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.

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.

Gender Equality and the Risk Assessment of Corporate Financialization:An Analysis of the Increase in the Proportion of Female Executives

This paper empirically investigates the impact of the proportion of female executives on the financialization of enterprises using a sample of listed companies in the Shanghai and Shenzhen stock markets from 2009-2018.Previous studies tend to conclude that female executives are risk averse,preventing firms from participating in high-risk financial investments.However,the results of this paper show that there is a positive relationship between the proportion of female executives and the degree of corporate financialization,with an increase of 1 percent in the proportion of female executives leading to an increase of 3.8 percent in the degree of corporate financialization.Further tests show that gender inequality is a possible mechanism influencing female executives'financial investment preferences in the unique gender culture context of China.This paper expands the research on the impact of non-institutional factors on corporate financialization,and also points out that unilaterally pursuing an increase in the proportion of female executives does not reduce the risk of corporate financialization,and that only an overall increase in the proportion of female executives can reduce the risk of corporate financialization.Improving gender equality at the social level can fundamentally reflect women's risk aversion characteristics and encourage enterprises to make more stable investment decisions.

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.

Does top executives' US experience matter? Evidence from US-listed Chinese firms

Foreign firms face enormous obstacles in attracting investors and analysts when issuing securities in the United States.We use US-listed Chinese firms as our research sample and find that firms that hire top executives(i.e.,Chief Executive Officer[CEO]or Chief Financial Officer[CFO]) with work experience in the US or educational qualifications from the US attract more US institutional investors and analysts.Further,we find that CFOs' US experience dominates the results.Corroborating our results,we further find that firms with US-experienced CFOs are more likely to hold conference calls and voluntarily issue management forecasts,which suggests that CFOs with a US background are better at communicating with US investors and analysts and acting in alignment with US norms compared with Chinese CFOs.Collectively,our results suggest that hiring a CFO with a US background could facilitate cross-listed foreign firms to lower US investors' and analysts' information disadvantage.

A Study on the Compensation Gap among Executives at Chinese Enterprises

Based on data for 2005 to 2012, an analysis of the compensation gap between top executives at different Chinese listed companies reveals the following conclusions. （1） The large compensation gap existing among executives at listed Chinese companies--in some years even larger than that between rank-and-file employees--is mainly caused by the exorbitant executive compensation at a minority of companies. （2） Between 2005 and 2012, the compensation gap first widened dramatically and then diminished gradually. The leading factor in this fluctuation was the drastic rise and fall in the level of executive compensation at a handful of financial enterprises. The main reason for the narrowing of the compensation gap is central government regulation, which has helped to curb the excessive growth of executive compensation in society as a whole. （3） Even in the same round of fluctuation, state-owned listed companies differ markedly from non-state-owned listed companies in the way their executive compensation is decided. （4） State-owned listed companies＇ executive compensation strategies and their internal governance structure have not played their due role in moderating the overly rapid growth of their executives＇ compensation or in reducing the compensation gap.

Binary Program Vulnerability Mining Based on Neural Network

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.

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.

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.

Improving Prediction Efficiency of Machine Learning Models for Cardiovascular Disease in IoST-Based Systems through Hyperparameter Optimization

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.

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.

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.

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.

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).

Research on Multi-Core Processor Analysis for WCET Estimation

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.

An Analysis of Causes of Professional Embezzlement Committed by Executives of State-Owned Enterprise Based on the “Triangle Theory”

According to the fraud"triangle theory",the causes of professional embezzlements committed by executives of China’s state-owned enterprises are mainly from pressure,opportunities and excuses.Among them,pressure is a huge psychological burden and desire generated by the combined action of the self-interested value orientation of the economic man and the value-oriented market economy in the pursuit of wealth.Opportunity refers mainly to the weak restrain on the asset operation responsibility of the executives,the cultural atmosphere of advocating the status and authority in the enterprises,and the lack of necessary power balance and internal control,all of them are caused by the system defects of the company systems under the public ownership.Excuses mainly have such forms as"kickbacks","borrowed money"and unreasonable design of remuneration and incentive systems,etc.The effective way to prevent executives of state-owned enterprises from committing professional embezzlement is to select the personnel with excellent conduct and ability as executives,create the corporate culture of honesty and trustworthiness,perfect a variety of mechanisms and systems,urge the effective implementation of the system,and maintain the normal operation of the mechanism.

Review of Arbitral Award of Network Loan and Analysis of Construction of Implementation Review Rules

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.

How Flexible Should the Law Be Against Criminal Corporate Executives?

Against the backdrop of a widely spread-ing global economic crisis, coupled with the slowdown facing China’s own economy, cases of fraud and corruption are becoming a

Auto executives:Worried While Being Happy

Xu Liuping,director of the board of Chang'an Auto Group,had just come back from Japan and north America before the opening of this year's Shanghai auto show.He knew something about the financial crisis towards the overseas auto industry from reports and during this