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Journal of Clinical and Nursing Research 2024年第9期8卷 47-52页

作者： jianming wei Yu Li Li Zhang Rui Wang Lu Chen Jiaojiao Zhao Jia Li Department of Dermatology the Fifth Medical Center of PLA General HospitalBeijing 100071China Department of Dermatology the First Medical Center of PLA General HospitalBeijing 100853China

Objective:To explore the clinical efficacy and safety of Chuzhi Shengfa tablets combined with finasteride in the treatment of male androgenetic alopecia(AGA).Methods:Sixty male patients with androgenetic alopecia admitted to our Department of Dermatology between January 2022 and January 2024 were randomly divided into two groups,with 30 patients in each *** control group was treated with finasteride,while the observation group received a combination of Chuzhi Shengfa tablets and *** clinical efficacy and adverse reactions in both groups were ***:The overall effectiveness rate in the observation group was 93.33%(28/30),significantly higher than the control group’s 73.33%(22/30),with a statistically significant difference(P0.05).Conclusion:The combination of Chuzhi Shengfa tablets and finasteride shows good clinical efficacy in treating male androgenetic ***,Chuzhi Shengfa tablets are convenient to administer and effectively improve efficacy,significantly improving patients’conditions,and demonstrating good clinical application value.

关键词： Chuzhi Shengfa tablets Finasteride Androgenetic alopecia

Effectiveness of Chuzhi Shengfa Tablets Combined with Ketoconazole Shampoo and Chuzhi Shengfa Tablets Combined with 5%Minoxidil Foam in the Treatment of Male Androgenetic Alopecia

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Journal of Clinical and Nursing Research 2024年第9期8卷 201-207页

Objective:To investigate the clinical efficacy and safety of Chuzhi Shengfa Tablets combined with ketoconazole shampoo and Chuzhi Shengfa Tablets combined with 5%minoxidil foam in the treatment of male androgenetic ***:From July 2022 to July 2023,120 male patients with androgenetic alopecia were selected from our Department of Dermatology and randomly divided into Control Group 1,Control Group 2,Observation Group 1,and Observation Group 2,with 30 patients in each *** Group 1 was treated with ketoconazole shampoo,Control Group 2 with 5%minoxidil foam,Observation Group 1 with ketoconazole shampoo combined with Chuzhi Shengfa Tablets,and Observation Group 2 with 5%minoxidil foam combined with Chuzhi Shengfa *** density,hair diameter,scalp oil secretion(using oil secretion scoring),and adverse reactions were compared before and after treatment across the four ***:After treatment,hair density and hair diameter significantly increased in all four groups compared to before treatment,while scalp oil secretion scores significantly decreased(P0.05).Conclusion:Chuzhi Shengfa Tablets combined with ketoconazole shampoo and Chuzhi Shengfa Tablets combined with 5%minoxidil foam are both effective and safe for treating male androgenetic *** combinations can significantly improve hair growth and are worthy of clinical promotion.

关键词： Chuzhi Shengfa Tablets Ketoconazole shampoo Minoxidil foam Male Androgenetic alopecia

番茄褐色皱纹果病毒(ToBRFV)研究进展

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园艺学报 2024年第2期51卷 439-452页

作者：韦建明黄鑫李云洲梁燕贵州大学农学院贵阳550025 西北农林科技大学园艺学院陕西杨凌712100

番茄褐色皱纹果病毒(tomato brown rugose fruit virus,ToBRFV)为帚状病毒科(Virgaviridae)烟草花叶病毒属(Tobamovirus)RNA病毒,可侵染包括番茄在内的多个科属植物,严重威胁安全生产。ToBRFV于2014年首次在以色列发现,随后蔓延至多个... 详细信息

番茄褐色皱纹果病毒(tomato brown rugose fruit virus,ToBRFV)为帚状病毒科(Virgaviridae)烟草花叶病毒属(Tobamovirus)RNA病毒,可侵染包括番茄在内的多个科属植物,严重威胁安全生产。ToBRFV于2014年首次在以色列发现,随后蔓延至多个国家和地区。2021年4月中国将该病毒列为检疫性病毒。本文中对该病毒的基因组结构、寄主范围、发病症状、传播方式、检测方法、寄主抗性以及防御措施等的研究进展进行了归纳总结,以期为防控和抗ToBRFV育种提供参考和借鉴。

关键词：番茄番茄褐色皱纹果病毒抗病育种

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水下连续发射弹体干扰特性及发射时序优化

兵工学报 2024年第1期45卷 197-205页

作者：刘方肖金石韦建明张志洋王聪海军工程大学兵器工程学院湖北武汉430033 哈尔滨工业大学航天学院黑龙江哈尔滨150001

随着对饱和攻击需求的提高,潜艇连续发射过程的发射时序协调控制研究变得迫切而紧要。考虑到弹体间的流体动力干扰是影响安全发射的主要因素,基于重叠网格多自由度仿真技术,针对连续发射的水下弹体开展姿态弹道干扰特性研究。通过分析... 详细信息

随着对饱和攻击需求的提高,潜艇连续发射过程的发射时序协调控制研究变得迫切而紧要。考虑到弹体间的流体动力干扰是影响安全发射的主要因素,基于重叠网格多自由度仿真技术,针对连续发射的水下弹体开展姿态弹道干扰特性研究。通过分析流场结构发现,以一定攻角发射的弹体形成的发卡形尾涡是造成后续弹体姿态弹道差异的主要原因。根据不同艇速、时间间隔和空间间隔下弹体间的干扰特性建立干扰评价模型。在保证干扰不影响后续弹体的前提下,以最短发射时长为目标,以综合评价函数为约束,基于改进的贪心算法对大筒多弹式布局的水下弹体开展发射时序优化研究,并采用均匀抽样方法验证优化结果准确性。研究结果表明:相对于均匀抽样方法,改进的贪心算法具有相当的计算准确度和更高的计算效率。

关键词：水下弹体连续发射姿态干扰评价发射时序

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An Exploration on Adaptive Iterative Learning Control for a Class of Commensurate High-order Uncertain Nonlinear Fractional Order Systems

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 618-627页

作者： jianming wei Youan Zhang Hu Bao School of Weaponry Engineering Naval University of Engineering College of Engineering Yantai Nanshan University Aeronautical College Yantai Nanshan University

This paper explores the adaptive iterative learning control method in the control of fractional order systems for the first time. An adaptive iterative learning control(AILC) scheme is presented for a class of commensurate high-order uncertain nonlinear fractional order systems in the presence of *** facilitate the controller design, a sliding mode surface of tracking errors is designed by using sufficient conditions of linear fractional order systems. To relax the assumption of the identical initial condition in iterative learning control(ILC), a new boundary layer function is proposed by employing MittagLeffler function. The uncertainty in the system is compensated for by utilizing radial basis function neural network. Fractional order differential type updating laws and difference type learning law are designed to estimate unknown constant parameters and time-varying parameter, respectively. The hyperbolic tangent function and a convergent series sequence are used to design robust control term for neural network approximation error and bounded disturbance, simultaneously guaranteeing the learning convergence along iteration. The system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapnov-like composite energy function(CEF)containing new integral type Lyapunov function, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.

关键词： Index Terms-Adaptive iterative learning control (AILC) boundary layer function composite energy function (CEF) frac-tional order differential learning law fractional order nonlinearsystems Mittag-Leffler function.

Multiple vehicle signals separation based on particle filtering in wireless sensor network

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Journal of Systems Engineering and Electronics 2008年第3期19卷 440-446页

作者： Yah Kai Huang Qi wei jianming Liu Haitao Shanghai Inst. of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 P. R. China

A novel statistical method based on particle filtering is presented for multiple vehicle acoustic signals separation problem in wireless sensor network. The particle filtering method is able to deal with non-Gaussian and nonlinear models and non-stationary sources. Using some instantaneously mixed observations of several real-world vehicle acoustic signals, the proposed statistical method is compared with a conventional non-stationary Blind Source Separation algorithm and attractive simulation results are achieved. Moreover, considering the natural convenience to transmit particles between sensor nodes, the algorithm based on particle filtering is believed to have potential to enable the task of multiple vehicles recognition collaboratively performed by sensor nodes in distributed wireless sensor network.

关键词： wireless sensor network Bayesian source separation particle filtering sequential Monte Carlo.

Trifocal tensor based side information generation for multi-view distributed video code

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High Technology Letters 2010年第3期16卷 268-273页

作者： Lin Xin Liu Haitao wei jianming Key Laboratory of Wireless Sensor Networks and Communication Shanghai Institute of Micro System and Information Technology Chinese Academy of Sciences Shanghai 200050 P.R. China School of Technical Shanghai Jiao Tong University Shanghai 201101 P.R. China

Distributed video coding （DVC） is a new video coding approach based on Wyner-Ziv theorem. The novel uplink-friendly DVC, which offers low-complexity, low-power consuming, and low-cost video encoding, has aroused more and more research interests. In this paper a new method based on multiple view geometry is presented for spatial side information generation of uncalibrated video sensor network. Trifocal tensor encapsulates all the geometric relations among three views that are independent of scene structure; it can be computed from image correspondences alone without requiring knowledge of the motion or calibration. Simulation results show that trifocal tensor-based spatial side information improves the rate-distortion performance over motion compensation based interpolation side information by a maximum gap of around 2dB. Then fusion merges the different side information （temporal and spatial） in order to improve the quality of the final one. Simulation results show that the rate-distortion gains about 0.4 dB.

关键词： multi-view distributed video coding (DVC) camera sensor networks trifocal tensor side information

Adaptive repetitive learning control for trajectory-keeping of satellite formation flying

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Journal of Control and Decision 2014年第4期1卷 317-331页

作者： Yunan Hu jianming wei Meimei Sun Department of Control Engineering Naval Aeronautical Engineering InstituteYantaiP.R.China

An adaptive repetitive control scheme is proposed for trajectory-keeping of satellite formation flying in the leader–follower mode which is described by Lawden *** system is parameterised by power series approximation and the unknown timevarying parameters are estimated by adaptive repetitive learning *** rigorous analysis by constructing a Lyapunov-like composite energy function(CEF),the stability of the closed-loop system is ***,a simulation example is provided to illustrate the effectiveness of the control algorithms proposed in this paper.

关键词： satellite formation flying trajectory-keeping adaptive repetitive learning control

Adaptive Iterative Learning Control for a Class of Nonlinear Time-varying Systems with Unknown Delays and Input Dead-zone

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IEEE/CAA Journal of Automatica Sinica 2014年第3期1卷 302-314页

作者： jianming wei Yunan Hu Meimei Sun the Department of Control Engineering Naval Aeronautical Engineering Institute

This paper presents an adaptive iterative learning control(AILC) scheme for a class of nonlinear systems with unknown time-varying delays and unknown input dead-zone.A novel nonlinear form of dead-zone nonlinearity is *** assumption of identical initial condition for iterative learning control(ILC) is removed by introducing boundary layer *** uncertainties with time-varying delays are compensated for by using appropriate Lyapunov-Krasovskii functional and Young’s *** basis function neural networks are used to model the time-varying *** hyperbolic tangent function is employed to avoid the problem of *** to the property of hyperbolic tangent function,the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function(CEF) in two cases,while keeping all the closedloop signals ***,a simulation example is presented to verify the effectiveness of the proposed approach.

关键词： Time-varying systems Delays Adaptive systems Learning (artificial intelligence) Nonlinear systems Trajectory Iterative methods

Efficient Multi-User for Task Offloading and Server Allocation in Mobile Edge Computing Systems

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China Communications 2022年第7期19卷 226-238页

作者： Qiuming Liu Jing Li jianming wei Ruoxuan Zhou Zheng Chai Shumin Liu School of Software Engineering Jiangxi University of Science and TechnologyNanchang 330013China Nanchang Key laboratory of Virtual Digital Factory and Cultural Communications Nanchang 330013China

Mobile edge computing has emerged as a new paradigm to enhance computing capabilities by offloading complicated tasks to nearby cloud *** conserve energy as well as maintain quality of service,low time complexity algorithm is proposed to complete task offloading and server *** this paper,a multi-user with multiple tasks and single server scenario is considered for small network,taking full account of factors including data size,bandwidth,channel state ***,we consider a multi-server scenario for bigger network,where the influence of task priority is taken into *** jointly minimize delay and energy cost,we propose a distributed unsupervised learning-based offloading framework for task offloading and server *** exploit a memory pool to store input data and corresponding decisions as key-value pairs for model to learn to solve optimization *** further reduce time cost and achieve near-optimal performance,we use convolutional neural networks to process mass data based on fully connected *** results show that the proposed algorithm performs better than other offloading schemes,which can generate near-optimal offloading decision timely.

关键词： distributed unsupervised learning energy efficiency mobile edge computing task offloading