Distribution by Scientific Domains
Distribution within Life Sciences

Kinds of Clustering

  • achr clustering
  • agglomerative clustering
  • bayesian clustering
  • clear clustering
  • familial clustering
  • geographic clustering
  • hierarchical clustering
  • phylogenetic clustering
  • price clustering
  • receptor clustering
  • significant clustering
  • spatial clustering
  • volatility clustering

  • Terms modified by Clustering

  • clustering algorithm
  • clustering analysis
  • clustering approach
  • clustering method
  • clustering methods
  • clustering pattern
  • clustering procedure
  • clustering process
  • clustering result
  • clustering technique
  • clustering techniques

  • Selected Abstracts


    Silke Jänichen
    Case-based object recognition requires a general case of the object that should be detected. Real-world applications such as the recognition of biological objects in images cannot be solved by one general case. A case base is necessary to handle the great natural variations in the appearance of these objects. In this paper, we will present how to learn a hierarchical case base of general cases. We present our conceptual clustering algorithm to learn groups of similar cases from a set of acquired structural cases of fungal spores. Due to its concept description, it explicitly supplies for each cluster a generalized case and a measure for the degree of its generalization. The resulting hierarchical case base is used for applications in the field of case-based object recognition. We present results based on our application for health monitoring of biologically hazardous material. [source]


    NEPHROLOGY, Issue 1 2002
    McDonald Sp


    Kee H. Chung
    Abstract We analyze market liquidity (i.e., spreads and depths) and quote clustering using data from the Kuala Lumpur Stock Exchange (KLSE), where the tick size increases with share price in a stepwise fashion. We find that stocks that are subject to larger mandatory tick sizes have wider spreads and less quote clustering. We also find that liquidity providers on the KLSE do not always quote larger depths for stocks with larger tick sizes. Overall, our results suggest that larger tick sizes for higher priced stocks are detrimental to market liquidity, although the adverse effect of larger tick sizes is mitigated by lower negotiation costs (i.e., less quote clustering). [source]


    ARCHAEOMETRY, Issue 6 2009
    M. J. BAXTER
    Cluster analysis is widely used in archaeological data analysis. Fuzzy clustering is a more modern technique than methods normally used by archaeologists and has not been much exploited. Applications that have been reported are sometimes unsatisfactory and usually do not exploit the ,fuzziness' of the procedure. After a brief review of the more common methods of cluster analysis, fuzzy ideas and fuzzy clustering are discussed. The method is applied to three data sets of different sizes and complexity, to illustrate particular aspects of, and problems in, application. Summarizing results is less easy than for more standard methods, but has the potential to reveal features of the data concealed by other methods. [source]

    Semi-Automatic Time-Series Transfer Functions via Temporal Clustering and Sequencing

    Jonathan Woodring
    Abstract When creating transfer functions for time-varying data, it is not clear what range of values to use for classification, as data value ranges and distributions change over time. In order to generate time-varying transfer functions, we search the data for classes that have similar behavior over time, assuming that data points that behave similarly belong to the same feature. We utilize a method we call temporal clustering and sequencing to find dynamic features in value space and create a corresponding transfer function. First, clustering finds groups of data points that have the same value space activity over time. Then, sequencing derives a progression of clusters over time, creating chains that follow value distribution changes. Finally, the cluster sequences are used to create transfer functions, as sequences describe the value range distributions over time in a data set. [source]

    Visual Clustering in Parallel Coordinates

    Hong Zhou
    Abstract Parallel coordinates have been widely applied to visualize high-dimensional and multivariate data, discerning patterns within the data through visual clustering. However, the effectiveness of this technique on large data is reduced by edge clutter. In this paper, we present a novel framework to reduce edge clutter, consequently improving the effectiveness of visual clustering. We exploit curved edges and optimize the arrangement of these curved edges by minimizing their curvature and maximizing the parallelism of adjacent edges. The overall visual clustering is improved by adjusting the shape of the edges while keeping their relative order. The experiments on several representative datasets demonstrate the effectiveness of our approach. [source]

    Space-Time Hierarchical Radiosity with Clustering and Higher-Order Wavelets

    Cyrille Damez
    Abstract We address in this paper the issue of computing diffuse global illumination solutions for animation sequences. The principal difficulties lie in the computational complexity of global illumination, emphasized by the movement of objects and the large number of frames to compute, as well as the potential for creating temporal discontinuities in the illumination, a particularly noticeable artifact. We demonstrate how space-time hierarchical radiosity, i.e. the application to the time dimension of a hierarchical decomposition algorithm, can be effectively used to obtain smooth animations: first by proposing the integration of spatial clustering in a space-time hierarchy; second, by using a higher-order wavelet basis adapted for the temporal dimension. The resulting algorithm is capable of creating time-dependent radiosity solutions efficiently. [source]

    Automatic Creation of Object Hierarchies for Radiosity Clustering

    Gordon Müller
    Using object clusters for hierarchical radiosity greatly improves the efficiency and thus usability of radiosity computations. By eliminating the quadratic starting phase very large scenes containing about 100k polygons can be handled efficiently. Although the main algorithm extends rather easily to using object clusters, the creation of ,good' object hierarchies is a difficult task both in terms of construction time and in the way how surfaces or objects are grouped to clusters. The quality of an object hierarchy for clustering depends on its ability to accurately simulate the hierarchy of the energy flow in a given scene. Additionally it should support visibility computations by providing efficient ray acceleration techniques. In this paper we will present a new approach of building hierarchies of object clusters. Our hybrid structuring algorithm provides accuracy and speed by combining a highly optimized bounding volume hierarchy together with uniform spatial subdivisions for nodes with regular object densities. The algorithm works without user intervention and is well suited for a wide variety of scenes. First results of using these hierarchies in a radiosity clustering environment are very promising and will be presented here. The combination of very deep hierarchies (we use a binary tree) together with an efficient ray acceleration structure shifts the computational effort away from form factor and visibility calculation towards accurately propagating the energy through the hierarchy. We will show how an efficient single pass gathering can be used to minimize traversal costs. [source]

    Algorithm for Spatial Clustering of Pavement Segments

    Chientai Yang
    This article formulates a new spatial search model for determining appropriate pavement preservation project termini. A spatial clustering algorithm using fuzzy c-mean clustering is developed to minimize the rating variation in each cluster (project) of pavement segments while considering minimal project scope (i.e., length) and cost, initial setup cost, and barriers, such as bridges. A case study using the actual roadway and pavement condition data in fiscal year 2005 on Georgia State Route 10 shows that the proposed algorithm can identify more appropriate segment clustering scheme, than the historical project termini. The benefits of using the developed algorithm are summarized, and recommendations for future research are discussed. [source]

    Clustering revealed in high-resolution simulations and visualization of multi-resolution features in fluid,particle models

    Krzysztof Boryczko
    Abstract Simulating natural phenomena at greater accuracy results in an explosive growth of data. Large-scale simulations with particles currently involve ensembles consisting of between 106 and 109 particles, which cover 105,106 time steps. Thus, the data files produced in a single run can reach from tens of gigabytes to hundreds of terabytes. This data bank allows one to reconstruct the spatio-temporal evolution of both the particle system as a whole and each particle separately. Realistically, for one to look at a large data set at full resolution at all times is not possible and, in fact, not necessary. We have developed an agglomerative clustering technique, based on the concept of a mutual nearest neighbor (MNN). This procedure can be easily adapted for efficient visualization of extremely large data sets from simulations with particles at various resolution levels. We present the parallel algorithm for MNN clustering and its timings on the IBM SP and SGI/Origin 3800 multiprocessor systems for up to 16 million fluid particles. The high efficiency obtained is mainly due to the similarity in the algorithmic structure of MNN clustering and particle methods. We show various examples drawn from MNN applications in visualization and analysis of the order of a few hundred gigabytes of data from discrete particle simulations, using dissipative particle dynamics and fluid particle models. Because data clustering is the first step in this concept extraction procedure, we may employ this clustering procedure to many other fields such as data mining, earthquake events and stellar populations in nebula clusters. Copyright © 2003 John Wiley & Sons, Ltd. [source]

    Clustering: An Essential Step from Diverging to Converging

    Marc Tassoul
    Within the context of new product development processes and the Creative Problem Solving (CPS) process, the authors have come to the view that clustering is to be seen as a separate step in the process of diverging and converging. Clustering is generally presented as part of the converging stages, and as such categorized as a selection technique, which in the authors' view does not do justice to this activity. It is about expanding knowledge, about connecting ideas, and connecting ideas to problem statements, functionalities, and values and consequences. It is about building a shared understanding, in other words about ,making sense', an essential creative activity in the development of concepts and, although different from a more freewheeling divergent phase, can be as creative and maybe even more so. Four kinds of clusterings are distinguished: object clustering, morphological clustering, functional clustering and gestalt clustering. Object clustering is mainly aimed at categorizing ideas into an overviewable set of groups of ideas. No special connections are being made, other then looking for similarities. Morphological clustering is used to split up a problem into subproblems after which the ideas generated are considered as subsolutions which can then be combined into concepts. Functional clustering is interesting when different approaches can be chosen to answer some question. It permits a more strategic choice to be made. Gestalt clustering is a more synthesis like approach, often with a more metaphoric and artistic stance. Collage is a good example of such clustering. General guidelines for clustering are: use a bottom-up process of emergence; postpone early rationalisations and verbalisations; start grouping ideas on the basis of feeling and intuition; and use metaphoric names to identify clusters. [source]

    The Amiel-Tison neurological assessment at term: Conceptual and methodological continuity in the course of follow-up

    Julie Gosselin
    Abstract The Amiel-Tison Neurological Assessment at Term (ATNAT) is part of a set of three different instruments based on a neuro-maturative framework. By sharing a same methodology and a similar scoring system, the use of these three assessments prevents any rupture in the course of high risk children follow-up from 32 weeks post-conception to 6 years of age. The ATNAT which takes 5 minutes to administer may be used in clinical setting as well as in research. Clustering of severe to mild neuro-cranial signs in the neonatal period permits identification of children who could benefit from early intervention. © 2005 Wiley-Liss, Inc. MRDD Research Reviews 2005;11:34,51. [source]

    Clustering of cardiovascular risk factors with diabetes in Chinese patients: the effects of sex and hyperinsulinaemia

    Z. -R.
    SUMMARY Objective This study was designed to investigate factors which affect the clustering of cardiovascular risk factors with diabetes in Chinese patients. Research Design and Methods: Six hundred and fifty-four patients with diabetes were assessed comprehensively for diabetes complications and cardiovascular risk factors in a metropolitan hospital in Beijing, China. Insulin resistance and secretion were also evaluated by measurement of glucose and insulin levels before and after a meal tolerance test. Results were analysed according to patient groups stratified by the number of cardiovascular risk factors coexisting with diabetes. Results Cardiovascular risk factors were common in Chinese diabetic patients. The clustering of three or more of these factors with diabetes occurred more often than by chance alone and was associated with postprandial hyperinsulinaemia. Patients with a high number of risk factors were more prone to macrovascular events but did not have higher albuminuria. Using the commonly adopted lower threshold for diagnosing obesity and central obesity in women, there were more women with multiple risk factors. However, this disappeared if the same criteria were used for men and women. Even in the presence of diabetes, cardiovascular risk factors were inadequately controlled in most patients. Conclusions The concurrence of diabetes and other cardiovascular risk factors which constitute the metabolic syndrome is a common phenomenon in urban Chinese diabetic patients. It is associated with hyperinsulinaemia and possibly the female sex. This study emphasises the importance of public health measures to control cardiovascular risk factors in patients with diabetes. [source]

    Clustering of cardiovascular risk factors in type 2 diabetes mellitus: prognostic significance and tracking

    J. Kaukua
    Summary Aim Little attention has been paid to the prognostic significance and tracking effect of risk factor clusters characteristic of type 2 diabetes mellitus. We studied the clustering of eight cardiovascular risk factors (smoking, high body mass index, elevated systolic blood pressure, high serum, low density lipoprotein (LDL) cholesterol, high serum LDL triglycerides, low serum, high density lipoprotein (HDL) cholesterol, high fasting blood glucose and high plasma insulin concentration) and their effect on the prognosis and the tracking effect. Methods This study is a population-based prospective follow-up of newly diagnosed type 2 diabetic subjects (n = 133, aged 45,64 years) in Eastern Finland. The following end points were used: all-cause mortality, cardiovascular mortality, and incidences of first myocardial infarction and first stroke. Furthermore, we studied the ,tracking effect' of the risk factor clusters during the 10-year follow-up period. Results When the clustering of risk factors typical of type 2 diabetes mellitus was taken into account, all-cause mortality increased from 28.6% to 50.0% (p <,0.05) and cardiovascular disease mortality increased from 14.3% to 50.0% (p <,0.01) depending on the number of risk factors present. The incidence of first myocardial infarction increased from 0% to 40.0% (p <,0.05) as the number of risk factors increased from 0 to 5. In survivors, the proportion of individuals with no risk factors decreased and the proportion on individuals with three to four risk factors increased during the 10-year follow-up period despite the high mortality among the group with many risk factors. Conclusions The risk factor clusters among type 2 diabetic subjects are of great predictive value and when not aggressively treated, show a relentless increase despite selective mortality. [source]

    Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment

    Nirmal Jayaram
    Abstract Probabilistic seismic risk assessment for spatially distributed lifelines is less straightforward than for individual structures. While procedures such as the ,PEER framework' have been developed for risk assessment of individual structures, these are not easily applicable to distributed lifeline systems, due to difficulties in describing ground-motion intensity (e.g. spectral acceleration) over a region (in contrast to ground-motion intensity at a single site, which is easily quantified using Probabilistic Seismic Hazard Analysis), and since the link between the ground-motion intensities and lifeline performance is usually not available in closed form. As a result, Monte Carlo simulation (MCS) and its variants are well suited for characterizing ground motions and computing resulting losses to lifelines. This paper proposes a simulation-based framework for developing a small but stochastically representative catalog of earthquake ground-motion intensity maps that can be used for lifeline risk assessment. In this framework, Importance Sampling is used to preferentially sample ,important' ground-motion intensity maps, and K -Means Clustering is used to identify and combine redundant maps in order to obtain a small catalog. The effects of sampling and clustering are accounted for through a weighting on each remaining map, so that the resulting catalog is still a probabilistically correct representation. The feasibility of the proposed simulation framework is illustrated by using it to assess the seismic risk of a simplified model of the San Francisco Bay Area transportation network. A catalog of just 150 intensity maps is generated to represent hazard at 1038 sites from 10 regional fault segments causing earthquakes with magnitudes between five and eight. The risk estimates obtained using these maps are consistent with those obtained using conventional MCS utilizing many orders of magnitudes more ground-motion intensity maps. Therefore, the proposed technique can be used to drastically reduce the computational expense of a simulation-based risk assessment, without compromising the accuracy of the risk estimates. This will facilitate computationally intensive risk analysis of systems such as transportation networks. Finally, the study shows that the uncertainties in the ground-motion intensities and the spatial correlations between ground-motion intensities at various sites must be modeled in order to obtain unbiased estimates of lifeline risk. Copyright © 2010 John Wiley & Sons, Ltd. [source]

    Variation in gene content among geographically diverse Sulfolobus isolates

    Dennis W. Grogan
    Summary The ability of competitive (i.e., comparative) genomic hybridization (CGH) to assess similarity across entire microbial genomes suggests that it should reveal diversification within and between natural populations of free-living prokaryotes. We used CGH to measure relatedness of genomes drawn from Sulfolobus populations that had been shown in a previous study to be diversified along geographical lines. Eight isolates representing a wide range of spatial separation were compared with respect to gene-specific tags based on a closely related reference strain (Sulfolobus solfataricus P2). For the purpose of assessing genetic divergence, 232 loci identified as polymorphic were assigned one of two alleles based on the corresponding fluorescence intensities from the arrays. Clustering of these binary genotypes was stable with respect to changes in the threshold and similarity criteria, and most of the groupings were consistent with an isolation-by-distance model of diversification. These results indicate that increasing spatial separation of geothermal sites correlates not only with minor sequence polymorphisms in conserved genes of Sulfolobus (demonstrated in the previous study), but also with the regions of difference (RDs) that occur between genomes of conspecifics. In view of the abundance of RDs in prokaryotic genomes and the relevance that some RDs may have for ecological adaptation, the results further suggest that CGH on microarrays may have advantages for investigating patterns of diversification in other free-living archaea and bacteria. [source]

    Neuroligin-3 is a neuronal adhesion protein at GABAergic and glutamatergic synapses

    Elaine C. Budreck
    Abstract Synaptic adhesion molecules are thought to play a critical role in the formation, function and plasticity of neuronal networks. Neuroligins (NL1,4) are a family of presumptive postsynaptic cell adhesion molecules. NL1 and NL2 isoforms are concentrated at glutamatergic and GABAergic synapses, respectively, but the cellular expression and synaptic localization of the endogenous NL3 and NL4 isoforms are unknown. We generated a panel of NL isoform-specific antibodies and examined the expression, developmental regulation and synaptic specificity of NL3. We found that NL3 was enriched in brain, where NL3 protein levels increased during postnatal development, coinciding with the peak of synaptogenesis. Subcellular fractionation revealed a concentration of NL3 in synaptic plasma membranes and postsynaptic densities. In cultured hippocampal neurons, endogenous NL3 was highly expressed and was localized at both glutamatergic and GABAergic synapses. Clustering of NL3 in hippocampal neurons by neurexin-expressing cells resulted in coaggregation of NL3 with glutamatergic and GABAergic scaffolding proteins. Finally, individual synapses contained colocalized NL2 and NL3 proteins, and coimmunoprecipitation studies revealed the presence of NL1,NL3 and NL2,NL3 complexes in brain extracts. These findings suggest that rodent NL3 is a synaptic adhesion molecule that is a shared component of glutamatergic and GABAergic synapses. [source]

    In vivo UVB irradiation induces clustering of Fas (CD95) on human epidermal cells

    Bo Bang
    Abstract:,In vitro studies with human cell lines have demonstrated that the death receptor Fas plays a role in ultraviolet (UV)-induced apoptosis. The purpose of the present study was to investigate the relation between Fas expression and apoptosis as well as clustering of Fas in human epidermis after a single dose of UVB irradiation. Normal healthy individuals were irradiated with three minimal erythema doses (MED) of UVB on forearm or buttock skin. Suction blisters from unirradiated and irradiated skin were raised, and Fas, FasL, and apoptosis of epidermal cells were quantified by flow cytometry. Clustering of Fas was demonstrated by confocal laser scanning microscopy on cryostat sections from skin biopsies. Soluble FasL in suction blister fluid was quantified by ELISA. Flow cytometric analysis demonstrated increased expression intensity of Fas after irradiation, with 1.6-, 2.2- and 2.7-fold increased median expression at 24, 48 and 72 h after irradiation, respectively (n = 4). Apoptosis was demonstrated by the TUNEL reaction, and the maximum of apoptotic cells was detected at 48 h after irradiation. Double-staining for Fas and TUNEL showed that apoptosis was restricted to the Fas-positive epidermal subpopulation, but there was no correlation between the intensities of Fas expression and TUNEL reaction. Median expression intensity of FasL-positive cells transiently decreased to 0.9- and 0.8-fold of the preirradiation respective level after 24 h and 48 h, respectively, and returned to the respective preirradiation level at 72 h after irradiation (n = 4). Concentrations of soluble FasL in suction blister fluid from UVB-irradiated skin did not differ from those in unirradiated skin (n = 5). Confocal laser scanning microscopy showed a rapid clustering of Fas within 30 min after irradiation. A simultaneous clustering of the adapter signalling protein FADD suggested that Fas clustering has a functional significance. Our results are in accordance with previous findings from in vitro studies, and suggest that Fas is activated in vivo in human epidermis after UVB exposure. [source]

    Structure,activity relationship of the p55 TNF receptor death domain and its lymphoproliferation mutants

    FEBS JOURNAL, Issue 5 2001
    Gert De Wilde
    Upon stimulation with tumor necrosis factor (TNF), the TNF receptor (TNFR55) mediates a multitude of effects both in normal and in tumor cells. Clustering of the intracellular domain of the receptor, the so-called death domain (DD), is responsible for both the initiation of cell killing and the activation of gene expression. To characterize this domain further, TNFR55 DD was expressed and purified as a thioredoxin fusion protein in Escherichia coli. Circular dichroism, steady-state and time-resolved fluorescence spectroscopy were used to compare TNFR55 DD with DDs of the Fas antigen (Fas), the Fas-associating protein with DD (FADD) and p75 nerve growth factor receptor, for which the 3-dimensional structure are already known. The structural information derived from the measurements strongly suggests that TNFR55 DD adopts a similar fold in solution. This prompted a homology modeling of the TNFR DD 3-D structure using FADD as a template. In vivo studies revealed a difference between the two lymphoproliferation (lpr) mutations. Biophysical techniques were used to analyze the effect of changing Leu351 to Ala and Leu351 to Asn on the global structure and its impact on the overall stability of TNFR55 DD. The results obtained from these experiments in combination with the modeled structure offer an explanation for the in vivo observed difference. [source]

    Spreads, Depths, and Quote Clustering on the NYSE and Nasdaq: Evidence after the 1997 Securities and Exchange Commission Rule Changes

    FINANCIAL REVIEW, Issue 4 2002
    Kee H. Chung
    This paper examines liquidity and quote clustering on the NYSE and Nasdaq using data after the two market reforms,the 1997 order,handling rule and minimum tick size changes. We find that Nasdaq,listed stocks exhibit wider spreads and smaller depths than NYSE,listed stocks and stocks with higher proportions of even,eighth and even,sixteenth quotes have wider quoted, effective, and realized spreads on both the NYSE and Nasdaq. This result differs from the findings by Bessembinder (1999, p. 404) that "trade execution costs on Nasdaq in late 1997 are no longer significantly explained by a tendency for liquidity providers to avoid odd,eighth quotations," and "odd,sixteenth avoidance has little relevance for explaining post,reform Nasdaq trading costs." [source]

    Larval fish assemblages along the south-eastern Australian shelf: linking mesoscale non-depth-discriminate structure and water masses

    Abstract We present findings of the first mesoscale study linking larval fish assemblages and water masses along shelf waters off south-eastern Australia (southern Queensland-New South Wales), based on vertical, non-depth discriminate data from surveys in October 2002 and 2003 (spring) and July 2004 (winter). Clustering and ordination were employed to discriminate between larval assemblages and, for the first time, to define water masses from water column temperature frequencies. Surveys yielded 18 128 larval fishes comprising 143 taxa from 96 identifiable families, with small pelagics accounting for 53% of the total. Three major recurrent larval assemblages were identified during the study, each of which matched one of three water masses, namely East Australian Current to the north (EAC; 20.5,23.4°C), Tasman Sea to the south (TAS; 14.8,17.5°C), and mixed EAC,TAS water in between (MIX; 18.3,19.9°C). All three assemblages were present in spring, whereas only EAC and MIX occurred in the more northerly constrained winter survey. Furthermore, boundaries between the EAC, MIX and TAS assemblages were found to be dynamic, with locations shifting temporally and spatially depending on EAC extent. Assemblage composition differed significantly between water masses across surveys, with EAC,TAS being most dissimilar. Such contrast was due to the presence of tropical/temperate taxa in EAC, primarily temperate-associated taxa in TAS, and a combination of EAC,TAS taxa within MIX consistent with the convergence of both waters. Results highlight the strength of employing larval assemblages as indicators of water masses, particularly in view of the potential effect of climate change on spawning habitats of shelf fishes. [source]

    An Approximation for the Rank Adjacency Statistic for Spatial Clustering with Sparse Data

    John Paul Ekwaru
    The rank adjacency statistic D provides a simple method to assess regional clustering. It is defined as the weighted average absolute difference in ranks of the data, taken over all possible pairs of adjacent regions. In this paper the usual normal approximation to the D statistic is found to give inaccurate results if the data are sparse and some regions have tied ranks. Adjusted formulae for the moments of D that allow for the existence of ties are derived. An example of analyses of sparse mortality data (with many regions having no deaths, and hence tied ranks) showed satisfactory agreement between the adjusted formulae and the empirical distribution of the D statistic. We conclude that the D statistic, when used with adjusted moments, provides a valid approximate method to evaluate spatial clustering, even in sparse data situations. [source]

    Power of the Rank Adjacency Statistic to Detect Spatial Clustering in a Small Number of Regions

    John Paul Ekwaru
    The rank adjacency statistic D is a statistical method for assessing spatial autocorrelation or clustering of geographical data. It was originally proposed for summarizing the geographical patterns of cancer data in Scotland (IARC 1985). In this paper, we investigate the power of the rank adjacency statistic to detect spatial clustering when a small number of regions is involved. The investigations were carried out using Monte Carlo simulations, which involved generating patterned/clustered values and computing the power with which the D statistic would detect it. To investigate the effects of region shapes, structure of the regions, and definition of weights, simulations were carried out using two different region shapes, binary and nonhinary weights, and three different lattice structures. The results indicate that in the typical example of considering Canadian total mortality at the electoral district level, the D statistic had adequate power to detect general spatial autocorrelation in twenty-five or more regions. There was an inverse relationship between power and the level of connectedness of the regions, which depends on the weighting function, shape, and arrangement of the regions. The power of the D statistic was also found to compare favorably with that of Moran's I statistic. [source]

    Are transient environmental agents involved in the cause of primary biliary cirrhosis?

    HEPATOLOGY, Issue 4 2009
    Evidence from space, time clustering analysis
    The cause of primary biliary cirrhosis (PBC) is unclear. Both genetic and environmental factors are likely to contribute. Some studies have suggested that one or more infectious agents may be involved. To examine whether infections may contribute to the cause of PBC, we have analyzed for space,time clustering using population-based data from northeast England over a defined period (1987,2003). Space,time clustering is observed when excess cases of a disease are found within limited geographical areas at limited periods of time. If present, it is suggestive of the involvement of one or more environmental components in the cause of a disease and is especially supportive of infections. A second-order procedure based on K -functions was used to test for global space,time clustering using residential addresses at the time of diagnosis. The Knox method determined the spatiotemporal range over which global clustering was strongest. K -function tests were repeated using nearest neighbor thresholds to adjust for variations in population density. Individual space,time clusters were identified using Kulldorff's scan statistic. Analysis of 1015 cases showed highly statistically significant space,time clustering (P < 0.001). Clustering was most marked for cases diagnosed within 1,4 months of one another. A number of specific space,time clusters were identified. In conclusion, these novel results suggest that transient environmental agents may play a role in the cause of PBC. (HEPATOLOGY 2009.) [source]

    Ultrastructural and molecular identification of a Wolbachia endosymbiont in a spider, Nephila clavata

    Hyun Woo Oh
    Abstract Wolbachia -like bacteria were observed in the egg cells of golden orb-weaving spider, Nephila clavata, by means of transmission electron microscopy. The bacteria exhibited the typical morphology of Wolbachia, including three enveloping membranes. Based on the amplification and sequencing of partial 16S rDNA and ftsZ gene, the bacteria were identified as Wolbachia, intracellular, transovarially inherited ,-proteobacteria in invertebrates. Phylogenetic analysis based on 16S rDNA and ftsZ gene sequences invariably indicated that the intracellular bacteria from N. clavata belonged to group A Wolbachia, which were found only from insects. Clustering of Wolbachia from N. clavata with group A Wolbachia indicates that the bacteria were probably transferred horizontally between insects and the spider. [source]

    Spatial clustering of childhood cancer in Great Britain during the period 1969,1993

    Richard J.Q. McNally
    Abstract The aetiology of childhood cancer is poorly understood. Both genetic and environmental factors are likely to be involved. The presence of spatial clustering is indicative of a very localized environmental component to aetiology. Spatial clustering is present when there are a small number of areas with greatly increased incidence or a large number of areas with moderately increased incidence. To determine whether localized environmental factors may play a part in childhood cancer aetiology, we analyzed for spatial clustering using a large set of national population-based data from Great Britain diagnosed 1969,1993. The Potthoff-Whittinghill method was used to test for extra-Poisson variation (EPV). Thirty-two thousand three hundred and twenty-three cases were allocated to 10,444 wards using diagnosis addresses. Analyses showed statistically significant evidence of clustering for acute lymphoblastic leukaemia (ALL) over the whole age range (estimate of EPV = 0.05, p = 0.002) and for ages 1,4 years (estimate of EPV = 0.03, p = 0.015). Soft-tissue sarcoma (estimate of EPV = 0.03, p = 0.04) and Wilms tumours (estimate of EPV = 0.04, p = 0.007) also showed significant clustering. Clustering tended to persist across different time periods for cases of ALL (estimate of between-time period EPV = 0.04, p =0.003). In conclusion, we observed low level spatial clustering that is attributable to a limited number of cases. This suggests that environmental factors, which in some locations display localized clustering, may be important aetiological agents in these diseases. For ALL and soft tissue sarcoma, but not Wilms tumour, common infectious agents may be likely candidates. © 2008 Wiley-Liss, Inc. [source]

    Clustering-based scheduling: A new class of scheduling algorithms for single-hop lightwave networks

    Sophia G. Petridou
    Abstract In wavelength division multiplexing (WDM) star networks, the construction of the transmission schedule is a key issue, which essentially affects the network performance. Up to now, classic scheduling techniques consider the nodes' requests in a sequential service order. However, these approaches are static and do not take into account the individual traffic pattern of each node. Owing to this major drawback, they suffer from low performance, especially when operating under asymmetric traffic. In this paper, a new class of scheduling algorithms for WDM star networks, which is based on the use of clustering techniques, is introduced. According to the proposed Clustering-Based Scheduling Algorithm (CBSA), the network's nodes are organized into clusters, based on the number of their requests per channel. Then, their transmission priority is defined beginning from the nodes belonging to clusters with higher demands and ending to the nodes of clusters with fewer requests. The main objective of the proposed scheme is to minimize the length of the schedule by rearranging the nodes' service order. Furthermore, the proposed CBSA scheme adopts a prediction mechanism to minimize the computational complexity of the scheduling algorithm. Extensive simulation results are presented, which clearly indicate that the proposed approach leads to a significantly higher throughput-delay performance when compared with conventional scheduling algorithms. We believe that the proposed clustering-based approach can be the base of a new generation of high-performance scheduling algorithms for WDM star networks. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    From collagen chemistry towards cell therapy , a personal journey

    Michael E. Grant
    Summary The Fell,Muir Award requires the recipient to deliver a lecture and a review manuscript which provides a personal overview of significant scientific developments in the field of matrix biology over the period of the recipient's career. In this context, this review considers the collagen family of structural proteins and the advances in biochemical, molecular biological and genetic techniques which led to the elucidation of the structure, synthesis and function of this important group of extracellular matrix constituents. Particular attention is focussed on early research on the identification and assembly of the soluble precursors of collagen types I and II, and the identification of the precursor of basement membrane collagen type IV. In subsequent studies investigating the maintenance of the chick chondrocyte phenotype in culture, the influence of the extracellular milieu was found to influence markedly both cell morphology and collagen gene expression. These studies led to the discovery of collagen type X whose expression is restricted to hypertrophic chondrocytes at sites of endochondral ossification. Such research provided a prelude to investigations of mammalian endochondral ossification which is known to be aberrant in a variety of human chondrodysplasias and is reactivated in bone fracture repair and in osteoarthritis. The cloning of bovine and then human collagen type X genes facilitated studies in relevant human diseases and contributed to the discovery of mutations in the COL10A1 gene in families with metaphyseal chondrodysplasia type Schmid. Clustering of mutations in the C-terminal domain of the type X collagen molecule has now been widely documented and investigations of the pathogenic mechanisms in animal models are beginning to suggest the prospect of novel treatment strategies. [source]

    Clustering and switching in semantic fluency: predictors of the development of Alzheimer's disease

    Ana B. Fagundo
    Abstract Objective The aims of the study are twofold: (1) to compare semantic fluency, clustering and switching performance among subjects with memory complaints, patients with Alzheimer Disease (AD), and healthy controls; and (2) to examine the clinical utility of the clustering/switching scoring system in the prediction of incident AD in subjects with memory complaints. Methods A semantic fluency task was used to compare thirty eight subjects with memory complaints, forty two AD patients and twenty five healthy controls on the total number of words generated, clustering and switching performance. Subjects with memory complaints were followed-up for a maximum period of two years and re-evaluated. They remained in the memory complaints group (twenty eight subjects) or were defined as probable AD (ten subjects). Results AD patients generated fewer correct words (p,<,0.001) and showed a reduction in clustering (p,=,0.008) and switching (p,<,0.001). Subjects with memory complaints showed a significant reduction in correct words (p,<,0.001) and clustering performance (p,=,0.008) compare to controls. In the first evaluation, the subgroup of patients who converted to AD at follow up produced less correct words (p,<,0.01) and smaller clusters (p,=,0.007) than the subgroup who did not become demented. There were no differences in switching between these two subgroups. AD development was better predicted by cluster size than by the total number of words generated or by switching. Conclusions Subjects with memory complaints and AD patients have an alteration in both qualitative and quantitative aspects of semantic fluency. A clustering analysis could enhance the reliability of early AD diagnosis. Copyright © 2008 John Wiley & Sons, Ltd. [source]

    A novel clustering algorithm using hypergraph-based granular computing

    Qun Liu
    Clustering is an important technique in data mining. In this paper, we introduce a new clustering algorithm. This algorithm, based on granular computing, constructs a hypergraph (simplicial complex) by the hypergraph bisection algorithm. It will discover the similarities and associations among documents. In some experiments on Web data, the proposed algorithm is used; the results are quite satisfactory. © 2009 Wiley Periodicals, Inc. [source]