Discovering Multidimensional Structure in Relational Data

DEFF Research Database (Denmark)

Jensen, Mikael Rune; Holmgren, Thomas; Pedersen, Torben Bach

2004-01-01

On-Line Analytical Processing (OLAP) systems based on multidimensional databases are essential elements of decision support. However, most existing data is stored in “ordinary” relational OLTP databases, i.e., data has to be (re-) modeled as multidimensional cubes before the advantages of OLAP to...... algorithms for discovering multidimensional schemas from relational databases. The algorithms take a wide range of available metadata into account in the discovery process, including functional and inclusion dependencies, and key and cardinality information....... tools are available. In this paper we present an approach for the automatic construction of multidimensional OLAP database schemas from existing relational OLTP databases, enabling easy OLAP design and analysis for most existing data sources. This is achieved through a set of practical and effective...

Multidimensional First-Order Dominance Comparisons of Population Wellbeing

DEFF Research Database (Denmark)

Siersbæk, Nikolaj; Østerdal, Lars Peter Raahave; Arndt, Thomas Channing

2017-01-01

This chapter conveys the concept of first-order dominance (FOD) with particular focus on applications to multidimensional population welfare comparisons. It gives an account of the fundamental equivalent definitions of FOD both in the one-dimensional and multidimensional setting, illustrated...

Image matrix processor for fast multi-dimensional computations

Science.gov (United States)

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

Integrative analysis of survival-associated gene sets in breast cancer.

Science.gov (United States)

Varn, Frederick S; Ung, Matthew H; Lou, Shao Ke; Cheng, Chao

2015-03-12

Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient's cancer. Identifying robust gene sets that are consistently predictive of a patient's clinical outcome has become one of the main challenges in the field. We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that quantitatively assesses a gene set's activity level in a given patient. We utilized this metric, along with patient time-to-event data, to perform survival analyses to identify the gene sets that were significantly correlated with patient survival. We then performed cross-dataset analyses to identify robust prognostic gene sets and to classify patients by metastasis status. Additionally, we created a gene set network based on component gene overlap to explore the relationship between gene sets derived from MSigDB. We developed a novel gene set based on this network's topology and applied the GSAS metric to characterize its role in patient survival. Using the GSAS metric, we identified 120 gene sets that were significantly associated with patient survival in all datasets tested. The gene overlap network analysis yielded a novel gene set enriched in genes shared by the robustly predictive gene sets. This gene set was highly correlated to patient survival when used alone. Most interestingly, removal of the genes in this gene set from the gene pool on MSigDB resulted in a large reduction in the number of predictive gene sets, suggesting a prominent role for these genes in breast cancer progression. The GSAS metric provided a useful medium by which we systematically investigated how gene sets from MSigDB relate to breast cancer patient survival. We used

Vision from next generation sequencing: multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development, aging and disease.

Science.gov (United States)

Yang, Hyun-Jin; Ratnapriya, Rinki; Cogliati, Tiziana; Kim, Jung-Woong; Swaroop, Anand

2015-05-01

Genomics and genetics have invaded all aspects of biology and medicine, opening uncharted territory for scientific exploration. The definition of "gene" itself has become ambiguous, and the central dogma is continuously being revised and expanded. Computational biology and computational medicine are no longer intellectual domains of the chosen few. Next generation sequencing (NGS) technology, together with novel methods of pattern recognition and network analyses, has revolutionized the way we think about fundamental biological mechanisms and cellular pathways. In this review, we discuss NGS-based genome-wide approaches that can provide deeper insights into retinal development, aging and disease pathogenesis. We first focus on gene regulatory networks (GRNs) that govern the differentiation of retinal photoreceptors and modulate adaptive response during aging. Then, we discuss NGS technology in the context of retinal disease and develop a vision for therapies based on network biology. We should emphasize that basic strategies for network construction and analyses can be transported to any tissue or cell type. We believe that specific and uniform guidelines are required for generation of genome, transcriptome and epigenome data to facilitate comparative analysis and integration of multi-dimensional data sets, and for constructing networks underlying complex biological processes. As cellular homeostasis and organismal survival are dependent on gene-gene and gene-environment interactions, we believe that network-based biology will provide the foundation for deciphering disease mechanisms and discovering novel drug targets for retinal neurodegenerative diseases. Published by Elsevier Ltd.

Zebrafish Expression Ontology of Gene Sets (ZEOGS): A Tool to Analyze Enrichment of Zebrafish Anatomical Terms in Large Gene Sets

Science.gov (United States)

Marsico, Annalisa

2013-01-01

Abstract The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene

Zebrafish Expression Ontology of Gene Sets (ZEOGS): a tool to analyze enrichment of zebrafish anatomical terms in large gene sets.

Science.gov (United States)

Prykhozhij, Sergey V; Marsico, Annalisa; Meijsing, Sebastiaan H

2013-09-01

The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene expression

MAGMA: Generalized Gene-Set Analysis of GWAS Data

NARCIS (Netherlands)

de Leeuw, C.A.; Mooij, J.M.; Heskes, T.; Posthuma, D.

2015-01-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical

MAGMA: generalized gene-set analysis of GWAS data.

NARCIS (Netherlands)

de Leeuw, C.A.; Mooij, J.M.; Heskes, T.; Posthuma, D.

2015-01-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical

Gene set analysis of purine and pyrimidine antimetabolites cancer therapies.

Science.gov (United States)

Fridley, Brooke L; Batzler, Anthony; Li, Liang; Li, Fang; Matimba, Alice; Jenkins, Gregory D; Ji, Yuan; Wang, Liewei; Weinshilboum, Richard M

2011-11-01

Responses to therapies, either with regard to toxicities or efficacy, are expected to involve complex relationships of gene products within the same molecular pathway or functional gene set. Therefore, pathways or gene sets, as opposed to single genes, may better reflect the true underlying biology and may be more appropriate units for analysis of pharmacogenomic studies. Application of such methods to pharmacogenomic studies may enable the detection of more subtle effects of multiple genes in the same pathway that may be missed by assessing each gene individually. A gene set analysis of 3821 gene sets is presented assessing the association between basal messenger RNA expression and drug cytotoxicity using ethnically defined human lymphoblastoid cell lines for two classes of drugs: pyrimidines [gemcitabine (dFdC) and arabinoside] and purines [6-thioguanine and 6-mercaptopurine]. The gene set nucleoside-diphosphatase activity was found to be significantly associated with both dFdC and arabinoside, whereas gene set γ-aminobutyric acid catabolic process was associated with dFdC and 6-thioguanine. These gene sets were significantly associated with the phenotype even after adjusting for multiple testing. In addition, five associated gene sets were found in common between the pyrimidines and two gene sets for the purines (3',5'-cyclic-AMP phosphodiesterase activity and γ-aminobutyric acid catabolic process) with a P value of less than 0.0001. Functional validation was attempted with four genes each in gene sets for thiopurine and pyrimidine antimetabolites. All four genes selected from the pyrimidine gene sets (PSME3, CANT1, ENTPD6, ADRM1) were validated, but only one (PDE4D) was validated for the thiopurine gene sets. In summary, results from the gene set analysis of pyrimidine and purine therapies, used often in the treatment of various cancers, provide novel insight into the relationship between genomic variation and drug response.

Gene set analysis for GWAS

DEFF Research Database (Denmark)

Debrabant, Birgit; Soerensen, Mette

2014-01-01

Abstract We discuss the use of modified Kolmogorov-Smirnov (KS) statistics in the context of gene set analysis and review corresponding null and alternative hypotheses. Especially, we show that, when enhancing the impact of highly significant genes in the calculation of the test statistic, the co...

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

Science.gov (United States)

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data

Directory of Open Access Journals (Sweden)

Tintle Nathan L

2012-08-01

Full Text Available Abstract Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

Studying the Complex Expression Dependences between Sets of Coexpressed Genes

Directory of Open Access Journals (Sweden)

Mario Huerta

2014-01-01

Full Text Available Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.

Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies.

Science.gov (United States)

Schaid, Daniel J; Sinnwell, Jason P; Jenkins, Gregory D; McDonnell, Shannon K; Ingle, James N; Kubo, Michiaki; Goss, Paul E; Costantino, Joseph P; Wickerham, D Lawrence; Weinshilboum, Richard M

2012-01-01

Gene-set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene-set, have plagued current approaches, often leading to ad hoc "fixes." To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene-level and gene-set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene-sets. However, other types of gene-set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene-sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene-sets, we use an efficient computational strategy that accounts for LD and provides accurate step-down adjusted P-values for each gene-set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene-set analyses. © 2011 Wiley Periodicals, Inc.

CAMS: OLAPing Multidimensional Data Streams Efficiently

Science.gov (United States)

Cuzzocrea, Alfredo

In the context of data stream research, taming the multidimensionality of real-life data streams in order to efficiently support OLAP analysis/mining tasks is a critical challenge. Inspired by this fundamental motivation, in this paper we introduce CAMS (C ube-based A cquisition model for M ultidimensional S treams), a model for efficiently OLAPing multidimensional data streams. CAMS combines a set of data stream processing methodologies, namely (i) the OLAP dimension flattening process, which allows us to obtain dimensionality reduction of multidimensional data streams, and (ii) the OLAP stream aggregation scheme, which aggregates data stream readings according to an OLAP-hierarchy-based membership approach. We complete our analytical contribution by means of experimental assessment and analysis of both the efficiency and the scalability of OLAPing capabilities of CAMS on synthetic multidimensional data streams. Both analytical and experimental results clearly connote CAMS as an enabling component for next-generation Data Stream Management Systems.

A Conceptual Model for Multidimensional Analysis of Documents

Science.gov (United States)

Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurlfluh, Gilles

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.

IGSA: Individual Gene Sets Analysis, including Enrichment and Clustering.

Science.gov (United States)

Wu, Lingxiang; Chen, Xiujie; Zhang, Denan; Zhang, Wubing; Liu, Lei; Ma, Hongzhe; Yang, Jingbo; Xie, Hongbo; Liu, Bo; Jin, Qing

2016-01-01

Analysis of gene sets has been widely applied in various high-throughput biological studies. One weakness in the traditional methods is that they neglect the heterogeneity of genes expressions in samples which may lead to the omission of some specific and important gene sets. It is also difficult for them to reflect the severities of disease and provide expression profiles of gene sets for individuals. We developed an application software called IGSA that leverages a powerful analytical capacity in gene sets enrichment and samples clustering. IGSA calculates gene sets expression scores for each sample and takes an accumulating clustering strategy to let the samples gather into the set according to the progress of disease from mild to severe. We focus on gastric, pancreatic and ovarian cancer data sets for the performance of IGSA. We also compared the results of IGSA in KEGG pathways enrichment with David, GSEA, SPIA, ssGSEA and analyzed the results of IGSA clustering and different similarity measurement methods. Notably, IGSA is proved to be more sensitive and specific in finding significant pathways, and can indicate related changes in pathways with the severity of disease. In addition, IGSA provides with significant gene sets profile for each sample.

The Molecular Signatures Database (MSigDB) hallmark gene set collection.

Science.gov (United States)

Liberzon, Arthur; Birger, Chet; Thorvaldsdóttir, Helga; Ghandi, Mahmoud; Mesirov, Jill P; Tamayo, Pablo

2015-12-23

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

Multidimensional spectrometer

Science.gov (United States)

Zanni, Martin Thomas; Damrauer, Niels H.

2010-07-20

A multidimensional spectrometer for the infrared, visible, and ultraviolet regions of the electromagnetic spectrum, and a method for making multidimensional spectroscopic measurements in the infrared, visible, and ultraviolet regions of the electromagnetic spectrum. The multidimensional spectrometer facilitates measurements of inter- and intra-molecular interactions.

Beyond main effects of gene-sets: harsh parenting moderates the association between a dopamine gene-set and child externalizing behavior.

Science.gov (United States)

Windhorst, Dafna A; Mileva-Seitz, Viara R; Rippe, Ralph C A; Tiemeier, Henning; Jaddoe, Vincent W V; Verhulst, Frank C; van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J

2016-08-01

In a longitudinal cohort study, we investigated the interplay of harsh parenting and genetic variation across a set of functionally related dopamine genes, in association with children's externalizing behavior. This is one of the first studies to employ gene-based and gene-set approaches in tests of Gene by Environment (G × E) effects on complex behavior. This approach can offer an important alternative or complement to candidate gene and genome-wide environmental interaction (GWEI) studies in the search for genetic variation underlying individual differences in behavior. Genetic variants in 12 autosomal dopaminergic genes were available in an ethnically homogenous part of a population-based cohort. Harsh parenting was assessed with maternal (n = 1881) and paternal (n = 1710) reports at age 3. Externalizing behavior was assessed with the Child Behavior Checklist (CBCL) at age 5 (71 ± 3.7 months). We conducted gene-set analyses of the association between variation in dopaminergic genes and externalizing behavior, stratified for harsh parenting. The association was statistically significant or approached significance for children without harsh parenting experiences, but was absent in the group with harsh parenting. Similarly, significant associations between single genes and externalizing behavior were only found in the group without harsh parenting. Effect sizes in the groups with and without harsh parenting did not differ significantly. Gene-environment interaction tests were conducted for individual genetic variants, resulting in two significant interaction effects (rs1497023 and rs4922132) after correction for multiple testing. Our findings are suggestive of G × E interplay, with associations between dopamine genes and externalizing behavior present in children without harsh parenting, but not in children with harsh parenting experiences. Harsh parenting may overrule the role of genetic factors in externalizing behavior. Gene-based and gene-set

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

Science.gov (United States)

2013-01-01

Background Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. Methods We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals. Results Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the

Discovery of cancer common and specific driver gene sets

Science.gov (United States)

2017-01-01

Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

APPRIS 2017: principal isoforms for multiple gene sets

Science.gov (United States)

Rodriguez-Rivas, Juan; Di Domenico, Tomás; Vázquez, Jesús; Valencia, Alfonso

2018-01-01

Abstract The APPRIS database (http://appris-tools.org) uses protein structural and functional features and information from cross-species conservation to annotate splice isoforms in protein-coding genes. APPRIS selects a single protein isoform, the ‘principal’ isoform, as the reference for each gene based on these annotations. A single main splice isoform reflects the biological reality for most protein coding genes and APPRIS principal isoforms are the best predictors of these main proteins isoforms. Here, we present the updates to the database, new developments that include the addition of three new species (chimpanzee, Drosophila melangaster and Caenorhabditis elegans), the expansion of APPRIS to cover the RefSeq gene set and the UniProtKB proteome for six species and refinements in the core methods that make up the annotation pipeline. In addition APPRIS now provides a measure of reliability for individual principal isoforms and updates with each release of the GENCODE/Ensembl and RefSeq reference sets. The individual GENCODE/Ensembl, RefSeq and UniProtKB reference gene sets for six organisms have been merged to produce common sets of splice variants. PMID:29069475

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

Directory of Open Access Journals (Sweden)

Hettne Kristina M

2013-01-01

Full Text Available Abstract Background Availability of chemical response-specific lists of genes (gene sets for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM, and that these can be used with gene set analysis (GSA methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. Methods We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human and 588 (mouse gene sets from the Comparative Toxicogenomics Database (CTD. We tested for significant differential expression (SDE (false discovery rate -corrected p-values Results Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the triazoles. We confirmed embryotoxic effects, and discriminated triazoles from other chemicals. Conclusions Gene set analysis with next-gen TM-derived chemical response-specific gene sets is a scalable method for identifying similarities in gene responses to other chemicals, from which one may infer potential mode of action and/or toxic effect.

Multidimensional building objects in a Danish geo-information infrastructure perspective

DEFF Research Database (Denmark)

Schrøder, Lise

2002-01-01

The emerging multidimensional GI- and VR-technologies within the professional disciplines dealing with design, planning and management processes is leading to a demand for four-dimensional building objects as part of the public geo-information infrastructure. The other way around the recognition...... of the building as a four-dimensional geo-phenomenon will provide a reference between different data sets whether representing buildings in two, three or four dimensions. Finally a central issue is the potential in using frameworks of multidimensional representations as interfaces to the available data sets...

Multidimensional scaling technique for analysis of magnetic storms ...

Indian Academy of Sciences (India)

R.Narasimhan(krishtel emaging) 1461 1996 Oct 15 13:05:22

Multidimensional Scaling (MDS) comprises a set of models and associated methods for construct- ing a geometrical representation of proximity and dominance relationship between elements in one or more sets of entities. MDS can be applied to data that express two types of relationships: proxim- ity relations and ...

Comparative study on gene set and pathway topology-based enrichment methods.

Science.gov (United States)

Bayerlová, Michaela; Jung, Klaus; Kramer, Frank; Klemm, Florian; Bleckmann, Annalen; Beißbarth, Tim

2015-10-22

Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both

LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

Science.gov (United States)

Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

2016-01-11

Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

NARCIS (Netherlands)

Hettne, K.M.; Boorsma, A.; Dartel, D.A. van; Goeman, J.J.; Jong, E. de; Piersma, A.H.; Stierum, R.H.; Kleinjans, J.C.; Kors, J.A.

2013-01-01

BACKGROUND: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

NARCIS (Netherlands)

Hettne, K.M.; Boorsma, A.; Dartel, van D.A.M.; Goeman, J.J.; Jong, de E.; Piersma, A.H.; Stierum, R.H.; Kleinjans, J.C.; Kors, J.A.

2013-01-01

Background: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set

Intuitionistic fuzzy (IF) evaluations of multidimensional model

International Nuclear Information System (INIS)

Valova, I.

2012-01-01

There are different logical methods for data structuring, but no one is perfect enough. Multidimensional model-MD of data is presentation of data in a form of cube (referred also as info-cube or hypercube) with data or in form of 'star' type scheme (referred as multidimensional scheme), by use of F-structures (Facts) and set of D-structures (Dimensions), based on the notion of hierarchy of D-structures. The data, being subject of analysis in a specific multidimensional model is located in a Cartesian space, being restricted by D-structures. In fact, the data is either dispersed or 'concentrated', therefore the data cells are not distributed evenly within the respective space. The moment of occurrence of any event is difficult to be predicted and the data is concentrated as per time periods, location of performed business event, etc. To process such dispersed or concentrated data, various technical strategies are needed. The basic methods for presentation of such data should be selected. The approaches of data processing and respective calculations are connected with different options for data representation. The use of intuitionistic fuzzy evaluations (IFE) provide us new possibilities for alternative presentation and processing of data, subject of analysis in any OLAP application. The use of IFE at the evaluation of multidimensional models will result in the following advantages: analysts will dispose with more complete information for processing and analysis of respective data; benefit for the managers is that the final decisions will be more effective ones; enabling design of more functional multidimensional schemes. The purpose of this work is to apply intuitionistic fuzzy evaluations of multidimensional model of data. (authors)

Simulation of a Multidimensional Input Quantum Perceptron

Science.gov (United States)

Yamamoto, Alexandre Y.; Sundqvist, Kyle M.; Li, Peng; Harris, H. Rusty

2018-06-01

In this work, we demonstrate the improved data separation capabilities of the Multidimensional Input Quantum Perceptron (MDIQP), a fundamental cell for the construction of more complex Quantum Artificial Neural Networks (QANNs). This is done by using input controlled alterations of ancillary qubits in combination with phase estimation and learning algorithms. The MDIQP is capable of processing quantum information and classifying multidimensional data that may not be linearly separable, extending the capabilities of the classical perceptron. With this powerful component, we get much closer to the achievement of a feedforward multilayer QANN, which would be able to represent and classify arbitrary sets of data (both quantum and classical).

Gene set analysis: limitations in popular existing methods and proposed improvements.

Science.gov (United States)

Mishra, Pashupati; Törönen, Petri; Leino, Yrjö; Holm, Liisa

2014-10-01

Gene set analysis is the analysis of a set of genes that collectively contribute to a biological process. Most popular gene set analysis methods are based on empirical P-value that requires large number of permutations. Despite numerous gene set analysis methods developed in the past decade, the most popular methods still suffer from serious limitations. We present a gene set analysis method (mGSZ) based on Gene Set Z-scoring function (GSZ) and asymptotic P-values. Asymptotic P-value calculation requires fewer permutations, and thus speeds up the gene set analysis process. We compare the GSZ-scoring function with seven popular gene set scoring functions and show that GSZ stands out as the best scoring function. In addition, we show improved performance of the GSA method when the max-mean statistics is replaced by the GSZ scoring function. We demonstrate the importance of both gene and sample permutations by showing the consequences in the absence of one or the other. A comparison of asymptotic and empirical methods of P-value estimation demonstrates a clear advantage of asymptotic P-value over empirical P-value. We show that mGSZ outperforms the state-of-the-art methods based on two different evaluations. We compared mGSZ results with permutation and rotation tests and show that rotation does not improve our asymptotic P-values. We also propose well-known asymptotic distribution models for three of the compared methods. mGSZ is available as R package from cran.r-project.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Multi-dimensional Fuzzy Euler Approximation

Directory of Open Access Journals (Sweden)

Yangyang Hao

2017-05-01

Full Text Available Multi-dimensional Fuzzy differential equations driven by multi-dimen-sional Liu process, have been intensively applied in many fields. However, we can not obtain the analytic solution of every multi-dimensional fuzzy differential equation. Then, it is necessary for us to discuss the numerical results in most situations. This paper focuses on the numerical method of multi-dimensional fuzzy differential equations. The multi-dimensional fuzzy Taylor expansion is given, based on this expansion, a numerical method which is designed for giving the solution of multi-dimensional fuzzy differential equation via multi-dimensional Euler method will be presented, and its local convergence also will be discussed.

Beyond main effects of gene-sets: harsh parenting moderates the association between a dopamine gene-set and child externalizing behavior

NARCIS (Netherlands)

J. Windhorst (Judith); V. Mileva-Seitz (Viara); R.C.A. Rippe (Ralph C.A.); H.W. Tiemeier (Henning); V.W.V. Jaddoe (Vincent); F.C. Verhulst (Frank); M.H. van IJzendoorn (Rien); M.J. Bakermans-Kranenburg (Marian)

2016-01-01

textabstractBackground: In a longitudinal cohort study, we investigated the interplay of harsh parenting and genetic variation across a set of functionally related dopamine genes, in association with children's externalizing behavior. This is one of the first studies to employ gene-based and

GSMA: Gene Set Matrix Analysis, An Automated Method for Rapid Hypothesis Testing of Gene Expression Data

Directory of Open Access Journals (Sweden)

Chris Cheadle

2007-01-01

Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of gene expression simultaneously for multiple lists of genes (gene sets against entire distributions of gene expression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

Annotating gene sets by mining large literature collections with protein networks.

Science.gov (United States)

Wang, Sheng; Ma, Jianzhu; Yu, Michael Ku; Zheng, Fan; Huang, Edward W; Han, Jiawei; Peng, Jian; Ideker, Trey

2018-01-01

Analysis of patient genomes and transcriptomes routinely recognizes new gene sets associated with human disease. Here we present an integrative natural language processing system which infers common functions for a gene set through automatic mining of the scientific literature with biological networks. This system links genes with associated literature phrases and combines these links with protein interactions in a single heterogeneous network. Multiscale functional annotations are inferred based on network distances between phrases and genes and then visualized as an ontology of biological concepts. To evaluate this system, we predict functions for gene sets representing known pathways and find that our approach achieves substantial improvement over the conventional text-mining baseline method. Moreover, our system discovers novel annotations for gene sets or pathways without previously known functions. Two case studies demonstrate how the system is used in discovery of new cancer-related pathways with ontological annotations.

Phylogenetics and evolution of Trx SET genes in fully sequenced land plants.

Science.gov (United States)

Zhu, Xinyu; Chen, Caoyi; Wang, Baohua

2012-04-01

Plant Trx SET proteins are involved in H3K4 methylation and play a key role in plant floral development. Genes encoding Trx SET proteins constitute a multigene family in which the copy number varies among plant species and functional divergence appears to have occurred repeatedly. To investigate the evolutionary history of the Trx SET gene family, we made a comprehensive evolutionary analysis on this gene family from 13 major representatives of green plants. A novel clustering (here named as cpTrx clade), which included the III-1, III-2, and III-4 orthologous groups, previously resolved was identified. Our analysis showed that plant Trx proteins possessed a variety of domain organizations and gene structures among paralogs. Additional domains such as PHD, PWWP, and FYR were early integrated into primordial SET-PostSET domain organization of cpTrx clade. We suggested that the PostSET domain was lost in some members of III-4 orthologous group during the evolution of land plants. At least four classes of gene structures had been formed at the early evolutionary stage of land plants. Three intronless orphan Trx SET genes from the Physcomitrella patens (moss) were identified, and supposedly, their parental genes have been eliminated from the genome. The structural differences among evolutionary groups of plant Trx SET genes with different functions were described, contributing to the design of further experimental studies.

Ranking metrics in gene set enrichment analysis: do they matter?

Science.gov (United States)

Zyla, Joanna; Marczyk, Michal; Weiner, January; Polanska, Joanna

2017-05-12

There exist many methods for describing the complex relation between changes of gene expression in molecular pathways or gene ontologies under different experimental conditions. Among them, Gene Set Enrichment Analysis seems to be one of the most commonly used (over 10,000 citations). An important parameter, which could affect the final result, is the choice of a metric for the ranking of genes. Applying a default ranking metric may lead to poor results. In this work 28 benchmark data sets were used to evaluate the sensitivity and false positive rate of gene set analysis for 16 different ranking metrics including new proposals. Furthermore, the robustness of the chosen methods to sample size was tested. Using k-means clustering algorithm a group of four metrics with the highest performance in terms of overall sensitivity, overall false positive rate and computational load was established i.e. absolute value of Moderated Welch Test statistic, Minimum Significant Difference, absolute value of Signal-To-Noise ratio and Baumgartner-Weiss-Schindler test statistic. In case of false positive rate estimation, all selected ranking metrics were robust with respect to sample size. In case of sensitivity, the absolute value of Moderated Welch Test statistic and absolute value of Signal-To-Noise ratio gave stable results, while Baumgartner-Weiss-Schindler and Minimum Significant Difference showed better results for larger sample size. Finally, the Gene Set Enrichment Analysis method with all tested ranking metrics was parallelised and implemented in MATLAB, and is available at https://github.com/ZAEDPolSl/MrGSEA . Choosing a ranking metric in Gene Set Enrichment Analysis has critical impact on results of pathway enrichment analysis. The absolute value of Moderated Welch Test has the best overall sensitivity and Minimum Significant Difference has the best overall specificity of gene set analysis. When the number of non-normally distributed genes is high, using Baumgartner

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

Science.gov (United States)

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators

Investigating the effect of paralogs on microarray gene-set analysis

LENUS (Irish Health Repository)

Faure, Andre J

2011-01-24

Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

Science.gov (United States)

Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2018-02-09

Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of

Multidimensional Heat Conduction

DEFF Research Database (Denmark)

Rode, Carsten

1998-01-01

Analytical theory of multidimensional heat conduction. General heat conduction equation in three dimensions. Steay state, analytical solutions. The Laplace equation. Method of separation of variables. Principle of superposition. Shape factors. Transient, multidimensional heat conduction....

Equating Multidimensional Tests under a Random Groups Design: A Comparison of Various Equating Procedures

Science.gov (United States)

Lee, Eunjung

2013-01-01

The purpose of this research was to compare the equating performance of various equating procedures for the multidimensional tests. To examine the various equating procedures, simulated data sets were used that were generated based on a multidimensional item response theory (MIRT) framework. Various equating procedures were examined, including…

Using the Andrews Plotss to Visualize Multidimensional Data in Multi-criteria Optimization

Directory of Open Access Journals (Sweden)

S. V. Groshev

2015-01-01

Full Text Available Currently, issues on processing of large data volumes are of great importance. Initially, the Andrews plots have been proposed to show multidimensional statistics on the plane. But as the Andrews plots retain information on the average values of the represented values, distances, and dispersion, the distances between the plots linearly indicate distances between the data points, and it becomes possible to use the plots under consideration for the graphical representation of multi-dimensional data of various kinds. The paper analyses a diversity of various mathematical apparatus for Andrews plotting to visualize multi-dimensional data.The first section provides basic information about the Andrews plots, as well as about a test set of multidimensional data in Iris Fischer’s literature. Analysis of the Andrews plot properties shows that they provide a limitlessly many one-dimensional projections on the vectors and, furthermore, the plots, which are nearer to each other, correspond to nearly points. All this makes it possible to use the plots under consideration for multi-dimensional data representation. The paper considers the Andrews plot formation based on Fourier transform functions, and from the analysis results of plotting based on a set of the test, it draws a conclusion that in this way it is possible to provide clustering of multidimensional data.The second section of the work deals with research of different ways to modify the Andrews plots in order to improve the perception of the graphical representation of multidimensional data. Different variants of the Andrews plot projections on the coordinate planes and arbitrary subspaces are considered. In addition, the paper studies an effect of the Andrews plot scaling on the visual perception of multidimensional data.The paper’s third section describes Andrews plotting based on different polynomials, in particular, Chebyshev and Legendre polynomials. It is shown that the resulting image is

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

Science.gov (United States)

Clark, Neil R; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D; Jones, Matthew R; Ma'ayan, Avi

2015-11-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

A human rights-consistent approach to multidimensional welfare measurement applied to sub-Saharan Africa

DEFF Research Database (Denmark)

Arndt, Channing; Mahrt, Kristi; Hussain, Azhar

2017-01-01

is in reality inconsistent with the Universal Declaration of Human Rights principles of indivisibility, inalienability, and equality. We show that a first-order dominance methodology maintains consistency with basic principles, discuss the properties of the multidimensional poverty index and first......The rights-based approach to development targets progress towards the realization of 30 articles set forth in the Universal Declaration of Human Rights. Progress is frequently measured using the multidimensional poverty index. While elegant and useful, the multidimensional poverty index...

The 'thousand words' problem: Summarizing multi-dimensional data

International Nuclear Information System (INIS)

Scott, David M.

2011-01-01

Research highlights: → Sophisticated process sensors produce large multi-dimensional data sets. → Plant control systems cannot handle images or large amounts of data. → Various techniques reduce the dimensionality, extracting information from raw data. → Simple 1D and 2D methods can often be extended to 3D and 4D applications. - Abstract: An inherent difficulty in the application of multi-dimensional sensing to process monitoring and control is the extraction and interpretation of useful information. Ultimately the measured data must be collapsed into a relatively small number of values that capture the salient characteristics of the process. Although multiple dimensions are frequently necessary to isolate a particular physical attribute (such as the distribution of a particular chemical species in a reactor), plant control systems are not equipped to use such data directly. The production of a multi-dimensional data set (often displayed as an image) is not the final step of the measurement process, because information must still be extracted from the raw data. In the metaphor of one picture being equal to a thousand words, the problem becomes one of paraphrasing a lengthy description of the image with one or two well-chosen words. Various approaches to solving this problem are discussed using examples from the fields of particle characterization, image processing, and process tomography.

Uniform approximation is more appropriate for Wilcoxon Rank-Sum Test in gene set analysis.

Directory of Open Access Journals (Sweden)

Zhide Fang

Full Text Available Gene set analysis is widely used to facilitate biological interpretations in the analyses of differential expression from high throughput profiling data. Wilcoxon Rank-Sum (WRS test is one of the commonly used methods in gene set enrichment analysis. It compares the ranks of genes in a gene set against those of genes outside the gene set. This method is easy to implement and it eliminates the dichotomization of genes into significant and non-significant in a competitive hypothesis testing. Due to the large number of genes being examined, it is impractical to calculate the exact null distribution for the WRS test. Therefore, the normal distribution is commonly used as an approximation. However, as we demonstrate in this paper, the normal approximation is problematic when a gene set with relative small number of genes is tested against the large number of genes in the complementary set. In this situation, a uniform approximation is substantially more powerful, more accurate, and less intensive in computation. We demonstrate the advantage of the uniform approximations in Gene Ontology (GO term analysis using simulations and real data sets.

Multidimensional poverty: an alternative measurement approach for the United States?

Science.gov (United States)

Waglé, Udaya R

2008-06-01

International poverty research has increasingly underscored the need to use multidimensional approaches to measure poverty. Largely embraced in Europe and elsewhere, this has not had much impact on the way poverty is measured in the United States. In this paper, I use a comprehensive multidimensional framework including economic well-being, capability, and social inclusion to examine poverty in the US. Data from the 2004 General Social Survey support the interconnectedness among these poverty dimensions, indicating that the multidimensional framework utilizing a comprehensive set of information provides a compelling value added to poverty measurement. The suggested demographic characteristics of the various categories of the poor are somewhat similar between this approach and other traditional approaches. But the more comprehensive and accurate measurement outcomes from this approach help policymakers target resources at the specific groups.

Multidimensional high harmonic spectroscopy

International Nuclear Information System (INIS)

Bruner, Barry D; Soifer, Hadas; Shafir, Dror; Dudovich, Nirit; Serbinenko, Valeria; Smirnova, Olga

2015-01-01

High harmonic generation (HHG) has opened up a new frontier in ultrafast science where attosecond time resolution and Angstrom spatial resolution are accessible in a single measurement. However, reconstructing the dynamics under study is limited by the multiple degrees of freedom involved in strong field interactions. In this paper we describe a new class of measurement schemes for resolving attosecond dynamics, integrating perturbative nonlinear optics with strong-field physics. These approaches serve as a basis for multidimensional high harmonic spectroscopy. Specifically, we show that multidimensional high harmonic spectroscopy can measure tunnel ionization dynamics with high precision, and resolves the interference between multiple ionization channels. In addition, we show how multidimensional HHG can function as a type of lock-in amplifier measurement. Similar to multi-dimensional approaches in nonlinear optical spectroscopy that have resolved correlated femtosecond dynamics, multi-dimensional high harmonic spectroscopy reveals the underlying complex dynamics behind attosecond scale phenomena. (paper)

Numeric invariants from multidimensional persistence

Energy Technology Data Exchange (ETDEWEB)

Skryzalin, Jacek [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlsson, Gunnar [Stanford Univ., Stanford, CA (United States)

2017-05-19

In this paper, we analyze the space of multidimensional persistence modules from the perspectives of algebraic geometry. We first build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence over one-dimensional persistence. We argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Lastly, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be used to study data.

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

NARCIS (Netherlands)

K.M. Hettne (Kristina); J. Boorsma (Jeffrey); D.A.M. van Dartel (Dorien A M); J.J. Goeman (Jelle); E.C. de Jong (Esther); A.H. Piersma (Aldert); R.H. Stierum (Rob); J. Kleinjans (Jos); J.A. Kors (Jan)

2013-01-01

textabstractBackground: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with

Multi-dimensional Bin Packing Problems with Guillotine Constraints

DEFF Research Database (Denmark)

Amossen, Rasmus Resen; Pisinger, David

2010-01-01

The problem addressed in this paper is the decision problem of determining if a set of multi-dimensional rectangular boxes can be orthogonally packed into a rectangular bin while satisfying the requirement that the packing should be guillotine cuttable. That is, there should exist a series of face...... parallel straight cuts that can recursively cut the bin into pieces so that each piece contains a box and no box has been intersected by a cut. The unrestricted problem is known to be NP-hard. In this paper we present a generalization of a constructive algorithm for the multi-dimensional bin packing...... problem, with and without the guillotine constraint, based on constraint programming....

Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

Science.gov (United States)

Gong, Wuming; Koyano-Nakagawa, Naoko; Li, Tongbin; Garry, Daniel J

2015-03-07

-CM transitions. We report a novel method to systematically integrate multi-dimensional -omics data and reconstruct the gene regulatory networks. This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

Identification of a robust gene signature that predicts breast cancer outcome in independent data sets

International Nuclear Information System (INIS)

Korkola, James E; Waldman, Frederic M; Blaveri, Ekaterina; DeVries, Sandy; Moore, Dan H II; Hwang, E Shelley; Chen, Yunn-Yi; Estep, Anne LH; Chew, Karen L; Jensen, Ronald H

2007-01-01

Breast cancer is a heterogeneous disease, presenting with a wide range of histologic, clinical, and genetic features. Microarray technology has shown promise in predicting outcome in these patients. We profiled 162 breast tumors using expression microarrays to stratify tumors based on gene expression. A subset of 55 tumors with extensive follow-up was used to identify gene sets that predicted outcome. The predictive gene set was further tested in previously published data sets. We used different statistical methods to identify three gene sets associated with disease free survival. A fourth gene set, consisting of 21 genes in common to all three sets, also had the ability to predict patient outcome. To validate the predictive utility of this derived gene set, it was tested in two published data sets from other groups. This gene set resulted in significant separation of patients on the basis of survival in these data sets, correctly predicting outcome in 62–65% of patients. By comparing outcome prediction within subgroups based on ER status, grade, and nodal status, we found that our gene set was most effective in predicting outcome in ER positive and node negative tumors. This robust gene selection with extensive validation has identified a predictive gene set that may have clinical utility for outcome prediction in breast cancer patients

A Bayesian variable selection procedure for ranking overlapping gene sets

DEFF Research Database (Denmark)

Skarman, Axel; Mahdi Shariati, Mohammad; Janss, Luc

2012-01-01

Background Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been de...

Delimiting Coalescence Genes (C-Genes) in Phylogenomic Data Sets.

Science.gov (United States)

Springer, Mark S; Gatesy, John

2018-02-26

coalescence methods have emerged as a popular alternative for inferring species trees with large genomic datasets, because these methods explicitly account for incomplete lineage sorting. However, statistical consistency of summary coalescence methods is not guaranteed unless several model assumptions are true, including the critical assumption that recombination occurs freely among but not within coalescence genes (c-genes), which are the fundamental units of analysis for these methods. Each c-gene has a single branching history, and large sets of these independent gene histories should be the input for genome-scale coalescence estimates of phylogeny. By contrast, numerous studies have reported the results of coalescence analyses in which complete protein-coding sequences are treated as c-genes even though exons for these loci can span more than a megabase of DNA. Empirical estimates of recombination breakpoints suggest that c-genes may be much shorter, especially when large clades with many species are the focus of analysis. Although this idea has been challenged recently in the literature, the inverse relationship between c-gene size and increased taxon sampling in a dataset-the 'recombination ratchet'-is a fundamental property of c-genes. For taxonomic groups characterized by genes with long intron sequences, complete protein-coding sequences are likely not valid c-genes and are inappropriate units of analysis for summary coalescence methods unless they occur in recombination deserts that are devoid of incomplete lineage sorting (ILS). Finally, it has been argued that coalescence methods are robust when the no-recombination within loci assumption is violated, but recombination must matter at some scale because ILS, a by-product of recombination, is the raison d'etre for coalescence methods. That is, extensive recombination is required to yield the large number of independently segregating c-genes used to infer a species tree. If coalescent methods are powerful

An Independent Filter for Gene Set Testing Based on Spectral Enrichment

NARCIS (Netherlands)

Frost, H Robert; Li, Zhigang; Asselbergs, Folkert W; Moore, Jason H

2015-01-01

Gene set testing has become an indispensable tool for the analysis of high-dimensional genomic data. An important motivation for testing gene sets, rather than individual genomic variables, is to improve statistical power by reducing the number of tested hypotheses. Given the dramatic growth in

Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

Directory of Open Access Journals (Sweden)

Andrew Williams

2015-12-01

Full Text Available Background: The presence of diverse types of nanomaterials (NMs in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2, carbon black (CB or carbon nanotubes (CNTs to determine the disease significance of these data-driven gene sets.Results: Biclusters representing inflammation (chemokine activity, DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032. The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles.Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several

Model-based gene set analysis for Bioconductor.

Science.gov (United States)

Bauer, Sebastian; Robinson, Peter N; Gagneur, Julien

2011-07-01

Gene Ontology and other forms of gene-category analysis play a major role in the evaluation of high-throughput experiments in molecular biology. Single-category enrichment analysis procedures such as Fisher's exact test tend to flag large numbers of redundant categories as significant, which can complicate interpretation. We have recently developed an approach called model-based gene set analysis (MGSA), that substantially reduces the number of redundant categories returned by the gene-category analysis. In this work, we present the Bioconductor package mgsa, which makes the MGSA algorithm available to users of the R language. Our package provides a simple and flexible application programming interface for applying the approach. The mgsa package has been made available as part of Bioconductor 2.8. It is released under the conditions of the Artistic license 2.0. peter.robinson@charite.de; julien.gagneur@embl.de.

Gene set analysis for interpreting genetic studies

DEFF Research Database (Denmark)

Pers, Tune H

2016-01-01

Interpretation of genome-wide association study (GWAS) results is lacking behind the discovery of new genetic associations. Consequently, there is an urgent need for data-driven methods for interpreting genetic association studies. Gene set analysis (GSA) can identify aetiologic pathways...

Structural modeling of the production quality as a multidimensional object of measurement and control

OpenAIRE

Зубрецкая, Наталья Анатольевна

2015-01-01

The structural-analytical models of product quality as a multidimensional process of evaluation, measurement and control are developed. The product quality is represented as a multi-factor, multi-criteria and multi-parameter estimation object. This structural formalization of quality demonstrates the multidimensional qualities: comprehensiveness due to a set of environmental factors; multicriteriality due collectively evaluated quality criteria; multiparameter information models that describe...

Genome-wide survey and developmental expression mapping of zebrafish SET domain-containing genes.

Directory of Open Access Journals (Sweden)

Xiao-Jian Sun

Full Text Available SET domain-containing proteins represent an evolutionarily conserved family of epigenetic regulators, which are responsible for most histone lysine methylation. Since some of these genes have been revealed to be essential for embryonic development, we propose that the zebrafish, a vertebrate model organism possessing many advantages for developmental studies, can be utilized to study the biological functions of these genes and the related epigenetic mechanisms during early development. To this end, we have performed a genome-wide survey of zebrafish SET domain genes. 58 genes total have been identified. Although gene duplication events give rise to several lineage-specific paralogs, clear reciprocal orthologous relationship reveals high conservation between zebrafish and human SET domain genes. These data were further subject to an evolutionary analysis ranging from yeast to human, leading to the identification of putative clusters of orthologous groups (COGs of this gene family. By means of whole-mount mRNA in situ hybridization strategy, we have also carried out a developmental expression mapping of these genes. A group of maternal SET domain genes, which are implicated in the programming of histone modification states in early development, have been identified and predicted to be responsible for all known sites of SET domain-mediated histone methylation. Furthermore, some genes show specific expression patterns in certain tissues at certain stages, suggesting the involvement of epigenetic mechanisms in the development of these systems. These results provide a global view of zebrafish SET domain histone methyltransferases in evolutionary and developmental dimensions and pave the way for using zebrafish to systematically study the roles of these genes during development.

A MULTIDIMENSIONAL AND MULTIPHYSICS APPROACH TO NUCLEAR FUEL BEHAVIOR SIMULATION

Energy Technology Data Exchange (ETDEWEB)

R. L. Williamson; J. D. Hales; S. R. Novascone; M. R. Tonks; D. R. Gaston; C. J. Permann; D. Andrs; R. C. Martineau

2012-04-01

Important aspects of fuel rod behavior, for example pellet-clad mechanical interaction (PCMI), fuel fracture, oxide formation, non-axisymmetric cooling, and response to fuel manufacturing defects, are inherently multidimensional in addition to being complicated multiphysics problems. Many current modeling tools are strictly 2D axisymmetric or even 1.5D. This paper outlines the capabilities of a new fuel modeling tool able to analyze either 2D axisymmetric or fully 3D models. These capabilities include temperature-dependent thermal conductivity of fuel; swelling and densification; fuel creep; pellet fracture; fission gas release; cladding creep; irradiation growth; and gap mechanics (contact and gap heat transfer). The need for multiphysics, multidimensional modeling is then demonstrated through a discussion of results for a set of example problems. The first, a 10-pellet rodlet, demonstrates the viability of the solution method employed. This example highlights the effect of our smeared cracking model and also shows the multidimensional nature of discrete fuel pellet modeling. The second example relies on our the multidimensional, multiphysics approach to analyze a missing pellet surface problem. As a final example, we show a lower-length-scale simulation coupled to a continuum-scale simulation.

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

Science.gov (United States)

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

Applied multidimensional scaling and unfolding

CERN Document Server

Borg, Ingwer; Mair, Patrick

2018-01-01

This book introduces multidimensional scaling (MDS) and unfolding as data analysis techniques for applied researchers. MDS is used for the analysis of proximity data on a set of objects, representing the data as distances between points in a geometric space (usually of two dimensions). Unfolding is a related method that maps preference data (typically evaluative ratings of different persons on a set of objects) as distances between two sets of points (representing the persons and the objects, resp.). This second edition has been completely revised to reflect new developments and the coverage of unfolding has also been substantially expanded. Intended for applied researchers whose main interests are in using these methods as tools for building substantive theories, it discusses numerous applications (classical and recent), highlights practical issues (such as evaluating model fit), presents ways to enforce theoretical expectations for the scaling solutions, and addresses the typical mistakes that MDS/unfoldin...

Multidimensional Models of Information Need

OpenAIRE

Yun-jie (Calvin) Xu; Kai Huang (Joseph) Tan

2009-01-01

User studies in information science have recognised relevance as a multidimensional construct. An implication of multidimensional relevance is that a user's information need should be modeled by multiple data structures to represent different relevance dimensions. While the extant literature has attempted to model multiple dimensions of a user's information need, the fundamental assumption that a multidimensional model is better than a uni-dimensional model has not been addressed. This study ...

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

Science.gov (United States)

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

Gene set of nuclear-encoded mitochondrial regulators is enriched for common inherited variation in obesity.

Directory of Open Access Journals (Sweden)

Nadja Knoll

Full Text Available There are hints of an altered mitochondrial function in obesity. Nuclear-encoded genes are relevant for mitochondrial function (3 gene sets of known relevant pathways: (1 16 nuclear regulators of mitochondrial genes, (2 91 genes for oxidative phosphorylation and (3 966 nuclear-encoded mitochondrial genes. Gene set enrichment analysis (GSEA showed no association with type 2 diabetes mellitus in these gene sets. Here we performed a GSEA for the same gene sets for obesity. Genome wide association study (GWAS data from a case-control approach on 453 extremely obese children and adolescents and 435 lean adult controls were used for GSEA. For independent confirmation, we analyzed 705 obesity GWAS trios (extremely obese child and both biological parents and a population-based GWAS sample (KORA F4, n = 1,743. A meta-analysis was performed on all three samples. In each sample, the distribution of significance levels between the respective gene set and those of all genes was compared using the leading-edge-fraction-comparison test (cut-offs between the 50(th and 95(th percentile of the set of all gene-wise corrected p-values as implemented in the MAGENTA software. In the case-control sample, significant enrichment of associations with obesity was observed above the 50(th percentile for the set of the 16 nuclear regulators of mitochondrial genes (p(GSEA,50 = 0.0103. This finding was not confirmed in the trios (p(GSEA,50 = 0.5991, but in KORA (p(GSEA,50 = 0.0398. The meta-analysis again indicated a trend for enrichment (p(MAGENTA,50 = 0.1052, p(MAGENTA,75 = 0.0251. The GSEA revealed that weak association signals for obesity might be enriched in the gene set of 16 nuclear regulators of mitochondrial genes.

Testlet-Based Multidimensional Adaptive Testing.

Science.gov (United States)

Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

2016-01-01

Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

Testlet-based Multidimensional Adaptive Testing

Directory of Open Access Journals (Sweden)

Andreas Frey

2016-11-01

Full Text Available Multidimensional adaptive testing (MAT is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT. MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, 1.5 and testlet sizes (3 items, 6 items, 9 items with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

Optimal structural inference of signaling pathways from unordered and overlapping gene sets.

Science.gov (United States)

Acharya, Lipi R; Judeh, Thair; Wang, Guangdi; Zhu, Dongxiao

2012-02-15

A plethora of bioinformatics analysis has led to the discovery of numerous gene sets, which can be interpreted as discrete measurements emitted from latent signaling pathways. Their potential to infer signaling pathway structures, however, has not been sufficiently exploited. Existing methods accommodating discrete data do not explicitly consider signal cascading mechanisms that characterize a signaling pathway. Novel computational methods are thus needed to fully utilize gene sets and broaden the scope from focusing only on pairwise interactions to the more general cascading events in the inference of signaling pathway structures. We propose a gene set based simulated annealing (SA) algorithm for the reconstruction of signaling pathway structures. A signaling pathway structure is a directed graph containing up to a few hundred nodes and many overlapping signal cascades, where each cascade represents a chain of molecular interactions from the cell surface to the nucleus. Gene sets in our context refer to discrete sets of genes participating in signal cascades, the basic building blocks of a signaling pathway, with no prior information about gene orderings in the cascades. From a compendium of gene sets related to a pathway, SA aims to search for signal cascades that characterize the optimal signaling pathway structure. In the search process, the extent of overlap among signal cascades is used to measure the optimality of a structure. Throughout, we treat gene sets as random samples from a first-order Markov chain model. We evaluated the performance of SA in three case studies. In the first study conducted on 83 KEGG pathways, SA demonstrated a significantly better performance than Bayesian network methods. Since both SA and Bayesian network methods accommodate discrete data, use a 'search and score' network learning strategy and output a directed network, they can be compared in terms of performance and computational time. In the second study, we compared SA and

Mechanism-based biomarker gene sets for glutathione depletion-related hepatotoxicity in rats

International Nuclear Information System (INIS)

Gao Weihua; Mizukawa, Yumiko; Nakatsu, Noriyuki; Minowa, Yosuke; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

2010-01-01

Chemical-induced glutathione depletion is thought to be caused by two types of toxicological mechanisms: PHO-type glutathione depletion [glutathione conjugated with chemicals such as phorone (PHO) or diethyl maleate (DEM)], and BSO-type glutathione depletion [i.e., glutathione synthesis inhibited by chemicals such as L-buthionine-sulfoximine (BSO)]. In order to identify mechanism-based biomarker gene sets for glutathione depletion in rat liver, male SD rats were treated with various chemicals including PHO (40, 120 and 400 mg/kg), DEM (80, 240 and 800 mg/kg), BSO (150, 450 and 1500 mg/kg), and bromobenzene (BBZ, 10, 100 and 300 mg/kg). Liver samples were taken 3, 6, 9 and 24 h after administration and examined for hepatic glutathione content, physiological and pathological changes, and gene expression changes using Affymetrix GeneChip Arrays. To identify differentially expressed probe sets in response to glutathione depletion, we focused on the following two courses of events for the two types of mechanisms of glutathione depletion: a) gene expression changes occurring simultaneously in response to glutathione depletion, and b) gene expression changes after glutathione was depleted. The gene expression profiles of the identified probe sets for the two types of glutathione depletion differed markedly at times during and after glutathione depletion, whereas Srxn1 was markedly increased for both types as glutathione was depleted, suggesting that Srxn1 is a key molecule in oxidative stress related to glutathione. The extracted probe sets were refined and verified using various compounds including 13 additional positive or negative compounds, and they established two useful marker sets. One contained three probe sets (Akr7a3, Trib3 and Gstp1) that could detect conjugation-type glutathione depletors any time within 24 h after dosing, and the other contained 14 probe sets that could detect glutathione depletors by any mechanism. These two sets, with appropriate scoring

MULTIDIMENSIONAL MODELING OF CORONAL RAIN DYNAMICS

Energy Technology Data Exchange (ETDEWEB)

Fang, X.; Xia, C.; Keppens, R. [Centre for mathematical Plasma Astrophysics, Department of Mathematics, KU Leuven, B-3001 Leuven (Belgium)

2013-07-10

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.

MULTIDIMENSIONAL MODELING OF CORONAL RAIN DYNAMICS

International Nuclear Information System (INIS)

Fang, X.; Xia, C.; Keppens, R.

2013-01-01

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.

Frost Multidimensional Perfectionism Scale: the portuguese version

Directory of Open Access Journals (Sweden)

Ana Paula Monteiro Amaral

2013-01-01

Full Text Available BACKGROUND: The Frost Multidimensional Perfectionism Scale is one of the most world widely used measures of perfectionism. OBJECTIVE: To analyze the psychometric properties of the Portuguese version of the Frost Multidimensional Perfectionism Scale. METHODS: Two hundred and seventeen (178 females students from two Portuguese Universities filled in the scale, and a subgroup (n = 166 completed a retest with a four weeks interval. RESULTS: The scale reliability was good (Cronbach alpha = .857. Corrected item-total correlations ranged from .019 to .548. The scale test-retest reliability suggested a good temporal stability with a test-retest correlation of .765. A principal component analysis with Varimax rotation was performed and based on the Scree plot, two robust factorial structures were found (four and six factors. The principal component analyses, using Monte Carlo PCA for parallel analyses confirmed the six factor solution. The concurrent validity with Hewitt and Flett MPS was high, as well as the discriminant validity of positive and negative affect (Profile of Mood Stats-POMS. DISCUSSION: The two factorial structures (of four and six dimensions of the Portuguese version of Frost Multidimensional Perfectionism Scale replicate the results from different authors, with different samples and cultures. This suggests this scale is a robust instrument to assess perfectionism, in several clinical and research settings as well as in transcultural studies.

Glutamatergic and GABAergic gene sets in attention-deficit/hyperactivity disorder

DEFF Research Database (Denmark)

Naaijen, Jill; Bralten, Janita; Poelmans, Geert

2017-01-01

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) often co-occur. Both are highly heritable; however, it has been difficult to discover genetic risk variants. Glutamate and GABA are main excitatory and inhibitory neurotransmitters in the brain; their balance...... within glutamatergic and GABAergic genes were investigated using the MAGMA software in an ADHD case-only sample (n=931), in which we assessed ASD symptoms and response inhibition on a Stop task. Gene set analysis for ADHD symptom severity, divided into inattention and hyperactivity/impulsivity symptoms...... is essential for proper brain development and functioning. In this study we investigated the role of glutamate and GABA genetics in ADHD severity, autism symptom severity and inhibitory performance, based on gene set analysis, an approach to investigate multiple genetic variants simultaneously. Common variants...

Applied multidimensional systems theory

CERN Document Server

Bose, Nirmal K

2017-01-01

Revised and updated, this concise new edition of the pioneering book on multidimensional signal processing is ideal for a new generation of students. Multidimensional systems or m-D systems are the necessary mathematical background for modern digital image processing with applications in biomedicine, X-ray technology and satellite communications. Serving as a firm basis for graduate engineering students and researchers seeking applications in mathematical theories, this edition eschews detailed mathematical theory not useful to students. Presentation of the theory has been revised to make it more readable for students, and introduce some new topics that are emerging as multidimensional DSP topics in the interdisciplinary fields of image processing. New topics include Groebner bases, wavelets, and filter banks.

SQL and Multidimensional Data

Directory of Open Access Journals (Sweden)

Mihaela MUNTEAN

2006-01-01

Full Text Available Using SQL you can manipulate multidimensional data and extract that data into a relational table. There are many PL/SQL packages that you can use directly in SQL*Plus or indirectly in Analytic Workspace Manager and OLAP Worksheet. In this article I discussed about some methods that you can use for manipulating and extracting multidimensional data.

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

Science.gov (United States)

Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

2016-03-01

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics

Successful Ageing and Multidimensional Poverty: The case of Peru

OpenAIRE

Olivera Angulo, Javier; Tournier, Isabelle

2016-01-01

This study investigated the determinants of Successful Ageing (SA) in a sample of 4,151 Peruvians aged between 65 and 80 years and living in poverty. A key contribution of this study is to combine the conceptual appeal of SA to measure well-being in old age with the multi-dimensional poverty counting approach developed in the economic literature. This setting allows for moving beyond the dichotomy of successful and usual ageing to take advantage of the full distribution of success along a set...

A PCA-Based Change Detection Framework for Multidimensional Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2015-08-10

Detecting changes in multidimensional data streams is an important and challenging task. In unsupervised change detection, changes are usually detected by comparing the distribution in a current (test) window with a reference window. It is thus essential to design divergence metrics and density estimators for comparing the data distributions, which are mostly done for univariate data. Detecting changes in multidimensional data streams brings difficulties to the density estimation and comparisons. In this paper, we propose a framework for detecting changes in multidimensional data streams based on principal component analysis, which is used for projecting data into a lower dimensional space, thus facilitating density estimation and change-score calculations. The proposed framework also has advantages over existing approaches by reducing computational costs with an efficient density estimator, promoting the change-score calculation by introducing effective divergence metrics, and by minimizing the efforts required from users on the threshold parameter setting by using the Page-Hinkley test. The evaluation results on synthetic and real data show that our framework outperforms two baseline methods in terms of both detection accuracy and computational costs.

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

Science.gov (United States)

Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed

Can survival prediction be improved by merging gene expression data sets?

Directory of Open Access Journals (Sweden)

Haleh Yasrebi

Full Text Available BACKGROUND: High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. RESULTS: Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. CONCLUSIONS: Merging did not deteriorate performance on average despite (a The diversity of microarray platforms used. (b The heterogeneity of patients cohorts. (c The heterogeneity of breast cancer disease. (d Substantial variation of time to death or relapse. (e The reduced number of genes in the merged data

The necessity-concerns framework: a multidimensional theory benefits from multidimensional analysis.

Science.gov (United States)

Phillips, L Alison; Diefenbach, Michael A; Kronish, Ian M; Negron, Rennie M; Horowitz, Carol R

2014-08-01

Patients' medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). We use polynomial regression to assess the multidimensional effect of stroke-event survivors' medication-related concerns and necessity beliefs on their adherence to stroke-prevention medication. Survivors (n = 600) rated their concerns, necessity beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. As posited by the necessity-concerns framework (NCF), the greatest and lowest adherence was reported by those necessity weak concerns and strong concerns/weak Necessity-Beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites.

Multi-dimensional imaging

CERN Document Server

Javidi, Bahram; Andres, Pedro

2014-01-01

Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field Multi-dimensional Imaging takes the reader from the introductory concepts through to the latest applications of these techniques. Split into 3 parts covering 3D image capture, processing, visualization and display, using 1) a Multi-View Approach and 2.) a Holographic Approach, followed by a 3rd part addressing other 3D systems approaches, applications and signal processing for advanced 3D imaging. This book describes recent developments, as well as the prospects and

CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.

Science.gov (United States)

Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua

2018-03-01

In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and

Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

Science.gov (United States)

Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

2014-05-01

Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

Science.gov (United States)

Rellán-Álvarez, Rubén; Lobet, Guillaume; Lindner, Heike; Pradier, Pierre-Luc; Sebastian, Jose; Yee, Muh-Ching; Geng, Yu; Trontin, Charlotte; LaRue, Therese; Schrager-Lavelle, Amanda; Haney, Cara H; Nieu, Rita; Maloof, Julin; Vogel, John P; Dinneny, José R

2015-01-01

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001 PMID:26287479

Adaptive Multidimensional Scaling : The Spatial Representation of Brand Consideration and Dissimilarity Judgments

NARCIS (Netherlands)

Bijmolt, T.H.A.; Wedel, M.; DeSarbo, W.S.

2002-01-01

We propose Adaptive Multidimensional Scaling (AMDS) for simultaneously deriving a brand map and market segments using consumer data on cognitive decision sets and brand dissimilarities.In AMDS, the judgment task is adapted to the individual respondent: dissimilarity judgments are collected only for

The West Haven-Yale Multidimensional Pain Inventory (WHYMPI).

Science.gov (United States)

Kerns, R D; Turk, D C; Rudy, T E

1985-12-01

The complexity of chronic pain has represented a major dilemma for clinical researchers interested in the reliable and valid assessment of the problem and the evaluation of treatment approaches. The West Haven-Yale Multidimensional Pain Inventory (WHYMPI) was developed in order to fill a widely recognized void in the assessment of clinical pain. Assets of the inventory are its brevity and clarity, its foundation in contemporary psychological theory, its multidimensional focus, and its strong psychometric properties. Three parts of the inventory, comprised of 12 scales, examine the impact of pain on the patients' lives, the responses of others to the patients' communications of pain, and the extent to which patients participate in common daily activities. The instrument is recommended for use in conjunction with behavioral and psychophysiological assessment strategies in the evaluation of chronic pain patients in clinical settings. The utility of the WHYMPI in empirical investigations of chronic pain is also discussed.

Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra

KAUST Repository

Cannistraci, Carlo Vittorio

2015-01-26

Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet\\'s performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis.

Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra

KAUST Repository

Cannistraci, Carlo Vittorio; Abbas, Ahmed; Gao, Xin

2015-01-01

Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet's performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis.

The Necessity-Concerns-Framework: A Multidimensional Theory Benefits from Multidimensional Analysis

Science.gov (United States)

Phillips, L. Alison; Diefenbach, Michael; Kronish, Ian M.; Negron, Rennie M.; Horowitz, Carol R.

2014-01-01

Background Patients’ medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). Purpose We use polynomial regression to assess the multidimensional effect of stroke-event survivors’ medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication. Methods Survivors (n=600) rated their concerns, necessity-beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. Results As posited by the Necessity-Concerns Framework (NCF), the greatest and lowest adherence was reported by those with strong necessity-beliefs/weak concerns and strong concerns/weak necessity-beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Conclusions Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites. PMID:24500078

On simplified application of multidimensional Savitzky-Golay filters and differentiators

Science.gov (United States)

Shekhar, Chandra

2016-02-01

I propose a simplified approach for multidimensional Savitzky-Golay filtering, to enable its fast and easy implementation in scientific and engineering applications. The proposed method, which is derived from a generalized framework laid out by Thornley (D. J. Thornley, "Novel anisotropic multidimensional convolution filters for derivative estimation and reconstruction" in Proceedings of International Conference on Signal Processing and Communications, November 2007), first transforms any given multidimensional problem into a unique one, by transforming coordinates of the sampled data nodes to unity-spaced, uniform data nodes, and then performs filtering and calculates partial derivatives on the unity-spaced nodes. It is followed by transporting the calculated derivatives back onto the original data nodes by using the chain rule of differentiation. The burden to performing the most cumbersome task, which is to carry out the filtering and to obtain derivatives on the unity-spaced nodes, is almost eliminated by providing convolution coefficients for a number of convolution kernel sizes and polynomial orders, up to four spatial dimensions. With the availability of the convolution coefficients, the task of filtering at a data node reduces merely to multiplication of two known matrices. Simplified strategies to adequately address near-boundary data nodes and to calculate partial derivatives there are also proposed. Finally, the proposed methodologies are applied to a three-dimensional experimentally obtained data set, which shows that multidimensional Savitzky-Golay filters and differentiators perform well in both the internal and the near-boundary regions of the domain.

Gene set-based module discovery in the breast cancer transcriptome

Directory of Open Access Journals (Sweden)

Zhang Michael Q

2009-02-01

Full Text Available Abstract Background Although microarray-based studies have revealed global view of gene expression in cancer cells, we still have little knowledge about regulatory mechanisms underlying the transcriptome. Several computational methods applied to yeast data have recently succeeded in identifying expression modules, which is defined as co-expressed gene sets under common regulatory mechanisms. However, such module discovery methods are not applied cancer transcriptome data. Results In order to decode oncogenic regulatory programs in cancer cells, we developed a novel module discovery method termed EEM by extending a previously reported module discovery method, and applied it to breast cancer expression data. Starting from seed gene sets prepared based on cis-regulatory elements, ChIP-chip data, and gene locus information, EEM identified 10 principal expression modules in breast cancer based on their expression coherence. Moreover, EEM depicted their activity profiles, which predict regulatory programs in each subtypes of breast tumors. For example, our analysis revealed that the expression module regulated by the Polycomb repressive complex 2 (PRC2 is downregulated in triple negative breast cancers, suggesting similarity of transcriptional programs between stem cells and aggressive breast cancer cells. We also found that the activity of the PRC2 expression module is negatively correlated to the expression of EZH2, a component of PRC2 which belongs to the E2F expression module. E2F-driven EZH2 overexpression may be responsible for the repression of the PRC2 expression modules in triple negative tumors. Furthermore, our network analysis predicts regulatory circuits in breast cancer cells. Conclusion These results demonstrate that the gene set-based module discovery approach is a powerful tool to decode regulatory programs in cancer cells.

On fully multidimensional and high order non oscillatory finite volume methods, I

International Nuclear Information System (INIS)

Lafon, F.

1992-11-01

A fully multidimensional flux formulation for solving nonlinear conservation laws of hyperbolic type is introduced to perform calculations on unstructured grids made of triangular or quadrangular cells. Fluxes are computed across dual median cells with a multidimensional 2D Riemann Solver (R2D Solver) whose intermediate states depend on either a three (on triangle R2DT solver) of four (on quadrangle, R2DQ solver) state solutions prescribed on the three or four sides of a gravity cell. Approximate Riemann solutions are computed via a linearization process of Roe's type involving multidimensional effects. Moreover, a monotonous scheme using stencil and central Lax-Friedrichs corrections on sonic curves are built in. Finally, high order accurate ENO-like (Essentially Non Oscillatory) reconstructions using plane and higher degree polynomial limitations are defined in the set up of finite element Lagrange spaces P k and Q k for k≥0, on triangles and quadrangles, respectively. Numerical experiments involving both linear and nonlinear conservation laws to be solved on unstructured grids indicate the ability of our techniques when dealing with strong multidimensional effects. An application to Euler's equations for the Mach three step problem illustrates the robustness and usefulness of our techniques using triangular and quadrangular grids. (Author). 33 refs., 13 figs

Multidimensional epidemic thresholds in diffusion processes over interdependent networks

International Nuclear Information System (INIS)

Salehi, Mostafa; Siyari, Payam; Magnani, Matteo; Montesi, Danilo

2015-01-01

Highlights: •We propose a new concept of multidimensional epidemic threshold for interdependent networks. •We analytically derive and numerically illustrate the conditions for multilayer epidemics. •We study the evolution of infection density and diffusion dynamics. -- Abstract: Several systems can be modeled as sets of interdependent networks where each network contains distinct nodes. Diffusion processes like the spreading of a disease or the propagation of information constitute fundamental phenomena occurring over such coupled networks. In this paper we propose a new concept of multidimensional epidemic threshold characterizing diffusion processes over interdependent networks, allowing different diffusion rates on the different networks and arbitrary degree distributions. We analytically derive and numerically illustrate the conditions for multilayer epidemics, i.e., the appearance of a giant connected component spanning all the networks. Furthermore, we study the evolution of infection density and diffusion dynamics with extensive simulation experiments on synthetic and real networks

Multidimensional singular integrals and integral equations

CERN Document Server

Mikhlin, Solomon Grigorievich; Stark, M; Ulam, S

1965-01-01

Multidimensional Singular Integrals and Integral Equations presents the results of the theory of multidimensional singular integrals and of equations containing such integrals. Emphasis is on singular integrals taken over Euclidean space or in the closed manifold of Liapounov and equations containing such integrals. This volume is comprised of eight chapters and begins with an overview of some theorems on linear equations in Banach spaces, followed by a discussion on the simplest properties of multidimensional singular integrals. Subsequent chapters deal with compounding of singular integrals

The null hypothesis of GSEA, and a novel statistical model for competitive gene set analysis

DEFF Research Database (Denmark)

Debrabant, Birgit

2017-01-01

MOTIVATION: Competitive gene set analysis intends to assess whether a specific set of genes is more associated with a trait than the remaining genes. However, the statistical models assumed to date to underly these methods do not enable a clear cut formulation of the competitive null hypothesis....... This is a major handicap to the interpretation of results obtained from a gene set analysis. RESULTS: This work presents a hierarchical statistical model based on the notion of dependence measures, which overcomes this problem. The two levels of the model naturally reflect the modular structure of many gene set...... analysis methods. We apply the model to show that the popular GSEA method, which recently has been claimed to test the self-contained null hypothesis, actually tests the competitive null if the weight parameter is zero. However, for this result to hold strictly, the choice of the dependence measures...

Constellation Map: Downstream visualization and interpretation of gene set enrichment results [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Yan Tan

2015-06-01

Full Text Available Summary: Gene set enrichment analysis (GSEA approaches are widely used to identify coordinately regulated genes associated with phenotypes of interest. Here, we present Constellation Map, a tool to visualize and interpret the results when enrichment analyses yield a long list of significantly enriched gene sets. Constellation Map identifies commonalities that explain the enrichment of multiple top-scoring gene sets and maps the relationships between them. Constellation Map can help investigators take full advantage of GSEA and facilitates the biological interpretation of enrichment results. Availability: Constellation Map is freely available as a GenePattern module at http://www.genepattern.org.

The Role of a Multidimensional Concept of Trust in the Performance of Global Virtual Teams

Science.gov (United States)

Bodensteiner, Nan Muir; Stecklein, Jonette M.

2002-01-01

This paper focuses on the concept of trust as an important ingredient of effective global virtual team performance. Definitions of trust and virtual teams are presented. The concept of trust is developed from its unilateral application (trust, absence of trust) to a multidimensional concept including cognitive and affective components. The special challenges of a virtual team are then discussed with particular emphasis on how a multidimensional concept of trust impacts these challenges. Propositions suggesting the multidimensional concept of trust moderates the negative impacts of distance, cross cultural and organizational differences, the effects of electronically mediated communication, reluctance to share information and a lack of hi story/future on the performance of virtual teams are stated. The paper concludes with recommendations and a set of techniques to build both cognitive and affective trust in virtual teams.

Development and assessment of Multi-dimensional flow models in the thermal-hydraulic system analysis code MARS

Energy Technology Data Exchange (ETDEWEB)

Chung, B. D.; Bae, S. W.; Jeong, J. J.; Lee, S. M

2005-04-15

A new multi-dimensional component has been developed to allow for more flexible 3D capabilities in the system code, MARS. This component can be applied in the Cartesian and cylindrical coordinates. For the development of this model, the 3D convection and diffusion terms are implemented in the momentum and energy equation. And a simple Prandtl's mixing length model is applied for the turbulent viscosity. The developed multi-dimensional component was assessed against five conceptual problems with analytic solution. And some SETs are calculated and compared with experimental data. With this newly developed multi-dimensional flow module, the MARS code can realistic calculate the flow fields in pools such as those occurring in the core, steam generators and IRWST.

Development and assessment of Multi-dimensional flow models in the thermal-hydraulic system analysis code MARS

International Nuclear Information System (INIS)

Chung, B. D.; Bae, S. W.; Jeong, J. J.; Lee, S. M.

2005-04-01

A new multi-dimensional component has been developed to allow for more flexible 3D capabilities in the system code, MARS. This component can be applied in the Cartesian and cylindrical coordinates. For the development of this model, the 3D convection and diffusion terms are implemented in the momentum and energy equation. And a simple Prandtl's mixing length model is applied for the turbulent viscosity. The developed multi-dimensional component was assessed against five conceptual problems with analytic solution. And some SETs are calculated and compared with experimental data. With this newly developed multi-dimensional flow module, the MARS code can realistic calculate the flow fields in pools such as those occurring in the core, steam generators and IRWST

Multidimensional Riemann problem with self-similar internal structure - part III - a multidimensional analogue of the HLLI Riemann solver for conservative hyperbolic systems

Science.gov (United States)

Balsara, Dinshaw S.; Nkonga, Boniface

2017-10-01

Just as the quality of a one-dimensional approximate Riemann solver is improved by the inclusion of internal sub-structure, the quality of a multidimensional Riemann solver is also similarly improved. Such multidimensional Riemann problems arise when multiple states come together at the vertex of a mesh. The interaction of the resulting one-dimensional Riemann problems gives rise to a strongly-interacting state. We wish to endow this strongly-interacting state with physically-motivated sub-structure. The fastest way of endowing such sub-structure consists of making a multidimensional extension of the HLLI Riemann solver for hyperbolic conservation laws. Presenting such a multidimensional analogue of the HLLI Riemann solver with linear sub-structure for use on structured meshes is the goal of this work. The multidimensional MuSIC Riemann solver documented here is universal in the sense that it can be applied to any hyperbolic conservation law. The multidimensional Riemann solver is made to be consistent with constraints that emerge naturally from the Galerkin projection of the self-similar states within the wave model. When the full eigenstructure in both directions is used in the present Riemann solver, it becomes a complete Riemann solver in a multidimensional sense. I.e., all the intermediate waves are represented in the multidimensional wave model. The work also presents, for the very first time, an important analysis of the dissipation characteristics of multidimensional Riemann solvers. The present Riemann solver results in the most efficient implementation of a multidimensional Riemann solver with sub-structure. Because it preserves stationary linearly degenerate waves, it might also help with well-balancing. Implementation-related details are presented in pointwise fashion for the one-dimensional HLLI Riemann solver as well as the multidimensional MuSIC Riemann solver.

Multidimensional Data Model and Query Language for Informetrics.

Science.gov (United States)

Niemi, Timo; Hirvonen, Lasse; Jarvelin, Kalervo

2003-01-01

Discusses multidimensional data analysis, or online analytical processing (OLAP), which offer a single subject-oriented source for analyzing summary data based on various dimensions. Develops a conceptual/logical multidimensional model for supporting the needs of informetrics, including a multidimensional query language whose basic idea is to…

Visualizing information across multidimensional post-genomic structured and textual databases.

Science.gov (United States)

Tao, Ying; Friedman, Carol; Lussier, Yves A

2005-04-15

Visualizing relationships among biological information to facilitate understanding is crucial to biological research during the post-genomic era. Although different systems have been developed to view gene-phenotype relationships for specific databases, very few have been designed specifically as a general flexible tool for visualizing multidimensional genotypic and phenotypic information together. Our goal is to develop a method for visualizing multidimensional genotypic and phenotypic information and a model that unifies different biological databases in order to present the integrated knowledge using a uniform interface. We developed a novel, flexible and generalizable visualization tool, called PhenoGenesviewer (PGviewer), which in this paper was used to display gene-phenotype relationships from a human-curated database (OMIM) and from an automatic method using a Natural Language Processing tool called BioMedLEE. Data obtained from multiple databases were first integrated into a uniform structure and then organized by PGviewer. PGviewer provides a flexible query interface that allows dynamic selection and ordering of any desired dimension in the databases. Based on users' queries, results can be visualized using hierarchical expandable trees that present views specified by users according to their research interests. We believe that this method, which allows users to dynamically organize and visualize multiple dimensions, is a potentially powerful and promising tool that should substantially facilitate biological research. PhenogenesViewer as well as its support and tutorial are available at http://www.dbmi.columbia.edu/pgviewer/ Lussier@dbmi.columbia.edu.

Using OWL reasoning to support the generation of novel gene sets for enrichment analysis.

Science.gov (United States)

Osumi-Sutherland, David J; Ponta, Enrico; Courtot, Melanie; Parkinson, Helen; Badi, Laura

2018-02-14

The Gene Ontology (GO) consists of over 40,000 terms for biological processes, cell components and gene product activities linked into a graph structure by over 90,000 relationships. It has been used to annotate the functions and cellular locations of several million gene products. The graph structure is used by a variety of tools to group annotated genes into sets whose products share function or location. These gene sets are widely used to interpret the results of genomics experiments by assessing which sets are significantly over- or under-represented in results lists. F Hoffmann-La Roche Ltd. has developed a bespoke, manually maintained controlled vocabulary (RCV) for use in over-representation analysis. Many terms in this vocabulary group GO terms in novel ways that cannot easily be derived using the graph structure of the GO. For example, some RCV terms group GO terms by the cell, chemical or tissue type they refer to. Recent improvements in the content and formal structure of the GO make it possible to use logical queries in Web Ontology Language (OWL) to automatically map these cross-cutting classifications to sets of GO terms. We used this approach to automate mapping between RCV and GO, largely replacing the increasingly unsustainable manual mapping process. We then tested the utility of the resulting groupings for over-representation analysis. We successfully mapped 85% of RCV terms to logical OWL definitions and showed that these could be used to recapitulate and extend manual mappings between RCV terms and the sets of GO terms subsumed by them. We also show that gene sets derived from the resulting GO terms sets can be used to detect the signatures of cell and tissue types in whole genome expression data. The rich formal structure of the GO makes it possible to use reasoning to dynamically generate novel, biologically relevant groupings of GO terms. GO term groupings generated with this approach can be used in. over-representation analysis to detect

Developing a Multi-Dimensional Evaluation Framework for Faculty Teaching and Service Performance

Science.gov (United States)

Baker, Diane F.; Neely, Walter P.; Prenshaw, Penelope J.; Taylor, Patrick A.

2015-01-01

A task force was created in a small, AACSB-accredited business school to develop a more comprehensive set of standards for faculty performance. The task force relied heavily on faculty input to identify and describe key dimensions that capture effective teaching and service performance. The result is a multi-dimensional framework that will be used…

Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

Science.gov (United States)

de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

2010-01-01

We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

Multidimensional poverty, household environment and short-term morbidity in India.

Science.gov (United States)

Dehury, Bidyadhar; Mohanty, Sanjay K

2017-01-01

Using the unit data from the second round of the Indian Human Development Survey (IHDS-II), 2011-2012, which covered 42,152 households, this paper examines the association between multidimensional poverty, household environmental deprivation and short-term morbidities (fever, cough and diarrhoea) in India. Poverty is measured in a multidimensional framework that includes the dimensions of education, health and income, while household environmental deprivation is defined as lack of access to improved sanitation, drinking water and cooking fuel. A composite index combining multidimensional poverty and household environmental deprivation has been computed, and households are classified as follows: multidimensional poor and living in a poor household environment, multidimensional non-poor and living in a poor household environment, multidimensional poor and living in a good household environment and multidimensional non-poor and living in a good household environment. Results suggest that about 23% of the population belonging to multidimensional poor households and living in a poor household environment had experienced short-term morbidities in a reference period of 30 days compared to 20% of the population belonging to multidimensional non-poor households and living in a poor household environment, 19% of the population belonging to multidimensional poor households and living in a good household environment and 15% of the population belonging to multidimensional non-poor households and living in a good household environment. Controlling for socioeconomic covariates, the odds of short-term morbidity was 1.47 [CI 1.40-1.53] among the multidimensional poor and living in a poor household environment, 1.28 [CI 1.21-1.37] among the multidimensional non-poor and living in a poor household environment and 1.21 [CI 1.64-1.28] among the multidimensional poor and living in a good household environment compared to the multidimensional non-poor and living in a good household

A cross-study gene set enrichment analysis identifies critical pathways in endometriosis

Directory of Open Access Journals (Sweden)

Bai Chunyan

2009-09-01

Full Text Available Abstract Background Endometriosis is an enigmatic disease. Gene expression profiling of endometriosis has been used in several studies, but few studies went further to classify subtypes of endometriosis based on expression patterns and to identify possible pathways involved in endometriosis. Some of the observed pathways are more inconsistent between the studies, and these candidate pathways presumably only represent a fraction of the pathways involved in endometriosis. Methods We applied a standardised microarray preprocessing and gene set enrichment analysis to six independent studies, and demonstrated increased concordance between these gene datasets. Results We find 16 up-regulated and 19 down-regulated pathways common in ovarian endometriosis data sets, 22 up-regulated and one down-regulated pathway common in peritoneal endometriosis data sets. Among them, 12 up-regulated and 1 down-regulated were found consistent between ovarian and peritoneal endometriosis. The main canonical pathways identified are related to immunological and inflammatory disease. Early secretory phase has the most over-represented pathways in the three uterine cycle phases. There are no overlapping significant pathways between the dataset from human endometrial endothelial cells and the datasets from ovarian endometriosis which used whole tissues. Conclusion The study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. By standardised microarray preprocessing and GSEA, we have increased the concordance in identifying many biological mechanisms involved in endometriosis. The identified gene pathways will shed light on the understanding of endometriosis and promote the development of novel therapies.

Multidimensional quantum entanglement with large-scale integrated optics.

Science.gov (United States)

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong; Santagati, Raffaele; Skrzypczyk, Paul; Salavrakos, Alexia; Tura, Jordi; Augusiak, Remigiusz; Mančinska, Laura; Bacco, Davide; Bonneau, Damien; Silverstone, Joshua W; Gong, Qihuang; Acín, Antonio; Rottwitt, Karsten; Oxenløwe, Leif K; O'Brien, Jeremy L; Laing, Anthony; Thompson, Mark G

2018-04-20

The ability to control multidimensional quantum systems is central to the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control, and analyze high-dimensional entanglement. A programmable bipartite entangled system is realized with dimensions up to 15 × 15 on a large-scale silicon photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality, and controllability of our multidimensional technology, and further exploit these abilities to demonstrate previously unexplored quantum applications, such as quantum randomness expansion and self-testing on multidimensional states. Our work provides an experimental platform for the development of multidimensional quantum technologies. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

GSHR, a Web-Based Platform Provides Gene Set-Level Analyses of Hormone Responses in Arabidopsis

Directory of Open Access Journals (Sweden)

Xiaojuan Ran

2018-01-01

Full Text Available Phytohormones regulate diverse aspects of plant growth and environmental responses. Recent high-throughput technologies have promoted a more comprehensive profiling of genes regulated by different hormones. However, these omics data generally result in large gene lists that make it challenging to interpret the data and extract insights into biological significance. With the rapid accumulation of theses large-scale experiments, especially the transcriptomic data available in public databases, a means of using this information to explore the transcriptional networks is needed. Different platforms have different architectures and designs, and even similar studies using the same platform may obtain data with large variances because of the highly dynamic and flexible effects of plant hormones; this makes it difficult to make comparisons across different studies and platforms. Here, we present a web server providing gene set-level analyses of Arabidopsis thaliana hormone responses. GSHR collected 333 RNA-seq and 1,205 microarray datasets from the Gene Expression Omnibus, characterizing transcriptomic changes in Arabidopsis in response to phytohormones including abscisic acid, auxin, brassinosteroids, cytokinins, ethylene, gibberellins, jasmonic acid, salicylic acid, and strigolactones. These data were further processed and organized into 1,368 gene sets regulated by different hormones or hormone-related factors. By comparing input gene lists to these gene sets, GSHR helped to identify gene sets from the input gene list regulated by different phytohormones or related factors. Together, GSHR links prior information regarding transcriptomic changes induced by hormones and related factors to newly generated data and facilities cross-study and cross-platform comparisons; this helps facilitate the mining of biologically significant information from large-scale datasets. The GSHR is freely available at http://bioinfo.sibs.ac.cn/GSHR/.

Multidimensional Poverty and Child Survival in India

Science.gov (United States)

Mohanty, Sanjay K.

2011-01-01

Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384

Multidimensional poverty and child survival in India.

Directory of Open Access Journals (Sweden)

Sanjay K Mohanty

Full Text Available Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses.The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed.Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

Multidimensional poverty and child survival in India.

Science.gov (United States)

Mohanty, Sanjay K

2011-01-01

Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

The emergence and evolution of the multidimensional organization

OpenAIRE

Strikwerda, J.; Stoelhorst, J.W.

2009-01-01

The article discusses multidimensional organizations and the evolution of complex organizations. The six characteristics of multidimensional organizations, disadvantages of the successful organizational structure that is categorized as a multidivisional, multi-unit or M-form, research by the Foundation for Management Studies which suggests that synergies across business divisions can be exploited by the M-form, a team approach to creating economic value, examples of multidimensional firms suc...

Identification of a conserved set of upregulated genes in mouse skeletal muscle hypertrophy and regrowth.

Science.gov (United States)

Chaillou, Thomas; Jackson, Janna R; England, Jonathan H; Kirby, Tyler J; Richards-White, Jena; Esser, Karyn A; Dupont-Versteegden, Esther E; McCarthy, John J

2015-01-01

The purpose of this study was to compare the gene expression profile of mouse skeletal muscle undergoing two forms of growth (hypertrophy and regrowth) with the goal of identifying a conserved set of differentially expressed genes. Expression profiling by microarray was performed on the plantaris muscle subjected to 1, 3, 5, 7, 10, and 14 days of hypertrophy or regrowth following 2 wk of hind-limb suspension. We identified 97 differentially expressed genes (≥2-fold increase or ≥50% decrease compared with control muscle) that were conserved during the two forms of muscle growth. The vast majority (∼90%) of the differentially expressed genes was upregulated and occurred at a single time point (64 out of 86 genes), which most often was on the first day of the time course. Microarray analysis from the conserved upregulated genes showed a set of genes related to contractile apparatus and stress response at day 1, including three genes involved in mechanotransduction and four genes encoding heat shock proteins. Our analysis further identified three cell cycle-related genes at day and several genes associated with extracellular matrix (ECM) at both days 3 and 10. In conclusion, we have identified a core set of genes commonly upregulated in two forms of muscle growth that could play a role in the maintenance of sarcomere stability, ECM remodeling, cell proliferation, fast-to-slow fiber type transition, and the regulation of skeletal muscle growth. These findings suggest conserved regulatory mechanisms involved in the adaptation of skeletal muscle to increased mechanical loading. Copyright © 2015 the American Physiological Society.

Fundamentals of applied multidimensional scaling for educational and psychological research

CERN Document Server

Ding, Cody S

2018-01-01

This book explores the fundamentals of multidimensional scaling (MDS) and how this analytic method can be used in applied setting for educational and psychological research. The book tries to make MDS more accessible to a wider audience in terms of the language and examples that are more relevant to educational and psychological research and less technical so that the readers are not overwhelmed by equations. The goal is for readers to learn the methods described in this book and immediately start using MDS via available software programs. The book also examines new applications that have previously not been discussed in MDS literature. It should be an ideal book for graduate students and researchers to better understand MDS. Fundamentals of Applied Multidimensional Scaling for Educational and Psychological Research is divided into three parts. Part I covers the basic and fundamental features of MDS models pertaining to applied research applications. Chapters in this section cover the essential features of da...

DNMT1 is associated with cell cycle and DNA replication gene sets in diffuse large B-cell lymphoma.

Science.gov (United States)

Loo, Suet Kee; Ab Hamid, Suzina Sheikh; Musa, Mustaffa; Wong, Kah Keng

2018-01-01

Dysregulation of DNA (cytosine-5)-methyltransferase 1 (DNMT1) is associated with the pathogenesis of various types of cancer. It has been previously shown that DNMT1 is frequently expressed in diffuse large B-cell lymphoma (DLBCL), however its functions remain to be elucidated in the disease. In this study, we gene expression profiled (GEP) shRNA targeting DNMT1(shDNMT1)-treated germinal center B-cell-like DLBCL (GCB-DLBCL)-derived cell line (i.e. HT) compared with non-silencing shRNA (control shRNA)-treated HT cells. Independent gene set enrichment analysis (GSEA) performed using GEPs of shRNA-treated HT cells and primary GCB-DLBCL cases derived from two publicly-available datasets (i.e. GSE10846 and GSE31312) produced three separate lists of enriched gene sets for each gene sets collection from Molecular Signatures Database (MSigDB). Subsequent Venn analysis identified 268, 145 and six consensus gene sets from analyzing gene sets in C2 collection (curated gene sets), C5 sub-collection [gene sets from gene ontology (GO) biological process ontology] and Hallmark collection, respectively to be enriched in positive correlation with DNMT1 expression profiles in shRNA-treated HT cells, GSE10846 and GSE31312 datasets [false discovery rate (FDR) 0.8) with DNMT1 expression and significantly downregulated (log fold-change <-1.35; p<0.05) following DNMT1 silencing in HT cells. These results suggest the involvement of DNMT1 in the activation of cell cycle and DNA replication in DLBCL cells. Copyright © 2017 Elsevier GmbH. All rights reserved.

Multidimensional family therapy lowers the rate of cannabis dependence in adolescents: A randomised controlled trial in Western European outpatient settings

NARCIS (Netherlands)

H. Rigter (Henk); C.E. Henderson (Craig); I. Pelc (Isidore); P. Tossmann (Peter); O. Phan (Olivier); V. Hendriks (Vincent); M. Schaub (Michael); C. Rowe (Cindy)

2013-01-01

textabstractBackground: Noticing a lack of evidence-based programmes for treating adolescents heavily using cannabis in Europe, government representatives from Belgium, France, Germany, The Netherlands, and Switzerland decided to have U.S.-developed multidimensional family therapy (MDFT) tested in

Structure of multidimensional patterns

International Nuclear Information System (INIS)

Smith, S.P.

1982-01-01

The problem of describing the structure of multidimensional data is important in exploratory data analysis, statistical pattern recognition, and image processing. A data set is viewed as a collection of points embedded in a high dimensional space. The primary goal of this research is to determine if the data have any clustering structure; such a structure implies the presence of class information (categories) in the data. A statistical hypothesis is used in the decision making. To this end, data with no structure are defined as data following the uniform distribution over some compact convex set in K-dimensional space, called the sampling window. This thesis defines two new tests for uniformity along with various sampling window estimators. The first test is a volume-based test which captures density changes in the data. The second test compares a uniformly distributed sample to the data by using the minimal spanning tree (MST) of the polled samples. Sampling window estimators are provided for simple sampling windows and use the convex hull of the data as a general sampling window estimator. For both of the tests for uniformity, theoretical results are provided on their size, and study their size and power against clustered alternatives is studied. Simulation is also used to study the efficacy of the sampling window estimators

A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

Science.gov (United States)

Newton, Richard; Wernisch, Lorenz

2014-01-01

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

Multidimensional fatigue and its correlates in hospitalised advanced cancer patients.

NARCIS (Netherlands)

Echteld, M.A.; Passchier, J.; Teunissen, S.; Claessen, S.; Wit, R. de; Rijt, C.C.D. van der

2007-01-01

Although fatigue is a multidimensional concept, multidimensional fatigue is rarely investigated in hospitalised cancer patients. We determined the levels and correlates of multidimensional fatigue in 100 advanced cancer patients admitted for symptom control. Fatigue dimensions were general fatigue

Identification of a set of genes showing regionally enriched expression in the mouse brain

Directory of Open Access Journals (Sweden)

Marra Marco A

2008-07-01

Full Text Available Abstract Background The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters ( Results We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Conclusion Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

Developing Multi-Dimensional Evaluation Criteria for English Learning Websites with University Students and Professors

Science.gov (United States)

Liu, Gi-Zen; Liu, Zih-Hui; Hwang, Gwo-Jen

2011-01-01

Many English learning websites have been developed worldwide, but little research has been conducted concerning the development of comprehensive evaluation criteria. The main purpose of this study is thus to construct a multi-dimensional set of criteria to help learners and teachers evaluate the quality of English learning websites. These…

The SET1 Complex Selects Actively Transcribed Target Genes via Multivalent Interaction with CpG Island Chromatin

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David A. Brown

2017-09-01

Full Text Available Chromatin modifications and the promoter-associated epigenome are important for the regulation of gene expression. However, the mechanisms by which chromatin-modifying complexes are targeted to the appropriate gene promoters in vertebrates and how they influence gene expression have remained poorly defined. Here, using a combination of live-cell imaging and functional genomics, we discover that the vertebrate SET1 complex is targeted to actively transcribed gene promoters through CFP1, which engages in a form of multivalent chromatin reading that involves recognition of non-methylated DNA and histone H3 lysine 4 trimethylation (H3K4me3. CFP1 defines SET1 complex occupancy on chromatin, and its multivalent interactions are required for the SET1 complex to place H3K4me3. In the absence of CFP1, gene expression is perturbed, suggesting that normal targeting and function of the SET1 complex are central to creating an appropriately functioning vertebrate promoter-associated epigenome.

Genome-Wide Temporal Expression Profiling in Caenorhabditis elegans Identifies a Core Gene Set Related to Long-Term Memory.

Science.gov (United States)

Freytag, Virginie; Probst, Sabine; Hadziselimovic, Nils; Boglari, Csaba; Hauser, Yannick; Peter, Fabian; Gabor Fenyves, Bank; Milnik, Annette; Demougin, Philippe; Vukojevic, Vanja; de Quervain, Dominique J-F; Papassotiropoulos, Andreas; Stetak, Attila

2017-07-12

The identification of genes related to encoding, storage, and retrieval of memories is a major interest in neuroscience. In the current study, we analyzed the temporal gene expression changes in a neuronal mRNA pool during an olfactory long-term associative memory (LTAM) in Caenorhabditis elegans hermaphrodites. Here, we identified a core set of 712 (538 upregulated and 174 downregulated) genes that follows three distinct temporal peaks demonstrating multiple gene regulation waves in LTAM. Compared with the previously published positive LTAM gene set (Lakhina et al., 2015), 50% of the identified upregulated genes here overlap with the previous dataset, possibly representing stimulus-independent memory-related genes. On the other hand, the remaining genes were not previously identified in positive associative memory and may specifically regulate aversive LTAM. Our results suggest a multistep gene activation process during the formation and retrieval of long-term memory and define general memory-implicated genes as well as conditioning-type-dependent gene sets. SIGNIFICANCE STATEMENT The identification of genes regulating different steps of memory is of major interest in neuroscience. Identification of common memory genes across different learning paradigms and the temporal activation of the genes are poorly studied. Here, we investigated the temporal aspects of Caenorhabditis elegans gene expression changes using aversive olfactory associative long-term memory (LTAM) and identified three major gene activation waves. Like in previous studies, aversive LTAM is also CREB dependent, and CREB activity is necessary immediately after training. Finally, we define a list of memory paradigm-independent core gene sets as well as conditioning-dependent genes. Copyright © 2017 the authors 0270-6474/17/376661-12$15.00/0.

Tracking difference in gene expression in a time-course experiment using gene set enrichment analysis.

Directory of Open Access Journals (Sweden)

Pui Shan Wong

Full Text Available Fistulifera sp. strain JPCC DA0580 is a newly sequenced pennate diatom that is capable of simultaneously growing and accumulating lipids. This is a unique trait, not found in other related microalgae so far. It is able to accumulate between 40 to 60% of its cell weight in lipids, making it a strong candidate for the production of biofuel. To investigate this characteristic, we used RNA-Seq data gathered at four different times while Fistulifera sp. strain JPCC DA0580 was grown in oil accumulating and non-oil accumulating conditions. We then adapted gene set enrichment analysis (GSEA to investigate the relationship between the difference in gene expression of 7,822 genes and metabolic functions in our data. We utilized information in the KEGG pathway database to create the gene sets and changed GSEA to use re-sampling so that data from the different time points could be included in the analysis. Our GSEA method identified photosynthesis, lipid synthesis and amino acid synthesis related pathways as processes that play a significant role in oil production and growth in Fistulifera sp. strain JPCC DA0580. In addition to GSEA, we visualized the results by creating a network of compounds and reactions, and plotted the expression data on top of the network. This made existing graph algorithms available to us which we then used to calculate a path that metabolizes glucose into triacylglycerol (TAG in the smallest number of steps. By visualizing the data this way, we observed a separate up-regulation of genes at different times instead of a concerted response. We also identified two metabolic paths that used less reactions than the one shown in KEGG and showed that the reactions were up-regulated during the experiment. The combination of analysis and visualization methods successfully analyzed time-course data, identified important metabolic pathways and provided new hypotheses for further research.

Symbolic Multidimensional Scaling

NARCIS (Netherlands)

P.J.F. Groenen (Patrick); Y. Terada

2015-01-01

markdownabstract__Abstract__ Multidimensional scaling (MDS) is a technique that visualizes dissimilarities between pairs of objects as distances between points in a low dimensional space. In symbolic MDS, a dissimilarity is not just a value but can represent an interval or even a histogram. Here,

Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods

Science.gov (United States)

Väremo, Leif; Nielsen, Jens; Nookaew, Intawat

2013-01-01

Gene set analysis (GSA) is used to elucidate genome-wide data, in particular transcriptome data. A multitude of methods have been proposed for this step of the analysis, and many of them have been compared and evaluated. Unfortunately, there is no consolidated opinion regarding what methods should be preferred, and the variety of available GSA software and implementations pose a difficulty for the end-user who wants to try out different methods. To address this, we have developed the R package Piano that collects a range of GSA methods into the same system, for the benefit of the end-user. Further on we refine the GSA workflow by using modifications of the gene-level statistics. This enables us to divide the resulting gene set P-values into three classes, describing different aspects of gene expression directionality at gene set level. We use our fully implemented workflow to investigate the impact of the individual components of GSA by using microarray and RNA-seq data. The results show that the evaluated methods are globally similar and the major separation correlates well with our defined directionality classes. As a consequence of this, we suggest to use a consensus scoring approach, based on multiple GSA runs. In combination with the directionality classes, this constitutes a more thorough basis for an enriched biological interpretation. PMID:23444143

An Improved Multidimensional MPA Procedure for Bidirectional Earthquake Excitations

OpenAIRE

Wang, Feng; Sun, Jian-Gang; Zhang, Ning

2014-01-01

Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA) method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two compone...

The emergence and evolution of the multidimensional organization

NARCIS (Netherlands)

Strikwerda, J.; Stoelhorst, J.W.

2009-01-01

The article discusses multidimensional organizations and the evolution of complex organizations. The six characteristics of multidimensional organizations, disadvantages of the successful organizational structure that is categorized as a multidivisional, multi-unit or M-form, research by the

Perceptual Salience and Children's Multidimensional Problem Solving

Science.gov (United States)

Odom, Richard D.; Corbin, David W.

1973-01-01

Uni- and multidimensional processing of 6- to 9-year olds was studied using recall tasks in which an array of stimuli was reconstructed to match a model array. Results indicated that both age groups were able to solve multidimensional problems, but that solution rate was retarded by the unidimensional processing of highly salient dimensions.…

Multidimensional Measurement of Poverty among Women in Sub-Saharan Africa

Science.gov (United States)

Batana, Yele Maweki

2013-01-01

Since the seminal work of Sen, poverty has been recognized as a multidimensional phenomenon. The recent availability of relevant databases renewed the interest in this approach. This paper estimates multidimensional poverty among women in fourteen Sub-Saharan African countries using the Alkire and Foster multidimensional poverty measures, whose…

Application of multidimensional IRT models to longitudinal data

NARCIS (Netherlands)

te Marvelde, J.M.; Glas, Cornelis A.W.; Van Landeghem, Georges; Van Damme, Jan

2006-01-01

The application of multidimensional item response theory (IRT) models to longitudinal educational surveys where students are repeatedly measured is discussed and exemplified. A marginal maximum likelihood (MML) method to estimate the parameters of a multidimensional generalized partial credit model

The SET1 Complex Selects Actively Transcribed Target Genes via Multivalent Interaction with CpG Island Chromatin.

Science.gov (United States)

Brown, David A; Di Cerbo, Vincenzo; Feldmann, Angelika; Ahn, Jaewoo; Ito, Shinsuke; Blackledge, Neil P; Nakayama, Manabu; McClellan, Michael; Dimitrova, Emilia; Turberfield, Anne H; Long, Hannah K; King, Hamish W; Kriaucionis, Skirmantas; Schermelleh, Lothar; Kutateladze, Tatiana G; Koseki, Haruhiko; Klose, Robert J

2017-09-05

Chromatin modifications and the promoter-associated epigenome are important for the regulation of gene expression. However, the mechanisms by which chromatin-modifying complexes are targeted to the appropriate gene promoters in vertebrates and how they influence gene expression have remained poorly defined. Here, using a combination of live-cell imaging and functional genomics, we discover that the vertebrate SET1 complex is targeted to actively transcribed gene promoters through CFP1, which engages in a form of multivalent chromatin reading that involves recognition of non-methylated DNA and histone H3 lysine 4 trimethylation (H3K4me3). CFP1 defines SET1 complex occupancy on chromatin, and its multivalent interactions are required for the SET1 complex to place H3K4me3. In the absence of CFP1, gene expression is perturbed, suggesting that normal targeting and function of the SET1 complex are central to creating an appropriately functioning vertebrate promoter-associated epigenome. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Multidimensional sexual perfectionism.

Science.gov (United States)

Stoeber, Joachim; Harvey, Laura N; Almeida, Isabel; Lyons, Emma

2013-11-01

Perfectionism is a multidimensional personality characteristic that can affect all areas of life. This article presents the first systematic investigation of multidimensional perfectionism in the domain of sexuality exploring the unique relationships that different forms of sexual perfectionism show with positive and negative aspects of sexuality. A sample of 272 university students (52 male, 220 female) completed measures of four forms of sexual perfectionism: self-oriented, partner-oriented, partner-prescribed, and socially prescribed. In addition, they completed measures of sexual esteem, sexual self-efficacy, sexual optimism, sex life satisfaction (capturing positive aspects of sexuality) and sexual problem self-blame, sexual anxiety, sexual depression, and negative sexual perfectionism cognitions during sex (capturing negative aspects). Results showed unique patterns of relationships for the four forms of sexual perfectionism, suggesting that partner-prescribed and socially prescribed sexual perfectionism are maladaptive forms of sexual perfectionism associated with negative aspects of sexuality whereas self-oriented and partner-oriented sexual perfectionism emerged as ambivalent forms associated with positive and negative aspects.

Multidimensional real analysis I differentiation

CERN Document Server

Duistermaat, J J; van Braam Houckgeest, J P

2004-01-01

Part one of the authors' comprehensive and innovative work on multidimensional real analysis. This book is based on extensive teaching experience at Utrecht University and gives a thorough account of differential analysis in multidimensional Euclidean space. It is an ideal preparation for students who wish to go on to more advanced study. The notation is carefully organized and all proofs are clean, complete and rigorous. The authors have taken care to pay proper attention to all aspects of the theory. In many respects this book presents an original treatment of the subject and it contains man

Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm

Directory of Open Access Journals (Sweden)

Lei Zhang

2016-01-01

Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.

Multidimensional flamelet-generated manifolds for partially premixed combustion

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Phuc-Danh; Vervisch, Luc; Subramanian, Vallinayagam; Domingo, Pascale [CORIA - CNRS and INSA de Rouen, Technopole du Madrillet, BP 8, 76801 Saint-Etienne-du-Rouvray (France)

2010-01-15

Flamelet-generated manifolds have been restricted so far to premixed or diffusion flame archetypes, even though the resulting tables have been applied to nonpremixed and partially premixed flame simulations. By using a projection of the full set of mass conservation species balance equations into a restricted subset of the composition space, unsteady multidimensional flamelet governing equations are derived from first principles, under given hypotheses. During the projection, as in usual one-dimensional flamelets, the tangential strain rate of scalar isosurfaces is expressed in the form of the scalar dissipation rates of the control parameters of the multidimensional flamelet-generated manifold (MFM), which is tested in its five-dimensional form for partially premixed combustion, with two composition space directions and three scalar dissipation rates. It is shown that strain-rate-induced effects can hardly be fully neglected in chemistry tabulation of partially premixed combustion, because of fluxes across iso-equivalence-ratio and iso-progress-of-reaction surfaces. This is illustrated by comparing the 5D flamelet-generated manifold with one-dimensional premixed flame and unsteady strained diffusion flame composition space trajectories. The formal links between the asymptotic behavior of MFM and stratified flame, weakly varying partially premixed front, triple-flame, premixed and nonpremixed edge flames are also evidenced. (author)

Glutamatergic and GABAergic gene sets in attention-deficit/hyperactivity disorder: association to overlapping traits in ADHD and autism.

Science.gov (United States)

Naaijen, J; Bralten, J; Poelmans, G; Glennon, J C; Franke, B; Buitelaar, J K

2017-01-10

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) often co-occur. Both are highly heritable; however, it has been difficult to discover genetic risk variants. Glutamate and GABA are main excitatory and inhibitory neurotransmitters in the brain; their balance is essential for proper brain development and functioning. In this study we investigated the role of glutamate and GABA genetics in ADHD severity, autism symptom severity and inhibitory performance, based on gene set analysis, an approach to investigate multiple genetic variants simultaneously. Common variants within glutamatergic and GABAergic genes were investigated using the MAGMA software in an ADHD case-only sample (n=931), in which we assessed ASD symptoms and response inhibition on a Stop task. Gene set analysis for ADHD symptom severity, divided into inattention and hyperactivity/impulsivity symptoms, autism symptom severity and inhibition were performed using principal component regression analyses. Subsequently, gene-wide association analyses were performed. The glutamate gene set showed an association with severity of hyperactivity/impulsivity (P=0.009), which was robust to correcting for genome-wide association levels. The GABA gene set showed nominally significant association with inhibition (P=0.04), but this did not survive correction for multiple comparisons. None of single gene or single variant associations was significant on their own. By analyzing multiple genetic variants within candidate gene sets together, we were able to find genetic associations supporting the involvement of excitatory and inhibitory neurotransmitter systems in ADHD and ASD symptom severity in ADHD.

Multidimensional splines for modeling FET nonlinearities

Energy Technology Data Exchange (ETDEWEB)

Barby, J A

1986-01-01

Circuit simulators like SPICE and timing simulators like MOTIS are used extensively for critical path verification of integrated circuits. MOSFET model evaluation dominates the run time of these simulators. Changes in technology results in costly updates, since modifications require reprogramming of the functions and their derivatives. The computational cost of MOSFET models can be reduced by using multidimensional polynomial splines. Since simulators based on the Newton Raphson algorithm require the function and first derivative, quadratic splines are sufficient for this purpose. The cost of updating the MOSFET model due to technology changes is greatly reduced since splines are derived from a set of points. Crucial for convergence speed of simulators is the fact that MOSFET characteristic equations are monotonic. This must be maintained by any simulation model. The splines the author designed do maintain monotonicity.

Shrinkage covariance matrix approach based on robust trimmed mean in gene sets detection

Science.gov (United States)

Karjanto, Suryaefiza; Ramli, Norazan Mohamed; Ghani, Nor Azura Md; Aripin, Rasimah; Yusop, Noorezatty Mohd

2015-02-01

Microarray involves of placing an orderly arrangement of thousands of gene sequences in a grid on a suitable surface. The technology has made a novelty discovery since its development and obtained an increasing attention among researchers. The widespread of microarray technology is largely due to its ability to perform simultaneous analysis of thousands of genes in a massively parallel manner in one experiment. Hence, it provides valuable knowledge on gene interaction and function. The microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints. Therefore, the sample covariance matrix in Hotelling's T2 statistic is not positive definite and become singular, thus it cannot be inverted. In this research, the Hotelling's T2 statistic is combined with a shrinkage approach as an alternative estimation to estimate the covariance matrix to detect significant gene sets. The use of shrinkage covariance matrix overcomes the singularity problem by converting an unbiased to an improved biased estimator of covariance matrix. Robust trimmed mean is integrated into the shrinkage matrix to reduce the influence of outliers and consequently increases its efficiency. The performance of the proposed method is measured using several simulation designs. The results are expected to outperform existing techniques in many tested conditions.

Fuzzy Clustering based Methodology for Multidimensional Data Analysis in Computational Forensic Domain

OpenAIRE

Kilian Stoffel; Paul Cotofrei; Dong Han

2012-01-01

As interdisciplinary domain requiring advanced and innovative methodologies the computational forensics domain is characterized by data being simultaneously large scaled and uncertain multidimensional and approximate. Forensic domain experts trained to discover hidden pattern from crime data are limited in their analysis without the assistance of a computational intelligence approach. In this paper a methodology and an automatic procedure based on fuzzy set theory and designed to infer precis...

A multidimensional subdiffusion model: An arbitrage-free market

International Nuclear Information System (INIS)

Li Guo-Hua; Zhang Hong; Luo Mao-Kang

2012-01-01

To capture the subdiffusive characteristics of financial markets, the subordinated process, directed by the inverse α-stale subordinator S α (t) for 0 < α < 1, has been employed as the model of asset prices. In this article, we introduce a multidimensional subdiffusion model that has a bond and K correlated stocks. The stock price process is a multidimensional subdiffusion process directed by the inverse α-stable subordinator. This model describes the period of stagnation for each stock and the behavior of the dependency between multiple stocks. Moreover, we derive the multidimensional fractional backward Kolmogorov equation for the subordinated process using the Laplace transform technique. Finally, using a martingale approach, we prove that the multidimensional subdiffusion model is arbitrage-free, and also gives an arbitrage-free pricing rule for contingent claims associated with the martingale measure. (interdisciplinary physics and related areas of science and technology)

Intervene: a tool for intersection and visualization of multiple gene or genomic region sets.

Science.gov (United States)

Khan, Aziz; Mathelier, Anthony

2017-05-31

A common task for scientists relies on comparing lists of genes or genomic regions derived from high-throughput sequencing experiments. While several tools exist to intersect and visualize sets of genes, similar tools dedicated to the visualization of genomic region sets are currently limited. To address this gap, we have developed the Intervene tool, which provides an easy and automated interface for the effective intersection and visualization of genomic region or list sets, thus facilitating their analysis and interpretation. Intervene contains three modules: venn to generate Venn diagrams of up to six sets, upset to generate UpSet plots of multiple sets, and pairwise to compute and visualize intersections of multiple sets as clustered heat maps. Intervene, and its interactive web ShinyApp companion, generate publication-quality figures for the interpretation of genomic region and list sets. Intervene and its web application companion provide an easy command line and an interactive web interface to compute intersections of multiple genomic and list sets. They have the capacity to plot intersections using easy-to-interpret visual approaches. Intervene is developed and designed to meet the needs of both computer scientists and biologists. The source code is freely available at https://bitbucket.org/CBGR/intervene , with the web application available at https://asntech.shinyapps.io/intervene .

Multi-dimensional Laplace transforms and applications

International Nuclear Information System (INIS)

Mughrabi, T.A.

1988-01-01

In this dissertation we establish new theorems for computing certain types of multidimensional Laplace transform pairs from known one-dimensional Laplace transforms. The theorems are applied to the most commonly used special functions and so we obtain many two and three dimensional Laplace transform pairs. As applications, some boundary value problems involving linear partial differential equations are solved by the use of multi-dimensional Laplace transformation. Also we establish some relations between the Laplace transformation and other integral transformation in two variables

Multi-dimensional virtual system introduced to enhance canonical sampling

Science.gov (United States)

Higo, Junichi; Kasahara, Kota; Nakamura, Haruki

2017-10-01

When an important process of a molecular system occurs via a combination of two or more rare events, which occur almost independently to one another, computational sampling for the important process is difficult. Here, to sample such a process effectively, we developed a new method, named the "multi-dimensional Virtual-system coupled Monte Carlo (multi-dimensional-VcMC)" method, where the system interacts with a virtual system expressed by two or more virtual coordinates. Each virtual coordinate controls sampling along a reaction coordinate. By setting multiple reaction coordinates to be related to the corresponding rare events, sampling of the important process can be enhanced. An advantage of multi-dimensional-VcMC is its simplicity: Namely, the conformation moves widely in the multi-dimensional reaction coordinate space without knowledge of canonical distribution functions of the system. To examine the effectiveness of the algorithm, we introduced a toy model where two molecules (receptor and its ligand) bind and unbind to each other. The receptor has a deep binding pocket, to which the ligand enters for binding. Furthermore, a gate is set at the entrance of the pocket, and the gate is usually closed. Thus, the molecular binding takes place via the two events: ligand approach to the pocket and gate opening. In two-dimensional (2D)-VcMC, the two molecules exhibited repeated binding and unbinding, and an equilibrated distribution was obtained as expected. A conventional canonical simulation, which was 200 times longer than 2D-VcMC, failed in sampling the binding/unbinding effectively. The current method is applicable to various biological systems.

Exploring Children's Face-Space: A Multidimensional Scaling Analysis of the Mental Representation of Facial Identity

Science.gov (United States)

Nishimura, Mayu; Maurer, Daphne; Gao, Xiaoqing

2009-01-01

We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an "odd-man-out" paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces…

Contributions to multidimensional quadrature formulas

International Nuclear Information System (INIS)

Guenther, C.

1976-11-01

The general objective of this paper is to construct multidimensional quadrature formulas similar to the Gaussian Quadrature Formulas in one dimension. The correspondence between these formulas and orthogonal and nonnegative polynomials is established. One part of the paper considers the construction of multidimensional quadrature formulas using only methods of algebraic geometry, on the other part it is tried to obtain results on quadrature formulas with real nodes and, if possible, with positive weights. The results include the existence of quadrature formulas, information on the number resp. on the maximum possible number of points in the formulas for given polynomial degree N and the construction of formulas. (orig.) [de

A multi-dimensional sampling method for locating small scatterers

International Nuclear Information System (INIS)

Song, Rencheng; Zhong, Yu; Chen, Xudong

2012-01-01

A multiple signal classification (MUSIC)-like multi-dimensional sampling method (MDSM) is introduced to locate small three-dimensional scatterers using electromagnetic waves. The indicator is built with the most stable part of signal subspace of the multi-static response matrix on a set of combinatorial sampling nodes inside the domain of interest. It has two main advantages compared to the conventional MUSIC methods. First, the MDSM is more robust against noise. Second, it can work with a single incidence even for multi-scatterers. Numerical simulations are presented to show the good performance of the proposed method. (paper)

Supervised and Unsupervised Learning of Multidimensional Acoustic Categories

Science.gov (United States)

Goudbeek, Martijn; Swingley, Daniel; Smits, Roel

2009-01-01

Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…

Minimal models of multidimensional computations.

Directory of Open Access Journals (Sweden)

Jeffrey D Fitzgerald

2011-03-01

Full Text Available The multidimensional computations performed by many biological systems are often characterized with limited information about the correlations between inputs and outputs. Given this limitation, our approach is to construct the maximum noise entropy response function of the system, leading to a closed-form and minimally biased model consistent with a given set of constraints on the input/output moments; the result is equivalent to conditional random field models from machine learning. For systems with binary outputs, such as neurons encoding sensory stimuli, the maximum noise entropy models are logistic functions whose arguments depend on the constraints. A constraint on the average output turns the binary maximum noise entropy models into minimum mutual information models, allowing for the calculation of the information content of the constraints and an information theoretic characterization of the system's computations. We use this approach to analyze the nonlinear input/output functions in macaque retina and thalamus; although these systems have been previously shown to be responsive to two input dimensions, the functional form of the response function in this reduced space had not been unambiguously identified. A second order model based on the logistic function is found to be both necessary and sufficient to accurately describe the neural responses to naturalistic stimuli, accounting for an average of 93% of the mutual information with a small number of parameters. Thus, despite the fact that the stimulus is highly non-Gaussian, the vast majority of the information in the neural responses is related to first and second order correlations. Our results suggest a principled and unbiased way to model multidimensional computations and determine the statistics of the inputs that are being encoded in the outputs.

Macro-level drivers of multidimensional poverty in sub-Saharan Africa: Explaining change in the Human Poverty Index

Directory of Open Access Journals (Sweden)

Heath Prince

2014-12-01

Full Text Available Poverty is increasingly recognised as a multidimensional phenomenon in the development literature, encompassing not only income, but also a range of factors related to broadening an individual’s freedoms to live a life of their own choosing. Poverty so understood suggests that alternative approaches to poverty measurement reflecting this multidimensionality may point towards alternative policies for poverty alleviation. The imperative to reinforce pro-poor policy development in sub-Saharan Africa with evaluation findings that reflect improvements in well-being, rather than solely improvements in national economies, has become self-evident as, despite decades of market-led development policies, much of the subcontinent remains mired in deprivation. As recognised by the 2014 African Evaluation Association’s biannual conference, fresh thinking and new evaluation metrics are required in order to create policies that more effectively increase well-being. This article explores the factors that may account for changes in one metric of multidimensional poverty in developing countries, the United Nation Development Program’s Human Poverty Index (HPI, and will be primarily concerned with measuring the effects on the HPI of policies and activities that relate to, or are explicitly meant to encourage, economic growth, increased literacy and improved health. The study focuses on the outcomes of a panel data set, created for the purpose of this study, of HPI scores for a set of 47 sub-Saharan countries, between 1990 and 2010, and a range of indicators that the development literature and theory suggest should have an effect on income poverty, asking, what is the relationship between these indicators and multidimensional poverty? A parallel set of models has been developed to measure the response of household consumption expenditure to changes in economic growth and human capabilities indicators. All models are estimated using fixed effects estimators and

Evaluation of endogenous control genes for gene expression studies across multiple tissues and in the specific sets of fat- and muscle-type samples of the pig.

Science.gov (United States)

Gu, Y R; Li, M Z; Zhang, K; Chen, L; Jiang, A A; Wang, J Y; Li, X W

2011-08-01

To normalize a set of quantitative real-time PCR (q-PCR) data, it is essential to determine an optimal number/set of housekeeping genes, as the abundance of housekeeping genes can vary across tissues or cells during different developmental stages, or even under certain environmental conditions. In this study, of the 20 commonly used endogenous control genes, 13, 18 and 17 genes exhibited credible stability in 56 different tissues, 10 types of adipose tissue and five types of muscle tissue, respectively. Our analysis clearly showed that three optimal housekeeping genes are adequate for an accurate normalization, which correlated well with the theoretical optimal number (r ≥ 0.94). In terms of economical and experimental feasibility, we recommend the use of the three most stable housekeeping genes for calculating the normalization factor. Based on our results, the three most stable housekeeping genes in all analysed samples (TOP2B, HSPCB and YWHAZ) are recommended for accurate normalization of q-PCR data. We also suggest that two different sets of housekeeping genes are appropriate for 10 types of adipose tissue (the HSPCB, ALDOA and GAPDH genes) and five types of muscle tissue (the TOP2B, HSPCB and YWHAZ genes), respectively. Our report will serve as a valuable reference for other studies aimed at measuring tissue-specific mRNA abundance in porcine samples. © 2011 Blackwell Verlag GmbH.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds.

Science.gov (United States)

Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav

2016-01-01

The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.

Benchmarking the Multidimensional Stellar Implicit Code MUSIC

Science.gov (United States)

Goffrey, T.; Pratt, J.; Viallet, M.; Baraffe, I.; Popov, M. V.; Walder, R.; Folini, D.; Geroux, C.; Constantino, T.

2017-04-01

We present the results of a numerical benchmark study for the MUltidimensional Stellar Implicit Code (MUSIC) based on widely applicable two- and three-dimensional compressible hydrodynamics problems relevant to stellar interiors. MUSIC is an implicit large eddy simulation code that uses implicit time integration, implemented as a Jacobian-free Newton Krylov method. A physics based preconditioning technique which can be adjusted to target varying physics is used to improve the performance of the solver. The problems used for this benchmark study include the Rayleigh-Taylor and Kelvin-Helmholtz instabilities, and the decay of the Taylor-Green vortex. Additionally we show a test of hydrostatic equilibrium, in a stellar environment which is dominated by radiative effects. In this setting the flexibility of the preconditioning technique is demonstrated. This work aims to bridge the gap between the hydrodynamic test problems typically used during development of numerical methods and the complex flows of stellar interiors. A series of multidimensional tests were performed and analysed. Each of these test cases was analysed with a simple, scalar diagnostic, with the aim of enabling direct code comparisons. As the tests performed do not have analytic solutions, we verify MUSIC by comparing it to established codes including ATHENA and the PENCIL code. MUSIC is able to both reproduce behaviour from established and widely-used codes as well as results expected from theoretical predictions. This benchmarking study concludes a series of papers describing the development of the MUSIC code and provides confidence in future applications.

Transcriptome-wide selection of a reliable set of reference genes for gene expression studies in potato cyst nematodes (Globodera spp.).

Science.gov (United States)

Sabeh, Michael; Duceppe, Marc-Olivier; St-Arnaud, Marc; Mimee, Benjamin

2018-01-01

Relative gene expression analyses by qRT-PCR (quantitative reverse transcription PCR) require an internal control to normalize the expression data of genes of interest and eliminate the unwanted variation introduced by sample preparation. A perfect reference gene should have a constant expression level under all the experimental conditions. However, the same few housekeeping genes selected from the literature or successfully used in previous unrelated experiments are often routinely used in new conditions without proper validation of their stability across treatments. The advent of RNA-Seq and the availability of public datasets for numerous organisms are opening the way to finding better reference genes for expression studies. Globodera rostochiensis is a plant-parasitic nematode that is particularly yield-limiting for potato. The aim of our study was to identify a reliable set of reference genes to study G. rostochiensis gene expression. Gene expression levels from an RNA-Seq database were used to identify putative reference genes and were validated with qRT-PCR analysis. Three genes, GR, PMP-3, and aaRS, were found to be very stable within the experimental conditions of this study and are proposed as reference genes for future work.

Mining tissue specificity, gene connectivity and disease association to reveal a set of genes that modify the action of disease causing genes

Directory of Open Access Journals (Sweden)

Reverter Antonio

2008-09-01

Full Text Available Abstract Background The tissue specificity of gene expression has been linked to a number of significant outcomes including level of expression, and differential rates of polymorphism, evolution and disease association. Recent studies have also shown the importance of exploring differential gene connectivity and sequence conservation in the identification of disease-associated genes. However, no study relates gene interactions with tissue specificity and disease association. Methods We adopted an a priori approach making as few assumptions as possible to analyse the interplay among gene-gene interactions with tissue specificity and its subsequent likelihood of association with disease. We mined three large datasets comprising expression data drawn from massively parallel signature sequencing across 32 tissues, describing a set of 55,606 true positive interactions for 7,197 genes, and microarray expression results generated during the profiling of systemic inflammation, from which 126,543 interactions among 7,090 genes were reported. Results Amongst the myriad of complex relationships identified between expression, disease, connectivity and tissue specificity, some interesting patterns emerged. These include elevated rates of expression and network connectivity in housekeeping and disease-associated tissue-specific genes. We found that disease-associated genes are more likely to show tissue specific expression and most frequently interact with other disease genes. Using the thresholds defined in these observations, we develop a guilt-by-association algorithm and discover a group of 112 non-disease annotated genes that predominantly interact with disease-associated genes, impacting on disease outcomes. Conclusion We conclude that parameters such as tissue specificity and network connectivity can be used in combination to identify a group of genes, not previously confirmed as disease causing, that are involved in interactions with disease causing

Using Variable Precision Rough Set for Selection and Classification of Biological Knowledge Integrated in DNA Gene Expression

Directory of Open Access Journals (Sweden)

Calvo-Dmgz D.

2012-12-01

Full Text Available DNA microarrays have contributed to the exponential growth of genomic and experimental data in the last decade. This large amount of gene expression data has been used by researchers seeking diagnosis of diseases like cancer using machine learning methods. In turn, explicit biological knowledge about gene functions has also grown tremendously over the last decade. This work integrates explicit biological knowledge, provided as gene sets, into the classication process by means of Variable Precision Rough Set Theory (VPRS. The proposed model is able to highlight which part of the provided biological knowledge has been important for classification. This paper presents a novel model for microarray data classification which is able to incorporate prior biological knowledge in the form of gene sets. Based on this knowledge, we transform the input microarray data into supergenes, and then we apply rough set theory to select the most promising supergenes and to derive a set of easy interpretable classification rules. The proposed model is evaluated over three breast cancer microarrays datasets obtaining successful results compared to classical classification techniques. The experimental results shows that there are not significat differences between our model and classical techniques but it is able to provide a biological-interpretable explanation of how it classifies new samples.

Influence of fusion dynamics on fission observables: A multidimensional analysis

Science.gov (United States)

Schmitt, C.; Mazurek, K.; Nadtochy, P. N.

2018-01-01

An attempt to unfold the respective influence of the fusion and fission stages on typical fission observables, and namely the neutron prescission multiplicity, is proposed. A four-dimensional dynamical stochastic Langevin model is used to calculate the decay by fission of excited compound nuclei produced in a wide set of heavy-ion collisions. The comparison of the results from such a calculation and experimental data is discussed, guided by predictions of the dynamical deterministic HICOL code for the compound-nucleus formation time. While the dependence of the latter on the entrance-channel properties can straigthforwardly explain some observations, a complex interplay between the various parameters of the reaction is found to occur in other cases. A multidimensional analysis of the respective role of these parameters, including entrance-channel asymmetry, bombarding energy, compound-nucleus fissility, angular momentum, and excitation energy, is proposed. It is shown that, depending on the size of the system, apparent inconsistencies may be deduced when projecting onto specific ordering parameters. The work suggests the possibility of delicate compensation effects in governing the measured fission observables, thereby highlighting the necessity of a multidimensional discussion.

Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset

Directory of Open Access Journals (Sweden)

Jihye Kim

2013-09-01

Full Text Available Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underlying these traits. Based on the previously published single nucleotide polymorphism (SNP genotype data on 8,842 individuals enrolled in the Korea Association Resource project, we performed a series of systematic genome-wide association analyses for 49 quantitative traits of basic epidemiological, anthropometric, or blood chemistry parameters. Each analysis result was subjected to subsequent gene set analyses based on Gene Ontology (GO terms using gene set analysis software, GSA-SNP, identifying a set of GO terms significantly associated to each trait (pcorr < 0.05. Pairwise comparison of the traits in terms of the semantic similarity in their GO sets revealed surprising cases where phenotypically uncorrelated traits showed high similarity in terms of biological pathways. For example, the pH level was related to 7 other traits that showed low phenotypic correlations with it. A literature survey implies that these traits may be regulated partly by common pathways that involve neuronal or nerve systems.

Devaney chaos, Li-Yorke chaos, and multi-dimensional Li-Yorke chaos for topological dynamics

Science.gov (United States)

Dai, Xiongping; Tang, Xinjia

2017-11-01

Let π : T × X → X, written T↷π X, be a topological semiflow/flow on a uniform space X with T a multiplicative topological semigroup/group not necessarily discrete. We then prove: If T↷π X is non-minimal topologically transitive with dense almost periodic points, then it is sensitive to initial conditions. As a result of this, Devaney chaos ⇒ Sensitivity to initial conditions, for this very general setting. Let R+↷π X be a C0-semiflow on a Polish space; then we show: If R+↷π X is topologically transitive with at least one periodic point p and there is a dense orbit with no nonempty interior, then it is multi-dimensional Li-Yorke chaotic; that is, there is a uncountable set Θ ⊆ X such that for any k ≥ 2 and any distinct points x1 , … ,xk ∈ Θ, one can find two time sequences sn → ∞ ,tn → ∞ with Moreover, let X be a non-singleton Polish space; then we prove: Any weakly-mixing C0-semiflow R+↷π X is densely multi-dimensional Li-Yorke chaotic. Any minimal weakly-mixing topological flow T↷π X with T abelian is densely multi-dimensional Li-Yorke chaotic. Any weakly-mixing topological flow T↷π X is densely Li-Yorke chaotic. We in addition construct a completely Li-Yorke chaotic minimal SL (2 , R)-acting flow on the compact metric space R ∪ { ∞ }. Our various chaotic dynamics are sensitive to the choices of the topology of the phase semigroup/group T.

OsiriX: an open-source software for navigating in multidimensional DICOM images.

Science.gov (United States)

Rosset, Antoine; Spadola, Luca; Ratib, Osman

2004-09-01

A multidimensional image navigation and display software was designed for display and interpretation of large sets of multidimensional and multimodality images such as combined PET-CT studies. The software is developed in Objective-C on a Macintosh platform under the MacOS X operating system using the GNUstep development environment. It also benefits from the extremely fast and optimized 3D graphic capabilities of the OpenGL graphic standard widely used for computer games optimized for taking advantage of any hardware graphic accelerator boards available. In the design of the software special attention was given to adapt the user interface to the specific and complex tasks of navigating through large sets of image data. An interactive jog-wheel device widely used in the video and movie industry was implemented to allow users to navigate in the different dimensions of an image set much faster than with a traditional mouse or on-screen cursors and sliders. The program can easily be adapted for very specific tasks that require a limited number of functions, by adding and removing tools from the program's toolbar and avoiding an overwhelming number of unnecessary tools and functions. The processing and image rendering tools of the software are based on the open-source libraries ITK and VTK. This ensures that all new developments in image processing that could emerge from other academic institutions using these libraries can be directly ported to the OsiriX program. OsiriX is provided free of charge under the GNU open-source licensing agreement at http://homepage.mac.com/rossetantoine/osirix.

Compositional models for credal sets

Czech Academy of Sciences Publication Activity Database

Vejnarová, Jiřina

2017-01-01

Roč. 90, č. 1 (2017), s. 359-373 ISSN 0888-613X R&D Projects: GA ČR(CZ) GA16-12010S Institutional support: RVO:67985556 Keywords : Imprecise probabilities * Credal sets * Multidimensional models * Conditional independence Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 2.845, year: 2016 http://library.utia.cas.cz/separaty/2017/MTR/vejnarova-0483288.pdf

Improving personality facet scores with multidimensional computer adaptive testing

DEFF Research Database (Denmark)

Makransky, Guido; Mortensen, Erik Lykke; Glas, Cees A W

2013-01-01

personality tests contain many highly correlated facets. This article investigates the possibility of increasing the precision of the NEO PI-R facet scores by scoring items with multidimensional item response theory and by efficiently administering and scoring items with multidimensional computer adaptive...

Gene-Based Analysis of Regionally Enriched Cortical Genes in GWAS Data Sets of Cognitive Traits and Psychiatric Disorders

DEFF Research Database (Denmark)

Ersland, Kari M; Christoforou, Andrea; Stansberg, Christine

2012-01-01

the regionally enriched cortical genes to mine a genome-wide association study (GWAS) of the Norwegian Cognitive NeuroGenetics (NCNG) sample of healthy adults for association to nine psychometric tests measures. In addition, we explored GWAS data sets for the serious psychiatric disorders schizophrenia (SCZ) (n...

Multi-Dimensional Aggregation for Temporal Data

DEFF Research Database (Denmark)

Böhlen, M. H.; Gamper, J.; Jensen, Christian Søndergaard

2006-01-01

Business Intelligence solutions, encompassing technologies such as multi-dimensional data modeling and aggregate query processing, are being applied increasingly to non-traditional data. This paper extends multi-dimensional aggregation to apply to data with associated interval values that capture...... that the data holds for each point in the interval, as well as the case where the data holds only for the entire interval, but must be adjusted to apply to sub-intervals. The paper reports on an implementation of the new operator and on an empirical study that indicates that the operator scales to large data...

Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes

OpenAIRE

Kreiman, Gabriel

2004-01-01

Sequence information and high‐throughput methods to measure gene expression levels open the door to explore transcriptional regulation using computational tools. Combinatorial regulation and sparseness of regulatory elements throughout the genome allow organisms to control the spatial and temporal patterns of gene expression. Here we study the organization of cis‐regulatory elements in sets of co‐regulated genes. We build an algorithm to search for combinations of transcription factor binding...

Executive Information Systems' Multidimensional Models

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available Executive Information Systems are design to improve the quality of strategic level of management in organization through a new type of technology and several techniques for extracting, transforming, processing, integrating and presenting data in such a way that the organizational knowledge filters can easily associate with this data and turn it into information for the organization. These technologies are known as Business Intelligence Tools. But in order to build analytic reports for Executive Information Systems (EIS in an organization we need to design a multidimensional model based on the business model from the organization. This paper presents some multidimensional models that can be used in EIS development and propose a new model that is suitable for strategic business requests.

The Tunneling Method for Global Optimization in Multidimensional Scaling.

Science.gov (United States)

Groenen, Patrick J. F.; Heiser, Willem J.

1996-01-01

A tunneling method for global minimization in multidimensional scaling is introduced and adjusted for multidimensional scaling with general Minkowski distances. The method alternates a local search step with a tunneling step in which a different configuration is sought with the same STRESS implementation. (SLD)

A study of multidimensional modeling approaches for data warehouse

Science.gov (United States)

Yusof, Sharmila Mat; Sidi, Fatimah; Ibrahim, Hamidah; Affendey, Lilly Suriani

2016-08-01

Data warehouse system is used to support the process of organizational decision making. Hence, the system must extract and integrate information from heterogeneous data sources in order to uncover relevant knowledge suitable for decision making process. However, the development of data warehouse is a difficult and complex process especially in its conceptual design (multidimensional modeling). Thus, there have been various approaches proposed to overcome the difficulty. This study surveys and compares the approaches of multidimensional modeling and highlights the issues, trend and solution proposed to date. The contribution is on the state of the art of the multidimensional modeling design.

Multidimensional scaling of musical time estimations.

Science.gov (United States)

Cocenas-Silva, Raquel; Bueno, José Lino Oliveira; Molin, Paul; Bigand, Emmanuel

2011-06-01

The aim of this study was to identify the psycho-musical factors that govern time evaluation in Western music from baroque, classic, romantic, and modern repertoires. The excerpts were previously found to represent variability in musical properties and to induce four main categories of emotions. 48 participants (musicians and nonmusicians) freely listened to 16 musical excerpts (lasting 20 sec. each) and grouped those that seemed to have the same duration. Then, participants associated each group of excerpts to one of a set of sine wave tones varying in duration from 16 to 24 sec. Multidimensional scaling analysis generated a two-dimensional solution for these time judgments. Musical excerpts with high arousal produced an overestimation of time, and affective valence had little influence on time perception. The duration was also overestimated when tempo and loudness were higher, and to a lesser extent, timbre density. In contrast, musical tension had little influence.

MADS goes genomic in conifers: towards determining the ancestral set of MADS-box genes in seed plants.

Science.gov (United States)

Gramzow, Lydia; Weilandt, Lisa; Theißen, Günter

2014-11-01

MADS-box genes comprise a gene family coding for transcription factors. This gene family expanded greatly during land plant evolution such that the number of MADS-box genes ranges from one or two in green algae to around 100 in angiosperms. Given the crucial functions of MADS-box genes for nearly all aspects of plant development, the expansion of this gene family probably contributed to the increasing complexity of plants. However, the expansion of MADS-box genes during one important step of land plant evolution, namely the origin of seed plants, remains poorly understood due to the previous lack of whole-genome data for gymnosperms. The newly available genome sequences of Picea abies, Picea glauca and Pinus taeda were used to identify the complete set of MADS-box genes in these conifers. In addition, MADS-box genes were identified in the growing number of transcriptomes available for gymnosperms. With these datasets, phylogenies were constructed to determine the ancestral set of MADS-box genes of seed plants and to infer the ancestral functions of these genes. Type I MADS-box genes are under-represented in gymnosperms and only a minimum of two Type I MADS-box genes have been present in the most recent common ancestor (MRCA) of seed plants. In contrast, a large number of Type II MADS-box genes were found in gymnosperms. The MRCA of extant seed plants probably possessed at least 11-14 Type II MADS-box genes. In gymnosperms two duplications of Type II MADS-box genes were found, such that the MRCA of extant gymnosperms had at least 14-16 Type II MADS-box genes. The implied ancestral set of MADS-box genes for seed plants shows simplicity for Type I MADS-box genes and remarkable complexity for Type II MADS-box genes in terms of phylogeny and putative functions. The analysis of transcriptome data reveals that gymnosperm MADS-box genes are expressed in a great variety of tissues, indicating diverse roles of MADS-box genes for the development of gymnosperms. This study is

Multidimensional poverty measure and analysis: a case study from Hechi City, China.

Science.gov (United States)

Wang, Yanhui; Wang, Baixue

2016-01-01

Aiming at the anti-poverty outline of China and the human-environment sustainable development, we propose a multidimensional poverty measure and analysis methodology for measuring the poverty-stricken counties and their contributing factors. We build a set of multidimensional poverty indicators with Chinese characteristics, integrating A-F double cutoffs, dimensional aggregation and decomposition approach, and GIS spatial analysis to evaluate the poor's multidimensional poverty characteristics under different geographic and socioeconomic conditions. The case study from 11 counties of Hechi City shows that, firstly, each county existed at least four respects of poverty, and overall the poverty level showed the spatial pattern of surrounding higher versus middle lower. Secondly, three main poverty contributing factors were unsafe housing, family health and adults' illiteracy, while the secondary factors include fuel type and children enrollment rate, etc., generally demonstrating strong autocorrelation; in terms of poverty degree, the western of the research area shows a significant aggregation effect, whereas the central and the eastern represent significant spatial heterogeneous distribution. Thirdly, under three kinds of socioeconomic classifications, the intra-classification diversities of H, A, and MPI are greater than their inter-classification ones, while each of the three indexes has a positive correlation with both the rocky desertification degree and topographic fragmentation degree, respectively. This study could help policymakers better understand the local poverty by identifying the poor, locating them and describing their characteristics, so as to take differentiated poverty alleviation measures according to specific conditions of each county.

A multidimensional continued fraction and some of its statistical properties

International Nuclear Information System (INIS)

Baldwin, P.R.

1992-01-01

The problem of simultaneously approximating a vector of irrational numbers with rationals is analyzed in a geometrical setting using notions of dynamical systems theory. The author discusses here a (vectorial) multidimensional continued-fraction algorithm (MCFA) of additive type, the generalized mediant algorithm (GMA), and gives a geometrical interpretation to it. He calculates the invariant measure of the GMA shift as well as its Kolmogorov-Sinai (KS) entropy for arbitrary number of irrationals. The KS entropy is related to the growth rate of denominators of the Euclidean algorithm. This is the first analytical calculation of the growth rate of denominators for any MCFA

Fatigue and multidimensional disease severity in chronic obstructive pulmonary disease

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Inal-Ince Deniz

2010-06-01

Full Text Available Abstract Background and aims Fatigue is associated with longitudinal ratings of health in patients with chronic obstructive pulmonary disease (COPD. Although the degree of airflow obstruction is often used to grade disease severity in patients with COPD, multidimensional grading systems have recently been developed. The aim of this study was to investigate the relationship between perceived and actual fatigue level and multidimensional disease severity in patients with COPD. Materials and methods Twenty-two patients with COPD (aged 52-74 years took part in the study. Multidimensional disease severity was measured using the SAFE and BODE indices. Perceived fatigue was assessed using the Fatigue Severity Scale (FSS and the Fatigue Impact Scale (FIS. Peripheral muscle endurance was evaluated using the number of sit-ups, squats, and modified push-ups that each patient could do. Results Thirteen patients (59% had severe fatigue, and their St George's Respiratory Questionnaire scores were significantly higher (p Conclusions Peripheral muscle endurance and fatigue perception in patients with COPD was related to multidimensional disease severity measured with both the SAFE and BODE indices. Improvements in perceived and actual fatigue levels may positively affect multidimensional disease severity and health status in COPD patients. Further research is needed to investigate the effects of fatigue perception and exercise training on patients with different stages of multidimensional COPD severity.

Multidimensional nonlinear descriptive analysis

CERN Document Server

Nishisato, Shizuhiko

2006-01-01

Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sampled randomly from a normal population and often involve nonlinear relations. This reference not only provides an overview of multidimensional nonlinear descriptive analysis (MUNDA) of discrete data, it also offers new results in a variety of fields. The first part of the book covers conceptual and technical preliminaries needed to understand the data analysis in subsequent chapters. The next two parts contain applications of MUNDA to diverse data types, with each chapter devoted to one type of categorical data, a brief historical comment, and basic skills peculiar to the data types. The final part examines several problems and then concludes with suggestions for futu...

Motivation and engagement in music and sport: testing a multidimensional framework in diverse performance settings.

Science.gov (United States)

Martin, Andrew J

2008-02-01

The present study assessed the application of a multidimensional model of motivation and engagement (the Motivation and Engagement Wheel) and its accompanying instrumentation (the Motivation and Engagement Scale) to the music and sport domains. Participants were 463 young classical musicians (N=224) and sportspeople (N=239). In both music and sport samples, the data confirmed the good fit of the four hypothesized higher-order dimensions and their 11 first-order dimensions: adaptive cognitions (self-efficacy, valuing, mastery orientation), adaptive behaviors (planning, task management, persistence), impeding/maladaptive cognitions (uncertain control, anxiety, failure avoidance), and maladaptive behaviors (self-handicapping, disengagement). Multigroup tests of factor invariance showed that in terms of underlying motivational constructs and the composition of and relationships among these constructs, key subsamples are not substantially different. Moreover-and of particular relevance to issues around the generalizability of the framework-the factor structure for music and sport samples was predominantly invariant.

Multidimensional Physical Self-Concept of Athletes with Physical Disabilities

Science.gov (United States)

Shapiro, Deborah R.; Martin, Jeffrey J.

2010-01-01

The purposes of this investigation were first to predict reported PA (physical activity) behavior and self-esteem using a multidimensional physical self-concept model and second to describe perceptions of multidimensional physical self-concept (e.g., strength, endurance, sport competence) among athletes with physical disabilities. Athletes (N =…

Genome-Wide Gene Set Analysis for Identification of Pathways Associated with Alcohol Dependence

Science.gov (United States)

Biernacka, Joanna M.; Geske, Jennifer; Jenkins, Gregory D.; Colby, Colin; Rider, David N.; Karpyak, Victor M.; Choi, Doo-Sup; Fridley, Brooke L.

2013-01-01

It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the “Synthesis and Degradation of Ketone Bodies” pathway. Our results also support the potential involvement of the “Neuroactive Ligand Receptor Interaction” pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence. PMID:22717047

Development of Multidimensional Gap Conductance model using Virtual Link Gap Element

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyo Chan; Yang, Yong Sik; Kim, Dae Ho; Bang, Je Geon; Kim, Sun Ki; Koo, Yang Hyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2013-10-15

The gap conductance that determines temperature gradient between pellet and cladding can be quite sensitive to gap thickness. For instance, once the gap size increases up to several micrometers in certain region, difference of pellet surface temperatures increases up to 100 Kelvin. Therefore, iterative thermo-mechanical coupled analysis is required to solve temperature distribution throughout pellet and cladding. Recently, multidimensional fuel performance codes have been being developed in the advanced countries to evaluate thermal behavior of fuel for off normal conditions and DBA(design based accident) conditions using the Finite Element Method (FEM). FRAPCON-FRAPTRAN code system, which is well known as the verified and reliable code, incorporates 1D thermal module and multidimensional mechanical module. In this code, multidimensional gap conductance model is not applied. ALCYONE developed by CEA introduces equivalent heat convection coefficient that represents multidimensional gap conductance as a function of gap thickness. BISON, which is multidimensional fuel performance code developed by INL, owns multidimensional gap conductance model using projected thermal contact. In general, thermal contact algorithm is nonlinear calculation which is expensive approach numerically. The gap conductance model for multi-dimension is difficult issue in terms of convergence and nonlinearity because gap conductance is function of gap thickness which depends on mechanical analysis at each iteration step. In this paper, virtual link gap (VLG) element has been proposed to resolve convergence issue and nonlinear characteristic of multidimensional gap conductance. In terms of calculation accuracy and convergence efficiency, the proposed VLG model was evaluated. LWR fuel performance codes should incorporate thermo-mechanical loop to solve gap conductance problem, iteratively. However, gap conductance in multidimensional model is difficult issue owing to its nonlinearity and

Canonical correlation analysis for gene-based pleiotropy discovery.

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Jose A Seoane

2014-10-01

Full Text Available Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy and for testing multiple variants for association with a single phenotype (gene-based association tests. Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study, we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1 with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels.

Conservative Initial Mapping For Multidimensional Simulations of Stellar Explosions

International Nuclear Information System (INIS)

Chen, Ke-Jung; Heger, Alexander; Almgren, Ann

2012-01-01

Mapping one-dimensional stellar profiles onto multidimensional grids as initial conditions for hydrodynamics calculations can lead to numerical artifacts, one of the most severe of which is the violation of conservation laws for physical quantities such as energy and mass. Here we introduce a numerical scheme for mapping one-dimensional spherically-symmetric data onto multidimensional meshes so that these physical quantities are conserved. We validate our scheme by porting a realistic 1D Lagrangian stellar profile to the new multidimensional Eulerian hydro code CASTRO. Our results show that all important features in the profiles are reproduced on the new grid and that conservation laws are enforced at all resolutions after mapping.

Balanced sensitivity functions for tuning multi-dimensional Bayesian network classifiers

NARCIS (Netherlands)

Bolt, J.H.; van der Gaag, L.C.

Multi-dimensional Bayesian network classifiers are Bayesian networks of restricted topological structure, which are tailored to classifying data instances into multiple dimensions. Like more traditional classifiers, multi-dimensional classifiers are typically learned from data and may include

Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

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Mohammad Nur Shodiq

2016-03-01

Full Text Available Spatio temporal data clustering is challenge task. The result of clustering data are utilized to investigate the seismic parameters. Seismic parameters are used to describe the characteristics of earthquake behavior. One of the effective technique to study multidimensional spatio temporal data is visualization. But, visualization of multidimensional data is complicated problem. Because, this analysis consists of observed data cluster and seismic parameters. In this paper, we propose a visualization system, called as IES (Indonesia Earthquake System, for cluster analysis, spatio temporal analysis, and visualize the multidimensional data of seismic parameters. We analyze the cluster analysis by using automatic clustering, that consists of get optimal number of cluster and Hierarchical K-means clustering. We explore the visual cluster and multidimensional data in low dimensional space visualization. We made experiment with observed data, that consists of seismic data around Indonesian archipelago during 2004 to 2014. Keywords: Clustering, visualization, multidimensional data, seismic parameters.

Multidimensional filter banks and wavelets research developments and applications

CERN Document Server

Levy, Bernard

1997-01-01

Multidimensional Filter Banks and Wavelets: Reserach Developments and Applications brings together in one place important contributions and up-to-date research results in this important area. Multidimensional Filter Banks and Wavelets: Research Developments and Applications serves as an excellent reference, providing insight into some of the most important research issues in the field.

On new physics searches with multidimensional differential shapes

Science.gov (United States)

Ferreira, Felipe; Fichet, Sylvain; Sanz, Veronica

2018-03-01

In the context of upcoming new physics searches at the LHC, we investigate the impact of multidimensional differential rates in typical LHC analyses. We discuss the properties of shape information, and argue that multidimensional rates bring limited information in the scope of a discovery, but can have a large impact on model discrimination. We also point out subtleties about systematic uncertainties cancellations and the Cauchy-Schwarz bound on interference terms.

Gene-set analysis based on the pharmacological profiles of drugs to identify repurposing opportunities in schizophrenia.

Science.gov (United States)

de Jong, Simone; Vidler, Lewis R; Mokrab, Younes; Collier, David A; Breen, Gerome

2016-08-01

Genome-wide association studies (GWAS) have identified thousands of novel genetic associations for complex genetic disorders, leading to the identification of potential pharmacological targets for novel drug development. In schizophrenia, 108 conservatively defined loci that meet genome-wide significance have been identified and hundreds of additional sub-threshold associations harbour information on the genetic aetiology of the disorder. In the present study, we used gene-set analysis based on the known binding targets of chemical compounds to identify the 'drug pathways' most strongly associated with schizophrenia-associated genes, with the aim of identifying potential drug repositioning opportunities and clues for novel treatment paradigms, especially in multi-target drug development. We compiled 9389 gene sets (2496 with unique gene content) and interrogated gene-based p-values from the PGC2-SCZ analysis. Although no single drug exceeded experiment wide significance (corrected pneratinib. This is a proof of principle analysis showing the potential utility of GWAS data of schizophrenia for the direct identification of candidate drugs and molecules that show polypharmacy. © The Author(s) 2016.

Shroud leakage flow models and a multi-dimensional coupling CFD (computational fluid dynamics) method for shrouded turbines

International Nuclear Information System (INIS)

Zou, Zhengping; Liu, Jingyuan; Zhang, Weihao; Wang, Peng

2016-01-01

Multi-dimensional coupling simulation is an effective approach for evaluating the flow and aero-thermal performance of shrouded turbines, which can balance the simulation accuracy and computing cost effectively. In this paper, 1D leakage models are proposed based on classical jet theories and dynamics equations, which can be used to evaluate most of the main features of shroud leakage flow, including the mass flow rate, radial and circumferential momentum, temperature and the jet width. Then, the 1D models are expanded to 2D distributions on the interface by using a multi-dimensional scaling method. Based on the models and multi-dimensional scaling, a multi-dimensional coupling simulation method for shrouded turbines is developed, in which, some boundary source and sink are set on the interface between the shroud and the main flow passage. To verify the precision, some simulations on the design point and off design points of a 1.5 stage turbine are conducted. It is indicated that the models and methods can give predictions with sufficient accuracy for most of the flow field features and will contribute to pursue deeper understanding and better design methods of shrouded axial turbines, which are the important devices in energy engineering. - Highlights: • Free and wall attached jet theories are used to model the leakage flow in shrouds. • Leakage flow rate is modeled by virtual labyrinth number and residual-energy factor. • A scaling method is applied to 1D model to obtain 2D distributions on interfaces. • A multi-dimensional coupling CFD method for shrouded turbines is proposed. • The proposed coupling method can give accurate predictions with low computing cost.

Multidimensional human dynamics in mobile phone communications.

Science.gov (United States)

Quadri, Christian; Zignani, Matteo; Capra, Lorenzo; Gaito, Sabrina; Rossi, Gian Paolo

2014-01-01

In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.

Multidimensional human dynamics in mobile phone communications.

Directory of Open Access Journals (Sweden)

Christian Quadri

Full Text Available In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages. Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.

GO(vis), a gene ontology visualization tool based on multi-dimensional values.

Science.gov (United States)

Ning, Zi; Jiang, Zhenran

2010-05-01

Most of gene product similarity measurements concentrate on the information content of Gene Ontology (GO) terms or use a path-based similarity between GO terms, which may ignore other important information contained in the structure of the ontology. In our study, we integrate different GO similarity measure approaches to analyze the functional relationship of genes and gene products with a new triangle-based visualization tool called GO(Vis). The purpose of this tool is to demonstrate the effect of three important information factors when measuring the similarity between gene products. One advantage of this tool is that its important ratio can be adjusted to meet different measuring requirements according to the biological knowledge of each factor. The experimental results demonstrate that GO(Vis) can display diagrams of the functional relationship for gene products effectively.

Bateria Multidimensional de Inteligência Infantil: desenvolvimento de instrumento Multidimensional Battery for Children's Intelligence: development of an instrument

Directory of Open Access Journals (Sweden)

Patrícia Waltz Schelini

2005-12-01

Full Text Available O estudo objetivou elaborar um conjunto de testes, denominado "Bateria Multidimensional de Inteligência Infantil" ou BMI, para avaliar capacidades do Modelo Cattell-Horn-Carroll. Entre as capacidades avaliadas estão as de inteligência cristalizada, inteligência fluida, velocidade de processamento cognitivo, memória a curto prazo, armazenamento e recuperação associativa a longo prazo e conhecimento quantitativo. A BMI foi composta por nove testes, apresentados a duas amostras de participantes. A primeira foi formada por 240 crianças, com idade entre sete e 12 anos. Constituída para que novos itens fossem testados, a segunda amostra foi formada por outras 206 crianças. Os resultados demonstraram a influência altamente significativa da idade sobre o desempenho dos testes. Os testes Informação Geral, Indução, Desempenho em Matemática, Vocabulário Geral e Vocabulário Ilus-trado apresentaram elevados coeficientes de precisão. A análise dos índices de dificuldade e do poder discriminativo permitiu a seleção do conjunto mais adequado de questões para compor a configuração final da Bateria.The goal of this study was elaborate a set of tests, "Multidimensional Battery for Children's Intelligence" or "BMI", according to the abilities included in the Cattell-Horn-Carroll's Model. Among these abilities are the ability of crystallized intelligence, fluid intelligence, processing speed, short-term memory, long-term storage and retrieval and quantitative knowledge. The BMI was composed by nine tests, presented to two samples of participants. The first sample comprised 240 children whose age ranged from seven to 12 years old. Constituted for the testing of new items, the second sample comprised another 206 children. The results demonstrated that the age had a high influence on the tests performance. Were found high reliability coefficients for the tests General Information, Induction, Mathematics Achievment, General Vocabulary and

SUSTAINABLE DEVELOPMENT, A MULTIDIMENSIONAL CONCEPT

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TEODORESCU ANA MARIA

2015-06-01

Full Text Available Sustainable development imposed itself as a corollary of economic term "development". Sustainable development is meant to be the summation of economic, environmental and social considerations for the present and especially for the future. The concept of sustainable development plays an important role in european and global meetings since 1972, the year it has been set for the first time. Strategies necessary to achieve the objectives of sustainable development have been developed, indicators meant to indicate the result of the implementation of policies have been created, national plans were oriented towards achieving the proposed targets. I wanted to highlight the multidimensional character of the concept of sustainable development. Thus, using specialized national and international literature, I have revealed different approaches of one pillar to the detriment of another pillar depending on the specific field. In the different concepts of sustainable development, the consensus is undoubtedly agreed on its components: economic, social, environmental. Based on this fact, the concept of sustainability has different connotations depending on the specific content of each discipline: biology, economics, sociology, environmental ethics. The multidimensional valence of sustainable development consists of three pillars ability to act together for the benefit of present and future generations. Being a multidimensional concept, importance attached to a pillar over another is directed according to the particularities of each field: in economy profit prevails, in ecology care of natural resources is the most important, the social aims improving human living conditions. The challenge of sustainable development is to combine all the economic, environmental and social benefits and the present generation to come. Ecological approach is reflected in acceptance of limited natural resources by preserving natural capital. In terms of the importance of

A stochastic approach to multi-gene expression dynamics

International Nuclear Information System (INIS)

Ochiai, T.; Nacher, J.C.; Akutsu, T.

2005-01-01

In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

Science.gov (United States)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

Two multi-dimensional uncertainty relations

International Nuclear Information System (INIS)

Skala, L; Kapsa, V

2008-01-01

Two multi-dimensional uncertainty relations, one related to the probability density and the other one related to the probability density current, are derived and discussed. Both relations are stronger than the usual uncertainty relations for the coordinates and momentum

Benefits of Multidimensional Measures of Child Well Being in China.

Science.gov (United States)

Gatenio Gabel, Shirley; Zhang, Yiwei

2017-11-06

In recent decades, measures of child well-being have evolved from single dimension to multidimensional measures. Multi-dimensional measures deepen and broaden our understanding of child well-being and inform us of areas of neglect. Child well-being in China today is measured through proxy measures of household need. This paper discusses the evolution of child well-being measures more generally, explores the benefits of positive indicators and multiple dimensions in formulating policy, and then reviews efforts to date by the Chinese government, researchers, and non-governmental and intergovernmental organizations to develop comprehensive multidimensional measures of child well-being in China. The domains and their potential interactions, as well as data sources and availability, are presented. The authors believe that child well-being in China would benefit from the development of a multidimensional index and that there is sufficient data to develop such an index.

Optimal sensor configuration for flexible structures with multi-dimensional mode shapes

International Nuclear Information System (INIS)

Chang, Minwoo; Pakzad, Shamim N

2015-01-01

A framework for deciding the optimal sensor configuration is implemented for civil structures with multi-dimensional mode shapes, which enhances the applicability of structural health monitoring for existing structures. Optimal sensor placement (OSP) algorithms are used to determine the best sensor configuration for structures with a priori knowledge of modal information. The signal strength at each node is evaluated by effective independence and modified variance methods. Euclidean norm of signal strength indices associated with each node is used to expand OSP applicability into flexible structures. The number of sensors for each method is determined using the threshold for modal assurance criterion (MAC) between estimated (from a set of observations) and target mode shapes. Kriging is utilized to infer the modal estimates for unobserved locations with a weighted sum of known neighbors. A Kriging model can be expressed as a sum of linear regression and random error which is assumed as the realization of a stochastic process. This study presents the effects of Kriging parameters for the accurate estimation of mode shapes and the minimum number of sensors. The feasible ranges to satisfy MAC criteria are investigated and used to suggest the adequate searching bounds for associated parameters. The finite element model of a tall building is used to demonstrate the application of optimal sensor configuration. The dynamic modes of flexible structure at centroid are appropriately interpreted into the outermost sensor locations when OSP methods are implemented. Kriging is successfully used to interpolate the mode shapes from a set of sensors and to monitor structures associated with multi-dimensional mode shapes. (paper)

Dynamic MR mammography: multidimensional visualization of contrast enhancement in virtual reality

International Nuclear Information System (INIS)

Englmeier, K.-H.; Siebert, M.; Griebel, J.; Lucht, R.; Brix, G.; Knopp, M.

2000-01-01

Background: The purpose of this study was the development of a method for fast and efficient analysis of dynamic MR images of the female breast. The image data sets were acquired with a saturation-recovery turbo-FLASH sequence which enables the detection of the kinetics of the contrast agent concentration in the whole breast with a high temporal and spatial resolution. In addition, a morphologic 3D-FLASH data set was acquired. Methods: The dynamic image datasets were analyzed by a pharmacokinetic model which enables the representation of the relevant functional tissue information by two parameters. In order to display simultaneously morphologic and functional tissue information, we developed a multidimensional visualization system, which enables a practical and intuitive human-computer interface in virtual reality. Discussions: The developed system allows the fast and efficient analysis of dynamic MR data sets. An important clinical application is the localization and definition of multiple lesions of the female breast. (orig.) [de

Frail Elders in an Urban District Setting in Malaysia: Multidimensional Frailty and Its Correlates.

Science.gov (United States)

Sathasivam, Jeyanthini; Kamaruzzaman, Shahrul Bahyah; Hairi, Farizah; Ng, Chiu Wan; Chinna, Karuthan

2015-11-01

In the past decade, the population in Malaysia has been rapidly ageing. This poses new challenges and issues that threaten the ability of the elderly to independently age in place. A multistage cross-sectional study on 789 community-dwelling elderly individuals aged 60 years and above was conducted in an urban district in Malaysia to assess the geriatric syndrome of frailty. Using a multidimensional frailty index, we detected 67.7% prefrail and 5.7% frail elders. Cognitive status was a significant correlate for frailty status among the respondents as well as those who perceived their health status as very poor or quite poor; but self-rated health was no longer significant when controlled for sociodemographic variables. Lower-body weakness and history of falls were associated with increasing frailty levels, and this association persisted in the multivariate model. This study offers support that physical disability, falls, and cognition are important determinants for frailty. This initial work on frailty among urban elders in Malaysia provides important correlations and identifies potential risk factors that can form the basis of information for targeted preventive measures for this vulnerable group in their prefrail state. © 2015 APJPH.

Reduced Set of Virulence Genes Allows High Accuracy Prediction of Bacterial Pathogenicity in Humans

Science.gov (United States)

Iraola, Gregorio; Vazquez, Gustavo; Spangenberg, Lucía; Naya, Hugo

2012-01-01

Although there have been great advances in understanding bacterial pathogenesis, there is still a lack of integrative information about what makes a bacterium a human pathogen. The advent of high-throughput sequencing technologies has dramatically increased the amount of completed bacterial genomes, for both known human pathogenic and non-pathogenic strains; this information is now available to investigate genetic features that determine pathogenic phenotypes in bacteria. In this work we determined presence/absence patterns of different virulence-related genes among more than finished bacterial genomes from both human pathogenic and non-pathogenic strains, belonging to different taxonomic groups (i.e: Actinobacteria, Gammaproteobacteria, Firmicutes, etc.). An accuracy of 95% using a cross-fold validation scheme with in-fold feature selection is obtained when classifying human pathogens and non-pathogens. A reduced subset of highly informative genes () is presented and applied to an external validation set. The statistical model was implemented in the BacFier v1.0 software (freely available at ), that displays not only the prediction (pathogen/non-pathogen) and an associated probability for pathogenicity, but also the presence/absence vector for the analyzed genes, so it is possible to decipher the subset of virulence genes responsible for the classification on the analyzed genome. Furthermore, we discuss the biological relevance for bacterial pathogenesis of the core set of genes, corresponding to eight functional categories, all with evident and documented association with the phenotypes of interest. Also, we analyze which functional categories of virulence genes were more distinctive for pathogenicity in each taxonomic group, which seems to be a completely new kind of information and could lead to important evolutionary conclusions. PMID:22916122

Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

Science.gov (United States)

2018-01-01

One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520

Visual modeling in an analysis of multidimensional data

Science.gov (United States)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

Multidimensional Scaling Localization Algorithm in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhang Dongyang

2014-02-01

Full Text Available Due to the localization algorithm in large-scale wireless sensor network exists shortcomings both in positioning accuracy and time complexity compared to traditional localization algorithm, this paper presents a fast multidimensional scaling location algorithm. By positioning algorithm for fast multidimensional scaling, fast mapping initialization, fast mapping and coordinate transform can get schematic coordinates of node, coordinates Initialize of MDS algorithm, an accurate estimate of the node coordinates and using the PRORUSTES to analysis alignment of the coordinate and final position coordinates of nodes etc. There are four steps, and the thesis gives specific implementation steps of the algorithm. Finally, compared with stochastic algorithms and classical MDS algorithm experiment, the thesis takes application of specific examples. Experimental results show that: the proposed localization algorithm has fast multidimensional scaling positioning accuracy in ensuring certain circumstances, but also greatly improves the speed of operation.

Development of multi-dimensional body image scale for malaysian female adolescents.

Science.gov (United States)

Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

Science.gov (United States)

Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei

2015-01-01

This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…

Identification of a core set of rhizobial infection genes using data from single cell-types

Directory of Open Access Journals (Sweden)

Da-Song eChen

2015-07-01

Full Text Available Genome-wide expression studies on nodulation have varied in their scale from entire root systems to dissected nodules or root sections containing nodule primordia. More recently efforts have focused on developing methods for isolation of root hairs from infected plants and the application of laser-capture microdissection technology to nodules. Here we analyze two published data sets to identify a core set of infection genes that are expressed in the nodule and in root hairs during infection. Among the genes identified were those encoding phenylpropanoid biosynthesis enzymes including Chalcone-O-Methyltransferase which is required for the production of the potent Nod gene inducer 4’,4-dihydroxy-2-methoxychalcone. A promoter-GUS analysis in transgenic hairy roots for two genes encoding Chalcone-O-Methyltransferase isoforms revealed their expression in rhizobially infected root hairs and the nodule infection zone but not in the nitrogen fixation zone. We also describe a group of Rhizobially Induced Peroxidases whose expression overlaps with the production of superoxide in rhizobially infected root hairs and in nodules and roots. Finally, we identify a cohort of co-regulated transcription factors as candidate regulators of these processes.

Synthesis of Joint Volumes, Visualization of Paths, and Revision of Viewing Sequences in a Multi-dimensional Seismic Data Viewer

Science.gov (United States)

Chen, D. M.; Clapp, R. G.; Biondi, B.

2006-12-01

Ricksep is a freely-available interactive viewer for multi-dimensional data sets. The viewer is very useful for simultaneous display of multiple data sets from different viewing angles, animation of movement along a path through the data space, and selection of local regions for data processing and information extraction. Several new viewing features are added to enhance the program's functionality in the following three aspects. First, two new data synthesis algorithms are created to adaptively combine information from a data set with mostly high-frequency content, such as seismic data, and another data set with mainly low-frequency content, such as velocity data. Using the algorithms, these two data sets can be synthesized into a single data set which resembles the high-frequency data set on a local scale and at the same time resembles the low- frequency data set on a larger scale. As a result, the originally separated high and low-frequency details can now be more accurately and conveniently studied together. Second, a projection algorithm is developed to display paths through the data space. Paths are geophysically important because they represent wells into the ground. Two difficulties often associated with tracking paths are that they normally cannot be seen clearly inside multi-dimensional spaces and depth information is lost along the direction of projection when ordinary projection techniques are used. The new algorithm projects samples along the path in three orthogonal directions and effectively restores important depth information by using variable projection parameters which are functions of the distance away from the path. Multiple paths in the data space can be generated using different character symbols as positional markers, and users can easily create, modify, and view paths in real time. Third, a viewing history list is implemented which enables Ricksep's users to create, edit and save a recipe for the sequence of viewing states. Then, the recipe

Analysis of Local Dependence and Multidimensionality in Graphical Loglinear Rasch Models

DEFF Research Database (Denmark)

Kreiner, Svend; Christensen, Karl Bang

2004-01-01

Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model......Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model...

A second-order cell-centered Lagrangian ADER-MOOD finite volume scheme on multidimensional unstructured meshes for hydrodynamics

Science.gov (United States)

Boscheri, Walter; Dumbser, Michael; Loubère, Raphaël; Maire, Pierre-Henri

2018-04-01

In this paper we develop a conservative cell-centered Lagrangian finite volume scheme for the solution of the hydrodynamics equations on unstructured multidimensional grids. The method is derived from the Eucclhyd scheme discussed in [47,43,45]. It is second-order accurate in space and is combined with the a posteriori Multidimensional Optimal Order Detection (MOOD) limiting strategy to ensure robustness and stability at shock waves. Second-order of accuracy in time is achieved via the ADER (Arbitrary high order schemes using DERivatives) approach. A large set of numerical test cases is proposed to assess the ability of the method to achieve effective second order of accuracy on smooth flows, maintaining an essentially non-oscillatory behavior on discontinuous profiles, general robustness ensuring physical admissibility of the numerical solution, and precision where appropriate.

Visualization and Dissemination of Multidimensional Proteomics Data Comparing Protein Abundance During Caenorhabditis elegans Development

Science.gov (United States)

Riffle, Michael; Merrihew, Gennifer E.; Jaschob, Daniel; Sharma, Vagisha; Davis, Trisha N.; Noble, William S.; MacCoss, Michael J.

2015-11-01

Regulation of protein abundance is a critical aspect of cellular function, organism development, and aging. Alternative splicing may give rise to multiple possible proteoforms of gene products where the abundance of each proteoform is independently regulated. Understanding how the abundances of these distinct gene products change is essential to understanding the underlying mechanisms of many biological processes. Bottom-up proteomics mass spectrometry techniques may be used to estimate protein abundance indirectly by sequencing and quantifying peptides that are later mapped to proteins based on sequence. However, quantifying the abundance of distinct gene products is routinely confounded by peptides that map to multiple possible proteoforms. In this work, we describe a technique that may be used to help mitigate the effects of confounding ambiguous peptides and multiple proteoforms when quantifying proteins. We have applied this technique to visualize the distribution of distinct gene products for the whole proteome across 11 developmental stages of the model organism Caenorhabditis elegans. The result is a large multidimensional dataset for which web-based tools were developed for visualizing how translated gene products change during development and identifying possible proteoforms. The underlying instrument raw files and tandem mass spectra may also be downloaded. The data resource is freely available on the web at http://www.yeastrc.org/wormpes/.

Multidimensional Databases and Data Warehousing

DEFF Research Database (Denmark)

Jensen, Christian S.; Pedersen, Torben Bach; Thomsen, Christian

The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses. The book aims to present the most important concepts within this subject in a precise and understandable manner. The book's coverage of fundamental concepts includes...

Background elimination methods for multidimensional coincidence γ-ray spectra

International Nuclear Information System (INIS)

Morhac, M.

1997-01-01

In the paper new methods to separate useful information from background in one, two, three and multidimensional spectra (histograms) measured in large multidetector γ-ray arrays are derived. The sensitive nonlinear peak clipping algorithm is the basis of the methods for estimation of the background in multidimensional spectra. The derived procedures are simple and therefore have a very low cost in terms of computing time. (orig.)

Multidimensional Poverty and Health Status as a Predictor of Chronic Income Poverty.

Science.gov (United States)

Callander, Emily J; Schofield, Deborah J

2015-12-01

Longitudinal analysis of Wave 5 to 10 of the nationally representative Household, Income and Labour Dynamics in Australia dataset was undertaken to assess whether multidimensional poverty status can predict chronic income poverty. Of those who were multidimensionally poor (low income plus poor health or poor health and insufficient education attainment) in 2007, and those who were in income poverty only (no other forms of disadvantage) in 2007, a greater proportion of those in multidimensional poverty continued to be in income poverty for the subsequent 5 years through to 2012. People who were multidimensionally poor in 2007 had 2.17 times the odds of being in income poverty each year through to 2012 than those who were in income poverty only in 2005 (95% CI: 1.23-3.83). Multidimensional poverty measures are a useful tool for policymakers to identify target populations for policies aiming to improve equity and reduce chronic disadvantage. Copyright © 2014 John Wiley & Sons, Ltd.

Towards Optimal Multi-Dimensional Query Processing with BitmapIndices

Energy Technology Data Exchange (ETDEWEB)

Rotem, Doron; Stockinger, Kurt; Wu, Kesheng

2005-09-30

Bitmap indices have been widely used in scientific applications and commercial systems for processing complex, multi-dimensional queries where traditional tree-based indices would not work efficiently. This paper studies strategies for minimizing the access costs for processing multi-dimensional queries using bitmap indices with binning. Innovative features of our algorithm include (a) optimally placing the bin boundaries and (b) dynamically reordering the evaluation of the query terms. In addition, we derive several analytical results concerning optimal bin allocation for a probabilistic query model. Our experimental evaluation with real life data shows an average I/O cost improvement of at least a factor of 10 for multi-dimensional queries on datasets from two different applications. Our experiments also indicate that the speedup increases with the number of query dimensions.

Multi-dimensional conversion to the ion-hybrid mode

International Nuclear Information System (INIS)

Tracy, E.R.; Kaufman, A.N.; Brizard, A.J.; Morehead, J.J.

1996-01-01

We first demonstrate that the dispersion matrix for linear conversion of a magnetosonic wave to an ion-hybrid wave (as in a D-T plasma) can be congruently transformed to Friedland's normal form. As a result, this conversion can be represented as a two-step process of successive linear conversions in phase space. We then proceed to study the multi-dimensional case of tokamak geometry. After fourier transforming the toroidal dependence, we deal with the two-dimensional poloidal xy-plane and the two-dimensional k x k y -plane, forming a four-dimensional phase space. The dispersion manifolds for the magnetosonic wave [D M (x, k) = 0] and the ion-hybrid wave [D H (x, k) = 0] are each three-dimensional. (Their intersection, on which mode conversion occurs, is two-dimensional.) The incident magnetosonic wave (radiated by an antenna) is a two-dimensional set of rays (a lagrangian manifold): k(x) = ∇θ(x), with θ(x) the phase of the magnetosonic wave. When these rays pierce the ion-hybrid dispersion manifold, they convert to a set of ion-hybrid rays. Then, when those rays intersect the magnetosonic dispersion manifold, they convert to a set of open-quotes reflectedclose quotes magnetosonic rays. This set of rays is distinct from the set of incident rays that have been reflected by the inner surface of the tokamak plasma. As a result, the total destructive interference that can occur in the one-dimensional case may become only partial. We explore the implications of this startling phenomenon both analytically and geometrically

Genomic determinants of sporulation in Bacilli and Clostridia: towards the minimal set of sporulation-specific genes.

Science.gov (United States)

Galperin, Michael Y; Mekhedov, Sergei L; Puigbo, Pere; Smirnov, Sergey; Wolf, Yuri I; Rigden, Daniel J

2012-11-01

Three classes of low-G+C Gram-positive bacteria (Firmicutes), Bacilli, Clostridia and Negativicutes, include numerous members that are capable of producing heat-resistant endospores. Spore-forming firmicutes include many environmentally important organisms, such as insect pathogens and cellulose-degrading industrial strains, as well as human pathogens responsible for such diseases as anthrax, botulism, gas gangrene and tetanus. In the best-studied model organism Bacillus subtilis, sporulation involves over 500 genes, many of which are conserved among other bacilli and clostridia. This work aimed to define the genomic requirements for sporulation through an analysis of the presence of sporulation genes in various firmicutes, including those with smaller genomes than B. subtilis. Cultivable spore-formers were found to have genomes larger than 2300 kb and encompass over 2150 protein-coding genes of which 60 are orthologues of genes that are apparently essential for sporulation in B. subtilis. Clostridial spore-formers lack, among others, spoIIB, sda, spoVID and safA genes and have non-orthologous displacements of spoIIQ and spoIVFA, suggesting substantial differences between bacilli and clostridia in the engulfment and spore coat formation steps. Many B. subtilis sporulation genes, particularly those encoding small acid-soluble spore proteins and spore coat proteins, were found only in the family Bacillaceae, or even in a subset of Bacillus spp. Phylogenetic profiles of sporulation genes, compiled in this work, confirm the presence of a common sporulation gene core, but also illuminate the diversity of the sporulation processes within various lineages. These profiles should help further experimental studies of uncharacterized widespread sporulation genes, which would ultimately allow delineation of the minimal set(s) of sporulation-specific genes in Bacilli and Clostridia. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Bifactor Approach to Modeling Multidimensionality of Physical Self-Perception Profile

Science.gov (United States)

Chung, ChihMing; Liao, Xiaolan; Song, Hairong; Lee, Taehun

2016-01-01

The multi-dimensionality of Physical Self-Perception Profile (PSPP) has been acknowledged by the use of correlated-factor model and second-order model. In this study, the authors critically endorse the bifactor model, as a substitute to address the multi-dimensionality of PSPP. To cross-validate the models, analyses are conducted first in…

Multidimensional quantum entanglement with large-scale integrated optics

DEFF Research Database (Denmark)

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong

2018-01-01

-dimensional entanglement. A programmable bipartite entangled system is realized with dimension up to 15 × 15 on a large-scale silicon-photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality......The ability to control multidimensional quantum systems is key for the investigation of fundamental science and for the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control and analyze high...

On multidimensional item response theory -- a coordinate free approach

OpenAIRE

Antal, Tamás

2007-01-01

A coordinate system free definition of complex structure multidimensional item response theory (MIRT) for dichotomously scored items is presented. The point of view taken emphasizes the possibilities and subtleties of understanding MIRT as a multidimensional extension of the ``classical'' unidimensional item response theory models. The main theorem of the paper is that every monotonic MIRT model looks the same; they are all trivial extensions of univariate item response theory.

An Analysis of Multi-dimensional Gender Inequality in Pakistan

OpenAIRE

Abdul Hamid; Aisha M. Ahmed

2011-01-01

Women make almost half of the population of Pakistan. They also contribute significantly to economic and social growth. However, in developing countries like Pakistan, women usually suffer from multidimensional inequality of opportunities leading to multidimensional poverty. The dimensions of family, women identity, health, education and women access to economic resources and employment contribute significantly to the discrimination of women. The provision of more opportunities to women in th...

Coverage and characteristics of the Affymetrix GeneChip Human Mapping 100K SNP set.

Directory of Open Access Journals (Sweden)

2006-05-01

Full Text Available Improvements in technology have made it possible to conduct genome-wide association mapping at costs within reach of academic investigators, and experiments are currently being conducted with a variety of high-throughput platforms. To provide an appropriate context for interpreting results of such studies, we summarize here results of an investigation of one of the first of these technologies to be publicly available, the Affymetrix GeneChip Human Mapping 100K set of single nucleotide polymorphisms (SNPs. In a systematic analysis of the pattern and distribution of SNPs in the Mapping 100K set, we find that SNPs in this set are undersampled from coding regions (both nonsynonymous and synonymous and oversampled from regions outside genes, relative to SNPs in the overall HapMap database. In addition, we utilize a novel multilocus linkage disequilibrium (LD coefficient based on information content (analogous to the information content scores commonly used for linkage mapping that is equivalent to the familiar measure r2 in the special case of two loci. Using this approach, we are able to summarize for any subset of markers, such as the Affymetrix Mapping 100K set, the information available for association mapping in that subset, relative to the information available in the full set of markers included in the HapMap, and highlight circumstances in which this multilocus measure of LD provides substantial additional insight about the haplotype structure in a region over pairwise measures of LD.

Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets

KAUST Repository

Permina, Elizaveta A.; Medvedeva, Yulia; Baeck, Pia M.; Hegde, Shubhada R.; Mande, Shekhar C.; Makeev, Vsevolod J.

2013-01-01

interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set

A Multidimensional Software Engineering Course

Science.gov (United States)

Barzilay, O.; Hazzan, O.; Yehudai, A.

2009-01-01

Software engineering (SE) is a multidimensional field that involves activities in various areas and disciplines, such as computer science, project management, and system engineering. Though modern SE curricula include designated courses that address these various subjects, an advanced summary course that synthesizes them is still missing. Such a…

Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

Science.gov (United States)

Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

2011-08-01

The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

Directory of Open Access Journals (Sweden)

Pugalendhi Ganesh Kumar

Full Text Available This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR-based method for redefining the criterion function of f-information (FI to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA, which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS. Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA, particle swarm optimization (PSO, and artificial bee colony algorithm (ABC on all the datasets. In the global cancer map with repeated measurements (GCM_RM dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%. In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively

The development of a collapsing method for the mixed group and point cross sections and its application on multi-dimensional deep penetration calculations

International Nuclear Information System (INIS)

Bor-Jing Chang; Yen-Wan H. Liu

1992-01-01

The HYBRID, or mixed group and point, method was developed to solve the neutron transport equation deterministically using detailed treatment at cross section minima for deep penetration calculations. Its application so far is limited to one-dimensional calculations due to the enormous computing time involved in multi-dimensional calculations. In this article, a collapsing method is developed for the mixed group and point cross section sets to provide a more direct and practical way of using the HYBRID method in the multi-dimensional calculations. A testing problem is run. The method is then applied to the calculation of a deep penetration benchmark experiment. It is observed that half of the window effect is smeared in the collapsing treatment, but it still provide a better cross section set than the VITAMIN-C cross sections for the deep penetrating calculations

A review of snapshot multidimensional optical imaging: Measuring photon tags in parallel

Energy Technology Data Exchange (ETDEWEB)

Gao, Liang, E-mail: gaol@illinois.edu [Department of Electrical and Computer Engineering, University of Illinois at Urbana–Champaign, 306 N. Wright St., Urbana, IL 61801 (United States); Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, 405 North Mathews Avenue, Urbana, IL 61801 (United States); Wang, Lihong V., E-mail: lhwang@wustl.edu [Optical imaging laboratory, Department of Biomedical Engineering, Washington University in St. Louis, One Brookings Dr., MO, 63130 (United States)

2016-02-29

Multidimensional optical imaging has seen remarkable growth in the past decade. Rather than measuring only the two-dimensional spatial distribution of light, as in conventional photography, multidimensional optical imaging captures light in up to nine dimensions, providing unprecedented information about incident photons’ spatial coordinates, emittance angles, wavelength, time, and polarization. Multidimensional optical imaging can be accomplished either by scanning or parallel acquisition. Compared with scanning-based imagers, parallel acquisition–also dubbed snapshot imaging–has a prominent advantage in maximizing optical throughput, particularly when measuring a datacube of high dimensions. Here, we first categorize snapshot multidimensional imagers based on their acquisition and image reconstruction strategies, then highlight the snapshot advantage in the context of optical throughput, and finally we discuss their state-of-the-art implementations and applications.

[Dynamic MR mammography. Multidimensional visualization of contrast medium enhancement in virtual reality].

Science.gov (United States)

Englmeier, K H; Griebel, J; Lucht, R; Knopp, M; Siebert, M; Brix, G

2000-03-01

The purpose of this study was the development of a method for fast and efficient analysis of dynamic MR images of the female breast. The image data sets were acquired with a saturation-recovery turbo-FLASH sequence which enables the detection of the kinetics of the contrast agent concentration in the whole breast with a high temporal and spatial resolution. In addition, a morphologic 3D-FLASH data set was acquired. The dynamic image datasets were analyzed by a pharmacokinetic model which enables the representation of the relevant functional tissue information by two parameters. In order to display simultaneously morphologic and functional tissue information, we developed a multidimensional visualization system, which enables a practical and intuitive human-computer interface in virtual reality. The developed system allows the fast and efficient analysis of dynamic MR data sets. An important clinical application is the localization and definition of multiple lesions of the female breast.

Meta-analysis of differentiating mouse embryonic stem cell gene expression kinetics reveals early change of a small gene set.

Directory of Open Access Journals (Sweden)

Clive H Glover

2006-11-01

Full Text Available Stem cell differentiation involves critical changes in gene expression. Identification of these should provide endpoints useful for optimizing stem cell propagation as well as potential clues about mechanisms governing stem cell maintenance. Here we describe the results of a new meta-analysis methodology applied to multiple gene expression datasets from three mouse embryonic stem cell (ESC lines obtained at specific time points during the course of their differentiation into various lineages. We developed methods to identify genes with expression changes that correlated with the altered frequency of functionally defined, undifferentiated ESC in culture. In each dataset, we computed a novel statistical confidence measure for every gene which captured the certainty that a particular gene exhibited an expression pattern of interest within that dataset. This permitted a joint analysis of the datasets, despite the different experimental designs. Using a ranking scheme that favored genes exhibiting patterns of interest, we focused on the top 88 genes whose expression was consistently changed when ESC were induced to differentiate. Seven of these (103728_at, 8430410A17Rik, Klf2, Nr0b1, Sox2, Tcl1, and Zfp42 showed a rapid decrease in expression concurrent with a decrease in frequency of undifferentiated cells and remained predictive when evaluated in additional maintenance and differentiating protocols. Through a novel meta-analysis, this study identifies a small set of genes whose expression is useful for identifying changes in stem cell frequencies in cultures of mouse ESC. The methods and findings have broader applicability to understanding the regulation of self-renewal of other stem cell types.

Advanced multi-dimensional imaging of gamma-ray radiation

International Nuclear Information System (INIS)

Woodring, Mitchell; Beddingfield, David; Souza, David; Entine, Gerald; Squillante, Michael; Christian, James; Kogan, Alex

2003-01-01

The tracking of radiation contamination and distribution has become a high-priority US DOE task. To support DOE needs, Radiation Monitoring Devices Inc. has been actively carrying out research and development on a gamma-radiation imager, RadCam 2000 TM . The imager is based upon a position-sensitive PMT coupled to a scintillator near a MURA coded aperture. The modulated gamma flux detected by the PSPMT is mathematically decoded to produce images that are computer displayed in near real time. Additionally, we have developed a data-manipulation scheme which allows a multi-dimensional data array, comprised of x position, y position, and energy, to be used in the imaging process. In the imager software a gate can be set on a specific isotope energy to reveal where in the field of view the gated data lies or, conversely, a gate can be set on an area in the field of view to examine what isotopes are present in that area. This process is complicated by the FFT decoding process used with the coded aperture; however, we have achieved excellent performance and results are presented here

Fast multi-dimensional NMR by minimal sampling

Science.gov (United States)

Kupče, Ēriks; Freeman, Ray

2008-03-01

A new scheme is proposed for very fast acquisition of three-dimensional NMR spectra based on minimal sampling, instead of the customary step-wise exploration of all of evolution space. The method relies on prior experiments to determine accurate values for the evolving frequencies and intensities from the two-dimensional 'first planes' recorded by setting t1 = 0 or t2 = 0. With this prior knowledge, the entire three-dimensional spectrum can be reconstructed by an additional measurement of the response at a single location (t1∗,t2∗) where t1∗ and t2∗ are fixed values of the evolution times. A key feature is the ability to resolve problems of overlap in the acquisition dimension. Applied to a small protein, agitoxin, the three-dimensional HNCO spectrum is obtained 35 times faster than systematic Cartesian sampling of the evolution domain. The extension to multi-dimensional spectroscopy is outlined.

Selection and validation of a set of reliable reference genes for quantitative sod gene expression analysis in C. elegans

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Vandesompele Jo

2008-01-01

Full Text Available Abstract Background In the nematode Caenorhabditis elegans the conserved Ins/IGF-1 signaling pathway regulates many biological processes including life span, stress response, dauer diapause and metabolism. Detection of differentially expressed genes may contribute to a better understanding of the mechanism by which the Ins/IGF-1 signaling pathway regulates these processes. Appropriate normalization is an essential prerequisite for obtaining accurate and reproducible quantification of gene expression levels. The aim of this study was to establish a reliable set of reference genes for gene expression analysis in C. elegans. Results Real-time quantitative PCR was used to evaluate the expression stability of 12 candidate reference genes (act-1, ama-1, cdc-42, csq-1, eif-3.C, mdh-1, gpd-2, pmp-3, tba-1, Y45F10D.4, rgs-6 and unc-16 in wild-type, three Ins/IGF-1 pathway mutants, dauers and L3 stage larvae. After geNorm analysis, cdc-42, pmp-3 and Y45F10D.4 showed the most stable expression pattern and were used to normalize 5 sod expression levels. Significant differences in mRNA levels were observed for sod-1 and sod-3 in daf-2 relative to wild-type animals, whereas in dauers sod-1, sod-3, sod-4 and sod-5 are differentially expressed relative to third stage larvae. Conclusion Our findings emphasize the importance of accurate normalization using stably expressed reference genes. The methodology used in this study is generally applicable to reliably quantify gene expression levels in the nematode C. elegans using quantitative PCR.

Testing of multidimensional tectonomagmatic discrimination diagrams on fresh and altered rocks

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Rivera-Gómez M. Abdelaly

2016-04-01

Full Text Available We evaluated 55 multidimensional diagrams proposed during 2004-2013 for the tectonic discrimination of ultrabasic, basic, intermediate, and acid magmas. The Miocene to Recent rock samples for testing the diagrams had not been used for constructing them. Eighteen test studies (2 from ocean island; 2 from ocean island/continental rift; 6 from continental rift; 4 from continental arc; 2 from island arc; 1 from mid-ocean ridge, and 1 from collision of relatively fresh rocks fully confirmed the satisfactory functioning of these diagrams for all tectonic fields for which they were proposed. Eight additional case studies on hydrothermally altered or moderately to highly weathered rocks were also presented to achieve further understanding of the functioning of these diagrams. For these rocks as well, the diagrams indicated the expected tectonic setting. We also show that for testing or using these diagrams the freely-available geochemistry databases should be used with caution but certainly after ascertaining the correct magma types to select the appropriate diagram sets. The results encourage us to recommend these diagrams for deciphering the tectonic setting of older terranes or areas with complex or transitional tectonic settings.

Evidence for intron length conservation in a set of mammalian genes associated with embryonic development

LENUS (Irish Health Repository)

2011-10-05

Abstract Background We carried out an analysis of intron length conservation across a diverse group of nineteen mammalian species. Motivated by recent research suggesting a role for time delays associated with intron transcription in gene expression oscillations required for early embryonic patterning, we searched for examples of genes that showed the most extreme conservation of total intron content in mammals. Results Gene sets annotated as being involved in pattern specification in the early embryo or containing the homeobox DNA-binding domain, were significantly enriched among genes with highly conserved intron content. We used ancestral sequences reconstructed with probabilistic models that account for insertion and deletion mutations to distinguish insertion and deletion events on lineages leading to human and mouse from their last common ancestor. Using a randomization procedure, we show that genes containing the homeobox domain show less change in intron content than expected, given the number of insertion and deletion events within their introns. Conclusions Our results suggest selection for gene expression precision or the existence of additional development-associated genes for which transcriptional delay is functionally significant.

Health, Wealth and Wisdom: Exploring Multidimensional Inequality in a Developing Country

Science.gov (United States)

Nilsson, Therese

2010-01-01

Despite a broad theoretical literature on multidimensional inequality and a widespread belief that welfare is not synonymous to income--not the least in a developing context--empirical inequality examinations rarely includes several welfare attributes. We explore three techniques on how to evaluate multidimensional inequality using Zambian…

Recycling Behavior: A Multidimensional Approach

Science.gov (United States)

Meneses, Gonzalo Diaz; Palacio, Asuncion Beerli

2005-01-01

This work centers on the study of consumer recycling roles to examine the sociodemographic and psychographic profile of the distribution of recycling tasks and roles within the household. With this aim in mind, an empirical work was carried out, the results of which suggest that recycling behavior is multidimensional and comprises the undertaking…

Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets

KAUST Repository

Permina, Elizaveta A.

2013-01-01

Identification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse. Copyright © 2013 Taylor & Francis.

Equivalent Gene Expression Profiles between Glatopa™ and Copaxone®.

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Josephine S D'Alessandro

Full Text Available Glatopa™ is a generic glatiramer acetate recently approved for the treatment of patients with relapsing forms of multiple sclerosis. Gene expression profiling was performed as a means to evaluate equivalence of Glatopa and Copaxone®. Microarray analysis containing 39,429 unique probes across the entire genome was performed in murine glatiramer acetate--responsive Th2-polarized T cells, a test system highly relevant to the biology of glatiramer acetate. A closely related but nonequivalent glatiramoid molecule was used as a control to establish assay sensitivity. Multiple probe-level (Student's t-test and sample-level (principal component analysis, multidimensional scaling, and hierarchical clustering statistical analyses were utilized to look for differences in gene expression induced by the test articles. The analyses were conducted across all genes measured, as well as across a subset of genes that were shown to be modulated by Copaxone. The following observations were made across multiple statistical analyses: the expression of numerous genes was significantly changed by treatment with Copaxone when compared against media-only control; gene expression profiles induced by Copaxone and Glatopa were not significantly different; and gene expression profiles induced by Copaxone and the nonequivalent glatiramoid were significantly different, underscoring the sensitivity of the test system and the multiple analysis methods. Comparative analysis was also performed on sets of transcripts relevant to T-cell biology and antigen presentation, among others that are known to be modulated by glatiramer acetate. No statistically significant differences were observed between Copaxone and Glatopa in the expression levels (magnitude and direction of these glatiramer acetate-regulated genes. In conclusion, multiple methods consistently supported equivalent gene expression profiles between Copaxone and Glatopa.

Multi-dimensional two-phase flow measurements in a large-diameter pipe using wire-mesh sensor

International Nuclear Information System (INIS)

Kanai, Taizo; Furuya, Masahiro; Arai, Takahiro; Shirakawa, Kenetsu; Nishi, Yoshihisa; Ueda, Nobuyuki

2011-01-01

The authors developed a method of measurement to determine the multi-dimensionality of two phase flow. A wire-mesh sensor (WMS) can acquire a void fraction distribution at a high temporal and spatial resolution and also estimate the velocity of a vertical rising flow by investigating the signal time-delay of the upstream WMS relative to downstream. Previously, one-dimensional velocity was estimated by using the same point of each WMS at a temporal resolution of 1.0 - 5.0 s. The authors propose to extend this time series analysis to estimate the multi-dimensional velocity profile via cross-correlation analysis between a point of upstream WMS and multiple points downstream. Bubbles behave in various ways according to size, which is used to classify them into certain groups via wavelet analysis before cross-correlation analysis. This method was verified by air-water straight and swirl flows within a large-diameter vertical pipe. A high-speed camera is used to set the parameter of cross-correlation analysis. The results revealed that for the rising straight and swirl flows, large scale bubbles tend to move to the center, while the small bubble is pushed to the outside or sucked into the space where the large bubbles existed. Moreover, it is found that this method can estimate the rotational component of velocity of the swirl flow as well as measuring the multi-dimensional velocity vector at high temporal resolutions of 0.2 s. (author)

A new multidimensional model with text dimensions: definition and implementation

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MariaJ. Martin-Bautista

2013-02-01

Full Text Available We present a new multidimensional model with textual dimensions based on a knowledge structure extracted from the texts, where any textual attribute in a database can be processed, and not only XML texts. This dimension allows to treat the textual data in the same way as the non-textual one in an automatic way, without user's intervention, so all the classical operations in the multidimensional model can been defined for this textual dimension. While most of the models dealing with texts that can be found in the literature are not implemented, in this proposal, the multidimensional model and the OLAP system have been implemented in a software tool, so it can be tested on real data. A case study with medical data is included in this work.

Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA

Science.gov (United States)

Messer, O. E. B.; Harris, J. A.; Hix, W. R.; Lentz, E. J.; Bruenn, S. W.; Mezzacappa, A.

2018-04-01

Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport, and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.

Gene expression profiles in prostate cancer: identification of candidate non-invasive diagnostic markers.

Science.gov (United States)

Mengual, L; Ars, E; Lozano, J J; Burset, M; Izquierdo, L; Ingelmo-Torres, M; Gaya, J M; Algaba, F; Villavicencio, H; Ribal, M J; Alcaraz, A

2014-04-01

To analyze gene expression profiles of prostate cancer (PCa) with the aim of determining the relevant differentially expressed genes and subsequently ascertain whether this differential expression is maintained in post-prostatic massage (PPM) urine samples. Forty-six tissue specimens (36 from PCa patients and 10 controls) and 158 urine PPM-urines (113 from PCa patients and 45 controls) were collected between December 2003 and May 2007. DNA microarrays were used to identify genes differentially expressed between tumour and control samples. Ten genes were technically validated in the same tissue samples by quantitative RT-PCR (RT-qPCR). Forty two selected differentially expressed genes were validated in an independent set of PPM-urines by qRT-PCR. Multidimensional scaling plot according to the expression of all the microarray genes showed a clear distinction between control and tumour samples. A total of 1047 differentially expressed genes (FDR≤.1) were indentified between both groups of samples. We found a high correlation in the comparison of microarray and RT-qPCR gene expression levels (r=.928, P<.001). Thirteen genes maintained the same fold change direction when analyzed in PPM-urine samples and in four of them (HOXC6, PCA3, PDK4 and TMPRSS2-ERG), these differences were statistically significant (P<.05). The analysis of PCa by DNA microarrays provides new putative mRNA markers for PCa diagnosis that, with caution, can be extrapolated to PPM-urines. Copyright © 2013 AEU. Published by Elsevier Espana. All rights reserved.

Multi-dimensional quasitoeplitz Markov chains

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Alexander N. Dudin

1999-01-01

Full Text Available This paper deals with multi-dimensional quasitoeplitz Markov chains. We establish a sufficient equilibrium condition and derive a functional matrix equation for the corresponding vector-generating function, whose solution is given algorithmically. The results are demonstrated in the form of examples and applications in queues with BMAP-input, which operate in synchronous random environment.

Multidimensional integral representations problems of analytic continuation

CERN Document Server

Kytmanov, Alexander M

2015-01-01

The monograph is devoted to integral representations for holomorphic functions in several complex variables, such as Bochner-Martinelli, Cauchy-Fantappiè, Koppelman, multidimensional logarithmic residue etc., and their boundary properties. The applications considered are problems of analytic continuation of functions from the boundary of a bounded domain in C^n. In contrast to the well-known Hartogs-Bochner theorem, this book investigates functions with the one-dimensional property of holomorphic extension along complex lines, and includes the problems of receiving multidimensional boundary analogs of the Morera theorem.   This book is a valuable resource for specialists in complex analysis, theoretical physics, as well as graduate and postgraduate students with an understanding of standard university courses in complex, real and functional analysis, as well as algebra and geometry.

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork

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Druka Arnis

2008-11-01

Full Text Available Abstract Background A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community. Description Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits. Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them. Conclusion By

Development and application of computer codes for multidimensional thermalhydraulic analyses of nuclear reactor components

International Nuclear Information System (INIS)

Carver, M.B.

1983-01-01

Components of reactor systems and related equipment are identified in which multidimensional computational thermal hydraulics can be used to advantage to assess and improve design. Models of single- and two-phase flow are reviewed, and the governing equations for multidimensional analysis are discussed. Suitable computational algorithms are introduced, and sample results from the application of particular multidimensional computer codes are given

Pathways into chronic multidimensional poverty amongst older people: a longitudinal study.

Science.gov (United States)

Callander, Emily J; Schofield, Deborah J

2016-03-07

The use of multidimensional poverty measures is becoming more common for measuring the living standards of older people. However, the pathways into poverty are relatively unknown, nor is it known how this affects the length of time people are in poverty for. Using Waves 1 to 12 of the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) survey, longitudinal analysis was undertaken to identify the order that key forms of disadvantage develop - poor health, low income and insufficient education attainment - amongst Australians aged 65 years and over in multidimensional poverty, and the relationship this has with chronic poverty. Path analysis and linear regression models were used. For all older people with at least a Year 10 level of education attainment earlier mental health was significantly related to later household income (p = 0.001) and wealth (p = 0.017). For all older people with at less than a Year 10 level of education attainment earlier household income was significantly related to later mental health (p = 0.021). When limited to those in multidimensional poverty who were in income poverty and also had poor health, older people generally fell into income poverty first and then developed poor health. The order in which income poverty and poor health were developed had a significant influence on the length of time older people with less than a Year 10 level of education attainment were in multidimensional poverty for. Those who developed poor health first then fell into income poverty spend significantly less time in multidimensional poverty (-4.90, p poverty then developed poor health. Knowing the order that different forms of disadvantage develop, and the influence this has on poverty entrenchment, is of use to policy makers wishing to provide interventions to prevent older people being in long-term multidimensional poverty.

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

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Gaora Peadar Ó

2010-10-01

Full Text Available Abstract Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of

Estimate of pulse-sequence data acquisition system for multi-dimensional measurement

Energy Technology Data Exchange (ETDEWEB)

Kitamura, Yasunori; Sakae, Takeji; Nohtomi, Akihiro; Matoba, Masaru [Kyushu Univ., Fukuoka (Japan). Faculty of Engineering; Matsumoto, Yuzuru

1996-07-01

A pulse-sequence data acquisition system has been newly designed and estimated for the measurement of one- or multi-dimensional pulse train coming from radiation detectors. In this system, in order to realize the pulse-sequence data acquisition, the arrival time of each pulse is recorded to a memory of a personal computer (PC). For the multi-dimensional data acquisition with several input channels, each arrival-time data is tagged with a `flag` which indicates the input channel of arriving pulse. Counting losses due to the existence of processing time of the PC are expected to be reduced by using a First-In-First-Out (FIFO) memory unit. In order to verify this system, a computer simulation was performed, Various sets of random pulse trains with different mean pulse rate (1-600 kcps) were generated by using Monte Carlo simulation technique. Those pulse trains were dealt with another code which simulates the newly-designed data acquisition system including a FIFO memory unit; the memory size was assumed to be 0-100 words. And the recorded pulse trains on the PC with the various FIFO memory sizes have been observed. From the result of the simulation, it appears that the system with 3 words FIFO memory unit works successfully up to the pulse rate of 10 kcps without any severe counting losses. (author)

Estimate of pulse-sequence data acquisition system for multi-dimensional measurement

International Nuclear Information System (INIS)

Kitamura, Yasunori; Sakae, Takeji; Nohtomi, Akihiro; Matoba, Masaru; Matsumoto, Yuzuru.

1996-01-01

A pulse-sequence data acquisition system has been newly designed and estimated for the measurement of one- or multi-dimensional pulse train coming from radiation detectors. In this system, in order to realize the pulse-sequence data acquisition, the arrival time of each pulse is recorded to a memory of a personal computer (PC). For the multi-dimensional data acquisition with several input channels, each arrival-time data is tagged with a 'flag' which indicates the input channel of arriving pulse. Counting losses due to the existence of processing time of the PC are expected to be reduced by using a First-In-First-Out (FIFO) memory unit. In order to verify this system, a computer simulation was performed, Various sets of random pulse trains with different mean pulse rate (1-600 kcps) were generated by using Monte Carlo simulation technique. Those pulse trains were dealt with another code which simulates the newly-designed data acquisition system including a FIFO memory unit; the memory size was assumed to be 0-100 words. And the recorded pulse trains on the PC with the various FIFO memory sizes have been observed. From the result of the simulation, it appears that the system with 3 words FIFO memory unit works successfully up to the pulse rate of 10 kcps without any severe counting losses. (author)

Identification and Validation of a New Set of Five Genes for Prediction of Risk in Early Breast Cancer

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Giorgio Mustacchi

2013-05-01

Full Text Available Molecular tests predicting the outcome of breast cancer patients based on gene expression levels can be used to assist in making treatment decisions after consideration of conventional markers. In this study we identified a subset of 20 mRNA differentially regulated in breast cancer analyzing several publicly available array gene expression data using R/Bioconductor package. Using RTqPCR we evaluate 261 consecutive invasive breast cancer cases not selected for age, adjuvant treatment, nodal and estrogen receptor status from paraffin embedded sections. The biological samples dataset was split into a training (137 cases and a validation set (124 cases. The gene signature was developed on the training set and a multivariate stepwise Cox analysis selected five genes independently associated with DFS: FGF18 (HR = 1.13, p = 0.05, BCL2 (HR = 0.57, p = 0.001, PRC1 (HR = 1.51, p = 0.001, MMP9 (HR = 1.11, p = 0.08, SERF1a (HR = 0.83, p = 0.007. These five genes were combined into a linear score (signature weighted according to the coefficients of the Cox model, as: 0.125FGF18 − 0.560BCL2 + 0.409PRC1 + 0.104MMP9 − 0.188SERF1A (HR = 2.7, 95% CI = 1.9–4.0, p < 0.001. The signature was then evaluated on the validation set assessing the discrimination ability by a Kaplan Meier analysis, using the same cut offs classifying patients at low, intermediate or high risk of disease relapse as defined on the training set (p < 0.001. Our signature, after a further clinical validation, could be proposed as prognostic signature for disease free survival in breast cancer patients where the indication for adjuvant chemotherapy added to endocrine treatment is uncertain.

Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies

Science.gov (United States)

Medina, Ignacio; Montaner, David; Bonifaci, Nuria; Pujana, Miguel Angel; Carbonell, José; Tarraga, Joaquin; Al-Shahrour, Fatima; Dopazo, Joaquin

2009-01-01

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/ PMID:19502494

Multi-dimensional database design and implementation of dam safety monitoring system

Directory of Open Access Journals (Sweden)

Zhao Erfeng

2008-09-01

Full Text Available To improve the effectiveness of dam safety monitoring database systems, the development process of a multi-dimensional conceptual data model was analyzed and a logic design was achieved in multi-dimensional database mode. The optimal data model was confirmed by identifying data objects, defining relations and reviewing entities. The conversion of relations among entities to external keys and entities and physical attributes to tables and fields was interpreted completely. On this basis, a multi-dimensional database that reflects the management and analysis of a dam safety monitoring system on monitoring data information has been established, for which factual tables and dimensional tables have been designed. Finally, based on service design and user interface design, the dam safety monitoring system has been developed with Delphi as the development tool. This development project shows that the multi-dimensional database can simplify the development process and minimize hidden dangers in the database structure design. It is superior to other dam safety monitoring system development models and can provide a new research direction for system developers.

Self-organizing maps of Kohonen (SOM) applied to multidimensional monitoring data of the IEA-R1 nuclear research reactor

International Nuclear Information System (INIS)

Affonso, Gustavo S.; Pereira, Iraci M.; Mesquita, Roberto N. de; Bueno, Elaine I.

2011-01-01

Multivariate statistics comprise a set of statistical methods used in situations where many variables are database space subsets. Initially applied to human, social and biological sciences, these methods are being applied to many other areas such as education, geology, chemistry, physics, engineering, and many others. This spectra expansion was possible due to recent technological development of computation hardware and software that allows high and complex databases to be treated iteratively enabling further analysis. Following this trend, the neural networks called Self-Organizing Maps are turning into a powerful tool on visualization of implicit and unknown correlations in big sized database sets. Originally created by Kohonen in 1981, it was applied to speech recognition tasks. The SOM is being used as a comparative parameter to evaluate the performance of new multidimensional analysis methodologies. Most of methods require good variable input selection criteria and SOM has contributed to clustering, classification and prediction of multidimensional engineering process variables. This work proposes a method of applying SOM to a set of 58 IEA-R1 operational variables at IPEN research reactor which are monitored by a Data Acquisition System (DAS). This data set includes variables as temperature, flow mass rate, coolant level, nuclear radiation, nuclear power and control bars position. DAS enables the creation and storage of historical data which are used to contribute to Failure Detection and Monitoring System development. Results show good agreement with previous studies using other methods as GMDH and other predictive methods. (author)

Self-organizing maps of Kohonen (SOM) applied to multidimensional monitoring data of the IEA-R1 nuclear research reactor

Energy Technology Data Exchange (ETDEWEB)

Affonso, Gustavo S.; Pereira, Iraci M.; Mesquita, Roberto N. de, E-mail: rnavarro@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Bueno, Elaine I., E-mail: ebueno@ifsp.gov.b [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), SP (Brazil)

2011-07-01

Multivariate statistics comprise a set of statistical methods used in situations where many variables are database space subsets. Initially applied to human, social and biological sciences, these methods are being applied to many other areas such as education, geology, chemistry, physics, engineering, and many others. This spectra expansion was possible due to recent technological development of computation hardware and software that allows high and complex databases to be treated iteratively enabling further analysis. Following this trend, the neural networks called Self-Organizing Maps are turning into a powerful tool on visualization of implicit and unknown correlations in big sized database sets. Originally created by Kohonen in 1981, it was applied to speech recognition tasks. The SOM is being used as a comparative parameter to evaluate the performance of new multidimensional analysis methodologies. Most of methods require good variable input selection criteria and SOM has contributed to clustering, classification and prediction of multidimensional engineering process variables. This work proposes a method of applying SOM to a set of 58 IEA-R1 operational variables at IPEN research reactor which are monitored by a Data Acquisition System (DAS). This data set includes variables as temperature, flow mass rate, coolant level, nuclear radiation, nuclear power and control bars position. DAS enables the creation and storage of historical data which are used to contribute to Failure Detection and Monitoring System development. Results show good agreement with previous studies using other methods as GMDH and other predictive methods. (author)

Multi-dimensional indoor location information model

NARCIS (Netherlands)

Xiong, Q.; Zhu, Q.; Zlatanova, S.; Huang, L.; Zhou, Y.; Du, Z.

2013-01-01

Aiming at the increasing requirements of seamless indoor and outdoor navigation and location service, a Chinese standard of Multidimensional Indoor Location Information Model is being developed, which defines ontology of indoor location. The model is complementary to 3D concepts like CityGML and

Identifying genetic marker sets associated with phenotypes via an efficient adaptive score test

KAUST Repository

Cai, T.; Lin, X.; Carroll, R. J.

2012-01-01

the overall effect of a marker-set have been actively studied in recent years. For example, score tests derived under an Empirical Bayes (EB) framework (Liu and others, 2007. Semiparametric regression of multidimensional genetic pathway data: least

The multidimensional nucleon structure

Directory of Open Access Journals (Sweden)

Pasquini Barbara

2016-01-01

Full Text Available We discuss different kinds of parton distributions, which allow one to obtain a multidimensional picture of the internal structure of the nucleon. We use the concept of generalized transverse momentum dependent parton distributions and Wigner distributions, which combine the features of transverse-momentum dependent parton distributions and generalized parton distributions. We show examples of these functions within a phenomenological quark model, with focus on the role of the spin-spin and spin-orbit correlations of quarks.

Multi-Dimensional Customer Data Analysis in Online Auctions

Institute of Scientific and Technical Information of China (English)

LAO Guoling; XIONG Kuan; QIN Zheng

2007-01-01

In this paper, we designed a customer-centered data warehouse system with five subjects: listing, bidding, transaction,accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example,analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types: impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.

Multidimensional artificial field embedding with spatial sensitivity

CSIR Research Space (South Africa)

Lunga, D

2013-06-01

Full Text Available Multidimensional embedding is a technique useful for characterizing spectral signature relations in hyperspectral images. However, such images consist of disjoint similar spectral classes that are spatially sensitive, thus presenting challenges...

Assessment of health surveys: fitting a multidimensional graded response model.

Science.gov (United States)

Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

Bridging cancer biology with the clinic: relative expression of a GRHL2-mediated gene-set pair predicts breast cancer metastasis.

Directory of Open Access Journals (Sweden)

Xinan Yang

Full Text Available Identification and characterization of crucial gene target(s that will allow focused therapeutics development remains a challenge. We have interrogated the putative therapeutic targets associated with the transcription factor Grainy head-like 2 (GRHL2, a critical epithelial regulatory factor. We demonstrate the possibility to define the molecular functions of critical genes in terms of their personalized expression profiles, allowing appropriate functional conclusions to be derived. A novel methodology, relative expression analysis with gene-set pairs (RXA-GSP, is designed to explore the potential clinical utility of cancer-biology discovery. Observing that Grhl2-overexpression leads to increased metastatic potential in vitro, we established a model assuming Grhl2-induced or -inhibited genes confer poor or favorable prognosis respectively for cancer metastasis. Training on public gene expression profiles of 995 breast cancer patients, this method prioritized one gene-set pair (GRHL2, CDH2, FN1, CITED2, MKI67 versus CTNNB1 and CTNNA3 from all 2717 possible gene-set pairs (GSPs. The identified GSP significantly dichotomized 295 independent patients for metastasis-free survival (log-rank tested p = 0.002; severe empirical p = 0.035. It also showed evidence of clinical prognostication in another independent 388 patients collected from three studies (log-rank tested p = 3.3e-6. This GSP is independent of most traditional prognostic indicators, and is only significantly associated with the histological grade of breast cancer (p = 0.0017, a GRHL2-associated clinical character (p = 6.8e-6, Spearman correlation, suggesting that this GSP is reflective of GRHL2-mediated events. Furthermore, a literature review indicates the therapeutic potential of the identified genes. This research demonstrates a novel strategy to integrate both biological experiments and clinical gene expression profiles for extracting and elucidating the genomic

MCMC estimation of multidimensional IRT models

NARCIS (Netherlands)

Beguin, Anton; Glas, Cornelis A.W.

1998-01-01

A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization to a model with multidimensional ability parameters are discussed. The procedure is a generalization of a procedure by J. Albert (1992) for estimating the two-parameter normal ogive model. The procedure will

Implementation of multidimensional databases in column-oriented NoSQL systems

OpenAIRE

Chevalier, Max; El Malki, Mohammed; Kopliku, Arlind; Teste, Olivier; Tournier, Ronan

2015-01-01

International audience; NoSQL (Not Only SQL) systems are becoming popular due to known advantages such as horizontal scalability and elasticity. In this paper, we study the implementation of multidimensional data warehouses with columnoriented NoSQL systems. We define mapping rules that transform the conceptual multidimensional data model to logical column-oriented models. We consider three different logical models and we use them to instantiate data warehouses. We focus on data loading, mode...

Portable laser synthesizer for high-speed multi-dimensional spectroscopy

Science.gov (United States)

Demos, Stavros G [Livermore, CA; Shverdin, Miroslav Y [Sunnyvale, CA; Shirk, Michael D [Brentwood, CA

2012-05-29

Portable, field-deployable laser synthesizer devices designed for multi-dimensional spectrometry and time-resolved and/or hyperspectral imaging include a coherent light source which simultaneously produces a very broad, energetic, discrete spectrum spanning through or within the ultraviolet, visible, and near infrared wavelengths. The light output is spectrally resolved and each wavelength is delayed with respect to each other. A probe enables light delivery to a target. For multidimensional spectroscopy applications, the probe can collect the resulting emission and deliver this radiation to a time gated spectrometer for temporal and spectral analysis.

Comparative genomic analysis of Brucella abortus vaccine strain 104M reveals a set of candidate genes associated with its virulence attenuation.

Science.gov (United States)

Yu, Dong; Hui, Yiming; Zai, Xiaodong; Xu, Junjie; Liang, Long; Wang, Bingxiang; Yue, Junjie; Li, Shanhu

2015-01-01

The Brucella abortus strain 104M, a spontaneously attenuated strain, has been used as a vaccine strain in humans against brucellosis for 6 decades in China. Despite many studies, the molecular mechanisms that cause the attenuation are still unclear. Here, we determined the whole-genome sequence of 104M and conducted a comprehensive comparative analysis against the whole genome sequences of the virulent strain, A13334, and other reference strains. This analysis revealed a highly similar genome structure between 104M and A13334. The further comparative genomic analysis between 104M and A13334 revealed a set of genes missing in 104M. Some of these genes were identified to be directly or indirectly associated with virulence. Similarly, a set of mutations in the virulence-related genes was also identified, which may be related to virulence alteration. This study provides a set of candidate genes associated with virulence attenuation in B.abortus vaccine strain 104M.

Effect Size Measures for Differential Item Functioning in a Multidimensional IRT Model

Science.gov (United States)

Suh, Youngsuk

2016-01-01

This study adapted an effect size measure used for studying differential item functioning (DIF) in unidimensional tests and extended the measure to multidimensional tests. Two effect size measures were considered in a multidimensional item response theory model: signed weighted P-difference and unsigned weighted P-difference. The performance of…

Phase space eigenfunctions of multidimensional quadratic Hamiltonians

International Nuclear Information System (INIS)

Dodonov, V.V.; Man'ko, V.I.

1986-01-01

We obtain the explicit expressions for phace space eigenfunctions (PSE),i.e. Weyl's symbols of dyadic operators like vertical stroken> ,vertical strokem>, being the solution of the Schroedinger equation with the Hamiltonian which is a quite arbitrary multidimensional quadratic form of the operators of Cartesian coordinates and conjugated to them momenta with time-dependent coefficients. It is shown that for an arbitrary quadratic Hamiltonian one can always construct the set of completely factorized PSE which are products of N factors, each factor being dependent only on two arguments for nnot=m and on a single argument for n=m. These arguments are nothing but constants of motion of the correspondent classical system. PSE are expressed in terms of the associated Laguerre polynomials in the case of a discrete spectrum and in terms of the Airy functions in the continuous spectrum case. Three examples are considered: a harmonic oscillator with a time-dependent frequency, a charged particle in a nonstationary uniform magnetic field, and a particle in a time-dependent uniform potential field. (orig.)

Development and assessment of multi-dimensional flow model in MARS compared with the RPI air-water experiment

International Nuclear Information System (INIS)

Lee, Seok Min; Lee, Un Chul; Bae, Sung Won; Chung, Bub Dong

2004-01-01

The Multi-Dimensional flow models in system code have been developed during the past many years. RELAP5-3D, CATHARE and TRACE has its specific multi-dimensional flow models and successfully applied it to the system safety analysis. In KAERI, also, MARS(Multi-dimensional Analysis of Reactor Safety) code was developed by integrating RELAP5/MOD3 code and COBRA-TF code. Even though COBRA-TF module can analyze three-dimensional flow models, it has a limitation to apply 3D shear stress dominant phenomena or cylindrical geometry. Therefore, Multi-dimensional analysis models are newly developed by implementing three-dimensional momentum flux and diffusion terms. The multi-dimensional model has been assessed compared with multi-dimensional conceptual problems and CFD code results. Although the assessment results were reasonable, the multi-dimensional model has not been validated to two-phase flow using experimental data. In this paper, the multi-dimensional air-water two-phase flow experiment was simulated and analyzed

A reference gene set for sex pheromone biosynthesis and degradation genes from the diamondback moth, Plutella xylostella, based on genome and transcriptome digital gene expression analyses.

Science.gov (United States)

He, Peng; Zhang, Yun-Fei; Hong, Duan-Yang; Wang, Jun; Wang, Xing-Liang; Zuo, Ling-Hua; Tang, Xian-Fu; Xu, Wei-Ming; He, Ming

2017-03-01

comprehensive gene data set of sex pheromone biosynthesis and degradation enzyme related genes in DBM created by genome- and transcriptome-wide identification, characterization and expression profiling. Our findings provide a basis to better understand the function of genes with tissue enriched expression. The results also provide information on the genes involved in sex pheromone biosynthesis and degradation, and may be useful to identify potential gene targets for pest control strategies by disrupting the insect-insect communication using pheromone-based behavioral antagonists.

Implementation of the Multidimensional Modeling Concepts into Object-Relational Databases

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available A key to survival in the business world is being able to analyze, plan and react to changing business conditions as fast as possible. With multidimensional models the managers can explore information at different levels of granularity and the decision makers at all levels can quickly respond to changes in the business climate-the ultimate goal of business intelligence. This paper focuses on the implementation of the multidimensional concepts into object-relational databases.

Deriving Multidimensional Poverty Indicators: Methodological Issues and an Empirical Analysis for Italy

Science.gov (United States)

Coromaldi, Manuela; Zoli, Mariangela

2012-01-01

Theoretical and empirical studies have recently adopted a multidimensional concept of poverty. There is considerable debate about the most appropriate degree of multidimensionality to retain in the analysis. In this work we add to the received literature in two ways. First, we derive indicators of multiple deprivation by applying a particular…

Measures for a multidimensional multiverse

Science.gov (United States)

Chung, Hyeyoun

2015-04-01

We explore the phenomenological implications of generalizing the causal patch and fat geodesic measures to a multidimensional multiverse, where the vacua can have differing numbers of large dimensions. We consider a simple model in which the vacua are nucleated from a D -dimensional parent spacetime through dynamical compactification of the extra dimensions, and compute the geometric contribution to the probability distribution of observations within the multiverse for each measure. We then study how the shape of this probability distribution depends on the time scales for the existence of observers, for vacuum domination, and for curvature domination (tobs,tΛ , and tc, respectively.) In this work we restrict ourselves to bubbles with positive cosmological constant, Λ . We find that in the case of the causal patch cutoff, when the bubble universes have p +1 large spatial dimensions with p ≥2 , the shape of the probability distribution is such that we obtain the coincidence of time scales tobs˜tΛ˜tc . Moreover, the size of the cosmological constant is related to the size of the landscape. However, the exact shape of the probability distribution is different in the case p =2 , compared to p ≥3 . In the case of the fat geodesic measure, the result is even more robust: the shape of the probability distribution is the same for all p ≥2 , and we once again obtain the coincidence tobs˜tΛ˜tc . These results require only very mild conditions on the prior probability of the distribution of vacua in the landscape. Our work shows that the observed double coincidence of time scales is a robust prediction even when the multiverse is generalized to be multidimensional; that this coincidence is not a consequence of our particular Universe being (3 +1 )-dimensional; and that this observable cannot be used to preferentially select one measure over another in a multidimensional multiverse.

The role of multidimensional instabilities in direct initiation of gaseous detonations in free space

KAUST Repository

Shen, Hua

2017-01-20

We numerically investigate the direct initiation of detonations driven by the propagation of a blast wave into a unconfined gaseous combustible mixture to study the role played by multidimensional instabilities in direct initiation of stable and unstable detonations. To this end, we first model the dynamics of unsteady propagation of detonation using the one-dimensional compressible Euler equations with a one-step chemical reaction model and cylindrical geometrical source terms. Subsequently, we use two-dimensional compressible Euler equations with just the chemical reaction source term to directly model cylindrical detonations. The one-dimensional results suggest that there are three regimes in the direct initiation for stable detonations, that the critical energy for mildly unstable detonations is not unique, and that highly unstable detonations are not self-sustainable. These phenomena agree well with one-dimensional theories and computations available in the literature. However, our two-dimensional results indicate that one-dimensional approaches are valid only for stable detonations. In mildly and highly unstable detonations, one-dimensional approaches break down because they cannot take the effects and interactions of multidimensional instabilities into account. In fact, instabilities generated in multidimensional settings yield the formation of strong transverse waves that, on one hand, increase the risk of failure of the detonation and, on the other hand, lead to the initiation of local over-driven detonations that enhance the overall self-sustainability of the global process. The competition between these two possible outcomes plays an important role in the direct initiation of detonations.

Multidimensional HAM-conditions

DEFF Research Database (Denmark)

Hansen, Ernst Jan de Place

Heat, Air and Moisture (HAM) conditions, experimental data are needed. Tests were performed in the large climate simulator at SBi involving full-scale wall elements. The elements were exposed for steady-state conditions, and temperature cycles simulating April and September climate in Denmark....... The effect on the moisture and temperature conditions of the addition of a vapour barrier and an outer cladding on timber frame walls was studied. The report contains comprehensive appendices documenting the full-scale tests. The tests were performed as a part of the project 'Model for Multidimensional Heat......, Air and Moisture Conditions in Building Envelope Components' carried out as a co-project between DTU Byg and SBi....

SM4MQ: A Semantic Model for Multidimensional Queries

DEFF Research Database (Denmark)

Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar

2017-01-01

On-Line Analytical Processing (OLAP) is a data analysis approach to support decision-making. On top of that, Exploratory OLAP is a novel initiative for the convergence of OLAP and the Semantic Web (SW) that enables the use of OLAP techniques on SW data. Moreover, OLAP approaches exploit different......, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD) data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply...

Identification of a novel set of genes reflecting different in vivo invasive patterns of human GBM cells

International Nuclear Information System (INIS)

Monticone, Massimiliano; Giaretti, Walter; Pfeffer, Ulrich; Daga, Antonio; Candiani, Simona; Romeo, Francesco; Mirisola, Valentina; Viaggi, Silvia; Melloni, Ilaria; Pedemonte, Simona; Zona, Gianluigi

2012-01-01

Most patients affected by Glioblastoma multiforme (GBM, grade IV glioma) experience a recurrence of the disease because of the spreading of tumor cells beyond surgical boundaries. Unveiling mechanisms causing this process is a logic goal to impair the killing capacity of GBM cells by molecular targeting. We noticed that our long-term GBM cultures, established from different patients, may display two categories/types of growth behavior in an orthotopic xenograft model: expansion of the tumor mass and formation of tumor branches/nodules (nodular like, NL-type) or highly diffuse single tumor cell infiltration (HD-type). We determined by DNA microarrays the gene expression profiles of three NL-type and three HD-type long-term GBM cultures. Subsequently, individual genes with different expression levels between the two groups were identified using Significance Analysis of Microarrays (SAM). Real time RT-PCR, immunofluorescence and immunoblot analyses, were performed for a selected subgroup of regulated gene products to confirm the results obtained by the expression analysis. Here, we report the identification of a set of 34 differentially expressed genes in the two types of GBM cultures. Twenty-three of these genes encode for proteins localized to the plasma membrane and 9 of these for proteins are involved in the process of cell adhesion. This study suggests the participation in the diffuse infiltrative/invasive process of GBM cells within the CNS of a novel set of genes coding for membrane-associated proteins, which should be thus susceptible to an inhibition strategy by specific targeting. Massimiliano Monticone and Antonio Daga contributed equally to this work

Identification of a novel set of genes reflecting different in vivo invasive patterns of human GBM cells.

Science.gov (United States)

Monticone, Massimiliano; Daga, Antonio; Candiani, Simona; Romeo, Francesco; Mirisola, Valentina; Viaggi, Silvia; Melloni, Ilaria; Pedemonte, Simona; Zona, Gianluigi; Giaretti, Walter; Pfeffer, Ulrich; Castagnola, Patrizio

2012-08-17

Most patients affected by Glioblastoma multiforme (GBM, grade IV glioma) experience a recurrence of the disease because of the spreading of tumor cells beyond surgical boundaries. Unveiling mechanisms causing this process is a logic goal to impair the killing capacity of GBM cells by molecular targeting.We noticed that our long-term GBM cultures, established from different patients, may display two categories/types of growth behavior in an orthotopic xenograft model: expansion of the tumor mass and formation of tumor branches/nodules (nodular like, NL-type) or highly diffuse single tumor cell infiltration (HD-type). We determined by DNA microarrays the gene expression profiles of three NL-type and three HD-type long-term GBM cultures. Subsequently, individual genes with different expression levels between the two groups were identified using Significance Analysis of Microarrays (SAM). Real time RT-PCR, immunofluorescence and immunoblot analyses, were performed for a selected subgroup of regulated gene products to confirm the results obtained by the expression analysis. Here, we report the identification of a set of 34 differentially expressed genes in the two types of GBM cultures. Twenty-three of these genes encode for proteins localized to the plasma membrane and 9 of these for proteins are involved in the process of cell adhesion. This study suggests the participation in the diffuse infiltrative/invasive process of GBM cells within the CNS of a novel set of genes coding for membrane-associated proteins, which should be thus susceptible to an inhibition strategy by specific targeting.Massimiliano Monticone and Antonio Daga contributed equally to this work.

Multi-dimensional design window search system using neural networks in reactor core design

International Nuclear Information System (INIS)

Kugo, Teruhiko; Nakagawa, Masayuki

2000-02-01

In the reactor core design, many parametric survey calculations should be carried out to decide an optimal set of basic design parameter values. They consume a large amount of computation time and labor in the conventional way. To support directly design work, we investigate a procedure to search efficiently a design window, which is defined as feasible design parameter ranges satisfying design criteria and requirements, in a multi-dimensional space composed of several basic design parameters. We apply the present method to the neutronics and thermal hydraulics fields and develop the multi-dimensional design window search system using it. The principle of the present method is to construct the multilayer neural network to simulate quickly a response of an analysis code through a training process, and to reduce computation time using the neural network without parametric study using analysis codes. The system works on an engineering workstation (EWS) with efficient man-machine interface for pre- and post-processing. This report describes the principle of the present method, the structure of the system, the guidance of the usages of the system, the guideline for the efficient training of neural networks, the instructions of the input data for analysis calculation and so on. (author)

Modelling of multidimensional quantum systems by the numerical functional integration

International Nuclear Information System (INIS)

Lobanov, Yu.Yu.; Zhidkov, E.P.

1990-01-01

The employment of the numerical functional integration for the description of multidimensional systems in quantum and statistical physics is considered. For the multiple functional integrals with respect to Gaussian measures in the full separable metric spaces the new approximation formulas exact on a class of polynomial functionals of a given summary degree are constructed. The use of the formulas is demonstrated on example of computation of the Green function and the ground state energy in multidimensional Calogero model. 15 refs.; 2 tabs

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

Energy Technology Data Exchange (ETDEWEB)

Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

International Nuclear Information System (INIS)

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-01-01

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC

Comparative genomic analysis of SET domain family reveals the origin, expansion, and putative function of the arthropod-specific SmydA genes as histone modifiers in insects.

Science.gov (United States)

Jiang, Feng; Liu, Qing; Wang, Yanli; Zhang, Jie; Wang, Huimin; Song, Tianqi; Yang, Meiling; Wang, Xianhui; Kang, Le

2017-06-01

The SET domain is an evolutionarily conserved motif present in histone lysine methyltransferases, which are important in the regulation of chromatin and gene expression in animals. In this study, we searched for SET domain-containing genes (SET genes) in all of the 147 arthropod genomes sequenced at the time of carrying out this experiment to understand the evolutionary history by which SET domains have evolved in insects. Phylogenetic and ancestral state reconstruction analysis revealed an arthropod-specific SET gene family, named SmydA, that is ancestral to arthropod animals and specifically diversified during insect evolution. Considering that pseudogenization is the most probable fate of the new emerging gene copies, we provided experimental and evolutionary evidence to demonstrate their essential functions. Fluorescence in situ hybridization analysis and in vitro methyltransferase activity assays showed that the SmydA-2 gene was transcriptionally active and retained the original histone methylation activity. Expression knockdown by RNA interference significantly increased mortality, implying that the SmydA genes may be essential for insect survival. We further showed predominantly strong purifying selection on the SmydA gene family and a potential association between the regulation of gene expression and insect phenotypic plasticity by transcriptome analysis. Overall, these data suggest that the SmydA gene family retains essential functions that may possibly define novel regulatory pathways in insects. This work provides insights into the roles of lineage-specific domain duplication in insect evolution. © The Authors 2017. Published by Oxford University Press.

Resolution Improvement in Multidimensional Nuclear Magnetic Resonance Spectroscopy of Proteins

International Nuclear Information System (INIS)

Duma, L.

2004-01-01

The work presented in this thesis is concerned with both liquid-state and solid-state nuclear magnetic resonance (NMR) spectroscopy. Most of this work is devoted to the investigation by solid-state NMR of C 13 -enriched compounds with the principal aim of presenting techniques devised for further improving the spectral resolution in multidimensional NMR of microcrystalline proteins. In fully C 13 -labelled compounds, the J-coupling induces a broadening of the carbon lineshapes. We show that spin-state-selective technique called IPAP can be successfully combined with standard polarisation transfer schemes in order to remove the J-broadening in multidimensional solid-state NMR correlation experiments of fully C 13 -enriched proteins. We present subsequently two techniques tailored for liquid-state NMR spectroscopy. The carbon directly detected techniques provide chemical shift information for all backbone hetero-nuclei. They are very attracting for the study of large bio-molecular systems or for the investigation of paramagnetic proteins. In the last part of this thesis, we study the spin-echo J-modulation for homonuclear two-spin 1/2 systems. Under magic-angle spinning, the theory of J-induced spin-echo modulation allows to derive a set of modulation regimes which give a spin-echo modulation exactly equal to the J-coupling. We show that the chemical-shift anisotropy and the dipolar interaction tend to stabilize the spin-echo J-modulation. The theoretical conclusions are supported by numerical simulations and experimental results obtained for three representative samples containing C 13 spin pairs. (author)

Multidimensional poverty and catastrophic health spending in the mountainous regions of Myanmar, Nepal and India.

Science.gov (United States)

Mohanty, Sanjay K; Agrawal, Nand Kishor; Mahapatra, Bidhubhusan; Choudhury, Dhrupad; Tuladhar, Sabarnee; Holmgren, E Valdemar

2017-01-18

Economic burden to households due to out-of-pocket expenditure (OOPE) is large in many Asian countries. Though studies suggest increasing household poverty due to high OOPE in developing countries, studies on association of multidimensional poverty and household health spending is limited. This paper tests the hypothesis that the multidimensionally poor are more likely to incur catastrophic health spending cutting across countries. Data from the Poverty and Vulnerability Assessment (PVA) Survey carried out by the International Center for Integrated Mountain Development (ICIMOD) has been used in the analyses. The PVA survey was a comprehensive household survey that covered the mountainous regions of India, Nepal and Myanmar. A total of 2647 households from India, 2310 households in Nepal and 4290 households in Myanmar covered under the PVA survey. Poverty is measured in a multidimensional framework by including the dimensions of education, income and energy, water and sanitation using the Alkire and Foster method. Health shock is measured using the frequency of illness, family sickness and death of any family member in a reference period of one year. Catastrophic health expenditure is defined as 40% above the household's capacity to pay. Results suggest that about three-fifths of the population in Myanmar, two-fifths of the population in Nepal and one-third of the population in India are multidimensionally poor. About 47% of the multidimensionally poor in India had incurred catastrophic health spending compared to 35% of the multidimensionally non-poor and the pattern was similar in both Nepal and Myanmar. The odds of incurring catastrophic health spending was 56% more among the multidimensionally poor than among the multidimensionally non-poor [95% CI: 1.35-1.76]. While health shocks to households are consistently significant predictors of catastrophic health spending cutting across country of residence, the educational attainment of the head of the household is

Quantum and Multidimensional Explanations in a Neurobiological Context of Mind.

Science.gov (United States)

Korf, Jakob

2015-08-01

This article examines the possible relevance of physical-mathematical multidimensional or quantum concepts aiming at understanding the (human) mind in a neurobiological context. Some typical features of the quantum and multidimensional concepts are briefly introduced, including entanglement, superposition, holonomic, and quantum field theories. Next, we consider neurobiological principles, such as the brain and its emerging (physical) mind, evolutionary and ontological origins, entropy, syntropy/neg-entropy, causation, and brain energy metabolism. In many biological processes, including biochemical conversions, protein folding, and sensory perception, the ubiquitous involvement of quantum mechanisms is well recognized. Quantum and multidimensional approaches might be expected to help describe and model both brain and mental processes, but an understanding of their direct involvement in mental activity, that is, without mediation by molecular processes, remains elusive. More work has to be done to bridge the gap between current neurobiological and physical-mathematical concepts with their associated quantum-mind theories. © The Author(s) 2014.

MODA: a new algorithm to compute optical depths in multidimensional hydrodynamic simulations

Science.gov (United States)

Perego, Albino; Gafton, Emanuel; Cabezón, Rubén; Rosswog, Stephan; Liebendörfer, Matthias

2014-08-01

Aims: We introduce the multidimensional optical depth algorithm (MODA) for the calculation of optical depths in approximate multidimensional radiative transport schemes, equally applicable to neutrinos and photons. Motivated by (but not limited to) neutrino transport in three-dimensional simulations of core-collapse supernovae and neutron star mergers, our method makes no assumptions about the geometry of the matter distribution, apart from expecting optically transparent boundaries. Methods: Based on local information about opacities, the algorithm figures out an escape route that tends to minimize the optical depth without assuming any predefined paths for radiation. Its adaptivity makes it suitable for a variety of astrophysical settings with complicated geometry (e.g., core-collapse supernovae, compact binary mergers, tidal disruptions, star formation, etc.). We implement the MODA algorithm into both a Eulerian hydrodynamics code with a fixed, uniform grid and into an SPH code where we use a tree structure that is otherwise used for searching neighbors and calculating gravity. Results: In a series of numerical experiments, we compare the MODA results with analytically known solutions. We also use snapshots from actual 3D simulations and compare the results of MODA with those obtained with other methods, such as the global and local ray-by-ray method. It turns out that MODA achieves excellent accuracy at a moderate computational cost. In appendix we also discuss implementation details and parallelization strategies.

Almost-sure identifiability of multidimensional harmonic retrieval

NARCIS (Netherlands)

Jiang, T; Sidiropoulos, ND; ten Berge, JMF

Two-dimensional (2-D) and, more generally, multidimensional harmonic retrieval is of interest in a variety of applications, including transmitter localization and joint time and frequency offset estimation in wireless communications. The associated identifiability problem is key in understanding the

MODELO MULTIDIMENSIONAL

Directory of Open Access Journals (Sweden)

Alexis Cedeño Trujillo

2006-04-01

Full Text Available

Data Warehousing, es una tecnología para el almacenamiento de grandes volúmenes de datos en una amplia perspectiva de tiempo para el soporte a la toma de decisiones. Debido a su orientación analítica, impone un procesamiento distinto al de los sistemas operacionales y requiere de un diseño de base de datos más cercano a la visión de los usuarios finales, permitiendo que sea más fácil la recuperación de información y la navegación. Este diseño de base de datos se conoce como modelo multidimensional, este artículo, abordará sus características principales.

A Multidimensional Theory of Suicide.

Science.gov (United States)

Leenaars, Antoon A; Dieserud, Gudrun; Wenckstern, Susanne; Dyregrov, Kari; Lester, David; Lyke, Jennifer

2018-04-05

Theory is the foundation of science; this is true in suicidology. Over decades of studies of suicide notes, Leenaars developed a multidimensional model of suicide, with international (crosscultural) studies and independent verification. To corroborate Leenaars's theory with a psychological autopsy (PA) study, examining age and sex of the decedent, and survivor's relationship to deceased. A PA study in Norway, with 120 survivors/informants was undertaken. Leenaars' theoretical-conceptual (protocol) analysis was undertaken of the survivors' narratives and in-depth interviews combined. Substantial interjudge reliability was noted (κ = .632). Overall, there was considerable confirmatory evidence of Leenaars's intrapsychic and interpersonal factors in suicide survivors' narratives. Differences were found in the age of the decedent, but not in sex, nor in the survivor's closeness of the relationship. Older deceased people were perceived to exhibit more heightened unbearable intrapsychic pain, associated with the suicide. Leenaars's theory has corroborative verification, through the decedents' suicide notes and the survivors' narratives. However, the multidimensional model needs further testing to develop a better evidence-based way of understanding suicide.

Confirmatory factor analysis and invariance testing between Blacks and Whites of the Multidimensional Health Locus of Control scale.

Science.gov (United States)

LaNoue, Marianna; Harvey, Abby; Mautner, Dawn; Ku, Bon; Scott, Kevin

2015-07-01

The factor structure of the Multidimensional Health Locus of Control scale remains in question. Additionally, research on health belief differences between Black and White respondents suggests that the Multidimensional Health Locus of Control scale may not be invariant. We reviewed the literature regarding the latent variable structure of the Multidimensional Health Locus of Control scale, used confirmatory factor analysis to confirm the three-factor structure of the Multidimensional Health Locus of Control, and analyzed between-group differences in the Multidimensional Health Locus of Control structure and means across Black and White respondents. Our results indicate differences in means and structure, indicating more research is needed to inform decisions regarding whether and how to deploy the Multidimensional Health Locus of Control appropriately.

Development and Validation of Multi-Dimensional Personality ...

African Journals Online (AJOL)

This study was carried out to establish the scientific processes for the development and validation of Multi-dimensional Personality Inventory (MPI). The process of development and validation occurred in three phases with five components of Agreeableness, Conscientiousness, Emotional stability, Extroversion, and ...

Analysis of Multidimensional Poverty: Theory and Case Studies ...

International Development Research Centre (IDRC) Digital Library (Canada)

2009-08-18

Aug 18, 2009 ... ... of applying a factorial technique, Multiple Correspondence Analysis, to poverty analysis. ... Analysis of Multidimensional Poverty: Theory and Case Studies ... agreement to support joint research projects in December 2017.

Translation and Validation of the Multidimensional Dyspnea-12 Questionnaire.

Science.gov (United States)

Amado Diago, Carlos Antonio; Puente Maestu, Luis; Abascal Bolado, Beatriz; Agüero Calvo, Juan; Hernando Hernando, Mercedes; Puente Bats, Irene; Agüero Balbín, Ramón

2018-02-01

Dyspnea is a multidimensional symptom, but this multidimensionality is not considered in most dyspnea questionnaires. The Dyspnea-12 takes a multidimensional approach to the assessment of dyspnea, specifically the sensory and the affective response. The objective of this study was to translate into Spanish and validate the Dyspnea-12 questionnaire. The original English version of the Dyspnea-12 questionnaire was translated into Spanish and backtranslated to analyze its equivalence. Comprehension of the text was verified by analyzing the responses of 10 patients. Reliability and validation of the questionnaire were studied in an independent group of COPD patients attending the pulmonology clinics of Hospital Universitario Marqués de Valdecilla, diagnosed and categorized according to GOLD guidelines. The mean age of the group (n=51) was 65 years and mean FEV1 was 50%. All patients understood all questions of the translated version of Dyspnea-12. Internal consistency of the questionnaire was α=0.937 and intraclass correlation coefficient was=.969; P<.001. Statistically significant correlations were found with HADS (anxiety r=.608 and depression r=.615), mMRC dyspnea (r=.592), 6MWT (r=-0.445), FEV1 (r=-0.312), all dimensions of CRQ-SAS (dyspnea r=-0.626; fatigue r=-0.718; emotional function r=-0.663; mastery r=-0.740), CAT (r=0.669), and baseline dyspnea index (r=-0.615). Dyspnea-12 scores were 10.32 points higher in symptomatic GOLD groups (B and D) (P<.001). The Spanish version of Dyspnea-12 is a valid and reliable instrument to study the multidimensional nature of dyspnea. Copyright © 2017 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

Multidimensional upwind hydrodynamics on unstructured meshes using graphics processing units - I. Two-dimensional uniform meshes

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Paardekooper, S.-J.

2017-08-01

We present a new method for numerical hydrodynamics which uses a multidimensional generalization of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which commonly use one-dimensional flux estimates as building blocks for a multidimensional integration, is its inherently multidimensional nature, and as a consequence its ability to recognize multidimensional stationary states that are not hydrostatic. A second novelty is the focus on graphics processing units (GPUs). By tailoring the algorithms specifically to GPUs, we are able to get speedups of 100-250 compared to a desktop machine. We compare the multidimensional upwind scheme to a traditional, dimensionally split implementation of the Roe solver on several test problems, and we find that the new method significantly outperforms the Roe solver in almost all cases. This comes with increased computational costs per time-step, which makes the new method approximately a factor of 2 slower than a dimensionally split scheme acting on a structured grid.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels.

Science.gov (United States)

Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J

2017-05-01

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.

Integrating gene transcription-based biomarkers to understand desert tortoise and ecosystem health

Science.gov (United States)

Bowen, Lizabeth; Miles, A. Keith; Drake, Karla K.; Waters, Shannon C.; Esque, Todd C.; Nussear, Kenneth E.

2015-01-01

Tortoises are susceptible to a wide variety of environmental stressors, and the influence of human disturbances on health and survival of tortoises is difficult to detect. As an addition to current diagnostic methods for desert tortoises, we have developed the first leukocyte gene transcription biomarker panel for the desert tortoise (Gopherus agassizii), enhancing the ability to identify specific environmental conditions potentially linked to declining animal health. Blood leukocyte transcript profiles have the potential to identify physiologically stressed animals in lieu of clinical signs. For desert tortoises, the gene transcript profile included a combination of immune or detoxification response genes with the potential to be modified by biological or physical injury and consequently provide information on the type and magnitude of stressors present in the animal’s habitat. Blood from 64 wild adult tortoises at three sites in Clark County, NV, and San Bernardino, CA, and from 19 captive tortoises in Clark County, NV, was collected and evaluated for genes indicative of physiological status. Statistical analysis using a priori groupings indicated significant differences among groups for several genes, while multidimensional scaling and cluster analyses of transcriptionC T values indicated strong differentiation of a large cluster and multiple outlying individual tortoises or small clusters in multidimensional space. These analyses highlight the effectiveness of the gene panel at detecting environmental perturbations as well as providing guidance in determining the health of the desert tortoise.

Identification of a novel set of genes reflecting different in vivo invasive patterns of human GBM cells

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Monticone Massimiliano

2012-08-01

Full Text Available Abstract Background Most patients affected by Glioblastoma multiforme (GBM, grade IV glioma experience a recurrence of the disease because of the spreading of tumor cells beyond surgical boundaries. Unveiling mechanisms causing this process is a logic goal to impair the killing capacity of GBM cells by molecular targeting. We noticed that our long-term GBM cultures, established from different patients, may display two categories/types of growth behavior in an orthotopic xenograft model: expansion of the tumor mass and formation of tumor branches/nodules (nodular like, NL-type or highly diffuse single tumor cell infiltration (HD-type. Methods We determined by DNA microarrays the gene expression profiles of three NL-type and three HD-type long-term GBM cultures. Subsequently, individual genes with different expression levels between the two groups were identified using Significance Analysis of Microarrays (SAM. Real time RT-PCR, immunofluorescence and immunoblot analyses, were performed for a selected subgroup of regulated gene products to confirm the results obtained by the expression analysis. Results Here, we report the identification of a set of 34 differentially expressed genes in the two types of GBM cultures. Twenty-three of these genes encode for proteins localized to the plasma membrane and 9 of these for proteins are involved in the process of cell adhesion. Conclusions This study suggests the participation in the diffuse infiltrative/invasive process of GBM cells within the CNS of a novel set of genes coding for membrane-associated proteins, which should be thus susceptible to an inhibition strategy by specific targeting. Massimiliano Monticone and Antonio Daga contributed equally to this work

Lagrangian multiforms and multidimensional consistency

Energy Technology Data Exchange (ETDEWEB)

Lobb, Sarah; Nijhoff, Frank [Department of Applied Mathematics, University of Leeds, Leeds LS2 9JT (United Kingdom)

2009-10-30

We show that well-chosen Lagrangians for a class of two-dimensional integrable lattice equations obey a closure relation when embedded in a higher dimensional lattice. On the basis of this property we formulate a Lagrangian description for such systems in terms of Lagrangian multiforms. We discuss the connection of this formalism with the notion of multidimensional consistency, and the role of the lattice from the point of view of the relevant variational principle.

Repression of Middle Sporulation Genes in Saccharomyces cerevisiae by the Sum1-Rfm1-Hst1 Complex Is Maintained by Set1 and H3K4 Methylation

Science.gov (United States)

Jaiswal, Deepika; Jezek, Meagan; Quijote, Jeremiah; Lum, Joanna; Choi, Grace; Kulkarni, Rushmie; Park, DoHwan; Green, Erin M.

2017-01-01

The conserved yeast histone methyltransferase Set1 targets H3 lysine 4 (H3K4) for mono, di, and trimethylation and is linked to active transcription due to the euchromatic distribution of these methyl marks and the recruitment of Set1 during transcription. However, loss of Set1 results in increased expression of multiple classes of genes, including genes adjacent to telomeres and middle sporulation genes, which are repressed under normal growth conditions because they function in meiotic progression and spore formation. The mechanisms underlying Set1-mediated gene repression are varied, and still unclear in some cases, although repression has been linked to both direct and indirect action of Set1, associated with noncoding transcription, and is often dependent on the H3K4me2 mark. We show that Set1, and particularly the H3K4me2 mark, are implicated in repression of a subset of middle sporulation genes during vegetative growth. In the absence of Set1, there is loss of the DNA-binding transcriptional regulator Sum1 and the associated histone deacetylase Hst1 from chromatin in a locus-specific manner. This is linked to increased H4K5ac at these loci and aberrant middle gene expression. These data indicate that, in addition to DNA sequence, histone modification status also contributes to proper localization of Sum1. Our results also show that the role for Set1 in middle gene expression control diverges as cells receive signals to undergo meiosis. Overall, this work dissects an unexplored role for Set1 in gene-specific repression, and provides important insights into a new mechanism associated with the control of gene expression linked to meiotic differentiation. PMID:29066473

A set of vectors for introduction of antibiotic resistance genes by in vitro Cre-mediated recombination

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Vassetzky Yegor S

2008-12-01

Full Text Available Abstract Background Introduction of new antibiotic resistance genes in the plasmids of interest is a frequent task in molecular cloning practice. Classical approaches involving digestion with restriction endonucleases and ligation are time-consuming. Findings We have created a set of insertion vectors (pINS carrying genes that provide resistance to various antibiotics (puromycin, blasticidin and G418 and containing a loxP site. Each vector (pINS-Puro, pINS-Blast or pINS-Neo contains either a chloramphenicol or a kanamycin resistance gene and is unable to replicate in most E. coli strains as it contains a conditional R6Kγ replication origin. Introduction of the antibiotic resistance genes into the vector of interest is achieved by Cre-mediated recombination between the replication-incompetent pINS and a replication-competent target vector. The recombination mix is then transformed into E. coli and selected by the resistance marker (kanamycin or chloramphenicol present in pINS, which allows to recover the recombinant plasmids with 100% efficiency. Conclusion Here we propose a simple strategy that allows to introduce various antibiotic-resistance genes into any plasmid containing a replication origin, an ampicillin resistance gene and a loxP site.

Multidimensional Analyses of Long-Term Clinical Courses of Asthma and Chronic Obstructive Pulmonary Disease

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Toru Oga

Full Text Available ABSTRACT: Asthma and chronic obstructive pulmonary disease (COPD are chronic respiratory disorders involving obstructive airway defects. There have been many discussions on their similarities and differences. Although airflow limitation expressed as forced expiratory volume in one second (FEV1 has been considered to be the main diagnostic assessment in both diseases, it does not reflect the functional impairment imparted to the patients by these diseases. Therefore, multidimensional approaches using multiple measurements in assessing disease control or severity have been recommended, and multiple endpoints in addition to FEV1 have been set recently in clinical trials so as not to miss the overall effects. In particular, as improving symptoms and health status as well as pulmonary function are important goals in the management of asthma and COPD, some patient-reported measurements such as health-related quality of life or dyspnea should be included. Nonetheless, there have been few reviews on the long-term clinical course comparing asthma and COPD as predicted by measurements other than airflow limitation. Here, we therefore analyzed and compared longitudinal changes in both physiological measurements and patient-reported measurements in asthma and COPD. Although both diseases showed similar long-term progressive airflow limitation similarly despite guideline-based therapies, disease progression was different in asthma and COPD. In asthma, patient-reported assessments of health status, disability and psychological status remained clinically stable over time, in contrast to the significant deterioration of these parameters in COPD. Thus, because a single measurement of airflow limitation is insufficient to monitor these diseases, multidimensional analyses are important not only for disease control but also for understanding disease progression in asthma and COPD. KEY WORDS: asthma, COPD, longitudinal survey, multidimensional analysis, patient

Wild immunology assessed by multidimensional mass cytometry.

Science.gov (United States)

Japp, Alberto Sada; Hoffmann, Kerstin; Schlickeiser, Stephan; Glauben, Rainer; Nikolaou, Christos; Maecker, Holden T; Braun, Julian; Matzmohr, Nadine; Sawitzki, Birgit; Siegmund, Britta; Radbruch, Andreas; Volk, Hans-Dieter; Frentsch, Marco; Kunkel, Desiree; Thiel, Andreas

2017-01-01

A great part of our knowledge on mammalian immunology has been established in laboratory settings. The use of inbred mouse strains enabled controlled studies of immune cell and molecule functions in defined settings. These studies were usually performed in specific-pathogen free (SPF) environments providing standardized conditions. In contrast, mammalians including humans living in their natural habitat are continuously facing pathogen encounters throughout their life. The influences of environmental conditions on the signatures of the immune system and on experimental outcomes are yet not well defined. Thus, the transferability of results obtained in current experimental systems to the physiological human situation has always been a matter of debate. Studies elucidating the diversity of "wild immunology" imprintings in detail and comparing it with those of "clean" lab mice are sparse. Here, we applied multidimensional mass cytometry to dissect phenotypic and functional differences between distinct groups of laboratory and pet shop mice as a source for "wild mice". For this purpose, we developed a 31-antibody panel for murine leukocyte subsets identification and a 35-antibody panel assessing various cytokines. Established murine leukocyte populations were easily identified and diverse immune signatures indicative of numerous pathogen encounters were classified particularly in pet shop mice and to a lesser extent in quarantine and non-SPF mice as compared to SPF mice. In addition, unsupervised analysis identified distinct clusters that associated strongly with the degree of pathogenic priming, including increased frequencies of activated NK cells and antigen-experienced B- and T-cell subsets. Our study unravels the complexity of immune signatures altered under physiological pathogen challenges and highlights the importance of carefully adapting laboratory settings for immunological studies in mice, including drug and therapy testing. © 2016 International Society

Nested element method in multidimensional neutron diffusion calculations

International Nuclear Information System (INIS)

Altiparmakov, D.V.

1983-01-01

A new numerical method is developed that is particularly efficient in solving the multidimensional neutron diffusion equation in geometrically complex systems. The needs for a generally applicable and fast running computer code have stimulated the inroad of a nonclassical (R-function) numerical method into the nuclear field. By using the R-functions, the geometrical components of the diffusion problem are a priori analytically implemented into the approximate solution. The class of functions, to which the approximate solution belongs, is chosen as close to the exact solution class as practically acceptable from the time consumption point of view. That implies a drastic reduction of the number of degrees of freedom, compared to the other methods. Furthermore, the reduced number of degrees of freedom enables calculation of large multidimensional problems on small computers

Optimal multi-dimensional poverty lines: The state of poverty in Iraq

Science.gov (United States)

Ameen, Jamal R. M.

2017-09-01

Poverty estimation based on calories intake is unrealistic. The established concept of multidimensional poverty has methodological weaknesses in the treatment of different dimensions and there is disagreement in methods of combining them into a single poverty line. This paper introduces a methodology to estimate optimal multidimensional poverty lines and uses the Iraqi household socio-economic survey data of 2012 to demonstrate the idea. The optimal poverty line for Iraq is found to be 170.5 Thousand Iraqi Dinars (TID).

Multidimensional Screening as a Pharmacology Laboratory Experience.

Science.gov (United States)

Malone, Marvin H.; And Others

1979-01-01

A multidimensional pharmacodynamic screening experiment that addresses drug interaction is included in the pharmacology-toxicology laboratory experience of pharmacy students at the University of the Pacific. The student handout with directions for the procedure is reproduced, drug compounds tested are listed, and laboratory evaluation results are…

SIDIS transverse spin azimuthal asymmetries at COMPASS: Multidimensional analysis

CERN Document Server

Parsamyan, Bakur

2015-01-01

Exploration of transverse spin structure of the nucleon via study of the spin (in)dependent azimuthal asymmetries in semi-inclusive deep inelastic scattering (SIDIS) and Drell-Yan (DY) reactions is one of the main aspects of the broad physics program of the COMPASS experiment (CERN, Switzerland). In past decade COMPASS has collected a considerable amount of polarized deuteron and proton SIDIS data while 2014 and 2015 runs were dedicated to the Drell-Yan measurements. Results on SIDIS azimuthal effects provided so far by COMPASS play an important role in general understanding of the three-dimensional nature of the nucleon. Giving access to the entire "twist-2" set of transverse momentum dependent (TMD) parton distribution functions (PDFs) and fragmentation functions (FFs) COMPASS data are being widely used in phenomenological analyses and experimental data fits. Recent unique and first ever x-$Q^{2}$-z-pT multidimensional results for transverse spin asymmetries obtained by COMPASS serve as a direct and unprece...

Multidimensional Learner Model In Intelligent Learning System

Science.gov (United States)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

Multidimensionality of thinking in the context of creativity studies.

Directory of Open Access Journals (Sweden)

Belolutskaya A.K.

2015-03-01

Full Text Available This article describes the theoretical difference between the flexibility and the multidimensionality of thinking. Multidimensionality is discussed as a characteristic of thinking that is necessary for exploration of the variability of structural transformations of problematic situations. The objective of the study was to examine a number of theories concerning the correlative connection between the multidimensionality of thinking and other characteristics of creative, productive thinking: the flexibility of thinking; the formation of an operation of dialectical thinking such as “mediation”; the ability of a person to use a scheme as an abstraction for analysis of various specific content. A total of 85 people participated in the study: they were 15 to 17 years old, students at a senior school in Kaliningradskaya oblast, winners of different stages of the all-Russian academic competition in physics, chemistry, and mathematics. All respondents had a high level of academic success and of general intelligence. The following techniques were used in this study: (1 my technique for diagnostics of the multidimensionality of thinking; (2 my technique of “schemes and paintings,” designed for diagnostics of the ability to relate abstract schemes and various specific content; (3 the Torrance Tests of Creative Thinking (verbal battery; (4 a diagnostic technique for dialectical thinking: “What can be simultaneous?” All the hypotheses were confirmed. Confirmation was received of the existence of a correlation connection; this finding counts in favor of the assumption that the parameters of thinking my colleagues and I were working with can in aggregate be considered an integral characteristic of human thinking. It allows us to distinguish significant features of a situation from secondary ones—that is, to see a substantial contradiction and to propose several options for its transformation.

Cuba: Multidimensional numerical integration library

Science.gov (United States)

Hahn, Thomas

2016-08-01

The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.

[Multidimensional family therapy: which influences, which specificities?].

Science.gov (United States)

Bonnaire, C; Bastard, N; Couteron, J-P; Har, A; Phan, O

2014-10-01

Among illegal psycho-active drugs, cannabis is the most consumed by French adolescents. Multidimensional family therapy (MDFT) is a family-based outpatient therapy which has been developed for adolescents with drug and behavioral problems. MDFT has shown its effectiveness in adolescents with substance abuse disorders (notably cannabis abuse) not only in the United States but also in Europe (International Cannabis Need of Treatment project). MDFT is a multidisciplinary approach and an evidence-based treatment, at the crossroads of developmental psychology, ecological theories and family therapy. Its psychotherapeutic techniques find its roots in a variety of approaches which include systemic family therapy and cognitive therapy. The aims of this paper are: to describe all the backgrounds of MDFT by highlighting its characteristics; to explain how structural and strategy therapies have influenced this approach; to explore the links between MDFT, brief strategic family therapy and multi systemic family therapy; and to underline the specificities of this family therapy method. The multidimensional family therapy was created on the bases of 1) the integration of multiple therapeutic techniques stemming from various family therapy theories; and 2) studies which have shown family therapy efficiency. Several trials have shown a better efficiency of MDFT compared to group treatment, cognitive-behavioral therapy and home-based treatment. Studies have also highlighted that MDFT led to superior treatment outcomes, especially among young people with severe drug use and psychiatric co-morbidities. In the field of systemic family therapies, MDFT was influenced by: 1) the structural family therapy (S. Minuchin), 2) the strategic family theory (J. Haley), and 3) the intergenerational family therapy (Bowen and Boszormenyi-Nagy). MDFT has specific aspects: MDFT therapists think in a multidimensional perspective (because an adolescent's drug abuse is a multidimensional disorder), they

Multidimensional improvements induced by an intensive obesity inpatients rehabilitation programme.

Science.gov (United States)

Giordano, Francesca; Berteotti, Michela; Budui, Simona; Calgaro, Nicole; Franceschini, Laura; Gilli, Federica; Masiero, Marina; Raschellà, Guido; Salvetti, Sabrina; Taddei, Micol; Schena, Federico; Busetto, Luca

2017-06-01

To analyse the short-term effectiveness of an intensive multidimensional inpatient programme specifically developed for patients with severe obesity. A multidisciplinary team managed a 3-week residential programme characterised by the integration of nutritional and physical rehabilitation with psychological and educational intervention. All patients consecutively admitted in 10 months were analysed at admission and discharge for changes in the following domains: anthropometry (weight, body mass index (BMI), waist and neck circumferences), cardiovascular risk factors (glycaemia, HbA1c, lipid profile, blood pressure), quality of life, eating behaviour, and physical performance (VO 2peak by incremental cycle ergometer test, 6-min walking test (6MWT), chair stands test). 136 subjects (61% females, median age 52.7 years) with obesity (mean BMI 43.2 kg/m 2 ) and multiple comorbidities were analysed. A 3.9% BMI reduction and a reduction in waist (-3.8%) and neck (-3.3%) circumferences were observed. Glycaemic control was achieved in 68% of patients with uncontrolled diabetes at admission. Blood pressure control was achieved in all patients with uncontrolled hypertension at admission. Total cholesterol (-16%), LDL-cholesterol (-19%) and triglycerides (-9%) were significantly reduced. Psychometric assessment showed improvements in quality of life perception and binge eating disorder. Finally, a significant improvement in physical performance (+4.7% improvement in VO 2peak , with longer distances in 6MWT and a higher number of standings) was observed. Our preliminary data prove that a 3-week programme determined a clinically significant multi-dimensional improvement in patients with severe obesity. Long-term follow-up data are needed to confirm the efficacy of our rehabilitation setting.

On the use of multi-dimensional scaling and electromagnetic tracking in high dose rate brachytherapy

Science.gov (United States)

Götz, Th I.; Ermer, M.; Salas-González, D.; Kellermeier, M.; Strnad, V.; Bert, Ch; Hensel, B.; Tomé, A. M.; Lang, E. W.

2017-10-01

High dose rate brachytherapy affords a frequent reassurance of the precise dwell positions of the radiation source. The current investigation proposes a multi-dimensional scaling transformation of both data sets to estimate dwell positions without any external reference. Furthermore, the related distributions of dwell positions are characterized by uni—or bi—modal heavy—tailed distributions. The latter are well represented by α—stable distributions. The newly proposed data analysis provides dwell position deviations with high accuracy, and, furthermore, offers a convenient visualization of the actual shapes of the catheters which guide the radiation source during the treatment.

Continued validation of the Multidimensional Perfectionism Scale.

Science.gov (United States)

Clavin, S L; Clavin, R H; Gayton, W F; Broida, J

1996-06-01

Scores on the Multidimensional Perfectionism Scale have been correlated with measures of obsessive-compulsive tendencies for women, so the validity of scores on this scale for 41 men was examined. Scores on the Perfectionism Scale were significantly correlated (.47-.03) with scores on the Maudsley Obsessive-Compulsive Inventory.

Multidimensional stochastic approximation using locally contractive functions

Science.gov (United States)

Lawton, W. M.

1975-01-01

A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.

Identification of the Core Set of Carbon-Associated Genes in a Bioenergy Grassland Soil.

Directory of Open Access Journals (Sweden)

Adina Howe

Full Text Available Despite the central role of soil microbial communities in global carbon (C cycling, little is known about soil microbial community structure and even less about their metabolic pathways. Efforts to characterize soil communities often focus on identifying differences in gene content across environmental gradients, but an alternative question is what genes are similar in soils. These genes may indicate critical species or potential functions that are required in all soils. Here we identified the "core" set of C cycling sequences widely present in multiple soil metagenomes from a fertilized prairie (FP. Of 226,887 sequences associated with known enzymes involved in the synthesis, metabolism, and transport of carbohydrates, 843 were identified to be consistently prevalent across four replicate soil metagenomes. This core metagenome was functionally and taxonomically diverse, representing five enzyme classes and 99 enzyme families within the CAZy database. Though it only comprised 0.4% of all CAZy-associated genes identified in FP metagenomes, the core was found to be comprised of functions similar to those within cumulative soils. The FP CAZy-associated core sequences were present in multiple publicly available soil metagenomes and most similar to soils sharing geographic proximity. In soil ecosystems, where high diversity remains a key challenge for metagenomic investigations, these core genes represent a subset of critical functions necessary for carbohydrate metabolism, which can be targeted to evaluate important C fluxes in these and other similar soils.

WEB LOG EXPLORER – CONTROL OF MULTIDIMENSIONAL DYNAMICS OF WEB PAGES

Directory of Open Access Journals (Sweden)

Mislav Šimunić

2012-07-01

Full Text Available Demand markets dictate and pose increasingly more requirements to the supplymarket that are not easily satisfied. The supply market presenting its web pages to thedemand market should find the best and quickest ways to respond promptly to the changesdictated by the demand market. The question is how to do that in the most efficient andquickest way. The data on the usage of web pages on a specific web site are recorded in alog file. The data in a log file are stochastic and unordered and require systematicmonitoring, categorization, analyses, and weighing. From the data processed in this way, itis necessary to single out and sort the data by their importance that would be a basis for acontinuous generation of dynamics/changes to the web site pages in line with the criterionchosen. To perform those tasks successfully, a new software solution is required. For thatpurpose, the authors have developed the first version of the WLE (WebLogExplorersoftware solution, which is actually realization of web page multidimensionality and theweb site as a whole. The WebLogExplorer enables statistical and semantic analysis of a logfile and on the basis thereof, multidimensional control of the web page dynamics. Theexperimental part of the work was done within the web site of HTZ (Croatian NationalTourist Board being the main portal of the global tourist supply in the Republic of Croatia(on average, daily "log" consists of c. 600,000 sets, average size of log file is 127 Mb, andc. 7000-8000 daily visitors on the web site.

An Improved Multidimensional MPA Procedure for Bidirectional Earthquake Excitations

Directory of Open Access Journals (Sweden)

Feng Wang

2014-01-01

Full Text Available Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two components earthquake excitations, and independent analysis in each direction is not required and the application of simplified superposition formulas is avoided. The strength reduction factor spectra based on superposition of earthquake excitations are discussed and compared with the traditional strength reduction factor spectra. The step-by-step procedure is proposed to estimate seismic demands of structures. Two examples are implemented to verify the accuracy of the method, and the results of the examples show that (1 the IMMPA method can be used to estimate the responses of structure subjected to bidirectional earthquake excitations. (2 Along with increase of peak of earthquake acceleration, structural response deviation estimated with the IMMPA method may also increase. (3 Along with increase of the number of total floors of structures, structural response deviation estimated with the IMMPA method may also increase.

Discrete nodal integral transport-theory method for multidimensional reactor physics and shielding calculations

International Nuclear Information System (INIS)

Lawrence, R.D.; Dorning, J.J.

1980-01-01

A coarse-mesh discrete nodal integral transport theory method has been developed for the efficient numerical solution of multidimensional transport problems of interest in reactor physics and shielding applications. The method, which is the discrete transport theory analogue and logical extension of the nodal Green's function method previously developed for multidimensional neutron diffusion problems, utilizes the same transverse integration procedure to reduce the multidimensional equations to coupled one-dimensional equations. This is followed by the conversion of the differential equations to local, one-dimensional, in-node integral equations by integrating back along neutron flight paths. One-dimensional and two-dimensional transport theory test problems have been systematically studied to verify the superior computational efficiency of the new method

Code Coupling for Multi-Dimensional Core Transient Analysis

International Nuclear Information System (INIS)

Park, Jin-Woo; Park, Guen-Tae; Park, Min-Ho; Ryu, Seok-Hee; Um, Kil-Sup; Lee Jae-Il

2015-01-01

After the CEA ejection, the nuclear power of the reactor dramatically increases in an exponential behavior until the Doppler effect becomes important and turns the reactivity balance and power down to lower levels. Although this happens in a very short period of time, only few seconds, the energy generated can be very significant and cause fuel failures. The current safety analysis methodology which is based on overly conservative assumptions with the point kinetics model results in quite adverse consequences. Thus, KEPCO Nuclear Fuel(KNF) is developing the multi-dimensional safety analysis methodology to mitigate the consequences of the single CEA ejection accident. For this purpose, three-dimensional core neutron kinetics code ASTRA, sub-channel analysis code THALES, and fuel performance analysis code FROST, which have transient calculation performance, were coupled using message passing interface (MPI). This paper presents the methodology used for code coupling and the preliminary simulation results with the coupled code system (CHASER). Multi-dimensional core transient analysis code system, CHASER, has been developed and it was applied to simulate a single CEA ejection accident. CHASER gave a good prediction of multi-dimensional core transient behaviors during transient. In the near future, the multi-dimension CEA ejection analysis methodology using CHASER is planning to be developed. CHASER is expected to be a useful tool to gain safety margin for reactivity initiated accidents (RIAs), such as a single CEA ejection accident

Code Coupling for Multi-Dimensional Core Transient Analysis

Energy Technology Data Exchange (ETDEWEB)

Park, Jin-Woo; Park, Guen-Tae; Park, Min-Ho; Ryu, Seok-Hee; Um, Kil-Sup; Lee Jae-Il [KEPCO NF, Daejeon (Korea, Republic of)

2015-05-15

After the CEA ejection, the nuclear power of the reactor dramatically increases in an exponential behavior until the Doppler effect becomes important and turns the reactivity balance and power down to lower levels. Although this happens in a very short period of time, only few seconds, the energy generated can be very significant and cause fuel failures. The current safety analysis methodology which is based on overly conservative assumptions with the point kinetics model results in quite adverse consequences. Thus, KEPCO Nuclear Fuel(KNF) is developing the multi-dimensional safety analysis methodology to mitigate the consequences of the single CEA ejection accident. For this purpose, three-dimensional core neutron kinetics code ASTRA, sub-channel analysis code THALES, and fuel performance analysis code FROST, which have transient calculation performance, were coupled using message passing interface (MPI). This paper presents the methodology used for code coupling and the preliminary simulation results with the coupled code system (CHASER). Multi-dimensional core transient analysis code system, CHASER, has been developed and it was applied to simulate a single CEA ejection accident. CHASER gave a good prediction of multi-dimensional core transient behaviors during transient. In the near future, the multi-dimension CEA ejection analysis methodology using CHASER is planning to be developed. CHASER is expected to be a useful tool to gain safety margin for reactivity initiated accidents (RIAs), such as a single CEA ejection accident.

Multidimensional Data Modeling For Location-Based Services

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kligys, Augustas; Pedersen, Torben Bach

2004-01-01

and requests of their users in multidimensional databases, i.e., data warehouses, and content delivery may be based on the results of complex queries on these data warehouses. Such queries aggregate detailed data in order to find useful patterns, e.g., in the interaction of a particular user with the services...

Multidimensional Data Modeling For Location-Based Services

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kligys, A.; Pedersen, Torben Bach

2003-01-01

and requests of their users in multidimensional databases, i.e., data warehouses; and content delivery may be based on the results of complex queries on these data warehouses. Such queries aggregate detailed data in order to find useful patterns, e.g., in the interaction of a particular user with the services...

The ACTTION–APS–AAPM Pain Taxonomy (AAAPT) Multidimensional Approach to Classifying Acute Pain Conditions

Science.gov (United States)

Kent, Michael L.; Tighe, Patrick J.; Belfer, Inna; Brennan, Timothy J.; Bruehl, Stephen; Brummett, Chad M.; Buckenmaier, Chester C.; Buvanendran, Asokumar; Cohen, Robert I.; Desjardins, Paul; Edwards, David; Fillingim, Roger; Gewandter, Jennifer; Gordon, Debra B.; Hurley, Robert W.; Kehlet, Henrik; Loeser, John D.; Mackey, Sean; McLean, Samuel A.; Polomano, Rosemary; Rahman, Siamak; Raja, Srinivasa; Rowbotham, Michael; Suresh, Santhanam; Schachtel, Bernard; Schreiber, Kristin; Schumacher, Mark; Stacey, Brett; Stanos, Steven; Todd, Knox; Turk, Dennis C.; Weisman, Steven J.; Wu, Christopher; Carr, Daniel B.; Dworkin, Robert H.; Terman, Gregory

2017-01-01

Objective. With the increasing societal awareness of the prevalence and impact of acute pain, there is a need to develop an acute pain classification system that both reflects contemporary mechanistic insights and helps guide future research and treatment. Existing classifications of acute pain conditions are limiting, with a predominant focus on the sensory experience (e.g., pain intensity) and pharmacologic consumption. Consequently, there is a need to more broadly characterize and classify the multidimensional experience of acute pain. Setting. Consensus report following expert panel involving the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION), American Pain Society (APS), and American Academy of Pain Medicine (AAPM). Methods. As a complement to a taxonomy recently developed for chronic pain, the ACTTION public-private partnership with the US Food and Drug Administration, the APS, and the AAPM convened a consensus meeting of experts to develop an acute pain taxonomy using prevailing evidence. Key issues pertaining to the distinct nature of acute pain are presented followed by the agreed-upon taxonomy. The ACTTION-APS-AAPM Acute Pain Taxonomy will include the following dimensions: 1) core criteria, 2) common features, 3) modulating factors, 4) impact/functional consequences, and 5) putative pathophysiologic pain mechanisms. Future efforts will consist of working groups utilizing this taxonomy to develop diagnostic criteria for a comprehensive set of acute pain conditions. Perspective. The ACTTION-APS-AAPM Acute Pain Taxonomy (AAAPT) is a multidimensional acute pain classification system designed to classify acute pain along the following dimensions: 1) core criteria, 2) common features, 3) modulating factors, 4) impact/functional consequences, and 5) putative pathophysiologic pain mechanisms. Conclusions. Significant numbers of patients still suffer from significant acute pain

Application of neural network to multi-dimensional design window search

International Nuclear Information System (INIS)

Kugo, T.; Nakagawa, M.

1996-01-01

In the reactor core design, many parametric survey calculations should be carried out to decide an optimal set of basic design parameter values. They consume a large amount of computation time and labor in the conventional way. To support directly such a work, we investigate a procedure to search efficiently a design window, which is defined as feasible design parameter ranges satisfying design criteria and requirements, in a multi-dimensional space composed of several basic design parameters. A principle of the present method is to construct the multilayer neural network to simulate quickly a response of an analysis code through a training process, and to reduce computation time using the neural network as a substitute of an analysis code. We apply the present method to a fuel pin design of high conversion light water reactors for the neutronics and thermal hydraulics fields to demonstrate performances of the method. (author)

ComVisMD - compact visualization of multidimensional data: experimenting with cricket players data

Science.gov (United States)

Dandin, Shridhar B.; Ducassé, Mireille

2018-03-01

Database information is multidimensional and often displayed in tabular format (row/column display). Presented in aggregated form, multidimensional data can be used to analyze the records or objects. Online Analytical database Processing (OLAP) proposes mechanisms to display multidimensional data in aggregated forms. A choropleth map is a thematic map in which areas are colored in proportion to the measurement of a statistical variable being displayed, such as population density. They are used mostly for compact graphical representation of geographical information. We propose a system, ComVisMD inspired by choropleth map and the OLAP cube to visualize multidimensional data in a compact way. ComVisMD displays multidimensional data like OLAP Cube, where we are mapping an attribute a (first dimension, e.g. year started playing cricket) in vertical direction, object coloring based on b (second dimension, e.g. batting average), mapping varying-size circles based on attribute c (third dimension, e.g. highest score), mapping numbers based on attribute d (fourth dimension, e.g. matches played). We illustrate our approach on cricket players data, namely on two tables Country and Player. They have a large number of rows and columns: 246 rows and 17 columns for players of one country. ComVisMD’s visualization reduces the size of the tabular display by a factor of about 4, allowing users to grasp more information at a time than the bare table display.

Testing the multidimensionality of the inventory of school motivation in a Dutch student sample.

Science.gov (United States)

Korpershoek, Hanke; Xu, Kun; Mok, Magdalena Mo Ching; McInerney, Dennis M; van der Werf, Greetje

2015-01-01

A factor analytic and a Rasch measurement approach were applied to evaluate the multidimensional nature of the school motivation construct among more than 7,000 Dutch secondary school students. The Inventory of School Motivation (McInerney and Ali, 2006) was used, which intends to measure four motivation dimensions (mastery, performance, social, and extrinsic motivation), each comprising of two first-order factors. One unidimensional model and three multidimensional models (4-factor, 8-factor, higher order) were fit to the data. Results of both approaches showed that the multidimensional models validly represented the school motivation among Dutch secondary school pupils, whereas model fit of the unidimensional model was poor. The differences in model fit between the three multidimensional models were small, although a different model was favoured by the two approaches. The need for improvement of some of the items and the need to increase measurement precision of several first-order factors are discussed.

Theory and application of deterministic multidimensional pointwise energy lattice physics methods

International Nuclear Information System (INIS)

Zerkle, M.L.

1999-01-01

The theory and application of deterministic, multidimensional, pointwise energy lattice physics methods are discussed. These methods may be used to solve the neutron transport equation in multidimensional geometries using near-continuous energy detail to calculate equivalent few-group diffusion theory constants that rigorously account for spatial and spectral self-shielding effects. A dual energy resolution slowing down algorithm is described which reduces the computer memory and disk storage requirements for the slowing down calculation. Results are presented for a 2D BWR pin cell depletion benchmark problem

Psychometric properties of the Multidimensional Students’ Life Satisfaction Scale in a sample of Chilean university students

Directory of Open Access Journals (Sweden)

Berta Schnettler

2017-07-01

Full Text Available The Multidimensional Students’ Life Satisfaction Scale is an instrument to assess life satisfaction in children and adolescents in five life domains. However, research on multidimensional life satisfaction in older students, such as those attending university, is still scarce. This paper undertook to evaluate the psychometric properties of the Multidimensional Students’ Life Satisfaction Scale in a sample of university students from five state universities in Chile. The Multidimensional Students’ Life Satisfaction Scale and Satisfaction with Life Scale were applied to 369 participants. Confirmatory factor analysis was used to evaluate the expected correlated five-factor model of the long version (40 items and the abbreviated version (30 items of the Multidimensional Students’ Life Satisfaction Scale. The goodness-of-fit values obtained from confirmatory factor analysis revealed that the data fit better to the 30-items and five-factor structure than to the 40-item structure. The convergent, concurrent and discriminant validity of the 30-item version was demonstrated. The 30-item version of the Multidimensional Students’ Life Satisfaction Scale may be a promising alternative to measure satisfaction in different life domains in university students, and a valuable tool for differential assessments that guide research and intervention on this population.

DaqProVis, a toolkit for acquisition, interactive analysis, processing and visualization of multidimensional data

Energy Technology Data Exchange (ETDEWEB)

Morhac, M. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)]. E-mail: fyzimiro@savba.sk; Matousek, V. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia); Turzo, I. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia); Kliman, J. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)

2006-04-01

Multidimensional data acquisition, processing and visualization system to analyze experimental data in nuclear physics is described. It includes a large number of sophisticated algorithms of the multidimensional spectra processing, including background elimination, deconvolution, peak searching and fitting.

Multidimensional first-order dominance comparisons of population wellbeing

DEFF Research Database (Denmark)

Arndt, Thomas Channing; Siersbæk, Nikolaj; Østerdal, Lars Peter Raahave

In this paper, we convey the concept of first-order dominance (FOD) with particular focus on applications to multidimensional population welfare comparisons. We give an account of the fundamental equivalent definitions of FOD, illustrated with simple numerical examples. An implementable method...

Using the Andrews Plotss to Visualize Multidimensional Data in Multi-criteria Optimization

OpenAIRE

S. V. Groshev; N. V. Pivovarova

2015-01-01

Currently, issues on processing of large data volumes are of great importance. Initially, the Andrews plots have been proposed to show multidimensional statistics on the plane. But as the Andrews plots retain information on the average values of the represented values, distances, and dispersion, the distances between the plots linearly indicate distances between the data points, and it becomes possible to use the plots under consideration for the graphical representation of multi-dimensional ...

Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor.

Science.gov (United States)

Kristiansen, Wenche; Karlsson, Robert; Rounge, Trine B; Whitington, Thomas; Andreassen, Bettina K; Magnusson, Patrik K; Fosså, Sophie D; Adami, Hans-Olov; Turnbull, Clare; Haugen, Trine B; Grotmol, Tom; Wiklund, Fredrik

2015-07-15

Genome-wide association (GWA) studies have reported 19 distinct susceptibility loci for testicular germ cell tumor (TGCT). A GWA study for TGCT was performed by genotyping 610 240 single-nucleotide polymorphisms (SNPs) in 1326 cases and 6687 controls from Sweden and Norway. No novel genome-wide significant associations were observed in this discovery stage. We put forward 27 SNPs from 15 novel regions and 12 SNPs previously reported, for replication in 710 case-parent triads and 289 cases and 290 controls. Predefined biological pathways and processes, in addition to a custom-built sex-determination gene set, were subject to enrichment analyses using Meta-Analysis Gene Set Enrichment of Variant Associations (M) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (I). In the combined meta-analysis, we observed genome-wide significant association for rs7501939 on chromosome 17q12 (OR = 0.78, 95% CI = 0.72-0.84, P = 1.1 × 10(-9)) and rs2195987 on chromosome 19p12 (OR = 0.76, 95% CI: 0.69-0.84, P = 3.2 × 10(-8)). The marker rs7501939 on chromosome 17q12 is located in an intron of the HNF1B gene, encoding a member of the homeodomain-containing superfamily of transcription factors. The sex-determination gene set (false discovery rate, FDRM cancer and apoptosis, was associated with TGCT (FDR utero are implicated in the development of TGCT. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models

Directory of Open Access Journals (Sweden)

Marius Pesavento

2004-08-01

Full Text Available A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.

Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data.

Science.gov (United States)

Kehl, Catherine; Simms, Andrew M; Toofanny, Rudesh D; Daggett, Valerie

2008-06-01

The Dynameomics project is our effort to characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations, as described by Beck et al. (in Protein Eng. Des. Select., the first paper in this series). The data produced by these simulations are highly multidimensional in structure and multi-terabytes in size. Both of these features present significant challenges for storage, retrieval and analysis. For optimal data modeling and flexibility, we needed a platform that supported both multidimensional indices and hierarchical relationships between related types of data and that could be integrated within our data warehouse, as described in the accompanying paper directly preceding this one. For these reasons, we have chosen On-line Analytical Processing (OLAP), a multi-dimensional analysis optimized database, as an analytical platform for these data. OLAP is a mature technology in the financial sector, but it has not been used extensively for scientific analysis. Our project is further more unusual for its focus on the multidimensional and analytical capabilities of OLAP rather than its aggregation capacities. The dimensional data model and hierarchies are very flexible. The query language is concise for complex analysis and rapid data retrieval. OLAP shows great promise for the dynamic protein analysis for bioengineering and biomedical applications. In addition, OLAP may have similar potential for other scientific and engineering applications involving large and complex datasets.

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

Science.gov (United States)

Navarro-Reig, Meritxell; Bedia, Carmen; Tauler, Romà; Jaumot, Joaquim

2018-04-03

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Microarray analysis identifies a common set of cellular genes modulated by different HCV replicon clones

Directory of Open Access Journals (Sweden)

Gerosolimo Germano

2008-06-01

Full Text Available Abstract Background Hepatitis C virus (HCV RNA synthesis and protein expression affect cell homeostasis by modulation of gene expression. The impact of HCV replication on global cell transcription has not been fully evaluated. Thus, we analysed the expression profiles of different clones of human hepatoma-derived Huh-7 cells carrying a self-replicating HCV RNA which express all viral proteins (HCV replicon system. Results First, we compared the expression profile of HCV replicon clone 21-5 with both the Huh-7 parental cells and the 21-5 cured (21-5c cells. In these latter, the HCV RNA has been eliminated by IFN-α treatment. To confirm data, we also analyzed microarray results from both the 21-5 and two other HCV replicon clones, 22-6 and 21-7, compared to the Huh-7 cells. The study was carried out by using the Applied Biosystems (AB Human Genome Survey Microarray v1.0 which provides 31,700 probes that correspond to 27,868 human genes. Microarray analysis revealed a specific transcriptional program induced by HCV in replicon cells respect to both IFN-α-cured and Huh-7 cells. From the original datasets of differentially expressed genes, we selected by Venn diagrams a final list of 38 genes modulated by HCV in all clones. Most of the 38 genes have never been described before and showed high fold-change associated with significant p-value, strongly supporting data reliability. Classification of the 38 genes by Panther System identified functional categories that were significantly enriched in this gene set, such as histones and ribosomal proteins as well as extracellular matrix and intracellular protein traffic. The dataset also included new genes involved in lipid metabolism, extracellular matrix and cytoskeletal network, which may be critical for HCV replication and pathogenesis. Conclusion Our data provide a comprehensive analysis of alterations in gene expression induced by HCV replication and reveal modulation of new genes potentially useful

Work disabilities and unmet needs for health care and rehabilitation among jobseekers: a community-level investigation using multidimensional work ability assessments

OpenAIRE

Ker?t?r, Raija; Taanila, Anja; Jokelainen, Jari; Soukainen, Jouko; Ala-Mursula, Leena

2016-01-01

Objective Comprehensive understanding of the prevalence and quality of work disabilities and unmet needs for health care and rehabilitation to support return to work (RTW) among jobseekers. Design Community-level, cross-sectional analysis with multidimensional clinical work ability assessments. Setting Paltamo, Finland. Participants Unemployed citizens either participating in the Full-Employment Project or long-term unemployed (n?=?230, 81%). Main outcome measures Based on data from theme int...

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting.

Science.gov (United States)

Zhao, Wei; Ware, Erin B; He, Zihuai; Kardia, Sharon L R; Faul, Jessica D; Smith, Jennifer A

2017-09-29

Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) ( p = 0.07).

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting

Directory of Open Access Journals (Sweden)

Wei Zhao

2017-09-01

Full Text Available Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index-associated genetic loci identified through large-scale genome-wide association studies (GWAS only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS. In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS. Childhood socioeconomic status (parental education was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488 by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA (p = 0.07.

Ordinal Comparison of Multidimensional Deprivation

DEFF Research Database (Denmark)

Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter

This paper develops an ordinal method of comparison of multidimensional inequality. In our model, population distribution g is more unequal than f when the distributions have common median and can be obtained from f  by one or more shifts in population density that increase inequality. For our be...... benchmark 2x2 case (i.e. the case of two binary outcome variables), we derive an empirical method for making inequality comparisons. As an illustration, we apply the model to childhood poverty in Mozambique....

Multidimensional Risk Management for Underground Electricity Networks

Directory of Open Access Journals (Sweden)

Garcez Thalles V.

2014-08-01

Full Text Available In the paper we consider an electricity provider company that makes decision on allocating resources on electric network maintenance. The investments decrease malfunction rate of network nodes. An accidental event (explosion, fire, etc. or a malfunctioning on underground system can have various consequences and in different perspectives, such as deaths and injuries of pedestrians, fires in nearby locations, disturbances in the flow of vehicular traffic, loss to the company image, operating and financial losses, etc. For this reason it is necessary to apply an approach of the risk management that considers the multidimensional view of the consequences. Furthermore an analysis of decision making should consider network dependencies between the nodes of the electricity distribution system. In the paper we propose the use of the simulation to assess the network effects (such as the increase of the probability of other accidental event and the occurrence of blackouts of the dependent nodes in the multidimensional risk assessment in electricity grid. The analyzed effects include node overloading due to malfunction of adjacent nodes and blackouts that take place where there is temporarily no path in the grid between the power plant and a node. The simulation results show that network effects have crucial role for decisions in the network maintenance – outcomes of decisions to repair a particular node in the network can have significant influence on performance of other nodes. However, those dependencies are non-linear. The effects of network connectivity (number of connections between nodes on its multidimensional performance assessment depend heavily on the overloading effect level. The simulation results do not depend on network type structure (random or small world – however simulation outcomes for random networks have shown higher variance compared to small-world networks.

Psychometric properties of the Multidimensional Anxiety Scale for ...

African Journals Online (AJOL)

Aim: To determine the psychometric properties of the Multidimensional Anxiety Scale for Children (MASC) in Nairobi public secondary school children, Kenya. Method: Concurrent self-administration of the MASC and Children's Depression Inventory (CDI) to students in Nairobi public secondary schools. Results: The MASC ...

Expanding the net: The re-evaluation of the multidimensional nomogram calculating the upper limit of normal PTH (maxPTH) in the setting of secondary hyperparathyroidism and the development of the MultIdimensional Predictive hyperparaTHyroid model (Mi-PTH).

Science.gov (United States)

Rajhbeharrysingh, Uma; El Youssef, Joseph; Leon, Enrique; Lasarev, Michael R; Klein, Robert; Vanek, Chaim; Mattar, Samer; Berber, Eren; Siperstein, Allan; Shindo, Maisie; Milas, Mira

2016-01-01

The multidimensional nomogram calculating the upper limit of normal PTH (maxPTH) model identifies a personalized upper limit of normal parathyroid hormone (PTH) and successfully predicts classical primary hyperparathyroidism (PHP). We aimed to assess whether maxPTH can distinguish normocalcemic PHP (NCPHP) from secondary hyperparathyroidism (SHP), including subjects who underwent bariatric surgery (BrS). A total of 172 subjects with 359 complete datasets of serum calcium (Ca), 25-OH vitamin D, and intact PTH from Oregon were analyzed: 123 subjects (212 datasets) with PHP and 47 (143) with SHP, including 28 (100) with previous BrS. An improved prediction model, MultIdimensional evaluation for Primary hyperparaTHyroidism (Mi-PTH), was created with the same variables as maxPTH by the use of a combined cohort (995 subjects) including participants from previous studies. In the Oregon cohort, maxPTH's sensitivity was 100% for classical PHP and 89% for NCPHP, but only 50% for normohormonal PHP (NHPHP) and 40% specific for SHP. In comparison, although sensitivity for NCPHP was similar (89%), Mi-PTH vastly improved SHP specificity (85%). In the combined cohort, Mi-PTH had better sensitivity of 98.5% (vs 95%) and specificity 97% (vs 85%). MaxPTH was sensitive in detecting PHP; however, there was low specificity for SHP, especially in patients who underwent BrS. The creation of Mi-PTH provided improved performance measures but requires further prospective evaluation. Copyright © 2016 Elsevier Inc. All rights reserved.

A multidimensional analysis and modelling of flotation process for selected Polish lithological copper ore types

Directory of Open Access Journals (Sweden)

Niedoba Tomasz

2017-01-01

Full Text Available The flotation of copper ore is a complex technological process that depends on many parameters. Therefore, it is necessary to take into account the complexity of this phenomenon by choosing a multidimensional data analysis. The paper presents the results of modelling and analysis of beneficiation process of sandstone copper ore. Considering the implementation of multidimensional statistical methods it was necessary to carry out a multi-level experiment, which included 4 parameters (size fraction, collector type and dosage, flotation time. The main aim of the paper was the preparation of flotation process models for the recovery and the content of the metal in products. A MANOVA was implemented to explore the relationship between dependent (β, ϑ, ε, η and independent (d, t, cd, ct variables. The design of models was based on linear and nonlinear regression. The results of the variation analysis indicated the high significance of all parameters for the process. The average degree of matching of linear models to experimental data was set at 49% and 33% for copper content in the concentrate and tailings and 47% for the recovery of copper minerals in the both. The results confirms the complexity and stochasticity of the Polish copper ore flotation.

Multidimensional and Multimodal Separations by HPTLC in Phytochemistry

Science.gov (United States)

Ciesla, Lukasz; Waksmundzka-Hajnos, Monika

HPTLC is one of the most widely applied methods in phytochemical analysis. It is due to its numerous advantages, e.g., it is the only chromatographic method offering the option of presenting the results as an image. Other advantages include simplicity, low costs, parallel analysis of samples, high sample capacity, rapidly obtained results, and possibility of multiple detection. HPTLC provides identification as well as quantitative results. It also enables the identification of adulterants. In case of complex samples, the resolving power of traditional one-dimensional chromatography is usually inadequate, hence special modes of development are required. Multidimensional and multimodal HPTLC techniques include those realized in one direction (UMD, IMD, GMD, BMD, AMD) as well as typical two-dimensional methods realized on mono- or bi-layers. In this manuscript, an overview on variable multidimensional and multimodal methods, applied in the analysis of phytochemical samples, is presented.

A Multidimensional Data Warehouse for Community Health Centers.

Science.gov (United States)

Kunjan, Kislaya; Toscos, Tammy; Turkcan, Ayten; Doebbeling, Brad N

2015-01-01

Community health centers (CHCs) play a pivotal role in healthcare delivery to vulnerable populations, but have not yet benefited from a data warehouse that can support improvements in clinical and financial outcomes across the practice. We have developed a multidimensional clinic data warehouse (CDW) by working with 7 CHCs across the state of Indiana and integrating their operational, financial and electronic patient records to support ongoing delivery of care. We describe in detail the rationale for the project, the data architecture employed, the content of the data warehouse, along with a description of the challenges experienced and strategies used in the development of this repository that may help other researchers, managers and leaders in health informatics. The resulting multidimensional data warehouse is highly practical and is designed to provide a foundation for wide-ranging healthcare data analytics over time and across the community health research enterprise.

Multidimensional (OLAP) Analysis for Designing Dynamic Learning Strategy

Science.gov (United States)

Rozeva, A.; Deliyska, B.

2010-10-01

Learning strategy in an intelligent learning system is generally elaborated on the basis of assessment of the following factors: learner's time for reaction, content of the learning object, amount of learning material in a learning object, learning object specification, e-learning medium and performance control. Current work proposes architecture for dynamic learning strategy design by implementing multidimensional analysis model of learning factors. The analysis model concerns on-line analytical processing (OLAP) of learner's data structured as multidimensional cube. Main components of the architecture are analysis agent for performing the OLAP operations on learner data cube, adaptation generator and knowledge selection agent for performing adaptive navigation in the learning object repository. The output of the analysis agent is involved in dynamic elaboration of learning strategy that fits best to learners profile and behavior. As a result an adaptive learning path for individual learner and for learner groups is generated.

Multidimensional generalized-ensemble algorithms for complex systems.

Science.gov (United States)

Mitsutake, Ayori; Okamoto, Yuko

2009-06-07

We give general formulations of the multidimensional multicanonical algorithm, simulated tempering, and replica-exchange method. We generalize the original potential energy function E(0) by adding any physical quantity V of interest as a new energy term. These multidimensional generalized-ensemble algorithms then perform a random walk not only in E(0) space but also in V space. Among the three algorithms, the replica-exchange method is the easiest to perform because the weight factor is just a product of regular Boltzmann-like factors, while the weight factors for the multicanonical algorithm and simulated tempering are not a priori known. We give a simple procedure for obtaining the weight factors for these two latter algorithms, which uses a short replica-exchange simulation and the multiple-histogram reweighting techniques. As an example of applications of these algorithms, we have performed a two-dimensional replica-exchange simulation and a two-dimensional simulated-tempering simulation using an alpha-helical peptide system. From these simulations, we study the helix-coil transitions of the peptide in gas phase and in aqueous solution.

Multidimensional biochemical information processing of dynamical patterns.

Science.gov (United States)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Multi-dimensional discovery of biomarker and phenotype complexes

Directory of Open Access Journals (Sweden)

Huang Kun

2010-10-01

Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

Research on Geometric Positioning Algorithm of License Plate in Multidimensional Parameter Space

Directory of Open Access Journals (Sweden)

Yinhua Huan

2014-05-01

Full Text Available Considering features of vehicle license plate location method which commonly used, in order to search a consistent location for reference images with license plates feature in multidimensional parameter space, a new algorithm of geometric location is proposed. Geometric location algorithm main include model training and real time search. Which not only adapt the gray-scale linearity and the gray non-linear changes, but also support changes of scale and angle. Compared with the mainstream locating software, numerical results shows under the same test conditions that the position deviation of geometric positioning algorithm is less than 0.5 pixel. Without taking into account the multidimensional parameter space, Geometric positioning algorithm position deviation is less than 1.0 pixel and angle deviation is less than 1.0 degree taking into account the multidimensional parameter space. This algorithm is robust, simple, practical and is better than the traditional method.

The reality of disability: Multidimensional poverty of people with disability and their families in Latin America.

Science.gov (United States)

Pinilla-Roncancio, Mónica

2017-12-30

Disability and poverty are interconnected and although this relationship has been recognised, there is a lack of empirical evidence to support any possible causal relationship in this topic, particularly in the context of Latin America (LA). This study tests the hypothesis "Disability increases the risk of multidimensional poverty of people living with disabilities and their families". Using national census data from Brazil, Chile, Colombia, Costa Rica and Mexico, the Global Multidimensional Poverty Index (Global MPI) was calculated with the aim of measuring and comparing the levels of multidimensional poverty of people living in households with and without disabled members in the five countries. We found that in the five countries people with disabilities and their families had higher incidence, intensity and levels of multidimensional poverty compared with people living in other households. Their levels of deprivation were also higher for all the indicators included in the Global MPI and the contribution of this group to the national MPI was higher than their share of the population, thus people with disabilities and their families are overrepresented in those living in multidimensional poverty. People with disabilities and their families are in worse conditions than poor households without disabled members and social policies should aim to reduce their high levels of multidimensional poverty and deprivation. Copyright © 2017 Elsevier Inc. All rights reserved.

An Overview of Multi-Dimensional Models of the Sacramento–San Joaquin Delta

Directory of Open Access Journals (Sweden)

Michael L. MacWilliams

2016-12-01

Full Text Available doi: https://doi.org/10.15447/sfews.2016v14iss4art2Over the past 15 years, the development and application of multi-dimensional hydrodynamic models in San Francisco Bay and the Sacramento–San Joaquin Delta has transformed our ability to analyze and understand the underlying physics of the system. Initial applications of three-dimensional models focused primarily on salt intrusion, and provided a valuable resource for investigating how sea level rise and levee failures in the Delta could influence water quality in the Delta under future conditions. However, multi-dimensional models have also provided significant insights into some of the fundamental biological relationships that have shaped our thinking about the system by exploring the relationship among X2, flow, fish abundance, and the low salinity zone. Through the coupling of multi-dimensional models with wind wave and sediment transport models, it has been possible to move beyond salinity to understand how large-scale changes to the system are likely to affect sediment dynamics, and to assess the potential effects on species that rely on turbidity for habitat. Lastly, the coupling of multi-dimensional hydrodynamic models with particle tracking models has led to advances in our thinking about residence time, the retention of food organisms in the estuary, the effect of south Delta exports on larval entrainment, and the pathways and behaviors of salmonids that travel through the Delta. This paper provides an overview of these recent advances and how they have increased our understanding of the distribution and movement of fish and food organisms. The applications presented serve as a guide to the current state of the science of Delta modeling and provide examples of how we can use multi-dimensional models to predict how future Delta conditions will affect both fish and water supply.

Development of realistic thermal-hydraulic system analysis codes ; development of thermal hydraulic test requirements for multidimensional flow modeling

Energy Technology Data Exchange (ETDEWEB)

Suh, Kune Yull; Yoon, Sang Hyuk; Noh, Sang Woo; Lee, Il Suk [Seoul National University, Seoul (Korea)

2002-03-01

This study is concerned with developing a multidimensional flow model required for the system analysis code MARS to more mechanistically simulate a variety of thermal hydraulic phenomena in the nuclear stem supply system. The capability of the MARS code as a thermal hydraulic analysis tool for optimized system design can be expanded by improving the current calculational methods and adding new models. In this study the relevant literature was surveyed on the multidimensional flow models that may potentially be applied to the multidimensional analysis code. Research items were critically reviewed and suggested to better predict the multidimensional thermal hydraulic behavior and to identify test requirements. A small-scale preliminary test was performed in the downcomer formed by two vertical plates to analyze multidimensional flow pattern in a simple geometry. The experimental result may be applied to the code for analysis of the fluid impingement to the reactor downcomer wall. Also, data were collected to find out the controlling parameters for the one-dimensional and multidimensional flow behavior. 22 refs., 40 figs., 7 tabs. (Author)

Transforming community services through the use of a multidimensional model of clinical leadership.

Science.gov (United States)

Leigh, Jacqueline Anne; Wild, Jill; Hynes, Celia; Wells, Stuart; Kurien, Anish; Rutherford, June; Rosen, Lyn; Ashcroft, Tim; Hartley, Victoria

2015-03-01

To evaluate the application of a Multidimensional Model of Clinical Leadership on the community healthcare leader and on transforming community services. Healthcare policy advocates clinical leadership as the vehicle to transform community and healthcare services. Few studies have identified the key components of an effective clinical leadership development model. The first two stages of Kirkpatrick's (Personnel Administrator 28, 1983, 62) Four/Five Levels of Evaluation were used to evaluate the application of the multidimensional model of clinical leadership. Eighty community healthcare leaders were exposed to this multidimensional clinical leadership development model through attendance of a community clinical leadership development programme. Twenty five leaders participated in focus group interviews. Data from the interviews were analysed utilising thematic content analysis. Three key themes emerged that influenced the development of best practice principles for clinical leadership development: 1. Personal leadership development 2. Organisational leadership 3. The importance of multiprofessional action learning/reflective groups Emergent best practice principles for clinical leadership development include adopting a multidimensional development approach. This approach encompasses: preparing the individual leader in the role and seeking organisational leadership development that promotes the vision and corporate values of the organisation and delivers on service improvement and innovation. Moreover, application of the Multidimensional Model of Clinical Leadership could offer the best platform for embedding the Six C's of Nursing (Compassion in Practice - Our Culture of Compassionate Care, Department of Health, Crown Copyright, 2012) within the culture of the healthcare organisation: care, compassion, courage, commitment, communication, and competency. This is achieved in part through the application of emotional intelligence to understand self and to develop the

Numerical simulation of multi-dimensional two-phase flow based on flux vector splitting

Energy Technology Data Exchange (ETDEWEB)

Staedtke, H.; Franchello, G.; Worth, B. [Joint Research Centre - Ispra Establishment (Italy)

1995-09-01

This paper describes a new approach to the numerical simulation of transient, multidimensional two-phase flow. The development is based on a fully hyperbolic two-fluid model of two-phase flow using separated conservation equations for the two phases. Features of the new model include the existence of real eigenvalues, and a complete set of independent eigenvectors which can be expressed algebraically in terms of the major dependent flow parameters. This facilitates the application of numerical techniques specifically developed for high speed single-phase gas flows which combine signal propagation along characteristic lines with the conservation property with respect to mass, momentum and energy. Advantages of the new model for the numerical simulation of one- and two- dimensional two-phase flow are discussed.

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

Science.gov (United States)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Assessment of wall friction model in multi-dimensional component of MARS with air–water cross flow experiment

Energy Technology Data Exchange (ETDEWEB)

Yang, Jin-Hwa [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Korea Atomic Energy Research Institute, 989-111, Daedeok-daero, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Choi, Chi-Jin [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Cho, Hyoung-Kyu, E-mail: chohk@snu.ac.kr [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Euh, Dong-Jin [Korea Atomic Energy Research Institute, 989-111, Daedeok-daero, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Park, Goon-Cherl [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of)

2017-02-15

Recently, high precision and high accuracy analysis on multi-dimensional thermal hydraulic phenomena in a nuclear power plant has been considered as state-of-the-art issues. System analysis code, MARS, also adopted a multi-dimensional module to simulate them more accurately. Even though it was applied to represent the multi-dimensional phenomena, but implemented models and correlations in that are one-dimensional empirical ones based on one-dimensional pipe experimental results. Prior to the application of the multi-dimensional simulation tools, however, the constitutive models for a two-phase flow need to be carefully validated, such as the wall friction model. Especially, in a Direct Vessel Injection (DVI) system, the injected emergency core coolant (ECC) on the upper part of the downcomer interacts with the lateral steam flow during the reflood phase in the Large-Break Loss-Of-Coolant-Accident (LBLOCA). The interaction between the falling film and lateral steam flow induces a multi-dimensional two-phase flow. The prediction of ECC flow behavior plays a key role in determining the amount of coolant that can be used as core cooling. Therefore, the wall friction model which is implemented to simulate the multi-dimensional phenomena should be assessed by multidimensional experimental results. In this paper, the air–water cross film flow experiments simulating the multi-dimensional phenomenon in upper part of downcomer as a conceptual problem will be introduced. The two-dimensional local liquid film velocity and thickness data were used as benchmark data for code assessment. And then the previous wall friction model of the MARS-MultiD in the annular flow regime was modified. As a result, the modified MARS-MultiD produced improved calculation result than previous one.

Multidimensional Gravitational Models: Fluxbrane and S-Brane Solutions with Polynomials

International Nuclear Information System (INIS)

Ivashchuk, V. D.; Melnikov, V. N.

2007-01-01

Main results in obtaining exact solutions for multidimensional models and their application to solving main problems of modern cosmology and black hole physics are described. Some new results on composite fluxbrane and S-brane solutions for a wide class of intersection rules are presented. These solutions are defined on a product manifold R* x M1 x ... x Mn which contains n Ricci-flat spaces M1,...,Mn with 1-dimensional R* and M1. They are defined up to a set of functions obeying non-linear differential equations equivalent to Toda-type equations with certain boundary conditions imposed. Exact solutions corresponding to configurations with two branes and intersections related to simple Lie algebras C2 and G2 are obtained. In these cases the functions Hs(z), s = 1, 2, are polynomials of degrees: (3, 4) and (6, 10), respectively, in agreement with a conjecture suggested earlier. Examples of simple S-brane solutions describing an accelerated expansion of a certain factor-space are given explicitely

Multi-dimensional Code Development for Safety Analysis of LMR

International Nuclear Information System (INIS)

Ha, K. S.; Jeong, H. Y.; Kwon, Y. M.; Lee, Y. B.

2006-08-01

A liquid metal reactor loaded a metallic fuel has the inherent safety mechanism due to the several negative reactivity feedback. Although this feature demonstrated through experiments in the EBR-II, any of the computer programs until now did not exactly analyze it because of the complexity of the reactivity feedback mechanism. A multi-dimensional detail program was developed through the International Nuclear Energy Research Initiative(INERI) from 2003 to 2005. This report includes the numerical coupling the multi-dimensional program and SSC-K code which is used to the safety analysis of liquid metal reactors in KAERI. The coupled code has been proved by comparing the analysis results using the code with the results using SAS-SASSYS code of ANL for the UTOP, ULOF, and ULOHS applied to the safety analysis for KALIMER-150

Nonparametric Bayesian inference for multidimensional compound Poisson processes

NARCIS (Netherlands)

Gugushvili, S.; van der Meulen, F.; Spreij, P.

2015-01-01

Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density r0 and intensity λ0. We take a nonparametric Bayesian approach to the problem and determine posterior contraction rates in this context,

Loglinear multidimensional IRT models for polytomously scired Items

NARCIS (Netherlands)

Kelderman, Henk

1988-01-01

A loglinear item response theory (IRT) model is proposed that relates polytomously scored item responses to a multidimensional latent space. Each item may have a different response function where each item response may be explained by one or more latent traits. Item response functions may follow a

Loglinear multidimensional IRT models for polytomously scored items

NARCIS (Netherlands)

Kelderman, Henk; Rijkes, Carl P.M.; Rijkes, Carl

1994-01-01

A loglinear IRT model is proposed that relates polytomously scored item responses to a multidimensional latent space. The analyst may specify a response function for each response, indicating which latent abilities are necessary to arrive at that response. Each item may have a different number of

Efficient algorithms of multidimensional γ-ray spectra compression

International Nuclear Information System (INIS)

Morhac, M.; Matousek, V.

2006-01-01

The efficient algorithms to compress multidimensional γ-ray events are presented. Two alternative kinds of compression algorithms based on both the adaptive orthogonal and randomizing transforms are proposed. In both algorithms we employ the reduction of data volume due to the symmetry of the γ-ray spectra

An individual-centered approach to multidimensional poverty: The cases of Chile, Colombia, Ecuador and Peru

NARCIS (Netherlands)

Franco-Correa, A.

2014-01-01

This paper deals with the problem of selecting the unit of analysis in multidimensional poverty analyses, which is a central decision to take, both from academic and normative points of view. The paper compares the results of an individual-level Multidimensional Poverty Index for Chile, Colombia,

Low-diffusion rotated upwind schemes, multigrid and defect correction for steady, multi-dimensional Euler flows

NARCIS (Netherlands)

Koren, B.; Hackbusch, W.; Trottenberg, U.

1991-01-01

Two simple, multi-dimensional upwind discretizations for the steady Euler equations are derived, with the emphasis Iying on bath a good accuracy and a good solvability. The multi-dimensional upwinding consists of applying a one-dimensional Riemann solver with a locally rotated left and right state,

Hidden multidimensional social structure modeling applied to biased social perception

Science.gov (United States)

Maletić, Slobodan; Zhao, Yi

2018-02-01

Intricacies of the structure of social relations are realized by representing a collection of overlapping opinions as a simplicial complex, thus building latent multidimensional structures, through which agents are, virtually, moving as they exchange opinions. The influence of opinion space structure on the distribution of opinions is demonstrated by modeling consensus phenomena when the opinion exchange between individuals may be affected by the false consensus effect. The results indicate that in the cases with and without bias, the road toward consensus is influenced by the structure of multidimensional space of opinions, and in the biased case, complete consensus is achieved. The applications of proposed modeling framework can easily be generalized, as they transcend opinion formation modeling.

Multidimensional simulations of core-collapse supernovae with CHIMERA

Science.gov (United States)

Lentz, Eric J.; Bruenn, S. W.; Yakunin, K.; Endeve, E.; Blondin, J. M.; Harris, J. A.; Hix, W. R.; Marronetti, P.; Messer, O. B.; Mezzacappa, A.

2014-01-01

Core-collapse supernovae are driven by a multidimensional neutrino radiation hydrodynamic (RHD) engine, and full simulation requires at least axisymmetric (2D) and ultimately symmetry-free 3D RHD simulation. We present recent and ongoing work with our multidimensional RHD supernova code CHIMERA to understand the nature of the core-collapse explosion mechanism and its consequences. Recently completed simulations of 12-25 solar mass progenitors(Woosley & Heger 2007) in well resolved (0.7 degrees in latitude) 2D simulations exhibit robust explosions meeting the observationally expected explosion energy. We examine the role of hydrodynamic instabilities (standing accretion shock instability, neutrino driven convection, etc.) on the explosion dynamics and the development of the explosion energy. Ongoing 3D and 2D simulations examine the role that simulation resolution and the removal of the imposed axisymmetry have in the triggering and development of an explosion from stellar core collapse. Companion posters will explore the gravitational wave signals (Yakunin et al.) and nucleosynthesis (Harris et al.) of our simulations.

New strategy for stable-isotope-aided, multidimensional NMR spectroscopy of DNA oligomers

Energy Technology Data Exchange (ETDEWEB)

Ono, Okira; Tate, Shin-Ichi; Kainosho, Masatsune [Tokyo Metropolitan Univ., Tokyo (Japan)

1994-12-01

Nuclear Magnetic Resonance (NMR) is the most efficient method for determining the solution structures of biomolecules. By applying multidimensional heteronuclear NMR techniques to {sup 13}C/{sup 15}N-labeled proteins, we can determine the solution structures of proteins with molecular mass of 20 to 30kDa at an accuracy similar to that of x-ray crystallography. Improvements in NMR instrumentation and techniques as well as the development of protein engineering methods for labeling proteins have rapidly advanced multidimensional heteronuclear NMR of proteins. In contrast, multidimensional heteronuclear NMR studies of nucleic acids is less advanced because there were no efficient methods for preparing large amounts of labeled DNA/RNA oligomers. In this report, we focused on the chemical synthesis of DNA oligomers labeled at specific residue(s). RNA oligomers with specific labels, which are difficult to synthesize by the enzyme method, can be synthesized by the chemical method. The specific labels are useful for conformational analysis of larger molecules such as protein-nucleic acid complexes.

Analyzing cross-reference transactions between authors by use of an asymmetric proximity measure and multidimensional unfolding

DEFF Research Database (Denmark)

Schneider, Jesper Wiborg; Borlund, Pia

2009-01-01

into the maps as relationships become overt. Finally, the study discusses how high publication activity influences mapping results considerably. To counter this effect, we demonstrate the appropriateness of correcting data for main effects by use of an asymmetric proximity measure of odds ratios....... of the author's dual roles of citing and being cited in a reference network. We model a set of 31 authors and compare the results to a recent author co-citation study of Information Science. We find that multidimensional unfolding is a reliable and insightful technique for modelling authors' citing and cited...... dimensions simultaneously. The common space of citing and cited positions exemplify that some authors have substantial discrepancies between their citing behaviour and the way their works are used by peers in the set. Further, modelling mutual relationships as asymmetric brings more accuracy and nuances...

Development of a set of SNP markers present in expressed genes of the apple.

Science.gov (United States)

Chagné, David; Gasic, Ksenija; Crowhurst, Ross N; Han, Yuepeng; Bassett, Heather C; Bowatte, Deepa R; Lawrence, Timothy J; Rikkerink, Erik H A; Gardiner, Susan E; Korban, Schuyler S

2008-11-01

Molecular markers associated with gene coding regions are useful tools for bridging functional and structural genomics. Due to their high abundance in plant genomes, single nucleotide polymorphisms (SNPs) are present within virtually all genomic regions, including most coding sequences. The objective of this study was to develop a set of SNPs for the apple by taking advantage of the wealth of genomics resources available for the apple, including a large collection of expressed sequenced tags (ESTs). Using bioinformatics tools, a search for SNPs within an EST database of approximately 350,000 sequences developed from a variety of apple accessions was conducted. This resulted in the identification of a total of 71,482 putative SNPs. As the apple genome is reported to be an ancient polyploid, attempts were made to verify whether those SNPs detected in silico were attributable either to allelic polymorphisms or to gene duplication or paralogous or homeologous sequence variations. To this end, a set of 464 PCR primer pairs was designed, PCR was amplified using two subsets of plants, and the PCR products were sequenced. The SNPs retrieved from these sequences were then mapped onto apple genetic maps, including a newly constructed map of a Royal Gala x A689-24 cross and a Malling 9 x Robusta 5, map using a bin mapping strategy. The SNP genotyping was performed using the high-resolution melting (HRM) technique. A total of 93 new markers containing 210 coding SNPs were successfully mapped. This new set of SNP markers for the apple offers new opportunities for understanding the genetic control of important horticultural traits using quantitative trait loci (QTL) or linkage disequilibrium analysis. These also serve as useful markers for aligning physical and genetic maps, and as potential transferable markers across the Rosaceae family.

[Measuring job satisfaction: development of a multidimensional scale].

Science.gov (United States)

Faraci, Palmira; Valenti, Giusy

2016-01-01

Although numerous studies have been done on the topic ofjob satisfaction, as regards the Italian research, the construction of specific psychometric instruments is lacking. The present paper is aimed to develop a scale to measure job satisfaction referring to our cultural context. Participants were 222 workers (36.5% males, 63.5% females) with an average age of 38.39 years (SD = 10.91). The formulated items were selected from a large item pool on the basis of the evaluation by a group of expert judges, and the item analysis procedure. In order to establish test validity, the following instruments were also administered: Occupational Stress Indicator, Satisfaction With Life Scale, Rosenberg Self-Esteem Scale, Multidimensional Scale of Perceived Social Support, and Beck Depression Inventory. Both exploratory and confirmatory factor analyses highlighted a 6-factor structure. Those factors were responsible for 51.30% of the total variance. Reliability analyses indicated satisfying internal consistency (ranging from alpha = .73 to alpha = .86). Construct validity was supported by results obtained calculating correlations with the theoretically associated variables. Our findings suggest promising psychometric properties for the presented measure. The instrument could be used in specific programs developed to promote well-being conditions in work settings.

Multidimensional Diagnostic Criteria for Chronic Pain: Introduction to the ACTTION-American Pain Society Pain Taxonomy (AAPT).

Science.gov (United States)

Dworkin, Robert H; Bruehl, Stephen; Fillingim, Roger B; Loeser, John D; Terman, Gregory W; Turk, Dennis C

2016-09-01

A variety of approaches have been used to develop diagnostic criteria for chronic pain. The published evidence of the reliability and validity of existing diagnostic criteria is limited, and these criteria have typically not been used in clinical practice. The availability of a widely accepted, consistently applied, and evidence-based taxonomy of diagnostic criteria would improve the quality of clinical research on chronic pain and would be of great value in clinical practice. To address the need for evidence-based diagnostic criteria for the major chronic pain conditions, the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership with the US Food and Drug Administration and the American Pain Society (APS) have collaborated on the development of the ACTTION-APS Pain Taxonomy (AAPT). AAPT provides a multidimensional framework that is applied systematically in the development of diagnostic criteria. This article (1) describes the background and rationale for AAPT; (2) presents the AAPT taxonomy and the specific conditions for which diagnostic criteria have been developed (to be published separately); (3) briefly reviews the 5 dimensions that constitute the AAPT multidimensional framework and describes the 7 accompanying articles that discuss these dimensions and other important issues involving AAPT; and (4) provides an overview of next steps, specifically, the general processes by which the initial set of diagnostic criteria (for which the evidence base has been drawn from the literature, systematic reviews, and secondary analyses of existing databases) will undergo additional assessments of reliability and validity. To address the need for evidence-based diagnostic criteria for the major chronic pain conditions, the AAPT provides a multidimensional framework that is applied systematically in the development of diagnostic criteria. The long-term objective of AAPT is to advance

Integral and Multidimensional Linear Distinguishers with Correlation Zero

DEFF Research Database (Denmark)

Bogdanov, Andrey; Leander, Gregor; Nyberg, Kaisa

2012-01-01

Zero-correlation cryptanalysis uses linear approximations holding with probability exactly 1/2. In this paper, we reveal fundamental links of zero-correlation distinguishers to integral distinguishers and multidimensional linear distinguishers. We show that an integral implies zero-correlation li...... weak key assumptions. © International Association for Cryptologic Research 2012....

Energy method for multi-dimensional balance laws with non-local dissipation

KAUST Repository

Duan, Renjun

2010-06-01

In this paper, we are concerned with a class of multi-dimensional balance laws with a non-local dissipative source which arise as simplified models for the hydrodynamics of radiating gases. At first we introduce the energy method in the setting of smooth perturbations and study the stability of constants states. Precisely, we use Fourier space analysis to quantify the energy dissipation rate and recover the optimal time-decay estimates for perturbed solutions via an interpolation inequality in Fourier space. As application, the developed energy method is used to prove stability of smooth planar waves in all dimensions n2, and also to show existence and stability of time-periodic solutions in the presence of the time-periodic source. Optimal rates of convergence of solutions towards the planar waves or time-periodic states are also shown provided initially L1-perturbations. © 2009 Elsevier Masson SAS.

Energy method for multi-dimensional balance laws with non-local dissipation

KAUST Repository

Duan, Renjun; Fellner, Klemens; Zhu, Changjiang

2010-01-01

In this paper, we are concerned with a class of multi-dimensional balance laws with a non-local dissipative source which arise as simplified models for the hydrodynamics of radiating gases. At first we introduce the energy method in the setting of smooth perturbations and study the stability of constants states. Precisely, we use Fourier space analysis to quantify the energy dissipation rate and recover the optimal time-decay estimates for perturbed solutions via an interpolation inequality in Fourier space. As application, the developed energy method is used to prove stability of smooth planar waves in all dimensions n2, and also to show existence and stability of time-periodic solutions in the presence of the time-periodic source. Optimal rates of convergence of solutions towards the planar waves or time-periodic states are also shown provided initially L1-perturbations. © 2009 Elsevier Masson SAS.

Spatial and multidimensional visualization of Indonesia's village health statistics.

Science.gov (United States)

Parmanto, Bambang; Paramita, Maria V; Sugiantara, Wayan; Pramana, Gede; Scotch, Matthew; Burke, Donald S

2008-06-11

A community health assessment (CHA) is used to identify and address health issues in a given population. Effective CHA requires timely and comprehensive information from a wide variety of sources, such as: socio-economic data, disease surveillance, healthcare utilization, environmental data, and health resource allocation. Indonesia is a developing country with 235 million inhabitants over 13,000 islands. There are significant barriers to conducting CHA in developing countries like Indonesia, such as the high cost of computing resources and the lack of computing skills necessary to support such an assessment. At the University of Pittsburgh, we have developed the Spatial OLAP (On-Line Analytical Processing) Visualization and Analysis Tool (SOVAT) for performing CHA. SOVAT combines Geographic Information System (GIS) technology along with an advanced multidimensional data warehouse structure to facilitate analysis of large, disparate health, environmental, population, and spatial data. The objective of this paper is to demonstrate the potential of SOVAT for facilitating CHA among developing countries by using health, population, healthcare resources, and spatial data from Indonesia for use in two CHA cases studies. Bureau of Statistics administered data sets from the Indonesian Census, and the Indonesian village statistics, were used in the case studies. The data consisted of: healthcare resources (number of healthcare professionals and facilities), population (census), morbidity and mortality, and spatial (GIS-formatted) information. The data was formatted, combined, and populated into SOVAT for CHA use. Case study 1 involves the distribution of healthcare professionals in Indonesia, while case study 2 involves malaria mortality. Screen shots are shown for both cases. The results for the CHA were retrieved in seconds and presented through the geospatial and numerical SOVAT interface. The case studies show the potential of spatial and multidimensional analysis using

Bayesian Dimensionality Assessment for the Multidimensional Nominal Response Model

Directory of Open Access Journals (Sweden)

Javier Revuelta

2017-06-01

Full Text Available This article introduces Bayesian estimation and evaluation procedures for the multidimensional nominal response model. The utility of this model is to perform a nominal factor analysis of items that consist of a finite number of unordered response categories. The key aspect of the model, in comparison with traditional factorial model, is that there is a slope for each response category on the latent dimensions, instead of having slopes associated to the items. The extended parameterization of the multidimensional nominal response model requires large samples for estimation. When sample size is of a moderate or small size, some of these parameters may be weakly empirically identifiable and the estimation algorithm may run into difficulties. We propose a Bayesian MCMC inferential algorithm to estimate the parameters and the number of dimensions underlying the multidimensional nominal response model. Two Bayesian approaches to model evaluation were compared: discrepancy statistics (DIC, WAICC, and LOO that provide an indication of the relative merit of different models, and the standardized generalized discrepancy measure that requires resampling data and is computationally more involved. A simulation study was conducted to compare these two approaches, and the results show that the standardized generalized discrepancy measure can be used to reliably estimate the dimensionality of the model whereas the discrepancy statistics are questionable. The paper also includes an example with real data in the context of learning styles, in which the model is used to conduct an exploratory factor analysis of nominal data.

Biodiversity as a multidimensional construct: a review, framework and case study of herbivory's impact on plant biodiversity

DEFF Research Database (Denmark)

Naeem, S.; Prager, Case; Weeks, Brian

2016-01-01

Biodiversity is inherently multidimensional, encompassing taxonomic, functional, phylogenetic, genetic, landscape and many other elements of variability of life on the Earth. However, this fundamental principle of multidimensionality is rarely applied in research aimed at understanding biodiversity...... on understory plant cover at Black Rock Forest, New York. Using three biodiversity dimensions (taxonomic, functional and phylogenetic diversity) to explore our framework, we found that herbivory alters biodiversity's multidimensional influence on plant cover; an effect not observable through a unidimensional...

Racial-ethnic self-schemas: Multi-dimensional identity-based motivation

Science.gov (United States)

Oyserman, Daphna

2008-01-01

Prior self-schema research focuses on benefits of being schematic vs. aschematic in stereotyped domains. The current studies build on this work, examining racial-ethnic self-schemas as multi-dimensional, containing multiple, conflicting, and non-integrated images. A multidimensional perspective captures complexity; examining net effects of dimensions predicts within-group differences in academic engagement and well-being. When racial-ethnicity self-schemas focus attention on membership in both in-group and broader society, engagement with school should increase since school is not seen as out-group defining. When racial-ethnicity self-schemas focus attention on inclusion (not obstacles to inclusion) in broader society, risk of depressive symptoms should decrease. Support for these hypotheses was found in two separate samples (8th graders, n = 213, 9th graders followed to 12th grade n = 141). PMID:19122837

An empirical study of multidimensional fidelity of COMPASS consultation.

Science.gov (United States)

Wong, Venus; Ruble, Lisa A; McGrew, John H; Yu, Yue

2018-06-01

Consultation is essential to the daily practice of school psychologists (National Association of School Psychologist, 2010). Successful consultation requires fidelity at both the consultant (implementation) and consultee (intervention) levels. We applied a multidimensional, multilevel conception of fidelity (Dunst, Trivette, & Raab, 2013) to a consultative intervention called the Collaborative Model for Promoting Competence and Success (COMPASS) for students with autism. The study provided 3 main findings. First, multidimensional, multilevel fidelity is a stable construct and increases over time with consultation support. Second, mediation analyses revealed that implementation-level fidelity components had distant, indirect effects on student Individualized Education Program (IEP) outcomes. Third, 3 fidelity components correlated with IEP outcomes: teacher coaching responsiveness at the implementation level, and teacher quality of delivery and student responsiveness at the intervention levels. Implications and future directions are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

Science.gov (United States)

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data

Can the Frost Multidimensional Perfectionism Scale assess perfeccionismo?

Science.gov (United States)

Burgess, Alexandra M; DiBartolo, Patricia Marten; Rendón, María Jose

2017-07-01

Although culture-based measurement bias threatens the validity of intergroup comparison research, measurement invariance is often assumed rather than demonstrated by researchers who draw conclusions about cross-cultural similarities or differences. The current article investigates the cross-cultural invariance of a popular measure of perfectionism, the Frost Multidimensional Perfectionism Scale (F-MPS; Frost, Marten, Lahart, & Rosenblate, 1990) for a Hispanic/Latina sample. Perfectionism, which encompasses high goal setting and sensitivity to critical evaluation, is a transdiagnostic risk factor for internalizing psychopathology that especially warrants focus among groups burdened by mental health disparities. Multiple samples were used in a series of analyses to construct a baseline first-order measurement model and test for cross-group equivalence. For model development, confirmatory factor analyses (CFAs) were used with 320 female participants (M age = 19.61 years) who identified primarily (n = 301) as European/European American. Measurement invariance testing was conducted with multigroup CFAs using another sample of female adults (n = 574; Mage = 21.21 years), identifying either as European/European American (n = 217) or Hispanic/Latina/Latin American (n = 357). Evidence was found for invariance across the revised F-MPS factor structure, pattern of factor loadings, and factor variances/covariances. Results indicate that predictive relationships may be compared across these groups, but caution is suggested when interpreting raw mean score differences due to intercept nonequivalence. Further, second-order model testing demonstrated support for the bidimensional model of perfectionism cross-culturally. Future research on perfectionism within the Latino/a population is encouraged using this equivalent item set. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Manycore Performance-Portability: Kokkos Multidimensional Array Library

Directory of Open Access Journals (Sweden)

H. Carter Edwards

2012-01-01

Full Text Available Large, complex scientific and engineering application code have a significant investment in computational kernels to implement their mathematical models. Porting these computational kernels to the collection of modern manycore accelerator devices is a major challenge in that these devices have diverse programming models, application programming interfaces (APIs, and performance requirements. The Kokkos Array programming model provides library-based approach to implement computational kernels that are performance-portable to CPU-multicore and GPGPU accelerator devices. This programming model is based upon three fundamental concepts: (1 manycore compute devices each with its own memory space, (2 data parallel kernels and (3 multidimensional arrays. Kernel execution performance is, especially for NVIDIA® devices, extremely dependent on data access patterns. Optimal data access pattern can be different for different manycore devices – potentially leading to different implementations of computational kernels specialized for different devices. The Kokkos Array programming model supports performance-portable kernels by (1 separating data access patterns from computational kernels through a multidimensional array API and (2 introduce device-specific data access mappings when a kernel is compiled. An implementation of Kokkos Array is available through Trilinos [Trilinos website, http://trilinos.sandia.gov/, August 2011].

Capturing Complex Multidimensional Data in Location-Based Data Warehouses

DEFF Research Database (Denmark)

Timko, Igor; Pedersen, Torben Bach

2004-01-01

Motivated by the increasing need to handle complex multidimensional data inlocation-based data warehouses, this paper proposes apowerful data model that is able to capture the complexities of such data. The model provides a foundation for handling complex transportationinfrastructures...

The Multidimensionality of Child Poverty: Evidence from Afghanistan

Science.gov (United States)

Trani, Jean-Francois; Biggeri, Mario; Mauro, Vincenzo

2013-01-01

This paper examines multidimensional poverty among children in Afghanistan using the Alkire-Foster method. Several previous studies have underlined the need to separate children from their adult nexus when studying poverty and treat them according to their own specificities. From the capability approach, child poverty is understood to be the lack…

Biodiversity as a multidimensional construct: a review, framework and case study of herbivory's impact on plant biodiversity

Science.gov (United States)

Naeem, S.; Prager, Case; Weeks, Brian; Varga, Alex; Flynn, Dan F. B.; Griffin, Kevin; Muscarella, Robert; Palmer, Matthew; Wood, Stephen; Schuster, William

2016-01-01

Biodiversity is inherently multidimensional, encompassing taxonomic, functional, phylogenetic, genetic, landscape and many other elements of variability of life on the Earth. However, this fundamental principle of multidimensionality is rarely applied in research aimed at understanding biodiversity's value to ecosystem functions and the services they provide. This oversight means that our current understanding of the ecological and environmental consequences of biodiversity loss is limited primarily to what unidimensional studies have revealed. To address this issue, we review the literature, develop a conceptual framework for multidimensional biodiversity research based on this review and provide a case study to explore the framework. Our case study specifically examines how herbivory by whitetail deer (Odocoileus virginianus) alters the multidimensional influence of biodiversity on understory plant cover at Black Rock Forest, New York. Using three biodiversity dimensions (taxonomic, functional and phylogenetic diversity) to explore our framework, we found that herbivory alters biodiversity's multidimensional influence on plant cover; an effect not observable through a unidimensional approach. Although our review, framework and case study illustrate the advantages of multidimensional over unidimensional approaches, they also illustrate the statistical and empirical challenges such work entails. Meeting these challenges, however, where data and resources permit, will be important if we are to better understand and manage the consequences we face as biodiversity continues to decline in the foreseeable future. PMID:27928041

Biodiversity as a multidimensional construct: a review, framework and case study of herbivory's impact on plant biodiversity.

Science.gov (United States)

Naeem, S; Prager, Case; Weeks, Brian; Varga, Alex; Flynn, Dan F B; Griffin, Kevin; Muscarella, Robert; Palmer, Matthew; Wood, Stephen; Schuster, William

2016-12-14

Biodiversity is inherently multidimensional, encompassing taxonomic, functional, phylogenetic, genetic, landscape and many other elements of variability of life on the Earth. However, this fundamental principle of multidimensionality is rarely applied in research aimed at understanding biodiversity's value to ecosystem functions and the services they provide. This oversight means that our current understanding of the ecological and environmental consequences of biodiversity loss is limited primarily to what unidimensional studies have revealed. To address this issue, we review the literature, develop a conceptual framework for multidimensional biodiversity research based on this review and provide a case study to explore the framework. Our case study specifically examines how herbivory by whitetail deer (Odocoileus virginianus) alters the multidimensional influence of biodiversity on understory plant cover at Black Rock Forest, New York. Using three biodiversity dimensions (taxonomic, functional and phylogenetic diversity) to explore our framework, we found that herbivory alters biodiversity's multidimensional influence on plant cover; an effect not observable through a unidimensional approach. Although our review, framework and case study illustrate the advantages of multidimensional over unidimensional approaches, they also illustrate the statistical and empirical challenges such work entails. Meeting these challenges, however, where data and resources permit, will be important if we are to better understand and manage the consequences we face as biodiversity continues to decline in the foreseeable future. © 2016 The Authors.

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

Directory of Open Access Journals (Sweden)

Maria E Pushpanathan

Full Text Available Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD. The Parkinson's Disease Sleep Scale (PDSS and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2 quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA and REM sleep behaviour disorder (RBD symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

Exploding and non-exploding stars: Coupling nuclear reaction networks to multidimensional hydrodynamics

International Nuclear Information System (INIS)

Kifonidis, K.; Mueller, E.; Plewa, T.

2001-01-01

After decades of one-dimensional nucleosynthesis calculations, the growth of computational resources has meanwhile reached a level, which for the first time allows astrophysicists to consider performing routinely realistic multidimensional nucleosynthesis calculations in explosive and, to some extent, also in non-explosive environments. In the present contribution we attempt to give a short overview of the physical and numerical problems which are encountered in these simulations. In addition, we assess the accuracy that can be currently achieved in the computation of nucleosynthetic yields, using multidimensional simulations of core collapse supernovae as an example

Factor structure and gender stability in the multidimensional condom attitudes scale.

Science.gov (United States)

Starosta, Amy J; Berghoff, Christopher R; Earleywine, Mitch

2015-06-01

Sexually transmitted infections continue to trouble the United States and can be attenuated through increased condom use. Attitudes about condoms are an important multidimensional factor that can affect sexual health choices and have been successfully measured using the Multidimensional Condom Attitudes Scale (MCAS). Such attitudes have the potential to vary between men and women, yet little work has been undertaken to identify if the MCAS accurately captures attitudes without being influenced by underlying gender biases. We examined the factor structure and gender invariance on the MCAS using confirmatory factor analysis and item response theory, within-subscale differential item functioning analyses. More than 770 participants provided data via the Internet. Results of differential item functioning analyses identified three items as differentially functioning between the genders, and removal of these items is recommended. Findings confirmed the previously hypothesized multidimensional nature of condom attitudes and the five-factor structure of the MCAS even after the removal of the three problematic items. In general, comparisons across genders using the MCAS seem reasonable from a methodological standpoint. Results are discussed in terms of improving sexual health research and interventions. © The Author(s) 2014.

Multidimensional profiles of health locus of control in Hispanic Americans.

Science.gov (United States)

Champagne, Brian R; Fox, Rina S; Mills, Sarah D; Sadler, Georgia Robins; Malcarne, Vanessa L

2016-10-01

Latent profile analysis identified health locus of control profiles among 436 Hispanic Americans who completed the Multidimensional Health Locus of Control scales. Results revealed four profiles: Internally Oriented-Weak, -Moderate, -Strong, and Externally Oriented. The profile groups were compared on sociocultural and demographic characteristics, health beliefs and behaviors, and physical and mental health outcomes. The Internally Oriented-Strong group had less cancer fatalism, religiosity, and equity health attributions, and more alcohol consumption than the other three groups; the Externally Oriented group had stronger equity health attributions and less alcohol consumption. Deriving multidimensional health locus of control profiles through latent profile analysis allows examination of the relationships of health locus of control subtypes to health variables. © The Author(s) 2015.

[Intraoperative multidimensional visualization].

Science.gov (United States)

Sperling, J; Kauffels, A; Grade, M; Alves, F; Kühn, P; Ghadimi, B M

2016-12-01

Modern intraoperative techniques of visualization are increasingly being applied in general and visceral surgery. The combination of diverse techniques provides the possibility of multidimensional intraoperative visualization of specific anatomical structures. Thus, it is possible to differentiate between normal tissue and tumor tissue and therefore exactly define tumor margins. The aim of intraoperative visualization of tissue that is to be resected and tissue that should be spared is to lead to a rational balance between oncological and functional results. Moreover, these techniques help to analyze the physiology and integrity of tissues. Using these methods surgeons are able to analyze tissue perfusion and oxygenation. However, to date it is not clear to what extent these imaging techniques are relevant in the clinical routine. The present manuscript reviews the relevant modern visualization techniques focusing on intraoperative computed tomography and magnetic resonance imaging as well as augmented reality, fluorescence imaging and optoacoustic imaging.

Applications of Convex Analysis to Multidimensional Scaling

OpenAIRE

Jan de Leeuw

2011-01-01

In this paper we discuss the convergence of an algorithm for metric and nonmetric multidimensional scaling that is very similar to the C-matrix algorithm of Guttman. The paper improves some earlier results in two respects. In the first place the analysis is extended to cover general Minkovski metrics, in the second place a more elementary proof of convergence based on results of Robert is presented.

Questionário multidimensional para análise da imagem do enfermeiro Cuestionario multidimensional para análisis de la imagen del enfermero A multidimensional questionnaire to evaluate the image of registered nurses

Directory of Open Access Journals (Sweden)

Luciana Barizon Luchesi

2010-01-01

Full Text Available OBJETIVO: Construir um questionário multidimensional para avaliar a percepção de alunos do ensino médio frente sobre a enfermagem e validar o questionário multidimensional em conteúdo, aparência e análise semântica. MÉTODOS: Estudo quanti-qualitativo com fins de instrumentação, utilizando o referencial teórico-metodológico de Pasquali, Silva e Ribeiro-Filho que recomendam as etapas de levantamento do conceito do constructo, geração dos itens do instrumento fundamentado na literatura e aferição das propriedades psicométricas. RESULTADOS: os itens do instrumento são derivados da literatura sobre psicologia social, história da enfermagem e escolha vocacional. Após validação de conteúdo, validação aparente e análise semântica, houve a aplicação do instrumento em uma amostra de 269 alunos. CONCLUSÃO: o instrumento mostrou-se de fácil entendimento e aplicação. Além de análise diagnóstica, o instrumento poderá ser utilizado em estudos experimentais.OBJETIVO: Construir un cuestionario multidimensional para evaluar la percepción de los alumnos de la enseñanza media sobre la enfermería y validar el cuestionario multidimensional en contenido, apariencia y análisis semántico. MÉTODOS: Estudio cuantitativo y cualitativo con fines de instrumentación, utilizando el marco teórico metodológico de Pasquali, Silva y Ribeiro-Filho que recomiendan las etapas de levantamiento del concepto del constructo, generación de los ítems del instrumento fundamentado en la literatura y evaluación de las propiedades psicométricas. RESULTADOS: Los ítems del instrumento son derivados de la literatura sobre psicología social, historia de la enfermería y elección vocacional. Después de la validación de contenido, validación aparente y análisis semántico, se aplicó el instrumento en una muestra de 269 alumnos. CONCLUSIÓN: El instrumento se mostró de fácil entendimiento y aplicación. Además del análisis de diagn

Multi-dimensional medical images compressed and filtered with wavelets

International Nuclear Information System (INIS)

Boyen, H.; Reeth, F. van; Flerackers, E.

2002-01-01

Full text: Using the standard wavelet decomposition methods, multi-dimensional medical images can be compressed and filtered by repeating the wavelet-algorithm on 1D-signals in an extra loop per extra dimension. In the non-standard decomposition for multi-dimensional images the areas that must be zero-filled in case of band- or notch-filters are more complex than geometric areas such as rectangles or cubes. Adding an additional dimension in this algorithm until 4D (e.g. a 3D beating heart) increases the geometric complexity of those areas even more. The aim of our study was to calculate the boundaries of the formed complex geometric areas, so we can use the faster non-standard decomposition to compress and filter multi-dimensional medical images. Because a lot of 3D medical images taken by PET- or SPECT-cameras have only a few layers in the Z-dimension and compressing images in a dimension with a few voxels is usually not worthwhile, we provided a solution in which one can choose which dimensions will be compressed or filtered. With the proposal of non-standard decomposition on Daubechies' wavelets D2 to D20 by Steven Gollmer in 1992, 1D data can be compressed and filtered. Each additional level works only on the smoothed data, so the transformation-time halves per extra level. Zero-filling a well-defined area alter the wavelet-transform and then performing the inverse transform will do the filtering. To be capable to compress and filter up to 4D-Images with the faster non-standard wavelet decomposition method, we have investigated a new method for calculating the boundaries of the areas which must be zero-filled in case of filtering. This is especially true for band- and notch filtering. Contrary to the standard decomposition method, the areas are no longer rectangles in 2D or cubes in 3D or a row of cubes in 4D: they are rectangles expanded with a half-sized rectangle in the other direction for 2D, cubes expanded with half cubes in one and quarter cubes in the

Transcriptional differences between normal and glioma-derived glial progenitor cells identify a core set of dysregulated genes.

Science.gov (United States)

Auvergne, Romane M; Sim, Fraser J; Wang, Su; Chandler-Militello, Devin; Burch, Jaclyn; Al Fanek, Yazan; Davis, Danielle; Benraiss, Abdellatif; Walter, Kevin; Achanta, Pragathi; Johnson, Mahlon; Quinones-Hinojosa, Alfredo; Natesan, Sridaran; Ford, Heide L; Goldman, Steven A

2013-06-27

Glial progenitor cells (GPCs) are a potential source of malignant gliomas. We used A2B5-based sorting to extract tumorigenic GPCs from human gliomas spanning World Health Organization grades II-IV. Messenger RNA profiling identified a cohort of genes that distinguished A2B5+ glioma tumor progenitor cells (TPCs) from A2B5+ GPCs isolated from normal white matter. A core set of genes and pathways was substantially dysregulated in A2B5+ TPCs, which included the transcription factor SIX1 and its principal cofactors, EYA1 and DACH2. Small hairpin RNAi silencing of SIX1 inhibited the expansion of glioma TPCs in vitro and in vivo, suggesting a critical and unrecognized role of the SIX1-EYA1-DACH2 system in glioma genesis or progression. By comparing the expression patterns of glioma TPCs with those of normal GPCs, we have identified a discrete set of pathways by which glial tumorigenesis may be better understood and more specifically targeted. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Performance of single and concatenated sets of mitochondrial genes at inferring metazoan relationships relative to full mitogenome data.

Directory of Open Access Journals (Sweden)

Justin C Havird

Full Text Available Mitochondrial (mt genes are some of the most popular and widely-utilized genetic loci in phylogenetic studies of metazoan taxa. However, their linked nature has raised questions on whether using the entire mitogenome for phylogenetics is overkill (at best or pseudoreplication (at worst. Moreover, no studies have addressed the comparative phylogenetic utility of mitochondrial genes across individual lineages within the entire Metazoa. To comment on the phylogenetic utility of individual mt genes as well as concatenated subsets of genes, we analyzed mitogenomic data from 1865 metazoan taxa in 372 separate lineages spanning genera to subphyla. Specifically, phylogenies inferred from these datasets were statistically compared to ones generated from all 13 mt protein-coding (PC genes (i.e., the "supergene" set to determine which single genes performed "best" at, and the minimum number of genes required to, recover the "supergene" topology. Surprisingly, the popular marker COX1 performed poorest, while ND5, ND4, and ND2 were most likely to reproduce the "supergene" topology. Averaged across all lineages, the longest ∼2 mt PC genes were sufficient to recreate the "supergene" topology, although this average increased to ∼5 genes for datasets with 40 or more taxa. Furthermore, concatenation of the three "best" performing mt PC genes outperformed that of the three longest mt PC genes (i.e, ND5, COX1, and ND4. Taken together, while not all mt PC genes are equally interchangeable in phylogenetic studies of the metazoans, some subset can serve as a proxy for the 13 mt PC genes. However, the exact number and identity of these genes is specific to the lineage in question and cannot be applied indiscriminately across the Metazoa.

Trust and credibility: measured by multidimensional scaling

International Nuclear Information System (INIS)

Warg, L.E.; Bodin, L.

1998-01-01

Full text of publication follows: in focus of much of today's research interest in risk communication, is the fact that the communities do not trust policy and decision makers such as politicians, government or industry people. This is especially serious in the years to come when we are expecting risk issues concerning for example the nuclear industry, global warming and hazardous waste, to be even higher on the political and social agenda all over the world. Despite the research efforts devoted to trust, society needs an in depth understanding of trust for conducting successful communication regarding environmental hazards. The present abstract is about an experimental study in psychology where focus has been on the possibility to use the multidimensional scaling technique to explore the characteristics people consider to be of importance when they say that certain persons are credible. In the study, a total of 61 students of the University of Oerebro, Sweden, were required to make comparisons of the similarity between 12 well-known swedish persons from politics science, media, industry, 'TV-world' and literature (two persons at a time), regarding their credibility when making statements about risks in society. In addition, the subjects were rating the importance of 19 factors for the credibility of a source. These 61 persons comprised three groups of students: pedagogists, business economists, and chemists. There were 61 % women and 39% men and the mean age was 23 years. The results will be analyzed using multidimensional scaling technique. Differences between the three groups will be analyzed and presented as well as those between men and women. In addition, the 19 factors will be discussed and considered when trying to label the dimensions accounted for by the multidimensional scaling technique. The result from this study will contribute to our understanding of important factors behind human judgments concerning trust and credibility. It will also point to a

Theme section: Multi-dimensional modelling, analysis and visualization

DEFF Research Database (Denmark)

Guilbert, Éric; Coltekin, Arzu; Antón Castro, Francesc/François

2016-01-01

(Biljecki et al., 2015) as well as the temporal, but also the scale dimension (Van Oosterom and Stoter, 2010) or, as mentioned by(Lu et al., 2016), multi-spectral and multi-sensor data. Such a view provides an organisation of multidimensional data around these different axes and it is time to explore each...

Self Esteem, Locus of Control and Multidimensional Perfectionism as the Predictors of Subjective Well Being

Science.gov (United States)

Karatas, Zeynep; Tagay, Ozlem

2012-01-01

The purpose of this study is to determine whether there is a relationship between self-esteem, locus of control and multidimensional perfectionism, and the extent to which the variables of self-esteem, locus of control and multidimensional perfectionism contribute to the prediction of subjective well-being. The study was carried out with 318 final…

The first set of EST resource for gene discovery and marker development in pigeonpea (Cajanus cajan L.

Directory of Open Access Journals (Sweden)

Byregowda Munishamappa

2010-03-01

.8% in molecular function. Further, 19 genes were identified differentially expressed between FW- responsive genotypes and 20 between SMD- responsive genotypes. Generated ESTs were compiled together with 908 ESTs available in public domain, at the time of analysis, and a set of 5,085 unigenes were defined that were used for identification of molecular markers in pigeonpea. For instance, 3,583 simple sequence repeat (SSR motifs were identified in 1,365 unigenes and 383 primer pairs were designed. Assessment of a set of 84 primer pairs on 40 elite pigeonpea lines showed polymorphism with 15 (28.8% markers with an average of four alleles per marker and an average polymorphic information content (PIC value of 0.40. Similarly, in silico mining of 133 contigs with ≥ 5 sequences detected 102 single nucleotide polymorphisms (SNPs in 37 contigs. As an example, a set of 10 contigs were used for confirming in silico predicted SNPs in a set of four genotypes using wet lab experiments. Occurrence of SNPs were confirmed for all the 6 contigs for which scorable and sequenceable amplicons were generated. PCR amplicons were not obtained in case of 4 contigs. Recognition sites for restriction enzymes were identified for 102 SNPs in 37 contigs that indicates possibility of assaying SNPs in 37 genes using cleaved amplified polymorphic sequences (CAPS assay. Conclusion The pigeonpea EST dataset generated here provides a transcriptomic resource for gene discovery and development of functional markers associated with biotic stress resistance. Sequence analyses of this dataset have showed conservation of a considerable number of pigeonpea transcripts across legume and model plant species analysed as well as some putative pigeonpea specific genes. Validation of identified biotic stress responsive genes should provide candidate genes for allele mining as well as candidate markers for molecular breeding.

Meta-analysis of Drosophila circadian microarray studies identifies a novel set of rhythmically expressed genes.

Directory of Open Access Journals (Sweden)

Kevin P Keegan

2007-11-01

Full Text Available Five independent groups have reported microarray studies that identify dozens of rhythmically expressed genes in the fruit fly Drosophila melanogaster. Limited overlap among the lists of discovered genes makes it difficult to determine which, if any, exhibit truly rhythmic patterns of expression. We reanalyzed data from all five reports and found two sources for the observed discrepancies, the use of different expression pattern detection algorithms and underlying variation among the datasets. To improve upon the methods originally employed, we developed a new analysis that involves compilation of all existing data, application of identical transformation and standardization procedures followed by ANOVA-based statistical prescreening, and three separate classes of post hoc analysis: cross-correlation to various cycling waveforms, autocorrelation, and a previously described fast Fourier transform-based technique. Permutation-based statistical tests were used to derive significance measures for all post hoc tests. We find application of our method, most significantly the ANOVA prescreening procedure, significantly reduces the false discovery rate relative to that observed among the results of the original five reports while maintaining desirable statistical power. We identify a set of 81 cycling transcripts previously found in one or more of the original reports as well as a novel set of 133 transcripts not found in any of the original studies. We introduce a novel analysis method that compensates for variability observed among the original five Drosophila circadian array reports. Based on the statistical fidelity of our meta-analysis results, and the results of our initial validation experiments (quantitative RT-PCR, we predict many of our newly found genes to be bona fide cyclers, and suggest that they may lead to new insights into the pathways through which clock mechanisms regulate behavioral rhythms.

Effective action in multidimensional quantum gravity, and spontaneous compactification

International Nuclear Information System (INIS)

Bagrov, V.G.; Bukhbinder, I.L.; Odintsov, S.D.

1987-01-01

The one-loop effective action (Casimir energy) is obtained for a special form of model of multidimensional quantum gravity and for several variants of d-dimensional quantum R 2 -gravity on the space M 4 x T/sub d//sub -4/, where M 4 is Minkowski space and T/sub d//sub -4/ is the (d-4)-dimensional torus. It is shown that the effective action of the model of multidimensional quantum gravity and R 2 -gravity without the cosmological term and Einstein term leads to instability of the classical compactification. By a numerical calculation it is demonstrated that the effective action of five-dimensional R 2 -gravity with the cosmological term admits a self-consistent spontaneous compactification. The one-loop effective action is also found for five-dimensional Einstein gravity with antisymmetric torsion on the space M 4 x S 1 (S 1 is the one-dimensional sphere)

SM4MQ: A Semantic Model for Multidimensional Queries

DEFF Research Database (Denmark)

Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar

2017-01-01

metadata artifacts (e.g., queries) to assist users with the analysis. However, modeling and sharing of most of these artifacts are typically overlooked. Thus, in this paper we focus on the query metadata artifact in the Exploratory OLAP context and propose an RDF-based vocabulary for its representation......, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD) data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply...... the method to a use case of transforming queries from SM4MQ to a vector representation. For the use case, we developed the prototype and performed an evaluation that shows how our approach can significantly ease and support user assistance such as query recommendation....

Expression map of a complete set of gustatory receptor genes in chemosensory organs of Bombyx mori.

Science.gov (United States)

Guo, Huizhen; Cheng, Tingcai; Chen, Zhiwei; Jiang, Liang; Guo, Youbing; Liu, Jianqiu; Li, Shenglong; Taniai, Kiyoko; Asaoka, Kiyoshi; Kadono-Okuda, Keiko; Arunkumar, Kallare P; Wu, Jiaqi; Kishino, Hirohisa; Zhang, Huijie; Seth, Rakesh K; Gopinathan, Karumathil P; Montagné, Nicolas; Jacquin-Joly, Emmanuelle; Goldsmith, Marian R; Xia, Qingyou; Mita, Kazuei

2017-03-01

Most lepidopteran species are herbivores, and interaction with host plants affects their gene expression and behavior as well as their genome evolution. Gustatory receptors (Grs) are expected to mediate host plant selection, feeding, oviposition and courtship behavior. However, due to their high diversity, sequence divergence and extremely low level of expression it has been difficult to identify precisely a complete set of Grs in Lepidoptera. By manual annotation and BAC sequencing, we improved annotation of 43 gene sequences compared with previously reported Grs in the most studied lepidopteran model, the silkworm, Bombyx mori, and identified 7 new tandem copies of BmGr30 on chromosome 7, bringing the total number of BmGrs to 76. Among these, we mapped 68 genes to chromosomes in a newly constructed chromosome distribution map and 8 genes to scaffolds; we also found new evidence for large clusters of BmGrs, especially from the bitter receptor family. RNA-seq analysis of diverse BmGr expression patterns in chemosensory organs of larvae and adults enabled us to draw a precise organ specific map of BmGr expression. Interestingly, most of the clustered genes were expressed in the same tissues and more than half of the genes were expressed in larval maxillae, larval thoracic legs and adult legs. For example, BmGr63 showed high expression levels in all organs in both larval and adult stages. By contrast, some genes showed expression limited to specific developmental stages or organs and tissues. BmGr19 was highly expressed in larval chemosensory organs (especially antennae and thoracic legs), the single exon genes BmGr53 and BmGr67 were expressed exclusively in larval tissues, the BmGr27-BmGr31 gene cluster on chr7 displayed a high expression level limited to adult legs and the candidate CO 2 receptor BmGr2 was highly expressed in adult antennae, where few other Grs were expressed. Transcriptional analysis of the Grs in B. mori provides a valuable new reference for

A Julia set model of field-directed morphogenesis: developmental biology and artificial life.

Science.gov (United States)

Levin, M

1994-04-01

One paradigm used in understanding the control of morphogenetic events is the concept of positional information, where sub-organismic components (such as cells) act in response to positional cues. It is important to determine what kinds of spatiotemporal patterns may be obtained by such a method, and what the characteristics of such a morphogenetic process might be. This paper presents a computer model of morphogenesis based on gene activity driven by interpreting a positional information field. In this model, the interactions of mutually regulating developmental genes are viewed as a map from R2 to R2, and are modeled by the complex number algebra. Functions in complex variables are used to simulate genetic interactions resulting in position-dependent differentiation. This is shown to be equivalent to computing modified Julia sets, and is seen to be sufficient to produce a very rich set of morphologies which are similar in appearance and several important characteristics to those of real organisms. The properties of this model can be used to study the potential role of fields and positional information as guiding factors in morphogenesis, as the model facilitates the study of static images, time-series (movies) and experimental alterations of the developmental process. It is thus shown that gene interactions can be modeled as a multi-dimensional algebra, and that only two interacting genes are sufficient for (i) complex pattern formation, (ii) chaotic differentiation behavior, and (iii) production of sharp edges from a continuous positional information field. This model is meant to elucidate the properties of the process of positional information-guided biomorphogenesis, not to serve as a simulation of any particular organism's development. Good quantitative data are not currently available on the interplay of gene products in morphogenesis. Thus, no attempt is made to link the images produced with actual pictures of any particular real organism. A brief

A novel hybrid approach with multidimensional-like effects for compressible flow computations

Science.gov (United States)

Kalita, Paragmoni; Dass, Anoop K.

2017-07-01

A multidimensional scheme achieves good resolution of strong and weak shocks irrespective of whether the discontinuities are aligned with or inclined to the grid. However, these schemes are computationally expensive. This paper achieves similar effects by hybridizing two schemes, namely, AUSM and DRLLF and coupling them through a novel shock switch that operates - unlike existing switches - on the gradient of the Mach number across the cell-interface. The schemes that are hybridized have contrasting properties. The AUSM scheme captures grid-aligned (and strong) shocks crisply but it is not so good for non-grid-aligned weaker shocks, whereas the DRLLF scheme achieves sharp resolution of non-grid-aligned weaker shocks, but is not as good for grid-aligned strong shocks. It is our experience that if conventional shock switches based on variables like density, pressure or Mach number are used to combine the schemes, the desired effect of crisp resolution of grid-aligned and non-grid-aligned discontinuities are not obtained. To circumvent this problem we design a shock switch based - for the first time - on the gradient of the cell-interface Mach number with very impressive results. Thus the strategy of hybridizing two carefully selected schemes together with the innovative design of the shock switch that couples them, affords a method that produces the effects of a multidimensional scheme with a lower computational cost. It is further seen that hybridization of the AUSM scheme with the recently developed DRLLFV scheme using the present shock switch gives another scheme that provides crisp resolution for both shocks and boundary layers. Merits of the scheme are established through a carefully selected set of numerical experiments.

Experimental observation of a multi-dimensional mixing behavior of steam-water flow in the MIDAS test facility

International Nuclear Information System (INIS)

Kweon, T. S.; Yun, B. J.; Ah, D. J.; Ju, I. C.; Song, C. H.; Park, J. K.

2001-01-01

Multi-dimensional thermal-hydraulic hehavior, such as ECC (Emergency Core Cooling) bypass, ECC penetration, steam-water condensation and accumulated water level, in an annular downcomer of a PWR (Pressurized Water Reactor) reactor vessel with a DVI(Direct Vessel Injection) injection mode is presented based on the experimental observations in the MIDAS (Multi-dimensional Investigation in Downcomer Annulus Simulation) steam-water facility. From the steady-state tests to similate a late reflood phase of LBLOCA (Large Break Loss-of-Coolant Accidents), major thermal-hydraulic phenomena in the downcomer are quantified under a wide range of test conditions. Especially, isothermal lines show well multi-dimensional phenomena of phase interaction between steam and water in the annulus downcomer. Overall test results show that multi-dimensional thermal-hydraulic behaviors occur in the downcomer annulus region as expected. The MIDAS test facility is a steam-water separate effect test facility, which is 1/4.93 linearly scaled-down of a 1400 MWe PWR type of nuclear reactor, with focusing on understanding multi-dimensional thermal-hydraulic phenomena in annulus downcomer with various types of safety injection location during refill or reflood phase of a LBLOCA in PWR

Accurate Gene Expression-Based Biodosimetry Using a Minimal Set of Human Gene Transcripts