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Biocatalytic enhancement of laccase immobilized on ZnFe_(2)O_(4) nanoparticles and its application for degradation of textile dyes

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Chinese Journal of Chemical Engineering 2024年第4期68卷 216-223页

作者： yuhang Wei Qingpeng Zhu Weiwei Xie Xinyue Wang Song Li Zhiming Chen School of Chemical and Environmental Engineering Anhui Laboratory of Functional Coordinated Complexes for Materials Chemistry and ApplicationAnhui Polytechnic UniversityWuhu 241000China School of Biology and Food Engineering Anhui Polytechnic UniversityWuhu 241000China

Efficient and convenient treatment of industrial dyeing wastewater is of great significance to guarantee human and animal *** work presented the enhanced catalytic activity at pH 3.0 of laccase immobilized on amino-functionalized ZnFe_(2)O_(4) nanoparticles(ZnFe_(2)O_(4)-laccase)and its application for the degradation of textile *** to the existence of a large number of oxygen vacancies on the surface of the ZnFe_(2)O_(4) nanoparticles,negative ions accumulated on the magnetic carriers,which resulted in a harsh optimal pH value of the ZnFe_(2)O_(4)-*** activity assays revealed that the ZnFe_(2)O_(4)-laccase possessed superior pH and thermal stabilities,excellent reusability,and noticeable organic solvent ***,the ZnFe_(2)O_(4) laccase presented efficient and sustainable degradation of high concentrations of textile *** initial decoloration efficiencies of malachite green(MG),brilliant green(BG),azophloxine,crystal violet(CV),reactive blue 19(RB19),and procion red MX-5B were approximately 99.1%,95.0%,93.3%,87.4%,86.1%,and 85.3%,*** 10 consecutive reuses,the degradation rates of the textile dyes still maintained about 98.2%,92.5%,83.2%,81.5%,79.8%and 65.9%,*** excellent dye degradation properties indicate that the ZnFe_(2)O_(4)-laccase has a technical application in high concentrations of dyestuff treatment.

关键词： ZnFe_(2)O_(4)-laccase Catalytic activity Stability and reusability Degradation of textile dye

An Improved Harris Hawk Optimization Algorithm for Flexible Job Shop Scheduling Problem

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Computers, Materials & Continua 2024年第2期78卷 2337-2360页

作者： Zhaolin Lv Yuexia Zhao Hongyue Kang Zhenyu Gao yuhang Qin College of Systems Engineering National University of Defense TechnologyChangsha410073China College of Information Management Nanjing Agricultural UniversityNanjing210031China Department of Intelligent Supply Chain JD LogisticsBeijing100076China College of Intelligent Science and Technology National University of Defense TechnologyChangsha410073China

Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production *** Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling ***,HHO suffers from premature convergence when solving NP-hard ***,this paper proposes an improved HHO algorithm(GNHHO)to solve the *** introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the *** paper chooses a two-segment encoding mode based on the job and the machine of the *** verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard ***,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s *** optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic ***,it achieves an average increase of 21.50%in the on-time order delivery *** results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.

关键词： Flexible job shop scheduling improved Harris hawk optimization algorithm(GNHHO) premature convergence maximum completion time(makespan)

All-optical complex field imaging using diffractive processors

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Light(Science & Applications) 2024年第6期13卷 1122-1139页

作者： Jingxi Li yuhang Li Tianyi Gan Che-Yung Shen Mona Jarrahi Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA90095USA Bioengineering Department University of CaliforniaLos AngelesCA90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA90095USA

Complex field imaging,which captures both the amplitude and phase information of input optical fields or objects,can offer rich structural insights into samples,such as their absorption and refractive index ***,conventional image sensors are intensity-based and inherently lack the capability to directly measure the phase distribution of a *** limitation can be overcome using interferometric or holographic methods,often supplemented by iterative phase retrieval algorithms,leading to a considerable increase in hardware complexity and computational ***,we present a complex field imager design that enables snapshot imaging of both the amplitude and quantitative phase information of input fields using an intensity-based sensor array without any digital *** design utilizes successive deep learning-optimized diffractive surfaces that are structured to collectively modulate the input complex field,forming two independent imaging channels that perform amplitude-to-amplitude and phase-to-intensity transformations between the input and output planes within a compact optical design,axially spanning~100 *** intensity distributions of the output fields at these two channels on the sensor plane directly correspond to the amplitude and quantitative phase profiles of the input complex field,eliminating the need for any digital image reconstruction *** experimentally validated the efficacy of our complex field diffractive imager designs through 3D-printed prototypes operating at the terahertz spectrum,with the output amplitude and phase channel images closely aligning with our numerical *** envision that this complex field imager will have various applications in security,biomedical imaging,sensing and material science,among others.

关键词： field. utilize collective

Dysfunction of dendritic cells in tumor microenvironment and immunotherapy

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Cancer Communications 2024年第9期44卷 1047-1070页

作者： Jie Chen yuhang Duan Junye Che Jianwei Zhu Jecho Institute Co. LtdShanghaiP.R.China Engineering Research Center of Cell&Therapeutic Antibody Ministry of EducationBeijingP.R.China Shanghai Jiao Tong University School of PharmacyShanghaiP.R.China

Dendritic cells(DCs)comprise diverse cell populations that play critical roles in antigen presentation and triggering immune responses in the ***,several factors impair the immune function of DCs and may promote immune evasion in *** the mechanism of DC dysfunction and the diverse functions of heterogeneous DCs in the tumormicroenvironment(TME)is critical for designing effective strategies for cancer *** applications targeting DCs summarized in this report aim to improve immune infiltration and enhance the biological function of DCs to modulate the TME to prevent cancer cells from evading the immune ***,factors in the TME that induce DC dysfunction,such as cytokines,hypoxic environment,tumor exosomes and metabolites,and co-inhibitory molecules,have been ***,several key signaling pathways involved in DC dysfunction and signal-relevant drugs evaluated in clinical trials were ***,this review provides an overview of current clinical immunotherapies targeting DCs,especially therapies with proven clinical outcomes,and explores future developments in DC immunotherapies.

关键词： DCs immunotherapy dendritic cells dysfunction of DCs tumor microenvironment

A comprehensive review of molecular optimization in artificial intelligence-based drug discovery

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Quantitative Biology 2024年第1期12卷 15-29页

作者： yuhang Xia Yongkang Wang Zhiwei Wang Wen Zhang School of Information Huazhong Agricultural UniversityWuhanChina

Drug discovery is aimed to design novel molecules with specific chemical properties for the treatment of targeting diseases. Generally, molecular optimization is one important step in drug discovery, which optimizes the physical and chemical properties of a molecule. Currently, artificial intelligence techniques have shown excellent success in drug discovery, which has emerged as a new strategy to address the challenges of drug design including molecular optimization, and drastically reduce the costs and time for drug discovery. We review the latest advances of molecular optimization in artificial intelligence-based drug discovery, including data resources, molecular properties, optimization methodologies, and assessment criteria for molecular optimization. Specifically, we classify the optimization methodologies into molecular mapping-based, molecular distribution matching-based, and guided search-based methods, respectively, and discuss the principles of these methods as well as their pros and cons. Moreover, we highlight the current challenges in molecular optimization and offer a variety of perspectives, including interpretability, multidimensional optimization, and model generalization, on potential new lines of research to pursue in future. This study provides a comprehensive review of molecular optimization in artificial intelligence-based drug discovery, which points out the challenges as well as the new prospects. This review will guide researchers who are interested in artificial intelligence molecular optimization.

关键词： artificial intelligence drug discovery molecular optimization

微反应器内丁基橡胶溶液法制备体系的反应特性研究

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化工学报 2021年第2期72卷 1001-1008页

作者：何宇航刘晴捷吕阳成清华大学化学工程系化学工程联合国家重点实验室北京100084

研究了微反应器内丁基橡胶溶液法制备体系的反应规律。结果表明以H2O为质子源、EtAlCl2为共引发剂时,控制反应温度为-60℃、水含量在0(control)到0.27 mmol/L之间,可在分钟级时间内高转化率地得到数均分子量高于300000的聚异丁烯产品,... 详细信息

研究了微反应器内丁基橡胶溶液法制备体系的反应规律。结果表明以H2O为质子源、EtAlCl2为共引发剂时,控制反应温度为-60℃、水含量在0(control)到0.27 mmol/L之间,可在分钟级时间内高转化率地得到数均分子量高于300000的聚异丁烯产品,此时链转移得到有效抑制,强化反应物料的初始混合对提升产品质量有利;引入异戊二烯会显著降低产物分子量和转化速度,可以通过使用酸性更弱的Et2AlCl代替EtAlCl2来稳定碳阳离子,抑制链转移,在-60℃下得到数均分子量接近150000的共聚产物,但反应速度缓慢,需要进一步优化和控制反应体系中的水含量来强化该过程。

关键词：丁基橡胶溶液聚合微反应器阳离子聚合制备聚合物

Ballistic performance of spaced multi-ply soft fabrics: Experimental and numerical investigation

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Defence Technology（防务技术） 2024年第4期34卷 143-155页

作者： Zhongwei Zhang Xiaoning Yang Yuan Lin Ziming Xiong yuhang Xiang Yi Zhou Mingyang Wang State Key Laboratory of Explosion&Impact and Disaster Prevention&Mitigation Army Engineering University of PLANanjing 210007China School of Mechanical Engineering Nanjing University of Science&TechnologyNanjing 210007China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200China Postdoctoral Station of Civil Engineering Army Engineering University of PLANanjing 210007China

It has been reported that the ply gap influences the ballistic resistance of spaced multi-ply fabric systems,but its working mechanism was not well-understood. This paper reports the experimental and numerical approaches and results of an investigation on the mechanisms that enable the improved ballistic performance of spaced multi-ply systems. Penetration tests were performed over a range of impact velocities ranging from 200 m/s to 400 m/s. The results confirmed that the ply gap is beneficial to the energy absorption capability of the systems. This is because the front plies tend to absorb more energy when they are not immediately constrained by the rear plies. During a ballistic event, the gap relieves the reflection of the compressive pulse, prolonging the projectile engagement time with the front plies;on the other hand, the rear plies become increasingly less active in dissipating energy as the gap *** the gap is sufficiently widened to avoid any interference between the plies before the failure of the front ply, the responses of the whole system no longer vary. It was also found that the ballistic performance of the spaced systems is influenced by ply thickness, impact velocity, and the stacking order of the ply gap.

关键词： Energy absorption capability Ply gap Ballistic performance The front ply The rear ply

Research on the identification of the production origin of Angelica dahurica using LIBS technology combined with machine learning algorithms

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Optoelectronics Letters 2024年第3期20卷 171-176页

作者： SUN Jiaxing LI Honglian YAO yuhang YAN Qiongyan DONG Fang College of Quality and Technology Supervising Hebei UniversityBaoding 071000China National and Local Joint Engineering Center of Measuring Instruments and Metrology Systems Baoding 071000China Key Laboratory of Energy Measurement and Safety Detection Technology in hebei Province Baoding 071000China

The origin of Angelica dahurica medicinal herbs varies, and their pharmacological effects also differ. In order to achieve rapid and accurate identification of the origin of Angelica dahurica medicinal herbs, this study utilizes laser induced breakdown spectroscopy(LIBS) technology combined with machine learning algorithms to identify the original source of Angelica dahurica. Sliced samples of Angelica dahurica were taken from four regions: hebei, henan, Zhejiang, and Sichuan. The spectral data from the sliced samples were used as features, and different algorithms including support vector machine(SVM), back propagation(BP) neural network, genetic algorithm-back propagation(GA-BP) neural network, particle swarm optimization-back propagation(PSO-BP) neural network, convolutional neural network(CNN), and CNN-SVM were employed to classify the origin of Angelica dahurica samples.

关键词： neural origin network

Channel-Feedback-Free Transmission for Downlink FD-RAN:A Radio Map Based Complex-Valued Precoding Network Approach

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China Communications 2024年第4期21卷 10-22页

作者： Zhao Jiwei Chen Jiacheng Sun Zeyu Shi yuhang Zhou Haibo Xuemin(Sherman)Shen School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310058China Department of Mathematics and Theories Peng Cheng LaboratoryShenzhen 518000China Department of Electrical and Computer Engineering University of WaterlooWaterlooOntarioN2L 3G1Canada

As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(FD-RAN),has emerged for more flexible spectrum resource utilization and lower network ***,with the decoupling of uplink base stations and downlink base stations in FDRAN,the traditional transmission mechanism,which relies on real-time channel feedback,is not suitable as the receiver is not able to feedback accurate and timely channel state information to the *** paper proposes a novel transmission scheme without relying on physical layer channel ***,we design a radio map based complex-valued precoding network(RMCPNet)model,which outputs the base station precoding based on user *** comprises multiple subnets,with each subnet responsible for extracting unique modal features from diverse input ***,the multimodal embeddings derived from these distinct subnets are integrated within the information fusion layer,culminating in a unified *** also develop a specific RMCPNet training algorithm that employs the negative spectral efficiency as the loss *** evaluate the performance of the proposed scheme on the public DeepMIMO dataset and show that RMCPNet can achieve 16%and 76%performance improvements over the conventional real-valued neural network and statistical codebook approach,respectively.

关键词： beamforming complex neural networks deep learning FD-RAN