501 research outputs found

    Performance comparison of point and spatial access methods

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    In the past few years a large number of multidimensional point access methods, also called multiattribute index structures, has been suggested, all of them claiming good performance. Since no performance comparison of these structures under arbitrary (strongly correlated nonuniform, short "ugly") data distributions and under various types of queries has been performed, database researchers and designers were hesitant to use any of these new point access methods. As shown in a recent paper, such point access methods are not only important in traditional database applications. In new applications such as CAD/CIM and geographic or environmental information systems, access methods for spatial objects are needed. As recently shown such access methods are based on point access methods in terms of functionality and performance. Our performance comparison naturally consists of two parts. In part I we w i l l compare multidimensional point access methods, whereas in part I I spatial access methods for rectangles will be compared. In part I we present a survey and classification of existing point access methods. Then we carefully select the following four methods for implementation and performance comparison under seven different data files (distributions) and various types of queries: the 2-level grid file, the BANG file, the hB-tree and a new scheme, called the BUDDY hash tree. We were surprised to see one method to be the clear winner which was the BUDDY hash tree. It exhibits an at least 20 % better average performance than its competitors and is robust under ugly data and queries. In part I I we compare spatial access methods for rectangles. After presenting a survey and classification of existing spatial access methods we carefully selected the following four methods for implementation and performance comparison under six different data files (distributions) and various types of queries: the R-tree, the BANG file, PLOP hashing and the BUDDY hash tree. The result presented two winners: the BANG file and the BUDDY hash tree. This comparison is a first step towards a standardized testbed or benchmark. We offer our data and query files to each designer of a new point or spatial access method such that he can run his implementation in our testbed

    Moving Beyond Noninformative Priors: Why and How to Choose Weakly Informative Priors in Bayesian Analyses

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    Throughout the last two decades, Bayesian statistical methods have proliferated throughout ecology and evolution. Numerous previous references established both philosophical and computational guidelines for implementing Bayesian methods. However, protocols for incorporating prior information, the defining characteristic of Bayesian philosophy, are nearly nonexistent in the ecological literature. Here, I hope to encourage the use of weakly informative priors in ecology and evolution by providing a ‘consumer\u27s guide’ to weakly informative priors. The first section outlines three reasons why ecologists should abandon noninformative priors: 1) common flat priors are not always noninformative, 2) noninformative priors provide the same result as simpler frequentist methods, and 3) noninformative priors suffer from the same high type I and type M error rates as frequentist methods. The second section provides a guide for implementing informative priors, wherein I detail convenient ‘reference’ prior distributions for common statistical models (i.e. regression, ANOVA, hierarchical models). I then use simulations to visually demonstrate how informative priors influence posterior parameter estimates. With the guidelines provided here, I hope to encourage the use of weakly informative priors for Bayesian analyses in ecology. Ecologists can and should debate the appropriate form of prior information, but should consider weakly informative priors as the new ‘default’ prior for any Bayesian model

    Optimal Multidimensional Query Processing Using Tree Striping

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    Abstract. In this paper, we propose a new technique for multidimensional query processing which can be widely applied in database systems. Our new technique, called tree striping, generalizes the well-known inverted lists and multidimension-al indexing approaches. A theoretical analysis of our generalized technique shows that both, inverted lists and multidimensional indexing approaches, are far from being optimal. A consequence of our analysis is that the use of a set of multidimen-sional indexes provides considerable improvements over one d-dimensional index (multidimensional indexing) or d one-dimensional indexes (inverted lists). The basic idea of tree striping is to use the optimal number k of lower-dimensional indexes determined by our theoretical analysis for efficient query processing. We confirm our theoretical results by an experimental evaluation on large amounts of real and synthetic data. The results show a speed-up of up to 310 % over the multi-dimensional indexing approach and a speed-up factor of up to 123 (12,300%) over the inverted-lists approach. 1

    Contrasting heterozygosity-fitness correlations across life in a long-lived seabird

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    Selection is a central force underlying evolutionary change and can vary in strength and direction, for example across time and space. The fitness consequences of individual genetic diversity have often been investigated by testing for multilocus heterozygosity-fitness correlations (HFCs), but few studies have been able to assess HFCs across life stages and in both sexes. Here, we test for HFCs using a 26-year longitudinal individual-based data set from a large population of a long-lived seabird (the common tern, Sterna hirundo), where 7,974 chicks and breeders of known age were genotyped at 15 microsatellite loci and sampled for life-history traits over the complete life cycle. Heterozygosity was not correlated with fledging or post-fledging prospecting probabilities, but was positively correlated with recruitment probability. For breeders, annual survival was not correlated with heterozygosity, but annual fledgling production was negatively correlated with heterozygosity in males and highest in intermediately heterozygous females. The contrasting HFCs among life stages and sexes indicate differential selective processes and emphasize the importance of assessing fitness consequences of traits over complete life histories

    Tracing Sub-Structure in the European American Population with PCA-Informative Markers

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    Genetic structure in the European American population reflects waves of migration and recent gene flow among different populations. This complex structure can introduce bias in genetic association studies. Using Principal Components Analysis (PCA), we analyze the structure of two independent European American datasets (1,521 individuals–307,315 autosomal SNPs). Individual variation lies across a continuum with some individuals showing high degrees of admixture with non-European populations, as demonstrated through joint analysis with HapMap data. The CEPH Europeans only represent a small fraction of the variation encountered in the larger European American datasets we studied. We interpret the first eigenvector of this data as correlated with ancestry, and we apply an algorithm that we have previously described to select PCA-informative markers (PCAIMs) that can reproduce this structure. Importantly, we develop a novel method that can remove redundancy from the selected SNP panels and show that we can effectively remove correlated markers, thus increasing genotyping savings. Only 150–200 PCAIMs suffice to accurately predict fine structure in European American datasets, as identified by PCA. Simulating association studies, we couple our method with a PCA-based stratification correction tool and demonstrate that a small number of PCAIMs can efficiently remove false correlations with almost no loss in power. The structure informative SNPs that we propose are an important resource for genetic association studies of European Americans. Furthermore, our redundancy removal algorithm can be applied on sets of ancestry informative markers selected with any method in order to select the most uncorrelated SNPs, and significantly decreases genotyping costs

    You eat what you are : personality-dependent filial cannibalism in a fish with paternal care

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    Many animal parents invest heavily to ensure offspring survival, yet some eventually consume some or all of their very own young. This so-called filial cannibalism is known from a wide range of taxa, but its adaptive benefit remains largely unclear. The extent to which parents cannibalize their broods varies substantially not only between species, but also between individuals, indicating that intrinsic behavioral differences, or animal personalities, might constitute a relevant proximate trigger for filial cannibalism. Using a marine fish with extensive paternal care, the common goby (Pomatoschistus microps), we investigated the influence of animal personality on filial cannibalism by assessing (1) behavioral consistency across a breeding and a nonbreeding context; (2) correlations between different breeding (egg fanning; filial cannibalism) and nonbreeding (activity) behaviors, and, in a separate experiment; (3) whether previously established personality scores affect filial cannibalism levels. We found consistent individual differences in activity across contexts. Partial filial cannibalism was independent of egg fanning but correlated strongly with activity, where active males cannibalized more eggs than less active males. This pattern was strong initially but vanished as the breeding season progressed. The incidence of whole clutch filial cannibalism increased with activity and clutch size. Our findings indicate that filial cannibalism cannot generally be adjusted independently of male personality and is thus phenotypically less plastic than typically assumed. The present work stresses the multidimensional interaction between animal personality, individual plasticity and the environment in shaping filial cannibalism.Peer reviewe

    Genomeâ wide analyses of psychological resilience in U.S. Army soldiers

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    Though a growing body of preclinical and translational research is illuminating a biological basis for resilience to stress, little is known about the genetic basis of psychological resilience in humans. We conducted genomeâ wide association studies (GWASs) of selfâ assessed (by questionnaire) and outcomeâ based (incident mental disorders from predeployment to postdeployment) resilience among European (EUR) ancestry soldiers in the Army study to assess risk and resilience in servicemembers. Selfâ assessed resilience (Nâ =â 11,492) was found to have significant commonâ variant heritability (h2 =â 0.162, seâ =â 0.050, pâ =â 5.37â Ã â 10â 4), and to be significantly negatively genetically correlated with neuroticism (rgâ =â â 0.388, pâ =â .0092). GWAS results from the EUR soldiers revealed a genomeâ wide significant locus on an intergenic region on Chr 4 upstream from doublecortinâ like kinase 2 (DCLK2) (four single nucleotide polymorphisms (SNPs) in LD; top SNP: rs4260523 [pâ =â 5.65â Ã â 10â 9] is an eQTL in frontal cortex), a member of the doublecortin family of kinases that promote survival and regeneration of injured neurons. A second gene, kelchâ like family member 36 (KLHL36) was detected at geneâ wise genomeâ wide significance [pâ =â 1.89â Ã â 10â 6]. A polygenic risk score derived from the selfâ assessed resilience GWAS was not significantly associated with outcomeâ based resilience. In very preliminary results, genomeâ wide significant association with outcomeâ based resilience was found for one locus (top SNP: rs12580015 [pâ =â 2.37â Ã â 10â 8]) on Chr 12 downstream from solute carrier family 15 member 5 (SLC15A5) in subjects (Nâ = 581) exposed to the highest level of deployment stress. The further study of genetic determinants of resilience has the potential to illuminate the molecular bases of stressâ related psychopathology and point to new avenues for therapeutic intervention.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149528/1/ajmgb32730.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149528/2/ajmgb32730_am.pd

    Longitudinal analyses of the DNA methylome in deployed military servicemen identify susceptibility loci for post-traumatic stress disorder

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    In order to determine the impact of the epigenetic response to traumatic stress on post-traumatic stress disorder (PTSD), this study examined longitudinal changes of genome-wide blood DNA methylation profiles in relation to the development of PTSD symptoms in two prospective military cohorts (one discovery and one replication data set). In the first cohort consisting of male Dutch military servicemen (n=93), the emergence of PTSD symptoms over a deployment period to a combat zone was significantly associated with alterations in DNA methylation levels at 17 genomic positions and 12 genomic regions. Evidence for mediation of the relation between combat trauma and PTSD symptoms by longitudinal changes in DNA methylation was observed at several positions and regions. Bioinformatic analyses of the reported associations identified significant enrichment in several pathways relevant for symptoms of PTSD. Targeted analyses of the significant findings from the discovery sample in an independent prospective cohort of male US marines (n=98) replicated the observed relation between decreases in DNA methylation levels and PTSD symptoms at genomic regions in ZFP57, RNF39 and HIST1H2APS2. Together, our study pinpoints three novel genomic regions where longitudinal decreases in DNA methylation across the period of exposure to combat trauma marks susceptibility for PTSD
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