Percutaneous coronary interventions have progressed through the era of plain balloon dilation, bare-metal stent insertion to drug-eluting stent treatment, which has significantly reduced the acute occlusion and resten...Percutaneous coronary interventions have progressed through the era of plain balloon dilation, bare-metal stent insertion to drug-eluting stent treatment, which has significantly reduced the acute occlusion and restenosis rates of target vessels and improved patient prognosis, making drug-eluting stents the mainstream interventional treatment for coronary artery disease. In recent years, drug-coated balloons(DCBs) have become a new treatment strategy for coronary artery disease, and the drugs used in the coating and the coating technology have progressed in the past years. Without permanent implant, a DCB delivers antiproliferative drugs rapidly and uniformly into the vessel wall via the excipient during a single balloon dilation. Many evidence suggests that DCB angioplasty is an effective measure for dealing with in-stent restenosis and de novo lesions in small coronary vessels.As more clinical studies are published, new evidence is emerging for the use of DCB angioplasty in a wide range of coronary diseases, and the indications are expanding internationally. Based on the latest research from China and elsewhere, the Expert Writing Committee of the Chinese Expert Consensus on Clinical Applications of Drug-Coated Balloon has updated the previous DCB consensus after evidence-based discussions and meetings in terms of adequate preparation of in-stent restenosis lesions, expansion of the indications for coronary de novo lesions, and precise guidance of DCB treatment by intravascular imaging and functional evaluation.展开更多
This review discussed the dilemma of small data faced by materials machine learning.First,we analyzed the limitations brought by small data.Then,the workflow of materials machine learning has been introduced.Next,the ...This review discussed the dilemma of small data faced by materials machine learning.First,we analyzed the limitations brought by small data.Then,the workflow of materials machine learning has been introduced.Next,the methods of dealing with small data were introduced,including data extraction from publications,materials database construction,high-throughput computations and experiments from the data source level;modeling algorithms for small data and imbalanced learning from the algorithm level;active learning and transfer learning from the machine learning strategy level.Finally,the future directions for small data machine learning in materials science were proposed.展开更多
This paper presents a 3D topology optimization approach for designing shell structures with a porous or void interior. It is shown that the resulting structures are significantly more robust towards load perturbations...This paper presents a 3D topology optimization approach for designing shell structures with a porous or void interior. It is shown that the resulting structures are significantly more robust towards load perturbations than completely solid structures optimized under the same conditions. The study indicates that the potential benefit of using porous structures is higher for lower total volume fractions.Compared to earlier work dealing with 2D topology optimization, we found several new effects in 3D problems. Most notably, the opportunity for designing closed shells significantly improves the performance of porous structures due to the sandwich effect. Furthermore, the paper introduces improved filter boundary conditions to ensure a completely uniform coating thickness at the design domain boundary.展开更多
Aimed at evaluating the structural stability and flutter risk of the system, this paper manages to quantify epistemic uncertainty in flutter analysis using evidence theory, including both parametric uncertainty and me...Aimed at evaluating the structural stability and flutter risk of the system, this paper manages to quantify epistemic uncertainty in flutter analysis using evidence theory, including both parametric uncertainty and method selection uncertainty, on the basis of information from limited experimental data of uncertain parameters. Two uncertain variables of the actuator coupling system with unknown probability distributions, that is bending and torsional stiffness, which are both described with multiple intervals and the basic belief assignment（BBA） extricated from the modal test of actuator coupling systems, are taken into account. Considering the difference in dealing with experimental data by different persons and the reliability of various information sources, a new combination rule of evidence––the generalized lower triangular matrices method is formed to acquire the combined BBA. Finally the parametric uncertainty and the epistemic uncertainty of flutter analysis method selection are considered in the same system to realize quantification. A typical rudder of missile is selected to examine the present method, and the dangerous range of velocity as well as relevant belief and plausibility functions is obtained. The results suggest that the present method is effective in obtaining the lower and upper bounds of flutter probability and assessing flutter risk of structures with limited experimental data of uncertain parameters and the belief of different methods.展开更多
1 INTRODUCTION This special issue contains a collection of papers dealing with various aspects of Integrating livestock and crop production systems in different parts of the world.Drafts of some papers were presented ...1 INTRODUCTION This special issue contains a collection of papers dealing with various aspects of Integrating livestock and crop production systems in different parts of the world.Drafts of some papers were presented and discussed at a 2-day international workshop in Quzhou,Hebei,China,during October 9-12,2019.The workshop was combined with a 2-day field trip to visit dairy and poultry farms and rural villages in Hebei.展开更多
Hydrogels are high-water-content soft materials with widely tunable physicochemical properties,resembling soft tissues.Tremendous progress in engineering hydrogels with good biocompatibility,suitable bioactivities,and...Hydrogels are high-water-content soft materials with widely tunable physicochemical properties,resembling soft tissues.Tremendous progress in engineering hydrogels with good biocompatibility,suitable bioactivities,and controlled geometries has made them promising candidates for broad applications.Nevertheless,conventional hydrogels usually suffer from weak mechanical properties,limiting their use in biomedical settings involving load-bearing and persistent mechanical deformations.Inspired by the extreme mechanical properties and multiscale hierarchical structures of biological tissues,mechanically robust tough hydrogels have been developed.Combining robust mechanical properties and other desired performance characteristics in functional tough hydrogels expands their opportunities in biomedical fields.This Account seeks to guide the readership regarding the recent progress in functional tough hydrogels with a focus on molecular/structural design and novel fabrications,particularly surrounding the works reported by our groups.Meanwhile,functional tough hydrogels for multiple biomedical applications are discussed,highlighting the underlying mechanisms governing their relevant applications.We begin by introducing the definition,measurements,and design principles of tough hydrogels and hydrogel adhesives in terms of soft materials mechanics.Various molecular and structural engineering approaches by building mechanical dissipation into stretchable hydrogels to realize stress homogenization or energy dissipation are exploited to fabricate tough hydrogels.Molecular engineering-based network architecture design of homogeneous hydrogels and structural engineering-based design of heterogeneous hydrogels are elaborated.The conventional energy-dissipation-based tough hydrogels are reinforced by the sacrificial bonds or components,leading to a substantial toughness reduction in subsequent loading cycles.To this end,new molecular designs,including highly entangled hydrogels and sliding-ring hydrogels,have been developed to reso展开更多
Inherited cardiovascular diseases(CVDs)threaten human health and pose an enormous economic burden worldwide.Genetic alteration is a major risk factor for many CVDs.These disorders are usually controlled by a pair of a...Inherited cardiovascular diseases(CVDs)threaten human health and pose an enormous economic burden worldwide.Genetic alteration is a major risk factor for many CVDs.These disorders are usually controlled by a pair of alleles,affecting offspring according to the Mendelian principle,regardless of isolated primary damage or secondary injury from other syndromes or deficiency.To date,there are hundreds of inherited CVDs.With advances in nextgeneration sequencing(NGS)technologies,rapid and accurate molecular diagnosis of patients with inherited CVDs is clinically practical.Besides,great improvements have been made in recent years,and targeted therapy and assist devices have been used in clinical practice.Yet there is still no totally efficient strategy for dealing with inherited CVDs.Accordingly.展开更多
Precise chemical cue presentation alongside advanced brainwide imaging techniques is important to the study of chemosensory processing in animals.Nevertheless,the dynamic nature of chemical-carrying media,such as wate...Precise chemical cue presentation alongside advanced brainwide imaging techniques is important to the study of chemosensory processing in animals.Nevertheless,the dynamic nature of chemical-carrying media,such as water or air,poses a significant challenge for delivering highly-controlled chemical flow to an animal subject.Moreover,contact-based cue manipulation and delivery easily shift the position of the animal subject,which is often undesirable for high-quality brain imaging.Additionally,more advanced interfacing tools that align with the diverse range of body part sizes of an animal,ranging from micrometer-scale neurons to meter-long limbs,are much needed.This is particularly crucial when dealing with dimensions that are beyond the reach of conventional experimental tools.展开更多
Frontiers of Environmental Science&Engineering(FESE)is one of the flagship journals of the Chinese Academy of Engineering.It is an international peer-reviewed journal that publishes cutting-edge scientific work in...Frontiers of Environmental Science&Engineering(FESE)is one of the flagship journals of the Chinese Academy of Engineering.It is an international peer-reviewed journal that publishes cutting-edge scientific work in all aspects of environmental disciplines.Since 2007,FESE has been an important platform for communicating the cutting-edge progress of theories,methods,technologies,and policies in environmental science and engineering.Its authors and readers involve scientists,engineers,and policymakers that are important stakeholders in dealing with environmental challenges.Prospective authors are encouraged to review recent issues of FESE to gain a deep understanding of the topics that are of great interest to the journal’s readers.In the cover letter,please clearly state the relevance to the journal’s publication scope and priorities.In particular,prospective authors are directed to the following instructions for further details on the scope,novelty and quality expectations,and minimum requirements.展开更多
Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language models.Training ...Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language models.Training data is the basis for developing detectors;however,the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English resources.This significantly affects the accuracy of Chinese offensive language detectors in practical applications,especially when dealing with hard cases or out-of-domain samples.To alleviate the limitations posed by available datasets,we introduce AugCOLD(Augmented Chinese Offensive Language Dataset),a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model generation.Furthermore,we employ a multiteacher distillation framework to enhance detection performance with unsupervised data.That is,we build multiple teachers with publicly accessible datasets and use them to assign soft labels to AugCOLD.The soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network,i.e.,the final offensive detector.We conduct experiments on multiple public test sets and our well-designed hard tests,demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.展开更多
Achieving carbon neutrality is crucial in dealing with climate change and containing the increase in global temperature at below 1.5℃compared with preindustrial levels.During the general debate at the 75th session of...Achieving carbon neutrality is crucial in dealing with climate change and containing the increase in global temperature at below 1.5℃compared with preindustrial levels.During the general debate at the 75th session of the United Nations General Assembly in September 2020,President Xi Jinping announced that China would adopt more vigorous policies and measures against climate change.展开更多
Machine learning has provided a huge wave of innovation in multiple fields,including computer vision,medical diagnosis,life sciences,molecular design,and instrumental development.This perspective focuses on the implem...Machine learning has provided a huge wave of innovation in multiple fields,including computer vision,medical diagnosis,life sciences,molecular design,and instrumental development.This perspective focuses on the implementation of machine learning in dealing with light-matter interaction,which governs those fields involving materials discovery,optical characterizations,and photonics technologies.We highlight the role of machine learning in accelerating technology development and boosting scientific innovation in the aforementioned aspects.We provide future directions for advanced computing techniques via multidisciplinary efforts that can help to transform optical materials into imaging probes,information carriers and photonics devices.展开更多
文摘Percutaneous coronary interventions have progressed through the era of plain balloon dilation, bare-metal stent insertion to drug-eluting stent treatment, which has significantly reduced the acute occlusion and restenosis rates of target vessels and improved patient prognosis, making drug-eluting stents the mainstream interventional treatment for coronary artery disease. In recent years, drug-coated balloons(DCBs) have become a new treatment strategy for coronary artery disease, and the drugs used in the coating and the coating technology have progressed in the past years. Without permanent implant, a DCB delivers antiproliferative drugs rapidly and uniformly into the vessel wall via the excipient during a single balloon dilation. Many evidence suggests that DCB angioplasty is an effective measure for dealing with in-stent restenosis and de novo lesions in small coronary vessels.As more clinical studies are published, new evidence is emerging for the use of DCB angioplasty in a wide range of coronary diseases, and the indications are expanding internationally. Based on the latest research from China and elsewhere, the Expert Writing Committee of the Chinese Expert Consensus on Clinical Applications of Drug-Coated Balloon has updated the previous DCB consensus after evidence-based discussions and meetings in terms of adequate preparation of in-stent restenosis lesions, expansion of the indications for coronary de novo lesions, and precise guidance of DCB treatment by intravascular imaging and functional evaluation.
基金This work was supported by the National Natural Science Foundation of China(No.52102140)Shanghai Pujiang Program(No.21PJD024)the Key Research Project of Zhejiang Laboratory(No.2021PE0AC02).
文摘This review discussed the dilemma of small data faced by materials machine learning.First,we analyzed the limitations brought by small data.Then,the workflow of materials machine learning has been introduced.Next,the methods of dealing with small data were introduced,including data extraction from publications,materials database construction,high-throughput computations and experiments from the data source level;modeling algorithms for small data and imbalanced learning from the algorithm level;active learning and transfer learning from the machine learning strategy level.Finally,the future directions for small data machine learning in materials science were proposed.
基金financial support from the Villum Foundation (the Next Top Project)DTU Mechanical Engineering
文摘This paper presents a 3D topology optimization approach for designing shell structures with a porous or void interior. It is shown that the resulting structures are significantly more robust towards load perturbations than completely solid structures optimized under the same conditions. The study indicates that the potential benefit of using porous structures is higher for lower total volume fractions.Compared to earlier work dealing with 2D topology optimization, we found several new effects in 3D problems. Most notably, the opportunity for designing closed shells significantly improves the performance of porous structures due to the sandwich effect. Furthermore, the paper introduces improved filter boundary conditions to ensure a completely uniform coating thickness at the design domain boundary.
基金co-supported by the National Natural Science Foundation of China(Nos.:91116005 and 11372023)
文摘Aimed at evaluating the structural stability and flutter risk of the system, this paper manages to quantify epistemic uncertainty in flutter analysis using evidence theory, including both parametric uncertainty and method selection uncertainty, on the basis of information from limited experimental data of uncertain parameters. Two uncertain variables of the actuator coupling system with unknown probability distributions, that is bending and torsional stiffness, which are both described with multiple intervals and the basic belief assignment（BBA） extricated from the modal test of actuator coupling systems, are taken into account. Considering the difference in dealing with experimental data by different persons and the reliability of various information sources, a new combination rule of evidence––the generalized lower triangular matrices method is formed to acquire the combined BBA. Finally the parametric uncertainty and the epistemic uncertainty of flutter analysis method selection are considered in the same system to realize quantification. A typical rudder of missile is selected to examine the present method, and the dangerous range of velocity as well as relevant belief and plausibility functions is obtained. The results suggest that the present method is effective in obtaining the lower and upper bounds of flutter probability and assessing flutter risk of structures with limited experimental data of uncertain parameters and the belief of different methods.
文摘1 INTRODUCTION This special issue contains a collection of papers dealing with various aspects of Integrating livestock and crop production systems in different parts of the world.Drafts of some papers were presented and discussed at a 2-day international workshop in Quzhou,Hebei,China,during October 9-12,2019.The workshop was combined with a 2-day field trip to visit dairy and poultry farms and rural villages in Hebei.
基金funding from the National Institutes of Health(R01HL153857,R01HL165176)the Brigham Research Institute.M.O.A.also acknowledges funding support from the TÜBÍTAK 2214-A Program(1059B141801395).
文摘Hydrogels are high-water-content soft materials with widely tunable physicochemical properties,resembling soft tissues.Tremendous progress in engineering hydrogels with good biocompatibility,suitable bioactivities,and controlled geometries has made them promising candidates for broad applications.Nevertheless,conventional hydrogels usually suffer from weak mechanical properties,limiting their use in biomedical settings involving load-bearing and persistent mechanical deformations.Inspired by the extreme mechanical properties and multiscale hierarchical structures of biological tissues,mechanically robust tough hydrogels have been developed.Combining robust mechanical properties and other desired performance characteristics in functional tough hydrogels expands their opportunities in biomedical fields.This Account seeks to guide the readership regarding the recent progress in functional tough hydrogels with a focus on molecular/structural design and novel fabrications,particularly surrounding the works reported by our groups.Meanwhile,functional tough hydrogels for multiple biomedical applications are discussed,highlighting the underlying mechanisms governing their relevant applications.We begin by introducing the definition,measurements,and design principles of tough hydrogels and hydrogel adhesives in terms of soft materials mechanics.Various molecular and structural engineering approaches by building mechanical dissipation into stretchable hydrogels to realize stress homogenization or energy dissipation are exploited to fabricate tough hydrogels.Molecular engineering-based network architecture design of homogeneous hydrogels and structural engineering-based design of heterogeneous hydrogels are elaborated.The conventional energy-dissipation-based tough hydrogels are reinforced by the sacrificial bonds or components,leading to a substantial toughness reduction in subsequent loading cycles.To this end,new molecular designs,including highly entangled hydrogels and sliding-ring hydrogels,have been developed to reso
基金Key R&D Program of Sichuan Province of China(No.2021YFQ0061)Science and Technology Department of Sichuan Province(No.2022ZYD0067 and MSGC20230024)+2 种基金Natural Science Foundation of China(Nos.82070324,82001496,and 82270249)Project of Chengdu Science and Technology Bureau(No.2021-YF05-02110-SN)China Postdoctoral Science Foundation(Nos.2020M680149 and 2020T130087ZX)
文摘Inherited cardiovascular diseases(CVDs)threaten human health and pose an enormous economic burden worldwide.Genetic alteration is a major risk factor for many CVDs.These disorders are usually controlled by a pair of alleles,affecting offspring according to the Mendelian principle,regardless of isolated primary damage or secondary injury from other syndromes or deficiency.To date,there are hundreds of inherited CVDs.With advances in nextgeneration sequencing(NGS)technologies,rapid and accurate molecular diagnosis of patients with inherited CVDs is clinically practical.Besides,great improvements have been made in recent years,and targeted therapy and assist devices have been used in clinical practice.Yet there is still no totally efficient strategy for dealing with inherited CVDs.Accordingly.
基金funded by a Croucher Innovation Award(CIA20CU01)from the Croucher Foundationthe General Research Fund(14100122)+4 种基金the Collaborative Research Fund(C6027-19GF&C7074-21GF)the Area of Excellence Scheme(AoE/M-604/16)of the Research Grants Councilthe University Grants Committee of Hong Kong,Chinathe Excellent Young Scientists Fund(Hong Kong and Macao,China)(82122001)from the National Natural Science Foundation of Chinathe Lo’s Family Charity Fund Limited(all to HK).
文摘Precise chemical cue presentation alongside advanced brainwide imaging techniques is important to the study of chemosensory processing in animals.Nevertheless,the dynamic nature of chemical-carrying media,such as water or air,poses a significant challenge for delivering highly-controlled chemical flow to an animal subject.Moreover,contact-based cue manipulation and delivery easily shift the position of the animal subject,which is often undesirable for high-quality brain imaging.Additionally,more advanced interfacing tools that align with the diverse range of body part sizes of an animal,ranging from micrometer-scale neurons to meter-long limbs,are much needed.This is particularly crucial when dealing with dimensions that are beyond the reach of conventional experimental tools.
文摘Frontiers of Environmental Science&Engineering(FESE)is one of the flagship journals of the Chinese Academy of Engineering.It is an international peer-reviewed journal that publishes cutting-edge scientific work in all aspects of environmental disciplines.Since 2007,FESE has been an important platform for communicating the cutting-edge progress of theories,methods,technologies,and policies in environmental science and engineering.Its authors and readers involve scientists,engineers,and policymakers that are important stakeholders in dealing with environmental challenges.Prospective authors are encouraged to review recent issues of FESE to gain a deep understanding of the topics that are of great interest to the journal’s readers.In the cover letter,please clearly state the relevance to the journal’s publication scope and priorities.In particular,prospective authors are directed to the following instructions for further details on the scope,novelty and quality expectations,and minimum requirements.
基金supported by the National Science Foundation for Distinguished Young Scholars(with No.62125604)the NSFC projects(Key project with No.61936010 and regular project with No.61876096)+1 种基金supported by the Guoqiang Institute of Tsinghua University,with Grant No.2019GQG1 and 2020GQG0005sponsored by Tsinghua-Toyota Joint Research Fund.
文摘Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language models.Training data is the basis for developing detectors;however,the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English resources.This significantly affects the accuracy of Chinese offensive language detectors in practical applications,especially when dealing with hard cases or out-of-domain samples.To alleviate the limitations posed by available datasets,we introduce AugCOLD(Augmented Chinese Offensive Language Dataset),a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model generation.Furthermore,we employ a multiteacher distillation framework to enhance detection performance with unsupervised data.That is,we build multiple teachers with publicly accessible datasets and use them to assign soft labels to AugCOLD.The soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network,i.e.,the final offensive detector.We conduct experiments on multiple public test sets and our well-designed hard tests,demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.
基金supported by the National Natural Science Foundation of China(72140004).
文摘Achieving carbon neutrality is crucial in dealing with climate change and containing the increase in global temperature at below 1.5℃compared with preindustrial levels.During the general debate at the 75th session of the United Nations General Assembly in September 2020,President Xi Jinping announced that China would adopt more vigorous policies and measures against climate change.
基金supported by the Australian Research Council(ARC)Discovery Early Career Researcher Award Scheme(J.Z.,DE180100669).
文摘Machine learning has provided a huge wave of innovation in multiple fields,including computer vision,medical diagnosis,life sciences,molecular design,and instrumental development.This perspective focuses on the implementation of machine learning in dealing with light-matter interaction,which governs those fields involving materials discovery,optical characterizations,and photonics technologies.We highlight the role of machine learning in accelerating technology development and boosting scientific innovation in the aforementioned aspects.We provide future directions for advanced computing techniques via multidisciplinary efforts that can help to transform optical materials into imaging probes,information carriers and photonics devices.
