The model for protection of personal information dis-closed according to the law has changed from indirect protection to direct protection.The indirect protection model for traditional repu-tation rights and privacy r...The model for protection of personal information dis-closed according to the law has changed from indirect protection to direct protection.The indirect protection model for traditional repu-tation rights and privacy rights was not enough to meet the practical needs of governance.However;due to the ambiguity in the application of the“reasonable”processing requirements,the direct protection model centered on Article 27 of the Personal Information Protection Law also is not enough to effectively respond to practical disputes.The essence of the problem is to resolve the tension between informa-tion circulation and risk control and reshape the legal order for the protection of personal information disclosed according to the law.The determination of“reasonable”should be centered on the scenario theory and holism interpretation and carried out by using the interpre-tation technique of the dynamic system under Article 998 of the Civil Code.With the support of scenario-based discussions and comparative propositions,the crawling and tag extraction of personal information.disclosed according to the law should be considered as reasonable processing;profiling and automated decision-making should not be covered in the scope of reasonable processing,in principle;for behav-iors such as correlation analysis,elements like information subject,identifiability and sensitivity should be comprehensively considered to draw open and inclusive conclusions in individual cases.展开更多
The possibility and rationality of introducing an bid-winning estimate based on a reasonable low price into construction bidding mode with bill of quantities were analyzed by setting up a model for bidding and tenderi...The possibility and rationality of introducing an bid-winning estimate based on a reasonable low price into construction bidding mode with bill of quantities were analyzed by setting up a model for bidding and tendering, and the functions of the estimate of reasonable low price in the bidding were revealed. On this basis, a new bidding mode of the project with bill of quantities was pro- posed. The application of the new mode will be advantageous to the promotion of the bill of quantities in China.展开更多
In this thesis, the interal relations between about shear looking, zero energy mode and patch test are studied, and a reasonable method provided for building general element of thick and thin plate with effectual and ...In this thesis, the interal relations between about shear looking, zero energy mode and patch test are studied, and a reasonable method provided for building general element of thick and thin plate with effectual and realiable numerical solution.展开更多
In April,the economy performed within a reasonable range,and sustained momentum of progress in overall stability.1.The service sector grew rapidly and modern service industries grew well In April,the Index of Services...In April,the economy performed within a reasonable range,and sustained momentum of progress in overall stability.1.The service sector grew rapidly and modern service industries grew well In April,the Index of Services Production increased by 7.4%year on year;0.2 percentage point slower than that of March,and 0.1 percentage point faster than that of the first two months.展开更多
Speech by Ji Bingxuan,Vice Chairman of the Standing Committee of the NPC and Vice President of CAFIU at the Opening Ceremony of the 35th Annual Meeting of the Inter Action Council Distinguished guests,Ladies and gentl...Speech by Ji Bingxuan,Vice Chairman of the Standing Committee of the NPC and Vice President of CAFIU at the Opening Ceremony of the 35th Annual Meeting of the Inter Action Council Distinguished guests,Ladies and gentlemen,friends:Good morning!展开更多
Both reasonable accommodation and accessibility are crucial concepts in the UN Convent ion on the Rights of Persons with Disabilities Those two concepts promote each other and should develop as a whole State parties...Both reasonable accommodation and accessibility are crucial concepts in the UN Convent ion on the Rights of Persons with Disabilities Those two concepts promote each other and should develop as a whole State parties of the Convention undertake immediate obligations to ensure the provision of reasonable accommodation, which has advantages such as characteristics of subjective rights, individualization, justiciability and convenience, making it a flexible tool for the protection of rights It can serve as a supplement to insufficient accessibility and play a unique role in other areas which are irrelevant to accessibility, so as to satisfy the special needs of certain subjects to the largest extent The State Party has an ex ante and progressive obligations to the realization of the accessibility construction, which has advantages of comman design, large scale, economization and no need for individualization consideration In China, various forms of reasonable accommodation have been applied in employment, but they have disadvantages of contingency, randomness, simplicity and lack of systematic support In the process of further promoting the employment of people with disabilities in China, in addition to strengthening accessibility construction, we must fully understand and flexibly adopt reasonable accommodation.展开更多
Injection of gas (CO_(2)) into coal seams is an effective method to benefit from both CO_(2) geological storage and coalbed methane recovery. Based on the dual pore structure of coal mass, and the Weibull distribution...Injection of gas (CO_(2)) into coal seams is an effective method to benefit from both CO_(2) geological storage and coalbed methane recovery. Based on the dual pore structure of coal mass, and the Weibull distribution of fracture permeability, a menmal-hydraulic-mechanical (THM) coupling mathematical model is proposed involving the non-isothermal adsorption of binary gases, dynamic gas diffusion between matrix and fractures, multiphase seepage, coal deformation, heat conduction and heat convection. This mathematical model is applied to study the process of CO_(2)-enhanced coalbed methane recovery (CO_(2)-ECBM). Results show that the CH4 content of CO_(2)-ECBM in coal seam decreases significantly when compared with that of regular drainage, and decreases rapidly in the early stage but slowly in the later stage. Coal seam permeability evolution is triggered by changes in gas adsorption/desorption, temperature and effective stress. For regular drainage, the early permeability shows a decreasing trend dominated by the increase of effective stress, while the later permeability shows an increasing trend dominated by the CH4 desorption caused shrinkage of coal matrix. For CO_(2)-ECBM, the permeability in coal seam generally shows a downward trend due to both matrix swelling induced by gas adsorption and thermal expansion, particularly near injection well. There appears an increased and delayed peak production rate of CH4. The CH4 production rate of CO_(2)-ECBM is always higher than that of regular drainage. The CH4 cumulative production and CO_(2) cumulative storage linearly increase with time, and the CH4 cumulative production of CO_(2)-ECBM increased by 39.2% in the duration of 5000 d compared with regular drainage. Reasonable CO_(2) injection starting time can overcome the issue of early CO_(2) breakthrough and ineffective increase of CH4 production. In the studied case, the optimal injection starting time is 2500 d. Compared with the simultaneous CH4 extraction and CO_(2) injection, the CH4 cumulative production of optimal time has increased by 30.1%. The research provides a reference for determining the reasonable CO_(2) injection time under similar conditions.展开更多
The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the settin...The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.展开更多
Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been studied.The aim of this study is to compare the char...Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been studied.The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.Design/methodology/approach:The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases.These publications were categorized based on their OA levels,including Gold OA,Green OA,and non-OA.The study explored retraction rates,time lags and reasons within these categories.Findings:The findings of this research revealed distinct patterns in retraction rates among different OA levels.Publications with Gold OA demonstrated the highest retraction rate,followed by Green OA and non-OA.A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions,while Green OA exhibited a higher proportion due to falsification and manipulation issues,along with a lower occurrence of plagiarism and authorship issues.The retraction time lag was shortest for Gold OA,followed by non-OA,and longest for Green OA.The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.A comparative study on characteristics of retracted publications across different open access levels Research limitations:There is no exploration of a wider range of OA levels,such as Hybrid OA and Bronze OA.Practical implications:The outcomes of this study suggest the need for increased attention to research integrity within the OA publications.The occurrences offalsification,manipulation,and ethical concerns within Green OA publications warrant attention from the scientific community.Originality/value:This study contributes to the understanding of research integrity in the realm of OA publications,shedding light on retraction patterns and reasons across different OA levels.展开更多
The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interest...The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.展开更多
In recent years,with the continuous development of deep learning and knowledge graph reasoning methods,more and more researchers have shown great interest in improving knowledge graph reasoning methods by inferring mi...In recent years,with the continuous development of deep learning and knowledge graph reasoning methods,more and more researchers have shown great interest in improving knowledge graph reasoning methods by inferring missing facts through reasoning.By searching paths on the knowledge graph and making fact and link predictions based on these paths,deep learning-based Reinforcement Learning(RL)agents can demonstrate good performance and interpretability.Therefore,deep reinforcement learning-based knowledge reasoning methods have rapidly emerged in recent years and have become a hot research topic.However,even in a small and fixed knowledge graph reasoning action space,there are still a large number of invalid actions.It often leads to the interruption of RL agents’wandering due to the selection of invalid actions,resulting in a significant decrease in the success rate of path mining.In order to improve the success rate of RL agents in the early stages of path search,this article proposes a knowledge reasoning method based on Deep Transfer Reinforcement Learning path(DTRLpath).Before supervised pre-training and retraining,a pre-task of searching for effective actions in a single step is added.The RL agent is first trained in the pre-task to improve its ability to search for effective actions.Then,the trained agent is transferred to the target reasoning task for path search training,which improves its success rate in searching for target task paths.Finally,based on the comparative experimental results on the FB15K-237 and NELL-995 datasets,it can be concluded that the proposed method significantly improves the success rate of path search and outperforms similar methods in most reasoning tasks.展开更多
Fair exchange protocols play a critical role in enabling two distrustful entities to conduct electronic data exchanges in a fair and secure manner.These protocols are widely used in electronic payment systems and elec...Fair exchange protocols play a critical role in enabling two distrustful entities to conduct electronic data exchanges in a fair and secure manner.These protocols are widely used in electronic payment systems and electronic contract signing,ensuring the reliability and security of network transactions.In order to address the limitations of current research methods and enhance the analytical capabilities for fair exchange protocols,this paper proposes a formal model for analyzing such protocols.The proposed model begins with a thorough analysis of fair exchange protocols,followed by the formal definition of fairness.This definition accurately captures the inherent requirements of fair exchange protocols.Building upon event logic,the model incorporates the time factor into predicates and introduces knowledge set axioms.This enhancement empowers the improved logic to effectively describe the state and knowledge of protocol participants at different time points,facilitating reasoning about their acquired knowledge.To maximize the intruder’s capabilities,channel errors are translated into the behaviors of the intruder.The participants are further categorized into honest participants and malicious participants,enabling a comprehensive evaluation of the intruder’s potential impact.By employing a typical fair exchange protocol as an illustrative example,this paper demonstrates the detailed steps of utilizing the proposed model for protocol analysis.The entire process of protocol execution under attack scenarios is presented,shedding light on the underlying reasons for the attacks and proposing corresponding countermeasures.The developedmodel enhances the ability to reason about and evaluate the security properties of fair exchange protocols,thereby contributing to the advancement of secure network transactions.展开更多
Purpose:The notable increase in retraction papers has attracted considerable attention from diverse stakeholders.Various sources are now offering information related to research integrity,including concerns voiced on ...Purpose:The notable increase in retraction papers has attracted considerable attention from diverse stakeholders.Various sources are now offering information related to research integrity,including concerns voiced on social media,disclosed lists of paper mills,and retraction notices accessible through journal websites.However,despite the availability of such resources,there remains a lack of a unified platform to consolidate this information,thereby hindering efficient searching and cross-referencing.Thus,it is imperative to develop a comprehensive platform for retracted papers and related concerns.This article aims to introduce“Amend,”a platform designed to integrate information on research integrity from diverse sources.Design/methodology/approach:The Amend platform consolidates concerns and lists of problematic articles sourced from social media platforms(e.g.,PubPeer,For Better Science),retraction notices from journal websites,and citation databases(e.g.,Web of Science,CrossRef).Moreover,Amend includes investigation and punishment announcements released by administrative agencies(e.g.,NSFC,MOE,MOST,CAS).Each related paper is marked and can be traced back to its information source via a provided link.Furthermore,the Amend database incorporates various attributes of retracted articles,including citation topics,funding details,open access status,and more.The reasons for retraction are identified and classified as either academic misconduct or honest errors,with detailed subcategories provided for further clarity.Findings:Within the Amend platform,a total of 32,515 retracted papers indexed in SCI,SSCI,and ESCI between 1980 and 2023 were identified.Of these,26,620(81.87%)were associated with academic misconduct.The retraction rate stands at 6.64 per 10,000 articles.Notably,the retraction rate for non-gold open access articles significantly differs from that for gold open access articles,with this disparity progressively widening over the years.Furthermore,the reasons for retractions have shifted from traditional individual behaviors like falsification,fabrication,plagiarism,and duplication to more organized large-scale fraudulent practices,including Paper Mills,Fake Peer-review,and Artificial Intelligence Generated Content(AIGC).Research limitations:The Amend platform may not fully capture all retracted and concerning papers,thereby impacting its comprehensiveness.Additionally,inaccuracies in retraction notices may lead to errors in tagged reasons.Practical implications:Amend provides an integrated platform for stakeholders to enhance monitoring,analysis,and research on academic misconduct issues.Ultimately,the Amend database can contribute to upholding scientific integrity.Originality/value:This study introduces a globally integrated platform for retracted and concerning papers,along with a preliminary analysis of the evolutionary trends in retracted papers.展开更多
Knowledge graph(KG)serves as a specialized semantic network that encapsulates intricate relationships among real-world entities within a structured framework.This framework facilitates a transformation in information ...Knowledge graph(KG)serves as a specialized semantic network that encapsulates intricate relationships among real-world entities within a structured framework.This framework facilitates a transformation in information retrieval,transitioning it from mere string matching to far more sophisticated entity matching.In this transformative process,the advancement of artificial intelligence and intelligent information services is invigorated.Meanwhile,the role ofmachine learningmethod in the construction of KG is important,and these techniques have already achieved initial success.This article embarks on a comprehensive journey through the last strides in the field of KG via machine learning.With a profound amalgamation of cutting-edge research in machine learning,this article undertakes a systematical exploration of KG construction methods in three distinct phases:entity learning,ontology learning,and knowledge reasoning.Especially,a meticulous dissection of machine learningdriven algorithms is conducted,spotlighting their contributions to critical facets such as entity extraction,relation extraction,entity linking,and link prediction.Moreover,this article also provides an analysis of the unresolved challenges and emerging trajectories that beckon within the expansive application of machine learning-fueled,large-scale KG construction.展开更多
Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning al...Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference.Therefore,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy environment.To begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual rule.Moreover,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are estimated.The results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,respectively.Lastly,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple layers.The corresponding solutions and their interval perturbations are investigated.It is found that theα-UTI reasoning chain method is stable in the case of chain reasoning.Two application examples in affective computing are given to verify the stability of theα-UTImethod.In summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.展开更多
Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurr...Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.展开更多
文摘The model for protection of personal information dis-closed according to the law has changed from indirect protection to direct protection.The indirect protection model for traditional repu-tation rights and privacy rights was not enough to meet the practical needs of governance.However;due to the ambiguity in the application of the“reasonable”processing requirements,the direct protection model centered on Article 27 of the Personal Information Protection Law also is not enough to effectively respond to practical disputes.The essence of the problem is to resolve the tension between informa-tion circulation and risk control and reshape the legal order for the protection of personal information disclosed according to the law.The determination of“reasonable”should be centered on the scenario theory and holism interpretation and carried out by using the interpre-tation technique of the dynamic system under Article 998 of the Civil Code.With the support of scenario-based discussions and comparative propositions,the crawling and tag extraction of personal information.disclosed according to the law should be considered as reasonable processing;profiling and automated decision-making should not be covered in the scope of reasonable processing,in principle;for behav-iors such as correlation analysis,elements like information subject,identifiability and sensitivity should be comprehensively considered to draw open and inclusive conclusions in individual cases.
文摘The possibility and rationality of introducing an bid-winning estimate based on a reasonable low price into construction bidding mode with bill of quantities were analyzed by setting up a model for bidding and tendering, and the functions of the estimate of reasonable low price in the bidding were revealed. On this basis, a new bidding mode of the project with bill of quantities was pro- posed. The application of the new mode will be advantageous to the promotion of the bill of quantities in China.
文摘In this thesis, the interal relations between about shear looking, zero energy mode and patch test are studied, and a reasonable method provided for building general element of thick and thin plate with effectual and realiable numerical solution.
文摘In April,the economy performed within a reasonable range,and sustained momentum of progress in overall stability.1.The service sector grew rapidly and modern service industries grew well In April,the Index of Services Production increased by 7.4%year on year;0.2 percentage point slower than that of March,and 0.1 percentage point faster than that of the first two months.
文摘Speech by Ji Bingxuan,Vice Chairman of the Standing Committee of the NPC and Vice President of CAFIU at the Opening Ceremony of the 35th Annual Meeting of the Inter Action Council Distinguished guests,Ladies and gentlemen,friends:Good morning!
文摘Both reasonable accommodation and accessibility are crucial concepts in the UN Convent ion on the Rights of Persons with Disabilities Those two concepts promote each other and should develop as a whole State parties of the Convention undertake immediate obligations to ensure the provision of reasonable accommodation, which has advantages such as characteristics of subjective rights, individualization, justiciability and convenience, making it a flexible tool for the protection of rights It can serve as a supplement to insufficient accessibility and play a unique role in other areas which are irrelevant to accessibility, so as to satisfy the special needs of certain subjects to the largest extent The State Party has an ex ante and progressive obligations to the realization of the accessibility construction, which has advantages of comman design, large scale, economization and no need for individualization consideration In China, various forms of reasonable accommodation have been applied in employment, but they have disadvantages of contingency, randomness, simplicity and lack of systematic support In the process of further promoting the employment of people with disabilities in China, in addition to strengthening accessibility construction, we must fully understand and flexibly adopt reasonable accommodation.
文摘Injection of gas (CO_(2)) into coal seams is an effective method to benefit from both CO_(2) geological storage and coalbed methane recovery. Based on the dual pore structure of coal mass, and the Weibull distribution of fracture permeability, a menmal-hydraulic-mechanical (THM) coupling mathematical model is proposed involving the non-isothermal adsorption of binary gases, dynamic gas diffusion between matrix and fractures, multiphase seepage, coal deformation, heat conduction and heat convection. This mathematical model is applied to study the process of CO_(2)-enhanced coalbed methane recovery (CO_(2)-ECBM). Results show that the CH4 content of CO_(2)-ECBM in coal seam decreases significantly when compared with that of regular drainage, and decreases rapidly in the early stage but slowly in the later stage. Coal seam permeability evolution is triggered by changes in gas adsorption/desorption, temperature and effective stress. For regular drainage, the early permeability shows a decreasing trend dominated by the increase of effective stress, while the later permeability shows an increasing trend dominated by the CH4 desorption caused shrinkage of coal matrix. For CO_(2)-ECBM, the permeability in coal seam generally shows a downward trend due to both matrix swelling induced by gas adsorption and thermal expansion, particularly near injection well. There appears an increased and delayed peak production rate of CH4. The CH4 production rate of CO_(2)-ECBM is always higher than that of regular drainage. The CH4 cumulative production and CO_(2) cumulative storage linearly increase with time, and the CH4 cumulative production of CO_(2)-ECBM increased by 39.2% in the duration of 5000 d compared with regular drainage. Reasonable CO_(2) injection starting time can overcome the issue of early CO_(2) breakthrough and ineffective increase of CH4 production. In the studied case, the optimal injection starting time is 2500 d. Compared with the simultaneous CH4 extraction and CO_(2) injection, the CH4 cumulative production of optimal time has increased by 30.1%. The research provides a reference for determining the reasonable CO_(2) injection time under similar conditions.
文摘The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.
基金the National Social Science Foundation of China(No.22CTQ032).
文摘Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been studied.The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.Design/methodology/approach:The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases.These publications were categorized based on their OA levels,including Gold OA,Green OA,and non-OA.The study explored retraction rates,time lags and reasons within these categories.Findings:The findings of this research revealed distinct patterns in retraction rates among different OA levels.Publications with Gold OA demonstrated the highest retraction rate,followed by Green OA and non-OA.A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions,while Green OA exhibited a higher proportion due to falsification and manipulation issues,along with a lower occurrence of plagiarism and authorship issues.The retraction time lag was shortest for Gold OA,followed by non-OA,and longest for Green OA.The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.A comparative study on characteristics of retracted publications across different open access levels Research limitations:There is no exploration of a wider range of OA levels,such as Hybrid OA and Bronze OA.Practical implications:The outcomes of this study suggest the need for increased attention to research integrity within the OA publications.The occurrences offalsification,manipulation,and ethical concerns within Green OA publications warrant attention from the scientific community.Originality/value:This study contributes to the understanding of research integrity in the realm of OA publications,shedding light on retraction patterns and reasons across different OA levels.
文摘The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.
基金supported by Key Laboratory of Information System Requirement,No.LHZZ202202Natural Science Foundation of Xinjiang Uyghur Autonomous Region(2023D01C55)Scientific Research Program of the Higher Education Institution of Xinjiang(XJEDU2023P127).
文摘In recent years,with the continuous development of deep learning and knowledge graph reasoning methods,more and more researchers have shown great interest in improving knowledge graph reasoning methods by inferring missing facts through reasoning.By searching paths on the knowledge graph and making fact and link predictions based on these paths,deep learning-based Reinforcement Learning(RL)agents can demonstrate good performance and interpretability.Therefore,deep reinforcement learning-based knowledge reasoning methods have rapidly emerged in recent years and have become a hot research topic.However,even in a small and fixed knowledge graph reasoning action space,there are still a large number of invalid actions.It often leads to the interruption of RL agents’wandering due to the selection of invalid actions,resulting in a significant decrease in the success rate of path mining.In order to improve the success rate of RL agents in the early stages of path search,this article proposes a knowledge reasoning method based on Deep Transfer Reinforcement Learning path(DTRLpath).Before supervised pre-training and retraining,a pre-task of searching for effective actions in a single step is added.The RL agent is first trained in the pre-task to improve its ability to search for effective actions.Then,the trained agent is transferred to the target reasoning task for path search training,which improves its success rate in searching for target task paths.Finally,based on the comparative experimental results on the FB15K-237 and NELL-995 datasets,it can be concluded that the proposed method significantly improves the success rate of path search and outperforms similar methods in most reasoning tasks.
基金the National Natural Science Foundation of China(Nos.61562026,61962020)Academic and Technical Leaders of Major Disciplines in Jiangxi Province(No.20172BCB22015)+1 种基金Special Fund Project for Postgraduate Innovation in Jiangxi Province(No.YC2020-B1141)Jiangxi Provincial Natural Science Foundation(No.20224ACB202006).
文摘Fair exchange protocols play a critical role in enabling two distrustful entities to conduct electronic data exchanges in a fair and secure manner.These protocols are widely used in electronic payment systems and electronic contract signing,ensuring the reliability and security of network transactions.In order to address the limitations of current research methods and enhance the analytical capabilities for fair exchange protocols,this paper proposes a formal model for analyzing such protocols.The proposed model begins with a thorough analysis of fair exchange protocols,followed by the formal definition of fairness.This definition accurately captures the inherent requirements of fair exchange protocols.Building upon event logic,the model incorporates the time factor into predicates and introduces knowledge set axioms.This enhancement empowers the improved logic to effectively describe the state and knowledge of protocol participants at different time points,facilitating reasoning about their acquired knowledge.To maximize the intruder’s capabilities,channel errors are translated into the behaviors of the intruder.The participants are further categorized into honest participants and malicious participants,enabling a comprehensive evaluation of the intruder’s potential impact.By employing a typical fair exchange protocol as an illustrative example,this paper demonstrates the detailed steps of utilizing the proposed model for protocol analysis.The entire process of protocol execution under attack scenarios is presented,shedding light on the underlying reasons for the attacks and proposing corresponding countermeasures.The developedmodel enhances the ability to reason about and evaluate the security properties of fair exchange protocols,thereby contributing to the advancement of secure network transactions.
基金NSFC(No.71974017)LIS Outstanding Talents Introducing Program,Bureau of Development and Planning of CAS(2022).
文摘Purpose:The notable increase in retraction papers has attracted considerable attention from diverse stakeholders.Various sources are now offering information related to research integrity,including concerns voiced on social media,disclosed lists of paper mills,and retraction notices accessible through journal websites.However,despite the availability of such resources,there remains a lack of a unified platform to consolidate this information,thereby hindering efficient searching and cross-referencing.Thus,it is imperative to develop a comprehensive platform for retracted papers and related concerns.This article aims to introduce“Amend,”a platform designed to integrate information on research integrity from diverse sources.Design/methodology/approach:The Amend platform consolidates concerns and lists of problematic articles sourced from social media platforms(e.g.,PubPeer,For Better Science),retraction notices from journal websites,and citation databases(e.g.,Web of Science,CrossRef).Moreover,Amend includes investigation and punishment announcements released by administrative agencies(e.g.,NSFC,MOE,MOST,CAS).Each related paper is marked and can be traced back to its information source via a provided link.Furthermore,the Amend database incorporates various attributes of retracted articles,including citation topics,funding details,open access status,and more.The reasons for retraction are identified and classified as either academic misconduct or honest errors,with detailed subcategories provided for further clarity.Findings:Within the Amend platform,a total of 32,515 retracted papers indexed in SCI,SSCI,and ESCI between 1980 and 2023 were identified.Of these,26,620(81.87%)were associated with academic misconduct.The retraction rate stands at 6.64 per 10,000 articles.Notably,the retraction rate for non-gold open access articles significantly differs from that for gold open access articles,with this disparity progressively widening over the years.Furthermore,the reasons for retractions have shifted from traditional individual behaviors like falsification,fabrication,plagiarism,and duplication to more organized large-scale fraudulent practices,including Paper Mills,Fake Peer-review,and Artificial Intelligence Generated Content(AIGC).Research limitations:The Amend platform may not fully capture all retracted and concerning papers,thereby impacting its comprehensiveness.Additionally,inaccuracies in retraction notices may lead to errors in tagged reasons.Practical implications:Amend provides an integrated platform for stakeholders to enhance monitoring,analysis,and research on academic misconduct issues.Ultimately,the Amend database can contribute to upholding scientific integrity.Originality/value:This study introduces a globally integrated platform for retracted and concerning papers,along with a preliminary analysis of the evolutionary trends in retracted papers.
基金supported in part by the Beijing Natural Science Foundation under Grants L211020 and M21032in part by the National Natural Science Foundation of China under Grants U1836106 and 62271045in part by the Scientific and Technological Innovation Foundation of Foshan under Grants BK21BF001 and BK20BF010。
文摘Knowledge graph(KG)serves as a specialized semantic network that encapsulates intricate relationships among real-world entities within a structured framework.This framework facilitates a transformation in information retrieval,transitioning it from mere string matching to far more sophisticated entity matching.In this transformative process,the advancement of artificial intelligence and intelligent information services is invigorated.Meanwhile,the role ofmachine learningmethod in the construction of KG is important,and these techniques have already achieved initial success.This article embarks on a comprehensive journey through the last strides in the field of KG via machine learning.With a profound amalgamation of cutting-edge research in machine learning,this article undertakes a systematical exploration of KG construction methods in three distinct phases:entity learning,ontology learning,and knowledge reasoning.Especially,a meticulous dissection of machine learningdriven algorithms is conducted,spotlighting their contributions to critical facets such as entity extraction,relation extraction,entity linking,and link prediction.Moreover,this article also provides an analysis of the unresolved challenges and emerging trajectories that beckon within the expansive application of machine learning-fueled,large-scale KG construction.
基金the National Natural Science Foundation of China under Grants 62176083,62176084,61877016,and 61976078the Key Research and Development Program of Anhui Province under Grant 202004d07020004the Natural Science Foundation of Anhui Province under Grant 2108085MF203.
文摘Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference.Therefore,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy environment.To begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual rule.Moreover,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are estimated.The results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,respectively.Lastly,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple layers.The corresponding solutions and their interval perturbations are investigated.It is found that theα-UTI reasoning chain method is stable in the case of chain reasoning.Two application examples in affective computing are given to verify the stability of theα-UTImethod.In summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.
基金the National Natural Science Founda-tion of China(62062062)hosted by Gulila Altenbek.
文摘Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.