, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053707625456539, language=EN, stringName=Ned Djilali), firstName=Ned, middleName=null, lastName=Djilali), prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, 4, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada
    4  Renewable Energy Research Group, King Abdulaziz University, Jeddah, Makkah 21589, Saudi Arabia, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053707898086304, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827521585865458, authorId=1166053707625456539, language=CN, stringName=Ned Djilali, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, 4, address=1  Department of Mechanical Engineering, University of Victoria, Victoria, BC V8W 2Y2, Canada
    2  Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada
    4  Renewable Energy Research Group, King Abdulaziz University, Jeddah, Makkah 21589, Saudi Arabia, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)]
    David P. Chassin , Sahand Behboodi , Curran Crawford , Ned Djilali)

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    Smart Grids with Intelligent Periphery: An Architecture for the Energy Internet
    [Author(id=1166055900927681070, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055901103841841, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, authorId=1166055900927681070, language=EN, stringName=Felix F. Wu, firstName=Felix F., middleName=null, lastName=Wu, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
    2  Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055901212893746, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, authorId=1166055900927681070, language=CN, stringName=Felix F. Wu, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
    2  Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055901317751348, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055901456163382, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, authorId=1166055901317751348, language=EN, stringName=Pravin P. Varaiya, firstName=Pravin P., middleName=null, lastName=Varaiya, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055901565215287, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, authorId=1166055901317751348, language=CN, stringName=Pravin P. Varaiya, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055901670072889, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055901808484923, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, authorId=1166055901670072889, language=EN, stringName=Ron S. Y. Hui, firstName=Ron S. Y., middleName=null, lastName=Hui, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055901917536828, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829739135361786, authorId=1166055901670072889, language=CN, stringName=Ron S. Y. Hui, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)]
    Felix F. Wu , Pravin P. Varaiya , Ron S. Y. Hui

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    An Approach for Cost-Efficient Grid Integration of Distributed Renewable Energy Sources
    [Author(id=1166053590319162000, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053590407242385, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053590319162000, language=EN, stringName=Till Luhmann, firstName=Till, middleName=null, lastName=Luhmann, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053590486934162, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053590319162000, language=CN, stringName=Till Luhmann, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053590570820244, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053590650512021, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053590570820244, language=EN, stringName=Enno Wieben, firstName=Enno, middleName=null, lastName=Wieben, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053590738592406, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053590570820244, language=CN, stringName=Enno Wieben, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053590818284184, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053590902170265, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053590818284184, language=EN, stringName=Riccardo Treydel, firstName=Riccardo, middleName=null, lastName=Treydel, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053590986056346, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053590818284184, language=CN, stringName=Riccardo Treydel, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053591069942428, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053591158022813, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053591069942428, language=EN, stringName=Michael Stadler, firstName=Michael, middleName=null, lastName=Stadler, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053591246103198, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053591069942428, language=CN, stringName=Michael Stadler, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166053591329989280, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166053591413875361, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053591329989280, language=EN, stringName=Thomas Kumm, firstName=Thomas, middleName=null, lastName=Kumm, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166053591497761442, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159827428266795596, authorId=1166053591329989280, language=CN, stringName=Thomas Kumm, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=null, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)] Till Luhmann , Enno Wieben , Riccardo Treydel , Michael Stadler , Thomas Kumm

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    Combining Market-Based Control with Distribution Grid Constraints when Coordinating Electric Vehicle Charging
    [Author(id=1166056116921753875, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829807007589329, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056117047582997, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829807007589329, authorId=1166056116921753875, language=EN, stringName=Geert Deconinck, firstName=Geert, middleName=null, lastName=Deconinck, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 KU Leuven-EnergyVille, Leuven 3001, Belgium, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056117139857686, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829807007589329, authorId=1166056116921753875, language=CN, stringName=Geert Deconinck, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 KU Leuven-EnergyVille, Leuven 3001, Belgium, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166056117236326680, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829807007589329, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056117362155802, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829807007589329, authorId=1166056117236326680, language=EN, stringName=Klaas De Craemer, firstName=Klaas De, middleName=null, lastName=Craemer, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  VITO-EnergyVille, Mol 2400, Belgium, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056117454430491, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829807007589329, authorId=1166056117236326680, language=CN, stringName=Bert Claessens, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  VITO-EnergyVille, Mol 2400, Belgium, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)] Geert Deconinck , Klaas De Craemer

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    Smart Grid Wide-Area Transmission System Visualization
    [Author(id=1166056088635367452, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829766784213920, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056089679749157, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829766784213920, authorId=1166056088635367452, language=EN, stringName=Thomas J. Overbye, firstName=Thomas J., middleName=null, lastName=Overbye, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056089797189670, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829766784213920, authorId=1166056088635367452, language=CN, stringName=Thomas J. Overbye, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166056089918824488, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829766784213920, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056090099179564, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829766784213920, authorId=1166056089918824488, language=EN, stringName=James Weber, firstName=James, middleName=null, lastName=Weber, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  PowerWorld Corporation, Champaign, IL 61820, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056090204037165, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829766784213920, authorId=1166056089918824488, language=CN, stringName=James Weber, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  PowerWorld Corporation, Champaign, IL 61820, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)] Thomas J. Overbye , James Weber

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    Recent Advances in 19Fluorine Magnetic Resonance Imaging with Perfluorocarbon Emulsions
    [Author(id=1166055896221671918, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055896355889652, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055896221671918, language=EN, stringName=Anne H. Schmieder, firstName=Anne H., middleName=null, lastName=Schmieder, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Division of Cardiology, Washington University School of Medical, St. Louis, MO 63110, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055896460747254, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055896221671918, language=CN, stringName=Anne H. Schmieder, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Division of Cardiology, Washington University School of Medical, St. Louis, MO 63110, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055896565604856, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055896737571323, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055896565604856, language=EN, stringName=Shelton D. Caruthers, firstName=Shelton D., middleName=null, lastName=Caruthers, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, 3, address=2  Toshiba Medical Research Institute USA, Inc., Cleveland, OH 44143, USA
    3  Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055896850817532, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055896565604856, language=CN, stringName=Shelton D. Caruthers, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, 3, address=2  Toshiba Medical Research Institute USA, Inc., Cleveland, OH 44143, USA
    3  Department of Biomedical Engineering, Washington University, St. Louis, MO 63130, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055896951480830, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055897089892864, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055896951480830, language=EN, stringName=Jochen Keupp, firstName=Jochen, middleName=null, lastName=Keupp, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=4, address=4  Philips Research Hamburg, Hamburg 22335, Germany, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055897194750465, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055896951480830, language=CN, stringName=Jochen Keupp, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=4, address=4  Philips Research Hamburg, Hamburg 22335, Germany, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055897299608067, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055897438020101, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055897299608067, language=EN, stringName=Samuel A. Wickline, firstName=Samuel A., middleName=null, lastName=Wickline, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Division of Cardiology, Washington University School of Medical, St. Louis, MO 63110, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055897547072006, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055897299608067, language=CN, stringName=Samuel A. Wickline, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Division of Cardiology, Washington University School of Medical, St. Louis, MO 63110, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055897647735304, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055897786147338, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055897647735304, language=EN, stringName=Gregory M. Lanza, firstName=Gregory M., middleName=null, lastName=Lanza, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Division of Cardiology, Washington University School of Medical, St. Louis, MO 63110, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055897891004939, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829703995482763, authorId=1166055897647735304, language=CN, stringName=Gregory M. Lanza, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Division of Cardiology, Washington University School of Medical, St. Louis, MO 63110, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)]
    Anne H. Schmieder , Shelton D. Caruthers , Jochen Keupp , Samuel A. Wickline , Gregory M. Lanza

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    Cardiac Remote Conditioning and Clinical Relevance: All Together Now!
    [Author(id=1166055837652411233, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055837790823268, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055837652411233, language=EN, stringName=Kristin Luther, firstName=Kristin, middleName=null, lastName=Luther, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055837883097958, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055837652411233, language=CN, stringName=Kristin Luther, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055837975372650, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055838097007470, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055837975372650, language=EN, stringName=Yang Song, firstName=Yang, middleName=null, lastName=Song, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  Hand and Microsurgical Center, TheSecond Affi liated Hospital of Harbin Medical University, Harbin 150001, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055838189282160, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055837975372650, language=CN, stringName=Yang Song, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2  Hand and Microsurgical Center, TheSecond Affi liated Hospital of Harbin Medical University, Harbin 150001, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055838289945457, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055838411580276, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055838289945457, language=EN, stringName=Yang Wang, firstName=Yang, middleName=null, lastName=Wang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055838503854966, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055838289945457, language=CN, stringName=Yang Wang, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055838600323959, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055838755513212, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055838600323959, language=EN, stringName=Xiaoping Ren, firstName=Xiaoping, middleName=null, lastName=Ren, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA
    2  Hand and Microsurgical Center, TheSecond Affi liated Hospital of Harbin Medical University, Harbin 150001, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055838851982206, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055838600323959, language=CN, stringName=Xiaoping Ren, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA
    2  Hand and Microsurgical Center, TheSecond Affi liated Hospital of Harbin Medical University, Harbin 150001, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055838944256896, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055839065891715, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055838944256896, language=EN, stringName=W. Keith Jones), firstName=W. Keith, middleName=null, lastName=Jones), prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055839162360709, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829665231725169, authorId=1166055838944256896, language=CN, stringName=W. Keith Jones, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1  Department of Molecular Pharmacology and Therapeutics, Stritch School of Medicine, Loyola University, Chicago, IL 60153, USA, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)]
    Kristin Luther , Yang Song , Yang Wang , Xiaoping Ren , W. Keith Jones)

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    Conjugation with Acridines Turns Nuclear Localization Sequence into Highly Active Antimicrobial Peptide
    [Author(id=1166055872372859058, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055872544825527, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055872372859058, language=EN, stringName=Wei Zhang, firstName=Wei, middleName=null, lastName=Zhang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055872645488824, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055872372859058, language=CN, stringName=Wei Zhang, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055872754540730, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055872926507199, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055872754540730, language=EN, stringName=Xiaoli Yang, firstName=Xiaoli, middleName=null, lastName=Yang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055873031364801, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055872754540730, language=CN, stringName=Xiaoli Yang, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055873132028100, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055873299800265, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055873132028100, language=EN, stringName=Jingjing Song, firstName=Jingjing, middleName=null, lastName=Song, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055873408852171, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055873132028100, language=CN, stringName=Jingjing Song, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055873513709775, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055873698259155, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055873513709775, language=EN, stringName=Xin Zheng, firstName=Xin, middleName=null, lastName=Zheng, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055873807311061, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055873513709775, language=CN, stringName=Xin Zheng, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055873916362968, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055874096718045, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055873916362968, language=EN, stringName=Jianbo Chen, firstName=Jianbo, middleName=null, lastName=Chen, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055874201575648, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055873916362968, language=CN, stringName=Jianbo Chen, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055874310627554, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=5, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055874499371238, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055874310627554, language=EN, stringName=Panpan Ma, firstName=Panpan, middleName=null, lastName=Ma, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055874604228840, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055874310627554, language=CN, stringName=Panpan Ma, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055874742640873, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=6, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055874906218733, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055874742640873, language=EN, stringName=Bangzhi Zhang, firstName=Bangzhi, middleName=null, lastName=Zhang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055875011076335, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055874742640873, language=CN, stringName=Bangzhi Zhang, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166055875115933938, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, orderNo=7, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166055875287900408, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055875115933938, language=EN, stringName=Rui Wang, firstName=Rui, middleName=null, lastName=Wang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166055875392758010, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829698026988165, authorId=1166055875115933938, language=CN, stringName=Rui Wang, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1  Key Laboratory of Preclinical Study for New Drugs of Gansu Province, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
    2  Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou 730000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)]
    Wei Zhang , Xiaoli Yang , Jingjing Song , Xin Zheng , Jianbo Chen , Panpan Ma , Bangzhi Zhang , Rui Wang

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.

  • Research
    A Personal Desktop Liquid-Metal Printer as a Pervasive Electronics Manufacturing Tool for Society in the Near Future
    [Author(id=1166056031844491986, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056031999681236, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056031844491986, language=EN, stringName=Jun Yang, firstName=Jun, middleName=null, lastName=Yang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056032108733141, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056031844491986, language=CN, stringName=Jun Yang, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166056032226173655, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056032372974297, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056032226173655, language=EN, stringName=Yang Yang, firstName=Yang, middleName=null, lastName=Yang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056032486220506, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056032226173655, language=CN, stringName=Yang Yang, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166056032603661020, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056032750461662, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056032603661020, language=EN, stringName=Zhizhu He, firstName=Zhizhu, middleName=null, lastName=He, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056033778066143, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056032603661020, language=CN, stringName=Zhizhu He, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166056033916478177, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056034067473123, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056033916478177, language=EN, stringName=Bowei Chen, firstName=Bowei, middleName=null, lastName=Chen, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056034184913636, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056033916478177, language=CN, stringName=Bowei Chen, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null), Author(id=1166056034528846566, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1166056034713395946, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056034528846566, language=EN, stringName=Jing Liu, firstName=Jing, middleName=null, lastName=Liu, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China
    2 Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1166056034818253547, tenantId=1045748351789510663, journalId=1155139928190095384, articleId=1159829713436861111, authorId=1166056034528846566, language=CN, stringName=Jing Liu, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1 Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China
    2 Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=null)]
    Jun Yang , Yang Yang , Zhizhu He , Bowei Chen , Jing Liu

    Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review paper provides a thorough illustration of these applications using different ML and DL approaches. The first part of the paper examines the basics of various particle physics types and establishes guidelines for assessing particle physics alongside the available learning models. Next, a detailed classification is provided for representing Jets that are reconstructed in high-energy collisions, mainly in proton-proton collisions at well-defined beam energies. This section covers various datasets, preprocessing techniques, and feature extraction and selection methods. The presented techniques can be applied to future hadron−hadron colliders (HHC), such as the high-luminosity LHC (HL-LHC) and the future circular collider−hadron−hadron (FCC-hh). The authors then explore several AI techniques analyses designed specifically for both image and point-cloud (PC) data in HEP. Additionally, a closer look is taken at the classification associated with Jet tagging in hadron collisions. In this review, various state-of-the-art (SOTA) techniques in ML and DL are examined, with a focus on their implications for HEP demands. More precisely, this discussion addresses various applications in extensive detail, such as Jet tagging, Jet tracking, and particle classification. The review concludes with an analysis of the current state of HEP using DL methodologies. It highlights the challenges and potential areas for future research, which are illustrated for each application.