试谈第二轮县(市)志公、检、法部类存在问题与解决办法

已出版的第二轮县(市)志公、检、法部类主要存在事物归属不当、内容与首轮志书不承接、部门志痕迹明显、缺少以事系人4个方面问题。解决这些问题需要做到:设置合理篇目、承接首轮志书、消除部门志痕迹;记述资料全面、系统、完整;记述内容应该承接首轮门类,在继承中实现创新。创新内容主要有3个方面:反映时代特色、地方特点;显示公安、司法干警风采;体现对确保经济体制改革成果、促进地方经济发展的作用。

论我国行政法体系发展的历史及法典化时代的来临

回顾我国行政法体系发展的历程,我国行政法体系主要经历了以行政组织法典则的制定为标志的起步阶段,以《行政诉讼法》的颁布为标志的初步形成阶段,以《立法法》的制定为标志的迅速发展阶段,以行政六法概念形成和全部到位为标志的相对有形阶段,以2014年依法治国的顶层设计为标志的瑕疵反思阶段,以及以《民法典》颁布为标志的成为热点阶段。我国目前的行政法体系状况主要呈现为有法群而无法群之引领,有法圈而无清晰边缘,有法阶而无严格位次,有法域而无准确部类。我国行政法体系的不完整性体现在相关典则缺失、典则颁布不平衡、规范错位、总则和分则关系不明、未形成公法闭环系统等方面。虽然来自公法相对滞后、诸国的立法经验、与政治关系密切、理论认知等方面的制约因素使我国行政法体系难以形成。然而,受《民法典》颁布、国家治理现代化、法治体系完整化、公法周延性以及行政法学理逐渐成熟等趋势的影响,我国行政法法典化已经是众望所归。因此,我国行政法的法典化应当通过对法治行政顶层设计的行政法文件进行梳理,对单行行政法规范完善,对部门行政法充实,对宪法延伸,对行政法部类划分,以及对行政法典总则构造的进路予以促成。

部类编排法应成为方志编纂学的一个基本原则——关于综合性方志部类设置的实践与思考

修志史上无所谓部类编排法,但类似部类设置的现象早已有之。在中华人民共和国成立后的两轮综合性新方志编修中,以部类谋篇布局是广泛采取并普遍认可的重要方法,这既是社会实践进程不断深化和现代科学迅速发展的必然要求和反映,也符合加强志书整体性和志书内容有机联系的发展趋势,因此部类编排法应成为方志编纂学的一个基本原则。确定部类范畴要遵循科学性、现实性、可行性三大依据,划分部类内容应坚持致用性、时代性、权威性、严谨性、包容性、开放性六大原则,实践中可借鉴六大部类、八大部类、十大部类三种参考模型,灵活运用基本原则,根据不同地情特点作出各自不同的取舍。

Response of fuzzy clustering on different threshold determination algorithms in spectral change vector analysis over Western Himalaya, India

Abstract： Change detection is a standard tool to extract and analyze the earth＇s surface features from remotely sensed data. Among the different change detection techniques, change vector analysis （CVA） have an exceptional advantage of discriminating change in terms of change magnitude and vector direction from multispectral bands. The estimation of precise threshold is one of the most crucial task in CVA to separate the change pixels from unchanged pixels because overall assessment of change detection method is highly dependent on selected threshold value. In recent years, integration of fuzzy clustering and remotely sensed data have become appropriate and realistic choice for change detection applications. The novelty of the proposed model lies within use of fuzzy maximum likelihood classification （FMLC） as fuzzy clustering in CVA. The FMLC based CVA is implemented using diverse threshold determination algorithms such as double-window flexible pace search （DFPS）, interactive trial and error （T＆E）, and 3x3-pixel kernel window （PKW）. Unlike existing CVA techniques, addition of fuzzy clustering in CVA permits each pixel to have multiple class categories and offers ease in threshold determination process. In present work, the comparative analysis has highlighted the performance of FMLC based CVA overimproved SCVA both in terms of accuracy assessment and operational complexity. Among all the examined threshold searching algorithms, FMLC based CVA using DFPS algorithm is found to be the most efficient method.

The Flying Geese Paradigm:Industrial Upgrade Strategy and Balanced Regional Development

On the basis of competency-based comparative advantage theory and reclassification of industries,this paper has discussed whether the FGP-type industry upgrade has taken place across different regions of China and whether China is able to transcend the middle-income trap through the FGP-type industry upgrade.This paper has discovered that no matter by traditional method of industry classification or the new method of industry classification,China has already experienced the FGP-type industry upgrade and entered into the second stage of this process.While relocating industries to central and western regions,China's eastern region does not have clear directions of industry upgrade of its own.Through analysis on the evolution of comparative advantages across regions,this paper has also discovered that in the process of the FGP industry upgrade,China is facing the risk of falling into comparative advantage trap.These factors are unfavorable to China's implementation of the FGP-type industry upgrade strategy,prevention of the comparative advantage interruptions that may confront middle-income countries and achievement of balanced regional development.

Tracking of human head with particle filter

To cope with the problem of tracking a human head in a complicated scene,we propose a method that adopts human skin color and hair color integrated with a kind of particle filter named condensation algorithm.Firstly,a novel method is presented to set up human head color model using skin color and hair color separately based on region growing.Compared with traditional human face model,this method is more precise and works well when human turns around and the face disappears in the image.Then a novel method is presented to use color model in condensation algorithm more effectively.In this method,a combination of edge detection result,color segmentation result and color edge detection result in an Omega window is used to measure the scale and position of human head in condensation.Experiments show that this approach can track human head in complicated scene even when human turns around or the distance of tracking a human head changes quickly.

Anti-promastigote Activity of the Amazon Plants

This study evaluated in vitro activity of ethanol extract, fractions, and isolated substance from Amazon species against promastigotes of L. amazonensis. The ethanol extracts were concentrated and fractionation. The anti-promastigote activity was evaluated through the cell viability assessment method （MTT）. The ethanol extract, fractions, and isolated substance from Himatanthus articulatus and Parahancorniafasciculata were inactive in promastigote ofL. amazonensis, as the ethanol extract ofPhysalis angulata. The hexane fractions from different parts ofMontrichardia linifera showed anti-promastigote activity probably due to the presence of steroids and terpenes. All species in studies were inactive, except ofM. linifera. The few polar constituents can be responsible for the activity. Therefore, the isolation and purification of the active on L. amazonensis promastigotes are urgently required.

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley's Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.