Retaining the death penalty and strict restricting the application of the death penalty is now a basic criminal policy in China, and from the judicial level, the key to the restriction of the death penalty is to study...Retaining the death penalty and strict restricting the application of the death penalty is now a basic criminal policy in China, and from the judicial level, the key to the restriction of the death penalty is to study what lenient sentencing discretion the criminal has to constitute ＂not to execute immediately＂ when he has reached the standard of the immediate execution of the death penalty, to cross the chasm from the immediate execution of the death penalty to the death sentence with a reprieve. The basic process of the sentencing is to establish a baseline punishment on the basis of the social harmfulness of the activities of the criminal, and then measure the profits and losses according to the offender＇s personal danger. Therefore, although the social harmfulness of the activities of the criminal reaches the standard of the ＂most heinous crimes＂, due to the existence of the fault of the victim, active compensation for the victim, and the motives of the small blames and other lenient sentencing discretions, the criminal＇s danger has not reached the degree of ＂flagrance＂. Apply the death sentence with a two-year reprieve and even the life imprisonment generally. If there are some strict sentencing discretions, such as ＂the crime means is extremely cruel＂, carefully consider the use of the immediate execution of the death penalty. Under the circumstances of the concurrence of the sentencing, carry on the overall consideration based on the comprehensive measurement of various circumstances of the sentencing.展开更多
Oxidative post-translational modifications of specific chloroplast proteins contribute to the initiation of retrograde signaling.The Arabidopsis thaliana EXECUTER1(EX1)protein,a chloroplast-localized singlet oxygen(^(...Oxidative post-translational modifications of specific chloroplast proteins contribute to the initiation of retrograde signaling.The Arabidopsis thaliana EXECUTER1(EX1)protein,a chloroplast-localized singlet oxygen(^(1)O_(2))sensor,undergoes tryptophan(Trp)643 oxidation by^(1)O_(2),a chloroplast-derived and light-dependent reactive oxygen species.The indole side chain of Trp is vulnerable to^(1)O_(2),leading to the generation of oxidized Trp variants and priming EX1 for degradation by a membrane-bound FtsH protease.The perception of^(1)O_(2)via Trp643 oxidation and subsequent EX1 proteolysis facilitate chloroplast-to-nucleus retrograde signaling.In this study,we discovered that the EX1-like protein EX2 also undergoes^(1)O_(2)-dependent Trp530 oxidation and FtsH-dependent turnover,which attenuates^(1)O_(2)signaling by decelerating EX1-Trp643 oxidation and subsequent EX1 degradation.Consistent with this finding,the loss of EX2 function reinforces EX1-dependent retrograde signaling by accelerating EX1-Trp643 oxidation and subsequent EX1 proteolysis,whereas overexpression of EX2 produces molecular phenotypes opposite to those observed in the loss-of-function mutants of EX2.Intriguingly,phylogenetic analysis suggests that EX2 may have emerged evolutionarily to attenuate the sensitivity of EX1 toward^(1)O_(2).Collectively,these results suggest that EX2 functions as a negative regulator of the EX1 signalosome through its own^(1)O_(2)-dependent oxidation,providing a new mechanistic insight into the regulation of EX1-mediated^(1)O_(2)signaling.展开更多
The network arbitration cases arising from the network lending disputes are pouring into the courts in large numbers.It is reported that the network arbitration system of some arbitration institutions even“can accept...The network arbitration cases arising from the network lending disputes are pouring into the courts in large numbers.It is reported that the network arbitration system of some arbitration institutions even“can accept more than 10,000 cases every day,”while online lending is booming,it has also caused a lot of contradictions and disputes,and traditional dispute resolution methods have failed to effectively respond to the need for efficient and convenient resolution of online lending disputes.This paper tries to study the arbitral award of online loans and proposes the construction of implementation review rules.展开更多
Parkinson’s disease can affect not only motor functions but also cognitive abilities,leading to cognitive impairment.One common issue in Parkinson’s disease with cognitive dysfunction is the difficulty in executive ...Parkinson’s disease can affect not only motor functions but also cognitive abilities,leading to cognitive impairment.One common issue in Parkinson’s disease with cognitive dysfunction is the difficulty in executive functioning.Executive functions help us plan,organize,and control our actions based on our goals.The brain area responsible for executive functions is called the prefrontal co rtex.It acts as the command center for the brain,especially when it comes to regulating executive functions.The role of the prefrontal cortex in cognitive processes is influenced by a chemical messenger called dopamine.However,little is known about how dopamine affects the cognitive functions of patients with Parkinson’s disease.In this article,the authors review the latest research on this topic.They start by looking at how the dopaminergic syste m,is alte red in Parkinson’s disease with executive dysfunction.Then,they explore how these changes in dopamine impact the synaptic structure,electrical activity,and connection components of the prefrontal cortex.The authors also summarize the relationship between Parkinson’s disease and dopamine-related cognitive issues.This information may offer valuable insights and directions for further research and improvement in the clinical treatment of cognitive impairment in Parkinson’s disease.展开更多
Chloroplast development depends on the synthesis and import of a large number of nuclear-encoded pro- teins. The synthesis of some of these proteins is affected by the functional state of the plastid via a process kno...Chloroplast development depends on the synthesis and import of a large number of nuclear-encoded pro- teins. The synthesis of some of these proteins is affected by the functional state of the plastid via a process known as retrograde signaling. Retrograde plastid-to-nucleus signaling has been often characterized in seedlings of Arabidopsis thaliana exposed to norflurazon （NF）, an inhibitor of carotenoid biosynthesis. Results of this work suggested that, throughout seedling development, a factor is released from the plastid to the cytoplasm that indicates a perturbation of plastid homeostasis and represses nuclear genes required for normal chloroplast development. The identity of this factor is still under debate. Reactive oxygen species （ROS） were among the candidates discussed as possible retrograde signals in NF-treated plants. In the present work, this proposed role of ROS has been analyzed. In seedlings grown from the very beginning in the presence of NF, ROS-dependent signaling was not detectable, whereas, in seedlings first exposed to NF after light-dependent chloroplast formation had been completed, enhanced ROS production occurred and, among oth- ers, 1O2-mediated and EXECUTER-dependent retrograde signaling was induced. Hence, depending on the developmental stage at which plants are exposed to NF, different retrograde signaling pathways may be activated, some of which are also active in non-treated plants under light stress.展开更多
Software security analysts typically only have access to the executable program and cannot directly access the source code of the program.This poses significant challenges to security analysis.While it is crucial to i...Software security analysts typically only have access to the executable program and cannot directly access the source code of the program.This poses significant challenges to security analysis.While it is crucial to identify vulnerabilities in such non-source code programs,there exists a limited set of generalized tools due to the low versatility of current vulnerability mining methods.However,these tools suffer from some shortcomings.In terms of targeted fuzzing,the path searching for target points is not streamlined enough,and the completely random testing leads to an excessively large search space.Additionally,when it comes to code similarity analysis,there are issues with incomplete code feature extraction,which may result in information loss.In this paper,we propose a cross-platform and cross-architecture approach to exploit vulnerabilities using neural network obfuscation techniques.By leveraging the Angr framework,a deobfuscation technique is introduced,along with the adoption of a VEX-IR-based intermediate language conversion method.This combination allows for the unified handling of binary programs across various architectures,compilers,and compilation options.Subsequently,binary programs are processed to extract multi-level spatial features using a combination of a skip-gram model with self-attention mechanism and a bidirectional Long Short-Term Memory(LSTM)network.Finally,the graph embedding network is utilized to evaluate the similarity of program functionalities.Based on these similarity scores,a target function is determined,and symbolic execution is applied to solve the target function.The solved content serves as the initial seed for targeted fuzzing.The binary program is processed by using the de-obfuscation technique and intermediate language transformation method,and then the similarity of program functions is evaluated by using a graph embedding network,and symbolic execution is performed based on these similarity scores.This approach facilitates cross-architecture analysis of executable programs without their source codes and concurrently reduces the risk of symbolic execution path explosion.展开更多
A framework that integrates planning,monitoring and replanning techniques is proposed.It can devise the best solution based on the current state according to specific objectives and properly deal with the influence of...A framework that integrates planning,monitoring and replanning techniques is proposed.It can devise the best solution based on the current state according to specific objectives and properly deal with the influence of abnormity on the plan execution.The framework consists of three parts:the hierarchical task network(HTN)planner based on Monte Carlo tree search(MCTS),hybrid plan monitoring based on forward and backward and norm-based replanning method selection.The HTN planner based on MCTS selects the optimal method for HTN compound task through pre-exploration.Based on specific objectives,it can identify the best solution to the current problem.The hybrid plan monitoring has the capability to detect the influence of abnormity on the effect of an executed action and the premise of an unexecuted action,thus trigger the replanning.The norm-based replanning selection method can measure the difference between the expected state and the actual state,and then select the best replanning algorithm.The experimental results reveal that our method can effectively deal with the influence of abnormity on the implementation of the plan and achieve the target task in an optimal way.展开更多
The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leadsto wide losses for various organizations. These dangers have proven that signature-based approaches are ins...The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leadsto wide losses for various organizations. These dangers have proven that signature-based approaches are insufficientto prevent emerging and polymorphic attacks. Therefore, this paper is proposing a Robust Malicious ExecutableDetection (RMED) using Host-based Machine Learning Classifier to discover malicious Portable Executable (PE)files in hosts using Windows operating systems through collecting PE headers and applying machine learningmechanisms to detect unknown infected files. The authors have collected a novel reliable dataset containing 116,031benign files and 179,071 malware samples from diverse sources to ensure the efficiency of RMED approach.The most effective PE headers that can highly differentiate between benign and malware files were selected totrain the model on 15 PE features to speed up the classification process and achieve real-time detection formalicious executables. The evaluation results showed that RMED succeeded in shrinking the classification timeto 91 milliseconds for each file while reaching an accuracy of 98.42% with a false positive rate equal to 1.58. Inconclusion, this paper contributes to the field of cybersecurity by presenting a comprehensive framework thatleverages Artificial Intelligence (AI) methods to proactively detect and prevent cyber-attacks.展开更多
This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)device.Ten distinct machine learning ap...This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)device.Ten distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter tuning.Significant improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and precision.The study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among algorithms.Decision Trees and Random Forests exhibited stable performance throughout the evaluation.While enhancing accuracy,hyperparameter optimization also led to increased execution time.Visual representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular disease.This research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.展开更多
BACKGROUND Intracerebral hemorrhage mainly occurs in middle-aged and elderly patients with hypertension,and surgery is currently the main treatment for hypertensive cerebral hemorrhage,but the bleeding caused by surge...BACKGROUND Intracerebral hemorrhage mainly occurs in middle-aged and elderly patients with hypertension,and surgery is currently the main treatment for hypertensive cerebral hemorrhage,but the bleeding caused by surgery will cause damage to the patient's nerve cells,resulting in cognitive and motor dysfunction,resulting in a decline in the patient's quality of life.AIM To investigate associations between cerebral arterial blood flow and executive and cognitive functions in depressed patients after acute hypertensive cerebral hemorrhage.METHODS Eighty-nine patients with depression after acute hypertensive cerebral hemorrhage who were admitted to our hospital between January 2019 and July 2021 were selected as the observation group,while 100 patients without depression who had acute hypertensive cerebral hemorrhage were selected as the control group.The attention span of the patients was assessed using the Paddle Pin Test while executive function was assessed using the Wisconsin Card Sorting Test(WCST)and cognitive function was assessed using the Montreal Cognitive Assessment Scale(MoCA).The Hamilton Depression Rating Scale(HAMD-24)was used to evaluate the severity of depression of involved patients.Cerebral arterial blood flow was measured in both groups.RESULTS The MoCA score,net scores I,II,III,IV,and the total net score of the scratch test in the observation group were significantly lower than those in the control group(P<0.05).Concurrently,the total number of responses,number of incorrect responses,number of persistent errors,and number of completed responses of the first classification in the WCST test were significantly higher in the observation group than those in the control group(P<0.05).Blood flow in the basilar artery,left middle cerebral artery,right middle cerebral artery,left anterior cerebral artery,and right anterior cerebral artery was significantly lower in the observation group than in the control group(P<0.05).The basilar artery,left middle cerebral artery,right middle cerebral artery,left anterior cerebral artery,and right anterior cerebral artery were positively correlated with the net and total net scores of each part of the Paddle Pin test and the MoCA score(P<0.05),and negatively correlated with each part of the WCST test(P<0.05).In the observation group,the post-treatment improvement was more prominent in the Paddle Pin test,WCST test,HAMD-24 score,and MoCA score compared with those in the pre-treatment period(P<0.05).Blood flow in the basilar artery,left middle cerebral artery,right middle cerebral artery,left anterior cerebral artery,and right anterior cerebral artery significantly improved in the observation group after treatment(P<0.05).CONCLUSION Impaired attention,and executive and cognitive functions are correlated with cerebral artery blood flow in patients with depression after acute hypertensive cerebral hemorrhage and warrant further study.展开更多
Green technological innovation is crucial for the manufacturing industry’s green transformation and sustainable development.This study examines the impact of executive overconfidence on corporate green innovation,foc...Green technological innovation is crucial for the manufacturing industry’s green transformation and sustainable development.This study examines the impact of executive overconfidence on corporate green innovation,focusing on the internal drivers of corporate innovation and using a sample of Shanghai and Shenzhen A-share listed manufacturing companies from 2013 to 2020.We further examine the mediating role of digital transformation and the moderating role of external attention.The findings indicate that executive overconfidence promotes corporate green technological innovation.Overconfident executives enhance green innovation by accelerating digital transformation.Moreover,external attention from analysts and media positively moderates the relationship between executive overconfidence and corporate green innovation.Heterogeneity analysis reveals that the positive impact of executive overconfidence on green innovation is more significant in non-state-owned enterprises,high-tech firms,and enterprises with lower pollution levels.展开更多
The present study aims to establish a literature review on intervention programs for executive functions(EFs)through the use of fundamental motor skills,from a neuropsychopedagogical perspective in subjects with Devel...The present study aims to establish a literature review on intervention programs for executive functions(EFs)through the use of fundamental motor skills,from a neuropsychopedagogical perspective in subjects with Developmental Coordination Disorder(DCD).An exploratory study was carried out through an integrative literature review.The research was carried out in the Scientific databases Electronic Library Online(SciELO),Latin American and Caribbean Literature in Health Sciences(LILACS),Virtual Health Library-Psychology Brazil(BVSPSI),Electronic Journals of Psychology(PePSIC),in the periodicals available in the Brazilian Digital Library of Theses and Dissertations(BDTD)and on the website of the Coordination for the Improvement of Higher Education Personnel(CAPES).The covering publications took place from 2018 to 2023,14 articles were selected for analysis.This literature review made it possible to create strategies for stimulating EF and Visuomotor Functions so that educators and other professionals can better deal with students with DCD.It was perceived the need to carry out and develop more empirical research regarding the intervention of EFs and Visuomotor Functions by educators and professionals,with a greater sampling amplitude,to increase the number of studies that enable interventions both in children and in teenagers with DCD.展开更多
The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in ...The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).展开更多
Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardwar...Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardware system.This literature review focuses on calculating WCET for multi-core processors,providing a survey of traditional methods used for static and dynamic analysis and highlighting the major challenges that arise from different program execution scenarios on multi-core platforms.This paper outlines the strengths and weaknesses of current methodologies and offers insights into prospective areas of research on multi-core analysis.By presenting a comprehensive analysis of the current state of research on multi-core processor analysis for WCET estimation,this review aims to serve as a valuable resource for researchers and practitioners in the field.展开更多
Human genome encodes six paralogous gasdermin genes:GSDMA,GSDMB,GSDMC,GSDMD,GSDME and DFNB59.1 Proteolytic cleavage of these gasdermin proteins liberates an N-terminal(NT)fragment from autoinhibition,which assembles i...Human genome encodes six paralogous gasdermin genes:GSDMA,GSDMB,GSDMC,GSDMD,GSDME and DFNB59.1 Proteolytic cleavage of these gasdermin proteins liberates an N-terminal(NT)fragment from autoinhibition,which assembles in membrane to form pores and execute pyroptotic cell death in general.1 In contrast to other gasdermins,gasdermin B(GSDMB)is the only gasdermin gene that has not been identified in rodents.Zhou et al first shed light on the molecular mechanism by which cytotoxic lymphocyte-derived granzyme A(GZMA)cleaves GSDMB to execute pyroptosis in GSDMB-positive cells,especially in cancer cells.2 In this issue of Cell,Hansen et al reported a dynamic host pathogen S.flexneri prevents GSDMB-mediated lysis by secreting IpaH7.8,which targets and ubiquitinates GSDMB for 26S proteasome destruction.3 They showed that GSDMB implements bacteriocidic ability by recognition of the phospholipids on Gram-negative bacterial membranes rather than lysing host cells.Although their experimental design and data are clearly presented and straightforward,there are still some doubts to be clarified.展开更多
Jinzhou New China Dragon(Group)Indus-trial Co.,Ltd.(JNCDGICL)plans to to-tally invest RMB300 million to construct amolybdenum mining and deep processing project.It will
A research team led by Prof.XUE Yuanchao from the Institute of Biophysics of the Chinese Academy of Sciences has developed a new method for global profiling of in-situ RNA–RNA contacts associated with a specific RNA-...A research team led by Prof.XUE Yuanchao from the Institute of Biophysics of the Chinese Academy of Sciences has developed a new method for global profiling of in-situ RNA–RNA contacts associated with a specific RNA-binding protein(RBP)and revealed positional mechanisms by which PTBP1-associated RNA loops regulate cassette exon splicing.This study was published online in Molecular Cell on March 22.In eukaryotes,the same pre-mRNA can produce multiple protein isoforms to execute similar or different biological functions through alternative splicing.Several longstanding models proposed that RBPs may regulate alternative splicing by modulating long-range RNA–RNA interactions(RRI).However,direct experimental evidence was lacking.展开更多
Emerging Internet of Things(IoT)applications require faster execution time and response time to achieve optimal performance.However,most IoT devices have limited or no computing capability to achieve such stringent ap...Emerging Internet of Things(IoT)applications require faster execution time and response time to achieve optimal performance.However,most IoT devices have limited or no computing capability to achieve such stringent application requirements.To this end,computation offloading in edge computing has been used for IoT systems to achieve the desired performance.Nevertheless,randomly offloading applications to any available edge without considering their resource demands,inter-application dependencies and edge resource availability may eventually result in execution delay and performance degradation.We introduce Edge-IoT,a machine learning-enabled orchestration framework in this paper,which utilizes the states of edge resources and application resource requirements to facilitate a resource-aware offloading scheme for minimizing the average latency.We further propose a variant bin-packing optimization model that co-locates applications firmly on edge resources to fully utilize available resources.Extensive experiments show the effectiveness and resource efficiency of the proposed approach.展开更多
文摘Retaining the death penalty and strict restricting the application of the death penalty is now a basic criminal policy in China, and from the judicial level, the key to the restriction of the death penalty is to study what lenient sentencing discretion the criminal has to constitute ＂not to execute immediately＂ when he has reached the standard of the immediate execution of the death penalty, to cross the chasm from the immediate execution of the death penalty to the death sentence with a reprieve. The basic process of the sentencing is to establish a baseline punishment on the basis of the social harmfulness of the activities of the criminal, and then measure the profits and losses according to the offender＇s personal danger. Therefore, although the social harmfulness of the activities of the criminal reaches the standard of the ＂most heinous crimes＂, due to the existence of the fault of the victim, active compensation for the victim, and the motives of the small blames and other lenient sentencing discretions, the criminal＇s danger has not reached the degree of ＂flagrance＂. Apply the death sentence with a two-year reprieve and even the life imprisonment generally. If there are some strict sentencing discretions, such as ＂the crime means is extremely cruel＂, carefully consider the use of the immediate execution of the death penalty. Under the circumstances of the concurrence of the sentencing, carry on the overall consideration based on the comprehensive measurement of various circumstances of the sentencing.
基金This research was supported by the Strategic Priority Research Program from the Chinese Academy of Sciences(grant no.XDB27040102)the 100-Talent Program of the Chinese Academy of Sciences and the National Natural Science Foundation of China(NSFC)(grant no.31871397)to C.K.Support from a President's International Fellowship Initiative(PIFI)postdoctoral fellowship from the Chinese Academy of Sciences(no.2019PB0066)to V.D.is also acknowledged.
文摘Oxidative post-translational modifications of specific chloroplast proteins contribute to the initiation of retrograde signaling.The Arabidopsis thaliana EXECUTER1(EX1)protein,a chloroplast-localized singlet oxygen(^(1)O_(2))sensor,undergoes tryptophan(Trp)643 oxidation by^(1)O_(2),a chloroplast-derived and light-dependent reactive oxygen species.The indole side chain of Trp is vulnerable to^(1)O_(2),leading to the generation of oxidized Trp variants and priming EX1 for degradation by a membrane-bound FtsH protease.The perception of^(1)O_(2)via Trp643 oxidation and subsequent EX1 proteolysis facilitate chloroplast-to-nucleus retrograde signaling.In this study,we discovered that the EX1-like protein EX2 also undergoes^(1)O_(2)-dependent Trp530 oxidation and FtsH-dependent turnover,which attenuates^(1)O_(2)signaling by decelerating EX1-Trp643 oxidation and subsequent EX1 degradation.Consistent with this finding,the loss of EX2 function reinforces EX1-dependent retrograde signaling by accelerating EX1-Trp643 oxidation and subsequent EX1 proteolysis,whereas overexpression of EX2 produces molecular phenotypes opposite to those observed in the loss-of-function mutants of EX2.Intriguingly,phylogenetic analysis suggests that EX2 may have emerged evolutionarily to attenuate the sensitivity of EX1 toward^(1)O_(2).Collectively,these results suggest that EX2 functions as a negative regulator of the EX1 signalosome through its own^(1)O_(2)-dependent oxidation,providing a new mechanistic insight into the regulation of EX1-mediated^(1)O_(2)signaling.
文摘The network arbitration cases arising from the network lending disputes are pouring into the courts in large numbers.It is reported that the network arbitration system of some arbitration institutions even“can accept more than 10,000 cases every day,”while online lending is booming,it has also caused a lot of contradictions and disputes,and traditional dispute resolution methods have failed to effectively respond to the need for efficient and convenient resolution of online lending disputes.This paper tries to study the arbitral award of online loans and proposes the construction of implementation review rules.
基金supported by the National Natural Science Foundation of China,No.82101263Jiangsu Province Science Foundation for Youths,No.BK20210903Research Foundation for Talented Scholars of Xuzhou Medical University,No.RC20552114(all to CT)。
文摘Parkinson’s disease can affect not only motor functions but also cognitive abilities,leading to cognitive impairment.One common issue in Parkinson’s disease with cognitive dysfunction is the difficulty in executive functioning.Executive functions help us plan,organize,and control our actions based on our goals.The brain area responsible for executive functions is called the prefrontal co rtex.It acts as the command center for the brain,especially when it comes to regulating executive functions.The role of the prefrontal cortex in cognitive processes is influenced by a chemical messenger called dopamine.However,little is known about how dopamine affects the cognitive functions of patients with Parkinson’s disease.In this article,the authors review the latest research on this topic.They start by looking at how the dopaminergic syste m,is alte red in Parkinson’s disease with executive dysfunction.Then,they explore how these changes in dopamine impact the synaptic structure,electrical activity,and connection components of the prefrontal cortex.The authors also summarize the relationship between Parkinson’s disease and dopamine-related cognitive issues.This information may offer valuable insights and directions for further research and improvement in the clinical treatment of cognitive impairment in Parkinson’s disease.
文摘Chloroplast development depends on the synthesis and import of a large number of nuclear-encoded pro- teins. The synthesis of some of these proteins is affected by the functional state of the plastid via a process known as retrograde signaling. Retrograde plastid-to-nucleus signaling has been often characterized in seedlings of Arabidopsis thaliana exposed to norflurazon （NF）, an inhibitor of carotenoid biosynthesis. Results of this work suggested that, throughout seedling development, a factor is released from the plastid to the cytoplasm that indicates a perturbation of plastid homeostasis and represses nuclear genes required for normal chloroplast development. The identity of this factor is still under debate. Reactive oxygen species （ROS） were among the candidates discussed as possible retrograde signals in NF-treated plants. In the present work, this proposed role of ROS has been analyzed. In seedlings grown from the very beginning in the presence of NF, ROS-dependent signaling was not detectable, whereas, in seedlings first exposed to NF after light-dependent chloroplast formation had been completed, enhanced ROS production occurred and, among oth- ers, 1O2-mediated and EXECUTER-dependent retrograde signaling was induced. Hence, depending on the developmental stage at which plants are exposed to NF, different retrograde signaling pathways may be activated, some of which are also active in non-treated plants under light stress.
文摘Software security analysts typically only have access to the executable program and cannot directly access the source code of the program.This poses significant challenges to security analysis.While it is crucial to identify vulnerabilities in such non-source code programs,there exists a limited set of generalized tools due to the low versatility of current vulnerability mining methods.However,these tools suffer from some shortcomings.In terms of targeted fuzzing,the path searching for target points is not streamlined enough,and the completely random testing leads to an excessively large search space.Additionally,when it comes to code similarity analysis,there are issues with incomplete code feature extraction,which may result in information loss.In this paper,we propose a cross-platform and cross-architecture approach to exploit vulnerabilities using neural network obfuscation techniques.By leveraging the Angr framework,a deobfuscation technique is introduced,along with the adoption of a VEX-IR-based intermediate language conversion method.This combination allows for the unified handling of binary programs across various architectures,compilers,and compilation options.Subsequently,binary programs are processed to extract multi-level spatial features using a combination of a skip-gram model with self-attention mechanism and a bidirectional Long Short-Term Memory(LSTM)network.Finally,the graph embedding network is utilized to evaluate the similarity of program functionalities.Based on these similarity scores,a target function is determined,and symbolic execution is applied to solve the target function.The solved content serves as the initial seed for targeted fuzzing.The binary program is processed by using the de-obfuscation technique and intermediate language transformation method,and then the similarity of program functions is evaluated by using a graph embedding network,and symbolic execution is performed based on these similarity scores.This approach facilitates cross-architecture analysis of executable programs without their source codes and concurrently reduces the risk of symbolic execution path explosion.
基金supported by the National Natural Science Foundation of China(61806221).
文摘A framework that integrates planning,monitoring and replanning techniques is proposed.It can devise the best solution based on the current state according to specific objectives and properly deal with the influence of abnormity on the plan execution.The framework consists of three parts:the hierarchical task network(HTN)planner based on Monte Carlo tree search(MCTS),hybrid plan monitoring based on forward and backward and norm-based replanning method selection.The HTN planner based on MCTS selects the optimal method for HTN compound task through pre-exploration.Based on specific objectives,it can identify the best solution to the current problem.The hybrid plan monitoring has the capability to detect the influence of abnormity on the effect of an executed action and the premise of an unexecuted action,thus trigger the replanning.The norm-based replanning selection method can measure the difference between the expected state and the actual state,and then select the best replanning algorithm.The experimental results reveal that our method can effectively deal with the influence of abnormity on the implementation of the plan and achieve the target task in an optimal way.
文摘The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leadsto wide losses for various organizations. These dangers have proven that signature-based approaches are insufficientto prevent emerging and polymorphic attacks. Therefore, this paper is proposing a Robust Malicious ExecutableDetection (RMED) using Host-based Machine Learning Classifier to discover malicious Portable Executable (PE)files in hosts using Windows operating systems through collecting PE headers and applying machine learningmechanisms to detect unknown infected files. The authors have collected a novel reliable dataset containing 116,031benign files and 179,071 malware samples from diverse sources to ensure the efficiency of RMED approach.The most effective PE headers that can highly differentiate between benign and malware files were selected totrain the model on 15 PE features to speed up the classification process and achieve real-time detection formalicious executables. The evaluation results showed that RMED succeeded in shrinking the classification timeto 91 milliseconds for each file while reaching an accuracy of 98.42% with a false positive rate equal to 1.58. Inconclusion, this paper contributes to the field of cybersecurity by presenting a comprehensive framework thatleverages Artificial Intelligence (AI) methods to proactively detect and prevent cyber-attacks.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU),Grant Number IMSIU-RG23151.
文摘This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)device.Ten distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter tuning.Significant improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and precision.The study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among algorithms.Decision Trees and Random Forests exhibited stable performance throughout the evaluation.While enhancing accuracy,hyperparameter optimization also led to increased execution time.Visual representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular disease.This research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.
文摘BACKGROUND Intracerebral hemorrhage mainly occurs in middle-aged and elderly patients with hypertension,and surgery is currently the main treatment for hypertensive cerebral hemorrhage,but the bleeding caused by surgery will cause damage to the patient's nerve cells,resulting in cognitive and motor dysfunction,resulting in a decline in the patient's quality of life.AIM To investigate associations between cerebral arterial blood flow and executive and cognitive functions in depressed patients after acute hypertensive cerebral hemorrhage.METHODS Eighty-nine patients with depression after acute hypertensive cerebral hemorrhage who were admitted to our hospital between January 2019 and July 2021 were selected as the observation group,while 100 patients without depression who had acute hypertensive cerebral hemorrhage were selected as the control group.The attention span of the patients was assessed using the Paddle Pin Test while executive function was assessed using the Wisconsin Card Sorting Test(WCST)and cognitive function was assessed using the Montreal Cognitive Assessment Scale(MoCA).The Hamilton Depression Rating Scale(HAMD-24)was used to evaluate the severity of depression of involved patients.Cerebral arterial blood flow was measured in both groups.RESULTS The MoCA score,net scores I,II,III,IV,and the total net score of the scratch test in the observation group were significantly lower than those in the control group(P<0.05).Concurrently,the total number of responses,number of incorrect responses,number of persistent errors,and number of completed responses of the first classification in the WCST test were significantly higher in the observation group than those in the control group(P<0.05).Blood flow in the basilar artery,left middle cerebral artery,right middle cerebral artery,left anterior cerebral artery,and right anterior cerebral artery was significantly lower in the observation group than in the control group(P<0.05).The basilar artery,left middle cerebral artery,right middle cerebral artery,left anterior cerebral artery,and right anterior cerebral artery were positively correlated with the net and total net scores of each part of the Paddle Pin test and the MoCA score(P<0.05),and negatively correlated with each part of the WCST test(P<0.05).In the observation group,the post-treatment improvement was more prominent in the Paddle Pin test,WCST test,HAMD-24 score,and MoCA score compared with those in the pre-treatment period(P<0.05).Blood flow in the basilar artery,left middle cerebral artery,right middle cerebral artery,left anterior cerebral artery,and right anterior cerebral artery significantly improved in the observation group after treatment(P<0.05).CONCLUSION Impaired attention,and executive and cognitive functions are correlated with cerebral artery blood flow in patients with depression after acute hypertensive cerebral hemorrhage and warrant further study.
基金This paper was funded by the Science and Technology Research Project of Chongqing Municipal Education Commission entitled“Research on Pricing of ETFs and Their Derivatives Driven by Multi-source Heterogeneous Data”(No.KJQN202300567).
文摘Green technological innovation is crucial for the manufacturing industry’s green transformation and sustainable development.This study examines the impact of executive overconfidence on corporate green innovation,focusing on the internal drivers of corporate innovation and using a sample of Shanghai and Shenzhen A-share listed manufacturing companies from 2013 to 2020.We further examine the mediating role of digital transformation and the moderating role of external attention.The findings indicate that executive overconfidence promotes corporate green technological innovation.Overconfident executives enhance green innovation by accelerating digital transformation.Moreover,external attention from analysts and media positively moderates the relationship between executive overconfidence and corporate green innovation.Heterogeneity analysis reveals that the positive impact of executive overconfidence on green innovation is more significant in non-state-owned enterprises,high-tech firms,and enterprises with lower pollution levels.
文摘The present study aims to establish a literature review on intervention programs for executive functions(EFs)through the use of fundamental motor skills,from a neuropsychopedagogical perspective in subjects with Developmental Coordination Disorder(DCD).An exploratory study was carried out through an integrative literature review.The research was carried out in the Scientific databases Electronic Library Online(SciELO),Latin American and Caribbean Literature in Health Sciences(LILACS),Virtual Health Library-Psychology Brazil(BVSPSI),Electronic Journals of Psychology(PePSIC),in the periodicals available in the Brazilian Digital Library of Theses and Dissertations(BDTD)and on the website of the Coordination for the Improvement of Higher Education Personnel(CAPES).The covering publications took place from 2018 to 2023,14 articles were selected for analysis.This literature review made it possible to create strategies for stimulating EF and Visuomotor Functions so that educators and other professionals can better deal with students with DCD.It was perceived the need to carry out and develop more empirical research regarding the intervention of EFs and Visuomotor Functions by educators and professionals,with a greater sampling amplitude,to increase the number of studies that enable interventions both in children and in teenagers with DCD.
文摘The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.2022ZTE09.
文摘Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardware system.This literature review focuses on calculating WCET for multi-core processors,providing a survey of traditional methods used for static and dynamic analysis and highlighting the major challenges that arise from different program execution scenarios on multi-core platforms.This paper outlines the strengths and weaknesses of current methodologies and offers insights into prospective areas of research on multi-core analysis.By presenting a comprehensive analysis of the current state of research on multi-core processor analysis for WCET estimation,this review aims to serve as a valuable resource for researchers and practitioners in the field.
基金The work was supported by the National Natural Science Foundation of China(No.82072223)Scientific Research Foundation of Graduate School of Southeast University(No.YBPY2172)+1 种基金333 High Level Talents Training Project of Jiangsu Province(No.BRA2019011)General Project of Military Logistics Research(No.CLB19J025).
文摘Human genome encodes six paralogous gasdermin genes:GSDMA,GSDMB,GSDMC,GSDMD,GSDME and DFNB59.1 Proteolytic cleavage of these gasdermin proteins liberates an N-terminal(NT)fragment from autoinhibition,which assembles in membrane to form pores and execute pyroptotic cell death in general.1 In contrast to other gasdermins,gasdermin B(GSDMB)is the only gasdermin gene that has not been identified in rodents.Zhou et al first shed light on the molecular mechanism by which cytotoxic lymphocyte-derived granzyme A(GZMA)cleaves GSDMB to execute pyroptosis in GSDMB-positive cells,especially in cancer cells.2 In this issue of Cell,Hansen et al reported a dynamic host pathogen S.flexneri prevents GSDMB-mediated lysis by secreting IpaH7.8,which targets and ubiquitinates GSDMB for 26S proteasome destruction.3 They showed that GSDMB implements bacteriocidic ability by recognition of the phospholipids on Gram-negative bacterial membranes rather than lysing host cells.Although their experimental design and data are clearly presented and straightforward,there are still some doubts to be clarified.
文摘Jinzhou New China Dragon(Group)Indus-trial Co.,Ltd.(JNCDGICL)plans to to-tally invest RMB300 million to construct amolybdenum mining and deep processing project.It will
文摘A research team led by Prof.XUE Yuanchao from the Institute of Biophysics of the Chinese Academy of Sciences has developed a new method for global profiling of in-situ RNA–RNA contacts associated with a specific RNA-binding protein(RBP)and revealed positional mechanisms by which PTBP1-associated RNA loops regulate cassette exon splicing.This study was published online in Molecular Cell on March 22.In eukaryotes,the same pre-mRNA can produce multiple protein isoforms to execute similar or different biological functions through alternative splicing.Several longstanding models proposed that RBPs may regulate alternative splicing by modulating long-range RNA–RNA interactions(RRI).However,direct experimental evidence was lacking.
基金supported by the National Natural Science Foundation of China under Grant Nos.61571401 and 61901416(part of the China Postdoctoral Science Foundation under Grant No.2021TQ0304)the Innovative Talent Colleges and the University of Henan Province under Grant No.18HASTIT021.
文摘Emerging Internet of Things(IoT)applications require faster execution time and response time to achieve optimal performance.However,most IoT devices have limited or no computing capability to achieve such stringent application requirements.To this end,computation offloading in edge computing has been used for IoT systems to achieve the desired performance.Nevertheless,randomly offloading applications to any available edge without considering their resource demands,inter-application dependencies and edge resource availability may eventually result in execution delay and performance degradation.We introduce Edge-IoT,a machine learning-enabled orchestration framework in this paper,which utilizes the states of edge resources and application resource requirements to facilitate a resource-aware offloading scheme for minimizing the average latency.We further propose a variant bin-packing optimization model that co-locates applications firmly on edge resources to fully utilize available resources.Extensive experiments show the effectiveness and resource efficiency of the proposed approach.
