Innovative Development of chinese Regions: Experience and Recommendations for Russia

Purpose: of the article is a parametric comparison of the features of the development of the regions of China and Russia for the possibility of using the Chinese experience in managing innovative development.Methods: comparison of the innovative potential of Russia and the PRC, as well as the possibilities of using the Chinese experience in the management of scientific, technical and innovative development in Russia was carried out using linear regression analysis and comparison of its indicators. Analysis and comparison were carried out using statistical data on innovative and economic development in statistical collections of Russia and China.Results: the article discusses the possibilities of using Chinese management experience in the development of the spheres of science, technology and higher education for the innovative and economic development of Russian regions. To a large extent, the experience of the PRC is already actively used in Russian state practice, while, in the context of Russia's economic difficulties in recent decades, it does not always work successfully. The work shows that the regions of the PRC are rapidly increasing their innovative activity in recent years, which contributes to the rapid growth of the well-being of their population. The number of regions-innovative and economic leaders is growing. Among all regions of Russia, only Moscow in level of innovational activity and GRP corresponds to the leading regions of China. The paper also shows that changes in the indicators of innovation activity of Russian regions have a relatively weak effect on their economic development.Conclusions and Relevance: it is recommended to carefully study the experience of the Chinese regions-innovation leaders and the Chinese innovation policy in general for application in Russia, as well as the development of Russian-Chinese innovation and scientific and technological cooperation

Structural damage detection based on cloud model and Dempster-Shafer evidence theory

Cloud model and D-S theory have been widely used in uncertainty reasoning. Meanwhile, modal strain energy and Inner Product Vector are also utilized as damage-sensitive features to detect structural damage. In this paper, a new structural damage identification approach is proposed based on Dempster-Shafer theory and cloud model. Cloud models were created to make uncertainty reasoning in damage structures by modal strain energy and the Inner Product Vector of acceleration. Then the results of the two methods were combined by using the Dempster-Shafer theory. Due to the classical D-S theory involves counter – intuitive behavious when the high conflicting evidences exists, the distance function was introduced to correct the conflict factor K and combine the evidences. Moreover, a model of simple beam was created to verify the feasibility and accuracy for the single-damage and the multiple-damage. The effects of noise on damage detection were investigated simultaneously. The results show that the method has strong anti-noise ability and high accuracy

Инновационное развитие китайских регионов: опыт и рекомендации для России

Purpose: of the article is a parametric comparison of the features of the development of the regions of China and Russia for the possibility of using the Chinese experience in managing innovative development.Methods: comparison of the innovative potential of Russia and the PRC, as well as the possibilities of using the Chinese experience in the management of scientific, technical and innovative development in Russia was carried out using linear regression analysis and comparison of its indicators. Analysis and comparison were carried out using statistical data on innovative and economic development in statistical collections of Russia and China.Results: the article discusses the possibilities of using Chinese management experience in the development of the spheres of science, technology and higher education for the innovative and economic development of Russian regions. To a large extent, the experience of the PRC is already actively used in Russian state practice, while, in the context of Russia's economic difficulties in recent decades, it does not always work successfully. The work shows that the regions of the PRC are rapidly increasing their innovative activity in recent years, which contributes to the rapid growth of the well-being of their population. The number of regions-innovative and economic leaders is growing. Among all regions of Russia, only Moscow in level of innovational activity and GRP corresponds to the leading regions of China. The paper also shows that changes in the indicators of innovation activity of Russian regions have a relatively weak effect on their economic development.Conclusions and Relevance: it is recommended to carefully study the experience of the Chinese regions-innovation leaders and the Chinese innovation policy in general for application in Russia, as well as the development of Russian-Chinese innovation and scientific and technological cooperation.Целью работы является параметрическое сравнение особенностей развития регионов Китая и России на предмет возможностей применения в РФ китайского опыта управления инновационным развитием.Метод или методология проведения работы. Сравнение инновационного потенциала РФ и КНР, а также возможностей применения в России китайского опыта в управлении научно-техническим и инновационным развитием проведено с помощью линейного регрессионного анализа и изучения его показателей. В работе использованы статистические данные по инновационному и экономическому развитию из статистических сборников России и КНР.Результаты работы. В представленном исследовании рассмотрены возможности применения китайского управленческого опыта по развитию сфер науки, технологий и высшей школы для инновационного и экономического развития регионов России. В значительной степени опыт КНР уже активно используется в российской государственной практике, при этом, в условиях экономических трудностей России в последние десятилетия, он далеко не всегда успешно работает. В статье показано, что регионы КНР быстро наращивают инновационную активность в последние годы, что способствует динамичному росту благосостояния их населения, а кроме того, увеличивается число регионов – инновационных и экономических лидеров. К аналогичным по уровню китайским регионам – инновационным лидерам в России сегодня в полной мере относится только Москва. В работе также показано, что изменения в показателях инновационной активности регионов России относительно слабо влияют на их экономическое развитие.Выводы. Рекомендуется внимательное изучение опыта китайских регионов – инновационных лидеров и китайской инновационной политики в целом для применения в России, а также развития российско-китайского инновационного и научно-технологического сотрудничества

Hybrid Renormalization for Quasi Distribution Amplitudes of A Light Baryon

We develop a hybrid scheme to renormalize quasi distribution amplitudes of a light baryon on the lattice, which combines the self-renormalization and ratio scheme. By employing self-renormalization, the UV divergences and linear divergence at large spatial separations in quasi distribution amplitudes are removed without introducing extra nonperturbative effects, while making a ratio with respect to the zero-momentum matrix element can properly remove the UV divergences in small spatial separations. As a specific application, distribution amplitudes of the $\Lambda$ baryon made of $uds$ are investigated, and the requisite equal-time correlators, which define quasi distribution amplitudes in coordinate space, are perturbatively calculated up to the next-to-leading order in strong coupling constant $\alpha_s$. These perturbative equal-time correlators are used to convert lattice QCD matrix elements to the continuum space during the renormalization process. Subsequently, quasi distribution amplitudes are matched onto lightcone distribution amplitudes by integrating out hard modes and the corresponding hard kernels are derived up to next-to-leading order in $\alpha_s$ including the hybrid counterterms. These results are valuable in the lattice-based investigation of the lightcone distribution amplitudes of a light baryon from the first principles of QCD.Comment: 25 pages, 4 figure

Multiscale Simulation of Surface Defect Influence in Nanoindentation by a Quasi-Continuum Method

Microscopic properties of crystal aluminum thin film have been investigated using the quasi-continuum method in order to study the influence of surface defects in nanoindentation. Various distances between the surface pit defect and indenter and various sizes of the pit have been calculated. In this simulation, as the distance between the pit and indenter increases, the nanohardness increases in a wave that goes up in a period of three atoms, and it is found closely related to the crystal structure of periodic atom arrangement on {1 1 1} atomic close-packed planes of FCC metal; there is almost no influence on the nanohardness when the adjacent distance between the pit and indenter is more than 16 atomic spacing. We have modified the theoretical equation of the necessary load for elastic-to-plastic transition of Al film with the initial surface defect size. Furthermore, when the size coefficient of width (of height) equals about one unit (half unit), the yield load experiences an obvious drop. When it reaches about two units (one unit), the yield load is nearly close to that of the nanoindentation on a stepped surface. Additionally, compared to the width, the height of surface pit defect displays a greater influence on the yield load of thin film

Learning to Detect: A Data-driven Approach for Network Intrusion Detection

With massive data being generated daily and the ever-increasing interconnectivity of the world’s Internet infrastructures, a machine learning based intrusion detection system (IDS) has become a vital component to protect our economic and national security. In this paper, we perform a comprehensive study on NSL-KDD, a network traffic dataset, by visualizing patterns and employing different learning-based models to detect cyber attacks. Unlike previous shallow learning and deep learning models that use the single learning model approach for intrusion detection, we adopt a hierarchy strategy, in which the intrusion and normal behavior are classified firstly, and then the specific types of attacks are classified. We demonstrate the advantage of the unsupervised representation learning model in binary intrusion detection tasks. Besides, we alleviate the data imbalance problem with SVM-SMOTE oversampling technique in 4-class classification and further demonstrate the effectiveness and the drawback of the oversampling mechanism with a deep neural network as a base model. Index Terms—Intrusio

Codon optimization, expression, purification, and functional characterization of recombinant human IL-25 in Pichia pastoris

Interleukin (IL)-25 (also known as IL-17E) is a distinct member of the IL-17 cytokine family which induces IL-4, IL-5, and IL-13 expression and promotes pathogenic T helper (Th)-2 cell responses in various organs. IL-25 has been shown to have crucial role between innate and adaptive immunity and also a key component of the protection of gastrointestinal helminthes. In this study, to produce bioactive recombinant human IL-25 (rhIL-25), the cDNA of mature IL-25 was performed codon optimization based on methylotropic yeast Pichia pastoris codon bias and cloned into the expression vector pPICZαA. The recombinant vector was transformed into P. pichia strain X-33 and selected by zeocin resistance. Benchtop fermentation and simple purification strategy were established to purify the rhIL-25 with about 17 kDa molecular mass. Functional analysis showed that purified rhIL-25 specifically bond to receptor IL-17BR and induce G-CSF production in vitro. Further annexin V-FITC/PI staining assay indicated that rhIL-25 induced apoptosis in two breast cancer cells, MDA-MB-231 and HBL-100. This study provides a new strategy for the large-scale production of bioactive IL-25 for biological and therapeutic applications

Domain Adaptive Person Search via GAN-based Scene Synthesis for Cross-scene Videos

Person search has recently been a challenging task in the computer vision domain, which aims to search specific pedestrians from real cameras.Nevertheless, most surveillance videos comprise only a handful of images of each pedestrian, which often feature identical backgrounds and clothing. Hence, it is difficult to learn more discriminative features for person search in real scenes. To tackle this challenge, we draw on Generative Adversarial Networks (GAN) to synthesize data from surveillance videos. GAN has thrived in computer vision problems because it produces high-quality images efficiently. We merely alter the popular Fast R-CNN model, which is capable of processing videos and yielding accurate detection outcomes. In order to appropriately relieve the pressure brought by the two-stage model, we design an Assisted-Identity Query Module (AIDQ) to provide positive images for the behind part. Besides, the proposed novel GAN-based Scene Synthesis model that can synthesize high-quality cross-id person images for person search tasks. In order to facilitate the feature learning of the GAN-based Scene Synthesis model, we adopt an online learning strategy that collaboratively learns the synthesized images and original images. Extensive experiments on two widely used person search benchmarks, CUHK-SYSU and PRW, have shown that our method has achieved great performance, and the extensive ablation study further justifies our GAN-synthetic data can effectively increase the variability of the datasets and be more realistic