Research on Chinese Industrial Cluster Patterns ——Take Haier Household Electrical Appliance as an Example

Industrial cluster is an aggregation of the related enterprises and institutions in certain field and in certain place. There are mainly three patterns for industrial clusters： market-oriented cluster, foreign fund oriented cluster and endogenous brand oriented cluster. Many economists have established their own theories about the patterns industrial cluster, but there are few dealing with one big enterprises and its cluster pattern. This paper, taking Haier household electrical appliance as an example, is trying to study one model of Chinese industrial cluster and analyze its characteristics with their effects on economy, as.well as the advantages together with the related suggestions from the authors.

An Algorithm for Mining Gradual Moving Object Clusters Pattern From Trajectory Streams

The discovery of gradual moving object clusters pattern from trajectory streams allows characterizing movement behavior in real time environment,which leverages new applications and services.Since the trajectory streams is rapidly evolving,continuously created and cannot be stored indefinitely in memory,the existing approaches designed on static trajectory datasets are not suitable for discovering gradual moving object clusters pattern from trajectory streams.This paper proposes a novel algorithm of gradual moving object clusters pattern discovery from trajectory streams using sliding window models.By processing the trajectory data in current window,the mining algorithm can capture the trend and evolution of moving object clusters pattern.Firstly,the density peaks clustering algorithm is exploited to identify clusters of different snapshots.The stable relationship between relatively few moving objects is used to improve the clustering efficiency.Then,by intersecting clusters from different snapshots,the gradual moving object clusters pattern is updated.The relationship of clusters between adjacent snapshots and the gradual property are utilized to accelerate updating process.Finally,experiment results on two real datasets demonstrate that our algorithm is effective and efficient.

Three photosynthetic patterns characterized by cluster analysis of gas exchange data in two rice populations

Plant photosynthetic rate is affected by stomatal status and internal CO2 carboxylation. Understanding which process determines photosynthetic rate is essential for developing strategies for breeding crops with high photosynthetic efficiency. In this study, we identified different physiological patterns of photosynthetic rate in two different rice populations. Photosynthetic gas exchange parameters were measured during the flowering stage in two rice populations. Clustering and correlation analyses were performed on the resulting data. Five or six groups were defined by K-means clustering according to differences in net photosynthetic rates(Pn). According to differences in stomatal conductance(gs) and carboxylation efficiency(CE), each group was clustered into three subgroups characterized by physiological patterns stomatal pattern, carboxylation pattern, and intermediate pattern. Pn was significantly correlated with gs(r = 0.810) and CE(r = 0.531). Pn was also significantly correlated with gs and CE in the three physiological patterns. The correlation coefficients were highest in the stomatal pattern(0.905 and 0.957) and lowest in the carboxylation pattern(0.825 and 0.859). Higher correlation coefficients between Pn and gs or CE in the three physiological patterns indicate that clustering is very important for understanding factors limiting rice photosynthesis. ? 2013 Production and hosting by Elsevier B.V. on behalf of Crop Science Society of

Mapping Diversity of Publication Patterns in the Social Sciences and Humanities: An Approach Making Use of Fuzzy Cluster Analysis

Purpose: To present a method for systematically mapping diversity of publication patterns at the author level in the social sciences and humanities in terms of publication type, publication language and co-authorship.Design/methodology/approach: In a follow-up to the hard partitioning clustering by Verleysen and Weeren in 2016, we now propose the complementary use of fuzzy cluster analysis, making use of a membership coefficient to study gradual differences between publication styles among authors within a scholarly discipline. The analysis of the probability density function of the membership coefficient allows to assess the distribution of publication styles within and between disciplines.Findings: As an illustration we analyze 1,828 productive authors affiliated in Flanders, Belgium. Whereas a hard partitioning previously identified two broad publication styles, an international one vs. a domestic one, fuzzy analysis now shows gradual differences among authors. Internal diversity also varies across disciplines and can be explained by researchers’ specialization and dissemination strategies.Research limitations: The dataset used is limited to one country for the years 2000–2011; a cognitive classification of authors may yield a different result from the affiliation-based classification used here.Practical implications: Our method is applicable to other bibliometric and research evaluation contexts, especially for the social sciences and humanities in non-Anglophone countries.Originality/value: The method proposed is a novel application of cluster analysis to the field of bibliometrics. Applied to publication patterns at the author level in the social sciences and humanities, for the first time it systematically documents intra-disciplinary diversity.

Caries Patterns in the Primary Dentition: Cluster Analysis of a Sample of 5,169 Arizona Children 5-59 Months of Age

Aim Cluster analysis was conducted on data from 5,169 United States （U.S.） Arizona children, age＇s 5-59-months with the goal of delineating patterns of caries in the primary dentition of pre-school children without a priori pattern definitions. Methodology Cluster analyses were conducted using all data for children ages 0-4 years in aggregate： 1） for all subjects, and 2） for subjects without crowned restored teeth. Each of these two sets of analyses consisted of 8 differently specified cluster analyses as a validation procedure. Results The caries patterns identified from the clustering analysis are： 1） smooth surfaces （other than the maxillary incisor）, 2） maxillary incisor, 3） occlusal surfaces of first molars, and 4） pit and fissure surfaces of second molars. Conclusion The cluster analysis findings were consistent with results produced by multidimensional scaling. These cross-validated patterns may represent resulting disease conditions from different risks or the timing of various risk factor exposures. As such, the patterns may be useful case definitions for caries risk factor investigations in children under 60 months of age.

Clustering-Inverse: A Generalized Model for Pattern-Based Time Series Segmentation

Patterned-based time series segmentation (PTSS) is an important task for many time series data mining applications. In this paper, according to the characteristics of PTSS, a generalized model is proposed for PTSS. First, a new inter-pretation for PTSS is given by comparing this problem with the prototype-based clustering (PC). Then, a novel model, called clustering-inverse model (CI-model), is presented. Finally, two algorithms are presented to implement this model. Our experimental results on artificial and real-world time series demonstrate that the proposed algorithms are quite effective.

Cluster analysis on summer precipitation field over Qinghai-Tibet Plateau from 1961 to 2004

The summer day-by-day precipitation data of 97 meteorological stations on the Qinghai-Tibet Plateau from 1961 to 2004 were selected to analyze the temporal-spatial distribution through accumulated variance,correlation analysis,regression analysis,empirical orthogonal function,power spectrum function and spatial analysis tools of GIS.The result showed that summer precipitation occupied a relatively high proportion in the area with less annual precipitation on the Plateau and the correlation between summer precipitation and annual precipitation was strong.The altitude of these stations and summer precipitation tendency presented stronger positive correlation below 2000 m,with correlation value up to 0.604（α=0.01）.The subtracting tendency values between 1961-1983 and 1984-2004 at five altitude ranges（2000-2500 m,2500-3000 m,3500-4000 m,4000-4500 m and above 4500 m）were above zero and accounted for 71.4%of the total.Using empirical orthogonal function, summer precipitation could be roughly divided into three precipitation pattern fields：the Southeast Plateau Pattern Field,the Northeast Plateau Pattern field and the Three Rivers＇ Headstream Regions Pattern Field.The former two ones had a reverse value from the north to the south and opposite line was along 35°N.The potential cycles of the three pattern fields were 5.33a,21.33a and 2.17a respectively,tested by the confidence probability of 90%.The station altitudes and summer precipitation potential cycles presented strong negative correlation in the stations above 4500 m,with correlation value of-0.626（α=0.01）.In Three Rivers Headstream Regions summer precipitation cycle decreased as the altitude rose in the stations above 3500 m and increased as the altitude rose in those below 3500 m.The empirical orthogonal function analysis in June precipitation,July precipitation and August precipitation showed that the June precipitation pattern field was similar to the July＇s,in which southern Plateau was positive and northern Plateau negative.But positive value area in July precipitation pattern field was obviously less than June＇s.The August pattern field was totally opposite to June＇s and July＇s.The positive area in August pattern field jumped from the southern Plateau to the northern Plateau.

Heterotic Classes and Utilization Patterns in Chinese Foxtail Millet [<i>Setaria italica</i>(L.) P. Beauv]

Utilization of heterosis to develop hybrid cultivars can significantly increase yield of most crops including foxtail millet. However, previous foxtail millet hybrid cultivars have been largely developed from crosses between sterile lines and conventional varieties or between sterile lines and varieties that are geographically distent from the sterile lines. The research on classification of heterotic classes and determinetaion of heterotic patterns has not been reported, which results in uncertainty in selection of parents for crosses and delays progress in utilization of high yielding hybrids in large-scale commercial production. In this study, a core collection of 128 accessions from China was grouped into six classes using combined analyses of population structure, pedigree, and clustering. The classification was conducted based mainly on molecular clustering of genotypic data, also considered the population structure and mathematical clustering using phenotypic data, and was finally validated through pedigree analysis. According to the transgressive and superstandard heterosis for grain yield, plant height, panicle length, panicle diameter, single panicle weight, grain weight per panicle, and 1000-grain weight collected from an incomplete-diallel-cross experiment, we identified six superior heterosis patterns (C2/C1, C2/C4, C2/C5, C2/C6, C1/C5 and C4/C5) and four inferior heterosis patterns (C1/C3, C1/C4, C1/C6 and C4/C6), and explored their potential applications in millet hybrid breeding. This study laid a foundation for effective use of foxtail millet heterosis in improving millet hybrid yield.

Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach

Comprehensive and joint applications of GIS and chemometric approach were applied in identification and spatial patterns of coastal water pollution sources with a large data set （5 years （2000-2004）, 17 parameters） obtained through coastal water monitoring of Southern Water Control Zone in Hong Kong. According to cluster analysis the pollution degree was significantly different between September-next May （the 1st period） and June-August （the 2nd period）. Based on these results, four potential pollution sources, such as organic/eutrophication pollution, natural pollution, mineral/anthropic pollution and fecal pollution were identified by factor analysis/principal component analysis. Then the factor scores of each monitoring site were analyzed using inverse distance weighting method, and the results indicated degree of the influence by various potential pollution sources differed among the monitoring sites. This study indicated that hybrid approach was useful and effective for identification of coastal water pollution source and spatial patterns.

Bohai crude oil identification by gas chromatogram fingerprinting quantitative analysis coupled with cluster analysis

By gas chromatogram, six crude oils fingerprinting distributed in four oilfields and four oil platforms were analyzed and the corre- sponding normal paraffin hydrocarbon （ including pristane and phytane） concentration was obtained by the internal standard methed. The normal paraffin hydrocarbon distribution patterns of six crude oils were built and compared. The cluster analysis on the normal paraffin hydrocarbon concentration was conducted for classification and some ratios of oils were used for oils comparison. The results indicated： there was a clear difference within different crude oils in different oil fields and a small difference between the crude oils in the same oil platform. The normal paraffin hydrocarbon distribution pattern and ratios, as well as the cluster analysis on the nomad paraffin hydrocarbon concentration can have a better differentiation result for the crude oils with small difference than the original gas chromatogram.

老年人群慢性病共病模式与失能状况的关联研究:基于四川省抽样调查

背景随着人口老龄化的进展,慢性病共病和失能老年人的数量与日俱增,给社会带来沉重的医疗负担。共病和失能联系紧密,但目前关于共病模式和失能状况的相关性研究较少。目的本研究旨在以四川省为例识别我国老年人群中常见的慢性病共病模式,并从个体层面探讨不同共病模式与失能状况之间的相关性。方法于2022年8—11月采用定额随机抽样方法在四川省抽取501例60岁及以上的老年人群样本,收集其慢性病患病状况、失能状况及一般人口学等信息。通过自组织映射神经网络和K-Means相结合的二次聚类方法,识别老年人群的常见共病模式。基于2021年国家医疗保障局首个《长期护理失能等级评估标准(试行)》判定样本的失能等级,应用逻辑回归模型探究慢性病共病模式与失能等级之间的关系。结果501例样本中,共病患病率为62.3%(312/501),失能率为74.3%(372/501);最终确定6种共病模式:关节炎或风湿病-高血压模式;血脂异常-高血压模式;肾脏疾病-关节炎或风湿病模式;癌症-关节炎或风湿病模式;哮喘-高血压-消化系统疾病模式;情感精神-记忆相关疾病模式。二分类逻辑回归分析结果显示,共病人群的失能风险是无共病人群的6.3倍(OR=6.3,95%CI=3.9~10.3,P<0.05)。多因素多分类逻辑回归分析结果显示,6种共病模式的失能风险均增加(P<0.05);其中情感精神-记忆相关疾病模式的共病人群失能风险最大,是无共病人群的10.7倍(OR=10.7,95%CI=1.7~63.6),其次是癌症-关节炎或风湿病模式(OR=7.8,95%CI=2.4~24.8)。结论四川省老年人共病患病率较高,多种共病模式均与失能的发生显著相关,尤其是情感精神-记忆相关疾病模式和癌症-关节炎或风湿病模式。医疗卫生保健系统应重点关注患有共病的老年群体,基于不同共病模式制定精准有效的长期护理政策和策略,预防延缓失能的发生、发展,提高老年人健康福祉,节约社会医疗卫生资源。

Kernel Generalized Noise Clustering Algorithm

To deal with the nonlinear separable problem, the generalized noise clustering （GNC） algorithm is extended to a kernel generalized noise clustering （KGNC） model. Different from the fuzzy c-means （FCM） model and the GNC model which are based on Euclidean distance, the presented model is based on kernel-induced distance by using kernel method. By kernel method the input data are nonlinearly and implicitly mapped into a high-dimensional feature space, where the nonlinear pattern appears linear and the GNC algorithm is performed. It is unnecessary to calculate in high-dimensional feature space because the kernel function can do it just in input space. The effectiveness of the proposed algorithm is verified by experiments on three data sets. It is concluded that the KGNC algorithm has better clustering accuracy than FCM and GNC in clustering data sets containing noisy data.

诱发台风暴雨型滑坡的降雨阈值研究——以泰顺县为例

在我国东南沿海地区,台风暴雨诱发了大量山体滑坡。建立诱发台风暴雨型滑坡的降雨阈值模型,可为该地区的滑坡预警提供参考依据。基于浙江省泰顺县2007—2022年以来发生的滑坡信息和日降雨量数据,进行了诱发滑坡的台风暴雨事件编目,初步揭示了台风暴雨型滑坡的发育规律和触发降雨特征,通过降雨强度(I)、降雨历时(D)的幂律关系构建了滑坡临界降雨阈值模型,并开展了不同台风降雨雨型的阈值模型对比。结果表明:台风暴雨型滑坡大量发生在与台风登陆方向接近的迎风坡,坡表植被多为乔木和竹林;诱发滑坡的台风降雨一般持续2~3 d,且降雨过程集中,降雨雨型以单峰型为主,总降雨量一般在200 mm以上;台风暴雨诱发滑坡的降雨阈值显著高于一般性的降雨,这种差异与台风降雨模式及大尺度气候环境有关;雨型也会显著影响降雨阈值,随着降雨峰值的后移,阈值逐渐降低,表明台风暴雨型滑坡对长时间降雨后出现的强降雨事件更加敏感。通过降雨阈值模型对9次台风降雨事件是否诱发滑坡进行了预测,预测结果与实际情况比较吻合,证明该模型及研究思路对台汛期东南沿海的滑坡监测预警有较强的参考价值。

Current Global Almond Trade and Its Consumption Patterns Analysis

This article aims to investigate the current situation of the international almond trade and its consumption patterns. Traditionally, almonds are characterized by their good taste and high quality and regarded as an ideal source of several natural health nutrients. At present, the United States is the leading almond producer and exporter in the world, accompanied by Germany, Spain and Japan, the biggest almond importing countries. In order to study almond consumption patterns, two indicators were used in our study, the Food Consumer Location Ratio （FCLR） and the Food Consumer Location Relative Ratio （FCLRR）. Furthermore, to identify the almond consumption groups, we carried out two cluster analyses based on FCLR and FCLRR values, Finally, an analysis of the factors which have an impact on a country＇s almond consumption was conducted. It shows that income level, endowment of resources and tradition as well as dietary habits are key factors that help to shape a country＇s almond consumption pattern.

A systematic method based on statistical pattern recognition for estimating product quality on-line

To avoid the complexity of building mechanistic models by studying the inner nature of the object, a systematic method based on statistical pattern recognition is developed in order to estimate the product quality on-line. The mapping relationship between a feature space and a product quality space can be built by using regression analysis, and in applying clustering analysis the product quality space can be partitioned automatically. Eventually, estimating product quality on-line can be accomplished by sorting the mapped data in the partitioned quality space. A concrete problem is proposed which has a relatively small ratio of training data to input variables. By implementing the method mentioned above, a satisfying result has been achieved. Furthermore, the further question about choosing suitable mapping methods is briefly discussed.

Classification of Masseter Activity Patterns during Chewing in Healthy Young Adults: The Effect of Taste Signals

This study examined the effects of the textural properties and chemical components of foods on masseter activity patterns. Ten healthy young participants (seven men and three women) were asked to chew four gummy candies with different flavors while their masseter activities were recorded by a surface electromyogram. The masseter activity patterns during chewing were analyzed quantitatively using a TP technique, generating three TP values (T25, T50 and T75). The textural analysis included four representative properties, and six sugars and four organic acids were tested in the chemical analysis. The hierarchical cluster analysis classified the T25 and T75 values into four subclusters and classified the T50 values into three subclusters. Two T75 subclusters differed significantly in the combined amounts of the two predominant sugars (sucrose and maltose);however, these T75 subclusters did not differ in their organic acid contents or textural properties. Therefore, sucrose and maltose affect masseter activity patterns during chewing, particularly in the later stage of masseter activity.

碳中和背景下新疆八大产业的集群发展态势与空间格局研究

不断推进“双碳”目标和特色产业发展是新疆经济社会高质量发展的必由之路.因此,基于2011―2021年新疆八大产业的数据,运用探索性空间数据分析法探究了新疆八大产业的集群发展态势和空间格局,并进一步探讨了碳达峰压力的影响效应.研究表明:1)新疆第一产业占比高于全国平均水平,新疆第二、三产业低于全国平均水平;并且,新疆产业结构高级化低于全国平均水平,产业结构合理化略高于全国平均水平.2)新疆八大产业聚集规模逐渐显现,且位于全国前列.3)新疆八大产业在总量、份额、结构和竞争力上均占据主导地位,是促进区域经济社会发展的优势产业.4)在研究期间内,新疆八大产业对就业和经济增长发挥着重要作用,是地区经济社会发展的重要动力.5)碳达峰压力对新疆八大产业集群发展的影响存在显著差异,有效促进了油气生产加工、绿色有机果蔬和新能源新材料产业的集群发展,但对其它产业集群发展的促进作用还未有效发挥.

Nuclear clustering in light neutron-rich nuclei

Clustering is a general phenomenon observed in light nuclei, especially in neutron-rich nuclei in which molecular configurations can be formed with various combinations of valence neutrons. Thus far, many theoretical models have been developed to describe nuclear clustering phenomena. These models are outlined in this review article, with an emphasis on their basic formulations and physical ingredients. In addition, various experimental tools, such as inelastic excitation and decay, transfer reactions, and resonant scattering reactions, have been applied to investigate the cluster structures inside the nucleus. Each tool possesses certain advantages and favorable applications, which are also described. In the case of neutron-rich nuclei, cluster structures may be configured as molecular states that form rotational bands with an extremely large moment of inertia and generate relatively large cluster decay width. The major experimental criteria for the identification of cluster formation are discussed herein.

Scaling up Kernel Grower Clustering Method for Large Data Sets via Core-sets

核栽培者是聚类最近 Camastra 和 Verri 建议的方法的一个新奇的核。它证明为各种各样的数据的好性能关于流行聚类的算法有利地设定并且比较。然而，方法的主要缺点是在处理大数据集合的弱可伸缩能力，它极大地限制它的应用程序。在这份报纸，我们用核心集合建议一个可伸缩起来的核栽培者方法，它是比为聚类的大数据的原来的方法显著地快的。同时，它能处理很大的数据集合。象合成数据集合一样的基准数据集合的数字实验显示出建议方法的效率。方法也被用于真实图象分割说明它的性能。

云南短头熊蜂体色模式多态性地理分布格局

【目的】熊蜂是自然环境中一类重要的传粉昆虫,其体表通常覆盖着颜色鲜亮的体毛,从而形成明显的体色模式。本研究旨在探明云南短头熊蜂Bombus breviceps体色模式多态性的地理分布格局,为熊蜂遗传进化及环境适应性研究提供基础数据。【方法】通过检视2017-2021年在云南和贵州共127个采样点采集的957头短头熊蜂标本[包括雌成蜂898头(蜂王103头、工蜂795头)以及雄成蜂59头],绘制雌、雄成蜂体色模式图,分析体色模式的类型及优势度。基于不同体节的体色组成对体色模式进行系统聚类,基于经纬度0.5°×0.5°单元格内体色类群组成分析云南短头熊蜂体色模式的地理分布格局。【结果】短头熊蜂胸部背板体毛的颜色在黑色、灰黄色和橙黄色间过渡变化,腹部背板体毛颜色有黑色、灰黄色、黄色和深棕色,腹部第1背板体毛均为黄色,黄色体毛由第1背板向后逐节延伸最多至第3背板的整节,第2,3背板的体毛为黄色、黑色或灰黄色,而深棕色体毛由腹部第6背板向前逐节延伸最多至第3背板的下半节;雌成蜂有81种体色模式,其中工蜂有80种,蜂王有13种,其中12种与工蜂相同,雄成蜂有37种体色模式,其中28种与雌成蜂相似。雌成蜂的81种体色模式中,优势体色模式有2种,丰盛体色模式有5种,常见体色模式有10种,稀少体色模式有64种。雌成蜂体色模式可聚为3个体色类群,即:A类群(黑胸棕尾),B-1类群(橙胸黑尾)和B-2类群(橙胸棕尾)。云南短头熊蜂体色模式的地理分布可划分为云南高原西部(Ⅰ)和云南高原东部(Ⅱ)2个大区。Ⅰ区进一步可分为滇中亚热带高原区(Ⅰ1)和滇西南热带低山宽谷区(Ⅰ2);Ⅱ区进一步可分为滇东南亚热带岩溶山地河谷区(Ⅱ1)和滇东北亚热带中山河谷区(Ⅱ2)。A体色类群仅分布于Ⅰ1小区,Ⅰ2小区仅有B-2类群分布,而B-1类群仅分布于Ⅱ区,且同域分布有B-2类群。体色模式多态性高低与分布地经纬度无明显相关性,云南高原中部24.00°-24.50°N,102.50°-103.00°E方格内的体色模式多态性最高,达18种;A体色类群分布地平均海拔[(1951±311)m]极显著高于B-1[(1568±352)m]和B-2[(1556±534)m]类群分布地平均海拔。【结论】云南短头熊蜂体色模式多态性丰富,可划分为3个主要的体色类群,其地理分布与气候区划、地型地貌和土地利用类型相关,地理区划特征明显,同区域内体色模式多态性向优势模式趋同。本研究结果对深入挖掘中国本土熊蜂资源和物种多样性保护具有重要意义,为不同生境利用与发展熊蜂提供技术支撑。