On the Construction of Deepening Anti - corruption Mechanism

It needs the foundation of system and the guarantee of organizational system for anti-corruption,but it is more necessary to build and form an effective anti-corruption mechanism,so that the anti-corruption can be really put into practice. Anti-corruption mechanism refers to a organic operation system of the interaction,interconnection and constraint between the constituent elements( parts) and elements of national anti-corruption,and as a system,anti-corruption mechanism should have the characteristics of system aticness,comprehensiveness,transparency,legalization,public participation,scientific dynam ic,and internationalism. The construction of deepening anti-corruption mechanism is the need for reconstructing the ruling legitimacy of the party and the governm ent. Adhering to the principle of treating both root causes and symptoms is necessary in the construction of anti-corruption m echanism,com bating and punishing corruption is an important part of anti-corruption,and the prevention and control of corruption is the basic project of anti-corruption. Therefore,the construction of prevention and control mechanism in the anti-corruption mechanism has a more far-reaching significance.

The Catastrophe of Corruption in the Sustainability of Foreign aid:A Prediction of Artificial Neural Network Method in Indonesia

The rising corruption levels in Indonesia are becoming a cause for concern and raise doubts about their impact on the stability of foreign aid in the country.Therefore,this study aims to predict the long-term viability of foreign aid in Indonesia based on international perceptions of corruption and corruption cases in the country.Data were obtained from World Governance Indicators,the Indonesian Ministry of Finance,and the World Bank,and the study used a backpropagation artificial neural network(ANN)for prediction.The results from ANN are compared to linear models and vector autoregression(VAR).The finding shows that ANN outperforms the other models based on the coefficient of determination and MSE values.Furthermore,it highlights the strong relationship between corruption perception and foreign aid sustainability with an R-value of 0.991.According to the ANN estimation,gratification has a significant impact on foreign aid.In response to this finding,the study recommends the Indonesian government take action to combat corruption in maintaining the international trust and ensuring the stability of foreign aid.

Analyzing and Optimizing Packet Corruption in RDMA Network

Remote direct memory access (RDMA) has become one of the state-of-the-art high-performance network technologies in datacenters. The reliable transport of RDMA is designed based on a lossless underlying network and cannot endure a high packet loss rate. However, except for switch buffer overflow, there is another kind of packet loss in the RDMA network, i.e., packet corruption, which has not been discussed in depth. The packet corruption incurs long application tail latency by causing timeout retransmissions. The challenges to solving packet corruption in the RDMA network include: 1) packet corruption is inevitable with any remedial mechanisms and 2) RDMA hardware is not programmable. This paper proposes some designs which can guarantee the expected tail latency of applications with the existence of packet corruption. The key idea is controlling the occurring probabilities of timeout events caused by packet corruption through transforming timeout retransmissions into out-of-order retransmissions. We build a probabilistic model to estimate the occurrence probabilities and real effects of the corruption patterns. We implement these two mechanisms with the help of programmable switches and the zero-byte message RDMA feature. We build an ns-3 simulation and implement optimization mechanisms on our testbed. The simulation and testbed experiments show that the optimizations can decrease the flow completion time by several orders of magnitudes with less than 3% bandwidth cost at different packet corruption rates.

Oscillatory and anti-oscillatory motifs in genetic regulatory networks

Recently, self-sustained oscillatory genetic regulatory networks （GRNs） have attracted significant attention in the biological field. Given a GRN, it is important to anticipate whether the network could generate oscillation with proper parameters, and what the key ingredients for the oscillation are. In this paper the ranges of some function-related parameters which are favorable to sustained oscillations are considered. In particular, some oscillatory motifs appearing with high-frequency in most of the oscillatory GRNs are observed. Moreover, there are some anti-oscillatory motifs which have a strong oscillation repressing effect. Some conclusions analyzing these motif effects and constructing oscillatory GRNs are provided.

Anti-windup compensation design for a class of distributed time-delayed cellular neural networks

Both time-delays and anti-windup(AW)problems are conventional problems in system design,which are scarcely discussed in cellular neural networks(CNNs).This paper discusses stabilization for a class of distributed time-delayed CNNs with input saturation.Based on the Lyapunov theory and the Schur complement principle,a bilinear matrix inequality(BMI)criterion is designed to stabilize the system with input saturation.By matrix congruent transformation,the BMI control criterion can be changed into linear matrix inequality(LMI)criterion,then it can be easily solved by the computer.It is a one-step AW strategy that the feedback compensator and the AW compensator can be determined simultaneously.The attraction domain and its optimization are also discussed.The structure of CNNs with both constant timedelays and distribute time-delays is more general.This method is simple and systematic,allowing dealing with a large class of such systems whose excitation satisfies the Lipschitz condition.The simulation results verify the effectiveness and feasibility of the proposed method.

Anti-synchronization Between Coupled Networks with Two Active Forms

这份报纸与非线性的信号的连接和互连网络行动学习在二个联合网络之间的反同步和它的控制。如果反同步不在二个如此的网络之间存在，适应控制器被设计到反同步他们。拓扑的结构被考虑的不同节点动力学和 nonidentical 和为在二个网络之间的反同步的有用标准被给。数字例子被举显示出我们的导出的结果的效率。

Prediction of Anti-Inflammatory Activity of a Series of Pyrimidine Derivatives, by Multiple Linear Regression and Artificial Neural Networks

Anti-inflammatory activity of a series of tri-substituted pyrimidine derivatives was predicted using two Quantitative Structure-Activity Relationship models. These relationships were developed from molecular descriptors calculated using the DFT quantum chemistry method using the B3LYP/6-31G(d,p) level of theory and molecular lipophilicity. Thus, the four descriptors which are the dipole moment μD, the energy of the highest occupied molecular orbital EHOMO, the isotropic polarizability α and the ACD/logP lipophilicity were selected for this purpose. The Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models are respectively accredited with the following statistical indicators: R2=91.28%, R2aj=89.11%, RMCE = 0.2831, R2ext=86.50% and R2=98.22%, R2aj=97.75%, RMCE = 0.1131, R2ext=98.54%. The results obtained with the artificial neural network are better than those of the multiple linear regression. However, these results show that the two models developed have very good predictive performance of anti-inflammatory activity. These two models can therefore be used to predict anti-inflammatory activity of new similar pyrimidine derivatives.

Existence and Exponential Stability of the Anti-Periodic Solutions for a Class of Impulsive CohenGrossberg Neural Networks with Mixed Delays

In this paper,we study the anti-periodic solutions for a class of impulsive Cohen-Grossberg neural networks with mixed delays.By using analysis techniques,some sufficient conditions are obtained which guarantee the existence and global exponential stability of the anti-periodic solutions.The criteria extend and improve some earlier results.Moreover,we give an examples to illustrate our main results.

创新要素集聚、反腐与创新效率提升

如何实现经济高速增长向高质量发展的动能转变是新时代中国特色社会主义经济亟待破解的重要命题。既有理论研究与实践经验表明,创新驱动是实现经济高质量发展的关键突破点,而创新要素的有效集聚则是实现创新驱动的必要条件。因此,现阶段从中央政府到地方政府均大力推进创新要素的有效集聚。从理论上看,在创新要素集聚过程中,政府扮演着十分重要的角色,而腐败作为一种阻碍资源有效配置的政府行为,可能不利于创新要素的有效集聚。文章将腐败行为引入创新要素集聚与创新效率的理论分析框架中,理论分析的结论初步表明创新要素集聚有利于创新效率提升,行政腐败则抑制了这一正向效应;当反腐力度加强时,这一抑制效应可能得到一定程度上的缓解。在理论分析的基础上,文章进一步基于2002—2016年我国省级面板数据,运用Tobit空间面板回归模型、IV-Tobit模型对上述结论进行了实证检验。实证结果表明,政府主导的创新要素集聚有效促进了创新效率的提升,而腐败行为的存在则抑制了这一正向效应。该研究结论在考虑内生性问题,并进行一系列稳健性检验后依然保持一致。同时,空间计量模型的分析结果显示创新要素集聚的空间溢出效应显著为负,即各地区之间存在“各自为政”的现象,缺乏区域协同创新。进一步研究发现,党的十八大之后反腐力度的加强有效地缓解了腐败所造成的负向效应,同时也使创新要素集聚的负向空间溢出效应得到了纠偏,表明党的十八大之后的反腐行动为“创新驱动发展战略”释放了制度红利,提供了有利于创新要素有效集聚与配置的生存土壤。以上研究发现对新发展阶段我国经济高质量发展的路径选择具有一定的参考价值。据此,文章认为腐败行为的创新抑制效应意味着加强反腐力度、简政放权能够改善创新要素集聚的制度环境。反腐虽然能够降低寻求政治关联的激励,提高创新效率,但市场机制扭曲才是腐败影响创新要素集聚的根源所在。因此,现阶段应从处理好政府与市场之间的关系入手,转变政府的职能,进一步完善市场机制,最终形成以市场配置为主、以政府引导为辅的创新要素集聚模式。

新时代中国民众反腐败效能感:本土概念与量表构建

意愿等心理机制是决定民众积极有序参与反腐败活动的重要因素,反腐败效能感概念的提出与测量正是对于这一问题的学理性探讨。反腐败效能感涵盖民众基于自我能力认知的内部效能感和基于对反腐败政策发生效用的外部效能感,其中对于具体反腐败政策的评价、对于不同层级的官员廉洁形象的评价以及对于反腐败参与意愿的倾向性态度等是中国本土的独有特征。基于民众反腐败效能感的微观测量为构建反腐倡廉宏观方略的长效动力机制提供了科学依据,对于提升国家治理能力现代化、实现从严治党背景下反腐倡廉工作的深入进行具有重要的知识积累和政策咨询意义。

一体推进“三不腐”战略的三重逻辑

一体推进“三不腐”是以习近平同志为核心的党中央顺应新时代反腐倡廉工作形势、斗争形势和廉政建设实践需要提出的战略部署和工作方针。一体推进“三不腐”战略形成的背后存在三重逻辑:由马克思主义唯物辩证法和马克思主义廉政观构成的科学理论来源;由中华传统优秀廉政文化和中国共产党百年反腐败斗争历程组成的历史进路;由新时代中国共产党持续推进自我革命、有效落实全面从严治党、长期践行中央八项规定精神的具体实践构建的现实基础。以理论、历史和实践为基础探寻一体推进“三不腐”战略的三重生成逻辑,有利于进一步探寻新时代中国共产党反腐败斗争指导思想的科学内涵、历史渊源和现实支撑,助力中国党风廉政建设事业的进一步发展。

铲除腐败问题产生的土壤和条件:内涵、原则与路径

腐败是危害党的生命力和战斗力的毒瘤,是与人类政治生活偕行的痼疾。铲除腐败问题产生的土壤和条件,既体现了马克思主义执政党对腐败发生机理的深刻认知,也彰显着从源头上防范和治理腐败的科学理念和鲜明指向。在反腐败斗争依然严峻复杂的形势下,铲除腐败问题产生的土壤和条件,要遵循习近平总书记关于党的自我革命的重要思想、一体推进“三不腐”方针所蕴含的策略和要求,准确把握腐败的形成要素、作用机理和衍生规律,确定科学的实践原则和思路;以“全周期管理”方式将不敢腐的强大震慑效能、不能腐的刚性制度约束、不想腐的思想教育融于一体,精准发力,多措并举,不断拓展反腐败斗争的广度和深度。

新形势下高校学生廉洁教育存在问题与对策

随着国家反腐倡廉工作的深入推进,党和国家对新形势下的高校廉洁教育工作提出新的要求。当前,大学生廉洁教育中存在的主要问题包括廉洁教育意识薄弱、参与积极性不足;廉洁教育未能有序推进、教育无层次、无重点;廉洁教育力量分散、育人格局欠佳。为更好地推进大学生廉洁教育工作,该文在深入理解廉洁育人内涵的基础上,立足于“三全育人”理念和“立德树人”目标,探索符合当代大学生特点的“全员、全程、全方位”三全齐力的廉洁育人途径,为大学生身心的健康成长、高等教育的高质量发展和反腐倡廉建设的稳步推进提供理论支撑。

城市防疫医疗救援网络的抗毁性与鲁棒性

为研究城市防疫医疗救援系统空间布局的合理性和防灾韧性,采用复杂网络技术构建了某城市防疫医疗救援网络模型,对其网络拓扑结构和网络特征基本参数进行分析,研究不同攻击模型下以边和点连通度为度量指标的结构抗毁性能力;通过设定不同的网络冗余与网络负荷,研究网络针对确定性攻击与随机性攻击的鲁棒性特征。研究结果可为城市防疫医疗救援系统的空间优化布局和核心场所强化建设提供理论支撑。

人工神经网络在治疗药物监测中的应用

人工神经网络(ANN)是对生物神经网络的一种模拟,通过相互连接而构成的自适应非线性动态网络系统,ANN的优势在于优化容易、建模简便、结果准确。该文根据文献资料对ANN在免疫抑制剂、抗菌药物、抗癫痫药物等治疗药物监测中的应用进展进行阐述,阐明ANN模型的优缺点以及未来的发展方向,希望为未来的研究者提供有价值的参考信息。ANN用于治疗药物监测有着巨大的潜在前景,有希望成为实现患者个体化用药的有效手段。

新时代高校研究生反腐和廉洁教育认知调查与对策建议

反腐和廉洁教育是新时代研究生思想政治教育的重要内容。课题组以问卷调查和深度访谈等方式对西南交通大学现阶段研究生反腐和廉洁教育工作的情况进行了调查研究,发现就现阶段研究生对廉洁教育途径、方法、内容等方面的认知状态来说,必须加强研究生廉洁教育意识的培养和固化,精准创新研究生廉洁教育的途径和方式,将廉洁教育课程化、实践化、常态化、数字化,不断丰富研究生廉洁教育的内容,才能提高研究生廉洁教育的实效性。

马克思廉价政府思想的理论考察与当代价值

廉政建设是推进全面从严治党、党的自我革命的有力保障。马克思在《法兰西内战》中总结了廉价政府的一系列思想,阐释了廉政机制保障,提出了约束贪腐的罢免制度,明确了揭露腐败的监督机制,揭示了规范权力运行的法律制度等。马克思廉价政府思想在本质上要求廉政建设必须具有自我革命的实践性、整合重构的系统性、管党治党的权威性。当代中国廉政建设实践对马克思廉价政府思想的创新发展取得突出成效,以建设党内法规体系保证党对廉政建设的坚强领导,以改革纪检监察体制保证党的执政地位长期巩固,以健全党和国家监督体系保证党的自我革命不断深化。马克思廉价政府思想的当代价值要求我们必须持续加强党对廉政建设的坚强领导和自我革命的政治使命,持续强化廉政建设的科学性和时代变迁的适应性,持续探索增强廉政建设执行力的内在动因和运行规律,持续提升中国特色社会主义廉政建设成果和治理效能。