Implementing Relative Ranking Evaluation Framework at Department of Energy (DOE) installations

International Nuclear Information System (INIS)

Sharma, S.K.; Williamson, D.; Treichel, L.C.; James, L.M.

1996-01-01

The US Department of Energy (DOE) Office of Environmental Restoration (EM-40) has developed the Relative Ranking Evaluation Framework (RREF) to help categorize release sites, facilities and buildings requiring restoration or decommissioning. Based on this framework, a computer tool, the Relative Rank Evaluation Program (RREP) has been developed to evaluate release sites, facilities and buildings, and to manage information pertaining to relative ranking evaluations. The relative ranking information is being used by both Headquarters and field project managers, and other environmental personnel responsible for planning, executing and evaluation environmental restoration activities at DOE installations. External stakeholders, such as representatives of federal and state regulatory agencies, local governments and communities in the vicinity of current and formerly used DOE installations may use this data to review proposed and planned activities

Ranking related entities: components and analyses

NARCIS (Netherlands)

Bron, M.; Balog, K.; de Rijke, M.

2010-01-01

Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given source entity. We propose a framework for addressing this task and perform a detailed analysis of four core components;

Associations of relative deprivation and income rank with depressive symptoms among older adults in Japan.

Science.gov (United States)

Gero, Krisztina; Kondo, Katsunori; Kondo, Naoki; Shirai, Kokoro; Kawachi, Ichiro

2017-09-01

Income is hypothesized to affect health not just through material pathways (i.e., the ability to purchase health-enhancing goods) but also through psychosocial pathways (e.g., social comparisons with others). Two concepts relevant to the psychosocial effects of income are: relative deprivation (for example expressed by the Yitzhaki Index, measuring the magnitude of difference in income among individuals) and Income Rank. This study examined whether higher relative deprivation and lower income rank are associated with depressive symptoms in an older population independently of absolute income. Using cross-sectional data of 83,100 participants (40,038 men and 43,062 women) in the Japan Gerontological Evaluation Study (JAGES), this study applied multiple logistic regression models to calculate the odds ratios (OR) of depression associated with relative deprivation/Income Rank. The Japanese Geriatric Depression Scale (GDS-15) was used to assess depressive symptoms, and subjects with a score of ≥5 were categorized as depressed. Reference groups for calculating the Yitzhaki Index and income rank were constructed based on same gender, age-group, and municipality of residence. The findings indicated that after controlling for demographic factors, each 100,000 yen increase in relative deprivation and 0.1 unit decrease in relative rank was associated with a 1.07 (95% CI = 1.07, 1.08) and a 1.15 (95% CI = 1.14, 1.16) times higher odds of depression, respectively, in men. The corresponding ORs in women were 1.05 (95% CI = 1.05, 1.06) and 1.12 (95% CI = 1.11, 1.13), respectively. After adjustment for other covariates and stratification by income quartiles, the results remained statistically significant. Women in the highest income quartile appeared to be more susceptible to the adverse mental health effects of low income rank, while among men the associations were reversed. Low income rank appeared to be more toxic for the poor. Concepts of relative income appear to

How to Rank Journals.

Science.gov (United States)

Bradshaw, Corey J A; Brook, Barry W

2016-01-01

There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

Science.gov (United States)

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A study on ranking ethical factors influencing customer loyalty

Directory of Open Access Journals (Sweden)

Mahmood Modiri

2013-10-01

Full Text Available Having loyal customer is the primary objective of any business owner since loyal customers purchase on regular basis, create sustainable growth and reduce risk of bankruptcy. During the past few years, many people argue that customer loyalty must be established through ethical values. In this paper, we present an empirical investigation to detect ethical factors influencing customer loyalty. The proposed study determines five criteria including customer repurchase, interest in brand, recommending brand to others, positive attitude toward brand and cognitive loyalty to brand. These criteria have been ranked using fuzzy analytical network process. The study determines 14 different ethical values, which may play essential role on customer loyalty and using VIKOR, different ethical values are ranked. The study indicates that welcoming customers is the most important factor followed by cheerfulness, on time delivery, being informative and having appropriate standards.

Unitary Root Music and Unitary Music with Real-Valued Rank Revealing Triangular Factorization

Science.gov (United States)

2010-06-01

AFRL-RY-WP-TP-2010-1213 UNITARY ROOT MUSIC AND UNITARY MUSIC WITH REAL-VALUED RANK REVEALING TRIANGULAR FACTORIZATION (Postprint) Nizar...DATES COVERED (From - To) June 2010 Journal Article Postprint 08 September 2006 – 31 August 2009 4. TITLE AND SUBTITLE UNITARY ROOT MUSIC AND...UNITARY MUSIC WITH REAL-VALUED RANK REVEALING TRIANGULAR FACTORIZATION (Postprint) 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA8650-05-D-1912-0007 5c

Use of search engine optimization factors for Google page rank prediction

OpenAIRE

Tvrdi, Barbara

2012-01-01

Over the years, search engines have become an important tool for finding information. It is known that users select the link on the first page of search results in 62% of the cases. Search engine optimization techniques enable website improvement and therefore a better ranking in search engines. The exact specification of the factors that affect website ranking is not disclosed by search engine owners. In this thesis we tried to choose some most frequently mentioned search engine optimizatio...

It's all relative: ranking the diversity of aquatic bacterial communities.

Science.gov (United States)

Shaw, Allison K; Halpern, Aaron L; Beeson, Karen; Tran, Bao; Venter, J Craig; Martiny, Jennifer B H

2008-09-01

The study of microbial diversity patterns is hampered by the enormous diversity of microbial communities and the lack of resources to sample them exhaustively. For many questions about richness and evenness, however, one only needs to know the relative order of diversity among samples rather than total diversity. We used 16S libraries from the Global Ocean Survey to investigate the ability of 10 diversity statistics (including rarefaction, non-parametric, parametric, curve extrapolation and diversity indices) to assess the relative diversity of six aquatic bacterial communities. Overall, we found that the statistics yielded remarkably similar rankings of the samples for a given sequence similarity cut-off. This correspondence, despite the different underlying assumptions of the statistics, suggests that diversity statistics are a useful tool for ranking samples of microbial diversity. In addition, sequence similarity cut-off influenced the diversity ranking of the samples, demonstrating that diversity statistics can also be used to detect differences in phylogenetic structure among microbial communities. Finally, a subsampling analysis suggests that further sequencing from these particular clone libraries would not have substantially changed the richness rankings of the samples.

Nonnegative Matrix Factorization with Rank Regularization and Hard Constraint.

Science.gov (United States)

Shang, Ronghua; Liu, Chiyang; Meng, Yang; Jiao, Licheng; Stolkin, Rustam

2017-09-01

Nonnegative matrix factorization (NMF) is well known to be an effective tool for dimensionality reduction in problems involving big data. For this reason, it frequently appears in many areas of scientific and engineering literature. This letter proposes a novel semisupervised NMF algorithm for overcoming a variety of problems associated with NMF algorithms, including poor use of prior information, negative impact on manifold structure of the sparse constraint, and inaccurate graph construction. Our proposed algorithm, nonnegative matrix factorization with rank regularization and hard constraint (NMFRC), incorporates label information into data representation as a hard constraint, which makes full use of prior information. NMFRC also measures pairwise similarity according to geodesic distance rather than Euclidean distance. This results in more accurate measurement of pairwise relationships, resulting in more effective manifold information. Furthermore, NMFRC adopts rank constraint instead of norm constraints for regularization to balance the sparseness and smoothness of data. In this way, the new data representation is more representative and has better interpretability. Experiments on real data sets suggest that NMFRC outperforms four other state-of-the-art algorithms in terms of clustering accuracy.

Ranking important factors on information technology in development free zone markets: An AHP implementation

Directory of Open Access Journals (Sweden)

Yahya Rostamnya

2012-08-01

Full Text Available Information technology (IT plays a vital role on developing different markets. In this paper, we study the impact of IT on developing businesses located mainly on free zones or in the borders of countries using analytical hierarchy process. The proposed study of this paper gathered the relative importance of five important factors influencing IT implementation. There are 12 experts and we use pairwise comparison to gather their insight and using Expert Choice we implement AHP for ranking the factors. The results indicate that management is the most important factor, followed by cultural and social items. The other factors including technical, investment and organization items are in lower degree of importance.

Impact factor, eigenfactor, article influence, scopus SNIP, and SCImage journal rank of occupational therapy journals.

Science.gov (United States)

Brown, Ted; Gutman, Sharon A

2018-05-18

Journals are currently assessed and ranked using a number of different quantitative performance metrics. To compare and correlate the publication metrics of English-language occupational therapy journals published in 2015. Bibliometric data was sourced for 14 English-language occupational therapy journals including the Journal Citations Report (JCR) 2-year impact factor (IF), Eigenfactor Score (EFS), Article Influence Score (AIS), Scopus Source Normalized Impact per Paper (SNIP), Scopus Citescore, and SCImago Journal Rank (SJR) score. The JCR, Scopus, and SJR 2015 bibliometric data were correlated. The top six English-language occupational therapy journals in relation to JCR IF, EFS, AIS, SNIP, Citescore, SJR score, and SJR IIF were AJOT, AOTJ, POPT, CJOT, SJOT, and BJOT. JCR IF, EFS, JCR AIS, SNIP, Citescore, SJR score and SJR IIF were all significantly correlated with coefficients ranging from 0.751 to 0.961 (p article rankings rather than the singular use of IF scores that currently and frequently occurs in many jurisdictions.

Evaluating ranking methods on heterogeneous digital library collections

CERN Document Server

Canévet, Olivier; Marian, Ludmila; Chonavel, Thierry

In the frame of research in particle physics, CERN has been developing its own web-based software /Invenio/ to run the digital library of all the documents related to CERN and fundamental physics. The documents (articles, photos, news, thesis, ...) can be retrieved through a search engine. The results matching the query of the user can be displayed in several ways: sorted by latest first, author, title and also ranked by word similarity. The purpose of this project is to study and implement a new ranking method in Invenio: distributed-ranking (D-Rank). This method aims at aggregating several ranking scores coming from different ranking methods into a new score. In addition to query-related scores such as word similarity, the goal of the work is to take into account non-query-related scores such as citations, journal impact factor and in particular scores related to the document access frequency in the database. The idea is that for two equally query-relevant documents, if one has been more downloaded for inst...

Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures

KAUST Repository

Akbudak, Kadir; Ltaief, Hatem; Mikhalev, Aleksandr; Keyes, David E.

2017-01-01

Covariance matrices are ubiquitous in computational science and engineering. In particular, large covariance matrices arise from multivariate spatial data sets, for instance, in climate/weather modeling applications to improve prediction using statistical methods and spatial data. One of the most time-consuming computational steps consists in calculating the Cholesky factorization of the symmetric, positive-definite covariance matrix problem. The structure of such covariance matrices is also often data-sparse, in other words, effectively of low rank, though formally dense. While not typically globally of low rank, covariance matrices in which correlation decays with distance are nearly always hierarchically of low rank. While symmetry and positive definiteness should be, and nearly always are, exploited for performance purposes, exploiting low rank character in this context is very recent, and will be a key to solving these challenging problems at large-scale dimensions. The authors design a new and flexible tile row rank Cholesky factorization and propose a high performance implementation using OpenMP task-based programming model on various leading-edge manycore architectures. Performance comparisons and memory footprint saving on up to 200K×200K covariance matrix size show a gain of more than an order of magnitude for both metrics, against state-of-the-art open-source and vendor optimized numerical libraries, while preserving the numerical accuracy fidelity of the original model. This research represents an important milestone in enabling large-scale simulations for covariance-based scientific applications.

Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures

KAUST Repository

Akbudak, Kadir

2017-05-11

Covariance matrices are ubiquitous in computational science and engineering. In particular, large covariance matrices arise from multivariate spatial data sets, for instance, in climate/weather modeling applications to improve prediction using statistical methods and spatial data. One of the most time-consuming computational steps consists in calculating the Cholesky factorization of the symmetric, positive-definite covariance matrix problem. The structure of such covariance matrices is also often data-sparse, in other words, effectively of low rank, though formally dense. While not typically globally of low rank, covariance matrices in which correlation decays with distance are nearly always hierarchically of low rank. While symmetry and positive definiteness should be, and nearly always are, exploited for performance purposes, exploiting low rank character in this context is very recent, and will be a key to solving these challenging problems at large-scale dimensions. The authors design a new and flexible tile row rank Cholesky factorization and propose a high performance implementation using OpenMP task-based programming model on various leading-edge manycore architectures. Performance comparisons and memory footprint saving on up to 200K×200K covariance matrix size show a gain of more than an order of magnitude for both metrics, against state-of-the-art open-source and vendor optimized numerical libraries, while preserving the numerical accuracy fidelity of the original model. This research represents an important milestone in enabling large-scale simulations for covariance-based scientific applications.

RankExplorer: Visualization of Ranking Changes in Large Time Series Data.

Science.gov (United States)

Shi, Conglei; Cui, Weiwei; Liu, Shixia; Xu, Panpan; Chen, Wei; Qu, Huamin

2012-12-01

For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.

Identifying and Ranking the Factors Affecting Virtuousness in Yazd University-Affiliated Hospitals

Directory of Open Access Journals (Sweden)

H Shekari

2015-07-01

Conclusion: The results of ranking the factors of organizational virtuous showed that for moving toward virtuousness, the factors of ethical Culture, vision and Care for Community should be improvedby promoting ethics (Providing ethical standards for employee’s and manager’s behavior, Corporate Philanthropy, considering virtues in mission and vision etc. in mentioned hospitals.

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

RANK/RANK-Ligand/OPG: Ein neuer Therapieansatz in der Osteoporosebehandlung

Directory of Open Access Journals (Sweden)

Preisinger E

2007-01-01

Full Text Available Die Erforschung der Kopplungsmechanismen zur Osteoklastogenese, Knochenresorption und Remodellierung eröffnete neue mögliche Therapieansätze in der Behandlung der Osteoporose. Eine Schlüsselrolle beim Knochenabbau spielt der RANK- ("receptor activator of nuclear factor (NF- κB"- Ligand (RANKL. Durch die Bindung von RANKL an den Rezeptor RANK wird die Knochenresorption eingeleitet. OPG (Osteoprotegerin sowie der für den klinischen Gebrauch entwickelte humane monoklonale Antikörper (IgG2 Denosumab blockieren die Bindung von RANK-Ligand an RANK und verhindern den Knochenabbau.

Ranking the Online Documents Based on Relative Credibility Measures

Directory of Open Access Journals (Sweden)

Ahmad Dahlan

2013-09-01

Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

Ranking the Online Documents Based on Relative Credibility Measures

Directory of Open Access Journals (Sweden)

Ahmad Dahlan

2009-05-01

Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

Ranking adverse drug reactions with crowdsourcing.

Science.gov (United States)

Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel; Altman, Russ B

2015-03-23

There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. The intent of the study was to rank ADRs according to severity. We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

Ranking Adverse Drug Reactions With Crowdsourcing

KAUST Repository

Gottlieb, Assaf

2015-03-23

Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

Ranking factors affecting the packing of saffron from the perspective of consumers

Directory of Open Access Journals (Sweden)

Arash Dorandish

2017-06-01

Full Text Available Packaging is a tool for recognition and differentiation of product and it plays a crucial role in consumers' purchasing decisions, and it can be used to create competitive advantages. Saffron is one of the most important agricultural crops in Iran and its packaging in accordance with consumer demand increases sales and satisfaction of the consumers. Therefore, the main objective of this study is to rank the factors affecting the packaging from the perspective of consumers of saffron in Mashhad. Data was collected in the form of 99 questionnaires that have been answered by the consumers of saffron in Mashhad in 2015. Analytic hierarchy process (AHP was used to rank these factors. The results showed that labeling information about internal and international standards and saffron nutrients on the package have the greatest impact on consumer preferences. Also, the results of the ranking alternatives indicated that attention to the brand labelled on the packing is the most important issue from the perspective of the consumers. Hence, labelling information elements on the package can be a good way for brand differentiation and increasing its value. According to the results, it is recommended that producers and suppliers of saffron pay more attention to features and information elements in package design.

PageRank as a method to rank biomedical literature by importance.

Science.gov (United States)

Yates, Elliot J; Dixon, Louise C

2015-01-01

Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

Grooming up the hierarchy: the exchange of grooming and rank-related benefits in a new world primate.

Directory of Open Access Journals (Sweden)

Barbara Tiddi

Full Text Available Seyfarth's model assumes that female primates derive rank-related benefits from higher-ranking females in exchange for grooming. As a consequence, the model predicts females prefer high-ranking females as grooming partners and compete for the opportunity to groom them. Therefore, allogrooming is expected to be directed up the dominance hierarchy and to occur more often between females with adjacent ranks. Although data from Old World primates generally support the model, studies on the relation between grooming and dominance rank in the New World genus Cebus have found conflicting results, showing considerable variability across groups and species. In this study, we investigated the pattern of grooming in wild tufted capuchin females (Cebus apella nigritus in Iguazú National Park, Argentina by testing both the assumption (i.e., that females gain rank-related return benefits from grooming and predictions (i.e., that females direct grooming up the dominance hierarchy and the majority of grooming occurs between females with adjacent ranks of Seyfarth's model. Study subjects were 9 adult females belonging to a single group. Results showed that grooming was given in return for tolerance during naturally occurring feeding, a benefit that higher-ranking females can more easily grant. Female grooming was directed up the hierarchy and was given more often to partners with similar rank. These findings provide supporting evidence for both the assumption and predictions of Seyfarth's model and represent, more generally, the first evidence of reciprocal behavioural interchanges driven by rank-related benefits in New World female primates.

Grooming up the hierarchy: the exchange of grooming and rank-related benefits in a new world primate.

Science.gov (United States)

Tiddi, Barbara; Aureli, Filippo; Schino, Gabriele

2012-01-01

Seyfarth's model assumes that female primates derive rank-related benefits from higher-ranking females in exchange for grooming. As a consequence, the model predicts females prefer high-ranking females as grooming partners and compete for the opportunity to groom them. Therefore, allogrooming is expected to be directed up the dominance hierarchy and to occur more often between females with adjacent ranks. Although data from Old World primates generally support the model, studies on the relation between grooming and dominance rank in the New World genus Cebus have found conflicting results, showing considerable variability across groups and species. In this study, we investigated the pattern of grooming in wild tufted capuchin females (Cebus apella nigritus) in Iguazú National Park, Argentina by testing both the assumption (i.e., that females gain rank-related return benefits from grooming) and predictions (i.e., that females direct grooming up the dominance hierarchy and the majority of grooming occurs between females with adjacent ranks) of Seyfarth's model. Study subjects were 9 adult females belonging to a single group. Results showed that grooming was given in return for tolerance during naturally occurring feeding, a benefit that higher-ranking females can more easily grant. Female grooming was directed up the hierarchy and was given more often to partners with similar rank. These findings provide supporting evidence for both the assumption and predictions of Seyfarth's model and represent, more generally, the first evidence of reciprocal behavioural interchanges driven by rank-related benefits in New World female primates.

Identify and rank key factors influencing the adoption of cloud computing for a healthy Electronics

Directory of Open Access Journals (Sweden)

Javad Shukuhy

2015-02-01

Full Text Available Cloud computing as a new technology with Internet infrastructure and new approaches can be significant benefits in providing medical services electronically. Aplying this technology in E-Health requires consideration of various factors. The main objective of this study is to identify and rank the factors influencing the adoption of e-health cloud. Based on the Technology-Organization-Environment (TOE framework and Human-Organization-Technology fit (HOT-fit model, 16 sub-factors were identified in four major factors. With survey of 60 experts, academics and experts in health information technology and with the help of fuzzy analytic hierarchy process had ranked these sub-factors and factors. In the literature, considering newness this study, no internal or external study, have not alluded these number of criteria. The results show that when deciding to adopt cloud computing in E-Health, respectively, must be considered technological, human, organizational and environmental factors.

Hierarchical partial order ranking

International Nuclear Information System (INIS)

Carlsen, Lars

2008-01-01

Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

Ranking of factors determining potassium mass balance in bicarbonate haemodialysis.

Science.gov (United States)

Basile, Carlo; Libutti, Pasquale; Lisi, Piero; Teutonico, Annalisa; Vernaglione, Luigi; Casucci, Francesco; Lomonte, Carlo

2015-03-01

One of the most important pathogenetic factors involved in the onset of intradialysis arrhytmias is the alteration in electrolyte concentration, particularly potassium (K(+)). Two studies were performed: Study A was designed to investigate above all the isolated effect of the factor time t on intradialysis K(+) mass balance (K(+)MB): 11 stable prevalent Caucasian anuric patients underwent one standard (∼4 h) and one long-hour (∼8 h) bicarbonate haemodialysis (HD) session. The latter were pair-matched as far as the dialysate and blood volume processed (90 L) and volume of ultrafiltration are concerned. Study B was designed to identify and rank the other factors determining intradialysis K(+)MB: 63 stable prevalent Caucasian anuric patients underwent one 4-h standard bicarbonate HD session. Dialysate K(+) concentration was 2.0 mmol/L in both studies. Blood samples were obtained from the inlet blood tubing immediately before the onset of dialysis and at t60, t120, t180 min and at end of the 4- and 8-h sessions for the measurement of plasma K(+), blood bicarbonates and blood pH. Additional blood samples were obtained at t360 min for the 8 h sessions. Direct dialysate quantification was utilized for K(+)MBs. Direct potentiometry with an ion-selective electrode was used for K(+) measurements. Study A: mean K(+)MBs were significantly higher in the 8-h sessions (4 h: -88.4 ± 23.2 SD mmol versus 8 h: -101.9 ± 32.2 mmol; P = 0.02). Bivariate linear regression analyses showed that only mean plasma K(+), area under the curve (AUC) of the hourly inlet dialyser diffusion concentration gradient of K(+) (hcgAUCK(+)) and AUC of blood bicarbonates and mean blood bicarbonates were significantly related to K(+)MB in both 4- and 8-h sessions. A multiple linear regression output with K(+)MB as dependent variable showed that only mean plasma K(+), hcgAUCK(+) and duration of HD sessions per se remained statistically significant. Study B: mean K(+)MBs were -86.7 ± 22.6 mmol

An empirical investigation on ranking financial risk factors using AHP method

Directory of Open Access Journals (Sweden)

Hassan Ghodrati

2014-05-01

Full Text Available This paper determines and ranks financial risk factors in Iranian corporations, using analytical hierarchy process (AHP. The present research includes one main question and four sub- questions. Its universe population includes managers, production and financial personnel of great corporations activating in Tehran Stock Exchange, who were selected to explain importance and weight of economic risks indices. The source of great corporations recognition is the Companies Registration Organization in Tehran Province, and according to this, there are 120 corporations. The results have indicated that financing risk maintains the highest priority followed by credit risk, liquidity risk, inflation risk and exchange risk. In terms of different risks associated with financing risk, risk of profit per share has been the number one priority followed by the risk of divisional profit per share, the risk of recessionary or boom and the risk of increasing partial pay profit rate. In terms of credit risk, the risk of loan has been number one priority followed by the risk of inability of loan payment and interest payment. Liquidity risk is another risk factor where demand has been the most important factor followed by rules and regulations and inflation risk. In terms of inflation, producers price risk has been the most important factor followed by consumer price risk, gross domestic product and producers price risk. Finally, in terms of different factors influencing exchange risk, export related issues are considered as the most important factors.

Improved efficacy of soluble human receptor activator of nuclear factor kappa B (RANK) fusion protein by site-directed mutagenesis.

Science.gov (United States)

Son, Young Jun; Han, Jihye; Lee, Jae Yeon; Kim, HaHyung; Chun, Taehoon

2015-06-01

Soluble human receptor activator of nuclear factor kappa B fusion immunoglobulin (hRANK-Ig) has been considered as one of the therapeutic agents to treat osteoporosis or diseases associated with bone destruction by blocking the interaction between RANK and the receptor activator of nuclear factor kappa B ligand (RANKL). However, no scientific record showing critical amino acid residues within the structural interface between the human RANKL and RANK complex is yet available. In this study, we produced several mutants of hRANK-Ig by replacement of amino acid residue(s) and tested whether the mutants had increased binding affinity to human RANKL. Based on the results from flow cytometry and surface plasmon resonance analyses, the replacement of E(125) with D(125), or E(125) and C(127) with D(125) and F(127) within loop 3 of cysteine-rich domain 3 of hRANK-Ig increases binding affinity to human RANKL over the wild-type hRANK-Ig. This result may provide the first example of improvement in the efficacy of hRANK-Ig by protein engineering and may give additional information to understand a more defined structural interface between hRANK and RANKL.

Identifying and ranking the factors affecting entrepreneurial marketing to facilitate exports

Directory of Open Access Journals (Sweden)

Mehdi Habibzadeh

2016-04-01

Full Text Available Small and medium enterprises (SMEs are believed the most important components of today’s businesses and they can boost the growth of economy. This paper presents an empirical investigation to identify and rank important factors influencing on entrepreneurial marketing to facilitate exports of SMEs. The study designs a questionnaire in Likert scale and distributes it among 387 randomly selected entrepreneurs who act as managers of some SMEs in city of Tehran, Iran. Cronbach alpha is calculated as 0.873, which is well above the acceptable level. Using principle component analysis, the study has determined four factors including competitive intelligence, competitive advantage, external factors and internal factors to facilitate the export of SMEs.

Impact factor analysis: combining prediction with parameter ranking to reveal the impact of behavior on health outcome

DEFF Research Database (Denmark)

Doryab, Afsaneh; Frost, Mads; Faurholt-Jepsen, Maria

2015-01-01

An increasing number of healthcare systems allow people to monitor behavior and provide feedback on health and wellness. Most applications, however, only offer feedback on behavior in form of visualization and data summaries. This paper presents a different approach—called impact factor analysis—...... in monitoring and control of mental illness, and we argue that the impact factor analysis can be useful in the design of other health and wellness systems....... ten bipolar patients, in which we were able to estimate mood values with an average mean absolute error of 0.5. This was used to rank the behavior parameters whose variations indicate changes in the mental state. The rankings acquired from our algorithms correspond to the patients’ rankings......, identifying physical activity and sleep as the highest impact parameters. These results revealed the feasibility of identifying behavioral impact factors. This data analysis motivated us to design an impact factor inference engine as part of the MONARCA system. To our knowledge, this is a novel approach...

Occupational stress and cardiovascular risk factors in high-ranking government officials and office workers.

Science.gov (United States)

Mirmohammadi, Seyyed Jalil; Taheri, Mahmoud; Mehrparvar, Amir Houshang; Heydari, Mohammad; Saadati Kanafi, Ali; Mostaghaci, Mehrdad

2014-08-01

Cardiovascular diseases are among the most important sources of mortality and morbidity, and have a high disease burden. There are some major well-known risk factors, which contribute to the development of these diseases. Occupational stress is caused due to imbalance between job demands and individual's ability, and it has been implicated as an etiology for cardiovascular diseases. This study was conducted to evaluate the cardiovascular risk factors and different dimensions of occupational stress in high-ranking government officials, comparing an age and sex-matched group of office workers with them. We invited 90 high-ranking officials who managed the main governmental offices in a city, and 90 age and sex-matched office workers. The subjects were required to fill the occupational role questionnaire (Osipow) which evaluated their personal and medical history as well as occupational stress. Then, we performed physical examination and laboratory tests to check for cardiovascular risk factors. Finally, the frequency of cardiovascular risk factors and occupational stress of two groups were compared. High-ranking officials in our study had less work experience in their current jobs and smoked fewer pack-years of cigarette, but they had higher waist and hip circumference, higher triglyceride level, more stress from role overload and responsibility, and higher total stress score. Our group of office workers had more occupational stress because of role ambiguity and insufficiency, but their overall job stress was less than officials. The officials have higher scores in some dimensions of occupational stress and higher overall stress score. Some cardiovascular risk factors were also more frequent in managers.

Receptor activator of nuclear factor kappa B (RANK as a determinant of peri-implantitis

Directory of Open Access Journals (Sweden)

Rakić Mia

2013-01-01

Full Text Available Background/Aim. Peri-implantitis presents inflammatory process that affects soft and hard supporting tissues of osseointegrated implant based on inflammatory osteoclastogenesis. The aim of this study was to investigate whether receptor activator of nuclear factor kappa B (RANK concentrations in peri-implant crevicular fluid could be associated with clinical parameters that reflect inflammatory nature of peri-implantitis. Methods. The study included 67 patients, 22 with diagnosed peri-implantitis, 22 persons with healthy peri-implant tissues and 23 patients with periodontitis. Clinical parameters from each patient were recorded and samples of peri-implant/gingival crevicular fluid were collected for the enzyme-linked immunosorbent assay (ELISA analysis. Results. RANK concentration was significantly increased in samples from the patients with periimplantitis when compared to healthy implants (p < 0.0001, where the average levels were 9 times higher. At the same time RANK concentration was significantly higher in periimplantitis than in periodontitis sites (p < 0.0001. In implant patients pocket depths and bleeding on probing values were positively associated with high RANK concentrations (p < 0.0001. Conclusion. These results revealed association of increased RANK concentration in samples of periimplant/ gingival crevicular fluid with peri-implant inflammation and suggests that RANK could be a pathologic determinant of peri-implantitis, thereby a potential parameter in assessment of peri-implant tissue inflammation and a potential target in designing treatment strategies.

Generalized rank weights of reducible codes, optimal cases and related properties

DEFF Research Database (Denmark)

Martinez Peñas, Umberto

2018-01-01

in network coding. In this paper, we study their security behavior against information leakage on networks when applied as coset coding schemes, giving the following main results: 1) we give lower and upper bounds on their generalized rank weights (GRWs), which measure worst case information leakage...... to the wire tapper; 2) we find new parameters for which these codes are MRD (meaning that their first GRW is optimal) and use the previous bounds to estimate their higher GRWs; 3) we show that all linear (over the extension field) codes, whose GRWs are all optimal for fixed packet and code sizes but varying...... length are reducible codes up to rank equivalence; and 4) we show that the information leaked to a wire tapper when using reducible codes is often much less than the worst case given by their (optimal in some cases) GRWs. We conclude with some secondary related properties: conditions to be rank...

Ranking of Delay Factors for Makkah’s Construction Industry

Directory of Open Access Journals (Sweden)

Al-Emad Nashwan

2017-01-01

Full Text Available This paper presents identification of significant delay factors encountered by Makkah’s construction industry using quantitative approach. A structured questionnaire developed based on literature review was verified through pilot study involved selected construction experts. Questionnaire survey was conducted amongst Makkah construction practitioners include contractors, consultants and project management consultancy. The survey managed to collect 100 valid responses which were used to rank the factors using average index approach. Results of the analysis for 10 most significant factors causing construction delay in Makkah construction industry are Difficulties in financing project by contractor, Poor coordination between parties, Shortage of manpower, Delays in producing design documents, Improper planning and scheduling of the project, Delay in progress payments, Low productivity level of labour, Poor communication between parties, Unqualified workforce and Poor contract management. This finding is helpful to Makkah construction’s community particularly projects’ stakeholders in avoiding potential delay for their future projects.

Evaluation of the osteoclastogenic process associated with RANK / RANK-L / OPG in odontogenic myxomas

Science.gov (United States)

González-Galván, María del Carmen; Mosqueda-Taylor, Adalberto; Bologna-Molina, Ronell; Setien-Olarra, Amaia; Marichalar-Mendia, Xabier; Aguirre-Urizar, José-Manuel

2018-01-01

Background Odontogenic myxoma (OM) is a benign intraosseous neoplasm that exhibits local aggressiveness and high recurrence rates. Osteoclastogenesis is an important phenomenon in the tumor growth of maxillary neoplasms. RANK (Receptor Activator of Nuclear Factor κappa B) is the signaling receptor of RANK-L (Receptor activator of nuclear factor kappa-Β ligand) that activates the osteoclasts. OPG (osteoprotegerin) is a decoy receptor for RANK-L that inhibits pro-osteoclastogenesis. The RANK / RANKL / OPG system participates in the regulation of osteolytic activity under normal conditions, and its alteration has been associated with greater bone destruction, and also with tumor growth. Objectives To analyze the immunohistochemical expression of OPG, RANK and RANK-L proteins in odontogenic myxomas (OMs) and their relationship with the tumor size. Material and Methods Eighteen OMs, 4 small ( 3cm) and 18 dental follicles (DF) that were included as control were studied by means of standard immunohistochemical procedure with RANK, RANKL and OPG antibodies. For the evaluation, 5 fields (40x) of representative areas of OM and DF were selected where the expression of each antibody was determined. Descriptive and comparative statistical analyses were performed with the obtained data. Results There are significant differences in the expression of RANK in OM samples as compared to DF (p = 0.022) and among the OMSs and OMLs (p = 0.032). Also a strong association is recognized in the expression of RANK-L and OPG in OM samples. Conclusions Activation of the RANK / RANK-L / OPG triad seems to be involved in the mechanisms of bone balance and destruction, as well as associated with tumor growth in odontogenic myxomas. Key words:Odontogenic myxoma, dental follicle, RANK, RANK-L, OPG, osteoclastogenesis. PMID:29680857

Ranking nodes in growing networks: When PageRank fails.

Science.gov (United States)

Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

2015-11-10

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Effect of State-Specific Factors on Acquisition Path Ranking

International Nuclear Information System (INIS)

Vincze, A.; Nemeth, A.

2015-01-01

The ''directed graph analysis'' has been shown to be a promising methodology to implement acquisition path analysis by the IAEA to support the State evaluation process. Based on this methodology a material flow network model has been developed under the Hungarian Support Programme to the IAEA, in which materials in different chemical and physical form can flow through pipes representing declared processes, material transports, diversions or undeclared processes. The ranking of the resulting acquisition paths of the analysis is a key step to facilitate the determination of technical objectives and the planning of safeguards implementation on State-level. These are determined by the attributes of the processes included into the graph and different state-specific factors. In this paper different set of attributes, State-specific factors and their functional combination will be tested for hypothetical case studies. (author)

Relative Performance Information, Rank Ordering and Employee Performance: A Research Note

NARCIS (Netherlands)

Kramer, S.; Maas, V.S.; van Rinsum, M.

2016-01-01

We conduct a laboratory experiment to examine whether the provision of detailed relative performance information (i.e., information about the specific performance levels of peers) affects employee performance. We also investigate how – if at all – explicit ranking of performance levels affects how

Grooming Up the Hierarchy: The Exchange of Grooming and Rank-Related Benefits in a New World Primate

OpenAIRE

Tiddi, Barbara; Aureli, Filippo; Schino, Gabriele

2012-01-01

Seyfarth’s model assumes that female primates derive rank-related benefits from higher-ranking females in exchange for grooming. As a consequence, the model predicts females prefer high-ranking females as grooming partners and compete for the opportunity to groom them. Therefore, allogrooming is expected to be directed up the dominance hierarchy and to occur more often between females with adjacent ranks. Although data from Old World primates generally support the model, studies o...

Postprandial lipemia: factoring in lipemic response for ranking foods for their healthiness.

Science.gov (United States)

Dias, Cintia Botelho; Moughan, Paul J; Wood, Lisa G; Singh, Harjinder; Garg, Manohar L

2017-09-18

One of the limitations for ranking foods and meals for healthiness on the basis of the glycaemic index (GI) is that the GI is subject to manipulation by addition of fat. Postprandial lipemia, defined as a rise in circulating triglyceride containing lipoproteins following consumption of a meal, has been recognised as a risk factor for the development of cardiovascular disease and other chronic diseases. Many non-modifiable factors (pathological conditions, genetic background, age, sex and menopausal status) and life-style factors (physical activity, smoking, alcohol and medication use, dietary choices) may modulate postprandial lipemia. The structure and the composition of a food or a meal consumed also plays an important role in the rate of postprandial appearance and clearance of triglycerides in the blood. However, a major difficulty in grading foods, meals and diets according to their potential to elevate postprandial triglyceride levels has been the lack of a standardised marker that takes into consideration both the general characteristics of the food and the food's fat composition and quantity. The release rate of lipids from the food matrix during digestion also has an important role in determining the postprandial lipemic effects of a food product. This article reviews the factors that have been shown to influence postprandial lipemia with a view to develop a novel index for ranking foods according to their healthiness. This index should take into consideration not only the glycaemic but also lipemic responses.

Minkowski metrics in creating universal ranking algorithms

Directory of Open Access Journals (Sweden)

Andrzej Ameljańczyk

2014-06-01

Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

RANK and RANK ligand expression in primary human osteosarcoma

Directory of Open Access Journals (Sweden)

Daniel Branstetter

2015-09-01

Our results demonstrate RANKL expression was observed in the tumor element in 68% of human OS using IHC. However, the staining intensity was relatively low and only 37% (29/79 of samples exhibited≥10% RANKL positive tumor cells. RANK expression was not observed in OS tumor cells. In contrast, RANK expression was clearly observed in other cells within OS samples, including the myeloid osteoclast precursor compartment, osteoclasts and in giant osteoclast cells. The intensity and frequency of RANKL and RANK staining in OS samples were substantially less than that observed in GCTB samples. The observation that RANKL is expressed in OS cells themselves suggests that these tumors may mediate an osteoclastic response, and anti-RANKL therapy may potentially be protective against bone pathologies in OS. However, the absence of RANK expression in primary human OS cells suggests that any autocrine RANKL/RANK signaling in human OS tumor cells is not operative, and anti-RANKL therapy would not directly affect the tumor.

Ranking nodes in growing networks: When PageRank fails

Science.gov (United States)

Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

2015-11-01

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Country-specific determinants of world university rankings

OpenAIRE

Pietrucha, Jacek

2017-01-01

This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42–71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: econom...

Some relations between rank, chromatic number and energy of graphs

International Nuclear Information System (INIS)

Akbari, S.; Ghorbani, E.; Zare, S.

2006-08-01

The energy of a graph G is defined as the sum of the absolute values of all eigenvalues of G and denoted by E(G). Let G be a graph and rank(G) be the rank of the adjacency matrix of G. In this paper we characterize all the graphs with E(G) = rank(G). Among other results we show that apart from a few families of graphs, E(G) ≥ 2max(χ(G), n - χ(G--bar)), where G-bar and χ(G) are the complement and the chromatic number of G, respectively. Moreover some new lower bounds for E(G) in terms of rank(G) are given. (author)

Decomposing tensors with structured matrix factors reduces to rank-1 approximations

DEFF Research Database (Denmark)

Comon, Pierre; Sørensen, Mikael; Tsigaridas, Elias

2010-01-01

Tensor decompositions permit to estimate in a deterministic way the parameters in a multi-linear model. Applications have been already pointed out in antenna array processing and digital communications, among others, and are extremely attractive provided some diversity at the receiver is availabl....... As opposed to the widely used ALS algorithm, non-iterative algorithms are proposed in this paper to compute the required tensor decomposition into a sum of rank-1 terms, when some factor matrices enjoy some structure, such as block-Hankel, triangular, band, etc....

A Survey on PageRank Computing

OpenAIRE

Berkhin, Pavel

2005-01-01

This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much mor...

LANL environmental restoration site ranking system: System description. Final report

International Nuclear Information System (INIS)

Merkhofer, L.; Kann, A.; Voth, M.

1992-01-01

The basic structure of the LANL Environmental Restoration (ER) Site Ranking System and its use are described in this document. A related document, Instructions for Generating Inputs for the LANL ER Site Ranking System, contains detailed descriptions of the methods by which necessary inputs for the system will be generated. LANL has long recognized the need to provide a consistent basis for comparing the risks and other adverse consequences associated with the various waste problems at the Lab. The LANL ER Site Ranking System is being developed to help address this need. The specific purpose of the system is to help improve, defend, and explain prioritization decisions at the Potential Release Site (PRS) and Operable Unit (OU) level. The precise relationship of the Site Ranking System to the planning and overall budget processes is yet to be determined, as the system is still evolving. Generally speaking, the Site Ranking System will be used as a decision aid. That is, the system will be used to aid in the planning and budgetary decision-making process. It will never be used alone to make decisions. Like all models, the system can provide only a partial and approximate accounting of the factors important to budget and planning decisions. Decision makers at LANL will have to consider factors outside of the formal system when making final choices. Some of these other factors are regulatory requirements, DOE policy, and public concern. The main value of the site ranking system, therefore, is not the precise numbers it generates, but rather the general insights it provides

LANL environmental restoration site ranking system: System description. Final report

Energy Technology Data Exchange (ETDEWEB)

Merkhofer, L.; Kann, A.; Voth, M. [Applied Decision Analysis, Inc., Menlo Park, CA (United States)

1992-10-13

The basic structure of the LANL Environmental Restoration (ER) Site Ranking System and its use are described in this document. A related document, Instructions for Generating Inputs for the LANL ER Site Ranking System, contains detailed descriptions of the methods by which necessary inputs for the system will be generated. LANL has long recognized the need to provide a consistent basis for comparing the risks and other adverse consequences associated with the various waste problems at the Lab. The LANL ER Site Ranking System is being developed to help address this need. The specific purpose of the system is to help improve, defend, and explain prioritization decisions at the Potential Release Site (PRS) and Operable Unit (OU) level. The precise relationship of the Site Ranking System to the planning and overall budget processes is yet to be determined, as the system is still evolving. Generally speaking, the Site Ranking System will be used as a decision aid. That is, the system will be used to aid in the planning and budgetary decision-making process. It will never be used alone to make decisions. Like all models, the system can provide only a partial and approximate accounting of the factors important to budget and planning decisions. Decision makers at LANL will have to consider factors outside of the formal system when making final choices. Some of these other factors are regulatory requirements, DOE policy, and public concern. The main value of the site ranking system, therefore, is not the precise numbers it generates, but rather the general insights it provides.

Assessment of the relationship between the output of the educational systems and the assumed effective factors in Medical Education written in Data Banks and Ranking of Iran Medical Faculties book.

Science.gov (United States)

Mishmast Nehy, GhA

2015-01-01

Developing and expanding the universities and increasing the admission of medical students did resolve the physician shortage, but it brought down the educational quality in return. To face this problem, the administrates needed to promote the quality of education which in turn needed accurate up to date information about conditions in different universities. Information about these issues was collected by the Medical Education Council Secretariat and finally published as the Data Bank and Ranking of the Medical Faculties. Method: Although nowadays ranking is more qualitative rather than quantitative, the above ranking was done by a statistical method. In this research, the intended statistic population consisted of the data included in the database and the ranking of all 38 medical faculties. To perform this research, the ranking of faculties in the comprehensive entrance exam which indicated the input of educational system was considered the index at first, and later, the ranking of the faculties in the effective factors in education, was arranged according to the regulation of the input system; then outputs of the educational system were adjusted according to the input system and finally a comprehensive table of all the educational information was provided. Then, the relationship of various factors in education with outputs of educational system were discussed. Result: The correlations of each and all factors, which have an effective part on education were considered separately, collectively, and together, based on the information of the above book. No connection was detected within the factors, which affected the education and the output in different universities. The only relation notable was the admission degree and the outcomes of the national basic science exams. Since no meaningful connection was found within the present parameters, it seemed to be wrong to follow the path that the other sections of the world have taken in choosing the ranking factors.

Ranking Operations Management conferences

NARCIS (Netherlands)

Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

2007-01-01

Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

Inhibition of osteoclastogenesis by RNA interference targeting RANK

Directory of Open Access Journals (Sweden)

Ma Ruofan

2012-08-01

Full Text Available Abstract Background Osteoclasts and osteoblasts regulate bone resorption and formation to allow bone remodeling and homeostasis. The balance between bone resorption and formation is disturbed by abnormal recruitment of osteoclasts. Osteoclast differentiation is dependent on the receptor activator of nuclear factor NF-kappa B (RANK ligand (RANKL as well as the macrophage colony-stimulating factor (M-CSF. The RANKL/RANK system and RANK signaling induce osteoclast formation mediated by various cytokines. The RANK/RANKL pathway has been primarily implicated in metabolic, degenerative and neoplastic bone disorders or osteolysis. The central role of RANK/RANKL interaction in osteoclastogenesis makes RANK an attractive target for potential therapies in treatment of osteolysis. The purpose of this study was to assess the effect of inhibition of RANK expression in mouse bone marrow macrophages on osteoclast differentiation and bone resorption. Methods Three pairs of short hairpin RNAs (shRNA targeting RANK were designed and synthesized. The optimal shRNA was selected among three pairs of shRNAs by RANK expression analyzed by Western blot and Real-time PCR. We investigated suppression of osteoclastogenesis of mouse bone marrow macrophages (BMMs using the optimal shRNA by targeting RANK. Results Among the three shRANKs examined, shRANK-3 significantly suppressed [88.3%] the RANK expression (p Conclusions These findings suggest that retrovirus-mediated shRNA targeting RANK inhibits osteoclast differentiation and osteolysis. It may appear an attractive target for preventing osteolysis in humans with a potential clinical application.

Teaching in the States: Salary and beyond Rankings

Science.gov (United States)

Marchant, Gregory J.; McCreary, John J.

2018-01-01

This report investigates factors relevant to choosing locations conducive to both attainment and maintenance of a teaching career. In addition to salary and cost of living, the investigators compiled and ranked variables related to family, such as parental income and education, and differences in political structures that affect careers in…

Neophilia Ranking of Scientific Journals.

Science.gov (United States)

Packalen, Mikko; Bhattacharya, Jay

2017-01-01

The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)-these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work.

Statistical methods for ranking data

CERN Document Server

Alvo, Mayer

2014-01-01

This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

On the rank 1 convexity of stored energy functions of physically linear stress-strain relations

Czech Academy of Sciences Publication Activity Database

Šilhavý, Miroslav; Bertram, A.; Böhlke, T.

2007-01-01

Roč. 86, č. 3 (2007), s. 235-243 ISSN 0374-3535 Institutional research plan: CEZ:AV0Z10190503 Keywords : generalized linear elastic law s * generalized strain measures * rank 1 convexity Subject RIV: BA - General Mathematics Impact factor: 0.743, year: 2007

SRS: Site ranking system for hazardous chemical and radioactive waste

International Nuclear Information System (INIS)

Rechard, R.P.; Chu, M.S.Y.; Brown, S.L.

1988-05-01

This report describes the rationale and presents instructions for a site ranking system (SRS). SRS ranks hazardous chemical and radioactive waste sites by scoring important and readily available factors that influence risk to human health. Using SRS, sites can be ranked for purposes of detailed site investigations. SRS evaluates the relative risk as a combination of potentially exposed population, chemical toxicity, and potential exposure of release from a waste site; hence, SRS uses the same concepts found in a detailed assessment of health risk. Basing SRS on the concepts of risk assessment tends to reduce the distortion of results found in other ranking schemes. More importantly, a clear logic helps ensure the successful application of the ranking procedure and increases its versatility when modifications are necessary for unique situations. Although one can rank sites using a detailed risk assessment, it is potentially costly because of data and resources required. SRS is an efficient approach to provide an order-of-magnitude ranking, requiring only readily available data (often only descriptive) and hand calculations. Worksheets are included to make the system easier to understand and use. 88 refs., 19 figs., 58 tabs

Country-specific determinants of world university rankings.

Science.gov (United States)

Pietrucha, Jacek

2018-01-01

This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42-71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: economic potential of the country, research and development expenditure, long-term political stability (freedom from war, occupation, coups and major changes in the political system), and institutional variables, including government effectiveness.

Hitting the Rankings Jackpot

Science.gov (United States)

Chapman, David W.

2008-01-01

Recently, Samford University was ranked 27th in the nation in a report released by "Forbes" magazine. In this article, the author relates how the people working at Samford University were surprised at its ranking. Although Samford is the largest privately institution in Alabama, its distinguished academic achievements aren't even…

Ranking of psychosocial and traditional risk factors by importance for coronary heart disease

DEFF Research Database (Denmark)

Schnohr, Peter; Marott, Jacob L; Kristensen, Tage S.

2015-01-01

.001] and systolic blood pressure (≥160 mmHg or blood pressure medication vs. never smoker; HR 1.74; 95% CI, 1.43-2.11; P ...-statistics and net reclassification improvement. During the follow-up, 1731 non-fatal and fatal coronary events were registered. In men, the highest ranking risk factors for coronary heart disease were vital exhaustion [high vs. low; hazard ratio (HR) 2.36; 95% confidence interval (CI), 1.70-3.26; P

PageRank of integers

International Nuclear Information System (INIS)

Frahm, K M; Shepelyansky, D L; Chepelianskii, A D

2012-01-01

We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers. (paper)

Critical review of methods for risk ranking of food related hazards, based on risks for human health

DEFF Research Database (Denmark)

van der Fels-Klerx, H. J.; van Asselt, E. D.; Raley, M.

2018-01-01

This study aimed to critically review methods for ranking risks related to food safety and dietary hazards on the basis of their anticipated human health impacts. A literature review was performed to identify and characterize methods for risk ranking from the fields of food, environmental science......, and the risk ranking method characterized. The methods were then clustered - based on their characteristics - into eleven method categories. These categories included: risk assessment, comparative risk assessment, risk ratio method, scoring method, cost of illness, health adjusted life years, multi......-criteria decision analysis, risk matrix, flow charts/decision trees, stated preference techniques and expert synthesis. Method categories were described by their characteristics, weaknesses and strengths, data resources, and fields of applications. It was concluded there is no single best method for risk ranking...

Factors affecting residency rank-listing: A Maxdiff survey of graduating Canadian medical students

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Forgie Melissa

2011-08-01

Full Text Available Abstract Background In Canada, graduating medical students consider many factors, including geographic, social, and academic, when ranking residency programs through the Canadian Residency Matching Service (CaRMS. The relative significance of these factors is poorly studied in Canada. It is also unknown how students differentiate between their top program choices. This survey study addresses the influence of various factors on applicant decision making. Methods Graduating medical students from all six Ontario medical schools were invited to participate in an online survey available for three weeks prior to the CaRMS match day in 2010. Max-Diff discrete choice scaling, multiple choice, and drop-list style questions were employed. The Max-Diff data was analyzed using a scaled simple count method. Data for how students distinguish between top programs was analyzed as percentages. Comparisons were made between male and female applicants as well as between family medicine and specialist applicants; statistical significance was determined by the Mann-Whitney test. Results In total, 339 of 819 (41.4% eligible students responded. The variety of clinical experiences and resident morale were weighed heavily in choosing a residency program; whereas financial incentives and parental leave attitudes had low influence. Major reasons that applicants selected their first choice program over their second choice included the distance to relatives and desirability of the city. Both genders had similar priorities when selecting programs. Family medicine applicants rated the variety of clinical experiences more importantly; whereas specialty applicants emphasized academic factors more. Conclusions Graduating medical students consider program characteristics such as the variety of clinical experiences and resident morale heavily in terms of overall priority. However, differentiation between their top two choice programs is often dependent on social/geographic factors

Class A scavenger receptor promotes osteoclast differentiation via the enhanced expression of receptor activator of NF-{kappa}B (RANK)

Energy Technology Data Exchange (ETDEWEB)

Takemura, Kenichi [Department of Cell Pathology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto 860-8556 (Japan); Department of Orthopaedic and Neuro-Musculoskeletal Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto (Japan); Sakashita, Naomi; Fujiwara, Yukio; Komohara, Yoshihiro; Lei, XiaoFeng; Ohnishi, Koji [Department of Cell Pathology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto 860-8556 (Japan); Suzuki, Hiroshi [National Research Center for Protozoan Diseases, Obihiro University of Agriculture and Veterinary Medicine, Hokkaido (Japan); Kodama, Tatsuhiko [Department of Molecular Biology and Medicine, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo (Japan); Mizuta, Hiroshi [Department of Orthopaedic and Neuro-Musculoskeletal Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto (Japan); Takeya, Motohiro, E-mail: takeya@kumamoto-u.ac.jp [Department of Cell Pathology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto 860-8556 (Japan)

2010-01-22

Osteoclasts originate from bone marrow monocyte/macrophage lineage cells, and their differentiation depends on macrophage colony-stimulating factor (M-CSF) and receptor activator nuclear factor kappa B (RANK) ligand. Class A scavenger receptor (SR-A) is one of the principal functional molecules of macrophages, and its level of expression declines during osteoclast differentiation. To investigate the role of SR-A in osteoclastogenesis, we examined pathological changes in femoral bone and the expression levels of osteoclastogenesis-related molecules in SR-A{sup -/-} mice. The femoral osseous density of SR-A{sup -/-} mice was higher than that of SR-A{sup +/+} mice, and the number of multinucleated osteoclasts was significantly decreased. An in vitro differentiation assay revealed that the differentiation of multinucleated osteoclasts from bone marrow-derived progenitor cells is impaired in SR-A{sup -/-} mice. Elimination of SR-A did not alter the expression level of the M-CSF receptor, c-fms; however, the expression levels of RANK and RANK-related osteoclast-differentiation molecules such as nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 1 (NFATc1) and microphthalmia-associated transcription factor (MITF) significantly decreased. Furthermore, acetylated low-density lipoprotein (AcLDL), an SR-A ligand, significantly increased the expression level of RANK and MITF during osteoclast differentiation. These data indicate that SR-A promotes osteoclastogenesis via augmentation of the expression level of RANK and its related molecules.

Social class rank, threat vigilance, and hostile reactivity.

Science.gov (United States)

Kraus, Michael W; Horberg, E J; Goetz, Jennifer L; Keltner, Dacher

2011-10-01

Lower-class individuals, because of their lower rank in society, are theorized to be more vigilant to social threats relative to their high-ranking upper-class counterparts. This class-related vigilance to threat, the authors predicted, would shape the emotional content of social interactions in systematic ways. In Study 1, participants engaged in a teasing interaction with a close friend. Lower-class participants--measured in terms of social class rank in society and within the friendship--more accurately tracked the hostile emotions of their friend. As a result, lower-class individuals experienced more hostile emotion contagion relative to upper-class participants. In Study 2, lower-class participants manipulated to experience lower subjective socioeconomic rank showed more hostile reactivity to ambiguous social scenarios relative to upper-class participants and to lower-class participants experiencing elevated socioeconomic rank. The results suggest that class affects expectations, perception, and experience of hostile emotion, particularly in situations in which lower-class individuals perceive their subordinate rank.

Rank Dynamics

Science.gov (United States)

Gershenson, Carlos

Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

Distant Supervision for Relation Extraction with Ranking-Based Methods

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Yang Xiang

2016-05-01

Full Text Available Relation extraction has benefited from distant supervision in recent years with the development of natural language processing techniques and data explosion. However, distant supervision is still greatly limited by the quality of training data, due to its natural motivation for greatly reducing the heavy cost of data annotation. In this paper, we construct an architecture called MIML-sort (Multi-instance Multi-label Learning with Sorting Strategies, which is built on the famous MIML framework. Based on MIML-sort, we propose three ranking-based methods for sample selection with which we identify relation extractors from a subset of the training data. Experiments are set up on the KBP (Knowledge Base Propagation corpus, one of the benchmark datasets for distant supervision, which is large and noisy. Compared with previous work, the proposed methods produce considerably better results. Furthermore, the three methods together achieve the best F1 on the official testing set, with an optimal enhancement of F1 from 27.3% to 29.98%.

PageRank without hyperlinks: Reranking with PubMed related article networks for biomedical text retrieval

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Lin Jimmy

2008-06-01

Full Text Available Abstract Background Graph analysis algorithms such as PageRank and HITS have been successful in Web environments because they are able to extract important inter-document relationships from manually-created hyperlinks. We consider the application of these techniques to biomedical text retrieval. In the current PubMed® search interface, a MEDLINE® citation is connected to a number of related citations, which are in turn connected to other citations. Thus, a MEDLINE record represents a node in a vast content-similarity network. This article explores the hypothesis that these networks can be exploited for text retrieval, in the same manner as hyperlink graphs on the Web. Results We conducted a number of reranking experiments using the TREC 2005 genomics track test collection in which scores extracted from PageRank and HITS analysis were combined with scores returned by an off-the-shelf retrieval engine. Experiments demonstrate that incorporating PageRank scores yields significant improvements in terms of standard ranked-retrieval metrics. Conclusion The link structure of content-similarity networks can be exploited to improve the effectiveness of information retrieval systems. These results generalize the applicability of graph analysis algorithms to text retrieval in the biomedical domain.

PageRank without hyperlinks: reranking with PubMed related article networks for biomedical text retrieval.

Science.gov (United States)

Lin, Jimmy

2008-06-06

Graph analysis algorithms such as PageRank and HITS have been successful in Web environments because they are able to extract important inter-document relationships from manually-created hyperlinks. We consider the application of these techniques to biomedical text retrieval. In the current PubMed(R) search interface, a MEDLINE(R) citation is connected to a number of related citations, which are in turn connected to other citations. Thus, a MEDLINE record represents a node in a vast content-similarity network. This article explores the hypothesis that these networks can be exploited for text retrieval, in the same manner as hyperlink graphs on the Web. We conducted a number of reranking experiments using the TREC 2005 genomics track test collection in which scores extracted from PageRank and HITS analysis were combined with scores returned by an off-the-shelf retrieval engine. Experiments demonstrate that incorporating PageRank scores yields significant improvements in terms of standard ranked-retrieval metrics. The link structure of content-similarity networks can be exploited to improve the effectiveness of information retrieval systems. These results generalize the applicability of graph analysis algorithms to text retrieval in the biomedical domain.

Some p-ranks related to orthogonal spaces

NARCIS (Netherlands)

Blokhuis, A.; Moorhouse, G.E.

1995-01-01

We determine the p-rank of the incidence matrix of hyperplanes of PG(n, p e) and points of a nondegenerate quadric. This yields new bounds for ovoids and the size of caps in finite orthogonal spaces. In particular, we show the nonexistence of ovoids in O10+ (2e ),O10+ (3e ),O9 (5e ),O12+ (5e

Discovering author impact: A PageRank perspective

OpenAIRE

Yan, Erjia; Ding, Ying

2010-01-01

This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International So...

PageRank tracker: from ranking to tracking.

Science.gov (United States)

Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

2014-06-01

Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

On the ranking of chemicals based on their PBT characteristics: comparison of different ranking methodologies using selected POPs as an illustrative example.

Science.gov (United States)

Sailaukhanuly, Yerbolat; Zhakupbekova, Arai; Amutova, Farida; Carlsen, Lars

2013-01-01

Knowledge of the environmental behavior of chemicals is a fundamental part of the risk assessment process. The present paper discusses various methods of ranking of a series of persistent organic pollutants (POPs) according to the persistence, bioaccumulation and toxicity (PBT) characteristics. Traditionally ranking has been done as an absolute (total) ranking applying various multicriteria data analysis methods like simple additive ranking (SAR) or various utility functions (UFs) based rankings. An attractive alternative to these ranking methodologies appears to be partial order ranking (POR). The present paper compares different ranking methods like SAR, UF and POR. Significant discrepancies between the rankings are noted and it is concluded that partial order ranking, as a method without any pre-assumptions concerning possible relation between the single parameters, appears as the most attractive ranking methodology. In addition to the initial ranking partial order methodology offers a wide variety of analytical tools to elucidate the interplay between the objects to be ranked and the ranking parameters. In the present study is included an analysis of the relative importance of the single P, B and T parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Relative Ranking Approach for Nano-Enabled Applications to Improve Risk-Based Decision Making: A Case Study of Army Materiel

Science.gov (United States)

2014-12-24

accidental expo- sures to carbon nanotubes and copper flakes incorporated into energy and obscurant materiel by Army workers rank highest relative to...that inhalation from accidental exposures to carbon nanotubes and copper flakes incorporated into energy and obscurant materiel by Army workers rank... copper (Cu), and titanium (Ti) flakes used in smokes and obscurants ranked the highest on the risk scale for sce- narios primarily involving accidental

Analysis and research of influence factors ranking of fuzzy language translation accuracy in literary works based on catastrophe progression method

Directory of Open Access Journals (Sweden)

Wei Dong

2017-02-01

Full Text Available This paper researches the problem of decline in translation accuracy caused by language “vagueness” in literary translation, and proposes to use the catastrophe model for importance ranking of various factors affecting the fuzzy language translation accuracy in literary works, and finally gives out the order of factors to be considered before translation. The multi-level evaluation system can be used to construct the relevant catastrophe progression model, and the normalization formula can be used to calculate the relative membership degree of each system and evaluation index, and make evaluation combined with the evaluation criteria table. The results show that, in the fuzzy language translation, in order to improve the translation accuracy, there is a need to consider the indicators ranking: A2 fuzzy language context → A1 words attribute → A3 specific meaning of digital words; B2 fuzzy semantics, B3 blur color words → B1 multiple meanings of words → B4 fuzzy digital words; C3 combination with context and cultural background, C4 specific connotation of color words → C1 combination with words emotion, C2 selection of words meaning → C5 combination with digits and language background.

Simpson's Paradox and Confounding Factors in University Rankings: A Demonstration Using QS 2011-12 Data

Science.gov (United States)

Soh, Kay Cheng

2012-01-01

University ranking has become ritualistic in higher education. Ranking results are taken as bona fide by rank users. Ranking systems usually use large data sets from highly heterogeneous universities of varied backgrounds. This poses the problem of Simpson's Paradox and the lurking variables causing it. Using QS 2011-2012 Ranking data, the dual…

Efficient Tensor Completion for Color Image and Video Recovery: Low-Rank Tensor Train.

Science.gov (United States)

Bengua, Johann A; Phien, Ho N; Tuan, Hoang Duong; Do, Minh N

2017-05-01

This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its definition from a well-balanced matricization scheme. Accordingly, new optimization formulations for tensor completion are proposed as well as two new algorithms for their solution. The first one called simple low-rank tensor completion via TT (SiLRTC-TT) is intimately related to minimizing a nuclear norm based on TT rank. The second one is from a multilinear matrix factorization model to approximate the TT rank of a tensor, and is called tensor completion by parallel matrix factorization via TT (TMac-TT). A tensor augmentation scheme of transforming a low-order tensor to higher orders is also proposed to enhance the effectiveness of SiLRTC-TT and TMac-TT. Simulation results for color image and video recovery show the clear advantage of our method over all other methods.

RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

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Bouchra Sojod

2017-05-01

Full Text Available Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases.

RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

Science.gov (United States)

Sojod, Bouchra; Chateau, Danielle; Mueller, Christopher G.; Babajko, Sylvie; Berdal, Ariane; Lézot, Frédéric; Castaneda, Beatriz

2017-01-01

Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg) and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases. PMID:28596739

Low-rank matrix approximation with manifold regularization.

Science.gov (United States)

Zhang, Zhenyue; Zhao, Keke

2013-07-01

This paper proposes a new model of low-rank matrix factorization that incorporates manifold regularization to the matrix factorization. Superior to the graph-regularized nonnegative matrix factorization, this new regularization model has globally optimal and closed-form solutions. A direct algorithm (for data with small number of points) and an alternate iterative algorithm with inexact inner iteration (for large scale data) are proposed to solve the new model. A convergence analysis establishes the global convergence of the iterative algorithm. The efficiency and precision of the algorithm are demonstrated numerically through applications to six real-world datasets on clustering and classification. Performance comparison with existing algorithms shows the effectiveness of the proposed method for low-rank factorization in general.

The structure of completely positive matrices according to their CP-rank and CP-plus-rank

NARCIS (Netherlands)

Dickinson, Peter James Clair; Bomze, Immanuel M.; Still, Georg J.

2015-01-01

We study the topological properties of the cp-rank operator $\\mathrm{cp}(A)$ and the related cp-plus-rank operator $\\mathrm{cp}^+(A)$ (which is introduced in this paper) in the set $\\mathcal{S}^n$ of symmetric $n\\times n$-matrices. For the set of completely positive matrices, $\\mathcal{CP}^n$, we

Most Important Factors for the Implementation of Shared Decision Making in Sciatica Care: Ranking among Professionals and Patients

Science.gov (United States)

Hofstede, Stefanie N.; van Bodegom-Vos, Leti; Wentink, Manon M.; Vleggeert-Lankamp, Carmen L. A.; Vliet Vlieland, Thea P. M.; de Mheen, Perla J. Marang-van

2014-01-01

Introduction Due to the increasing specialization of medical professionals, patients are treated by multiple disciplines. To ensure that delivered care is patient-centered, it is crucial that professionals and the patient together decide on treatment (shared decision making (SDM)). However, it is not known how SDM should be integrated in multidisciplinary practice. This study determines the most important factors for SDM implementation in sciatica care, as it is known that a prior inventory of factors is crucial to develop a successful implementation strategy. Methods 246 professionals (general practitioners, physical therapists, neurologists, neurosurgeons, orthopedic surgeons) (30% response) and 155 patients (96% response) responded to an internet-based survey. Respondents ranked barriers and facilitators identified in previous interviews, on their importance using Maximum Difference Scaling. Feeding back the personal top 5 most important factors, each respondent indicated whether these factors were barriers or facilitators. Hierarchical Bayes estimation was used to estimate the relative importance (RI) of each factor. Results Professionals assigned the highest importance to: quality of professional-patient relationship (RI 4.87; CI 4.75–4.99); importance of quick recovery of patient (RI 4.83; CI 4.69–4.97); and knowledge about treatment options (RI 6.64; CI 4.53–4.74), which were reported as barrier and facilitator. Professionals working in primary care had a different ranking than those working in hospital care. Patients assigned the highest importance to: correct diagnosis by professionals (barrier, RI 8.19; CI 7.99–8.38); information provision about treatment options and potential harm and benefits (RI 7.87; CI 7.65–8.08); and explanation of the professional about the care trajectory (RI 7.16; CI 6.94–7.38), which were reported as barrier and facilitator. Conclusions Knowledge, information provision and a good relationship are the most important

Identification and ranking of the risk factors of cloud computing in State-Owned organizations

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Noor Mohammad Yaghoubi

2015-05-01

Full Text Available Rapid development of processing and storage technologies and the success of the Internet have made computing resources cheaper, more powerful and more available than before. This technological trend has enabled the realization of a new computing model called cloud computing. Recently, the State-Owned organizations have begun to utilize cloud computing architectures, platforms, and applications to deliver services and meet constituents’ needs. Despite all of the advantages and opportunities of cloud computing technology, there are so many risks that State-Owned organizations need to know about before their migration to cloud environment. The purpose of this study is to identify and rank the risks factors of cloud computing in State-Owned organizations by making use of IT experts’ opinion. Firstly, by reviewing key articles, a comprehensive list of risks factors were extracted and classified into two categories: tangible and intangible. Then, six experts were interviewed about these risks and their classifications, and 10 risks were identified. After that, process of ranking the risks was done by seeking help from 52 experts and by fuzzy analytic hierarchy process. The results show that experts have identified intangible risks as the most important risks in cloud computing usage by State-Owned organizations. As the results indicate, "data confidentiality" risk has the highest place among the other risks.

Ranking system for mixed radioactive and hazardous waste sites

International Nuclear Information System (INIS)

Hawley, K.A.; Napier, B.A.

1985-01-01

The Environmental Protection Agency's Hazard Ranking System (HRS) is a simplified management decision tool that provides a common basis for evaluating a multitude of hazardous waste sites. A deficiency in the HRS for application to Department of Energy mixed radioactive and hazardous waste sites is its inability to explicitly handle radioactive material. A modification to the basic HRS to add the capability to consider radioactivity is described. The HRS considers the exposure routes of direct contact, fire/explosion, atmospheric release, surface-water release, and ground-water release. Each exposure route is further divided into release, route, containment, waste, and target characteristics. To maintain the basic HRS structure, only the waste characteristics section of each exposure route was modified. A ranking system was developed, using radiation dose pathway analysis, to group radionuclides by dose factors. For mixed waste sites, the ranking factor derived for radionuclides is compared with the ranking factor obtained for hazardous chemicals and the most restrictive is used in the overall ranking. The modified HRS has the advantages of being compatible with the original HRS, has reasonable information requirements, and provides scientifically defensible conclusions. 17 references, 2 figures, 6 tables

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

International Nuclear Information System (INIS)

Eliazar, Iddo

2015-01-01

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

2015-04-15

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars.

Probabilistic low-rank factorization accelerates tensor network simulations of critical quantum many-body ground states

Science.gov (United States)

Kohn, Lucas; Tschirsich, Ferdinand; Keck, Maximilian; Plenio, Martin B.; Tamascelli, Dario; Montangero, Simone

2018-01-01

We provide evidence that randomized low-rank factorization is a powerful tool for the determination of the ground-state properties of low-dimensional lattice Hamiltonians through tensor network techniques. In particular, we show that randomized matrix factorization outperforms truncated singular value decomposition based on state-of-the-art deterministic routines in time-evolving block decimation (TEBD)- and density matrix renormalization group (DMRG)-style simulations, even when the system under study gets close to a phase transition: We report linear speedups in the bond or local dimension of up to 24 times in quasi-two-dimensional cylindrical systems.

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

Directory of Open Access Journals (Sweden)

Licamele Louis

2010-03-01

Full Text Available Abstract Background There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights. Results In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries. Conclusions We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public. We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related cell types. Even in the absence of a known (i.e., labeled experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.

Ranking Journals Using Social Choice Theory Methods: A Novel Approach in Bibliometrics

Energy Technology Data Exchange (ETDEWEB)

Aleskerov, F.T.; Pislyakov, V.; Subochev, A.N.

2016-07-01

We use data on economic, management and political science journals to produce quantitative estimates of (in)consistency of evaluations based on seven popular bibliometric indica (impact factor, 5-year impact factor, immediacy index, article influence score, h-index, SNIP and SJR). We propose a new approach to aggregating journal rankings: since rank aggregation is a multicriteria decision problem, ordinal ranking methods from social choice theory may solve it. We apply either a direct ranking method based on majority rule (the Copeland rule, the Markovian method) or a sorting procedure based on a tournament solution, such as the uncovered set and the minimal externally stable set. We demonstrate that aggregate rankings reduce the number of contradictions and represent the set of single-indicator-based rankings better than any of the seven rankings themselves. (Author)

Quantitative Analysis of Mixtures of Monoprotic Acids Applying Modified Model-Based Rank Annihilation Factor Analysis on Variation Matrices of Spectrophotometric Acid-Base Titrations

Directory of Open Access Journals (Sweden)

Ebrahim Ghorbani-Kalhor

2015-04-01

Full Text Available In the current work, a new version of rank annihilation factor analysis was developedto circumvent the rank deficiency problem in multivariate data measurements.Simultaneous determination of dissociation constant and concentration of monoprotic acids was performed by applying model-based rank annihilation factor analysis on variation matrices of spectrophotometric acid-base titrations data. Variation matrices can be obtained by subtracting first row of data matrix from all rows of the main data matrix. This method uses variation matrices instead of multivariate spectrophotometric acid-base titrations matrices to circumvent the rank deficiency problem in the rank quantitation step. The applicability of this approach was evaluated by simulated data at first stage, then the binary mixtures of ascorbic and sorbic acids as model compounds were investigated by the proposed method. At the end, the proposed method was successfully applied for resolving the ascorbic and sorbic acid in an orange juice real sample. Therefore, unique results were achieved by applying rank annihilation factor analysis on variation matrix and using hard soft model combination advantage without any problem and difficulty in rank determination. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-bidi-language:AR-SA;}    

Validating rankings in soccer championships

Directory of Open Access Journals (Sweden)

Annibal Parracho Sant'Anna

2012-08-01

Full Text Available The final ranking of a championship is determined by quality attributes combined with other factors which should be filtered out of any decision on relegation or draft for upper level tournaments. Factors like referees' mistakes and difficulty of certain matches due to its accidental importance to the opponents should have their influence reduced. This work tests approaches to combine classification rules considering the imprecision of the number of points as a measure of quality and of the variables that provide reliable explanation for it. Two home-advantage variables are tested and shown to be apt to enter as explanatory variables. Independence between the criteria is checked against the hypothesis of maximal correlation. The importance of factors and of composition rules is evaluated on the basis of correlation between rank vectors, number of classes and number of clubs in tail classes. Data from five years of the Brazilian Soccer Championship are analyzed.

RANKING RELATIONS USING ANALOGIES IN BIOLOGICAL AND INFORMATION NETWORKS1

Science.gov (United States)

Silva, Ricardo; Heller, Katherine; Ghahramani, Zoubin; Airoldi, Edoardo M.

2013-01-01

Analogical reasoning depends fundamentally on the ability to learn and generalize about relations between objects. We develop an approach to relational learning which, given a set of pairs of objects S = {A(1) : B(1), A(2) : B(2), …, A(N) : B(N)}, measures how well other pairs A : B fit in with the set S. Our work addresses the following question: is the relation between objects A and B analogous to those relations found in S? Such questions are particularly relevant in information retrieval, where an investigator might want to search for analogous pairs of objects that match the query set of interest. There are many ways in which objects can be related, making the task of measuring analogies very challenging. Our approach combines a similarity measure on function spaces with Bayesian analysis to produce a ranking. It requires data containing features of the objects of interest and a link matrix specifying which relationships exist; no further attributes of such relationships are necessary. We illustrate the potential of our method on text analysis and information networks. An application on discovering functional interactions between pairs of proteins is discussed in detail, where we show that our approach can work in practice even if a small set of protein pairs is provided. PMID:24587838

Comparison Between Impact Factor, Eigenfactor Metrics, and SCimago Journal Rank Indicator of Pediatric Neurology Journals

OpenAIRE

Kianifar, Hamidreza; Sadeghi, Ramin; Zarifmahmoudi, Leili

2014-01-01

Background: Impact Factor (IF) as a major journal quality indicator has a series of shortcomings including effect of self-citation, review articles, total number of articles, etc. In this study, we compared 4 journals quality indices ((IF), Eigenfactor Score (ES), Article Influence Score (AIS) and SCImago Journal Rank indicator (SJR)) in the specific Pediatric Neurology journals. Methods: All ISI and Scopus indexed specific Pediatric Neurology journals were compared regarding their 2011 IF, E...

Scalable Faceted Ranking in Tagging Systems

Science.gov (United States)

Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

Ranking structures and rank-rank correlations of countries: The FIFA and UEFA cases

Science.gov (United States)

Ausloos, Marcel; Cloots, Rudi; Gadomski, Adam; Vitanov, Nikolay K.

2014-04-01

Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures in both cases.

Ranking factors of an investment in cogeneration: sensitivity analysis ranking the technical and economical factors

International Nuclear Information System (INIS)

Sundberg, Gunnel

2001-01-01

A deregulation of the electricity market in Europe will result in increased competition among the power-producing companies. They will therefore carefully estimate the financial risk in an investment in new power-producing capability. One part of the risk assessment is to perform a sensitivity analysis. This paper presents a sensitivity analysis using factorial design, resulting in an assessment of the most important technical and economical factors affecting an investment in gas turbine combined cycle and a steam cycle fired by wood chips. The study is performed using a simulation model that optimises the operation of existing power plants and potential new investments to fulfil the desired heat demand. The local utility system analysed is a Swedish district heating system with 655 GWh y -1 heat demand. The conclusion is that to understand which of the technical and economical factors affect the investment, it is not sufficient to investigate the parameters of the studied plant, but also the parameters related to the competing plants. Both the individual effects of the factors and the effect of their interaction should be investigated. For the energy system studied the price of natural gas, price of wood chips and investment cost have the major influence on the profitability of the investment. (Author)

Comparing classical and quantum PageRanks

Science.gov (United States)

Loke, T.; Tang, J. W.; Rodriguez, J.; Small, M.; Wang, J. B.

2017-01-01

Following recent developments in quantum PageRanking, we present a comparative analysis of discrete-time and continuous-time quantum-walk-based PageRank algorithms. Relative to classical PageRank and to different extents, the quantum measures better highlight secondary hubs and resolve ranking degeneracy among peripheral nodes for all networks we studied in this paper. For the discrete-time case, we investigated the periodic nature of the walker's probability distribution for a wide range of networks and found that the dominant period does not grow with the size of these networks. Based on this observation, we introduce a new quantum measure using the maximum probabilities of the associated walker during the first couple of periods. This is particularly important, since it leads to a quantum PageRanking scheme that is scalable with respect to network size.

Priority ranking of safety-related systems for structural assessment at Savannah River Site

International Nuclear Information System (INIS)

Kao, G.C.; Daugherty, W.L.; Barnes, D.M.

1993-01-01

In order to extend the service life of safety related structures and systems in a logical manner, a Structural Enhancement Program was initiated to evaluate the structural integrity of eight systems, namely: cooling water system, emergency cooling system, moderator recovery system, supplementary safety system, water removal system, service raw water system, service clarified water system, and river water system. Since the level of importance of each system to reactor operations varies from one system to another, the scope of structural integrity evaluation for each system should be prioritized accordingly. This paper presents the assessment of system priority for structural evaluation based on a ranking methodology and specifies the level of structural evaluation consistent with the established priority. The effort was undertaken by a five-member panel representing four major disciplines, including: structures, reactor engineering/operations, risk management, and materials. The above systems were divided into a total of thirty-five subsystems. These subsystems were then ranked with six attributes, namely: safety classification, degradation mechanisms, difficulty of replacement, failure mode, radiation dose to workers, and consequence of failure. Each attribute was assigned a set of consequences or events with corresponding weighting scores. The results of the ranking process yielded two groups of subsystems, categorized as Priority I and II subsystems. The level of structural assessment was then formulated accordingly. The prioritized approach will allow more efficient allocation of resources, so that the Structural Enhancement Program can be implemented in a cost-effective and efficient manner

Recognition and Ranking Critical Success Factors of Business Intelligence in Hospitals -- Case Study: Hasheminejad Hospital

OpenAIRE

Naderinejad, Marjan; Tarokh, Mohammad Jafar; Poorebrahimi, Alireza

2014-01-01

Business Intelligence, not as a tool of a product but as a new approach is propounded in organizations to make tough decisions in business as shortly as possible. Hospital managers often need business intelligence in their fiscal, operational, and clinical reports and indices. The main goal of recognition and ranking CSF is implementation of a business intelligent system in hospitals to increase success factor of application of business intelligence in health and treatment sector. This paper ...

Level-rank duality of untwisted and twisted D-branes

International Nuclear Information System (INIS)

Naculich, Stephen G.; Schnitzer, Howard J.

2006-01-01

Level-rank duality of untwisted and twisted D-branes of WZW models is explored. We derive the relation between D0-brane charges of level-rank dual untwisted D-branes of su-bar (N) K and sp-bar (n) k , and of level-rank dual twisted D-branes of su-bar (2n+1) 2k+1 . The analysis of level-rank duality of twisted D-branes of su-bar (2n+1) 2k+1 is facilitated by their close relation to untwisted D-branes of sp-bar (n) k . We also demonstrate level-rank duality of the spectrum of an open string stretched between untwisted or twisted D-branes in each of these cases

Pipeline for the Analysis of ChIP-seq Data and New Motif Ranking Procedure

KAUST Repository

Ashoor, Haitham

2011-06-01

This thesis presents a computational methodology for ab-initio identification of transcription factor binding sites based on ChIP-seq data. This method consists of three main steps, namely ChIP-seq data processing, motif discovery and models selection. A novel method for ranking the models of motifs identified in this process is proposed. This method combines multiple factors in order to rank the provided candidate motifs. It combines the model coverage of the ChIP-seq fragments that contain motifs from which that model is built, the suitable background data made up of shuffled ChIP-seq fragments, and the p-value that resulted from evaluating the model on actual and background data. Two ChIP-seq datasets retrieved from ENCODE project are used to evaluate and demonstrate the ability of the method to predict correct TFBSs with high precision. The first dataset relates to neuron-restrictive silencer factor, NRSF, while the second one corresponds to growth-associated binding protein, GABP. The pipeline system shows high precision prediction for both datasets, as in both cases the top ranked motif closely resembles the known motifs for the respective transcription factors.

Adiabatic quantum algorithm for search engine ranking.

Science.gov (United States)

Garnerone, Silvano; Zanardi, Paolo; Lidar, Daniel A

2012-06-08

We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web pages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top-ranked log(n) entries of the quantum PageRank state can then be estimated with a polynomial quantum speed-up. Moreover, the quantum PageRank state can be used in "q-sampling" protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.

Diversity rankings among bacterial lineages in soil.

Science.gov (United States)

Youssef, Noha H; Elshahed, Mostafa S

2009-03-01

We used rarefaction curve analysis and diversity ordering-based approaches to rank the 11 most frequently encountered bacterial lineages in soil according to diversity in 5 previously reported 16S rRNA gene clone libraries derived from agricultural, undisturbed tall grass prairie and forest soils (n=26,140, 28 328, 31 818, 13 001 and 53 533). The Planctomycetes, Firmicutes and the delta-Proteobacteria were consistently ranked among the most diverse lineages in all data sets, whereas the Verrucomicrobia, Gemmatimonadetes and beta-Proteobacteria were consistently ranked among the least diverse. On the other hand, the rankings of alpha-Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes and Chloroflexi varied widely in different soil clone libraries. In general, lineages exhibiting largest differences in diversity rankings also exhibited the largest difference in relative abundance in the data sets examined. Within these lineages, a positive correlation between relative abundance and diversity was observed within the Acidobacteria, Actinobacteria and Chloroflexi, and a negative diversity-abundance correlation was observed within the Bacteroidetes. The ecological and evolutionary implications of these results are discussed.

SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

Science.gov (United States)

Shams, Bita; Haratizadeh, Saman

2016-09-01

Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

Experienced stigma and its impacts in psychosis: The role of social rank and external shame.

Science.gov (United States)

Wood, Lisa; Irons, Chris

2017-09-01

Experienced stigma is detrimental to those who experience psychosis and can cause emotional distress and hinder recovery. This study aimed to explore the relationship between experienced stigma with emotional distress and recovery in people with psychosis. It explored the role of external shame and social rank as mediators in these relationships. A cross-sectional design was implemented. Fifty-two service users were administered a battery of questionnaires examining experienced stigma, external shame, social rank, personal recovery, positive symptoms, depression, and anxiety. Correlation and multiple regression analysis were conducted on the data. Where appropriate, mediation analysis was employed to explore social rank and external shame as mediatory variables. Experienced stigma was significantly related to shame (social rank and external shame), positive symptoms, emotional distress (depression and anxiety), and personal recovery. The impact of experienced stigma on depression was mediated by external shame. Social rank was a mediator between experienced stigma and personal recovery only. People with psychosis who have experienced stigma are likely to experience emotional distress and be inhibited in their recovery. This was found to be partly mediated by external shame and low social rank. Clinical approaches to stigma need to target these as potential maintenance factors. Experienced stigma is significantly related to shame (social rank and external shame) emotional distress, and reduced personal recovery. External shame mediated the relationship between experienced stigma and depression in psychosis. Social rank mediated the relationship between experienced stigma and personal recovery. Clinical approaches to stigma should include the assessment of external shame and low social rank. © 2017 The British Psychological Society.

A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem

DEFF Research Database (Denmark)

Montoya-Martinez, Jair; Artes-Rodriguez, Antonio; Pontil, Massimiliano

2014-01-01

We consider the estimation of the Brain Electrical Sources (BES) matrix from noisy electroencephalographic (EEG) measurements, commonly named as the EEG inverse problem. We propose a new method to induce neurophysiological meaningful solutions, which takes into account the smoothness, structured...... sparsity, and low rank of the BES matrix. The method is based on the factorization of the BES matrix as a product of a sparse coding matrix and a dense latent source matrix. The structured sparse-low-rank structure is enforced by minimizing a regularized functional that includes the ℓ21-norm of the coding...... matrix and the squared Frobenius norm of the latent source matrix. We develop an alternating optimization algorithm to solve the resulting nonsmooth-nonconvex minimization problem. We analyze the convergence of the optimization procedure, and we compare, under different synthetic scenarios...

Tumor Necrosis Factor α Stimulates Osteoclast Differentiation by a Mechanism Independent of the Odf/Rankl–Rank Interaction

Science.gov (United States)

Kobayashi, Kanichiro; Takahashi, Naoyuki; Jimi, Eijiro; Udagawa, Nobuyuki; Takami, Masamichi; Kotake, Shigeru; Nakagawa, Nobuaki; Kinosaki, Masahiko; Yamaguchi, Kyoji; Shima, Nobuyuki; Yasuda, Hisataka; Morinaga, Tomonori; Higashio, Kanji; Martin, T. John; Suda, Tatsuo

2000-01-01

Osteoclast differentiation factor (ODF, also called RANKL/TRANCE/OPGL) stimulates the differentiation of osteoclast progenitors of the monocyte/macrophage lineage into osteoclasts in the presence of macrophage colony-stimulating factor (M-CSF, also called CSF-1). When mouse bone marrow cells were cultured with M-CSF, M-CSF–dependent bone marrow macrophages (M-BMMφ) appeared within 3 d. Tartrate-resistant acid phosphatase–positive osteoclasts were also formed when M-BMMφ were further cultured for 3 d with mouse tumor necrosis factor α (TNF-α) in the presence of M-CSF. Osteoclast formation induced by TNF-α was inhibited by the addition of respective antibodies against TNF receptor 1 (TNFR1) or TNFR2, but not by osteoclastogenesis inhibitory factor (OCIF, also called OPG, a decoy receptor of ODF/RANKL), nor the Fab fragment of anti–RANK (ODF/RANKL receptor) antibody. Experiments using M-BMMφ prepared from TNFR1- or TNFR2-deficient mice showed that both TNFR1- and TNFR2-induced signals were important for osteoclast formation induced by TNF-α. Osteoclasts induced by TNF-α formed resorption pits on dentine slices only in the presence of IL-1α. These results demonstrate that TNF-α stimulates osteoclast differentiation in the presence of M-CSF through a mechanism independent of the ODF/RANKL–RANK system. TNF-α together with IL-1α may play an important role in bone resorption of inflammatory bone diseases. PMID:10637272

Dominance-based ranking functions for interval-valued intuitionistic fuzzy sets.

Science.gov (United States)

Chen, Liang-Hsuan; Tu, Chien-Cheng

2014-08-01

The ranking of interval-valued intuitionistic fuzzy sets (IvIFSs) is difficult since they include the interval values of membership and nonmembership. This paper proposes ranking functions for IvIFSs based on the dominance concept. The proposed ranking functions consider the degree to which an IvIFS dominates and is not dominated by other IvIFSs. Based on the bivariate framework and the dominance concept, the functions incorporate not only the boundary values of membership and nonmembership, but also the relative relations among IvIFSs in comparisons. The dominance-based ranking functions include bipolar evaluations with a parameter that allows the decision-maker to reflect his actual attitude in allocating the various kinds of dominance. The relationship for two IvIFSs that satisfy the dual couple is defined based on four proposed ranking functions. Importantly, the proposed ranking functions can achieve a full ranking for all IvIFSs. Two examples are used to demonstrate the applicability and distinctiveness of the proposed ranking functions.

Co-integration Rank Testing under Conditional Heteroskedasticity

DEFF Research Database (Denmark)

Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

null distributions of the rank statistics coincide with those derived by previous authors who assume either i.i.d. or (strict and covariance) stationary martingale difference innovations. We then propose wild bootstrap implementations of the co-integrating rank tests and demonstrate that the associated...... bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show the same is also true of the corresponding rank tests based on the i.i.d. bootstrap of Swensen (2006). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap......, it preserves in the re-sampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence sug- gests that, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples un...

RankProdIt: A web-interactive Rank Products analysis tool

Directory of Open Access Journals (Sweden)

Laing Emma

2010-08-01

Full Text Available Abstract Background The first objective of a DNA microarray experiment is typically to generate a list of genes or probes that are found to be differentially expressed or represented (in the case of comparative genomic hybridizations and/or copy number variation between two conditions or strains. Rank Products analysis comprises a robust algorithm for deriving such lists from microarray experiments that comprise small numbers of replicates, for example, less than the number required for the commonly used t-test. Currently, users wishing to apply Rank Products analysis to their own microarray data sets have been restricted to the use of command line-based software which can limit its usage within the biological community. Findings Here we have developed a web interface to existing Rank Products analysis tools allowing users to quickly process their data in an intuitive and step-wise manner to obtain the respective Rank Product or Rank Sum, probability of false prediction and p-values in a downloadable file. Conclusions The online interactive Rank Products analysis tool RankProdIt, for analysis of any data set containing measurements for multiple replicated conditions, is available at: http://strep-microarray.sbs.surrey.ac.uk/RankProducts

Relationship between Journal-Ranking Metrics for a Multidisciplinary Set of Journals

Science.gov (United States)

Perera, Upeksha; Wijewickrema, Manjula

2018-01-01

Ranking of scholarly journals is important to many parties. Studying the relationships among various ranking metrics is key to understanding the significance of one metric based on another. This research investigates the relationship among four major journal-ranking indicators: the impact factor (IF), the Eigenfactor score (ES), the "h."…

Critical review of methods for risk ranking of food-related hazards, based on risks for human health.

Science.gov (United States)

Van der Fels-Klerx, H J; Van Asselt, E D; Raley, M; Poulsen, M; Korsgaard, H; Bredsdorff, L; Nauta, M; D'agostino, M; Coles, D; Marvin, H J P; Frewer, L J

2018-01-22

This study aimed to critically review methods for ranking risks related to food safety and dietary hazards on the basis of their anticipated human health impacts. A literature review was performed to identify and characterize methods for risk ranking from the fields of food, environmental science and socio-economic sciences. The review used a predefined search protocol, and covered the bibliographic databases Scopus, CAB Abstracts, Web of Sciences, and PubMed over the period 1993-2013. All references deemed relevant, on the basis of predefined evaluation criteria, were included in the review, and the risk ranking method characterized. The methods were then clustered-based on their characteristics-into eleven method categories. These categories included: risk assessment, comparative risk assessment, risk ratio method, scoring method, cost of illness, health adjusted life years (HALY), multi-criteria decision analysis, risk matrix, flow charts/decision trees, stated preference techniques and expert synthesis. Method categories were described by their characteristics, weaknesses and strengths, data resources, and fields of applications. It was concluded there is no single best method for risk ranking. The method to be used should be selected on the basis of risk manager/assessor requirements, data availability, and the characteristics of the method. Recommendations for future use and application are provided.

Abundances of polycyclic aromatic hydrocarbons (PAHs) in 14 chinese and american coals and their relation to coal rank and weathering

Science.gov (United States)

Wang, R.; Liu, Gaisheng; Zhang, Jiahua; Chou, C.-L.; Liu, J.

2010-01-01

The abundances of 16 polycyclic aromatic hydrocarbons (PAHs) on the priority list of the United States Environmental Protection Agency (U.S. EPA) have been determined in 14 Chinese and American coals. The ranks of the samples range from lignite, bituminous coal, anthracite, to natural coke. Soxhlet extraction was conducted on each coal for 48 h. The extract was analyzed on a gas chromatograph-mass spectrometer (GC-MS). The results show that the total PAH content ranged from 0.31 to 57.6 ??g/g of coal (on a dry basis). It varied with coal rank and is highest in the maturity range of bituminous coal rank. High-molecular-weight (HMW) PAHs are predominant in low-rank coals, but low-molecular-weight (LMW) PAHs are predominant in high-rank coals. The low-sulfur coals have a higher PAH content than high-sulfur coals. It may be explained by an increasing connection between disulfide bonds and PAHs in high-sulfur coal. In addition, it leads us to conclude that the PAH content of coals may be related to the depositional environment. ?? 2010 American Chemical Society.

Integrated inventory ranking system for oilfield equipment industry

Directory of Open Access Journals (Sweden)

Jalel Ben Hmida

2014-01-01

Full Text Available Purpose: This case study is motivated by the subcontracting problem in an oilfield equipment and service company where the management needs to decide which parts to manufacture in-house when the capacity is not enough to make all required parts. Currently the company is making subcontracting decisions based on management’s experience. Design/methodology/approach: Working with the management, a decision support system (DSS is developed to rank parts by integrating three inventory classification methods considering both quantitative factors such as cost and demand, and qualitative factors such as functionality, efficiency, and quality. The proposed integrated inventory ranking procedure will make use of three classification methods: ABC, FSN, and VED. Findings: An integration mechanism using weights is developed to rank the parts based on the total priority scores. The ranked list generated by the system helps management to identify about 50 critical parts to manufacture in-house. Originality/value: The integration of all three inventory classification techniques into a single system is a unique feature of this research. This is important as it provides a more inclusive, big picture view of the DSS for management’s use in making business decisions.

Sex-reversed correlation between stress levels and dominance rank in a captive non-breeder flock of crows.

Science.gov (United States)

Ode, Minami; Asaba, Akari; Miyazawa, Eri; Mogi, Kazutaka; Kikusui, Takefumi; Izawa, Ei-Ichi

2015-07-01

Group living has both benefits and costs to individuals; benefits include efficient acquisition of resources, and costs include stress from social conflicts among group members. Such social challenges result in hierarchical dominance ranking among group members as a solution to avoid escalating conflict that causes different levels of basal stress between individuals at different ranks. Stress-associated glucocorticoid (corticosterone in rodents and birds; CORT) levels are known to correlate with dominance rank in diverse taxa and to covary with various social factors, such as sex and dominance maintenance styles. Although there is much evidence for sex differences in the basal levels of CORT in various species, the correlation of sex differences in basal CORT with dominance rank is poorly understood. We investigated the correlation between CORT metabolites (CM) in the droppings and social factors, including rank and sex, in a captive non-breeder group of crows. In this group, all the single males dominated all the single females, and dominance ranks were stable among single males but relatively unstable among single females. CM levels and rank were significantly correlated in a sex-reversed fashion: males at higher rank (i.e., more dominant) had higher CM, whereas females at higher rank exhibited lower CM. This is the first evidence of sex-reversed patterns of CM-rank correlation in birds. The results suggest that different mechanisms of stress-dominance relationships operate on the sexes in non-breeder crow aggregations; in males, stress is associated with the cost of aggressive displays, whereas females experience subordination stress due to males' overt aggression. Copyright © 2015 Elsevier Inc. All rights reserved.

A novel application of PageRank and user preference algorithms for assessing the relative performance of track athletes in competition.

Science.gov (United States)

Beggs, Clive B; Shepherd, Simon J; Emmonds, Stacey; Jones, Ben

2017-01-01

Ranking enables coaches, sporting authorities, and pundits to determine the relative performance of individual athletes and teams in comparison to their peers. While ranking is relatively straightforward in sports that employ traditional leagues, it is more difficult in sports where competition is fragmented (e.g. athletics, boxing, etc.), with not all competitors competing against each other. In such situations, complex points systems are often employed to rank athletes. However, these systems have the inherent weakness that they frequently rely on subjective assessments in order to gauge the calibre of the competitors involved. Here we show how two Internet derived algorithms, the PageRank (PR) and user preference (UP) algorithms, when utilised with a simple 'who beat who' matrix, can be used to accurately rank track athletes, avoiding the need for subjective assessment. We applied the PR and UP algorithms to the 2015 IAAF Diamond League men's 100m competition and compared their performance with the Keener, Colley and Massey ranking algorithms. The top five places computed by the PR and UP algorithms, and the Diamond League '2016' points system were all identical, with the Kendall's tau distance between the PR standings and '2016' points system standings being just 15, indicating that only 5.9% of pairs differed in their order between these two lists. By comparison, the UP and '2016' standings displayed a less strong relationship, with a tau distance of 95, indicating that 37.6% of the pairs differed in their order. When compared with the standings produced using the Keener, Colley and Massey algorithms, the PR standings appeared to be closest to the Keener standings (tau distance = 67, 26.5% pair order disagreement), whereas the UP standings were more similar to the Colley and Massey standings, with the tau distances between these ranking lists being only 48 (19.0% pair order disagreement) and 59 (23.3% pair order disagreement) respectively. In particular, the

A novel application of PageRank and user preference algorithms for assessing the relative performance of track athletes in competition.

Directory of Open Access Journals (Sweden)

Clive B Beggs

Full Text Available Ranking enables coaches, sporting authorities, and pundits to determine the relative performance of individual athletes and teams in comparison to their peers. While ranking is relatively straightforward in sports that employ traditional leagues, it is more difficult in sports where competition is fragmented (e.g. athletics, boxing, etc., with not all competitors competing against each other. In such situations, complex points systems are often employed to rank athletes. However, these systems have the inherent weakness that they frequently rely on subjective assessments in order to gauge the calibre of the competitors involved. Here we show how two Internet derived algorithms, the PageRank (PR and user preference (UP algorithms, when utilised with a simple 'who beat who' matrix, can be used to accurately rank track athletes, avoiding the need for subjective assessment. We applied the PR and UP algorithms to the 2015 IAAF Diamond League men's 100m competition and compared their performance with the Keener, Colley and Massey ranking algorithms. The top five places computed by the PR and UP algorithms, and the Diamond League '2016' points system were all identical, with the Kendall's tau distance between the PR standings and '2016' points system standings being just 15, indicating that only 5.9% of pairs differed in their order between these two lists. By comparison, the UP and '2016' standings displayed a less strong relationship, with a tau distance of 95, indicating that 37.6% of the pairs differed in their order. When compared with the standings produced using the Keener, Colley and Massey algorithms, the PR standings appeared to be closest to the Keener standings (tau distance = 67, 26.5% pair order disagreement, whereas the UP standings were more similar to the Colley and Massey standings, with the tau distances between these ranking lists being only 48 (19.0% pair order disagreement and 59 (23.3% pair order disagreement respectively. In

College student reactions to health warning labels: sociodemographic and psychosocial factors related to perceived effectiveness of different approaches.

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Berg, Carla J; Thrasher, James F; Westmaas, J Lee; Buchanan, Taneisha; Pinsker, Erika A; Ahluwalia, Jasjit S

2011-12-01

To examine factors associated with perceiving different types of pictorial cigarette health warning labels as most effective in motivating smokers to quit or preventing smoking initiation among college students. We administered an online survey to 24,055 students attending six Southeast colleges in Fall, 2010. We obtained complete data for the current analyses from 2600. Current smoking prevalence was 23.5%. The largest majority (78.6%) consistently rated gruesome images as most effective, 19.5% rated testimonial images as most effective, and only a small proportion rated either standard (1.6%) or human suffering images (0.3%) as most effective. Subsequent analyses focused on differences between those endorsing gruesome images or testimonials as most effective. Factors related to ranking testimonials versus gruesome images as most effective included being female (pmarketing (p=0.01). Among smokers, factors related to ranking testimonials as most effective versus gruesome images included being female (p=0.03), being White (p=0.03), higher autonomous motivation (p=0.03), and greater extrinsic self-efficacy (p=0.02). Understanding factors related to perceived effectiveness of different pictorial warnings among subpopulations should inform health warning labels released by the FDA. Copyright © 2011 Elsevier Inc. All rights reserved.

Fourth-rank gravity and cosmology

International Nuclear Information System (INIS)

Marrakchi, A.L.; Tapia, V.

1992-07-01

We consider the consequences of describing the metric properties of space-time through a quartic line element. The associated ''metric'' is a fourth-rank tensor G μυλπ . In order to recover a Riemannian behaviour of the geometry it is necessary to have G μυλπ = g (μυ g λπ) . We construct a theory for the gravitational field based on the fourth-rank metric G μυλπ . In the absence of matter the fourth-rank metric becomes separable and the theory coincides with General Relativity. In the presence of matter we can maintain Riemmanianicity, but now gravitation couples, as compared to General Relativity, in a different way to matter. We develop a simple cosmological model based on a FRW metric with matter described by a perfect fluid. For the present time the field equations are compatible with k OBS = O and Ω OBS t CLAS approx. 10 20 t PLANCK approx. 10 -23 s. Our final and most important result is the fact that the entropy is an increasing function of time. When interpreted at the light of General Relativity the treatment is shown to be almost equivalent to that of the standard model of cosmology combined with the inflationary scenario. (author). 16 refs, 1 fig

The 5-year incidence of bleb-related infection and its risk factors after filtering surgeries with adjunctive mitomycin C: collaborative bleb-related infection incidence and treatment study 2.

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Yamamoto, Tetsuya; Sawada, Akira; Mayama, Chihiro; Araie, Makoto; Ohkubo, Shinji; Sugiyama, Kazuhisa; Kuwayama, Yasuaki

2014-05-01

To report the 5-year incidence of bleb-related infection after mitomycin C-augmented glaucoma filtering surgery and to investigate the risk factors for infections. Prospective, observational cohort study. A total of 1098 eyes of 1098 glaucoma patients who had undergone mitomycin C-augmented trabeculectomy or trabeculectomy combined with phacoemulsification and intraocular lens implantation performed at 34 clinical centers. Patients were followed up at 6-month intervals for 5 years, with special attention given to bleb-related infections. The follow-up data were analyzed via Kaplan-Meier survival analysis and the Cox proportional hazards model. Incidence of bleb-related infection over 5 years and risk factors for infections. Of the 1098 eyes, a bleb-related infection developed in 21 eyes. Kaplan-Meier survival analysis revealed that the incidence of bleb-related infection was 2.2±0.5% (cumulative incidence ± standard error) at the 5-year follow-up for all cases, whereas it was 7.9±3.1% and 1.7±0.4% for cases with and without a history of bleb leakage, respectively (P = 0.000, log-rank test). When only eyes with a well-functioning bleb were counted, it was 3.9±1.0%. No differences were found between the trabeculectomy cases and the combined surgery cases (P = 0.398, log-rank test) or between cases with a fornix-based flap and those with a limbal-based flap (P = 0.651, log-rank test). The Cox model revealed that a history of bleb leakage and younger age were risk factors for infections. The 5-year cumulative incidence of bleb-related infection was 2.2±0.5% in eyes treated with mitomycin C-augmented trabeculectomy or trabeculectomy combined with phacoemulsification and intraocular lens implantation in our prospective, multicenter study. Bleb leakage and younger age were the main risk factors for infections. Copyright © 2014 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Cell adhesion signaling regulates RANK expression in osteoclast precursors.

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Ayako Mochizuki

Full Text Available Cells with monocyte/macrophage lineage expressing receptor activator of NF-κB (RANK differentiate into osteoclasts following stimulation with the RANK ligand (RANKL. Cell adhesion signaling is also required for osteoclast differentiation from precursors. However, details of the mechanism by which cell adhesion signals induce osteoclast differentiation have not been fully elucidated. To investigate the participation of cell adhesion signaling in osteoclast differentiation, mouse bone marrow-derived macrophages (BMMs were used as osteoclast precursors, and cultured on either plastic cell culture dishes (adherent condition or the top surface of semisolid methylcellulose gel loaded in culture tubes (non-adherent condition. BMMs cultured under the adherent condition differentiated into osteoclasts in response to RANKL stimulation. However, under the non-adherent condition, the efficiency of osteoclast differentiation was markedly reduced even in the presence of RANKL. These BMMs retained macrophage characteristics including phagocytic function and gene expression profile. Lipopolysaccharide (LPS and tumor necrosis factor -αTNF-α activated the NF-κB-mediated signaling pathways under both the adherent and non-adherent conditions, while RANKL activated the pathways only under the adherent condition. BMMs highly expressed RANK mRNA and protein under the adherent condition as compared to the non-adherent condition. Also, BMMs transferred from the adherent to non-adherent condition showed downregulated RANK expression within 24 hours. In contrast, transferring those from the non-adherent to adherent condition significantly increased the level of RANK expression. Moreover, interruption of cell adhesion signaling by echistatin, an RGD-containing disintegrin, decreased RANK expression in BMMs, while forced expression of either RANK or TNFR-associated factor 6 (TRAF6 in BMMs induced their differentiation into osteoclasts even under the non

Systematic monitoring of male circumcision scale-up in Nyanza, Kenya: exploratory factor analysis of service quality instrument and performance ranking.

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Omondi Aduda, Dickens S; Ouma, Collins; Onyango, Rosebella; Onyango, Mathews; Bertrand, Jane

2014-01-01

Considerable conceptual and operational complexities related to service quality measurements and variability in delivery contexts of scaled-up medical male circumcision, pose real challenges to monitoring implementation of quality and safety. Clarifying latent factors of the quality instruments can enhance contextual applicability and the likelihood that observed service outcomes are appropriately assessed. To explore factors underlying SYMMACS service quality assessment tool (adopted from the WHO VMMC quality toolkit) and; determine service quality performance using composite quality index derived from the latent factors. Using a comparative process evaluation of Voluntary Medical Male Circumcision Scale-Up in Kenya site level data was collected among health facilities providing VMMC over two years. Systematic Monitoring of the Medical Male Circumcision Scale-Up quality instrument was used to assess availability of guidelines, supplies and equipment, infection control, and continuity of care services. Exploratory factor analysis was performed to clarify quality structure. Fifty four items and 246 responses were analyzed. Based on Eigenvalue >1.00 cut-off, factors 1, 2 & 3 were retained each respectively having eigenvalues of 5.78; 4.29; 2.99. These cumulatively accounted for 29.1% of the total variance (12.9%; 9.5%; 6.7%) with final communality estimates being 13.06. Using a cut-off factor loading value of ≥0.4, fifteen items loading on factor 1, five on factor 2 and one on factor 3 were retained. Factor 1 closely relates to preparedness to deliver safe male circumcisions while factor two depicts skilled task performance and compliance with protocols. Of the 28 facilities, 32% attained between 90th and 95th percentile (excellent); 45% between 50th and 75th percentiles (average) and 14.3% below 25th percentile (poor). the service quality assessment instrument may be simplified to have nearly 20 items that relate more closely to service outcomes. Ranking of

Clinical prognostic significance and pro-metastatic activity of RANK/RANKL via the AKT pathway in endometrial cancer.

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Wang, Jing; Liu, Yao; Wang, Lihua; Sun, Xiao; Wang, Yudong

2016-02-02

RANK/RANKL plays a key role in metastasis of certain malignant tumors, which makes it a promising target for developing novel therapeutic strategies for cancer. However, the prognostic value and pro-metastatic activity of RANK in endometrial cancer (EC) remain to be determined. Thus, the present study investigated the effect of RANK on the prognosis of EC patients, as well as the pro-metastatic activity of EC cells. The results indicated that those with high expression of RANK showed decreased overall survival and progression-free survival. Statistical analysis revealed the positive correlations between RANK/RANKL expression and metastasis-related factors. Additionally, RANK/RANKL significantly promoted cell migration/invasion via activating AKT/β-catenin/Snail pathway in vitro. However, RANK/RANKL-induced AKT activation could be suppressed after osteoprotegerin (OPG) treatment. Furthermore, the combination of medroxyprogesterone acetate (MPA) and RANKL could in turn attenuate the effect of RANKL alone. Similarly, MPA could partially inhibit the RANK-induced metastasis in an orthotopic mouse model via suppressing AKT/β-catenin/Snail pathway. Therefore, therapeutic inhibition of MPA in RANK/RANKL-induced metastasis was mediated by AKT/β-catenin/Snail pathway both in vitro and in vivo, suggesting a potential target of RANK for gene-based therapy for EC.

Reduced-Rank Adaptive Filtering Using Krylov Subspace

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Sergueï Burykh

2003-01-01

Full Text Available A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions of linear systems. The alternative interpretation so obtained is used to study the properties of each considered technique and to relate one reduced-rank method to another as well as to algorithms used in computational linear algebra. Practical issues are discussed and low-complexity versions are also included in our study. It is believed that the insight developed in this paper can be further used to improve existing reduced-rank methods according to known results in the domain of Krylov subspace methods.

Priority ranking of safety-related systems for structural enhancement assessment at Savannah River Site

International Nuclear Information System (INIS)

Kao, G.C.; Daugherty, W.L.; Barnes, D.M.

1992-09-01

In order to extend the service life of safety related structures and systems in a logical manner, a Structural Enhancement Program was initiated to evaluate the structural integrity of eight (8) systems, namely: Cooling Water System, Emergency Cooling System, Moderator Recovery System supplementary Safety System, Water Removal System, Service Raw Water System, Service Clarified Water System, and River Water System. Since the level of importance of each system to reactor operations varies from one system to another, the scope of structural integrity evaluation for each system should be prioritized accordingly. This paper presents the assessment of system priority for structural evaluation based on a ranking methodology and specifies the level of structural evaluation consistent with the established priority. The effort was undertaken by a five-member panel representing four (4) major disciplines, including. structures, reactor engineering/operations, risk management and materials. The above systems were divided into a total of thirty-five (35) subsystem. These subsystems were then ranked with six (6) attributes, namely: Safety Classification, Degradation Mechanisms, Difficulty of Replacement, Failure Mode, Radiation Dose to Workers and Consequence of Failure. Each attribute was assigned a set of consequences or events with corresponding weighting scores. The results of the ranking process yielded two groups of subsystems, categorized as Priority I and II subsystems. The level of structural assessment was then formulated accordingly. The prioritized approach will allow more efficient allocation of resources, so that the Structural Enhancement Program can be implemented in a cost-effective and efficient manner

Gender Disparities in Faculty Rank: Factors that Affect Advancement of Women Scientists at Academic Medical Centers

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Cristina M. López

2018-04-01

Full Text Available While a significant portion of women within academic science are employed within medical schools, women faculty in these academic medical centers are disproportionately represented in lower faculty ranks. The medical school setting is a critical case for both understanding and advancing women in basic sciences. This study highlights the findings from focus groups conducted with women faculty across Assistant, Associate, and Full Professor ranks (n = 35 in which they discussed barriers and facilitators for advancement of women basic scientists at an academic medical center. Qualitative analysis demonstrated several emergent themes that affect women’s advancement, including gendered expectation norms (e.g., good citizenship, volunteerism, work-life balance, mentorship/sponsorship, adoption of a team science approach, tenure process milestones, soft money research infrastructure, institution specific policies (or lack thereof, and operating within an MD-biased culture. These findings are compared with the extant literature of women scientists in STEM institutions. Factors that emerged from these focus groups highlight the need for evidence-based interventions in the often overlooked STEM arena of academic medical centers.

Rank of quantized universal enveloping algebras and modular functions

International Nuclear Information System (INIS)

Majid, S.; Soibelman, Ya.S.

1991-01-01

We compute an intrinsic rank invariant for quasitriangular Hopf algebras in the case of general quantum groups U q (g). As a function of q the rank has remarkable number theoretic properties connected with modular covariance and Galois theory. A number of examples are treated in detail, including rank (U q (su(3)) and rank (U q (e 8 )). We briefly indicate a physical interpretation as relating Chern-Simons theory with the theory of a quantum particle confined to an alcove of g. (orig.)

A Markov chain model for image ranking system in social networks

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Zin, Thi Thi; Tin, Pyke; Toriu, Takashi; Hama, Hiromitsu

2014-03-01

In today world, different kinds of networks such as social, technological, business and etc. exist. All of the networks are similar in terms of distributions, continuously growing and expanding in large scale. Among them, many social networks such as Facebook, Twitter, Flickr and many others provides a powerful abstraction of the structure and dynamics of diverse kinds of inter personal connection and interaction. Generally, the social network contents are created and consumed by the influences of all different social navigation paths that lead to the contents. Therefore, identifying important and user relevant refined structures such as visual information or communities become major factors in modern decision making world. Moreover, the traditional method of information ranking systems cannot be successful due to their lack of taking into account the properties of navigation paths driven by social connections. In this paper, we propose a novel image ranking system in social networks by using the social data relational graphs from social media platform jointly with visual data to improve the relevance between returned images and user intentions (i.e., social relevance). Specifically, we propose a Markov chain based Social-Visual Ranking algorithm by taking social relevance into account. By using some extensive experiments, we demonstrated the significant and effectiveness of the proposed social-visual ranking method.

An empirical study for ranking risk factors using linear assignment: A case study of road construction

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Amin Foroughi

2012-04-01

Full Text Available Road construction projects are considered as the most important governmental issues since there are normally heavy investments required in such projects. There is also shortage of financial resources in governmental budget, which makes the asset allocation more challenging. One primary step in reducing the cost is to determine different risks associated with execution of such project activities. In this study, we present some important risk factors associated with road construction in two levels for a real-world case study of rail-road industry located between two cities of Esfahan and Deligan. The first group of risk factors includes the probability and the effects for various attributes including cost, time, quality and performance. The second group of risk factors includes socio-economical factors as well as political and managerial aspects. The study finds 21 main risk factors as well as 193 sub risk factors. The factors are ranked using groups decision-making method called linear assignment. The preliminary results indicate that the road construction projects could finish faster with better outcome should we carefully consider risk factors and attempt to reduce their impacts.

Social Rank, Stress, Fitness, and Life Expectancy in Wild Rabbits

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von Holst, Dietrich; Hutzelmeyer, Hans; Kaetzke, Paul; Khaschei, Martin; Schönheiter, Ronald

Wild rabbits of the two sexes have separate linear rank orders, which are established and maintained by intensive fights. The social rank of individuals strongly influence their fitness: males and females that gain a high social rank, at least at the outset of their second breeding season, have a much higher lifetime fitness than subordinate individuals. This is because of two separate factors: a much higher fecundity and annual reproductive success and a 50% longer reproductive life span. These results are in contrast to the view in evolutionary biology that current reproduction can be increased only at the expense of future survival and/or fecundity. These concepts entail higher physiological costs in high-ranking mammals, which is not supported by our data: In wild rabbits the physiological costs of social positions are caused predominantly by differential psychosocial stress responses that are much lower in high-ranking than in low-ranking individuals.

Is a gene important for bone resorption a candidate for obesity? An association and linkage study on the RANK (receptor activator of nuclear factor-kappaB) gene in a large Caucasian sample.

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Zhao, Lan-Juan; Guo, Yan-Fang; Xiong, Dong-Hai; Xiao, Peng; Recker, Robert R; Deng, Hong-Wen

2006-11-01

In light of findings that osteoporosis and obesity may share some common genetic determination and previous reports that RANK (receptor activator of nuclear factor-kappaB) is expressed in skeletal muscles which are important for energy metabolism, we hypothesize that RANK, a gene essential for osteoclastogenesis, is also important for obesity. In order to test the hypothesis with solid data we first performed a linkage analysis around the RANK gene in 4,102 Caucasian subjects from 434 pedigrees, then we genotyped 19 SNPs in or around the RANK gene. A family-based association test (FBAT) was performed with both a quantitative measure of obesity [fat mass, lean mass, body mass index (BMI), and percentage fat mass (PFM)] and a dichotomously defined obesity phenotype-OB (OB if BMI > or = 30 kg/m(2)). In the linkage analysis, an empirical P = 0.004 was achieved at the location of the RANK gene for BMI. Family-based association analysis revealed significant associations of eight SNPs with at least one obesity-related phenotype (P obesity phenotype. The P value is 0.126 for OB, 0.033 for fat mass, 0.021 for lean mass, 0.016 for BMI, and 0.006 for PFM. The haplotype data analyses provide further association evidence. In conclusion, for the first time, our results suggest that RANK is a novel candidate for determination of obesity.

Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

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LI Lan-yin

2017-04-01

Full Text Available The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank，which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes，topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct subgraphs，and iteratively estimates lower/upper bounds of PageRank scores through subgraphs. Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithm can find k nodes much faster than the existing approaches.

A folk-psychological ranking of personality facets

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Eka Roivainen

2016-10-01

Full Text Available Background Which personality facets should a general personality test measure? No consensus exists on the facet structure of personality, the nature of facets, or the correct method of identifying the most significant facets. However, it can be hypothesized (the lexical hypothesis that high frequency personality describing words more likely represent important personality facets and rarely used words refer to less significant aspects of personality. Participants and procedure A ranking of personality facets was performed by studying the frequency of the use of popular personality adjectives in causal clauses (because he is a kind person on the Internet and in books as attributes of the word person (kind person. Results In Study 1, the 40 most frequently used adjectives had a cumulative usage frequency equal to that of the rest of the 295 terms studied. When terms with a higher-ranking dictionary synonym or antonym were eliminated, 23 terms remained, which represent 23 different facets. In Study 2, clusters of synonymous terms were examined. Within the top 30 clusters, personality terms were used 855 times compared to 240 for the 70 lower-ranking clusters. Conclusions It is hypothesized that personality facets represented by the top-ranking terms and clusters of terms are important and impactful independent of their correlation with abstract underlying personality factors (five/six factor models. Compared to hierarchical personality models, lists of important facets probably better cover those aspects of personality that are situated between the five or six major domains.

Augmenting the Deliberative Method for Ranking Risks.

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Susel, Irving; Lasley, Trace; Montezemolo, Mark; Piper, Joel

2016-01-01

The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.

Consequence ranking of radionuclides in Hanford tank waste

International Nuclear Information System (INIS)

Schmittroth, F.A.; De Lorenzo, T.H.

1995-09-01

Radionuclides in the Hanford tank waste are ranked relative to their consequences for the Low-Level Tank Waste program. The ranking identifies key radionuclides where further study is merited. In addition to potential consequences for intrude and drinking-water scenarios supporting low-level waste activities, a ranking based on shielding criteria is provided. The radionuclide production inventories are based on a new and independent ORIGEN2 calculation representing the operation of all Hanford single-pass reactors and the N Reactor

RANKL/RANK: from bone loss to the prevention of breast cancer.

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Sigl, Verena; Jones, Laundette P; Penninger, Josef M

2016-11-01

RANK and RANKL, a receptor ligand pair belonging to the tumour necrosis factor family, are the critical regulators of osteoclast development and bone metabolism. Besides their essential function in bone, RANK and RANKL have also been identified as the key factors for the formation of a lactating mammary gland in pregnancy. Mechanistically, RANK and RANKL link the sex hormone progesterone with stem cell expansion and proliferation of mammary epithelial cells. Based on their normal physiology, RANKL/RANK control the onset of hormone-induced breast cancer through the expansion of mammary progenitor cells. Recently, we and others were able to show that RANK and RANKL are also critical regulators of BRCA1-mutation-driven breast cancer. Currently, the preventive strategy for BRCA1-mutation carriers includes preventive mastectomy, associated with wide-ranging risks and psychosocial effects. The search for an alternative non-invasive prevention strategy is therefore of paramount importance. As our work strongly implicates RANK and RANKL as key molecules involved in the initiation of BRCA1-associated breast cancer, we propose that anti-RANKL therapy could be a feasible preventive strategy for women carrying BRCA1 mutations, and by extension to other women with high risk of breast cancer. © 2016 The Authors.

A Case-Based Reasoning Method with Rank Aggregation

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Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

VaRank: a simple and powerful tool for ranking genetic variants

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Véronique Geoffroy

2015-03-01

Full Text Available Background. Most genetic disorders are caused by single nucleotide variations (SNVs or small insertion/deletions (indels. High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians.Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients.Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan

2014-04-17

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

Low-rank coal research

Energy Technology Data Exchange (ETDEWEB)

Weber, G. F.; Laudal, D. L.

1989-01-01

This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

Group social rank is associated with performance on a spatial learning task.

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Langley, Ellis J G; van Horik, Jayden O; Whiteside, Mark A; Madden, Joah R

2018-02-01

Dominant individuals differ from subordinates in their performances on cognitive tasks across a suite of taxa. Previous studies often only consider dyadic relationships, rather than the more ecologically relevant social hierarchies or networks, hence failing to account for how dyadic relationships may be adjusted within larger social groups. We used a novel statistical method: randomized Elo-ratings, to infer the social hierarchy of 18 male pheasants, Phasianus colchicus , while in a captive, mixed-sex group with a linear hierarchy. We assayed individual learning performance of these males on a binary spatial discrimination task to investigate whether inter-individual variation in performance is associated with group social rank. Task performance improved with increasing trial number and was positively related to social rank, with higher ranking males showing greater levels of success. Motivation to participate in the task was not related to social rank or task performance, thus indicating that these rank-related differences are not a consequence of differences in motivation to complete the task. Our results provide important information about how variation in cognitive performance relates to an individual's social rank within a group. Whether the social environment causes differences in learning performance or instead, inherent differences in learning ability predetermine rank remains to be tested.

Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants

Science.gov (United States)

Hüllermeier, Eyke; Fürnkranz, Johannes

The term “preference learning” refers to the application of machine learning methods for inducing preference models from empirical data. In the recent literature, corresponding problems appear in various guises. After a brief overview of the field, this work focuses on a particular learning scenario called label ranking where the problem is to learn a mapping from instances to rankings over a finite number of labels. Our approach for learning such a ranking function, called ranking by pairwise comparison (RPC), first induces a binary preference relation from suitable training data, using a natural extension of pairwise classification. A ranking is then derived from this relation by means of a ranking procedure. This paper elaborates on a key advantage of such an approach, namely the fact that our learner can be adapted to different loss functions by using different ranking procedures on the same underlying order relations. In particular, the Spearman rank correlation is minimized by using a simple weighted voting procedure. Moreover, we discuss a loss function suitable for settings where candidate labels must be tested successively until a target label is found. In this context, we propose the idea of “empirical conditioning” of class probabilities. A related ranking procedure, called “ranking through iterated choice”, is investigated experimentally.

Matrix completion via a low rank factorization model and an Augmented Lagrangean Succesive Overrelaxation Algorithm

Directory of Open Access Journals (Sweden)

Hugo Lara

2014-12-01

Full Text Available The matrix completion problem (MC has been approximated by using the nuclear norm relaxation. Some algorithms based on this strategy require the computationally expensive singular value decomposition (SVD at each iteration. One way to avoid SVD calculations is to use alternating methods, which pursue the completion through matrix factorization with a low rank condition. In this work an augmented Lagrangean-type alternating algorithm is proposed. The new algorithm uses duality information to define the iterations, in contrast to the solely primal LMaFit algorithm, which employs a Successive Over Relaxation scheme. The convergence result is studied. Some numerical experiments are given to compare numerical performance of both proposals.

Low-ranking female Japanese macaques make efforts for social grooming.

Science.gov (United States)

Kurihara, Yosuke

2016-04-01

Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates.

Low-ranking female Japanese macaques make efforts for social grooming

Science.gov (United States)

Kurihara, Yosuke

2016-01-01

Abstract Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates. PMID:29491896

Low Rank Approximation Algorithms, Implementation, Applications

CERN Document Server

Markovsky, Ivan

2012-01-01

Matrix low-rank approximation is intimately related to data modelling; a problem that arises frequently in many different fields. Low Rank Approximation: Algorithms, Implementation, Applications is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory. Applications described include: system and control theory: approximate realization, model reduction, output error, and errors-in-variables identification; signal processing: harmonic retrieval, sum-of-damped exponentials, finite impulse response modeling, and array processing; machine learning: multidimensional scaling and recommender system; computer vision: algebraic curve fitting and fundamental matrix estimation; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; ...

Efficient Low Rank Tensor Ring Completion

OpenAIRE

Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin

2017-01-01

Using the matrix product state (MPS) representation of the recently proposed tensor ring decompositions, in this paper we propose a tensor completion algorithm, which is an alternating minimization algorithm that alternates over the factors in the MPS representation. This development is motivated in part by the success of matrix completion algorithms that alternate over the (low-rank) factors. In this paper, we propose a spectral initialization for the tensor ring completion algorithm and ana...

Sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants.

Science.gov (United States)

Gerner, Nadine V; Cailleaud, Kevin; Bassères, Anne; Liess, Matthias; Beketov, Mikhail A

2017-11-01

Hydrocarbons have an utmost economical importance but may also cause substantial ecological impacts due to accidents or inadequate transportation and use. Currently, freshwater biomonitoring methods lack an indicator that can unequivocally reflect the impacts caused by hydrocarbons while being independent from effects of other stressors. The aim of the present study was to develop a sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants, which can be used in hydrocarbon-specific bioindicators. We employed the Relative Sensitivity method and developed the sensitivity ranking S hydrocarbons based on literature ecotoxicological data supplemented with rapid and mesocosm test results. A first validation of the sensitivity ranking based on an earlier field study has been conducted and revealed the S hydrocarbons ranking to be promising for application in sensitivity based indicators. Thus, the first results indicate that the ranking can serve as the core component of future hydrocarbon-specific and sensitivity trait based bioindicators.

On Rank Driven Dynamical Systems

Science.gov (United States)

Veerman, J. J. P.; Prieto, F. J.

2014-08-01

We investigate a class of models related to the Bak-Sneppen (BS) model, initially proposed to study evolution. The BS model is extremely simple and yet captures some forms of "complex behavior" such as self-organized criticality that is often observed in physical and biological systems. In this model, random fitnesses in are associated to agents located at the vertices of a graph . Their fitnesses are ranked from worst (0) to best (1). At every time-step the agent with the worst fitness and some others with a priori given rank probabilities are replaced by new agents with random fitnesses. We consider two cases: The exogenous case where the new fitnesses are taken from an a priori fixed distribution, and the endogenous case where the new fitnesses are taken from the current distribution as it evolves. We approximate the dynamics by making a simplifying independence assumption. We use Order Statistics and Dynamical Systems to define a rank-driven dynamical system that approximates the evolution of the distribution of the fitnesses in these rank-driven models, as well as in the BS model. For this simplified model we can find the limiting marginal distribution as a function of the initial conditions. Agreement with experimental results of the BS model is excellent.

An R package for analyzing and modeling ranking data.

Science.gov (United States)

Lee, Paul H; Yu, Philip L H

2013-05-14

In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance. In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought

Does the Peer Group matter? The Effect of Relative Rank on Educational Choice

DEFF Research Database (Denmark)

Skov, Peter Rohde

as a point of comparison. I investigate this theory using a school-by-grade fixed effects model and comprehensive administrative data. I examine the non-linear relationships between peers educational achievement on choice of secondary education. I show that the relative rank in the classroom have......In this paper I investigate whether a social contrast mechanism affects the choice of secondary schooling. Based on a theory of relative deprivation, a strand of research in social inequality of educational attainment shows that, controlling for the students ability, students who attends schools...... with more privileged peers have lower educational attainment and less prestigious labor market careers. This theory shows that students with similar ability may be regarded differently depending on context, which may affect the students' academic self-image. This also means that the students use their peers...

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Science.gov (United States)

Huang, Zhengnan; Zhang, Hongjiu; Boss, Jonathan; Goutman, Stephen A; Mukherjee, Bhramar; Dinov, Ivo D; Guan, Yuanfang

2017-12-01

Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

Cointegration rank testing under conditional heteroskedasticity

DEFF Research Database (Denmark)

Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, Robert M.

2010-01-01

We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the vector of series under test is driven by globally stationary, conditionally heteroskedastic......, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples under a variety of conditionally heteroskedastic innovation processes. An empirical application to the term structure of interest rates is given....

How can journal impact factors be normalized across fields of science? An assessment in terms of percentile ranks and fractional counts

NARCIS (Netherlands)

Leydesdorff, L.; Zhou, P.; Bornmann, L.

2013-01-01

Using the CD-ROM version of the Science Citation Index 2010 (N = 3,705 journals), we study the (combined) effects of (a) fractional counting on the impact factor (IF) and (b) transformation of the skewed citation distributions into a distribution of 100 percentiles and six percentile rank classes

Optimization of the two-sample rank Neyman-Pearson detector

Science.gov (United States)

Akimov, P. S.; Barashkov, V. M.

1984-10-01

The development of optimal algorithms concerned with rank considerations in the case of finite sample sizes involves considerable mathematical difficulties. The present investigation provides results related to the design and the analysis of an optimal rank detector based on a utilization of the Neyman-Pearson criteria. The detection of a signal in the presence of background noise is considered, taking into account n observations (readings) x1, x2, ... xn in the experimental communications channel. The computation of the value of the rank of an observation is calculated on the basis of relations between x and the variable y, representing interference. Attention is given to conditions in the absence of a signal, the probability of the detection of an arriving signal, details regarding the utilization of the Neyman-Pearson criteria, the scheme of an optimal rank, multichannel, incoherent detector, and an analysis of the detector.

Society of Pediatric Psychology Workforce Survey: Factors Related to Compensation of Pediatric Psychologists.

Science.gov (United States)

Brosig, Cheryl L; Hilliard, Marisa E; Williams, Andre; Armstrong, F Daniel; Christidis, Peggy; Kichler, Jessica; Pendley, Jennifer Shroff; Stamm, Karen E; Wysocki, Tim

2017-05-01

To summarize compensation results from the 2015 Society of Pediatric Psychology (SPP) Workforce Survey and identify factors related to compensation of pediatric psychologists. All full members of SPP ( n  = 1,314) received the online Workforce Survey; 404 (32%) were returned with usable data. The survey assessed salary, benefits, and other income sources. The relationship between demographic and employment-related factors and overall compensation was explored.   Academic rank, level of administrative responsibility, and cost of living index of employment location were associated with compensation. Compensation did not vary by gender; however, women were disproportionately represented at the assistant and associate professor level. Compensation of pediatric psychologists is related to multiple factors. Longitudinal administration of the Workforce Survey is needed to determine changes in compensation and career advancement for this profession over time. Strategies to increase the response rate of future Workforce Surveys are discussed. © The Author 2017. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Critical review of methodology and application of risk ranking for prioritisation of food and feed related issues, on the basis of the size of anticipated health impact

DEFF Research Database (Denmark)

van der Fels-Klerx, H. J.; van Asselt, E. D.; Raley, M.

, an overarching framework was developed for selection of the appropriate method(s) that could be used for risk ranking of feed and food related hazards, on the basis of human health impact. This framework has the format of a decision tool, with which – given the characteristics of the risk ranking question...... at hand - the most appropriate method(s) can be selected. Application of this overall framework to several case studies showed it can be a useful tool for risk managers/assessors to select the most suitable method for risk ranking of feed/food and diet related hazards, on the basis of expected human......This study aimed to critically review methodologies for ranking of risks related to feed/food safety and nutritional hazards, on the basis of their anticipated human health impact. An extensive systematic literature review was performed to identify and characterize the available methodologies...

Enhancing the Ranking of a Web Page in the Ocean of Data

Directory of Open Access Journals (Sweden)

Hitesh KUMAR SHARMA

2013-10-01

Full Text Available In today's world, web is considered as ocean of data and information (like text, videos, multimedia etc. consisting of millions and millions of web pages in which web pages are linked with each other like a tree. It is often argued that, especially considering the dynamic of the internet, too much time has passed since the scientific work on PageRank, as that it still could be the basis for the ranking methods of the Google search engine. There is no doubt that within the past years most likely many changes, adjustments and modifications regarding the ranking methods of Google have taken place, but PageRank was absolutely crucial for Google's success, so that at least the fundamental concept behind PageRank should still be constitutive. This paper describes the components which affects the ranking of the web pages and helps in increasing the popularity of web site. By adapting these factors website developers can increase their site's page rank and within the PageRank concept, considering the rank of a document is given by the rank of those documents which link to it. Their rank again is given by the rank of documents which link to them. The PageRank of a document is always determined recursively by the PageRank of other documents.

Expanding the landscape of N=2 rank 1 SCFTs

International Nuclear Information System (INIS)

Argyres, Philip C.; Lotito, Matteo; Lü, Yongchao; Martone, Mario

2016-01-01

We refine our previous proposal http://arxiv.org/abs/1505.04814http://arxiv.org/abs/1601.00011P. Argyres, M. Lotito, Y. Lü and M. Martone, Geometric constraints on the space of N=2 SCFTs III: enhanced Coulomb branches and central charges, to appear. for systematically classifying 4d rank-1 N=2 SCFTs by constructing their possible Coulomb branch geometries. Four new recently discussed rank-1 theories http://dx.doi.org/10.1007/JHEP03(2016)083http://arxiv.org/abs/1601.02077, including novel N=3 SCFTs, sit beautifully in our refined classification framework. By arguing for the consistency of their RG flows we can make a strong case for the existence of at least four additional rank-1 SCFTs, nearly doubling the number of known rank-1 SCFTs. The refinement consists of relaxing the assumption that the flavor symmetries of the SCFTs have no discrete factors. This results in an enlarged (but finite) set of possible rank-1 SCFTs. Their existence can be further constrained using consistency of their central charges and RG flows.

Construction Project Success ranking through the Data Envelopment Analysis

Directory of Open Access Journals (Sweden)

Mazyar Zahedi-Seresht

2014-09-01

Full Text Available The purpose of this paper is to rank construction projects' success in a post delivery phase. To attain this objective, a data envelopment analysis (DEA approach is used. The model's output is a project success index which is calculated based on five project success criteria. These criteria which are determined by a two-round Delphi questionnaire survey are time performance, cost performance, quality, HSE, and customer satisfaction. The input factors which have effects on the output measures are Organizational Sponsorship, Project Manager Competency, Customer Organization, Project Operational Environment and Organizational Experience. The tool adopted to determine these factors is questionnaire. This model is applied for 9 projects with different importance of output and input factors and the reasonable result is achieved for ranking these projects.

Cross-cultural differences in processing of architectural ranking: evidence from an event-related potential study.

Science.gov (United States)

Mecklinger, Axel; Kriukova, Olga; Mühlmann, Heiner; Grunwald, Thomas

2014-01-01

Visual object identification is modulated by perceptual experience. In a cross-cultural ERP study we investigated whether cultural expertise determines how buildings that vary in their ranking between high and low according to the Western architectural decorum are perceived. Two groups of German and Chinese participants performed an object classification task in which high- and low-ranking Western buildings had to be discriminated from everyday life objects. ERP results indicate that an early stage of visual object identification (i.e., object model selection) is facilitated for high-ranking buildings for the German participants, only. At a later stage of object identification, in which object knowledge is complemented by information from semantic and episodic long-term memory, no ERP evidence for cultural differences was obtained. These results suggest that the identification of architectural ranking is modulated by culturally specific expertise with Western-style architecture already at an early processing stage.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

2014-01-01

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

Ranking of integration factors within supply chains of forward and backward types - recommendations from researches

Directory of Open Access Journals (Sweden)

Bernd Hentschel

2015-06-01

Full Text Available Background: Integration trends are one of main determinants of the development of modern logistics. After the period of interest focused mainly on supply chains realizing one-way flows only, at present there is a time for supply chains characterized by two-way flows, realizing at the same time both forward and backward flows. The possibility of various configurations of such chains requires identification of integration factors and determination of their influence on the results of the whole supply chain. Experiences of the science as well as the practice of supply chains show the urgent need of learning of reasons of the integration within supply chains of the two-way type.  Material and methods: The researches on modeling and simulation of integration processes within supply chains of forward and backward type were carried out in the environment of iGrafx Process 2013 for Six Sigma. The empirical material obtained in these researches was put to the statistical analysis by the used of Minitab 17. The identification of the significance of differences was made with the help of analysis of variance ANOVA. Additionally the analysis of differences in form of absolute averages was made.  The following measures are main ones for the evaluation of the integration of a supply chain of forward and backward types: cashflow, profitability, service level.  Results: 8 192 simulation experiments were made for 6 integration factors: accessibility of recycled materials, production planning, stock management, integration of transport, unification of packing materials and optimization of the material flow. Based on the analysis of the significance and values of differences, the results of the influence of each integration factor on global results of supply chains of forward and backward type were obtained. They were used to prepare the ranking of integration factors. The main factors, forming the integration shape of two-way supply chains were: stock

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Directory of Open Access Journals (Sweden)

Zhengnan Huang

2017-12-01

Full Text Available Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark

Energy Technology Data Exchange (ETDEWEB)

Gittens, Alex; Kottalam, Jey; Yang, Jiyan; Ringenburg, Michael, F.; Chhugani, Jatin; Racah, Evan; Singh, Mohitdeep; Yao, Yushu; Fischer, Curt; Ruebel, Oliver; Bowen, Benjamin; Lewis, Norman, G.; Mahoney, Michael, W.; Krishnamurthy, Venkat; Prabhat, Mr

2017-07-27

We investigate the performance and scalability of the randomized CX low-rank matrix factorization and demonstrate its applicability through the analysis of a 1TB mass spectrometry imaging (MSI) dataset, using Apache Spark on an Amazon EC2 cluster, a Cray XC40 system, and an experimental Cray cluster. We implemented this factorization both as a parallelized C implementation with hand-tuned optimizations and in Scala using the Apache Spark high-level cluster computing framework. We obtained consistent performance across the three platforms: using Spark we were able to process the 1TB size dataset in under 30 minutes with 960 cores on all systems, with the fastest times obtained on the experimental Cray cluster. In comparison, the C implementation was 21X faster on the Amazon EC2 system, due to careful cache optimizations, bandwidth-friendly access of matrices and vector computation using SIMD units. We report these results and their implications on the hardware and software issues arising in supporting data-centric workloads in parallel and distributed environments.

Global network centrality of university rankings

Science.gov (United States)

Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

2017-10-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

A network-based dynamical ranking system for competitive sports

Science.gov (United States)

Motegi, Shun; Masuda, Naoki

2012-12-01

From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

An application of multiple criteria decision-making techniques for ranking different national Iranian oil refining and distribution companies

Directory of Open Access Journals (Sweden)

Ibrahim Nazari

2012-10-01

Full Text Available Performance measurement plays an essential role on management of governmental agencies especially when profitability is not the primary concern and we need to consider other important factors than profitability such as customer satisfaction, etc. In this paper, we propose a multi-criteria decision making method to rank different national Iranian oil refining and distribution companies. The proposed study of this paper uses six factors including per capita supply, energy cost, physical productivity of labor, staff participation, quality control inspection of stations and education per capita. The proposed study uses Entropy to find the relative importance of each criterion and TOPSIS to rank 37 alternatives based on cities and three regions. The results of the implementation of our method indicate that central regions close to capital city of the country maintains the highest ranking (0.9122 while southern regions maintains the lowest comes in the lowest priority (0.0569 and the northern region is in the middle (0.7635.

Low-rank coal study. Volume 4. Regulatory, environmental, and market analyses

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

The regulatory, environmental, and market constraints to development of US low-rank coal resources are analyzed. Government-imposed environmental and regulatory requirements are among the most important factors that determine the markets for low-rank coal and the technology used in the extraction, delivery, and utilization systems. Both state and federal controls are examined, in light of available data on impacts and effluents associated with major low-rank coal development efforts. The market analysis examines both the penetration of existing markets by low-rank coal and the evolution of potential markets in the future. The electric utility industry consumes about 99 percent of the total low-rank coal production. This use in utility boilers rose dramatically in the 1970's and is expected to continue to grow rapidly. In the late 1980's and 1990's, industrial direct use of low-rank coal and the production of synthetic fuels are expected to start growing as major new markets.

Development of a new biofidelity ranking system for anthropomorphic test devices.

Science.gov (United States)

Rhule, Heather H; Maltese, Matthew R; Donnelly, Bruce R; Eppinger, Rolf H; Brunner, Jill K; Bolte, John H

2002-11-01

A new biofidelity assessment system is being developed and applied to three side impact dummies: the WorldSID-alpha, the ES-2 and the SID-HIII. This system quantifies (1) the ability of a dummy to load a vehicle as a cadaver does, "External Biofidelity," and (2) the ability of a dummy to replicate those cadaver responses that best predict injury potential, "Internal Biofidelity." The ranking system uses cadaver and dummy responses from head drop tests, thorax and shoulder pendulum tests, and whole body sled tests. Each test condition is assigned a weight factor based on the number of human subjects tested to form the biomechanical response corridor and how well the biofidelity tests represent FMVSS 214, side NCAP (SNCAP) and FMVSS 201 Pole crash environments. For each response requirement, the cumulative variance of the dummy response relative to the mean cadaver response (DCV) and the cumulative variance of the mean cadaver response relative to the mean plus one standard deviation (CCV) are calculated. The ratio of DCV/CCV expresses how well the dummy response duplicates the mean cadaver response: a smaller ratio indicating better biofidelity. For each test condition, the square root is taken of each Response Comparison Value (DCV/CCV), and then these values are averaged and multiplied by the appropriate Test Condition Weight. The weighted and averaged comparison values are then summed and divided by the sum of the Test Condition Weights to obtain a rank for each body region. Each dummy obtains an overall rank for External Biofidelity and an overall rank for Internal Biofidelity comprised of an average of the ranks from each body region. Of the three dummies studied, the selected comparison test data indicate that the WorldSID-alpha prototype dummy demonstrated the best overall External Biofidelity although improvement is needed in all of the dummies to better replicate human kinematics. All three dummies estimate potential injury assessment with similar levels of

GROWTH OF CORMORANT PHALACROCORAX-CARBO-SINENSIS CHICKS IN RELATION TO BROOD SIZE, AGE RANKING AND PARENTAL FISHING EFFORT

NARCIS (Netherlands)

PLATTEEUW, M; KOFFIJBERG, K; DUBBELDAM, W

1995-01-01

Growth parameters of Cormorant hatchlings are described in relation to brood size and age ranking of each chick within individual broods. Growth rates, expressed as body mass increment per day over the period of linear, growth (5-30 days), ranged from 56.4-102.8 g . d(-1) and were found to be

Time evolution of Wikipedia network ranking

Science.gov (United States)

Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

2013-12-01

We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

Low rank magnetic resonance fingerprinting.

Science.gov (United States)

Mazor, Gal; Weizman, Lior; Tal, Assaf; Eldar, Yonina C

2016-08-01

Magnetic Resonance Fingerprinting (MRF) is a relatively new approach that provides quantitative MRI using randomized acquisition. Extraction of physical quantitative tissue values is preformed off-line, based on acquisition with varying parameters and a dictionary generated according to the Bloch equations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore high under-sampling ratio in the sampling domain (k-space) is required. This under-sampling causes spatial artifacts that hamper the ability to accurately estimate the quantitative tissue values. In this work, we introduce a new approach for quantitative MRI using MRF, called Low Rank MRF. We exploit the low rank property of the temporal domain, on top of the well-known sparsity of the MRF signal in the generated dictionary domain. We present an iterative scheme that consists of a gradient step followed by a low rank projection using the singular value decomposition. Experiments on real MRI data demonstrate superior results compared to conventional implementation of compressed sensing for MRF at 15% sampling ratio.

Life history in male mandrills (Mandrillus sphinx): physical development, dominance rank, and group association.

Science.gov (United States)

Setchell, Joanna M; Wickings, E Jean; Knapp, Leslie A

2006-12-01

We assess life history from birth to death in male mandrills (Mandrillus sphinx) living in a semifree-ranging colony in Gabon, using data collected for 82 males that attained at least the age of puberty, including 33 that reached adulthood and 25 that died, yielding data for their entire lifespan. We describe patterns of mortality and injuries, dominance rank, group association, growth and stature, and secondary sexual character expression across the male lifespan. We examine relationships among these variables and investigate potential influences on male life history, including differences in the social environment (maternal rank and group demography) and early development, with the aim of identifying characteristics of successful males. Sons of higher-ranking females were more likely to survive to adulthood than sons of low-ranking females. Adolescent males varied consistently in the rate at which they developed, and this variation was related to a male's own dominance rank. Males with fewer peers and sons of higher-ranking and heavier mothers also matured faster. However, maternal variables were not significantly related to dominance rank during adolescence, the age at which males attained adult dominance rank, or whether a male became alpha male. Among adult males, behavior and morphological development were related to a male's own dominance rank, and sons of high-ranking females were larger than sons of low-ranking females. Alpha males were always the most social, and the most brightly colored males, but were not necessarily the largest males present. Finally, alpha male tenure was related to group demography, with larger numbers of rival adult males and maturing adolescent males reducing the time a male spent as alpha male. Tenure did not appear to be related to characteristics of the alpha male himself. 2006 Wiley-Liss, Inc.

Activity of coals of different rank to ozone

Directory of Open Access Journals (Sweden)

Vladimir Kaminskii

2017-12-01

Full Text Available Coals of different rank were studied in order to characterize their activity to ozone decomposition and changes of their properties at interaction with ozone. Effects of coal rank on their reactivity to ozone were described by means of kinetic modeling. To this end, a model was proposed for evaluation of kinetic parameters describing coals activity to ozone. This model considers a case when coals surface properties change during interaction with ozone (deactivation processes. Two types of active sites (zones at the surface that are able to decompose ozone were introduced in the model differing by their deactivation rates. Activity of sites that are being deactivated at relatively higher rate increases with rank from 2400 1/min for lignite to 4000 1/min for anthracite. Such dependence is related to increase of micropores share in coals structure that grows from lignites to anthracites. Parameter characterizing initial total activity of coals to ozone decomposition also depends on rank by linear trend and vary between 2.40 for lignites up to 4.98 for anthracite. The proposed model could further be used in studies of coals oxidation processes and tendency to destruction under the weathering and oxidation conditions.

Impact factor (if) of hospitality, leisure, sports & tourism journals: current trends, overall ranking and temporal stability over a four year period

OpenAIRE

Sans-Rosell, Nuria; Reverter Masià, Joaquín; Hernández González, Vicenç

2013-01-01

A journal’s “impact factor” (IF) is the bibliometric index that reflects the frequency with which an ‘‘average article’’ from a scientific journal has been cited in subsequent publications.The purpose of the present study is to examine the current impact factor of Hospitality, Leisure, Sports & Tourism journals, their overall ranking and temporal stability over a four year period. For this reason, we have included the impact factor of the scientific journals classifiedin the “Hospitality,...

Multiple graph regularized protein domain ranking.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Citation analysis of mental health nursing journals: how should we rank thee?

Science.gov (United States)

Hunt, Glenn E; Happell, Brenda; Chan, Sally W-C; Cleary, Michelle

2012-12-01

The journal impact factor (JIF), and how best to rate the performance of a journal and the articles they contain, are areas of great debate. The aim of this paper was to assess various ranking methods of journal quality for mental health nursing journals, and to list the top 10 articles that have received the most number of citations to date. Seven mental health nursing journals were chosen for the analysis of citations they received in 2010, as well as their current impact factors from two sources, and other data for ranking purposes. There was very little difference in the top four mental health nursing journals and their overall rankings when combining various bibliometric indicators. That said, the International Journal of Mental Health Nursing is currently the highest ranked mental health nursing journal based on JIF, but publishes fewer articles per year compared to other journals. Overall, very few articles received 50 or more citations. This study shows that researchers need to consider more than one ranking method when deciding where to send or publish their research. © 2012 The Authors. International Journal of Mental Health Nursing © 2012 Australian College of Mental Health Nurses Inc.

A stable systemic risk ranking in China's banking sector: Based on principal component analysis

Science.gov (United States)

Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

2018-02-01

In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

Multiplex PageRank.

Directory of Open Access Journals (Sweden)

Arda Halu

Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Multiplex PageRank.

Science.gov (United States)

Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

2013-01-01

Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan

2012-11-19

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-01-01

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

Directory of Open Access Journals (Sweden)

Wang Jim

2012-11-01

Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Opportunities in low-rank coal applications for synfuels and power industries in Mexico

International Nuclear Information System (INIS)

Winch, R.A.; Alejandro, I.; Hernandez, G.

1992-01-01

The utilization of domestic coal is an important ingredient in the generation strategy of electricity in Mexico. The relative ranking of the MICARE and Sabinas coals, compared to other coals tested at the Energy and Environmental Research Center (EERC) pilot test facility at Grand Forks is an important factor for future economic fuel studies. A test comparison between US and Mexican coals was made and observations are listed

Improving Ranking Using Quantum Probability

OpenAIRE

Melucci, Massimo

2011-01-01

The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

How Many Alternatives Can Be Ranked? A Comparison of the Paired Comparison and Ranking Methods.

Science.gov (United States)

Ock, Minsu; Yi, Nari; Ahn, Jeonghoon; Jo, Min-Woo

2016-01-01

To determine the feasibility of converting ranking data into paired comparison (PC) data and suggest the number of alternatives that can be ranked by comparing a PC and a ranking method. Using a total of 222 health states, a household survey was conducted in a sample of 300 individuals from the general population. Each respondent performed a PC 15 times and a ranking method 6 times (two attempts of ranking three, four, and five health states, respectively). The health states of the PC and the ranking method were constructed to overlap each other. We converted the ranked data into PC data and examined the consistency of the response rate. Applying probit regression, we obtained the predicted probability of each method. Pearson correlation coefficients were determined between the predicted probabilities of those methods. The mean absolute error was also assessed between the observed and the predicted values. The overall consistency of the response rate was 82.8%. The Pearson correlation coefficients were 0.789, 0.852, and 0.893 for ranking three, four, and five health states, respectively. The lowest mean absolute error was 0.082 (95% confidence interval [CI] 0.074-0.090) in ranking five health states, followed by 0.123 (95% CI 0.111-0.135) in ranking four health states and 0.126 (95% CI 0.113-0.138) in ranking three health states. After empirically examining the consistency of the response rate between a PC and a ranking method, we suggest that using five alternatives in the ranking method may be superior to using three or four alternatives. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Selection and ranking of patient video cases in paediatric neurology in relation to learner levels.

Science.gov (United States)

Balslev, Thomas; Muijtjens, Arno M M; Maarbjerg, Sabine Frølich; de Grave, Willem

2018-05-01

Teaching and learning with patient video cases may add authenticity, enhance diagnostic accuracy and improve chances of early diagnosis. The aim of this study is firstly to identify selection criteria for key Patient video cases (PVCs), secondly to identify trends in relevance of PVCs for learner levels and thirdly, to rank PVCs for learner levels. Based on a literature review, we identified criteria for key PVCs for use in paediatric neurology. We then performed a multi-round Delphi analysis to obtain agreement between 28 expert clinician teachers concerning key PVCs for four learner levels. We identified two major criteria: key PVCs should demonstrate key movements, and these movements should be subtle and/or difficult to note. The expert clinician teachers subsequently assessed a list of 14 topics for key PVCs. We found a clear, increasing trend in relevance scores, from medical students to young residents to experienced residents and specialists. For medical students and residents, epileptic spasms, Down syndrome, developmental delay, cerebral palsy and absence epilepsy were highly ranked. For specialists, conditions like chorea, focal seizures or eye movement disorders topped the ranking list, although ranking was less clear for this group of advanced learners. Key PVCs should demonstrate movements that are difficult to note for learners. Ranked lists of key PVCs for teaching and learning at different learner levels are now available and may help institutions build validated local libraries of PVCs. Copyright © 2017 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Multimodal biometric system using rank-level fusion approach.

Science.gov (United States)

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles

Science.gov (United States)

Eom, Young-Ho; Shepelyansky, Dima L.

2013-01-01

How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013 PMID:24098338

Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.

Directory of Open Access Journals (Sweden)

Young-Ho Eom

Full Text Available How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013.

Incorporating the surfing behavior of web users into PageRank

OpenAIRE

Ashyralyyev, Shatlyk

2013-01-01

Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013. Thesis (Master's) -- Bilkent University, 2013. Includes bibliographical references leaves 68-73 One of the most crucial factors that determines the effectiveness of a large-scale commercial web search engine is the ranking (i.e., order) in which web search results are presented to the end user. In modern web search engines, the skeleton for the rank...

Escaping the repugnant conclusion: rank-discounted utilitarianism with variable population

OpenAIRE

Asheim, Geir Bjarne; Zuber, Stéphane

2014-01-01

We contribute to population ethics by proposing and axiomatizing rank-discounted critical-level generalized utilitarianism (RDCLU). Population ethics is needed for evaluation of policies, e.g., concerning climate change, where population size depends on the chosen policy. We show that critical-level generalized utilitarianism and (a version of) critical-level leximin are the limits of RDCLU for extreme values of the rank utility discount factor. Moreover, we establish how RDCLU avoids serious...

How Prospective Physical Medicine and Rehabilitation Trainees Rank Residency Training Programs.

Science.gov (United States)

Auriemma, Michael J; Whitehair, Curtis L

2018-03-01

Since the inception of the National Resident Matching Program, multiple studies have investigated the factors applicants consider important to ranking prospective residency programs. However, only 2 previous studies focused on prospective physical medicine and rehabilitation (PM&R) trainees, and the most recent of these studies was published in 1993. It is unknown whether these previous studies are reflective of current prospective PM&R residents. To assess various factors that contribute to prospective PM&R residents' decision making in choosing a residency program and compare these findings with previous studies. An anonymous, voluntary questionnaire. A single PM&R residency program. All applicants to a single PM&R residency program. All applicants to our PM&R residency program were invited to participate in a 44-item, 5-point Likert-based questionnaire. Applicants were asked to rate the importance of various factors as they related to constructing their residency rank list. Means and standard deviations were calculated for items included in the survey. A response rate of 26% was obtained, with the responses of 98 applicants (20%) ultimately analyzed. The highest rated factors included "perceived happiness of current residents," "opportunities for hands-on procedure training," "perceived camaraderie among current residents," "perceived camaraderie among faculty and current residents," "perceived quality of current residents," and "perceived work/life balance among current residents." Although male and female respondents demonstrated similar ranking preferences, an apparent difference was detected between how genders rated the importance of "whether the program projects a favorable environment for women" and "whether the program projects a favorable environment for minorities." As compared with previous PM&R applicants, current prospective trainees seem to place greater importance on skill acquisition over didactic teaching. Prospective PM&R residents highly value

Wikipedia ranking of world universities

Science.gov (United States)

Lages, José; Patt, Antoine; Shepelyansky, Dima L.

2016-03-01

We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the reliable features of this approach. At the same time WRWU incorporates all knowledge accumulated at 24 Wikipedia editions giving stronger highlights for historically important universities leading to a different estimation of efficiency of world countries in university education. The historical development of university ranking is analyzed during ten centuries of their history.

AP600 passive containment cooling system phenomena identification and ranking table

International Nuclear Information System (INIS)

Spencer, D.R.; Woodcock, Joel

1999-01-01

This paper presents the Phenomena Identification and Ranking Table (PIRT) used in the containment Design Basis Analysis (DBA) for the AP600 nuclear power plant. The PIRT is a tool generally applied to best estimate thermal hydraulic analyses. In the conservative analytical modeling approach used for the AP600 DBA containment pressure response, the PIRT was a tool used to show completeness and relevance of the test database in accordance with the Code of Federal Regulations for advanced plant design. Additionally, the ranking of phenomena by relative importance in a PIRT allows appropriate focusing of resources during model development and licensing review. The focus of the paper is on the organization and structure of the PIRT to show level of detail and format accepted for the AP600, for potential application to other containment designs or accident scenarios. Conclusions of general interest are discussed regarding table organization and structure, the process for developing relative ranking and incorporating expert opinion, and the definition and usage of the relative ranking in support of the conservative evaluation model. The AP600 containment evaluation model approach, as influenced by the relative rankings, is briefly described to put into context this unique application of the PIRT to a conservative methodology. The bases for relative ranking of each phenomenon, which included expert opinion, and quantitative results of scaling and testing, was submitted to the NRC as part of AP600-specific evaluations. Since a PIRT supports the sufficiency of both a testing program and analytical modeling, the process followed to generate and confirm the PIRT, an important part of the licensing acceptance, was a focus of extensive NRC review. General descriptions of key phenomena are provided to aid in understanding the containment PIRT for more general applications for containment evaluations of other PWR designs or for other scenarios. (author)

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

Science.gov (United States)

Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

2017-08-18

Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

Ranking Canadian oil and gas projects using TOPSIS

Directory of Open Access Journals (Sweden)

Seyed Jafar Sadjadi

2017-08-01

Full Text Available One of the primary concerns for investment in oil and gas projects is to have a comprehensive understanding on different issues associated with this industry. The industry is mainly influ-enced by the price of oil and gas and in some events, many production units have been forced to shut down solely because of low price of oil and gas. Environmental issues are other important factors, which may put pressure on Canada’s political affairs since the country has strong com-mitment to reduce green gas effect. In this paper, we introduce a multi-criteria decision making method, which helps us rank different projects in terms of investment. The proposed study con-siders different investment factors including net present value, rate of return, benefit-cost analy-sis and payback period along with the intensity of green gas effects for ranking the present oil and gas projects in Canada.

Econophysics of a ranked demand and supply resource allocation problem

Science.gov (United States)

Priel, Avner; Tamir, Boaz

2018-01-01

We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees.

MRI reconstruction of multi-image acquisitions using a rank regularizer with data reordering

Energy Technology Data Exchange (ETDEWEB)

Adluru, Ganesh, E-mail: gadluru@gmail.com; Anderson, Jeffrey [UCAIR, Department of Radiology, University of Utah, Salt Lake City, Utah 84108 (United States); Gur, Yaniv [IBM Almaden Research Center, San Jose, California 95120 (United States); Chen, Liyong; Feinberg, David [Advanced MRI Technologies, Sebastpool, California, 95472 (United States); DiBella, Edward V. R. [UCAIR, Department of Radiology, University of Utah, Salt Lake City, Utah 84108 and Department of Bioengineering, University of Utah, Salt Lake City, Utah 84112 (United States)

2015-08-15

Purpose: To improve rank constrained reconstructions for undersampled multi-image MRI acquisitions. Methods: Motivated by the recent developments in low-rank matrix completion theory and its applicability to rapid dynamic MRI, a new reordering-based rank constrained reconstruction of undersampled multi-image data that uses prior image information is proposed. Instead of directly minimizing the nuclear norm of a matrix of estimated images, the nuclear norm of reordered matrix values is minimized. The reordering is based on the prior image estimates. The method is tested on brain diffusion imaging data and dynamic contrast enhanced myocardial perfusion data. Results: Good quality images from data undersampled by a factor of three for diffusion imaging and by a factor of 3.5 for dynamic cardiac perfusion imaging with respiratory motion were obtained. Reordering gave visually improved image quality over standard nuclear norm minimization reconstructions. Root mean squared errors with respect to ground truth images were improved by ∼18% and ∼16% with reordering for diffusion and perfusion applications, respectively. Conclusions: The reordered low-rank constraint is a way to inject prior image information that offers improvements over a standard low-rank constraint for undersampled multi-image MRI reconstructions.

MRI reconstruction of multi-image acquisitions using a rank regularizer with data reordering

International Nuclear Information System (INIS)

Adluru, Ganesh; Anderson, Jeffrey; Gur, Yaniv; Chen, Liyong; Feinberg, David; DiBella, Edward V. R.

2015-01-01

Purpose: To improve rank constrained reconstructions for undersampled multi-image MRI acquisitions. Methods: Motivated by the recent developments in low-rank matrix completion theory and its applicability to rapid dynamic MRI, a new reordering-based rank constrained reconstruction of undersampled multi-image data that uses prior image information is proposed. Instead of directly minimizing the nuclear norm of a matrix of estimated images, the nuclear norm of reordered matrix values is minimized. The reordering is based on the prior image estimates. The method is tested on brain diffusion imaging data and dynamic contrast enhanced myocardial perfusion data. Results: Good quality images from data undersampled by a factor of three for diffusion imaging and by a factor of 3.5 for dynamic cardiac perfusion imaging with respiratory motion were obtained. Reordering gave visually improved image quality over standard nuclear norm minimization reconstructions. Root mean squared errors with respect to ground truth images were improved by ∼18% and ∼16% with reordering for diffusion and perfusion applications, respectively. Conclusions: The reordered low-rank constraint is a way to inject prior image information that offers improvements over a standard low-rank constraint for undersampled multi-image MRI reconstructions

Returns to Tenure: Time or Rank?

DEFF Research Database (Denmark)

Buhai, Ioan Sebastian

-specific investment, efficiency-wages or adverse-selection models. However, rent extracting arguments as suggested by the theory of internal labor markets, indicate that the relative position of the worker in the seniority hierarchy of the firm, her 'seniority rank', may also explain part of the observed returns...... relative to their peer workers), as predicted by theories on unionized and insider-outsider markets....

Irreversible inhibition of RANK expression as a possible mechanism for IL-3 inhibition of RANKL-induced osteoclastogenesis

Energy Technology Data Exchange (ETDEWEB)

Khapli, Shruti M.; Tomar, Geetanjali B.; Barhanpurkar, Amruta P.; Gupta, Navita; Yogesha, S.D.; Pote, Satish T. [National Center for Cell Science, University of Pune Campus, Pune 411 007 (India); Wani, Mohan R., E-mail: mohanwani@nccs.res.in [National Center for Cell Science, University of Pune Campus, Pune 411 007 (India)

2010-09-03

Research highlights: {yields} IL-3 inhibits receptor activator of NF-{kappa}B ligand (RANKL)-induced osteoclastogenesis. {yields} IL-3 inhibits RANKL-induced JNK activation. {yields} IL-3 down-regulates expression of c-Fos and NFATc1 transcription factors. {yields} IL-3 down-regulates RANK expression posttranscriptionally and irreversibly. {yields} IL-3 inhibits in vivo RANK expression. -- Abstract: IL-3, a cytokine secreted by activated T lymphocytes, stimulates the proliferation, differentiation and survival of pluripotent hematopoietic stem cells. In this study, we investigated the mechanism of inhibitory action of IL-3 on osteoclast differentiation. We show here that IL-3 significantly inhibits receptor activator of NF-{kappa}B (RANK) ligand (RANKL)-induced activation of c-Jun N-terminal kinase (JNK). IL-3 down-regulates expression of c-Fos and nuclear factor of activated T cells (NFATc1) transcription factors. In addition, IL-3 down-regulates RANK expression posttranscriptionally in both purified osteoclast precursors and whole bone marrow cells. Furthermore, the inhibitory effect of IL-3 on RANK expression was irreversible. Interestingly, IL-3 inhibits in vivo RANK expression in mice. Thus, we provide the first evidence that IL-3 irreversibly inhibits RANK expression that results in inhibition of important signaling molecules induced by RANKL.

Irreversible inhibition of RANK expression as a possible mechanism for IL-3 inhibition of RANKL-induced osteoclastogenesis

International Nuclear Information System (INIS)

Khapli, Shruti M.; Tomar, Geetanjali B.; Barhanpurkar, Amruta P.; Gupta, Navita; Yogesha, S.D.; Pote, Satish T.; Wani, Mohan R.

2010-01-01

Research highlights: → IL-3 inhibits receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis. → IL-3 inhibits RANKL-induced JNK activation. → IL-3 down-regulates expression of c-Fos and NFATc1 transcription factors. → IL-3 down-regulates RANK expression posttranscriptionally and irreversibly. → IL-3 inhibits in vivo RANK expression. -- Abstract: IL-3, a cytokine secreted by activated T lymphocytes, stimulates the proliferation, differentiation and survival of pluripotent hematopoietic stem cells. In this study, we investigated the mechanism of inhibitory action of IL-3 on osteoclast differentiation. We show here that IL-3 significantly inhibits receptor activator of NF-κB (RANK) ligand (RANKL)-induced activation of c-Jun N-terminal kinase (JNK). IL-3 down-regulates expression of c-Fos and nuclear factor of activated T cells (NFATc1) transcription factors. In addition, IL-3 down-regulates RANK expression posttranscriptionally in both purified osteoclast precursors and whole bone marrow cells. Furthermore, the inhibitory effect of IL-3 on RANK expression was irreversible. Interestingly, IL-3 inhibits in vivo RANK expression in mice. Thus, we provide the first evidence that IL-3 irreversibly inhibits RANK expression that results in inhibition of important signaling molecules induced by RANKL.

University Rankings and Social Science

OpenAIRE

Marginson, S.

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real outputs are of no common value. It is necessary that rankings be soundly based in scientific terms if a virtuous relationship between performance and...

University Rankings: How Well Do They Measure Library Service Quality?

Science.gov (United States)

Jackson, Brian

2015-01-01

University rankings play an increasingly large role in shaping the goals of academic institutions and departments, while removing universities themselves from the evaluation process. This study compares the library-related results of two university ranking publications with scores on the LibQUAL+™ survey to identify if library service quality--as…

24 CFR 599.401 - Ranking of applications.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 3 2010-04-01 2010-04-01 false Ranking of applications. 599.401... Communities § 599.401 Ranking of applications. (a) Ranking order. Rural and urban applications will be ranked... applications ranked first. (b) Separate ranking categories. After initial ranking, both rural and urban...

On Page Rank

NARCIS (Netherlands)

Hoede, C.

In this paper the concept of page rank for the world wide web is discussed. The possibility of describing the distribution of page rank by an exponential law is considered. It is shown that the concept is essentially equal to that of status score, a centrality measure discussed already in 1953 by

Citation graph based ranking in Invenio

CERN Document Server

Marian, Ludmila; Rajman, Martin; Vesely, Martin

2010-01-01

Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

Computing Principal Eigenvectors of Large Web Graphs: Algorithms and Accelerations Related to PageRank and HITS

Science.gov (United States)

Nagasinghe, Iranga

2010-01-01

This thesis investigates and develops a few acceleration techniques for the search engine algorithms used in PageRank and HITS computations. PageRank and HITS methods are two highly successful applications of modern Linear Algebra in computer science and engineering. They constitute the essential technologies accounted for the immense growth and…

Propuesta de rankings de universidades españolas en redes sociales

OpenAIRE

Zarco, Carmen (UNIR); Del-Barrio-García, Salvador; Córdon, Óscar

2016-01-01

University rankings have become popular tools to evaluate the results of academic institutions. The existing proposals of rankings of universities in Spain, based on social networking sites, show some limitations related to their lack of coverage, their specificity, and their lack of transparency in the ranking definition. The goal of this work is to introduce a general design framework for coherent classifications to analyze the impact of all Spanish universities, both public and private, in...

Ranking of microRNA target prediction scores by Pareto front analysis.

Science.gov (United States)

Sahoo, Sudhakar; Albrecht, Andreas A

2010-12-01

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts. Copyright © 2010 Elsevier Ltd. All rights reserved.

When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

KAUST Repository

Wang, Jim Jing-Yan

2017-06-28

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.

University Rankings: The Web Ranking

Science.gov (United States)

Aguillo, Isidro F.

2012-01-01

The publication in 2003 of the Ranking of Universities by Jiao Tong University of Shanghai has revolutionized not only academic studies on Higher Education, but has also had an important impact on the national policies and the individual strategies of the sector. The work gathers the main characteristics of this and other global university…

Ranking Specific Sets of Objects.

Science.gov (United States)

Maly, Jan; Woltran, Stefan

2017-01-01

Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in many applications certain elements from the entire power set might not be required and can be neglected in the ranking process. For instance, certain sets might be ruled out due to hard constraints or are not satisfying some background theory. In this paper, we treat the computational problem whether an order on a given subset of the power set of elements satisfying different variants of dominance and independence can be found, given a ranking on the elements. We show that this problem is tractable for partial rankings and NP-complete for total rankings.

Social norms and rank-based nudging: Changing willingness to pay for healthy food.

Science.gov (United States)

Aldrovandi, Silvio; Brown, Gordon D A; Wood, Alex M

2015-09-01

People's evaluations in the domain of healthy eating are at least partly determined by the choice context. We systematically test reference level and rank-based models of relative comparisons against each other and explore their application to social norms nudging, an intervention that aims at influencing consumers' behavior by addressing their inaccurate beliefs about their consumption relative to the consumption of others. Study 1 finds that the rank of a product or behavior among others in the immediate comparison context, rather than its objective attributes, influences its evaluation. Study 2 finds that when a comparator is presented in isolation the same rank-based process occurs based on information retrieved from memory. Study 3 finds that telling people how their consumption ranks within a normative comparison sample increases willingness to pay for a healthy food by over 30% relative to the normal social norms intervention that tells them how they compare to the average. We conclude that social norms interventions should present rank information (e.g., "you are in the most unhealthy 10% of eaters") rather than information relative to the average (e.g., "you consume 500 calories more than the average person"). (c) 2015 APA, all rights reserved).

Factors influencing emergency medicine physicians' management of sports-related concussions: a community-wide study.

Science.gov (United States)

Giebel, Stephen; Kothari, Rashmi; Koestner, Amy; Mohney, Gretchen; Baker, Robert

2011-12-01

Numerous guidelines to grade and manage sports-related concussions have been published. However, little is known about how frequently they are implemented in the emergency department. This study evaluates the current practices of emergency physicians (EPs) in managing sports-related concussions. To evaluate the current practice of EP evaluation and management of sports-related concussions. All EPs and emergency medicine residents in Kalamazoo County were surveyed regarding their management of sports-related concussions. The surveys obtained demographic data, participants' use of guidelines, and the importance of clinical and non-clinical factors in deciding when to allow a player to return to play. Of the 73 EP respondents, only 23% used a nationally recognized guideline, with no significant difference between attending and resident EPs. The symptomatic complaints of loss of consciousness, amnesia of the event, and difficulty concentrating were ranked most important by EPs in assessing patients with sports-related concussions. Among non-clinical factors, residents were significantly more likely than attendings to report that medical-legal, parental, and players' concerns were more likely to influence their decision in allowing a patient to return to play. EPs take into consideration important clinical factors in assessing patients with sports-related concussion. However, almost 75% do not use any nationally recognized guideline in their evaluation. Residents are more likely than attendings to be influenced by non-clinical factors. Copyright © 2011 Elsevier Inc. All rights reserved.

VisualRank: applying PageRank to large-scale image search.

Science.gov (United States)

Jing, Yushi; Baluja, Shumeet

2008-11-01

Because of the relative ease in understanding and processing text, commercial image-search systems often rely on techniques that are largely indistinguishable from text-search. Recently, academic studies have demonstrated the effectiveness of employing image-based features to provide alternative or additional signals. However, it remains uncertain whether such techniques will generalize to a large number of popular web queries, and whether the potential improvement to search quality warrants the additional computational cost. In this work, we cast the image-ranking problem into the task of identifying "authority" nodes on an inferred visual similarity graph and propose VisualRank to analyze the visual link structures among images. The images found to be "authorities" are chosen as those that answer the image-queries well. To understand the performance of such an approach in a real system, we conducted a series of large-scale experiments based on the task of retrieving images for 2000 of the most popular products queries. Our experimental results show significant improvement, in terms of user satisfaction and relevancy, in comparison to the most recent Google Image Search results. Maintaining modest computational cost is vital to ensuring that this procedure can be used in practice; we describe the techniques required to make this system practical for large scale deployment in commercial search engines.

A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

Directory of Open Access Journals (Sweden)

Yubao Sun

2015-01-01

Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

A hybrid MCDM approach for ranking suppliers by considering ethical factors

OpenAIRE

Azadfallah, Mohammad

2016-01-01

One of the negative effects of cooperating with un-ethically behaving suppliers is that it may devastate the companies' credibility among employees, customers and the public. In this paper, a hybrid Multiple Criteria Decision Making (MCDM) approach (Disjunctive-WPM method) is proposed to resolve this limitation. The proposed methods consist of the following steps: 1. drop unethical solutions and 2. rank the remaining solutions. Therefore, the aim of t...

Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Ranking Support Vector Machine with Kernel Approximation

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

University Rankings and Social Science

Science.gov (United States)

Marginson, Simon

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

The higher rank numerical range of matrix polynomials

OpenAIRE

Aretaki, Aikaterini; Maroulas, John

2011-01-01

The notion of the higher rank numerical range $\\Lambda_{k}(L(\\lambda))$ for matrix polynomials $L(\\lambda)=A_{m}\\lambda^{m}+...+A_{1}\\lambda+A_{0}$ is introduced here and some fundamental geometrical properties are investigated. Further, the sharp points of $\\Lambda_{k}(L(\\lambda))$ are defined and their relation to the numerical range $w(L(\\lambda))$ is presented. A connection of $\\Lambda_{k}(L(\\lambda))$ with the vector-valued higher rank numerical range $\\Lambda_{k}(A_{0},..., A_{m})$ is a...

Two-dimensional ranking of Wikipedia articles

Science.gov (United States)

Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.

2010-10-01

The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications.

Science.gov (United States)

Tao, Chenyang; Nichols, Thomas E; Hua, Xue; Ching, Christopher R K; Rolls, Edmund T; Thompson, Paul M; Feng, Jianfeng

2017-01-01

We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. Copyright © 2016. Published by Elsevier Inc.

Fourth-rank gravity. A progress report

International Nuclear Information System (INIS)

Tapia, V.

1992-04-01

We consider the consequences of describing the metric properties of space-time through a quartic line element. The associated ''metric'' is a fourth-rank tensor. After developing some fundamentals for such geometry, we construct a field theory for the gravitational field. This theory coincides with General Relativity in the vacuum case. Departures from General Relativity are obtained only in the presence of matter. We develop a simple cosmological model which is not in contradiction with the observed value Ω approx. 0.2-0.3 for the energy density parameter. A further application concerns conformal field theory. We are able to prove that a conformal field theory possesses an infinite-dimensional symmetry group only if the dimension of space-time is equal to the rank of the metric. In this case we are able to construct an integrable conformal field theory in four dimensions. The model is renormalisable by power counting. (author). 9 refs

Elitism, Sharing and Ranking Choices in Evolutionary Multi-Criterion Optimisation

OpenAIRE

Pursehouse, R.C.; Fleming, P.J.

2002-01-01

Elitism and sharing are two mechanisms that are believed to improve the performance of an evolutionary multi-criterion optimiser. The relative performance of of the two most popular ranking strategies is largely unknown. Using a new empirical inquiry framework, this report studies the effect of elitism, sharing and ranking design choices using a benchmark suite of two-criterion problems.........

In-Degree and PageRank of web pages: why do they follow similar power laws?

NARCIS (Netherlands)

Litvak, Nelli; Scheinhardt, Willem R.W.; Volkovich, Y.

2009-01-01

PageRank is a popularity measure designed by Google to rank Web pages. Experiments confirm that PageRank values obey a power law with the same exponent as In-Degree values. This paper presents a novel mathematical model that explains this phenomenon. The relation between PageRank and In-Degree is

Comparative study to explore factors affecting E-government ranking: the case of Malaysia, Nigeria and Republic of Korea

OpenAIRE

Wan Rozaini Sheik Osman; Hasanaein Mohamed; Muhammad Shahzad Aslam; Saima Nisar

2017-01-01

The present study aims to find out the criteria for e-government ranking generally as well as particularly focusing on Malaysia’s e-government ranking. In addition, with regard to the Malaysia’s e-government ranking, the results shown that, most of the Human Capital, Online Services and Telecommunication Infrastructure and its sub-indicators has not seen any improvement through the previous periods comparing with other countries such as Republic of Korea. Indeed, this comparative study sought...

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

Science.gov (United States)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

Relationships between nurse- and physician-to-population ratios and state health rankings.

Science.gov (United States)

Bigbee, Jeri L

2008-01-01

To evaluate the relationship between nurse-to-population ratios and population health, as indicated by state health ranking, and to compare the findings with physician-to-population ratios. Secondary analysis correlational design. The sample consisted of all 50 states in the United States. Data sources included the United Health Foundation's 2006 state health rankings, the 2004 National Sample Survey for Registered Nurses, and the U.S. Health Workforce Profile from the New York Center for Health Workforce Studies. Significant relationships between nurse-to-population ratio and overall state health ranking (rho=-.446, p tf?>=.001) and 11 of the 18 components of that ranking were found. Significant components included motor vehicle death rate, high school graduation rate, violent crime rate, infectious disease rate, percentage of children in poverty, percentage of uninsured residents, immunization rate, adequacy of prenatal care, number of poor mental health days, number of poor physical health days, and premature death rate, with higher nurse-to-population ratios associated with higher health rankings. Specialty (public health and school) nurse-to-population ratios were not as strongly related to state health ranking. Physician-to-population ratios were also significantly related to state health ranking, but were associated with different components than nurses. These findings suggest that greater nurses per capita may be uniquely associated with healthier communities; however, further multivariate research is needed.

14 CFR 1214.1105 - Final ranking.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of... preference will be included in this final ranking in accordance with applicable regulations. ...

In-degree and pageRank of web pages: Why do they follow similar power laws?

NARCIS (Netherlands)

Litvak, Nelli; Scheinhardt, Willem R.W.; Volkovich, Y.

The PageRank is a popularity measure designed by Google to rank Web pages. Experiments confirm that the PageRank obeys a 'power law' with the same exponent as the In-Degree. This paper presents a novel mathematical model that explains this phenomenon. The relation between the PageRank and In-Degree

Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models

NARCIS (Netherlands)

Hallin, M.; van den Akker, R.; Werker, B.J.M.

2012-01-01

Abstract: This paper introduces rank-based tests for the cointegrating rank in an Error Correction Model with i.i.d. elliptical innovations. The tests are asymptotically distribution-free, and their validity does not depend on the actual distribution of the innovations. This result holds despite the

Universal scaling in sports ranking

International Nuclear Information System (INIS)

Deng Weibing; Li Wei; Cai Xu; Bulou, Alain; Wang Qiuping A

2012-01-01

Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters. (paper)

Maximising information recovery from rank-order codes

Science.gov (United States)

Sen, B.; Furber, S.

2007-04-01

The central nervous system encodes information in sequences of asynchronously generated voltage spikes, but the precise details of this encoding are not well understood. Thorpe proposed rank-order codes as an explanation of the observed speed of information processing in the human visual system. The work described in this paper is inspired by the performance of SpikeNET, a biologically inspired neural architecture using rank-order codes for information processing, and is based on the retinal model developed by VanRullen and Thorpe. This model mimics retinal information processing by passing an input image through a bank of Difference of Gaussian (DoG) filters and then encoding the resulting coefficients in rank-order. To test the effectiveness of this encoding in capturing the information content of an image, the rank-order representation is decoded to reconstruct an image that can be compared with the original. The reconstruction uses a look-up table to infer the filter coefficients from their rank in the encoded image. Since the DoG filters are approximately orthogonal functions, they are treated as their own inverses in the reconstruction process. We obtained a quantitative measure of the perceptually important information retained in the reconstructed image relative to the original using a slightly modified version of an objective metric proposed by Petrovic. It is observed that around 75% of the perceptually important information is retained in the reconstruction. In the present work we reconstruct the input using a pseudo-inverse of the DoG filter-bank with the aim of improving the reconstruction and thereby extracting more information from the rank-order encoded stimulus. We observe that there is an increase of 10 - 15% in the information retrieved from a reconstructed stimulus as a result of inverting the filter-bank.

On Locally Most Powerful Sequential Rank Tests

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 36, č. 1 (2017), s. 111-125 ISSN 0747-4946 R&D Projects: GA ČR GA17-07384S Grant - others:Nadační fond na podporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : nonparametric test s * sequential ranks * stopping variable Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 0.339, year: 2016

Recurrent fuzzy ranking methods

Science.gov (United States)

Hajjari, Tayebeh

2012-11-01

With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

Fourth-rank cosmology

International Nuclear Information System (INIS)

Marrakchi, A.E.L.; Tapia, V.

1992-05-01

Some cosmological implications of the recently proposed fourth-rank theory of gravitation are studied. The model exhibits the possibility of being free from the horizon and flatness problems at the price of introducing a negative pressure. The field equations we obtain are compatible with k obs =0 and Ω obs t clas approx. 10 20 t Planck approx. 10 -23 s. When interpreted at the light of General Relativity the treatment is shown to be almost equivalent to that of the standard model of cosmology combined with the inflationary scenario. Hence, an interpretation of the negative pressure hypothesis is provided. (author). 8 refs

A new mutually reinforcing network node and link ranking algorithm.

Science.gov (United States)

Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E

2015-10-23

This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

A new mutually reinforcing network node and link ranking algorithm

Science.gov (United States)

Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

2015-10-01

This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

A new mutually reinforcing network node and link ranking algorithm

Science.gov (United States)

Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

2015-01-01

This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity. PMID:26492958

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

Science.gov (United States)

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

Preference Learning and Ranking by Pairwise Comparison

Science.gov (United States)

Fürnkranz, Johannes; Hüllermeier, Eyke

This chapter provides an overview of recent work on preference learning and ranking via pairwise classification. The learning by pairwise comparison (LPC) paradigm is the natural machine learning counterpart to the relational approach to preference modeling and decision making. From a machine learning point of view, LPC is especially appealing as it decomposes a possibly complex prediction problem into a certain number of learning problems of the simplest type, namely binary classification. We explain how to approach different preference learning problems, such as label and instance ranking, within the framework of LPC. We primarily focus on methodological aspects, but also address theoretical questions as well as algorithmic and complexity issues.

Relation between coal rank, char reactivity, textural properties and NO emissions

Energy Technology Data Exchange (ETDEWEB)

Arenillas, A.; Rubiera, F.; Parra, J.B.; Pis, J.J. [Instituto Nacional del Carbon, Oviedo (Spain)

1999-07-01

A low volatile bituminous coal was pyrolysed at different heating rates to produce chars with different textural properties. There was a linear relationship between char reactivity and active surface area. The effect of coal rank on coal char textural properties was studied using a range of bituminous coals. The influence of textural properties and reactivity on NO emissions, and on the heterogeneous reduction of NO is discussed. 6 refs., 2 figs., 2 tabs.

A biplex approach to PageRank centrality: From classic to multiplex networks.

Science.gov (United States)

Pedroche, Francisco; Romance, Miguel; Criado, Regino

2016-06-01

In this paper, we present a new view of the PageRank algorithm inspired by multiplex networks. This new approach allows to introduce a new centrality measure for classic complex networks and a new proposal to extend the usual PageRank algorithm to multiplex networks. We give some analytical relations between these new approaches and the classic PageRank centrality measure, and we illustrate the new parameters presented by computing them on real underground networks.

A biplex approach to PageRank centrality: From classic to multiplex networks

Science.gov (United States)

Pedroche, Francisco; Romance, Miguel; Criado, Regino

2016-06-01

In this paper, we present a new view of the PageRank algorithm inspired by multiplex networks. This new approach allows to introduce a new centrality measure for classic complex networks and a new proposal to extend the usual PageRank algorithm to multiplex networks. We give some analytical relations between these new approaches and the classic PageRank centrality measure, and we illustrate the new parameters presented by computing them on real underground networks.

A Hybrid Model Ranking Search Result for Research Paper Searching on Social Bookmarking

Directory of Open Access Journals (Sweden)

pijitra jomsri

2015-11-01

Full Text Available Social bookmarking and publication sharing systems are essential tools for web resource discovery. The performance and capabilities of search results from research paper bookmarking system are vital. Many researchers use social bookmarking for searching papers related to their topics of interest. This paper proposes a combination of similarity based indexing “tag title and abstract” and static ranking to improve search results. In this particular study, the year of the published paper and type of research paper publication are combined with similarity ranking called (HybridRank. Different weighting scores are employed. The retrieval performance of these weighted combination rankings are evaluated using mean values of NDCG. The results suggest that HybridRank and similarity rank with weight 75:25 has the highest NDCG scores. From the preliminary result of experiment, the combination ranking technique provide more relevant research paper search results. Furthermore the chosen heuristic ranking can improve the efficiency of research paper searching on social bookmarking websites.

Ranking alternatives based on imprecise multi-criteria data and pairwise overlap dominance relations

DEFF Research Database (Denmark)

Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt

illustrative example is given for comparison with standard methods like PROMETHEE. The proposed methodology takes into account the risk attitudes of decision makers, organizing the alternatives and ranking them according to their relevance. The whole interactive decision support allows understanding...

Money counts for a Times Higher Education top-rank

NARCIS (Netherlands)

Marconi, G.; Ritzen, J.M.M.

2014-01-01

This paper analyses the relationship between a university’s expenditure per student and its position in international university rankings. We take into account other factors that are expected to play a role, such as university mission, size, and productive inefficiency. We formalise these concepts

Universal emergence of PageRank

Energy Technology Data Exchange (ETDEWEB)

Frahm, K M; Georgeot, B; Shepelyansky, D L, E-mail: frahm@irsamc.ups-tlse.fr, E-mail: georgeot@irsamc.ups-tlse.fr, E-mail: dima@irsamc.ups-tlse.fr [Laboratoire de Physique Theorique du CNRS, IRSAMC, Universite de Toulouse, UPS, 31062 Toulouse (France)

2011-11-18

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter {alpha} Element-Of ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when {alpha} {yields} 1. The whole network can be divided into a core part and a group of invariant subspaces. For {alpha} {yields} 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at {alpha} {yields} 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

Universal emergence of PageRank

International Nuclear Information System (INIS)

Frahm, K M; Georgeot, B; Shepelyansky, D L

2011-01-01

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter α ∈ ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when α → 1. The whole network can be divided into a core part and a group of invariant subspaces. For α → 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at α → 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Science.gov (United States)

Fushing, Hsieh; McAssey, Michael P; Beisner, Brianne; McCowan, Brenda

2011-03-15

We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Directory of Open Access Journals (Sweden)

Hsieh Fushing

2011-03-01

Full Text Available We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Ranking benchmarks of top 100 players in men's professional tennis.

Science.gov (United States)

Reid, Machar; Morris, Craig

2013-01-01

In men's professional tennis, players aspire to hold the top ranking position. On the way to the top spot, reaching the top 100 can be seen as a significant career milestone. National Federations undertake extensive efforts to assist their players to reach the top 100. However, objective data considering reasonable ranking yardsticks for top 100 success in men's professional tennis are lacking. Therefore, it is difficult for National Federations and those involved in player development to give empirical programming advice to young players. By taking a closer look at the ranking history of professional male tennis players, this article tries to provide those involved in player development a more objective basis for decision-making. The 100 names, countries, birthdates and ranking histories of the top 100 players listed in the Association of Tennis Professionals (ATP) at 31 December 2009 were recorded from websites in the public domain. Descriptive statistics were reported for the ranking milestones of interest. Results confirmed the merits of the International Tennis Federation's junior tour with 91% of the top 100 professionals earning a junior ranking, the mean peak of which was 94.1, s=148.9. On average, top 100 professionals achieved their best junior rankings and earned their first ATP point at similar ages, suggesting that players compete on both the junior and professional tours during their transition. Once professionally ranked, players took an average 4.5, s=2.1 years to reach the ATP top 100 at the mean age of 21.5, s=2.6 years, which contrasts with the mean current age of the top 100 of 26.8, s=3.2. The best professional rankings of players born in 1982 or earlier were positively related to the ages at which players earned their first ATP point and then entered the top 100, suggesting that the ages associated with these ranking milestones may have some forecasting potential. Future work should focus on the change in top 100 demographics over time as well

An Analytic Hierarchy Process-based Method to Rank the Critical Success Factors of Implementing a Pharmacy Barcode System.

Science.gov (United States)

Alharthi, Hana; Sultana, Nahid; Al-Amoudi, Amjaad; Basudan, Afrah

2015-01-01

Pharmacy barcode scanning is used to reduce errors during the medication dispensing process. However, this technology has rarely been used in hospital pharmacies in Saudi Arabia. This article describes the barriers to successful implementation of a barcode scanning system in Saudi Arabia. A literature review was conducted to identify the relevant critical success factors (CSFs) for a successful dispensing barcode system implementation. Twenty-eight pharmacists from a local hospital in Saudi Arabia were interviewed to obtain their perception of these CSFs. In this study, planning (process flow issues and training requirements), resistance (fear of change, communication issues, and negative perceptions about technology), and technology (software, hardware, and vendor support) were identified as the main barriers. The analytic hierarchy process (AHP), one of the most widely used tools for decision making in the presence of multiple criteria, was used to compare and rank these identified CSFs. The results of this study suggest that resistance barriers have a greater impact than planning and technology barriers. In particular, fear of change is the most critical factor, and training is the least critical factor.

On the growth of rank for subgroups of finitely generated groups

International Nuclear Information System (INIS)

Osin, D V

1999-01-01

In [1] and [2] the functions of rank growth were independently introduced and investigated for subgroups of a finitely generated free group. In the present paper the concept of growth of rank is extended to subgroups of an arbitrary finitely generated group G, and the dependence of the asymptotic behaviour of the above functions on the choice of a finite generating set in G is studied. For a broad class of groups (which includes, in particular, the free polynilpotent groups) estimates for the growth of rank for subgroups are obtained that generalize the wellknown Baumslag-Eidel'kind result on finitely generated normal subgroups. Some problems related to the realization of arbitrary functions as functions of rank growth for subgroups of soluble groups are treated

RANK, RANKL and osteoprotegerin in arthritic bone loss

Directory of Open Access Journals (Sweden)

M.C. Bezerra

2005-02-01

Full Text Available Rheumatoid arthritis is characterized by the presence of inflammatory synovitis and destruction of joint cartilage and bone. Tissue proteinases released by synovia, chondrocytes and pannus can cause cartilage destruction and cytokine-activated osteoclasts have been implicated in bone erosions. Rheumatoid arthritis synovial tissues produce a variety of cytokines and growth factors that induce monocyte differentiation to osteoclasts and their proliferation, activation and longer survival in tissues. More recently, a major role in bone erosion has been attributed to the receptor activator of nuclear factor kappa B ligand (RANKL released by activated lymphocytes and osteoblasts. In fact, osteoclasts are markedly activated after RANKL binding to the cognate RANK expressed on the surface of these cells. RANKL expression can be upregulated by bone-resorbing factors such as glucocorticoids, vitamin D3, interleukin 1 (IL-1, IL-6, IL-11, IL-17, tumor necrosis factor-alpha, prostaglandin E2, or parathyroid hormone-related peptide. Supporting this idea, inhibition of RANKL by osteoprotegerin, a natural soluble RANKL receptor, prevents bone loss in experimental models. Tumor growth factor-ß released from bone during active bone resorption has been suggested as one feedback mechanism for upregulating osteoprotegerin and estrogen can increase its production on osteoblasts. Modulation of these systems provides the opportunity to inhibit bone loss and deformity in chronic arthritis.

Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing

OpenAIRE

Jin, Zhe; Lai, Yen-Lung; Hwang, Jung-Yeon; Kim, Soohyung; Teoh, Andrew Beng Jin

2017-01-01

In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector into discrete index (max ranked) hashed code. We demonstrate two realizations from IoM hashing notion, namely Gaussian Random Projection based and Uniformly Random Permutation based hashing schemes. The disc...

A Ranking Approach to Genomic Selection.

Science.gov (United States)

Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

2015-01-01

Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

Dynamic Matrix Rank

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

2009-01-01

We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

Rankings, creatividad y urbanismo

Directory of Open Access Journals (Sweden)

JOAQUÍN SABATÉ

2008-08-01

Full Text Available La competencia entre ciudades constituye uno de los factores impulsores de procesos de renovación urbana y los rankings han devenido instrumentos de medida de la calidad de las ciudades. Nos detendremos en el caso de un antiguo barrio industrial hoy en vías de transformación en distrito "creativo" por medio de una intervención urbanística de gran escala. Su análisis nos descubre tres claves críticas. En primer lugar, nos obliga a plantearnos la definición de innovación urbana y cómo se integran el pasado, la identidad y la memoria en la construcción del futuro. Nos lleva a comprender que la innovación y el conocimiento no se "dan" casualmente, sino que son el fruto de una larga y compleja red en la que participan saberes, espacios, actores e instituciones diversas en naturaleza, escala y magnitud. Por último nos obliga a reflexionar sobre el valor que se le otorga a lo local en los procesos de renovación urbana.Competition among cities constitutes one ofthe main factors o furban renewal, and rankings have become instruments to indícate cities quality. Studying the transformation of an old industrial quarter into a "creative district" by the means ofa large scale urban project we highlight three main conclusions. First, itasks us to reconsider the notion ofurban innovation and hoto past, identity and memory should intégrate the future development. Second, it shows that innovation and knowledge doesn't yield per chance, but are the result ofa large and complex grid of diverse knowledges, spaces, agents and institutions. Finally itforces us to reflect about the valué attributed to the "local" in urban renewalprocesses.

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

International Nuclear Information System (INIS)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A.

2009-01-01

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

Energy Technology Data Exchange (ETDEWEB)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A. [Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta (Canada)

2009-01-15

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle. (author)

Comparative study to explore factors affecting E-government ranking: the case of Malaysia, Nigeria and Republic of Korea

Directory of Open Access Journals (Sweden)

Wan Rozaini Sheik Osman

2017-12-01

Full Text Available The present study aims to find out the criteria for e-government ranking generally as well as particularly focusing on Malaysia’s e-government ranking. In addition, with regard to the Malaysia’s e-government ranking, the results shown that, most of the Human Capital, Online Services and Telecommunication Infrastructure and its sub-indicators has not seen any improvement through the previous periods comparing with other countries such as Republic of Korea. Indeed, this comparative study sought to highlight of the tangible part of the e-government ranking through explored the gap between the e-government of Malaysia and other countries such as Republic of Korea. Moreover, this study discovered the weakest dimensions of e-government applications to assist the government to address them. Besides that, this comparative study also attempts to help the countries all over the world especially those developing ones in enhancing the performance of the e-government simply by understanding the reasons of the utilization by the respective stakeholders.

Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

Directory of Open Access Journals (Sweden)

Donglei Du

Full Text Available Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A What is the general difference between signal emitting and receiving in a protein interactome? B Which proteins are among the top ranked in directional ranking? C Are high ranked proteins more evolutionarily conserved than low ranked ones? D Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

Science.gov (United States)

Du, Donglei; Lee, Connie F; Li, Xiu-Qing

2012-01-01

Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

An alternative approach to risk rank chemicals on the threat they pose to the aquatic environment.

Science.gov (United States)

Johnson, Andrew C; Donnachie, Rachel L; Sumpter, John P; Jürgens, Monika D; Moeckel, Claudia; Pereira, M Gloria

2017-12-01

This work presents a new and unbiased method of risk ranking chemicals based on the threat they pose to the aquatic environment. The study ranked 12 metals, 23 pesticides, 11 other persistent organic pollutants (POPs), 13 pharmaceuticals, 10 surfactants and similar compounds and 2 nanoparticles (total of 71) of concern against one another by comparing their median UK river water and median ecotoxicity effect concentrations. To complement this, by giving an assessment on potential wildlife impacts, risk ranking was also carried out by comparing the lowest 10th percentile of the effects data with the highest 90th percentile of the exposure data. In other words, risk was pared down to just toxicity versus exposure. Further modifications included incorporating bioconcentration factors, using only recent water measurements and excluding either lethal or sub-lethal effects. The top ten chemicals, based on the medians, which emerged as having the highest risk to organisms in UK surface waters using all the ecotoxicity data were copper, aluminium, zinc, ethinylestradiol (EE2), linear alkylbenzene sulfonate (LAS), triclosan, manganese, iron, methomyl and chlorpyrifos. By way of contrast, using current UK environmental quality standards as the comparator to median UK river water concentrations would have selected 6 different chemicals in the top ten. This approach revealed big differences in relative risk; for example, zinc presented a million times greater risk then metoprolol and LAS 550 times greater risk than nanosilver. With the exception of EE2, most pharmaceuticals were ranked as having a relatively low risk. Copyright © 2017 Elsevier B.V. All rights reserved.

Face the hierarchy: ERP and oscillatory brain responses in social rank processing.

Science.gov (United States)

Breton, Audrey; Jerbi, Karim; Henaff, Marie-Anne; Cheylus, Anne; Baudouin, Jean-Yves; Schmitz, Christina; Krolak-Salmon, Pierre; Van der Henst, Jean-Baptiste

2014-01-01

Recognition of social hierarchy is a key feature that helps us navigate through our complex social environment. Neuroimaging studies have identified brain structures involved in the processing of hierarchical stimuli but the precise temporal dynamics of brain activity associated with such processing remains largely unknown. Here, we used electroencephalography to examine the effect of social hierarchy on neural responses elicited by faces. In contrast to previous studies, the key manipulation was that a hierarchical context was constructed, not by varying facial expressions, but by presenting neutral-expression faces in a game setting. Once the performance-based hierarchy was established, participants were presented with high-rank, middle-rank and low-rank player faces and had to evaluate the rank of each face with respect to their own position. Both event-related potentials and task-related oscillatory activity were investigated. Three main findings emerge from the study. First, the experimental manipulation had no effect on the early N170 component, which may suggest that hierarchy did not modulate the structural encoding of neutral-expression faces. Second, hierarchy significantly modulated the amplitude of the late positive potential (LPP) within a 400-700 ms time-window, with more a prominent LPP occurring when the participants processed the face of the highest-rank player. Third, high-rank faces were associated with the highest reduction of alpha power. Taken together these findings provide novel electrophysiological evidence for enhanced allocation of attentional resource in the presence of high-rank faces. At a broader level, this study brings new insights into the neural processing underlying social categorization.

A tilting approach to ranking influence

KAUST Repository

Genton, Marc G.

2014-12-01

We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking the data in terms of that influence. Our method is based on, first, perturbing the value of the statistic by ‘tilting’, or reweighting, each data value, where the total amount of tilt is constrained to be the least possible, subject to achieving a given small perturbation of the statistic, and, then, taking the ranking of the influence of data values to be that which corresponds to ranking the changes in data weights. It is shown, both theoretically and numerically, that this ranking does not depend on the size of the perturbation, provided that the perturbation is sufficiently small. That simple result leads directly to an elegant geometric interpretation of the ranks; they are the ranks of the lengths of projections of the weights onto a ‘line’ determined by the first empirical principal component function in a generalized measure of covariance. To illustrate the generality of the method we introduce and explore it in the case of functional data, where (for example) it leads to generalized boxplots. The method has the advantage of providing an interpretable ranking that depends on the statistic under consideration. For example, the ranking of data, in terms of their influence on the value of a statistic, is different for a measure of location and for a measure of scale. This is as it should be; a ranking of data in terms of their influence should depend on the manner in which the data are used. Additionally, the ranking recognizes, rather than ignores, sign, and in particular can identify left- and right-hand ‘tails’ of the distribution of a random function or vector.

$C^1$ actions on manifolds by lattices in Lie groups with sufficiently high rank

OpenAIRE

Damjanovic, Danijela; Zhang, Zhiyuan

2018-01-01

In this paper we study Zimmer's conjecture for $C^1$ actions of higher-rank lattices of a connected, semisimple Lie group with finite center on compact manifolds. We show that if the Lie group has no compact factor, and all of whose non-compact factors are of ranks in some sense sufficiently large with respect to the dimension of the manifold, then every $C^1$ action of an irreducible, co-compact lattice has a finite image. As a corollary of our results, for every (uniform or non-uniform) lat...

Ranking scientific publications: the effect of nonlinearity

Science.gov (United States)

Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru

2014-10-01

Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

Ranking scientific publications: the effect of nonlinearity.

Science.gov (United States)

Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; Di, Zengru

2014-10-17

Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

Rank Advancement in Academic Careers: Sex Differences and the Effects of Productivity.

Science.gov (United States)

Long, J. Scott; And Others

1993-01-01

Presents evidence on sex differences in rank advancement in academic careers, and considers the relative importance of quality and quantity of publications. Results for 556 male and 450 female biochemists show the importance of time in rank and number of publications and that rates of promotion are lower for women. (SLD)

Statistical Optimality in Multipartite Ranking and Ordinal Regression.

Science.gov (United States)

Uematsu, Kazuki; Lee, Yoonkyung

2015-05-01

Statistical optimality in multipartite ranking is investigated as an extension of bipartite ranking. We consider the optimality of ranking algorithms through minimization of the theoretical risk which combines pairwise ranking errors of ordinal categories with differential ranking costs. The extension shows that for a certain class of convex loss functions including exponential loss, the optimal ranking function can be represented as a ratio of weighted conditional probability of upper categories to lower categories, where the weights are given by the misranking costs. This result also bridges traditional ranking methods such as proportional odds model in statistics with various ranking algorithms in machine learning. Further, the analysis of multipartite ranking with different costs provides a new perspective on non-smooth list-wise ranking measures such as the discounted cumulative gain and preference learning. We illustrate our findings with simulation study and real data analysis.

Ranking in evolving complex networks

Science.gov (United States)

Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

2017-05-01

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

Charting taxonomic knowledge through ontologies and ranking algorithms

Science.gov (United States)

Huber, Robert; Klump, Jens

2009-04-01

Since the inception of geology as a modern science, paleontologists have described a large number of fossil species. This makes fossilized organisms an important tool in the study of stratigraphy and past environments. Since taxonomic classifications of organisms, and thereby their names, change frequently, the correct application of this tool requires taxonomic expertise in finding correct synonyms for a given species name. Much of this taxonomic information has already been published in journals and books where it is compiled in carefully prepared synonymy lists. Because this information is scattered throughout the paleontological literature, it is difficult to find and sometimes not accessible. Also, taxonomic information in the literature is often difficult to interpret for non-taxonomists looking for taxonomic synonymies as part of their research. The highly formalized structure makes Open Nomenclature synonymy lists ideally suited for computer aided identification of taxonomic synonyms. Because a synonymy list is a list of citations related to a taxon name, its bibliographic nature allows the application of bibliometric techniques to calculate the impact of synonymies and taxonomic concepts. TaxonRank is a ranking algorithm based on bibliometric analysis and Internet page ranking algorithms. TaxonRank uses published synonymy list data stored in TaxonConcept, a taxonomic information system. The basic ranking algorithm has been modified to include a measure of confidence on species identification based on the Open Nomenclature notation used in synonymy list, as well as other synonymy specific criteria. The results of our experiments show that the output of the proposed ranking algorithm gives a good estimate of the impact a published taxonomic concept has on the taxonomic opinions in the geological community. Also, our results show that treating taxonomic synonymies as part of on an ontology is a way to record and manage taxonomic knowledge, and thus contribute

Preferences for domestic fuel. Analysis with socio-economic factors and rankings in Kolkata, India

International Nuclear Information System (INIS)

Gupta, Gautam; Koehlin, Gunnar

2006-01-01

The choice of domestic fuel is a matter of great concern for households and policy makers in India. This paper investigates the demand for domestic fuels when households face four choices: Fuelwood, Coal, Kerosene and LPG. The study is based on a survey of 500 households in Kolkata, India. The demand estimates are conducted using a two-stage process where the first stage investigates choice and the second the quantity used. Determinants of fuel demand are identified and their relative importance shown. Extending the study, the paper also analyses the choice of the main cooking fuel in terms of the households' stated rankings of six fuels for five attributes. The policy discussion indicates that subsidies have less potential to reduce polluting fuels such as coal and fuelwood due to weak cross-price elasticities, while increased availability of LPG and potentially also increased awareness of indoor air pollution have greater prospect. (author)

Groundwater contaminant plume ranking

International Nuclear Information System (INIS)

1988-08-01

Containment plumes at Uranium Mill Tailings Remedial Action (UMTRA) Project sites were ranked to assist in Subpart B (i.e., restoration requirements of 40 CFR Part 192) compliance strategies for each site, to prioritize aquifer restoration, and to budget future requests and allocations. The rankings roughly estimate hazards to the environment and human health, and thus assist in determining for which sites cleanup, if appropriate, will provide the greatest benefits for funds available. The rankings are based on the scores that were obtained using the US Department of Energy's (DOE) Modified Hazard Ranking System (MHRS). The MHRS and HRS consider and score three hazard modes for a site: migration, fire and explosion, and direct contact. The migration hazard mode score reflects the potential for harm to humans or the environment from migration of a hazardous substance off a site by groundwater, surface water, and air; it is a composite of separate scores for each of these routes. For ranking the containment plumes at UMTRA Project sites, it was assumed that each site had been remediated in compliance with the EPA standards and that relict contaminant plumes were present. Therefore, only the groundwater route was scored, and the surface water and air routes were not considered. Section 2.0 of this document describes the assumptions and procedures used to score the groundwater route, and Section 3.0 provides the resulting scores for each site. 40 tabs

Talking about relations: Factors influencing the production of relational descriptions

Directory of Open Access Journals (Sweden)

Adriana eBaltaretu

2016-02-01

Full Text Available In a production experiment (Experiment 1 and an acceptability rating one (Experiment 2, we assessed two factors, spatial position and salience, which may influence the production of relational descriptions (such as the ball between the man and the drawer. In Experiment 1, speakers were asked to refer unambiguously to a target object (a ball. In Experiment 1a, we addressed the role of spatial position, more specifically if speakers mention the entity positioned leftmost in the scene as (first relatum. The results showed a preference to start with the left entity, however, only as a trend, which leaves room for other factors that could influence spatial reference. Thus, in the following studies, we varied salience systematically, by making one of the relatum candidates animate (Experiment 1b, and by adding attention capture cues, first subliminally by priming one relatum candidate with a flash (Experiment 1c, then explicitly by using salient colors for objects (Experiment 1d. Results indicate that spatial position played a dominant role. Entities on the left were mentioned more often as (first relatum than those on the right (Experiment 1a, 1b, 1c, 1d. Animacy affected reference production in one out of three studies (in Experiment 1d. When salience was manipulated by priming visual attention or by using salient colors, there were no significant effects (Experiment 1c, 1d. In the acceptability rating study (Experiment 2, participants expressed their preference for specific relata, by ranking descriptions on the basis of how good they thought the descriptions fitted the scene. Results show that participants preferred most the description that had an animate entity as the first mentioned relatum. The relevance of these results for models of reference production is discussed.

On Locally Most Powerful Sequential Rank Tests

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 36, č. 1 (2017), s. 111-125 ISSN 0747-4946 R&D Projects: GA ČR GA17-07384S Grant - others:Nadační fond na podporu vědy(CZ) Neuron Institutional support: RVO:67985556 Keywords : nonparametric test s * sequential ranks * stopping variable Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 0.339, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/kalina-0474065.pdf

Host social rank and parasites: plains zebra (Equus quagga) and intestinal helminths in Uganda.

Science.gov (United States)

Fugazzola, M C; Stancampiano, L

2012-08-13

The main aim of this study was to evaluate the relationship between the social hierarchy of plain zebra, Equus quagga, and the level of parasitism. For the study 141 fecal samples from the same number of animals were collected within the two major populations of E. quagga of Uganda (Lake Mburo Conservation Area and Kidepo Valley National Park). Quantitative (eggs per gram of feces) and qualitative parasite assessment were performed with standard methods. The relationship between parasite burden and individual host features was analyzed using Generalized Linear Models. Strongyles, cestodes, Strongyloides sp. and oxiurids where present in the examined samples. Social rank and age class significantly affect all parasites' abundance with dominant individuals being less parasitized than subordinate individuals, regardless of the parasite groups excluding oxiurids. Sex could not been shown to be related with any of the found parasites. Age was positively related with strongyles and oxiurids abundance and negatively related with cestodes and Strongyloides sp. The main result of the present study was the evidence that social status influences parasite level with dominant zebras shedding less parasite eggs than subordinate ones. Social rank appears, therefore, as an important factor giving rise to parasite aggregation in plain zebras. Copyright © 2012 Elsevier B.V. All rights reserved.

Cultural Variation in Situation Assessment: Influence of Source Credibility and Rank Status

National Research Council Canada - National Science Library

Heacox, N

2000-01-01

.... Although information content, rank status, and source credibility have received much attention by researchers in command and control decision-making, cultural variations in these factors have seldom been studied...

On Rank and Nullity

Science.gov (United States)

Dobbs, David E.

2012-01-01

This note explains how Emil Artin's proof that row rank equals column rank for a matrix with entries in a field leads naturally to the formula for the nullity of a matrix and also to an algorithm for solving any system of linear equations in any number of variables. This material could be used in any course on matrix theory or linear algebra.

Ranking economic history journals

DEFF Research Database (Denmark)

Di Vaio, Gianfranco; Weisdorf, Jacob Louis

2010-01-01

This study ranks-for the first time-12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We also...... compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential for economic...... history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

Ranking Economic History Journals

DEFF Research Database (Denmark)

Di Vaio, Gianfranco; Weisdorf, Jacob Louis

This study ranks - for the first time - 12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We...... also compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential...... for economic history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

A Universal Rank-Size Law

Science.gov (United States)

2016-01-01

A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations. PMID:27812192

Rankings of International Achievement Test Performance and Economic Strength: Correlation or Conjecture?

Directory of Open Access Journals (Sweden)

CHRISTOPHER H. TIENKEN

2008-04-01

Full Text Available Examining a popular political notion, this article presents results from a series of Spearman Rho calculations conducted to investigate relationships between countries’ rankings on international tests of mathematics and science and future economic competitiveness as measured by the 2006 World Economic Forum’s Growth Competitiveness Index (GCI. The study investigated the existence of relationships between international test rankings from three different time periods during the last 50 years of U.S. education policy development (i.e., 1957–1982, 1983–2000, and 2001–2006 and 2006 GCI ranks. It extends previous research on the topic by investigating how GCI rankings in the top 50 percent and bottom 50 percent relate to rankings on international tests for the countries that participated in each test. The study found that the relationship between ranks on international tests of mathematics and science and future economic strength is stronger among nations with lower-performing economies. Nations with strong economies, such as the United States, demonstrate a weaker, nonsignificant relationship.

RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

Science.gov (United States)

Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

2015-01-01

Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

RANK rewires energy homeostasis in lung cancer cells and drives primary lung cancer.

Science.gov (United States)

Rao, Shuan; Sigl, Verena; Wimmer, Reiner Alois; Novatchkova, Maria; Jais, Alexander; Wagner, Gabriel; Handschuh, Stephan; Uribesalgo, Iris; Hagelkruys, Astrid; Kozieradzki, Ivona; Tortola, Luigi; Nitsch, Roberto; Cronin, Shane J; Orthofer, Michael; Branstetter, Daniel; Canon, Jude; Rossi, John; D'Arcangelo, Manolo; Botling, Johan; Micke, Patrick; Fleur, Linnea La; Edlund, Karolina; Bergqvist, Michael; Ekman, Simon; Lendl, Thomas; Popper, Helmut; Takayanagi, Hiroshi; Kenner, Lukas; Hirsch, Fred R; Dougall, William; Penninger, Josef M

2017-10-15

Lung cancer is the leading cause of cancer deaths. Besides smoking, epidemiological studies have linked female sex hormones to lung cancer in women; however, the underlying mechanisms remain unclear. Here we report that the receptor activator of nuclear factor-kB (RANK), the key regulator of osteoclastogenesis, is frequently expressed in primary lung tumors, an active RANK pathway correlates with decreased survival, and pharmacologic RANK inhibition reduces tumor growth in patient-derived lung cancer xenografts. Clonal genetic inactivation of KRas G12D in mouse lung epithelial cells markedly impairs the progression of KRas G12D -driven lung cancer, resulting in a significant survival advantage. Mechanistically, RANK rewires energy homeostasis in human and murine lung cancer cells and promotes expansion of lung cancer stem-like cells, which is blocked by inhibiting mitochondrial respiration. Our data also indicate survival differences in KRas G12D -driven lung cancer between male and female mice, and we show that female sex hormones can promote lung cancer progression via the RANK pathway. These data uncover a direct role for RANK in lung cancer and may explain why female sex hormones accelerate lung cancer development. Inhibition of RANK using the approved drug denosumab may be a therapeutic drug candidate for primary lung cancer. © 2017 Rao et al.; Published by Cold Spring Harbor Laboratory Press.

Block models and personalized PageRank.

Science.gov (United States)

Kloumann, Isabel M; Ugander, Johan; Kleinberg, Jon

2017-01-03

Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods through the "seed set expansion problem": given a subset [Formula: see text] of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate in the space of "landing probabilities" of a random walk rooted at the seed set, ranking nodes according to weighted sums of landing probabilities of different length walks. Both schemes, however, lack an a priori relationship to the seed set objective. In this work, we develop a principled framework for evaluating ranking methods by studying seed set expansion applied to the stochastic block model. We derive the optimal gradient for separating the landing probabilities of two classes in a stochastic block model and find, surprisingly, that under reasonable assumptions the gradient is asymptotically equivalent to personalized PageRank for a specific choice of the PageRank parameter [Formula: see text] that depends on the block model parameters. This connection provides a formal motivation for the success of personalized PageRank in seed set expansion and node ranking generally. We use this connection to propose more advanced techniques incorporating higher moments of landing probabilities; our advanced methods exhibit greatly improved performance, despite being simple linear classification rules, and are even competitive with belief propagation.

Tracking and fixed ranking of leukocyte telomere length across the adult life course

DEFF Research Database (Denmark)

Benetos, Athanase; Kark, Jeremy D; Susser, Ezra

2013-01-01

whether age-dependent LTL attrition during adulthood can substantially affect individuals' LTL ranking (e.g., longer or shorter LTL) in relation to their peers. We measured LTL in samples donated 12 years apart on average by 1156 participants in four longitudinal studies. We observed correlations of 0.......91-0.96 between baseline and follow-up LTLs. Ranking individuals by deciles revealed that 94.1% (95% confidence interval of 92.6-95.4%) showed no rank change or a 1 decile change over time. We conclude that in adults, LTL is virtually anchored to a given rank with the passage of time. Accordingly, the links...... of LTL with atherosclerosis and longevity appear to be established early in life. It is unlikely that lifestyle and its modification during adulthood exert a major impact on LTL ranking....

Hazard-ranking of agricultural pesticides for chronic health effects in Yuma County, Arizona.

Science.gov (United States)

Sugeng, Anastasia J; Beamer, Paloma I; Lutz, Eric A; Rosales, Cecilia B

2013-10-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam-sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. Copyright © 2013 Elsevier B.V. All rights reserved.

Hazard-Ranking of Agricultural Pesticides for Chronic Health Effects in Yuma County, Arizona

Science.gov (United States)

Sugeng, Anastasia J.; Beamer, Paloma I.; Lutz, Eric A.; Rosales, Cecilia B.

2013-01-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. PMID:23783270

Smoking is rank! But, not as rank as other drugs and bullying say New Zealand parents of pre-adolescent children.

Science.gov (United States)

Glover, Marewa; Kira, Anette; Min, Sandar; Scragg, Robert; Nosa, Vili; McCool, Judith; Bullen, Chris

2011-12-01

Despite the established risks associated with smoking, 21% of New Zealand adults smoke. Prevalence among Māori (indigenous) and Pacific Island New Zealanders is disproportionately high. Prevention of smoking initiation is a key component of tobacco control. Keeping Kids Smokefree--a quasi-experimental trial--aimed to do this by changing parental smoking behaviour and attitudes. However, little is known about parents' attitudes to smoking in comparison with other concerns. Parents of 4,144 children attending five urban schools in a high smoking prevalence population in Auckland, New Zealand, were asked to rank seven concerns on a paper-based questionnaire, including smoking, alcohol and bullying, from most to least serious. Methamphetamine and other illicit 'hard' drugs were ranked as most serious followed by marijuana smoking, alcohol drinking, bullying, cigarette smoking, sex and obesity. Never smokers ranked cigarette smoking as more serious than current or ex-smokers. Parents' under-estimation of the serious nature of tobacco smoking relative to other drugs could partly explain low participation rates in parent-focused smoking initiation prevention programs.

Exact Rational Expectations, Cointegration, and Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren; Swensen, Anders Rygh

We interpret the linear relations from exact rational expectations models as restrictions on the parameters of the statistical model called the cointegrated vector autoregressive model for non-stationary variables. We then show how reduced rank regression, Anderson (1951), plays an important role...

Exact rational expectations, cointegration, and reduced rank regression

DEFF Research Database (Denmark)

Johansen, Søren; Swensen, Anders Rygh

We interpret the linear relations from exact rational expectations models as restrictions on the parameters of the statistical model called the cointegrated vector autoregressive model for non-stationary variables. We then show how reduced rank regression, Anderson (1951), plays an important role...

Exact rational expectations, cointegration, and reduced rank regression

DEFF Research Database (Denmark)

Johansen, Søren; Swensen, Anders Rygh

2008-01-01

We interpret the linear relations from exact rational expectations models as restrictions on the parameters of the statistical model called the cointegrated vector autoregressive model for non-stationary variables. We then show how reduced rank regression, Anderson (1951), plays an important role...

A DEA-TOPSIS approach for ranking credit institutions

Directory of Open Access Journals (Sweden)

Mohammad Ehsani

2014-09-01

Full Text Available Measuring the relative efficiency of financial units plays essential role for making strategic decisions such as business development, downsizing, etc. This paper presents an empirical investigation to rank different branches of a credit institution named Samen in city of Semnan, Iran. The proposed study uses data envelopment analysis (DEA for measuring the relative efficiency of 17 units. The results indicate that five units were efficient and using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS, the efficient units are ranked based on some inputs/outputs. The results of this study indicate that most branches of this financial unit performed poorly and a restructure in their businesses is necessary. In addition, the study has provided some evidences that considering employee wage, bank deposit and administration expenses as inputs for DEA implementation seems to provide better results than using total assets and equities.

Error analysis of stochastic gradient descent ranking.

Science.gov (United States)

Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

2013-06-01

Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

Contests with rank-order spillovers

NARCIS (Netherlands)

M.R. Baye (Michael); D. Kovenock (Dan); C.G. de Vries (Casper)

2012-01-01

textabstractThis paper presents a unified framework for characterizing symmetric equilibrium in simultaneous move, two-player, rank-order contests with complete information, in which each player's strategy generates direct or indirect affine "spillover" effects that depend on the rank-order of her

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

Science.gov (United States)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

Rank distributions: A panoramic macroscopic outlook

Science.gov (United States)

Eliazar, Iddo I.; Cohen, Morrel H.

2014-01-01

This paper presents a panoramic macroscopic outlook of rank distributions. We establish a general framework for the analysis of rank distributions, which classifies them into five macroscopic "socioeconomic" states: monarchy, oligarchy-feudalism, criticality, socialism-capitalism, and communism. Oligarchy-feudalism is shown to be characterized by discrete macroscopic rank distributions, and socialism-capitalism is shown to be characterized by continuous macroscopic size distributions. Criticality is a transition state between oligarchy-feudalism and socialism-capitalism, which can manifest allometric scaling with multifractal spectra. Monarchy and communism are extreme forms of oligarchy-feudalism and socialism-capitalism, respectively, in which the intrinsic randomness vanishes. The general framework is applied to three different models of rank distributions—top-down, bottom-up, and global—and unveils each model's macroscopic universality and versatility. The global model yields a macroscopic classification of the generalized Zipf law, an omnipresent form of rank distributions observed across the sciences. An amalgamation of the three models establishes a universal rank-distribution explanation for the macroscopic emergence of a prevalent class of continuous size distributions, ones governed by unimodal densities with both Pareto and inverse-Pareto power-law tails.

Importance of intrinsic and non-network contribution in PageRank centrality and its effect on PageRank localization

OpenAIRE

Deyasi, Krishanu

2016-01-01

PageRank centrality is used by Google for ranking web-pages to present search result for a user query. Here, we have shown that PageRank value of a vertex also depends on its intrinsic, non-network contribution. If the intrinsic, non-network contributions of the vertices are proportional to their degrees or zeros, then their PageRank centralities become proportion to their degrees. Some simulations and empirical data are used to support our study. In addition, we have shown that localization ...

Ranking as parameter estimation

Czech Academy of Sciences Publication Activity Database

Kárný, Miroslav; Guy, Tatiana Valentine

2009-01-01

Roč. 4, č. 2 (2009), s. 142-158 ISSN 1745-7645 R&D Projects: GA MŠk 2C06001; GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : ranking * Bayesian estimation * negotiation * modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/AS/karny- ranking as parameter estimation.pdf

The optimized expansion based low-rank method for wavefield extrapolation

KAUST Repository

Wu, Zedong

2014-03-01

Spectral methods are fast becoming an indispensable tool for wavefield extrapolation, especially in anisotropic media because it tends to be dispersion and artifact free as well as highly accurate when solving the wave equation. However, for inhomogeneous media, we face difficulties in dealing with the mixed space-wavenumber domain extrapolation operator efficiently. To solve this problem, we evaluated an optimized expansion method that can approximate this operator with a low-rank variable separation representation. The rank defines the number of inverse Fourier transforms for each time extrapolation step, and thus, the lower the rank, the faster the extrapolation. The method uses optimization instead of matrix decomposition to find the optimal wavenumbers and velocities needed to approximate the full operator with its explicit low-rank representation. As a result, we obtain lower rank representations compared with the standard low-rank method within reasonable accuracy and thus cheaper extrapolations. Additional bounds set on the range of propagated wavenumbers to adhere to the physical wave limits yield unconditionally stable extrapolations regardless of the time step. An application on the BP model provided superior results compared to those obtained using the decomposition approach. For transversely isotopic media, because we used the pure P-wave dispersion relation, we obtained solutions that were free of the shear wave artifacts, and the algorithm does not require that n > 0. In addition, the required rank for the optimization approach to obtain high accuracy in anisotropic media was lower than that obtained by the decomposition approach, and thus, it was more efficient. A reverse time migration result for the BP tilted transverse isotropy model using this method as a wave propagator demonstrated the ability of the algorithm.

Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

Science.gov (United States)

Li, Jun; Zhao, Patrick X

2016-01-01

Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.

The exact probability distribution of the rank product statistics for replicated experiments.

Science.gov (United States)

Eisinga, Rob; Breitling, Rainer; Heskes, Tom

2013-03-18

The rank product method is a widely accepted technique for detecting differentially regulated genes in replicated microarray experiments. To approximate the sampling distribution of the rank product statistic, the original publication proposed a permutation approach, whereas recently an alternative approximation based on the continuous gamma distribution was suggested. However, both approximations are imperfect for estimating small tail probabilities. In this paper we relate the rank product statistic to number theory and provide a derivation of its exact probability distribution and the true tail probabilities. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Low-rank extremal positive-partial-transpose states and unextendible product bases

International Nuclear Information System (INIS)

Leinaas, Jon Magne; Sollid, Per Oyvind; Myrheim, Jan

2010-01-01

It is known how to construct, in a bipartite quantum system, a unique low-rank entangled mixed state with positive partial transpose (a PPT state) from an unextendible product basis (UPB), defined as an unextendible set of orthogonal product vectors. We point out that a state constructed in this way belongs to a continuous family of entangled PPT states of the same rank, all related by nonsingular unitary or nonunitary product transformations. The characteristic property of a state ρ in such a family is that its kernel Ker ρ has a generalized UPB, a basis of product vectors, not necessarily orthogonal, with no product vector in Im ρ, the orthogonal complement of Ker ρ. The generalized UPB in Ker ρ has the special property that it can be transformed to orthogonal form by a product transformation. In the case of a system of dimension 3x3, we give a complete parametrization of orthogonal UPBs. This is then a parametrization of families of rank 4 entangled (and extremal) PPT states, and we present strong numerical evidence that it is a complete classification of such states. We speculate that the lowest rank entangled and extremal PPT states also in higher dimensions are related to generalized, nonorthogonal UPBs in similar ways.

Diversifying customer review rankings.

Science.gov (United States)

Krestel, Ralf; Dokoohaki, Nima

2015-06-01

E-commerce Web sites owe much of their popularity to consumer reviews accompanying product descriptions. On-line customers spend hours and hours going through heaps of textual reviews to decide which products to buy. At the same time, each popular product has thousands of user-generated reviews, making it impossible for a buyer to read everything. Current approaches to display reviews to users or recommend an individual review for a product are based on the recency or helpfulness of each review. In this paper, we present a framework to rank product reviews by optimizing the coverage of the ranking with respect to sentiment or aspects, or by summarizing all reviews with the top-K reviews in the ranking. To accomplish this, we make use of the assigned star rating for a product as an indicator for a review's sentiment polarity and compare bag-of-words (language model) with topic models (latent Dirichlet allocation) as a mean to represent aspects. Our evaluation on manually annotated review data from a commercial review Web site demonstrates the effectiveness of our approach, outperforming plain recency ranking by 30% and obtaining best results by combining language and topic model representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Journal Rankings by Health Management Faculty Members: Are There Differences by Rank, Leadership Status, or Area of Expertise?

Science.gov (United States)

Menachemi, Nir; Hogan, Tory H; DelliFraine, Jami L

2015-01-01

Health administration (HA) faculty members publish in a variety of journals, including journals focused on management, economics, policy, and information technology. HA faculty members are evaluated on the basis of the quality and quantity of their journal publications. However, it is unclear how perceptions of these journals vary by subdiscipline, department leadership role, or faculty rank. It is also not clear how perceptions of journals may have changed over the past decade since the last evaluation of journal rankings in the field was published. The purpose of the current study is to examine how respondents rank journals in the field of HA, as well as the variation in perception by academic rank, department leadership status, and area of expertise. Data were drawn from a survey of HA faculty members at U.S. universities, which was completed in 2012. Different journal ranking patterns were noted for faculty members of different subdisciplines. The health management-oriented journals (Health Care Management Review and Journal of Healthcare Management) were ranked higher than in previous research, suggesting that journal ranking perceptions may have changed over the intervening decade. Few differences in perceptions were noted by academic rank, but we found that department chairs were more likely than others to select Health Affairs in their top three most prestigious journals (β = 0.768; p journal prestige varied between a department chair and untenured faculty in different disciplines, and this perceived difference could have implications for promotion and tenure decisions.

Algebraic and computational aspects of real tensor ranks

CERN Document Server

Sakata, Toshio; Miyazaki, Mitsuhiro

2016-01-01

This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. Although tensor ranks have been often argued in the complex number field, it should be emphasized that this book treats real tensor ranks, which have direct applications in statistics. The book provides several interesting ideas, including determinant polynomials, determinantal ideals, absolutely nonsingular tensors, absolutely full column rank tensors, and their connection to bilinear maps and Hurwitz-Radon numbers. In addition to reviews of methods to determine real tensor ranks in details, global theories such as the Jacobian method are also reviewed in details. The book includes as well an accessible and comprehensive introduction of mathematical backgrounds, with basics of positive polynomials and calculations by using the Groebner basis. Furthermore, this book provides insights into numerical methods of finding tensor ranks through...

Pyrolysis characteristics and kinetics of low rank coals by distributed activation energy model

International Nuclear Information System (INIS)

Song, Huijuan; Liu, Guangrui; Wu, Jinhu

2016-01-01

Highlights: • Types of carbon in coal structure were investigated by curve-fitted "1"3C NMR spectra. • The work related pyrolysis characteristics and kinetics with coal structure. • Pyrolysis kinetics of low rank coals were studied by DAEM with Miura integral method. • DAEM could supply accurate extrapolations under relatively higher heating rates. - Abstract: The work was conducted to investigate pyrolysis characteristics and kinetics of low rank coals relating with coal structure by thermogravimetric analysis (TGA), the distributed activation energy model (DAEM) and solid-state "1"3C Nuclear Magnetic Resonance (NMR). Four low rank coals selected from different mines in China were studied in the paper. TGA was carried out with a non-isothermal temperature program in N_2 at the heating rate of 5, 10, 20 and 30 °C/min to estimate pyrolysis processes of coal samples. The results showed that corresponding characteristic temperatures and the maximum mass loss rates increased as heating rate increased. Pyrolysis kinetics parameters were investigated by the DAEM using Miura integral method. The DAEM was accurate verified by the good fit between the experimental and calculated curves of conversion degree x at the selected heating rates and relatively higher heating rates. The average activation energy was 331 kJ/mol (coal NM), 298 kJ/mol (coal NX), 302 kJ/mol (coal HLJ) and 196 kJ/mol (coal SD), respectively. The curve-fitting analysis of "1"3C NMR spectra was performed to characterize chemical structures of low rank coals. The results showed that various types of carbon functional groups with different relative contents existed in coal structure. The work indicated that pyrolysis characteristics and kinetics of low rank coals were closely associated with their chemical structures.

Ranking of bank branches with undesirable and fuzzy data: A DEA-based approach

Directory of Open Access Journals (Sweden)

Sohrab Kordrostami

2016-07-01

Full Text Available Banks are one of the most important financial sectors in order to the economic development of each country. Certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. Sometimes the performance of banks must be measured in the presence of undesirable and vague factors. For these reasons in the current paper a procedure based on data envelopment analysis (DEA is introduced for evaluating the efficiency and complete ranking of decision making units (DMUs where undesirable and fuzzy measures exist. To illustrate, in the presence of undesirable and fuzzy measures, DMUs are evaluated by using a fuzzy expected value approach and DMUs with similar efficiency scores are ranked by using constraints and the Maximal Balance Index based on the optimal shadow prices. Afterwards, the efficiency scores of 25 branches of an Iranian commercial bank are evaluated using the proposed method. Also, a complete ranking of bank branches is presented to discriminate branches.

Measuring Vocational Preferences: Ranking versus Categorical Rating Procedures.

Science.gov (United States)

Carifio, James

1978-01-01

Describes a study to compare the relative validities of ranking v categorical rating procedures for obtaining student vocational preference data in exploratory program assignment situations. Students indicated their vocational program preferences from career clusters, and the frequency of wrong assignments made by each method was analyzed. (MF)

Livelihood Activities And Wealth Ranking Among Rural Households ...

African Journals Online (AJOL)

Livelihood Activities And Wealth Ranking Among Rural Households In The Farming Systems Of Western Kenya. ... African Journal of Livestock Extension ... The study examined the relationship between the livelihood activities of rural households in the farming systems of Western Kenya in relation to their wealth. A stratified ...

On predicting student performance using low-rank matrix factorization techniques

DEFF Research Database (Denmark)

Lorenzen, Stephan Sloth; Pham, Dang Ninh; Alstrup, Stephen

2017-01-01

Predicting the score of a student is one of the important problems in educational data mining. The scores given by an individual student reflect how a student understands and applies the knowledge conveyed in class. A reliable performance prediction enables teachers to identify weak students...... that require remedial support, generate adaptive hints, and improve the learning of students. This work focuses on predicting the score of students in the quiz system of the Clio Online learning platform, the largest Danish supplier of online learning materials, covering 90% of Danish elementary schools...... and the current version of the data set is very sparse, the very low-rank approximation can capture enough information. This means that the simple baseline approach achieves similar performance compared to other advanced methods. In future work, we will restrict the quiz data set, e.g. only including quizzes...

About the use of rank transformation in sensitivity analysis of model output

International Nuclear Information System (INIS)

Saltelli, Andrea; Sobol', Ilya M

1995-01-01

Rank transformations are frequently employed in numerical experiments involving a computational model, especially in the context of sensitivity and uncertainty analyses. Response surface replacement and parameter screening are tasks which may benefit from a rank transformation. Ranks can cope with nonlinear (albeit monotonic) input-output distributions, allowing the use of linear regression techniques. Rank transformed statistics are more robust, and provide a useful solution in the presence of long tailed input and output distributions. As is known to practitioners, care must be employed when interpreting the results of such analyses, as any conclusion drawn using ranks does not translate easily to the original model. In the present note an heuristic approach is taken, to explore, by way of practical examples, the effect of a rank transformation on the outcome of a sensitivity analysis. An attempt is made to identify trends, and to correlate these effects to a model taxonomy. Employing sensitivity indices, whereby the total variance of the model output is decomposed into a sum of terms of increasing dimensionality, we show that the main effect of the rank transformation is to increase the relative weight of the first order terms (the 'main effects'), at the expense of the 'interactions' and 'higher order interactions'. As a result the influence of those parameters which influence the output mostly by way of interactions may be overlooked in an analysis based on the ranks. This difficulty increases with the dimensionality of the problem, and may lead to the failure of a rank based sensitivity analysis. We suggest that the models can be ranked, with respect to the complexity of their input-output relationship, by mean of an 'Association' index I y . I y may complement the usual model coefficient of determination R y 2 as a measure of model complexity for the purpose of uncertainty and sensitivity analysis

Does learning performance in horses relate to fearfulness, baseline stress hormone, and social rank?

DEFF Research Database (Denmark)

Christensen, Janne Winther; Ahrendt, Line Peerstrup; Lintrup, Randi

2012-01-01

The ability of horses to learn and remember new tasks is fundamentally important for their use by humans. Fearfulness may, however, interfere with learning, because stimuli in the environment can overshadow signals from the rider or handler. In addition, prolonged high levels of stress hormones c...... to behavioural responses in a standardised fear test. Learning performance in the home environment, however, appears unrelated to fearfulness, social rank and baseline FCM levels.......The ability of horses to learn and remember new tasks is fundamentally important for their use by humans. Fearfulness may, however, interfere with learning, because stimuli in the environment can overshadow signals from the rider or handler. In addition, prolonged high levels of stress hormones can...... affect neurons within the hippocampus; a brain region central to learning and memory. In a series of experiments, we aimed to investigate the link between performance in two learning tests, the baseline level of stress hormones, measured as faecal cortisol metabolites (FCM), fearfulness, and social rank...

Canonical correlation analysis of professional stress,social support,and professional burnout among low-rank army officers

Directory of Open Access Journals (Sweden)

Chuan-yun LI

2011-12-01

Full Text Available Objective The present study investigates the influence of professional stress and social support on professional burnout among low-rank army officers.Methods The professional stress,social support,and professional burnout scales among low-rank army officers were used as test tools.Moreover,the officers of established units(battalion,company,and platoon were chosen as test subjects.Out of the 260 scales sent,226 effective scales were received.The descriptive statistic and canonical correlation analysis models were used to analyze the influence of each variable.Results The scores of low-rank army officers in the professional stress,social support,and professional burnout scales were more than average,except on two factors,namely,interpersonal support and de-individualization.The canonical analysis identified three groups of canonical correlation factors,of which two were up to a significant level(P < 0.001.After further eliminating the social support variable,the canonical correlation analysis of professional stress and burnout showed that the canonical correlation coefficients P corresponding to 1 and 2 were 0.62 and 0.36,respectively,and were up to a very significant level(P < 0.001.Conclusion The low-rank army officers experience higher professional stress and burnout levels,showing a lower sense of accomplishment,emotional exhaustion,and more serious depersonalization.However,social support can reduce the onset and seriousness of professional burnout among these officers by lessening pressure factors,such as career development,work features,salary conditions,and other personal factors.

THE USE OF RANKING SAMPLING METHOD WITHIN MARKETING RESEARCH

Directory of Open Access Journals (Sweden)

CODRUŢA DURA

2011-01-01

Full Text Available Marketing and statistical literature available to practitioners provides a wide range of sampling methods that can be implemented in the context of marketing research. Ranking sampling method is based on taking apart the general population into several strata, namely into several subdivisions which are relatively homogenous regarding a certain characteristic. In fact, the sample will be composed by selecting, from each stratum, a certain number of components (which can be proportional or non-proportional to the size of the stratum until the pre-established volume of the sample is reached. Using ranking sampling within marketing research requires the determination of some relevant statistical indicators - average, dispersion, sampling error etc. To that end, the paper contains a case study which illustrates the actual approach used in order to apply the ranking sample method within a marketing research made by a company which provides Internet connection services, on a particular category of customers – small and medium enterprises.

Sugeno integral ranking of release scenarios in a low and intermediate waste repository

International Nuclear Information System (INIS)

Kim, S. Ho; Kim, Tae Woon; Ha, Jae Joo

2004-01-01

In the present study, a multi criteria decision-making (MCDM) problem of ranking of important radionuclide release scenarios in a low and intermediate radioactive waste repository is to treat on the basis of λ-fuzzy measures and Sugeno integral. Ranking of important scenarios can lead to the provision of more effective safety measure in a design stage of the repository. The ranking is determined by a relative degree of appropriateness of scenario alternatives. To demonstrate a validation of the proposed approach to ranking of release scenarios, results of the previous AHP study are used and compared with them of the present SIAHP approach. Since the AHP approach uses importance weight based on additive probability measures, the interaction among criteria is ignored. The comparison of scenarios ranking obtained from these two approaches enables us to figure out the effect of different models for interaction among criteria

Social, economic and demographic factors relating to interregional migration in the Philippines: 1970-1980.

Science.gov (United States)

Llasa, R N

1982-10-01

The study attempts to identify the different social, economic, and demographic factors relating to interregional migration in the Philippines for the decade 1970-1980. The dependent variable used is the regional net migration rate estimated through the national growth rate method. Using the rank order correlation technique, the relationship between the dependent variable and the different independent variables were determined. It is found that the following variables were positively related to interregional migration: percentage of 20-29 year old population, previous in-migrants, median family income, land area, primacy index, level of urbanization, level of education, and percentage of never married population. However, the first 3 variables mentioned seem to be the most significant determinants of regional net migration rates, which indicates that net migration in the Philippines during the last decade tends to be more dependent upon previous migration patterns and less dependent upon current socioeconomic development.

Predicting disease risk using bootstrap ranking and classification algorithms.

Directory of Open Access Journals (Sweden)

Ohad Manor

Full Text Available Genome-wide association studies (GWAS are widely used to search for genetic loci that underlie human disease. Another goal is to predict disease risk for different individuals given their genetic sequence. Such predictions could either be used as a "black box" in order to promote changes in life-style and screening for early diagnosis, or as a model that can be studied to better understand the mechanism of the disease. Current methods for risk prediction typically rank single nucleotide polymorphisms (SNPs by the p-value of their association with the disease, and use the top-associated SNPs as input to a classification algorithm. However, the predictive power of such methods is relatively poor. To improve the predictive power, we devised BootRank, which uses bootstrapping in order to obtain a robust prioritization of SNPs for use in predictive models. We show that BootRank improves the ability to predict disease risk of unseen individuals in the Wellcome Trust Case Control Consortium (WTCCC data and results in a more robust set of SNPs and a larger number of enriched pathways being associated with the different diseases. Finally, we show that combining BootRank with seven different classification algorithms improves performance compared to previous studies that used the WTCCC data. Notably, diseases for which BootRank results in the largest improvements were recently shown to have more heritability than previously thought, likely due to contributions from variants with low minimum allele frequency (MAF, suggesting that BootRank can be beneficial in cases where SNPs affecting the disease are poorly tagged or have low MAF. Overall, our results show that improving disease risk prediction from genotypic information may be a tangible goal, with potential implications for personalized disease screening and treatment.

Efficient anisotropic quasi-P wavefield extrapolation using an isotropic low-rank approximation

KAUST Repository

Zhang, Zhendong; Liu, Yike; Alkhalifah, Tariq Ali; Wu, Zedong

2017-01-01

efficient. A dynamic implementation of this approach decomposes the original pseudo-differential operator into a Laplacian, handled using the low-rank approximation of the spectral operator, plus an angular dependent correction factor applied in the space

Ranking of Prokaryotic Genomes Based on Maximization of Sortedness of Gene Lengths.

Science.gov (United States)

Bolshoy, A; Salih, B; Cohen, I; Tatarinova, T

How variations of gene lengths (some genes become longer than their predecessors, while other genes become shorter and the sizes of these factions are randomly different from organism to organism) depend on organismal evolution and adaptation is still an open question. We propose to rank the genomes according to lengths of their genes, and then find association between the genome rank and variousproperties, such as growth temperature, nucleotide composition, and pathogenicity. This approach reveals evolutionary driving factors. The main purpose of this study is to test effectiveness and robustness of several ranking methods. The selected method of evaluation is measuring of overall sortedness of the data. We have demonstrated that all considered methods give consistent results and Bubble Sort and Simulated Annealing achieve the highest sortedness. Also, Bubble Sort is considerably faster than the Simulated Annealing method.

Discovering urban mobility patterns with PageRank based traffic modeling and prediction

Science.gov (United States)

Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

2017-11-01

Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.

Model of Decision Making through Consensus in Ranking Case

Science.gov (United States)

Tarigan, Gim; Darnius, Open

2018-01-01

The basic problem to determine ranking consensus is a problem to combine some rankings those are decided by two or more Decision Maker (DM) into ranking consensus. DM is frequently asked to present their preferences over a group of objects in terms of ranks, for example to determine a new project, new product, a candidate in a election, and so on. The problem in ranking can be classified into two major categories; namely, cardinal and ordinal rankings. The objective of the study is to obtin the ranking consensus by appying some algorithms and methods. The algorithms and methods used in this study were partial algorithm, optimal ranking consensus, BAK (Borde-Kendal)Model. A method proposed as an alternative in ranking conssensus is a Weighted Distance Forward-Backward (WDFB) method, which gave a little difference i ranking consensus result compare to the result oethe example solved by Cook, et.al (2005).

A combined QSAR and partial order ranking approach to risk assessment.

Science.gov (United States)

Carlsen, L

2006-04-01

QSAR generated data appear as an attractive alternative to experimental data as foreseen in the proposed new chemicals legislation REACH. A preliminary risk assessment for the aquatic environment can be based on few factors, i.e. the octanol-water partition coefficient (Kow), the vapour pressure (VP) and the potential biodegradability of the compound in combination with the predicted no-effect concentration (PNEC) and the actual tonnage in which the substance is produced. Application of partial order ranking, allowing simultaneous inclusion of several parameters leads to a mutual prioritisation of the investigated substances, the prioritisation possibly being further analysed through the concept of linear extensions and average ranks. The ranking uses endpoint values (log Kow and log VP) derived from strictly linear 'noise-deficient' QSAR models as input parameters. Biodegradation estimates were adopted from the BioWin module of the EPI Suite. The population growth impairment of Tetrahymena pyriformis was used as a surrogate for fish lethality.

An exploration in the will psychology of Otto Rank: human intentionality and individuality.

Science.gov (United States)

Isono, Masayo

2012-12-01

The author explores the meaning and the importance of the will in Rank's relation-based self-creative, self-constructive psychology and argues for the consideration of the concept of the will in psychoanalysis. The paper shows that Rank's concept of the will explains what gives a human being the impetus to choose an action, positive or negative. When validated by the other, this will, the power of intention, enables a person to create his/her unique individuality. The paper reviews Rank's definition of will and traces the evolution of his ideas of intentionality in his writings. Further, the author discusses how Rank attempts to capture the subtle movements of the human mind as suffused with struggles and dynamic interplay between external and internal forces.

The Privilege of Ranking: Google Plays Ball.

Science.gov (United States)

Wiggins, Richard

2003-01-01

Discussion of ranking systems used in various settings, including college football and academic admissions, focuses on the Google search engine. Explains the PageRank mathematical formula that scores Web pages by connecting the number of links; limitations, including authenticity and accuracy of ranked Web pages; relevancy; adjusting algorithms;…

Acclimation to high CO2 in maize is related to water status and dependent on leaf rank.

Science.gov (United States)

Prins, Anneke; Mukubi, Josephine Muchwesi; Pellny, Till K; Verrier, Paul J; Beyene, Getu; Lopes, Marta Silva; Emami, Kaveh; Treumann, Achim; Lelarge-Trouverie, Caroline; Noctor, Graham; Kunert, Karl J; Kerchev, Pavel; Foyer, Christine H

2011-02-01

The responses of C(3) plants to rising atmospheric CO(2) levels are considered to be largely dependent on effects exerted through altered photosynthesis. In contrast, the nature of the responses of C(4) plants to high CO(2) remains controversial because of the absence of CO(2) -dependent effects on photosynthesis. In this study, the effects of atmospheric CO(2) availability on the transcriptome, proteome and metabolome profiles of two ranks of source leaves in maize (Zea mays L.) were studied in plants grown under ambient CO(2) conditions (350 +/- 20 µL L(-1) CO(2) ) or with CO(2) enrichment (700 +/- 20 µL L(-1) CO(2) ). Growth at high CO(2) had no effect on photosynthesis, photorespiration, leaf C/N ratios or anthocyanin contents. However, leaf transpiration rates, carbohydrate metabolism and protein carbonyl accumulation were altered at high CO(2) in a leaf-rank specific manner. Although no significant CO(2) -dependent changes in the leaf transcriptome were observed, qPCR analysis revealed that the abundance of transcripts encoding a Bowman-Birk protease inhibitor and a serpin were changed by the growth CO(2) level in a leaf rank specific manner. Moreover, CO(2) -dependent changes in the leaf proteome were most evident in the oldest source leaves. Small changes in water status may be responsible for the observed responses to high CO(2,) particularly in the older leaf ranks. © 2010 Blackwell Publishing Ltd.

Yager’s ranking method for solving the trapezoidal fuzzy number linear programming

Science.gov (United States)

Karyati; Wutsqa, D. U.; Insani, N.

2018-03-01

In the previous research, the authors have studied the fuzzy simplex method for trapezoidal fuzzy number linear programming based on the Maleki’s ranking function. We have found some theories related to the term conditions for the optimum solution of fuzzy simplex method, the fuzzy Big-M method, the fuzzy two-phase method, and the sensitivity analysis. In this research, we study about the fuzzy simplex method based on the other ranking function. It is called Yager's ranking function. In this case, we investigate the optimum term conditions. Based on the result of research, it is found that Yager’s ranking function is not like Maleki’s ranking function. Using the Yager’s function, the simplex method cannot work as well as when using the Maleki’s function. By using the Yager’s function, the value of the subtraction of two equal fuzzy numbers is not equal to zero. This condition makes the optimum table of the fuzzy simplex table is undetected. As a result, the simplified fuzzy simplex table becomes stopped and does not reach the optimum solution.

Rank-dependent grooming patterns and cortisol alleviation in Barbary macaques.

Science.gov (United States)

Sonnweber, Ruth S; Ravignani, Andrea; Stobbe, Nina; Schiestl, Gisela; Wallner, Bernard; Fitch, W Tecumseh

2015-06-01

Flexibly adapting social behavior to social and environmental challenges helps to alleviate glucocorticoid (GC) levels, which may have positive fitness implications for an individual. For primates, the predominant social behavior is grooming. Giving grooming to others is particularly efficient in terms of GC mitigation. However, grooming is confined by certain limitations such as time constraints or restricted access to other group members. For instance, dominance hierarchies may impact grooming partner availability in primate societies. Consequently specific grooming patterns emerge. In despotic species focusing grooming activity on preferred social partners significantly ameliorates GC levels in females of all ranks. In this study we investigated grooming patterns and GC management in Barbary macaques, a comparably relaxed species. We monitored changes in grooming behavior and cortisol (C) for females of different ranks. Our results show that the C-amelioration associated with different grooming patterns had a gradual connection with dominance hierarchy: while higher-ranking individuals showed lowest urinary C measures when they focused their grooming on selected partners within their social network, lower-ranking individuals expressed lowest C levels when dispersing their grooming activity evenly across their social partners. We argue that the relatively relaxed social style of Barbary macaque societies allows individuals to flexibly adapt grooming patterns, which is associated with rank-specific GC management. © 2015 Wiley Periodicals, Inc.

PageRank, HITS and a unified framework for link analysis

Energy Technology Data Exchange (ETDEWEB)

Ding, Chris; He, Xiaofeng; Husbands, Parry; Zha, Hongyuan; Simon, Horst

2001-10-01

Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement between authority and hub webpages, while PageRank emphasizes hyperlink weight normalization and web surfing based on random walk models. We systematically generalize/combine these concepts into a unified framework. The ranking framework contains a large algorithm space; HITS and PageRank are two extreme ends in this space. We study several normalized ranking algorithms which are intermediate between HITS and PageRank, and obtain closed-form solutions. We show that, to first order approximation, all ranking algorithms in this framework, including PageRank and HITS, lead to same ranking which is highly correlated with ranking by indegree. These results support the notion that in web resource ranking indegree and outdegree are of fundamental importance. Rankings of webgraphs of different sizes and queries are presented to illustrate our analysis.

Generalized PageRank on Directed Configuration Networks

NARCIS (Netherlands)

Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana

2017-01-01

Note: formula is not displayed correctly. This paper studies the distribution of a family of rankings, which includes Google’s PageRank, on a directed configuration model. In particular, it is shown that the distribution of the rank of a randomly chosen node in the graph converges in distribution to

Exploiting Tensor Rank-One Decomposition in Probabilistic Inference

Czech Academy of Sciences Publication Activity Database

Savický, Petr; Vomlel, Jiří

2007-01-01

Roč. 43, č. 5 (2007), s. 747-764 ISSN 0023-5954 R&D Projects: GA MŠk 1M0545; GA MŠk 1M0572; GA ČR GA201/04/0393 Institutional research plan: CEZ:AV0Z10300504; CEZ:AV0Z10750506 Keywords : graphical probabilistic models * probabilistic inference * tensor rank Subject RIV: BD - Theory of Information Impact factor: 0.552, year: 2007 http://dml.cz/handle/10338.dmlcz/135810

OutRank

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Steinhausen, Uwe

2008-01-01

Outlier detection is an important data mining task for consistency checks, fraud detection, etc. Binary decision making on whether or not an object is an outlier is not appropriate in many applications and moreover hard to parametrize. Thus, recently, methods for outlier ranking have been proposed...

Ranking Theory and Conditional Reasoning.

Science.gov (United States)

Skovgaard-Olsen, Niels

2016-05-01

Ranking theory is a formal epistemology that has been developed in over 600 pages in Spohn's recent book The Laws of Belief, which aims to provide a normative account of the dynamics of beliefs that presents an alternative to current probabilistic approaches. It has long been received in the AI community, but it has not yet found application in experimental psychology. The purpose of this paper is to derive clear, quantitative predictions by exploiting a parallel between ranking theory and a statistical model called logistic regression. This approach is illustrated by the development of a model for the conditional inference task using Spohn's (2013) ranking theoretic approach to conditionals. Copyright © 2015 Cognitive Science Society, Inc.

Communities in Large Networks: Identification and Ranking

DEFF Research Database (Denmark)

Olsen, Martin

2008-01-01

We study the problem of identifying and ranking the members of a community in a very large network with link analysis only, given a set of representatives of the community. We define the concept of a community justified by a formal analysis of a simple model of the evolution of a directed graph. ...... and its immediate surroundings. The members are ranked with a “local” variant of the PageRank algorithm. Results are reported from successful experiments on identifying and ranking Danish Computer Science sites and Danish Chess pages using only a few representatives....

Nominal versus Attained Weights in Universitas 21 Ranking

Science.gov (United States)

Soh, Kaycheng

2014-01-01

Universitas 21 Ranking of National Higher Education Systems (U21 Ranking) is one of the three new ranking systems appearing in 2012. In contrast with the other systems, U21 Ranking uses countries as the unit of analysis. It has several features which lend it with greater trustworthiness, but it also shared some methodological issues with the other…

Quantitative assessments of municipal waste management systems: using different indicators to compare and rank programs in New York State.

Science.gov (United States)

Greene, Krista L; Tonjes, David J

2014-04-01

The primary objective of waste management technologies and policies in the United States is to reduce the harmful environmental impacts of waste, particularly those relating to energy consumption and climate change. Performance indicators are frequently used to evaluate the environmental quality of municipal waste systems, as well as to compare and rank programs relative to each other in terms of environmental performance. However, there currently is no consensus on the best indicator for performing these environmental evaluations. The purpose of this study is to examine the common performance indicators used to assess the environmental benefits of municipal waste systems to determine if there is agreement between them regarding which system performs best environmentally. Focus is placed on how indicator selection influences comparisons between municipal waste management programs and subsequent system rankings. The waste systems of ten municipalities in the state of New York, USA, were evaluated using each common performance indicator and Spearman correlations were calculated to see if there was a significant association between system rank orderings. Analyses showed that rank orders of waste systems differ substantially when different indicators are used. Therefore, comparative system assessments based on indicators should be considered carefully, especially those intended to gauge environmental quality. Insight was also gained into specific factors which may lead to one system achieving higher rankings than another. However, despite the insufficiencies of indicators for comparative quality assessments, they do provide important information for waste managers and they can assist in evaluating internal programmatic performance and progress. To enhance these types of assessments, a framework for scoring indicators based on criteria that evaluate their utility and value for system evaluations was developed. This framework was used to construct an improved model for

A Comprehensive Analysis of Marketing Journal Rankings

Science.gov (United States)

Steward, Michelle D.; Lewis, Bruce R.

2010-01-01

The purpose of this study is to offer a comprehensive assessment of journal standings in Marketing from two perspectives. The discipline perspective of rankings is obtained from a collection of published journal ranking studies during the past 15 years. The studies in the published ranking stream are assessed for reliability by examining internal…

The BiPublishers ranking: Main results and methodological problems when constructing rankings of academic publishers

Directory of Open Access Journals (Sweden)

Torres-Salinas, Daniel

2015-12-01

Full Text Available We present the results of the Bibliometric Indicators for Publishers project (also known as BiPublishers. This project represents the first attempt to systematically develop bibliometric publisher rankings. The data for this project was derived from the Book Citation Index and the study time period was 2009-2013. We have developed 42 rankings: 4 by fields and 38 by disciplines. We display six indicators for publishers divided into three types: output, impact and publisher’s profile. The aim is to capture different characteristics of the research performance of publishers. 254 publishers were processed and classified according to publisher type: commercial publishers and university presses. We present the main publishers by field and then discuss the principal challenges presented when developing this type of tool. The BiPublishers ranking is an on-going project which aims to develop and explore new data sources and indicators to better capture and define the research impact of publishers.Presentamos los resultados del proyecto Bibliometric Indicators for Publishers (BiPublishers. Es el primer proyecto que desarrolla de manera sistemática rankings bibliométricos de editoriales. La fuente de datos empleada es el Book Citation Index y el periodo de análisis 2009-2013. Se presentan 42 rankings: 4 por áreas y 38 por disciplinas. Mostramos seis indicadores por editorial divididos según su tipología: producción, impacto y características editoriales. Se procesaron 254 editoriales y se clasificaron según el tipo: comerciales y universitarias. Se presentan las principales editoriales por áreas. Después, se discuten los principales retos a superar en el desarrollo de este tipo de herramientas. El ranking Bipublishers es un proyecto en desarrollo que persigue analizar y explorar nuevas fuentes de datos e indicadores para captar y definir el impacto de las editoriales académicas.

PageRank in scale-free random graphs

NARCIS (Netherlands)

Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana; Bonata, Anthony; Chung, Fan; Pralat, Paweł

2014-01-01

We analyze the distribution of PageRank on a directed configuration model and show that as the size of the graph grows to infinity, the PageRank of a randomly chosen node can be closely approximated by the PageRank of the root node of an appropriately constructed tree. This tree approximation is in

46 CFR 282.11 - Ranking of flags.

Science.gov (United States)

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Ranking of flags. 282.11 Section 282.11 Shipping... COMMERCE OF THE UNITED STATES Foreign-Flag Competition § 282.11 Ranking of flags. The operators under each... priority of costs which are representative of the flag. For liner cargo vessels, the ranking of operators...

MiRNA-TF-gene network analysis through ranking of biomolecules for multi-informative uterine leiomyoma dataset.

Science.gov (United States)

Mallik, Saurav; Maulik, Ujjwal

2015-10-01

Gene ranking is an important problem in bioinformatics. Here, we propose a new framework for ranking biomolecules (viz., miRNAs, transcription-factors/TFs and genes) in a multi-informative uterine leiomyoma dataset having both gene expression and methylation data using (statistical) eigenvector centrality based approach. At first, genes that are both differentially expressed and methylated, are identified using Limma statistical test. A network, comprising these genes, corresponding TFs from TRANSFAC and ITFP databases, and targeter miRNAs from miRWalk database, is then built. The biomolecules are then ranked based on eigenvector centrality. Our proposed method provides better average accuracy in hub gene and non-hub gene classifications than other methods. Furthermore, pre-ranked Gene set enrichment analysis is applied on the pathway database as well as GO-term databases of Molecular Signatures Database with providing a pre-ranked gene-list based on different centrality values for comparing among the ranking methods. Finally, top novel potential gene-markers for the uterine leiomyoma are provided. Copyright © 2015 Elsevier Inc. All rights reserved.

Can Future Academic Surgeons be Identified in the Residency Ranking Process?

Science.gov (United States)

Beninato, Toni; Kleiman, David A; Zarnegar, Rasa; Fahey, Thomas J

2016-01-01

The goal of surgical residency training programs is to train competent surgeons. Academic surgical training programs also have as a mission training future academicians-surgical scientists, teachers, and leaders. However, selection of surgical residents is dependent on a relatively unscientific process. Here we sought to determine how well the residency selection process is able to identify future academicians in surgery. Rank lists from an academic surgical residency program from 1992 to 1997 were examined. All ranked candidates׳ career paths after residency were reviewed to determine whether they stayed in academics, were university affiliated, or in private practice. The study was performed at New York Presbyterian Hospital-Weill Cornell Medical College, New York, NY. A total of 663 applicants for general surgery residency participated in this study. In total 6 rank lists were evaluated, which included 663 candidates. Overall 76% remained in a general surgery subspecialty. Of those who remained in general surgery, 49% were in private practice, 20% were university affiliated, and 31% had academic careers. Approximately 47% of candidates that were ranked in the top 20 had ≥20 publications, with decreasing percentages as rank number increased. There was a strong correlation between the candidates׳ rank position and pursuing an academic career (p career. The residency selection process can identify candidates likely to be future academicians. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Male rank affects reproductive success and offspring performance in bank voles.

Science.gov (United States)

Kruczek, Małgorzata; Zatorska, Magdalena

2008-07-05

Laboratory studies reveal that in several rodent species the females prefer dominant males as mating partners. Here we investigate the correlation between males' social rank and their reproductive success. Similar numbers of females mating with relatively more dominant or relatively more subordinate males produced a litter, and parturition took place 19-21 days after mating. Relatively more dominant males tended to sire more pups than did relatively more subordinates, but the mean number of offspring per litter did not differ significantly between the two groups. Significantly more pups fathered by relatively more dominant males survived to weaning than those sired by relatively more subordinate fathers. Dominance had a long-term effect on the reproductive activity of the offspring: their rate of sexual maturation was increased. In pups sired by a relatively more dominant father, the uteruses of females, and the testes and accessory sex glands of males, were significantly heavier than those of offspring born to relatively more subordinate males. Our results suggest that social rank is an important determinant of the reproductive success of bank vole males.

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

Science.gov (United States)

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

Ranking Entities in Networks via Lefschetz Duality

DEFF Research Database (Denmark)

Aabrandt, Andreas; Hansen, Vagn Lundsgaard; Poulsen, Bjarne

2014-01-01

then be ranked according to how essential their positions are in the network by considering the effect of their respective absences. Defining a ranking of a network which takes the individual position of each entity into account has the purpose of assigning different roles to the entities, e.g. agents......, in the network. In this paper it is shown that the topology of a given network induces a ranking of the entities in the network. Further, it is demonstrated how to calculate this ranking and thus how to identify weak sub-networks in any given network....

Otto Rank, the Rankian circle in Philadelphia, and the origins of Carl Rogers' person-centered psychotherapy.

Science.gov (United States)

deCarvalho, R J

1999-05-01

Otto Rank's will therapy helped shape the ideas and techniques of relationship therapy developed by the Philadelphia social workers Jessie Taft, Virginia Robinson, and Frederick Allen in the 1930s. Rank's work and these ideas and techniques in turn strongly influenced the formulation of Carl Rogers' person-centered psychotherapy. This article compares and contrasts will, relationship, and person-centered approaches to psychotherapy and discusses the social factors--primarily the professional conflicts between a male-dominated psychiatry and female social workers over the independent practice of psychotherapy--that were crucial in the dissemination of Rank's psychological thought and the early popularity of Rogers.

Which Factors Drive the Decision to Boycott and Opt Out of Research Rankings?

OpenAIRE

Michael Berlemann; Justus Haucap

2012-01-01

This note contains an empirical analysis of the decision of German-speaking business scholars to boycott and opt out of the best known research ranking of business scholars, initiated and published by Germany’s largest business daily, Handelsblatt. Our analysis indicates that scientists who are more senior (already have a longer academic career) and scientists who have been either less successful or less eager to publish their research in internationally well renown journals with high impac...

A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model

Directory of Open Access Journals (Sweden)

Madjid Tavana

2007-01-01

Full Text Available Ordinal consensus ranking problems have received much attention in the management science literature. A problem arises in situations where a group of k decision makers (DMs is asked to rank order n alternatives. The question is how to combine the DM rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking; however, the similarity of consensus rankings generated by the different algorithms is largely unknown. In this paper, we propose a new hybrid distance-based ideal-seeking consensus ranking model (DCM. The proposed hybrid model combines parts of the two commonly used consensus ranking techniques of Beck and Lin (1983 and Cook and Kress (1985 into an intuitive and computationally simple model. We illustrate our method and then run a Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda and Kendall (Kendall 1962 and the two methods proposed by Beck and Lin (1983 and Cook and Kress (1985. DCM and Beck and Lin's method yielded the most similar consensus rankings, whereas the Cook-Kress method and the Borda-Kendall method yielded the least similar consensus rankings.

Factors related to the economic sustainability of two-year chemistry-based technology training programs

Science.gov (United States)

Backus, Bridgid A.

Two-year chemistry-based technology training (CBTT) programs in the U.S. are important in the preparation of the professional technical workforce. The purpose of this study was to identify, examine, and analyze factors related to the economic sustainability of CBTT programs. A review of literature identified four clustered categories of 31 sub-factors related to program sustainability. Three research questions relating to program sustainability were: (1) What is the relative importance of the identified factors?, (2) What differences exist between the opinions of administrators and faculty?, and (3) What are the interrelationships among the factors? In order to answer these questions, survey data gathered from CBTT programs throughout the United States were analyzed statistically. Conclusions included the following: (1) Rank order of the importance to sustainability of the clustered categories was: (1) Partnerships, (2) Employer and Student Educational Goals, (3) Faculty and Their Resources, and (4) Community Perceptions and Marketing Strategies. (2) Significant correlations between ratings of sustainability and the sub-factors included: degree of partnering, college responsiveness, administration involvement in partnerships, experiential learning opportunities, employer input in curriculum development, use of skill standards, number of program graduates, student job placement, professional development opportunities, administrator support, presence of a champion, flexible scheduling, program visibility, perception of chemical technicians, marketing plans, and promotion to secondary students. (3) Faculty and administrators differed significantly on only two sub-factor ratings: employer assisted curriculum development, and faculty workloads. (4) Significant differences in ratings by small program faculty and administrators and large program faculty and administrators were indicated, with most between small program faculty and large program administrators. The study

Die Rolle von RANK-Ligand und Osteoprotegerin bei Osteoporose

Directory of Open Access Journals (Sweden)

Hofbauer LC

2004-01-01

Full Text Available Receptor activator of nuclear factor (NF- κB ligand (RANKL, sein zellulärer Rezeptor RANK und der Decoy-Rezeptor Osteoprotegerin (OPG stellen ein essentielles Zytokinsystem für die Zellbiologie von Osteoklasten dar. Verschiedene Untersuchungen belegen die Bedeutung von Störungen des OPG/RANKL/RANK-Systems bei der Pathogenese metabolischer Knochenerkrankungen. In dieser Arbeit werden die wichtigsten Störungen des OPG/RANKL/RANK-Systems bei verschiedenen Osteoporoseformen dargestellt. Östrogenrezeptor- (ER- Agonisten wie 17 β-Östradiol, Raloxifen und Genistein stimulieren die osteoblastäre Produktion von OPG durch Aktivierung von ER- α in vitro, während Lymphozyten von Patientinnen mit Östrogenmangel RANKL überexprimieren. Die parenterale Gabe von OPG vermag den mit Östrogenmangel assoziierten Knochenverlust im Tiermodell und in einer kleineren klinischen Studie zu verhindern. Glukokortikoide und Immunsuppressiva steigern gleichzeitig die RANKL-Expression und hemmen die OPG-Produktion in osteoblastären Zellen in vitro. Glukokortikoide sind auch in vivo imstande, die OPG-Serumspiegel deutlich zu reduzieren. Dagegen hemmen biomechanische Reize in vitro die RANKL-Produktion und steigern die OPG-Produktion. Ein Fehlen dieser biomechanischen Reize bei längerer Immobilisierung kann daher den RANKL/OPG-Quotienten steigern, während die tierexperimentelle Immobilisierungs-Osteoporose durch die parenterale Gabe von OPG gemildert werden kann.

Dietary supplementation and doping-related factors in high-level sailing

Directory of Open Access Journals (Sweden)

Rodek Jelena

2012-12-01

Full Text Available Abstract Background Although dietary supplements (DSs in sports are considered a natural need resulting from athletes’ increased physical demands, and although they are often consumed by athletes, data on DS usage in Olympic sailing are scarce. The aim of this study was to study the use of and attitudes towards DSs and doping problems in high-level competitive sailing. Methods The sample consisted of 44 high-level sailing athletes (5 of whom were female; total mean age 24.13 ± 6.67 years and 34 coaches (1 of whom was female; total mean age 37.01 ± 11.70. An extensive, self-administered questionnaire of substance use was used, and the subjects were asked about sociodemographic data, sport-related factors, DS-related factors (i.e., usage of and knowledge about DSs, sources of information, and doping-related factors. The Kruskal-Wallis ANOVA was used to determine the differences in group characteristics, and Spearman’s rank order correlation and a logistic regression analysis were used to define the relationships between the studied variables. Results DS usage is relatively high. More than 77% of athletes consume DSs, and 38% do so on a regular basis (daily. The athletes place a high degree of trust in their coaches and/or physicians regarding DSs and doping. The most important reason for not consuming DSs is the opinion that DSs are useless and a lack of knowledge about DSs. The likelihood of doping is low, and one-third of the subjects believe that doping occurs in sailing (no significant differences between athletes and coaches. The logistic regression found crew number (i.e., single vs. double crew to be the single significant predictor of DS usage, with a higher probability of DS consumption among single crews. Conclusion Because of the high consumption of DSs future investigations should focus on real nutritional needs in sailing sport. Also, since athletes reported that their coaches are the primary source of information about

Efficient anisotropic quasi-P wavefield extrapolation using an isotropic low-rank approximation

KAUST Repository

Zhang, Zhendong

2017-12-17

The computational cost of quasi-P wave extrapolation depends on the complexity of the medium, and specifically the anisotropy. Our effective-model method splits the anisotropic dispersion relation into an isotropic background and a correction factor to handle this dependency. The correction term depends on the slope (measured using the gradient) of current wavefields and the anisotropy. As a result, the computational cost is independent of the nature of anisotropy, which makes the extrapolation efficient. A dynamic implementation of this approach decomposes the original pseudo-differential operator into a Laplacian, handled using the low-rank approximation of the spectral operator, plus an angular dependent correction factor applied in the space domain to correct for anisotropy. We analyze the role played by the correction factor and propose a new spherical decomposition of the dispersion relation. The proposed method provides accurate wavefields in phase and more balanced amplitudes than a previous spherical decomposition. Also, it is free of SV-wave artifacts. Applications to a simple homogeneous transverse isotropic medium with a vertical symmetry axis (VTI) and a modified Hess VTI model demonstrate the effectiveness of the approach. The Reverse Time Migration (RTM) applied to a modified BP VTI model reveals that the anisotropic migration using the proposed modeling engine performs better than an isotropic migration.

Rank aggregation of local expert knowledge for conservation planning of the critically endangered saola.

Science.gov (United States)

Wilkinson, Nicholas M; Van Duc, Luong

2017-06-01

There has been much recent interest in using local knowledge and expert opinion for conservation planning, particularly for hard-to-detect species. Although it is possible to ask for direct estimation of quantities such as population size, relative abundance is easier to estimate. However, an expert's knowledge is often geographically restricted relative to the area of interest. Combining (or aggregating) experts' assessments of relative abundance is difficult when each expert only knows a part of the area of interest. We used Google's PageRank algorithm to aggregate ranked abundance scores elicited from local experts through a rapid rural-appraisal method. We applied this technique to conservation planning for the saola (Pseudoryx nghetinhensis), a poorly known bovid. Near a priority landscape for the species, composed of 3 contiguous protected areas, we asked groups of local people to indicate relative abundances of saola and other species by placing beans on community maps. For each village, we used this information to rank areas within the knowledge area of that village for saola abundance. We used simulations to compare alternative methods to aggregate the rankings from the different villages. The best-performing method was then used to produce a single map of relative abundance across the entire landscape, an area larger than that known to any one village. This map has informed prioritization of surveys and conservation action in the continued absence of direct information about the saola. © 2016 Society for Conservation Biology.

Fair ranking of researchers and research teams.

Science.gov (United States)

Vavryčuk, Václav

2018-01-01

The main drawback of ranking of researchers by the number of papers, citations or by the Hirsch index is ignoring the problem of distributing authorship among authors in multi-author publications. So far, the single-author or multi-author publications contribute to the publication record of a researcher equally. This full counting scheme is apparently unfair and causes unjust disproportions, in particular, if ranked researchers have distinctly different collaboration profiles. These disproportions are removed by less common fractional or authorship-weighted counting schemes, which can distribute the authorship credit more properly and suppress a tendency to unjustified inflation of co-authors. The urgent need of widely adopting a fair ranking scheme in practise is exemplified by analysing citation profiles of several highly-cited astronomers and astrophysicists. While the full counting scheme often leads to completely incorrect and misleading ranking, the fractional or authorship-weighted schemes are more accurate and applicable to ranking of researchers as well as research teams. In addition, they suppress differences in ranking among scientific disciplines. These more appropriate schemes should urgently be adopted by scientific publication databases as the Web of Science (Thomson Reuters) or the Scopus (Elsevier).

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

Science.gov (United States)

Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A

2017-09-01

Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.

Low-rank coal study : national needs for resource development. Volume 2. Resource characterization

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

Comprehensive data are presented on the quantity, quality, and distribution of low-rank coal (subbituminous and lignite) deposits in the United States. The major lignite-bearing areas are the Fort Union Region and the Gulf Lignite Region, with the predominant strippable reserves being in the states of North Dakota, Montana, and Texas. The largest subbituminous coal deposits are in the Powder River Region of Montana and Wyoming, The San Juan Basin of New Mexico, and in Northern Alaska. For each of the low-rank coal-bearing regions, descriptions are provided of the geology; strippable reserves; active and planned mines; classification of identified resources by depth, seam thickness, sulfur content, and ash content; overburden characteristics; aquifers; and coal properties and characteristics. Low-rank coals are distinguished from bituminous coals by unique chemical and physical properties that affect their behavior in extraction, utilization, or conversion processes. The most characteristic properties of the organic fraction of low-rank coals are the high inherent moisture and oxygen contents, and the correspondingly low heating value. Mineral matter (ash) contents and compositions of all coals are highly variable; however, low-rank coals tend to have a higher proportion of the alkali components CaO, MgO, and Na/sub 2/O. About 90% of the reserve base of US low-rank coal has less than one percent sulfur. Water resources in the major low-rank coal-bearing regions tend to have highly seasonal availabilities. Some areas appear to have ample water resources to support major new coal projects; in other areas such as Texas, water supplies may be constraining factor on development.

Treatment plan ranking using physical and biological indices

International Nuclear Information System (INIS)

Ebert, M. A.; University of Western Asutralia, WA

2001-01-01

Full text: The ranking of dose distributions is of importance in several areas such as i) comparing rival treatment plans, ii) comparing iterations in an optimisation routine, and iii) dose-assessment of clinical trial data. This study aimed to investigate the influence of choice of objective function in ranking tumour dose distributions. A series of physical (mean, maximum, minimum, standard deviation of dose) dose-volume histogram (DVH) reduction indices and biologically-based (tumour-control probability - TCP; equivalent uniform dose -EUD) indices were used to rank a series of hypothetical DVHs, as well as DVHs obtained from a series of 18 prostate patients. The distribution in ranking and change in distribution with change in indice parameters were investigated. It is found that not only is the ranking of DVHs dependent on the actual model used to perform the DVH reduction, it is also found to depend on the inherent characteristics of each model (i.e., selected parameters). The adjacent figure shows an example where the 18 prostate patients are ranked (grey-scale from black to white) by EUD when an α value of 0.8 Gy -1 is used in the model. The change of ranking as α varies is evident. Conclusion: This study has shown that the characteristics of the model selected in plan optimisation or DVH ranking will have an impact on the ranking obtained. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

Global cities rankings. A research agenda or a neoliberal urban planning tool?

Directory of Open Access Journals (Sweden)

Cándida Gago García

2017-03-01

Full Text Available This paper contains a theoretical reflection about the methodology and meaning given to the global city rankings. There is a very large academic production about the role that some cities have in global territorial processes, which has been related to the concept of global city. Many recent contributions from the mass media, advertising and consulting services must be considered also in the analysis. All of them have included new indicators in order to show the main role that cultural services have acquired in the urban economy. Also the city rankings are being used as a tool in neoliberal policies. These policies stress the position that cities have in the rankings, which are used in practices of city-branding and to justify the neoliberal decisions that are being taken. In fact, we think that rankings are used inappropriately and that it is necessary a deep and new reflection about them.

[A preliminary study of the work values of male nurses in Taiwan and related factors].

Science.gov (United States)

Hsu, Yu-Ying; Tang, Woung-Ru; Chang, Yue-Cune; Maa, Suh-Hwa

2013-04-01

Male nurses account for 1.08% of Taiwan's total professional nursing workforce. While work values are known to impact the practice of female nurses, the work values of male nurses have never been fully evaluated. The aim of this study was to explore the work values of male nurses in Taiwan and related factors. We applied a cross-sectional design that targeted all male nurses nationwide and used a structured questionnaire distributed by mail to collect data. Data were collected from 1,087 Taiwan-based male nurses with 745 valid responses. Mean score for overall work value was 2.78 (on a maximum scale of 4). Socio-demographic differences contributed to work value variance among respondents. Major factors of influence on work value included education, work unit, work position, work rank, salary, hospital classification, and reason for choosing a nursing career. This study found personal characteristics, occupational roles, job performance, and reason for choosing a career in nursing to all correlate strongly with work value.

Rank diversity of languages: generic behavior in computational linguistics.

Science.gov (United States)

Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

2015-01-01

Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: "heads" consist of words which almost do not change their rank in time, "bodies" are words of general use, while "tails" are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.

Canine length in wild male baboons: maturation, aging and social dominance rank.

Directory of Open Access Journals (Sweden)

Jordi Galbany

Full Text Available Canines represent an essential component of the dentition for any heterodont mammal. In primates, like many other mammals, canines are frequently used as weapons. Hence, tooth size and wear may have significant implications for fighting ability, and consequently for social dominance rank, reproductive success, and fitness. We evaluated sources of variance in canine growth and length in a well-studied wild primate population because of the potential importance of canines for male reproductive success in many primates. Specifically, we measured maxillary canine length in 80 wild male baboons (aged 5.04-20.45 years from the Amboseli ecosystem in southern Kenya, and examined its relationship with maturation, age, and social dominance rank. In our analysis of maturation, we compared food-enhanced baboons (those that fed part time at a refuse pit associated with a tourist lodge with wild-feeding males, and found that food-enhanced males achieved long canines earlier than wild-feeding males. Among adult males, canine length decreased with age because of tooth wear. We found some evidence that, after controlling for age, longer canines were associated with higher adult dominance rank (accounting for 9% of the variance in rank, but only among relatively high-ranking males. This result supports the idea that social rank, and thus reproductive success and fitness, may depend in part on fighting ability mediated by canine size.

Evaluation of treatment effects by ranking

DEFF Research Database (Denmark)

Halekoh, U; Kristensen, K

2008-01-01

In crop experiments measurements are often made by a judge evaluating the crops' conditions after treatment. In the present paper an analysis is proposed for experiments where plots of crops treated differently are mutually ranked. In the experimental layout the crops are treated on consecutive...... plots usually placed side by side in one or more rows. In the proposed method a judge ranks several neighbouring plots, say three, by ranking them from best to worst. For the next observation the judge moves on by no more than two plots, such that up to two plots will be re-evaluated again...... in a comparison with the new plot(s). Data from studies using this set-up were analysed by a Thurstonian random utility model, which assumed that the judge's rankings were obtained by comparing latent continuous utilities or treatment effects. For the latent utilities a variance component model was considered...

Strategic alternatives ranking methodology: Multiple RCRA incinerator evaluation test case

International Nuclear Information System (INIS)

Baker, G.; Thomson, R.D.; Reece, J.; Springer, L.; Main, D.

1988-01-01

This paper presents an important process approach to permit quantification and ranking of multiple alternatives being considered in remedial actions or hazardous waste strategies. This process is a methodology for evaluating programmatic options in support of site selection or environmental analyses. Political or other less tangible motivations for alternatives may be quantified by means of establishing the range of significant variables, weighting their importance, and by establishing specific criteria for scoring individual alternatives. An application of the process to a recent AFLC program permitted ranking incineration alternatives from a list of over 130 options. The process forced participation by the organizations to be effected, allowed a consensus of opinion to be achieved, allowed complete flexibility to evaluate factor sensitivity, and resulted in strong, quantifiable support for any subsequent site-selection action NEPA documents

Generalized Reduced Rank Tests using the Singular Value Decomposition

NARCIS (Netherlands)

F.R. Kleibergen (Frank); R. Paap (Richard)

2003-01-01

textabstractWe propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables

Beyond Low Rank: A Data-Adaptive Tensor Completion Method

OpenAIRE

Zhang, Lei; Wei, Wei; Shi, Qinfeng; Shen, Chunhua; Hengel, Anton van den; Zhang, Yanning

2017-01-01

Low rank tensor representation underpins much of recent progress in tensor completion. In real applications, however, this approach is confronted with two challenging problems, namely (1) tensor rank determination; (2) handling real tensor data which only approximately fulfils the low-rank requirement. To address these two issues, we develop a data-adaptive tensor completion model which explicitly represents both the low-rank and non-low-rank structures in a latent tensor. Representing the no...

Generalized reduced rank tests using the singular value decomposition

NARCIS (Netherlands)

Kleibergen, F.R.; Paap, R.

2002-01-01

We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables for the LDU

Trachomatous Scar Ranking: A Novel Outcome for Trachoma Studies.

Science.gov (United States)

Baldwin, Angela; Ryner, Alexander M; Tadesse, Zerihun; Shiferaw, Ayalew; Callahan, Kelly; Fry, Dionna M; Zhou, Zhaoxia; Lietman, Thomas M; Keenan, Jeremy D

2017-06-01

AbstractWe evaluated a new trachoma scarring ranking system with potential use in clinical research. The upper right tarsal conjunctivas of 427 individuals from Ethiopian villages with hyperendemic trachoma were photographed. An expert grader first assigned a scar grade to each photograph using the 1981 World Health Organization (WHO) grading system. Then, all photographs were ranked from least (rank = 1) to most scarring (rank = 427). Photographic grading found 79 (18.5%) conjunctivae without scarring (C0), 191 (44.7%) with minimal scarring (C1), 105 (24.6%) with moderate scarring (C2), and 52 (12.2%) with severe scarring (C3). The ranking method demonstrated good internal validity, exhibiting a monotonic increase in the median rank across the levels of the 1981 WHO grading system. Intrarater repeatability was better for the ranking method (intraclass correlation coefficient = 0.84, 95% CI = 0.74-0.94). Exhibiting better internal and external validity, this ranking method may be useful for evaluating the difference in scarring between groups of individuals.

CNN-based ranking for biomedical entity normalization.

Science.gov (United States)

Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

2017-10-03

Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

RANK und RANKL - Vom Knochen zum Mammakarzinom

Directory of Open Access Journals (Sweden)

Sigl V

2012-01-01

Full Text Available RANK („Receptor Activator of NF-κB“ und sein Ligand RANKL sind Schlüsselmoleküle im Knochenmetabolismus und spielen eine essenzielle Rolle in der Entstehung von pathologischen Knochenveränderungen. Die Deregulation des RANK/RANKL-Systems ist zum Beispiel ein Hauptgrund für das Auftreten von postmenopausaler Osteoporose bei Frauen. Eine weitere wesentliche Funktion von RANK und RANKL liegt in der Entwicklung von milchsekretierenden Drüsen während der Schwangerschaft. Dabei regulieren Sexualhormone, wie zum Beispiel Progesteron, die Expression von RANKL und induzieren dadurch die Proliferation von epithelialen Zellen der Brust. Seit Längerem war schon bekannt, dass RANK und RANKL in der Metastasenbildung von Brustkrebszellen im Knochengewebe beteiligt sind. Wir konnten nun das RANK/RANKLSystem auch als essenziellen Mechanismus in der Entstehung von hormonellem Brustkrebs identifizieren. In diesem Beitrag werden wir daher den neuesten Erkenntnissen besondere Aufmerksamkeit schenken und diese kritisch in Bezug auf Brustkrebsentwicklung betrachten.

Rank hypocrisies the insult of the REF

CERN Document Server

Sayer, Derek

2015-01-01

"The REF is right out of Havel's and Kundera's Eastern Europe: a state-administered exercise to rank academic research like hotel chains dependent on the active collaboration of the UK professoriate. In crystalline text steeped in cold rage, Sayer takes aim at the REF's central claim, that it is a legitimate process of expert peer review. He critiques university and national-level REF processes against actual practices of scholarly review as found in academic journals, university presses, and North American tenure procedures. His analysis is damning. If the REF fails as scholarly review, how can academics and universities continue to participate? And how can government use its rankings as a basis for public policy?" - Tarak Barkawi, Reader in the Department of International Relations, London School of Economics "Many academics across the world have come to see the REF as an arrogant attempt to raise national research standards that has resulted in a variety of self-inflicted wounds to UK higher education. Der...

Using incomplete citation data for MEDLINE results ranking.

Science.gov (United States)

Herskovic, Jorge R; Bernstam, Elmer V

2005-01-01

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Convergence of Inner-Iteration GMRES Methods for Rank-Deficient Least Squares Problems

Czech Academy of Sciences Publication Activity Database

Morikuni, Keiichi; Hayami, K.

2015-01-01

Roč. 36, č. 1 (2015), s. 225-250 ISSN 0895-4798 Institutional support: RVO:67985807 Keywords : least squares problem * iterative methods * preconditioner * inner-outer iteration * GMRES method * stationary iterative method * rank-deficient problem Subject RIV: BA - General Mathematics Impact factor: 1.883, year: 2015

What Factors Influence Where Researchers Deposit their Data? A Survey of Researchers Submitting to Data Repositories

Directory of Open Access Journals (Sweden)

Shea Swauger

2015-02-01

Full Text Available In order to better understand the factors that most influence where researchers deposit their data when they have a choice, we collected survey data from researchers who deposited phylogenetic data in either the TreeBASE or Dryad data repositories. Respondents were asked to rank the relative importance of eight possible factors. We found that factors differed in importance for both TreeBASE and Dryad, and that the rankings differed subtly but significantly between TreeBASE and Dryad users. On average, TreeBASE users ranked the domain specialization of the repository highest, while Dryad users ranked as equal highest their trust in the persistence of the repository and the ease of its data submission process. Interestingly, respondents (particularly Dryad users were strongly divided as to whether being directed to choose a particular repository by a journal policy or funding agency was among the most or least important factors. Some users reported depositing their data in multiple repositories and archiving their data voluntarily.

Using centrality to rank web snippets

NARCIS (Netherlands)

Jijkoun, V.; de Rijke, M.; Peters, C.; Jijkoun, V.; Mandl, T.; Müller, H.; Oard, D.W.; Peñas, A.; Petras, V.; Santos, D.

2008-01-01

We describe our participation in the WebCLEF 2007 task, targeted at snippet retrieval from web data. Our system ranks snippets based on a simple similarity-based centrality, inspired by the web page ranking algorithms. We experimented with retrieval units (sentences and paragraphs) and with the

Neural Ranking Models with Weak Supervision

NARCIS (Netherlands)

Dehghani, M.; Zamani, H.; Severyn, A.; Kamps, J.; Croft, W.B.

2017-01-01

Despite the impressive improvements achieved by unsupervised deep neural networks in computer vision and NLP tasks, such improvements have not yet been observed in ranking for information retrieval. The reason may be the complexity of the ranking problem, as it is not obvious how to learn from

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Rank Diversity of Languages: Generic Behavior in Computational Linguistics

Science.gov (United States)

Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

2015-01-01

Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: “heads” consist of words which almost do not change their rank in time, “bodies” are words of general use, while “tails” are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied. PMID:25849150

Differential invariants for higher-rank tensors. A progress report

International Nuclear Information System (INIS)

Tapial, V.

2004-07-01

We outline the construction of differential invariants for higher-rank tensors. In section 2 we outline the general method for the construction of differential invariants. A first result is that the simplest tensor differential invariant contains derivatives of the same order as the rank of the tensor. In section 3 we review the construction for the first-rank tensors (vectors) and second-rank tensors (metrics). In section 4 we outline the same construction for higher-rank tensors. (author)

Citation ranking versus peer evaluation of senior faculty research performance

DEFF Research Database (Denmark)

Meho, Lokman I.; Sonnenwald, Diane H.

2000-01-01

The purpose of this study is to analyze the relationship between citation ranking and peer evaluation in assessing senior faculty research performance. Other studies typically derive their peer evaluation data directly from referees, often in the form of ranking. This study uses two additional...... indicator of research performance of senior faculty members? Citation data, book reviews, and peer ranking were compiled and examined for faculty members specializing in Kurdish studies. Analysis shows that normalized citation ranking and citation content analysis data yield identical ranking results....... Analysis also shows that normalized citation ranking and citation content analysis, book reviews, and peer ranking perform similarly (i.e., are highly correlated) for high-ranked and low-ranked senior scholars. Additional evaluation methods and measures that take into account the context and content...

Ranking accounting, banking and finance journals: A note

OpenAIRE

Halkos, George; Tzeremes, Nickolaos

2012-01-01

This paper by applying Data Envelopment Analysis (DEA) ranks Economics journals in the field of Accounting, Banking and Finance. By using one composite input and one composite output the paper ranks 57 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with the highest rankings in the field are Journal of Fi...

University rankings in computer science

DEFF Research Database (Denmark)

Ehret, Philip; Zuccala, Alesia Ann; Gipp, Bela

2017-01-01

This is a research-in-progress paper concerning two types of institutional rankings, the Leiden and QS World ranking, and their relationship to a list of universities’ ‘geo-based’ impact scores, and Computing Research and Education Conference (CORE) participation scores in the field of computer...... science. A ‘geo-based’ impact measure examines the geographical distribution of incoming citations to a particular university’s journal articles for a specific period of time. It takes into account both the number of citations and the geographical variability in these citations. The CORE participation...... score is calculated on the basis of the number of weighted proceedings papers that a university has contributed to either an A*, A, B, or C conference as ranked by the Computing Research and Education Association of Australasia. In addition to calculating the correlations between the distinct university...

Adaptive distributional extensions to DFR ranking

DEFF Research Database (Denmark)

Petersen, Casper; Simonsen, Jakob Grue; Järvelin, Kalervo

2016-01-01

-fitting distribution. We call this model Adaptive Distributional Ranking (ADR) because it adapts the ranking to the statistics of the specific dataset being processed each time. Experiments on TREC data show ADR to outperform DFR models (and their extensions) and be comparable in performance to a query likelihood...

Are university rankings useful to improve research? A systematic review.

Science.gov (United States)

Vernon, Marlo M; Balas, E Andrew; Momani, Shaher

2018-01-01

Concerns about reproducibility and impact of research urge improvement initiatives. Current university ranking systems evaluate and compare universities on measures of academic and research performance. Although often useful for marketing purposes, the value of ranking systems when examining quality and outcomes is unclear. The purpose of this study was to evaluate usefulness of ranking systems and identify opportunities to support research quality and performance improvement. A systematic review of university ranking systems was conducted to investigate research performance and academic quality measures. Eligibility requirements included: inclusion of at least 100 doctoral granting institutions, be currently produced on an ongoing basis and include both global and US universities, publish rank calculation methodology in English and independently calculate ranks. Ranking systems must also include some measures of research outcomes. Indicators were abstracted and contrasted with basic quality improvement requirements. Exploration of aggregation methods, validity of research and academic quality indicators, and suitability for quality improvement within ranking systems were also conducted. A total of 24 ranking systems were identified and 13 eligible ranking systems were evaluated. Six of the 13 rankings are 100% focused on research performance. For those reporting weighting, 76% of the total ranks are attributed to research indicators, with 24% attributed to academic or teaching quality. Seven systems rely on reputation surveys and/or faculty and alumni awards. Rankings influence academic choice yet research performance measures are the most weighted indicators. There are no generally accepted academic quality indicators in ranking systems. No single ranking system provides a comprehensive evaluation of research and academic quality. Utilizing a combined approach of the Leiden, Thomson Reuters Most Innovative Universities, and the SCImago ranking systems may provide

Freudenthal ranks: GHZ versus W

International Nuclear Information System (INIS)

Borsten, L

2013-01-01

The Hilbert space of three-qubit pure states may be identified with a Freudenthal triple system. Every state has an unique Freudenthal rank ranging from 1 to 4, which is determined by a set of automorphism group covariants. It is shown here that the optimal success rates for winning a three-player non-local game, varying over all local strategies, are strictly ordered by the Freudenthal rank of the shared three-qubit resource. (paper)

Ranking U-Sapiens 2010-2

Directory of Open Access Journals (Sweden)

Carlos-Roberto Peña-Barrera

2011-08-01

Full Text Available Los principales objetivos de esta investigación son los siguientes: (1 que la comunidad científica nacional e internacional y la sociedad en general co-nozcan los resultados del Ranking U-Sapiens Colombia 2010_2, el cual clasifica a cada institución de educación superior colombiana según puntaje, posición y cuartil; (2 destacar los movimientos más importantes al comparar los resultados del ranking 2010_1 con los del 2010_2; (3 publicar las respuestas de algunos actores de la academia nacional con respecto a la dinámica de la investigación en el país; (4 reconocer algunas instituciones, medios de comunicación e investigadores que se han interesado a modo de reflexión, referenciación o citación por esta investigación; y (5 dar a conocer el «Sello Ranking U-Sapiens Colombia» para las IES clasificadas. El alcance de este estudio en cuanto a actores abordó todas y cada una de las IES nacionales (aunque solo algunas lograran entrar al ranking y en cuanto a tiempo, un periodo referido al primer semestre de 2010 con respecto a: (1 los resultados 2010-1 de revistas indexadas en Publindex, (2 los programas de maestrías y doctorados activos durante 2010-1 según el Ministerio de Educación Nacional, y (3 los resultados de grupos de investigación clasificados para 2010 según Colciencias. El método empleado para esta investigación es el mismo que para el ranking 2010_1, salvo por una especificación aún más detallada en uno de los pasos del modelo (las variables α, β, γ; es completamente cuantitativo y los datos de las variables que fundamentan sus resultados provienen de Colciencias y el Ministerio de Educación Nacional; y en esta ocasión se darán a conocer los resultados por variable para 2010_1 y 2010_2. Los resultados más relevantes son estos: (1 entraron 8 IES al ranking y salieron 3; (2 las 3 primeras IES son públicas; (3 en total hay 6 instituciones universitarias en el ranking; (4 7 de las 10 primeras IES son

Ranking Quality in Higher Education: Guiding or Misleading?

Science.gov (United States)

Bergseth, Brita; Petocz, Peter; Abrandt Dahlgren, Madeleine

2014-01-01

The study examines two different models of measuring, assessing and ranking quality in higher education. Do different systems of quality assessment lead to equivalent conclusions about the quality of education? This comparative study is based on the rankings of 24 Swedish higher education institutions. Two ranking actors have independently…

Blind Reduced-Rank MMSE Detector for DS-CDMA Systems

Directory of Open Access Journals (Sweden)

Xiaodong Cai

2003-01-01

Full Text Available We first develop a reduced-rank minimum mean squared error (MMSE detector for direct-sequence (DS code division multiple access (CDMA by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which is obtained from an estimated covariance matrix. Our analysis and simulation results show that when the desired user′s signal is in a low-dimensional subspace, there exists an optimal subspace so that the blind reduced-rank MMSE detector lying in this subspace has the best performance. By properly choosing a subsspace, we guarantee that the optimal blind reduced-rank MMSE detector is obtained. An adaptive blind reduced-rank MMSE detector, based on a subspace tracking algorithm, is developed. The adaptive blind reduced-rank MMSE detector exhibits superior steady-state performance and fast convergence speed.

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

International Nuclear Information System (INIS)

Gao, Hao; Osher, Stanley; Yu, Hengyong; Wang, Ge

2011-01-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. (papers)

Hazard Ranking Method for Populations Exposed to Arsenic in Private Water Supplies: Relation to Bedrock Geology.

Science.gov (United States)

Crabbe, Helen; Fletcher, Tony; Close, Rebecca; Watts, Michael J; Ander, E Louise; Smedley, Pauline L; Verlander, Neville Q; Gregory, Martin; Middleton, Daniel R S; Polya, David A; Studden, Mike; Leonardi, Giovanni S

2017-12-01

Approximately one million people in the UK are served by private water supplies (PWS) where main municipal water supply system connection is not practical or where PWS is the preferred option. Chronic exposure to contaminants in PWS may have adverse effects on health. South West England is an area with elevated arsenic concentrations in groundwater and over 9000 domestic dwellings here are supplied by PWS. There remains uncertainty as to the extent of the population exposed to arsenic (As), and the factors predicting such exposure. We describe a hazard assessment model based on simplified geology with the potential to predict exposure to As in PWS. Households with a recorded PWS in Cornwall were recruited to take part in a water sampling programme from 2011 to 2013. Bedrock geologies were aggregated and classified into nine Simplified Bedrock Geological Categories (SBGC), plus a cross-cutting "mineralized" area. PWS were sampled by random selection within SBGCs and some 508 households volunteered for the study. Transformations of the data were explored to estimate the distribution of As concentrations for PWS by SBGC. Using the distribution per SBGC, we predict the proportion of dwellings that would be affected by high concentrations and rank the geologies according to hazard. Within most SBGCs, As concentrations were found to have log-normal distributions. Across these areas, the proportion of dwellings predicted to have drinking water over the prescribed concentration value (PCV) for As ranged from 0% to 20%. From these results, a pilot predictive model was developed calculating the proportion of PWS above the PCV for As and hazard ranking supports local decision making and prioritization. With further development and testing, this can help local authorities predict the number of dwellings that might fail the PCV for As, based on bedrock geology. The model presented here for Cornwall could be applied in areas with similar geologies. Application of the method

Factors Affecting Entrepreneurship and Business Sustainability

Directory of Open Access Journals (Sweden)

Ana Tur-Porcar

2018-02-01

Full Text Available Sustainability is becoming increasingly important for society, and the creation of business ventures is one area where sustainability is critical. We examined the factors affecting actions that are designed to foster business sustainability. These factors are related to the environment, behavior, human relations, and business activity. Based on questionnaire responses from experts, the Analytic Hierarchy Process (AHP method was used to rank sustainable business criteria according to their importance for entrepreneurs starting sustainable businesses. The results indicate that the most important drivers of sustainable entrepreneurship are behavioral factors and business factors. Ethical principles and values, together with competitive intelligence, are crucial for undertaking actions that lead to sustainability.

Relative importance and interrelations between psychosocial factors and individualized quality of life of hemodialysis patients.

Science.gov (United States)

Tovbin, David; Gidron, Yori; Jean, Tzipora; Granovsky, Ricardo; Schnieder, Alla

2003-09-01

Since quality of life (QOL) of hemodialysis (HD) patients is low and frequently difficult to improve by medical therapy, it is important to identify psychosocial correlates and life-domains important for HD patients' QOL. Our hypothesis was that psychosocial factors reflecting appraisal, external and internal resources/impediments correlate with QOL and compensate for adverse effects of disease-related variables on QOL. Forty-eight chronic HD-patients identified and rank-ordered life-domains important for QOL and rated their level of satisfaction with those domains. This was performed using a slightly modified version of the Self-Evaluated Individualized QOL (SEiQOL) Scale. Psychosocial factors included perceived-control (PC), social-support and hostility. Demographic and disease-related factors included age, gender, cardiovascular disease (CVD), diabetes, hematocrit, albumin and C-reactive protein. QOL was significantly correlated with PC (r = 0.65) and social-support (r = 0.38), and inversely correlated with hostility (r = -0.31), diabetes and hypoalbuminemia (all at least p < 0.05). PC mediated effects of certain variables (e.g., albumin, gender, hostility) and moderated effects of little social-support and hypoalbuminemia on QOL. Patients' most important QOL domains were health, with which satisfaction was lowest, followed by family, with which satisfaction was highest. Pending replication with larger samples, assessment and enhancement of PC may improve HD patients' QOL.

Hyper-local, directions-based ranking of places

DEFF Research Database (Denmark)

Venetis, Petros; Gonzalez, Hector; Jensen, Christian S.

2011-01-01

they are numerous and contain precise locations. Specifically, the paper proposes a framework that takes a user location and a collection of near-by places as arguments, producing a ranking of the places. The framework enables a range of aspects of directions queries to be exploited for the ranking of places......, including the frequency with which places have been referred to in directions queries. Next, the paper proposes an algorithm and accompanying data structures capable of ranking places in response to hyper-local web queries. Finally, an empirical study with very large directions query logs offers insight...... into the potential of directions queries for the ranking of places and suggests that the proposed algorithm is suitable for use in real web search engines....

Customer Ranking Model for Project Businesses: A Case Study from the Automotive Industry

Directory of Open Access Journals (Sweden)

Bernd Markus Zunk

2014-03-01