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An Adaptive Hybrid Optimization Strategy for Resource Allocation in Network Function Virtualization

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1617-1636页

作者： Chumei Wen delu zeng School of Mathematics South China University of TechnologyGuangzhou510640China School of Electronic and Information Engineering South China University of TechnologyGuangzhou510640China

With the rapid development of Network Function Virtualization(NFV),the problem of low resource utilizationin traditional data centers is gradually being ***,existing research does not optimize both localand global allocation of resources in data ***,we propose an adaptive hybrid optimization strategy thatcombines dynamic programming and neural networks to improve resource utilization and service quality in *** approach encompasses a service function chain simulation generator,a parallel architecture servicesystem,a dynamic programming strategy formaximizing the utilization of local server resources,a neural networkfor predicting the global utilization rate of resources and a global resource optimization strategy for bottleneck andredundant *** the implementation of our local and global resource allocation strategies,the systemperformance is significantly optimized through simulation.

关键词： NFV resource allocation decision-making optimization service function

Vector bundle constraint for particle swarm optimization and its application to active contour modeling

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Progress in Natural Science:Materials International 2007年第10期17卷 1220-1225页

作者： zeng delu, Zhou Zhiheng and Xie Shengli(College of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China) College of Electronic and Information Engineering South China University of Technology Guangzhou 510641 China

Active contour modeling (ACM) has been shown to be a powerful method in object boundary extraction. In this paper, a new ACM based on vector bundle constraint for particle swarm optimization (VBCPSO-ACM) is proposed. Different from the traditional particle swarm optimization (PSO), in the process of velocity update, a vector bundle is predefined for each particle and velocity update of the particle is restricted to its bundle. Applying this idea to ACM, control points on the contour are treated as particles in PSO and the evolution of the contour is driven by the particles. Meanwhile, global searching is shifted to local searching in ACM by decreasing the number of neighbors and inertia. In addition, the addition and deletion of particles on the active contour make this new model possible for representing the real boundaries more precisely. The proposed VBCPSO-ACM can avoid self-intersection during contour evolving and also extract inhomogeneous boundaries. The simulation results proved its great performance in performing contour extraction.

关键词： boundary extraction active contour modeling particle swarm optimization velocity update vector bundle.

RBF neural network and active circles based algorithm for contours extraction

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Progress in Natural Science:Materials International 2007年第6期17卷 681-686页

作者： Zhou Zhiheng, zeng delu and Xie Shengli(College of Electronic & Information Engineering, South China University of Technology, Guangzhou 510640, China) College of Electronic & Information Engineering South China University of Technology Guangzhou 510640 China

For the contours extraction from the images, active contour model and self-organizing map based approach are popular nowadays. But they are still confronted with the problems that the optimization of energy function will trap in local minimums and the contour evolutions greatly depend on the initial contour selection. Addressing to these problems, a contours extraction algorithm based on RBF neural network is proposed here. A series of circles with adaptive radius and center is firstly used to search image feature points that are scattered enough. After the feature points are clustered, a group of radial basis functions are constructed. Using the pixels’ intensities and gradients as the input vector, the final object contour can be obtained by the predicting ability of the neural network. The RBF neural network based algorithm is tested on three kinds of images, such as changing topology, complicated background, and blurring or noisy boundary. Simulation results show that the proposed algorithm performs contours extraction greatly.

关键词： contours extraction RBF neural network dynamic clustering.

两种变形Zn-Cu-Ti锌合金的组织与性能

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特种铸造及有色合金 2012年第11期32卷 1054-1058页

作者：王艳肖来荣万磊张宏岭曾德露刘峤中南大学材料科学与工程学院中南大学有色金属材料科学与工程教育部重点实验室

采用熔铸、挤压的方法制备了Zn-1.0Cu-0.2Ti(简称ZCT)和Zn-1.0Cu-0.2Ti-0.05Mg(简称ZCTMg)两种变形锌合金,分析了两种合金的相组成,观察了合金的微观组织,测试了合金的拉伸性能和蠕变性能,研究了合金的微观组织和性能之间的关系。结果表... 详细信息

采用熔铸、挤压的方法制备了Zn-1.0Cu-0.2Ti(简称ZCT)和Zn-1.0Cu-0.2Ti-0.05Mg(简称ZCTMg)两种变形锌合金,分析了两种合金的相组成,观察了合金的微观组织,测试了合金的拉伸性能和蠕变性能,研究了合金的微观组织和性能之间的关系。结果表明,ZCT和ZCTMg两种合金均主要由η相、ε相和TiZn15相组成;ZCTMg合金的铸态组织较ZCT有一定细化,挤压态合金的抗拉强度由ZCT的212.35MPa提高到ZCTMg的248.90MPa;ZCTMg合金的抗蠕变性能较ZCT合金有明显提高,合金稳态蠕变速率由ZCT的2.17×10-5s-1降低到ZCTMg的3.68×10-7s-1,晶界上的微纳米级TiZn15相粒子和较大的晶粒是提高合金蠕变性能的主要原因。

关键词： Zn-Cu-Ti合金组织性能拉伸蠕变

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一种基于非参数贝叶斯理论的语音增强算法

厦门大学学报（自然科学版） 2017年第3期56卷 423-428页

作者：吴佳雯刘沁婷曾德炉丁兴号李琳厦门大学信息科学与技术学院福建厦门361005 华南理工大学数学学院广东广州510641

提出一种基于非参数贝叶斯理论的语音增强算法,在稀疏表示的框架下,把字典学习、稀疏系数表示和噪声方差估计融合成一个贝叶斯后验估计的过程,并利用Spike-Slab先验加强稀疏性.首先,将带噪语音分解为干净语音、高斯噪声和残余噪声3个子... 详细信息

提出一种基于非参数贝叶斯理论的语音增强算法,在稀疏表示的框架下,把字典学习、稀疏系数表示和噪声方差估计融合成一个贝叶斯后验估计的过程,并利用Spike-Slab先验加强稀疏性.首先,将带噪语音分解为干净语音、高斯噪声和残余噪声3个子信号,分别对该3种子信号采用不同的先验概率模型表达,接着采用马尔科夫链-蒙特卡洛算法计算出3个模型中每个参数对应的后验概率,最后基于稀疏表示的框架重构出干净语音.实验数据使用NOIZEUS语音库,采用PESQ和SegSNR作为质量评价指标,分别在信噪比为0,5和10dB的高斯白噪声、火车噪声和街道噪声上验证了其可行性,并与多种常用语音增强方法进行对比,发现其在低信噪比非平稳噪声情况下的增强效果更为理想.

关键词：稀疏表示非参数贝叶斯 Spike-Slab先验自适应字典语音增强

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水平热型连铸定向凝固设备研究

特种铸造及有色合金 2014年第5期34卷 510-512页

作者：王彦红肖来荣胡炜曾德露宋宇峰刘峤中南大学材料科学与工程学院中南大学有色金属材料科学与工程教育部重点实验室

设计制造了氩气气氛保护下的水平热型连铸定向凝固设备,该设备将水平连续铸造与定向凝固技术结合起来,集熔炼、保温、净化、凝固于一体,可制备出表面光洁、质量优异的定向凝固线材。介绍了该设备的结构组成、工作原理。

关键词：定向凝固水平热型连铸线材

Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

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Neural Regeneration Research 2025年第1期20卷 159-173页

作者： Man Han Deyang zeng Wei Tan Xingxing Chen Shuyuan Bai Qiong Wu Yushan Chen Zhen Wei Yufei Mei Yan zeng Brain Science and Advanced Technology Institute Wuhan University of Science and TechnologyWuhanHubei ProvinceChina Geriatric Hospital Affiliated to Wuhan University of Science and Technology WuhanHubei ProvinceChina School of Public Health Wuhan University of Science and TechnologyWuhanHubei ProvinceChina

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral *** studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and *** how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress *** this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of *** focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine *** determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic ***,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

关键词： amygdala chronic mild stress chronic social defeat stress corticolimbic system depression hippocampus medial prefrontal cortex nucleus accumbens social stress models ventral tegmental area

Glucocorticoid receptor signaling in the brain and its involvement in cognitive function

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Neural Regeneration Research 2025年第9期20卷 2520-2537页

作者： Chonglin Su Taiqi Huang Meiyu Zhang Yanyu Zhang Yan zeng Xingxing Chen Brain Science and Advanced Technology Institute Hubei Province Key Laboratory of Occupational Hazard Identification and ControlSchool of MedicineWuhan University of Science and TechnologyWuhanHubei ProvinceChina

The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental *** the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an important component of the hypothalamicpituitary-a d renal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and *** glucoco rticoid receptor influences cognitive processes,including glutamate neurotransmission,calcium signaling,and the activation of brain-derived neurotrophic factor-mediated pathways,through a combination of genomic and non-genomic *** interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor,there by affecting the hypothalamic-pituitary-a d renal axis and stress-related cognitive *** appropriate level of glucocorticoid receptor expression can improve cognitive function,while excessive glucocorticoid receptors or long-term exposure to glucoco rticoids may lead to cognitive *** with cognitive impairment-associated diseases,such as Alzheimer's disease,aging,depression,Parkinson's disease,Huntington's disease,stroke,and addiction,often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor *** review provides a comprehensive overview of the functions of the glucoco rticoid receptor in the hypothalamic-pituitary-a d renal axis and cognitive *** emphasizes that appropriate glucocorticoid receptor signaling fa cilitates learning and memory,while its dysregulation can lead to cognitive *** provides clues about how glucocorticoid receptor signaling can be targeted to ove rcome cognitive disability-related disorders.

关键词： brain-derived neurotrophic factor calcium signaling glucocorticoid receptor glucocorticoid glutamate transmission hypothalamic-pituitary-adrenal axis long-term potentiation neurocognitive disorders neuroplasticity stress

Advances in genotypic antimicrobialresistance testing: a comprehensive review

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Science China Life Sciences 2025年第01期 130-143页

作者： Boheng Duan Xianjun zeng Junping Peng Huan Kui College of Nanchang University Department of Imaging The Second Affiliated Hospital of Nanchang University NHC Key Laboratory of Systems Biology of Pathogens National Institute of Pathogen BiologyChinese Academy of Medical Sciences & Peking Union Medical College Key Laboratory of Respiratory Disease Pathogenomics Chinese Academy of Medical Sciences & Peking Union Medical College Key Laboratory of Pathogen Infection Prevention and Control (Ministry of Education) State Key Laboratory of Respiratory Health and MultimorbidityNational Institute of Pathogen BiologyChinese Academy of Medical Sciences & Peking Union Medical College

Antimicrobial resistance(AMR) represents a substantial threat to global public health, complicating the treatment of common infections and leading to prolonged illness and escalated healthcare expenses. To effectively combat AMR, timely and accurate detection is crucial for AMR surveillance and individual-based therapy. Phenotypic antibiotic resistance testing(AST) has long been considered the gold standard in clinical applications, serving as the foundation for clinical AMR diagnosis and optimized therapy. It has significantly contributed to ensuring patients′ health and the development of novel antimicrobials. Despite advancements in automated culture-based AST technologies,inherent limitations impede the widespread use of phenotypic AST in AMR surveillance. Genotypic AST technologies offer a promising alternative option, exhibiting advantages of rapidity, high sensitivity, and specificity. With the continuous advancement and expanding applications of genotypic AST technologies, such as microfluidics, mass spectrometry, and high-resolution melting curve analysis, new vigor has been injected into the development and clinical implementation of genotypic AST technologies. In this narrative review, we discuss the principles, applications, and advancements of emerging genotypic AST methods in clinical settings. The comprehensive review aims to highlight the significant scientific potential of emerging genotypic AST technologies in clinical AMR diagnosis, providing insights to enhance existing methods and explore novel approaches.

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