Dopamine in the prefrontal cortex plays multiple roles in the executive function of patients with Parkinson's disease

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.

Bibliographical Review on Rehabilitation of Executive Functions in Patients With Developmental Coordination Disorder(DCD)

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.

The Mediating Effect of Digital Transformation on the Link Between Executive Overconfidence and Corporate Green Innovation

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.

Planning,monitoring and replanning techniques for handling abnormity in HTN-based planning and execution

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.

Perspectives and Experiences of Education Stakeholders: A Quantitative Study on the Adoption of Artificial Intelligence in Executive Training Using Structural Equation Modeling

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).

Cerebral arterial blood flow,attention,and executive and cognitive functions in depressed patients after acute hypertensive cerebral hemorrhage

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.

Robust Malicious Executable Detection Using Host-Based Machine Learning Classifier

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.

Supervision of higher executives in commercial banks --From the view of game theory

After reviewing the bad news and corruptions of the higher executives in commercial banks recent years, the article first analyzes the characteristics of all these things, and use game theory to analyzes the actions between the higher executives and administrative sections and further construes with cost and benefit utility model, and finally put up some countermeasures.

Analysis on the effect of the change and growth of the top executives of listed companies

In the structure of the company, the top management is the main part of the company. The decesion they make have an important impact on the growth of the company＇s stock price changes, the company＇s performance and other enterprises. Therefore, executive replacement as an important part of corporate governance, will affect the growth of the company. This paper analyzes the factors of the change of executive, so as to study the effect of the performance of the company after the replacement of the executives.

The Trade-Off Between Performance and Security of Virtualized Trusted Execution Environment on Android

Nowadays,with the significant growth of the mobile market,security issues on the Android Operation System have also become an urgent matter.Trusted execution environment(TEE)technologies are considered an option for satisfying the inviolable property by taking advantage of hardware security.However,for Android,TEE technologies still contain restrictions and limitations.The first issue is that non-original equipment manufacturer developers have limited access to the functionality of hardware-based TEE.Another issue of hardware-based TEE is the cross-platform problem.Since every mobile device supports different TEE vendors,it becomes an obstacle for developers to migrate their trusted applications to other Android devices.A software-based TEE solution is a potential approach that allows developers to customize,package and deliver the product efficiently.Motivated by that idea,this paper introduces a VTEE model,a software-based TEE solution,on Android devices.This research contributes to the analysis of the feasibility of using a virtualized TEE on Android devices by considering two metrics:computing performance and security.The experiment shows that the VTEE model can host other software-based TEE services and deliver various cryptography TEE functions on theAndroid environment.The security evaluation shows that adding the VTEE model to the existing Android does not addmore security issues to the traditional design.Overall,this paper shows applicable solutions to adjust the balance between computing performance and security.

Economic Policy Uncertainty,Heterogeneity of Executives and Enterprise Innovation

This study analyzes how economic policy uncertainty affects corporate innovation,and the moderating effects of executive heterogeneity.A threephase dynamic investment and financing model is first built to analyze the mechanism.Empirical analysis confirms that the increase in the degree of economic policy uncertainty promotes enterprise innovation.Further results show that this promotion effect is more significant in enterprises with male executives,low educational level,no financial experience and political background.Moreover,the positive impact is only found in enterprises with moderate executive ability,and the overconfidence of senior executives plays a positive regulating role in it.

Clinical study of different modes of repetitive transcranial magnetic stimulation in the treatment of post‑stroke executive dysfunction

Objective:To investigate the clinical efficacy of intermittent theta burst stimulation(iTBS)and high frequency repetitive transcranial magnetic stimulation(rTMS)on post‑stroke executive impairment(PSEI).Methods:Ninety patients with PSEI who were hospitalized in the rehabilitation department of Xuzhou Central Hospital and Xuzhou Rehabilitation Hospital from April 2021 to June 2022 were selected and divided into iTBS group,high‑frequency group and control group.All three groups of patients received routine rehabilitation training,given rTMS treatment with iTBS,10 Hz and shame stimulation for 4 weeks.Before and after treatment,all the patients were evaluated with the Montreal cognitive assessment(MoCA),the frontal assessment battery(FAB),troop color‑word test(SCWT),shape trails test(STT),digit span test(DST)and event related potential P300.Results:After treatment,MoCA,FAB,SCWT,STT,DST scores,P300 latency and amplitude were significantly better in the three groups than before treatment(P<0.05).MoCA,FAB,SCWT,STT‑B,DST scores,P300 latency and amplitude in the iTBS group and high‑frequency group were better than in the control group,with significant differences(P<0.05).The difference between iTBS group and high‑frequency group was not statistically significant(P>0.05).Conclusion:iTBS can improve PSEI,and the efficacy is comparable to 10Hz rTMS.iTBS takes less time with better efficiency,and it is worth popularizing and applying in clinic.

网络协议软件漏洞挖掘技术综述

网络协议软件部署和应用非常广泛,在网络空间提供了诸如通信、传输、控制、管理等多样化的功能.近年来,其安全性逐渐受到学术界和工业界的重视,及时发现和修补网络协议软件漏洞,成为一项重要的课题.网络协议软件由于部署形态多样、协议交互过程复杂、相同协议规范的多个协议实现存在功能差异等特点,使得其漏洞挖掘技术面临诸多挑战.首先对网络协议软件漏洞挖掘技术进行分类,对已有关键技术的内涵进行界定.其次,进一步综述网络协议软件漏洞挖掘4个方面的技术进展,包括网络协议描述方法、挖掘对象适配技术、模糊测试技术和基于程序分析的漏洞挖掘方法,通过对比分析归纳不同方法的技术优势及评价维度.最后,总结网络协议软件漏洞挖掘的技术现状和挑战,并提炼5个潜在研究方向.

Impact of Portable Executable Header Features on Malware Detection Accuracy

One aspect of cybersecurity,incorporates the study of Portable Executables(PE)files maleficence.Artificial Intelligence(AI)can be employed in such studies,since AI has the ability to discriminate benign from malicious files.In this study,an exclusive set of 29 features was collected from trusted implementations,this set was used as a baseline to analyze the presented work in this research.A Decision Tree(DT)and Neural Network Multi-Layer Perceptron(NN-MLPC)algorithms were utilized during this work.Both algorithms were chosen after testing a few diverse procedures.This work implements a method of subgrouping features to answer questions such as,which feature has a positive impact on accuracy when added?Is it possible to determine a reliable feature set to distinguish a malicious PE file from a benign one?when combining features,would it have any effect on malware detection accuracy in a PE file?Results obtained using the proposed method were improved and carried few observations.Generally,the obtained results had practical and numerical parts,for the practical part,the number of features and which features included are the main factors impacting the calculated accuracy,also,the combination of features is as crucial in these calculations.Numerical results included,finding accuracies with enhanced values,for example,NN_MLPC attained 0.979 and 0.98;for DT an accuracy of 0.9825 and 0.986 was attained.

ESG表现如何赋能企业绿色技术创新?--来自中国上市公司的微观证据

经济新发展阶段下ESG是可持续导向下企业运营的重要理念。在绿色发展导向下,如何将企业环境、社会与公司治理(ESG)等多重责任嵌入到企业创新体系之中,驱动传统创新向绿色创新与绿色发展转型,成为了学界关注的焦点议题。本文以2011年—2019年中国沪深A股上市公司为研究样本,考察了上市公司ESG表现对企业绿色技术创新的影响及其内在作用机制。研究结果表明:(1)企业ESG表现驱动了企业绿色技术创新,对企业绿色技术创新具有显著的促进效应,在考虑内生性问题后研究结论依然稳健;区分ESG表现各类维度,企业环境责任、社会责任与公司治理表现对企业绿色技术创新均产生显著的促进效应。(2)内在机制检验结果表明,ESG表现主要通过强化企业环保投入、缓解企业融资约束以及提高企业内部控制质量以促进企业绿色技术创新。(3)调节机制检验结果表明,外部环境规制(环保补助与排污收费)与内部高管激励(薪酬激励与股权激励)在ESG表现与企业绿色技术创新之间产生显著的正向调节效应,即在ESG表现驱动企业绿色技术创新过程中,外部环境规制与内部高管激励制度具有外部的资源补偿效应、合法性倒逼效应以及内部激励效应。(4)异质性分析结果表明,ESG表现对企业绿色技术创新的驱动效应在国有企业、通过国际ISO14001环境认证企业与制造业企业中更为明显。而且经济效应检验结果表明,ESG表现驱动企业绿色技术创新有助于企业改善经济绩效。本研究为绿色发展导向下强化企业ESG理念,基于可持续导向与企业社会责任融入企业创新体系驱动企业绿色转型发展,最终实现企业与社会环境的共生融合发展提供政策启示。

高管薪酬结构与企业创新——基于高管风险承担视角

创新是企业获得技术优势的重要行为,有助于国家实现高水平科技自立自强,高管是企业做出创新决策的主体。以2008—2021年中国沪深A股上市公司为研究对象,对高管薪酬结构影响企业创新的效应及作用机制进行了实证检验。研究发现,随着高管薪酬结构中股权薪酬比例的提升,企业创新投入水平呈先上升后下降的倒“U”型趋势。进一步地,以激励物的Delta指数和Vega指数为度量的高管风险承担在薪酬结构影响企业创新的路径中发挥了中介作用。异质性分析表明,高管股权薪酬对企业创新的正向激励效果仅显著存在于非国有企业和位于高市场化程度地区的企业当中。因此,企业要制定合理的薪酬结构,适当提高股权薪酬占比,并注重改善激励环境提升高管的风险承担能力,为企业创新创造良好的内外部环境。

数字化转型与企业ESG表现——基于媒体关注度与高管过度自信的双重视角

基于2017—2022年沪深A股制造业上市公司的面板数据,从媒体关注度和高管过度自信两个视角出发,实证研究上市公司数字化转型影响ESG表现的两条路径。相关数据研究表明:第一,数字化转型与企业ESG表现存在显著的线性相关关系;第二,高管过度自信会影响数字化转型对企业ESG表现的促进作用;第三,数字化转型通过媒体关注度影响企业ESG表现。稳健性检验结果表明,在考虑倾向得分匹配法、工具变量法、替换被解释变量等方法后,数字化转型对企业ESG表现的促进作用仍然成立。异质性分析结果表明,国有企业和大规模企业能更好地利用数字化转型,积极履行社会责任,帮助企业提升ESG表现,为企业实现高质量发展提供了指引。

老年遗忘型轻度认知障碍执行功能的神经机制及数字干预

阿尔茨海默病具有极高的发病率和致死率。遗忘型轻度认知障碍(Amnestic Mild Cognitive Impairment,aMCI)作为临床前驱期,探究其形成和发展机制有助于预防阿尔茨海默病的发生。现有研究显示,多个执行域缺陷与aMCI记忆衰退密切相关,但尚未回答何种执行域是关键致病因子、关键干预治疗靶标等科学问题。为突破以往研究将执行功能视作整体抑或割裂元素的局限性,本研究拟从执行功能结构全貌着眼,在提出aMCI执行功能与记忆损害关系假说的基础上,利用脑电技术系统考察aMCI抑制、刷新和转换三种执行功能子成分的时域、时频和动态脑网络特征;并结合三维卷积神经网络筛选、识别执行功能缺陷的特异性神经靶标,探索将抑制域相关神经标记物加入aMCI早期识别的可能性;最后,通过纵向因果设计分析不同靶向数字干预对aMCI患者的训练效果及神经基础,以揭示抑制域相关额顶控制网络在干预中的重要作用。本研究有望从计算认知神经视角阐明抑制是aMCI执行功能缺损和干预的认知新靶点,进而为aMCI早期识别和制定精准化诊疗方案提供循证依据。

沉浸式3D虚拟仿真实验平台构建

为解决传统实践教学在时间、空间上的局限性,增强实践教学的互动性,以虚拟智慧城市中的物联网创新应用为研究对象,结合虚拟现实技术,在实验内容和教学模式中融入价值创造和创业素养,构建融入“创新实验路径”和“多层次综合实验项目”的物联网专业沉浸式3D虚拟仿真实验平台。采用布鲁姆教学目标分类法设计3D虚拟仿真实验教学目标,并按照IAPVE的实施模型,构建基于3D虚拟仿真实验平台的教学实施模型和考核评价模型。实施结果表明,该3D虚拟仿真实验平台及教学实施和考核评价模型可指导实践教学改革,实现学生综合能力的全面协同提升。

航空发动机叶片装配执行过程智能检测及AR引导

为了提高航空发动机叶片装配执行过程的作业智能化程度,本文提出一种航空发动机叶片装配执行过程智能检测及AR引导方法,该方法包括叶片编码识别、物料AR出入库和齐套摆放过程状态检测3个环节。针对航空发动机叶片物料缺乏自动化识别和智能化纠错的问题,搭建基于编码识别的叶片物料管理架构,提出基于图像处理的叶片编码图像前处理增强操作,并利用贝叶斯纠错对识别结果进行正误判断和纠错校正的后处理操作,提高了叶片编码识别准确率;在物料人工出入库环节,利用AR增强可视化信息辅助用户快速执行作业任务,降低了叶片物料选取作业的时间;针对叶片物料齐套准备过程,构建了基于检测比对的防错纠错系统,避免发生人为错误。所提叶片装配执行过程智能检测及AR增强辅助引导方法可以有效减少人力物力和时间消耗,在推动航空发动机迈向智能化和自动化生产上起到技术支撑作用。