Construction,structure and photocatalysis of janus nanofiber modified by g-C3N4 nanosheets heterostructure photocatalysts

The construction of photocatalyst with gradient band structure is guided by the principle of band gap engineering. Rational structural design is advanced and applied to construct a new-typed peculiarly structural and functional carbon-based [TiO₂/C]//[Bi₂WO₆/C] Janus nanofiber modified by g-C₃N₄ nanosheets heterostructure photocatalyst (denoted as TB-JgHP). The flexible carbon-based [TiO₂/C]//[Bi₂WO₆/C] Janus nanofiber with one side responding to ultraviolet light and the other capturing visible light is fabricated by conjugate electrospinning, and then g-C₃N₄ nanosheets are uniformly grown in-situ on the surface of the Janus nanofibers by using gas-solid reaction via gasification of urea. The optimized TB-JgHP possesses remarkable hydrogen evolution efficiency (17.48 mmol h⁻¹ g⁻¹) and methylene blue degradation rate (99.2%) under simulated sunlight illumination for 100 min, demonstrating prominent dual-functional characteristics. The enhanced photocatalytic performance benefits from the unique Janus structure as well as the synergistic effects among the triple heterostructures of TiO₂ and Bi₂WO₆, g-C₃N₄ and TiO₂, g-C₃N₄ and Bi₂WO₆. The formation of gradient band structure among heterostructures is more conducive to the multi-step separation of photo-induced electron-hole pairs and more effective absorption of light. Further, flexible self-standing carbon-based photocatalysts not only have outstanding electron transport performance, but also are easy to separate from solution with preeminent recyclable stability. Based on a series of characterization techniques, it is further proved that TB-JgHP has higher carrier separation efficiency than the counterpart contrast samples. The formation mechanism of TB-JgHP is proposed, and the construction technique is established. The design philosophy and construction technique presented in this work pave a new avenue for research and development of other heterostructure photocatalysts.     

A comprehensive survey on computer vision based concepts,methodologies, analysis and applications for automatic gun/knife detection

The ability to detect gun and gun held in hand or other body parts is a typical human skill. The same problem presents an imperative task for computer vision system. Automatic observer independent detection of hand held gun or gun held in the other body part, whether it is visible or concealed, provides enhance security in vulnerable places and initiates appropriate action there. Compare to the automatic object detection systems, automatic detection of gun has very few successful attempts. In the present scope of this paper, we present an extensive survey on automatic detection of gun and define a taxonomy for this particular detection system. We also describe the inherent difficulties related with this problem. In this survey of published papers, we examine different approaches used in state-of-the-art attempts and compare performances of these approaches. Finally, this paper concludes pointing to the possible research gaps in related fields.     

Multiple Empirical Kernel Learning with Majority Projection for imbalanced problems

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To make MEKL suit for the imbalanced problems, this paper introduces a weight matrix and a regularization term into MEKL. The weight matrix assigns high misclassification cost to the minority samples to balanced misclassification cost between minority and majority class. The regularization term named Majority Projection (MP) is used to make the classification hyperplane fit the distribution shape of majority samples and enlarge the between-class distance of minority and majority class. The contributions of this work are: (i) assigning high cost to minority samples to deal with imbalanced problems, (ii) introducing a new regularization term to concern the property of data distribution, (iii) and modifying the original PAC-Bayes bound to test the error upper bound of MEKL-MP. Through analyzing the experimental results, the proposed MEKL-MP is well suited to the imbalanced problems and has lower generalization risk in accordance with the value of PAC-Bayes bound.     

A hybrid multiple feature construction approach for classification using Genetic Programming

The purpose of feature construction is to create new higher-level features from original ones. Genetic Programming (GP) was usually employed to perform feature construction tasks due to its flexible representation. Filter-based approach and wrapper-based approach are two commonly used feature construction approaches according to their different evaluation functions. In this paper, we propose a hybrid feature construction approach using genetic programming (Hybrid-GPFC) that combines filter’s fitness function and wrapper’s fitness function, and propose a multiple feature construction method that stores top excellent individuals during a single GP run. Experiments on ten datasets show that our proposed multiple feature construction method (Fcm) can achieve better (or equivalent) classification performance than the single feature construction method (Fcs), and our Hybrid-GPFC can obtain better classification performance than filter-based feature construction approaches (Filter-GPFC) and wrapper-based feature construction approaches (Wrapper-GPFC) in most cases. Further investigations on combinations of constructed features and original features show that constructed features augmented with original features do not improve the classification performance comparing with constructed features only. The comparisons with three state-of-art methods show that in majority of cases, our proposed hybrid multiple feature construction approach can achieve better classification performance.     

基于时间延迟的多类型维修与经济生产批量联合优化研究

针对目前未能较好的综合考虑多维修类型与经济生产批量联合优化的问题，首先考虑多类型维修关系，基于时间延迟理论求出故障和缺陷次数的表达式；其次，在此基础上，综合考虑生产费用和维修费用的基础上，构建了多类型维修和经济生产批量联合优化模型，以单位时间内总费用最小为优化目标，获得最优检查间隔期和经济生产批量；最后，通过算例分析验证了模型的有效性，说明了第一类缺陷检查次数的多少对费用和经济生产批量影响不大。     

混合物联合暴露风险评估方法进展及其对我国构建相关体系借鉴作用

基于人类通过多种途径暴露于多种物质,以及混合物共存可能诱导联合毒性效应的现实,混合物联合暴露风险评估受到国际社会的广泛关注。许多国家依据各自提出的评估指南开展风险评估,其评估结果为科学决策提供依据。本文通过分析国际上混合物联合暴露风险评估模型构建方法和框架,探讨构建我国食品中混合物联合作用风险评估体系和框架。     

Prediction of Power Consumption in a Mechanically Agitated Gassed Reactor in Viscous Batches

Volumetric mass transfer coefficient, power input, and gas holdup are key parameters in the design of mechanically agitated gas‐liquid contactors. Although the majority of industrial batches are of higher viscosity, reliable transport characteristics correlations for viscous batches are lacking in literature. These correlations are often based on the power input as the scale of energy dissipation. In order to develop reliable power input correlations, its measurements were carried out in a pilot‐plant vessel using multiple impellers of various types and diameters. Power input correlation shapes providing the best match with the comprehensive database are also expected to predict most precisely the impeller power in industrial‐scale vessels.     

Application of Lyapunov's Methods for Analyzing the Stability of a Tubular Chemical Reactor with Recycle

The first and second Lyapunov methods were adapted to analyze the stability of a tubular chemical reactor with recycle. The criterion of local stability in the form of inequalities was derived using Lyapunov's first method. It is an explicit algebraic form, despite the fact that the mathematical model of the reactor is a partial differential problem with a boundary condition. As part of the second Lyapunov method, a mathematical criterion for non-local stability was derived in the form of an increase of Lyapunov's function. Both criteria are presented on graphs.     

Model recovery anti-windup for output saturated SISO linear closed loops

We define model recovery anti-windup for SISO linear control systems with output saturation. We address the problem by relying on a hybrid modification of the linear closed loop which employs a suitable logic variable to activate/deactivate various components of a control scheme. The scheme relies on a finite-time observation law, an open-loop observer and an open-loop input generator which is capable of driving the plant output within the saturation limits. Then the control scheme is based on suitable (hybrid) resetting laws allowing the controller to operate on the artificial output signal generated by the open-loop observer when the actual plant output is outside the saturation limits. Unlike existing results, not only we prove uniform global asymptotic stability of the closed loop, but we also prove the local preservation and global recovery properties, typical of model recovery anti-windup paradigms. We also illustrate the proposed technique on an example study.