WorldWideScience

Sample records for rank candidate bases

  1. Metabolomics-based approach for ranking the candidate structures of unidentified peaks in capillary electrophoresis time-of-flight mass spectrometry.

    Science.gov (United States)

    Yamamoto, Hiroyuki; Sasaki, Kazunori

    2017-04-01

    One of the technical challenges encountered during metabolomics research is determining the chemical structures of unidentified peaks. We have developed a metabolomics-based chemoinformatics approach for ranking the candidate structures of unidentified peaks. Our approach uses information about the known metabolites detected in samples containing unidentified peaks and involves three discrete steps. The first step involves identifying "precursor/product metabolites" as potential reactants or products derived from the unidentified peaks. In the second step, candidate structures for the unidentified peak are searched against the PubChem database using a molecular formula. These structures are then ranked by structural similarity against precursor/product metabolites and candidate structures. In the third step, the migration time is predicted to refine the candidate structures. Two simulation studies were conducted to highlight the efficacy of our approach, including the use of 20 proteinogenic amino acids as pseudo-unidentified peaks, and leave-one-out experiments for all of the annotated metabolites with and without filtering against the Human Metabolome Database. We also applied our approach to two unidentified peaks in a urine sample, which were identified as glycocyamidine and N-acetylglycine. These results suggest that our approach could be used to identify unidentified peaks during metabolomics analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Ranking candidate genes in rat models of type 2 diabetes

    Directory of Open Access Journals (Sweden)

    Ståhl Fredrik

    2009-07-01

    Full Text Available Abstract Background Rat models are frequently used to find genomic regions that contribute to complex diseases, so called quantitative trait loci (QTLs. In general, the genomic regions found to be associated with a quantitative trait are rather large, covering hundreds of genes. To help selecting appropriate candidate genes from QTLs associated with type 2 diabetes models in rat, we have developed a web tool called Candidate Gene Capture (CGC, specifically adopted for this disorder. Methods CGC combines diabetes-related genomic regions in rat with rat/human homology data, textual descriptions of gene effects and an array of 789 keywords. Each keyword is assigned values that reflect its co-occurrence with 24 different reference terms describing sub-phenotypes of type 2 diabetes (for example "insulin resistance". The genes are then ranked based on the occurrences of keywords in the describing texts. Results CGC includes QTLs from type 2 diabetes models in rat. When comparing gene rankings from CGC based on one sub-phenotype, with manual gene ratings for four QTLs, very similar results were obtained. In total, 24 different sub-phenotypes are available as reference terms in the application and based on differences in gene ranking, they fall into separate clusters. Conclusion The very good agreement between the CGC gene ranking and the manual rating confirms that CGC is as a reliable tool for interpreting textual information. This, together with the possibility to select many different sub-phenotypes, makes CGC a versatile tool for finding candidate genes. CGC is publicly available at http://ratmap.org/CGC.

  3. 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.

  4. 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...

  5. DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank.

    Science.gov (United States)

    Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

    2016-06-15

    Identifying drug-target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug-target interactions of new candidate drugs or targets. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. http://datamining-iip.fudan.edu.cn/service/DrugE-Rank zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  6. Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

    Science.gov (United States)

    Saunders, Diane G O; Win, Joe; Cano, Liliana M; Szabo, Les J; Kamoun, Sophien; Raffaele, Sylvain

    2012-01-01

    Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i) contain a secretion signal, (ii) are encoded by in planta induced genes, (iii) have similarity to haustorial proteins, (iv) are small and cysteine rich, (v) contain a known effector motif or a nuclear localization signal, (vi) are encoded by genes with long intergenic regions, (vii) contain internal repeats, and (viii) do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.

  7. Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

    Directory of Open Access Journals (Sweden)

    Diane G O Saunders

    Full Text Available Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i contain a secretion signal, (ii are encoded by in planta induced genes, (iii have similarity to haustorial proteins, (iv are small and cysteine rich, (v contain a known effector motif or a nuclear localization signal, (vi are encoded by genes with long intergenic regions, (vii contain internal repeats, and (viii do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.

  8. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun

    2012-01-01

    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent 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 (i.e., strength) of a player, for example, depends on 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. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  9. Ranking images based on aesthetic qualities.

    OpenAIRE

    Gaur, Aarushi

    2015-01-01

    The qualitative assessment of image content and aesthetic impression is affected by various image attributes and relations between the attributes. Modelling of such assessments in the form of objective rankings and learning image representations based on them is not a straightforward problem. The criteria can be varied with different levels of complexity for various applications. A highly-complex problem could involve a large number of interrelated attributes and features alongside varied rul...

  10. 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.

  11. 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.

  12. Quantum probability ranking principle for ligand-based virtual screening.

    Science.gov (United States)

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  13. Quantum probability ranking principle for ligand-based virtual screening

    Science.gov (United States)

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  14. Combining Document-and Paragraph-Based Entity Ranking

    NARCIS (Netherlands)

    Rode, H.; Serdyukov, Pavel; Hiemstra, Djoerd

    2008-01-01

    We study entity ranking on the INEX entity track and pro- pose a simple graph-based ranking approach that enables to combine scores on document and paragraph level. The com- bined approach improves the retrieval results not only on the INEX testset, but similarly on TREC’s expert finding task.

  15. Transit shapes and self-organizing maps as a tool for ranking planetary candidates: application to Kepler and K2

    Science.gov (United States)

    Armstrong, D. J.; Pollacco, D.; Santerne, A.

    2017-03-01

    A crucial step in planet hunting surveys is to select the best candidates for follow-up observations, given limited telescope resources. This is often performed by human 'eyeballing', a time consuming and statistically awkward process. Here, we present a new, fast machine learning technique to separate true planet signals from astrophysical false positives. We use self-organizing maps (SOMs) to study the transit shapes of Kepler and K2 known and candidate planets. We find that SOMs are capable of distinguishing known planets from known false positives with a success rate of 87.0 per cent, using the transit shape alone. Furthermore, they do not require any candidate to be dispositioned prior to use, meaning that they can be used early in a mission's lifetime. A method for classifying candidates using a SOM is developed, and applied to previously unclassified members of the Kepler Objects of Interest (KOI) list as well as candidates from the K2 mission. The method is extremely fast, taking minutes to run the entire KOI list on a typical laptop. We make PYTHON code for performing classifications publicly available, using either new SOMs or those created in this work. The SOM technique represents a novel method for ranking planetary candidate lists, and can be used both alone or as part of a larger autovetting code.

  16. Image Registration based on Low Rank Matrix: Rank-Regularized SSD.

    Science.gov (United States)

    Ghaffari, Aboozar; Fatemizadeh, Emad

    2017-08-25

    Similarity measure is a main core of image registration algorithms. Spatially varying intensity distortion is an important challenge which affects the performance of similarity measures. Correlation among pixels is the main characteristic of this distortion. Similarity measures such as sum-of-squareddifferences (SSD) and mutual information (MI) ignore this correlation; Hence, perfect registration cannot be achieved in the presence of this distortion. In this paper, we model this correlation with the aid of the low rank matrix theory. Based on this model, we compensate this distortion analytically and introduce Rank-Regularized SSD (RRSSD). This new similarity measure is a modified SSD based on singular values of difference image in mono-modal imaging. In fact, image registration and distortion correction are performed simultaneously in the proposed model. Based on our experiments, the RRSSD similarity measure achieves clinically acceptable registration results, and outperforms other state-of-the-art similarity measures such as the well-known method of residual complexity.

  17. INTEL: Intel based systems move up in supercomputing ranks

    CERN Document Server

    2002-01-01

    "The TOP500 supercomputer rankings released today at the Supercomputing 2002 conference show a dramatic increase in the number of Intel-based systems being deployed in high-performance computing (HPC) or supercomputing areas" (1/2 page).

  18. Ranking the dermatology programs based on measurements of academic achievement.

    Science.gov (United States)

    Wu, Jashin J; Ramirez, Claudia C; Alonso, Carol A; Berman, Brian; Tyring, Stephen K

    2007-07-13

    The only dermatology rankings in the past were based on National Institutes of Health (NIH) funding and journal citations. To determine the highest ranking academic dermatology programs based on 5 outcome measures and on an overall ranking scale. To the best of our knowledge, this is the first report to rank the dermatology programs on 4 of the following outcome measures of academic achievement and with an overall ranking. We collected extensive 2001 to 2004 data ranging from total publications to grant funding on 107 U.S. dermatology programs and their full-time faculty. Data from part-time and volunteer faculty were not used. Publications in 2001 to 2004; NIH funding in 2004; Dermatology Foundation grants in 2001 to 2004; faculty lectures in 2004 delivered at national conferences; number of full-time faculty members who were on the editorial boards of the top 3 U.S. dermatology journals and the top 4 subspecialty journals We used the 5 outcome measures to tabulate the highest ranking programs in each category. Using a weighted ranking system, we also tabulated the overall top 30 dermatology programs based on these 5 outcome measures. We were not able to determine the total amount of NIH funding in dollars of the dermatology divisions. The impact factors of the journal in which these publications appeared was not factored into our calculations. Since faculty members may collaborate on the same publication, some publications may have been double-counted. In descending order, the 5 highest ranked academic programs are the University of Pennsylvania; University of California, San Francisco; Yale-New Haven Medical Center; New York University; and University of Michigan. This ranking system may allow residents and faculty to improve the academic achievements at their respective programs.

  19. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    Science.gov (United States)

    Chang, Heyou; Zheng, Hao

    2017-01-01

    Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.

  20. 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.

  1. A network-based dynamical ranking system for competitive sports.

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-01-01

    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.

  2. Severe language effect in university rankings: particularly Germany and France are wronged in citation-based rankings.

    Science.gov (United States)

    van Raan, Anthony F J; van Leeuwen, Thed N; Visser, Martijn S

    2011-08-01

    We applied a set of standard bibliometric indicators to monitor the scientific state-of-arte of 500 universities worldwide and constructed a ranking on the basis of these indicators (Leiden Ranking 2010). We find a dramatic and hitherto largely underestimated language effect in the bibliometric, citation-based measurements of research performance when comparing the ranking based on all Web of Science (WoS) covered publications and on only English WoS covered publications, particularly for Germany and France.

  3. Image Re-Ranking Based on Topic Diversity.

    Science.gov (United States)

    Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

    2017-08-01

    Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

  4. International Conference on Robust Rank-Based and Nonparametric Methods

    CERN Document Server

    McKean, Joseph

    2016-01-01

    The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with r...

  5. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    This paper introduces Rank-based Interactive Evolution (RIE) which is an alternative to interactive evolution driven by computational models of user preferences to generate personalized content. In RIE, the computational models are adapted to the preferences of users which, in turn, are used...... as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

  6. Ranking Scientific Publications Based on Their Citation Graph

    CERN Document Server

    Marian, L; Rajman, M

    2009-01-01

    CDS Invenio is the web-based integrated digital library system developed at CERN. It is a suite of applications which provides the framework and tools for building and managing an autonomous digital library server. Within this framework, the goal of this project is to implement new ranking methods based on the bibliographic citation graph extracted from the CDS Invenio database. As a first step, we implemented the Citation Count as a baseline ranking method. The major disadvantage of this method is that all citations are treated equally, disregarding their importance and their publication date. To overcome this drawback, we consider two different approaches: a link-based approach which extends the PageRank model to the bibliographic citation graph and a time-dependent approach which takes into account time in the citation counts. In addition, we also combined these two approaches in a hybrid model based on a time-dependent PageRank. In the present document, we describe the conceptual background behind our new...

  7. Low-Rank Affinity Based Local-Driven Multilabel Propagation

    Directory of Open Access Journals (Sweden)

    Teng Li

    2013-01-01

    Full Text Available This paper presents a novel low-rank affinity based local-driven algorithm to robustly propagate the multilabels from training images to test images. A graph is constructed over the segmented local image regions. The labels for vertices from the training data are derived based on the context among different training images, and the derived vertex labels are propagated to the unlabeled vertices via the graph. The multitask low-rank affinity, which jointly seeks the sparsity-consistent low-rank affinities from multiple feature matrices, is applied to compute the edge weights between graph vertices. The inference process of multitask low-rank affinity is formulated as a constrained nuclear norm and ℓ2,1-norm minimization problem. The optimization is conducted efficiently with the augmented Lagrange multiplier method. Based on the learned local patch labels we can predict the multilabels for the test images. Experiments on multilabel image annotation demonstrate the encouraging results from the proposed framework.

  8. PREFERENCE BASED TERM WEIGHTING FOR ARABIC FIQH DOCUMENT RANKING

    Directory of Open Access Journals (Sweden)

    Khadijah Fahmi Hayati Holle

    2015-03-01

    Full Text Available In document retrieval, besides the suitability of query with search results, there is also a subjective user assessment that is expected to be a deciding factor in document ranking. This preference aspect is referred at the fiqh document searching. People tend to prefer on certain fiqh methodology without rejecting other fiqh methodologies. It is necessary to investigate preference factor in addition to the relevance factor in the document ranking. Therefore, this research proposed a method of term weighting based on preference to rank documents according to user preference. The proposed method is also combined with term weighting based on documents index and books index so it sees relevance and preference aspect. The proposed method is Inverse Preference Frequency with α value (IPFα. In this method, we calculate preference value by IPF term weighting. Then, the preference values of terms that is equal with the query are multiplied by α. IPFα combined with the existing weighting methods become TF.IDF.IBF.IPFα. Experiment of the proposed method uses dataset of several Arabic fiqh documents. Evaluation uses recall, precision, and f-measure calculations. Proposed term weighting method is obtained to rank the document in the right order according to user preference. It is shown from the result with recall value reach 75%, precision 100%, and f-measure 85.7% respectively.

  9. Generating and evaluating a ranked candidate gene list for potential vertebrate heart field regulators

    Directory of Open Access Journals (Sweden)

    G. Musso

    2015-12-01

    Full Text Available The vertebrate heart develops from two distinct lineages of cardiomyocytes that arise from the first and second heart fields (FHF and SHF, respectively. The FHF forms the primitive heart tube, while adding cells from the SHF allows elongation at both poles of the tube. Initially seen as an exclusive characteristic of higher vertebrates, recent work has demonstrated the presence of a distinct FHF and SHF in lower vertebrates, including zebrafish. We found that key transcription factors that regulate septation and chamber formation in higher vertebrates, including Tbx5 and Pitx2, influence relative FHF and SHF contributions to the zebrafish heart tube. To identify molecular modulators of heart field migration, we used microarray-based expression profiling following inhibition of tbx5a and pitx2ab in embryonic zebrafish (Mosimann & Panakova, et al, 2015; GSE70750. Here, we describe in more detail the procedure used to process, prioritize, and analyze the expression data for functional enrichment.

  10. ConformRank: A conformity-based rank for finding top-k influential users

    Science.gov (United States)

    Wang, Qiyao; Jin, Yuehui; Cheng, Shiduan; Yang, Tan

    2017-05-01

    Finding influential users is a hot topic in social networks. For example, advertisers identify influential users to make a successful campaign. Retweeters forward messages from original users, who originally publish messages. This action is referred to as retweeting. Retweeting behaviors generate influence. Original users have influence on retweeters. Whether retweeters keep the same sentiment as original users is taken into consideration in this study. Influence is calculated based on conformity from emotional perspective after retweeting. A conformity-based algorithm, called ConformRank, is proposed to find top-k influential users, who make the most users keep the same sentiment after retweeting messages. Emotional conformity is introduced to denote how users conform to original users from the emotional perspective. Conforming weights are introduced to denote how two users keep the same sentiment after retweeting messages. Emotional conformity is applied for users and conforming weights are used for relations. Experiments were conducted on Sina Weibo. Experimental results show that users have larger influence when they publish positive messages.

  11. NDRC: A Disease-Causing Genes Prioritized Method Based on Network Diffusion and Rank Concordance.

    Science.gov (United States)

    Fang, Minghong; Hu, Xiaohua; Wang, Yan; Zhao, Junmin; Shen, Xianjun; He, Tingting

    2015-07-01

    Disease-causing genes prioritization is very important to understand disease mechanisms and biomedical applications, such as design of drugs. Previous studies have shown that promising candidate genes are mostly ranked according to their relatedness to known disease genes or closely related disease genes. Therefore, a dangling gene (isolated gene) with no edges in the network can not be effectively prioritized. These approaches tend to prioritize those genes that are highly connected in the PPI network while perform poorly when they are applied to loosely connected disease genes. To address these problems, we propose a new disease-causing genes prioritization method that based on network diffusion and rank concordance (NDRC). The method is evaluated by leave-one-out cross validation on 1931 diseases in which at least one gene is known to be involved, and it is able to rank the true causal gene first in 849 of all 2542 cases. The experimental results suggest that NDRC significantly outperforms other existing methods such as RWR, VAVIEN, DADA and PRINCE on identifying loosely connected disease genes and successfully put dangling genes as potential candidate disease genes. Furthermore, we apply NDRC method to study three representative diseases, Meckel syndrome 1, Protein C deficiency and Peroxisome biogenesis disorder 1A (Zellweger). Our study has also found that certain complex disease-causing genes can be divided into several modules that are closely associated with different disease phenotype.

  12. Do PageRank-based author rankings outperform simple citation counts?

    CERN Document Server

    Fiala, Dalibor; Žitnik, Slavko; Bajec, Marko

    2015-01-01

    The basic indicators of a researcher's productivity and impact are still the number of publications and their citation counts. These metrics are clear, straightforward, and easy to obtain. When a ranking of scholars is needed, for instance in grant, award, or promotion procedures, their use is the fastest and cheapest way of prioritizing some scientists over others. However, due to their nature, there is a danger of oversimplifying scientific achievements. Therefore, many other indicators have been proposed including the usage of the PageRank algorithm known for the ranking of webpages and its modifications suited to citation networks. Nevertheless, this recursive method is computationally expensive and even if it has the advantage of favouring prestige over popularity, its application should be well justified, particularly when compared to the standard citation counts. In this study, we analyze three large datasets of computer science papers in the categories of artificial intelligence, software engineering,...

  13. Hyper-local, directions-based ranking of places

    DEFF Research Database (Denmark)

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

    2011-01-01

    , 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......, enables so-called hyper-local web querying where the location of a user is accurate at a much finer granularity than with IP-based positioning. This paper addresses the problem of determining the importance of points of interest, or places, in local-search results. In doing so, the paper proposes...

  14. Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication

    Directory of Open Access Journals (Sweden)

    Tong Wang

    2017-01-01

    Full Text Available In recent years, there has been dramatic proliferation of research concerned with fifth-generation (5G mobile communication networks, among which device-to-device (D2D communication is one of the key technologies. Due to the intermittent connection of nodes, the D2D network topology may be disconnected frequently, which will lead to failure in transmission of large data files. In opportunistic networks, in case of encountering nodes which never meet before a flood message blindly to cause tremendous network overhead, a novel opportunistic network routing protocol based on social rank and intermeeting time (SRIT is proposed in this paper. An improved utility approach applied in utility replication based on encounter durations and intermeeting time is put forward to enhance the routing efficiency. Meanwhile, in order to select better candidate nodes in the network, a social graph among people is established when they socially relate to each other in social rank replication. The results under the scenario show an advantage of the proposed opportunistic network routing based on social rank and intermeeting time (SRIT over the compared algorithms in terms of delivery ratio, average delivery latency, and overhead ratio.

  15. Cardinal priority ranking based decision making for economic ...

    African Journals Online (AJOL)

    To access the indifference band, interaction with the decision maker is obtained via cardinal priority ranking (CPR) of the objectives. The cardinal priority ranking is constructed in the functional space and then transformed into the decision space, so the cardinal priority ranking of objectives relate the decision maker's ...

  16. Rank-Based Analysis of Unbalanced Repeated Measures Data

    Directory of Open Access Journals (Sweden)

    M. Mushfiqur Rashid

    2012-07-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* 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:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} In this article, we have developed a rank (intra-subject based analysis of clinical trials with unbalanced repeated measures data. We assume that the errors within each patient are exchangeable and continuous random variables. This rank-based inference is valid when the unbalanced data are missing either completely at random or by design. A drop in dispersion test is developed for general linear hypotheses. A numerical example is given to illustrate the procedure.

  17. Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.

    Science.gov (United States)

    Chen, Jinying; Yu, Hong

    2017-04-01

    Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, EHR notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information overload and help them focus on medical terms that matter most to them. Targeted education can then be developed to improve patient EHR comprehension and the quality of care. The aim of this work was to develop FIT (Finding Important Terms for patients), an unsupervised natural language processing (NLP) system that ranks medical terms in EHR notes based on their importance to patients. We built FIT on a new unsupervised ensemble ranking model derived from the biased random walk algorithm to combine heterogeneous information resources for ranking candidate terms from each EHR note. Specifically, FIT integrates four single views (rankers) for term importance: patient use of medical concepts, document-level term salience, word co-occurrence based term relatedness, and topic coherence. It also incorporates partial information of term importance as conveyed by terms' unfamiliarity levels and semantic types. We evaluated FIT on 90 expert-annotated EHR notes and used the four single-view rankers as baselines. In addition, we implemented three benchmark unsupervised ensemble ranking methods as strong baselines. FIT achieved 0.885 AUC-ROC for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FIT for identifying important terms from EHR notes was 0.813 AUC-ROC. Both performance scores significantly exceeded the corresponding scores from the four single rankers (P<0.001). FIT also outperformed the three ensemble rankers for most metrics. Its performance is relatively insensitive to its parameter. FIT can automatically identify EHR terms important to patients. It may help develop future interventions

  18. A data-mining approach to rank candidate protein-binding partners-The case of biogenesis of lysosome-related organelles complex-1 (BLOC-1).

    Science.gov (United States)

    Rodriguez-Fernandez, I A; Dell'Angelica, E C

    2009-04-01

    The study of protein-protein interactions is a powerful approach to uncovering the molecular function of gene products associated with human disease. Protein-protein interaction data are accumulating at an unprecedented pace owing to interactomics projects, although it has been recognized that a significant fraction of these data likely represents false positives. During our studies of biogenesis of lysosome-related organelles complex-1 (BLOC-1), a protein complex involved in protein trafficking and containing the products of genes mutated in Hermansky-Pudlak syndrome, we faced the problem of having too many candidate binding partners to pursue experimentally. In this work, we have explored ways of efficiently gathering high-quality information about candidate binding partners and presenting the information in a visually friendly manner. We applied the approach to rank 70 candidate binding partners of human BLOC-1 and 102 candidates of its counterpart from Drosophila melanogaster. The top candidate for human BLOC-1 was the small GTPase encoded by the RAB11A gene, which is a paralogue of the Rab38 and Rab32 proteins in mammals and the lightoid gene product in flies. Interestingly, genetic analyses in D. melanogaster uncovered a synthetic sick/lethal interaction between Rab11 and lightoid. The data-mining approach described herein can be customized to study candidate binding partners for other proteins or possibly candidates derived from other types of 'omics' data.

  19. Who Should Rank Our Journals...And Based on What?

    Science.gov (United States)

    Cherkowski, Sabre; Currie, Russell; Hilton, Sandy

    2012-01-01

    Purpose: This study aims to establish the use of active scholar assessment (ASA) in the field of education leadership as a new methodology in ranking administration and leadership journals. The secondary purpose of this study is to respond to the paucity of research on journal ranking in educational administration and leadership.…

  20. 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.

  1. An Automatic Web Service Composition Framework Using QoS-Based Web Service Ranking Algorithm.

    Science.gov (United States)

    Mallayya, Deivamani; Ramachandran, Baskaran; Viswanathan, Suganya

    2015-01-01

    Web service has become the technology of choice for service oriented computing to meet the interoperability demands in web applications. In the Internet era, the exponential addition of web services nominates the "quality of service" as essential parameter in discriminating the web services. In this paper, a user preference based web service ranking (UPWSR) algorithm is proposed to rank web services based on user preferences and QoS aspect of the web service. When the user's request cannot be fulfilled by a single atomic service, several existing services should be composed and delivered as a composition. The proposed framework allows the user to specify the local and global constraints for composite web services which improves flexibility. UPWSR algorithm identifies best fit services for each task in the user request and, by choosing the number of candidate services for each task, reduces the time to generate the composition plans. To tackle the problem of web service composition, QoS aware automatic web service composition (QAWSC) algorithm proposed in this paper is based on the QoS aspects of the web services and user preferences. The proposed framework allows user to provide feedback about the composite service which improves the reputation of the services.

  2. 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.

  3. A network-based dynamical ranking system for competitive sports

    National Research Council Canada - National Science Library

    Motegi, Shun; Masuda, Naoki

    2012-01-01

    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...

  4. Personalized Profile Based Search Interface With Ranked and Clustered Display

    National Research Council Canada - National Science Library

    Kumar, Sachin; Oztekin, B. U; Ertoz, Levent; Singhal, Saurabh; Han, Euihong; Kumar, Vipin

    2001-01-01

    We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list...

  5. Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy.

    Directory of Open Access Journals (Sweden)

    Yuling Tian

    Full Text Available For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

  6. A rank-based Prediction Algorithm of Learning User's Intention

    Science.gov (United States)

    Shen, Jie; Gao, Ying; Chen, Cang; Gong, HaiPing

    Internet search has become an important part in people's daily life. People can find many types of information to meet different needs through search engines on the Internet. There are two issues for the current search engines: first, the users should predetermine the types of information they want and then change to the appropriate types of search engine interfaces. Second, most search engines can support multiple kinds of search functions, each function has its own separate search interface. While users need different types of information, they must switch between different interfaces. In practice, most queries are corresponding to various types of information results. These queries can search the relevant results in various search engines, such as query "Palace" contains the websites about the introduction of the National Palace Museum, blog, Wikipedia, some pictures and video information. This paper presents a new aggregative algorithm for all kinds of search results. It can filter and sort the search results by learning three aspects about the query words, search results and search history logs to achieve the purpose of detecting user's intention. Experiments demonstrate that this rank-based method for multi-types of search results is effective. It can meet the user's search needs well, enhance user's satisfaction, provide an effective and rational model for optimizing search engines and improve user's search experience.

  7. Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

    DEFF Research Database (Denmark)

    Shungin, Dmitry; Deng, Wei Q; Varga, Tibor V

    2017-01-01

    Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between vari...... (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them....... variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv...... and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial

  8. MicroRNA prediction with a novel ranking algorithm based on random walks.

    Science.gov (United States)

    Xu, Yunpen; Zhou, Xuefeng; Zhang, Weixiong

    2008-07-01

    MicroRNA (miRNAs) play essential roles in post-transcriptional gene regulation in animals and plants. Several existing computational approaches have been developed to complement experimental methods in discovery of miRNAs that express restrictively in specific environmental conditions or cell types. These computational methods require a sufficient number of characterized miRNAs as training samples, and rely on genome annotation to reduce the number of predicted putative miRNAs. However, most sequenced genomes have not been well annotated and many of them have a very few experimentally characterized miRNAs. As a result, the existing methods are not effective or even feasible for identifying miRNAs in these genomes. Aiming at identifying miRNAs from genomes with a few known miRNA and/or little annotation, we propose and develop a novel miRNA prediction method, miRank, based on our new random walks- based ranking algorithm. We first tested our method on Homo sapiens genome; using a very few known human miRNAs as samples, our method achieved a prediction accuracy greater than 95%. We then applied our method to predict 200 miRNAs in Anopheles gambiae, which is the most important vector of malaria in Africa. Our further study showed that 78 out of the 200 putative miRNA precursors encode mature miRNAs that are conserved in at least one other animal species. These conserved putative miRNAs are good candidates for further experimental study to understand malaria infection. MiRank is programmed in Matlab on Windows platform. The source code is available upon request.

  9. Environmental restoration risk-based prioritization work package planning and risk ranking methodology. Revision 2

    Energy Technology Data Exchange (ETDEWEB)

    Dail, J.L.; Nanstad, L.D.; White, R.K.

    1995-06-01

    This document presents the risk-based prioritization methodology developed to evaluate and rank Environmental Restoration (ER) work packages at the five US Department of Energy, Oak Ridge Field Office (DOE-ORO) sites [i.e., Oak Ridge K-25 Site (K-25), Portsmouth Gaseous Diffusion Plant (PORTS), Paducah Gaseous Diffusion Plant (PGDP), Oak Ridge National Laboratory (ORNL), and the Oak Ridge Y-12 Plant (Y-12)], the ER Off-site Program, and Central ER. This prioritization methodology was developed to support the increased rigor and formality of work planning in the overall conduct of operations within the DOE-ORO ER Program. Prioritization is conducted as an integral component of the fiscal ER funding cycle to establish program budget priorities. The purpose of the ER risk-based prioritization methodology is to provide ER management with the tools and processes needed to evaluate, compare, prioritize, and justify fiscal budget decisions for a diverse set of remedial action, decontamination and decommissioning, and waste management activities. The methodology provides the ER Program with a framework for (1) organizing information about identified DOE-ORO environmental problems, (2) generating qualitative assessments of the long- and short-term risks posed by DOE-ORO environmental problems, and (3) evaluating the benefits associated with candidate work packages designed to reduce those risks. Prioritization is conducted to rank ER work packages on the basis of the overall value (e.g., risk reduction, stakeholder confidence) each package provides to the ER Program. Application of the methodology yields individual work package ``scores`` and rankings that are used to develop fiscal budget requests. This document presents the technical basis for the decision support tools and process.

  10. PageRank-based identification of signaling crosstalk from transcriptomics data: the case of Arabidopsis thaliana.

    Science.gov (United States)

    Omranian, Nooshin; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2012-04-01

    The levels of cellular organization, from gene transcription to translation to protein-protein interaction and metabolism, operate via tightly regulated mutual interactions, facilitating organismal adaptability and various stress responses. Characterizing the mutual interactions between genes, transcription factors, and proteins involved in signaling, termed crosstalk, is therefore crucial for understanding and controlling cells' functionality. We aim at using high-throughput transcriptomics data to discover previously unknown links between signaling networks. We propose and analyze a novel method for crosstalk identification which relies on transcriptomics data and overcomes the lack of complete information for signaling pathways in Arabidopsis thaliana. Our method first employs a network-based transformation of the results from the statistical analysis of differential gene expression in given groups of experiments under different signal-inducing conditions. The stationary distribution of a random walk (similar to the PageRank algorithm) on the constructed network is then used to determine the putative transcripts interrelating different signaling pathways. With the help of the proposed method, we analyze a transcriptomics data set including experiments from four different stresses/signals: nitrate, sulfur, iron, and hormones. We identified promising gene candidates, downstream of the transcription factors (TFs), associated to signaling crosstalk, which were validated through literature mining. In addition, we conduct a comparative analysis with the only other available method in this field which used a biclustering-based approach. Surprisingly, the biclustering-based approach fails to robustly identify any candidate genes involved in the crosstalk of the analyzed signals. We demonstrate that our proposed method is more robust in identifying gene candidates involved downstream of the signaling crosstalk for species for which large transcriptomics data sets

  11. Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions.

    Directory of Open Access Journals (Sweden)

    Dmitry Shungin

    2017-06-01

    Full Text Available Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP may reflect underlying gene-environment (G×E or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv, G×E interaction effects (with smoking and physical activity, and marginal genetic effects (Pm. Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010. Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05. SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann-Whitney = 1.46×10-5, and the odds ratio of SNPs with nominally significant (<0.05 Pm and Pv was 1.33 (95% CI: 1.12, 1.57 for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05 were enriched with nominally significant Pv values (Pbinomial = 8.63×10-9 and 8.52×10-7 for SNP × smoking and SNP × physical activity, respectively. We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them.

  12. Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy

    OpenAIRE

    Tian, Yuling; Zhang, Hongxian

    2016-01-01

    For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic?there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a...

  13. 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.

  14. Greedy bases in rank 2 quantum cluster algebras.

    Science.gov (United States)

    Lee, Kyungyong; Li, Li; Rupel, Dylan; Zelevinsky, Andrei

    2014-07-08

    We identify a quantum lift of the greedy basis for rank 2 coefficient-free cluster algebras. Our main result is that our construction does not depend on the choice of initial cluster, that it builds all cluster monomials, and that it produces bar-invariant elements. We also present several conjectures related to this quantum greedy basis and the triangular basis of Berenstein and Zelevinsky.

  15. Bibliometric Rankings of Journals Based on the Thomson Reuters Citations Database

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael)

    2015-01-01

    markdownabstract__Abstract__ Virtually all rankings of journals are based on citations, including self citations by journals and individual academics. The gold standard for bibliometric rankings based on citations data is the widely-used Thomson Reuters Web of Science (2014) citations database,

  16. Image Inpainting Algorithm Based on Low-Rank Approximation and Texture Direction

    Directory of Open Access Journals (Sweden)

    Jinjiang Li

    2014-01-01

    Full Text Available Existing image inpainting algorithm based on low-rank matrix approximation cannot be suitable for complex, large-scale, damaged texture image. An inpainting algorithm based on low-rank approximation and texture direction is proposed in the paper. At first, we decompose the image using low-rank approximation method. Then the area to be repaired is interpolated by level set algorithm, and we can reconstruct a new image by the boundary values of level set. In order to obtain a better restoration effect, we make iteration for low-rank decomposition and level set interpolation. Taking into account the impact of texture direction, we segment the texture and make low-rank decomposition at texture direction. Experimental results show that the new algorithm is suitable for texture recovery and maintaining the overall consistency of the structure, which can be used to repair large-scale damaged image.

  17. 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.

  18. 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...

  19. 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.

  20. Acceleration of MR parameter mapping using annihilating filter‐based low rank hankel matrix (ALOHA)

    National Research Council Canada - National Science Library

    Lee, Dongwook; Jin, Kyong Hwan; Kim, Eung Yeop; Park, Sung‐Hong; Ye, Jong Chul

    2016-01-01

    .... However, increased scan time makes it difficult for routine clinical use. This article aims at developing an accelerated MR parameter mapping technique using annihilating filter based low-rank Hankel matrix approach (ALOHA...

  1. Rank-Based miRNA Signatures for Early Cancer Detection

    Directory of Open Access Journals (Sweden)

    Mario Lauria

    2014-01-01

    Full Text Available We describe a new signature definition and analysis method to be used as biomarker for early cancer detection. Our new approach is based on the construction of a reference map of transcriptional signatures of both healthy and cancer affected individuals using circulating miRNA from a large number of subjects. Once such a map is available, the diagnosis for a new patient can be performed by observing the relative position on the map of his/her transcriptional signature. To demonstrate its efficacy for this specific application we report the results of the application of our method to published datasets of circulating miRNA, and we quantify its performance compared to current state-of-the-art methods. A number of additional features make this method an ideal candidate for large-scale use, for example, as a mass screening tool for early cancer detection or for at-home diagnostics. Specifically, our method is minimally invasive (because it works well with circulating miRNA, it is robust with respect to lab-to-lab protocol variability and batch effects (it requires that only the relative ranking of expression value of miRNA in a profile be accurate not their absolute values, and it is scalable to a large number of subjects. Finally we discuss the need for HPC capability in a widespread application of our or similar methods.

  2. PosMed: ranking genes and bioresources based on Semantic Web Association Study

    Science.gov (United States)

    Makita, Yuko; Kobayashi, Norio; Yoshida, Yuko; Doi, Koji; Mochizuki, Yoshiki; Nishikata, Koro; Matsushima, Akihiro; Takahashi, Satoshi; Ishii, Manabu; Takatsuki, Terue; Bhatia, Rinki; Khadbaatar, Zolzaya; Watabe, Hajime; Masuya, Hiroshi; Toyoda, Tetsuro

    2013-01-01

    Positional MEDLINE (PosMed; http://biolod.org/PosMed) is a powerful Semantic Web Association Study engine that ranks biomedical resources such as genes, metabolites, diseases and drugs, based on the statistical significance of associations between user-specified phenotypic keywords and resources connected directly or inferentially through a Semantic Web of biological databases such as MEDLINE, OMIM, pathways, co-expressions, molecular interactions and ontology terms. Since 2005, PosMed has long been used for in silico positional cloning studies to infer candidate disease-responsible genes existing within chromosomal intervals. PosMed is redesigned as a workbench to discover possible functional interpretations for numerous genetic variants found from exome sequencing of human disease samples. We also show that the association search engine enhances the value of mouse bioresources because most knockout mouse resources have no phenotypic annotation, but can be associated inferentially to phenotypes via genes and biomedical documents. For this purpose, we established text-mining rules to the biomedical documents by careful human curation work, and created a huge amount of correct linking between genes and documents. PosMed associates any phenotypic keyword to mouse resources with 20 public databases and four original data sets as of May 2013. PMID:23761449

  3. A Citation-Based Ranking of German-Speaking Researchers in Business Administration with Data of Google Scholar

    Science.gov (United States)

    Dilger, Alexander; Müller, Harry

    2013-01-01

    Rankings of academics can be constructed in two different ways, either based on journal rankings or based on citations. Although citation-based rankings promise some fundamental advantages they are still not common in German-speaking business administration. However, the choice of the underlying database is crucial. This article argues that for…

  4. 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.

  5. GoDec+: Fast and Robust Low-Rank Matrix Decomposition Based on Maximum Correntropy.

    Science.gov (United States)

    Guo, Kailing; Liu, Liu; Xu, Xiangmin; Xu, Dong; Tao, Dacheng

    2017-04-24

    GoDec is an efficient low-rank matrix decomposition algorithm. However, optimal performance depends on sparse errors and Gaussian noise. This paper aims to address the problem that a matrix is composed of a low-rank component and unknown corruptions. We introduce a robust local similarity measure called correntropy to describe the corruptions and, in doing so, obtain a more robust and faster low-rank decomposition algorithm: GoDec+. Based on half-quadratic optimization and greedy bilateral paradigm, we deliver a solution to the maximum correntropy criterion (MCC)-based low-rank decomposition problem. Experimental results show that GoDec+ is efficient and robust to different corruptions including Gaussian noise, Laplacian noise, salt & pepper noise, and occlusion on both synthetic and real vision data. We further apply GoDec+ to more general applications including classification and subspace clustering. For classification, we construct an ensemble subspace from the low-rank GoDec+ matrix and introduce an MCC-based classifier. For subspace clustering, we utilize GoDec+ values low-rank matrix for MCC-based self-expression and combine it with spectral clustering. Face recognition, motion segmentation, and face clustering experiments show that the proposed methods are effective and robust. In particular, we achieve the state-of-the-art performance on the Hopkins 155 data set and the first 10 subjects of extended Yale B for subspace clustering.

  6. MONITORING THE PROCESS MEAN BASED ON QUALITY CONTROL CHARTS USING ON FOLDED RANKED SET SAMPLING

    Directory of Open Access Journals (Sweden)

    Amjad Al-Nasser

    2013-02-01

    Full Text Available In this paper, we propose a new quality control chart for the sample mean based on the folded ranked set sampling (FRSS method. The new charts are compared with the classical control charts using simple random sampling (SRS and ranked set sampling (RSS. A simulation study shows that the FRSS control charts have smaller average run length (ARL compared with their counterpart charts using SRS and RSS.

  7. Entity-based Stochastic Analysis of Search Results for Query Expansion and Results Re-Ranking

    Science.gov (United States)

    2015-11-20

    Entity-based Stochastic Analysis of Search Results for Query Expansion and Results Re-Ranking Pavlos Fafalios and Yannis Tzitzikas Institute of...dynamically and analyzed stochastically using a Random Walk method. The result of this analysis is exploited in two different contexts: for automatic query ...expansion and for re-ranking a set of retrieved results. Eval- uation results in the 2015 TREC Clinical Decision Support Track illustrate that query

  8. Ranking the quality of protein structure models using sidechain based network properties.

    Science.gov (United States)

    Ghosh, Soma; Vishveshwara, Saraswathi

    2014-01-01

    Determining the correct structure of a protein given its sequence still remains an arduous task with many researchers working towards this goal. Most structure prediction methodologies result in the generation of a large number of probable candidates with the final challenge being to select the best amongst these. In this work, we have used Protein Structure Networks of native and modeled proteins in combination with Support Vector Machines to estimate the quality of a protein structure model and finally to provide ranks for these models. Model ranking is performed using regression analysis and helps in model selection from a group of many similar and good quality structures. Our results show that structures with a rank greater than 16 exhibit native protein-like properties while those below 10 are non-native like. The tool is also made available as a web-server ( http://vishgraph.mbu.iisc.ernet.in/GraProStr/native_non_native_ranking.html), where, 5 modelled structures can be evaluated at a given time.

  9. Network Based Integrated Analysis of Phenotype-Genotype Data for Prioritization of Candidate Symptom Genes

    Directory of Open Access Journals (Sweden)

    Xing Li

    2014-01-01

    Full Text Available Background. Symptoms and signs (symptoms in brief are the essential clinical manifestations for individualized diagnosis and treatment in traditional Chinese medicine (TCM. To gain insights into the molecular mechanism of symptoms, we develop a computational approach to identify the candidate genes of symptoms. Methods. This paper presents a network-based approach for the integrated analysis of multiple phenotype-genotype data sources and the prediction of the prioritizing genes for the associated symptoms. The method first calculates the similarities between symptoms and diseases based on the symptom-disease relationships retrieved from the PubMed bibliographic database. Then the disease-gene associations and protein-protein interactions are utilized to construct a phenotype-genotype network. The PRINCE algorithm is finally used to rank the potential genes for the associated symptoms. Results. The proposed method gets reliable gene rank list with AUC (area under curve 0.616 in classification. Some novel genes like CALCA, ESR1, and MTHFR were predicted to be associated with headache symptoms, which are not recorded in the benchmark data set, but have been reported in recent published literatures. Conclusions. Our study demonstrated that by integrating phenotype-genotype relationships into a complex network framework it provides an effective approach to identify candidate genes of symptoms.

  10. 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.

  11. Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

    Directory of Open Access Journals (Sweden)

    Christof Winter

    Full Text Available Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

  12. The ranking of scientists based on scientific publications assessment.

    Science.gov (United States)

    Zerem, Enver

    2017-11-01

    It is generally accepted that the scientific impact factor (Web of Science) and the total number of citations of the articles published in a journal, are the most relevant parameters of the journal's significance. However, the significance of scientists is much more complicated to establish and the value of their scientific production cannot be directly reflected by the importance of the journals in which their articles are published. Evaluating the significance of scientists' accomplishments involves more complicated metrics than just their publication records. Based on a long term of academic experience, the author proposes objective criteria to estimate the scientific merit of an individual's publication record. This metric can serve as a pragmatic tool and the nidus for discussion within the readership of this journal. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

    Directory of Open Access Journals (Sweden)

    Wan Li

    Full Text Available The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial. Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

  14. Patch-Based Image Inpainting via Two-Stage Low Rank Approximation.

    Science.gov (United States)

    Guo, Qiang; Gao, Shanshan; Zhang, Xiaofeng; Yin, Yilong; Zhang, Caiming

    2017-05-09

    To recover the corrupted pixels, traditional inpainting methods based on low-rank priors generally need to solve a convex optimization problem by an iterative singular value shrinkage algorithm. In this paper, we propose a simple method for image inpainting using low rank approximation, which avoids the time-consuming iterative shrinkage. Specifically, if similar patches of a corrupted image are identified and reshaped as vectors, then a patch matrix can be constructed by collecting these similar patch-vectors. Due to its columns being highly linearly correlated, this patch matrix is low-rank. Instead of using an iterative singular value shrinkage scheme, the proposed method utilizes low rank approximation with truncated singular values to derive a closed-form estimate for each patch matrix. Depending upon an observation that there exists a distinct gap in the singular spectrum of patch matrix, the rank of each patch matrix is empirically determined by a heuristic procedure. Inspired by the inpainting algorithms with component decomposition, a two-stage low rank approximation (TSLRA) scheme is designed to recover image structures and refine texture details of corrupted images. Experimental results on various inpainting tasks demonstrate that the proposed method is comparable and even superior to some state-of-the-art inpainting algorithms.

  15. Evaluation of project based learning sufficiency of teacher candidates

    Directory of Open Access Journals (Sweden)

    Vasfi Tugun

    2012-01-01

    Full Text Available The aim of that research, it is the project based learning process suffuciency of teacher candidates who developedmultimedia by working in online and blended groups. Importance of research Being able to guide to studies that is going tobe done about assessment of multimedia projection for project based educational application to teachers and teachercandidates and It has been thought as an advisor source about being arranged new educational environment for the futureto teacher and teacher candidates for project based educational application and multimedia projection. Research is anexperimental study and has been shaped according to pre-test and last-test research model with the two groups. This groupsare online group and blended group. Discussion of research In the result of the study, in the process of project basedlearning, it is determined that the success level in multimedia development of teacher candidates who work in blendedlearning model is higher than the success level of teacher candidates who work in online learning model.

  16. Frictional Behavior of Fe-based Cladding Candidates for PWR

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Young-Ho; Kim, Hyung-Kyu [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Byun, Thak Sang [Oak Ridge National Lab., Oak Ridge (United States)

    2014-10-15

    After the recent nuclear disaster at Fukushima Daiichi reactors, there is a growing consensus on the development of new fuel systems (i.e., accident-tolerant fuel, ATF) that have high safety margins under design-basis accident (DBA) and beyond design-basis accident (BDBA). A common objective of various developing candidates is to archive the outstanding corrosion-resistance under severe accidents such as DBA and DBDA conditions for decreasing hydrogen production and increasing coping time to respond to severe accidents. ATF could be defined as new fuel/cladding system with enhanced accident tolerant to loss of active cooling in the core for a considerably longer time period under severe accidents while maintaining or improving the fuel performance during normal operations. This means that, in normal operating conditions, new fuel systems should be applicable to current operating PWRs for suppressing various degradation mechanisms of current fuel assembly without excessive design changes. When considering that one of the major degradation mechanisms of PWR fuel assemblies is a grid-to-rod fretting (GTRF), it is necessary to examine the tribological behavior of various ATF candidates at initial development stage. In this study, friction and reciprocating wear behavior of two kinds of Fe-based ATF candidates were examined with a reciprocating wear tests at room temperature (RT) air and water. The objective is to examine the compatibilities of these Fe-based alloys against current Zr-based alloy properties, which is used as major structural materials of PWR fuel assemblies. The reciprocating wear behaviors of Fe-based accident-tolerant fuel cladding candidates against current Zr-based alloy has been studied using a reciprocating sliding wear tester in room temperature air and water. Frictional behavior and wear depth were used for evaluating the applicability and compatibilities of Fe-based candidates without significant design changes of PWR fuel assemblies

  17. Ranking library materials

    OpenAIRE

    Lewandowski, Dirk

    2015-01-01

    Purpose: This paper discusses ranking factors suitable for library materials and shows that ranking in general is a complex process and that ranking for library materials requires a variety of techniques. Design/methodology/approach: The relevant literature is reviewed to provide a systematic overview of suitable ranking factors. The discussion is based on an overview of ranking factors used in Web search engines. Findings: While there are a wide variety of ranking factors appl...

  18. Introducing Trimming and Function Ranking to SolidWorks based on Function Analysis

    NARCIS (Netherlands)

    Chechurin, L.S.; Wits, Wessel Willems; Bakker, Hans M.; Vaneker, Thomas H.J.

    2015-01-01

    TRIZ based Function Analysis models existing products based on functional interactions between product parts. Such a function model description is the ideal starting point for product innovation. Design engineers can apply (TRIZ) methods such as trimming and function ranking to this function model

  19. Introducing trimming and function ranking to Solid Works based on function analysis

    NARCIS (Netherlands)

    Chechurin, Leonid S.; Wits, Wessel Willems; Bakker, Hans M.; Cascini, G.; Vaneker, Thomas H.J.

    2011-01-01

    TRIZ based Function Analysis models existing products based on functional interactions between product parts. Such a function model description is the ideal starting point for product innovation. Design engineers can apply (TRIZ) methods such as trimming and function ranking to this function model

  20. Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity

    Directory of Open Access Journals (Sweden)

    Hyuncheol Kim

    2014-01-01

    Full Text Available We address object tracking problem as a multitask feature learning process based on low-rank representation of features with joint sparsity. We first select features with low-rank representation within a number of initial frames to obtain subspace basis. Next, the features represented by the low-rank and sparse property are learned using a modified joint sparsity-based multitask feature learning framework. Both the features and sparse errors are then optimally updated using a novel incremental alternating direction method. The low-rank minimization problem for learning multitask features can be achieved by a few sequences of efficient closed form update process. Since the proposed method attempts to perform the feature learning problem in both multitask and low-rank manner, it can not only reduce the dimension but also improve the tracking performance without drift. Experimental results demonstrate that the proposed method outperforms existing state-of-the-art tracking methods for tracking objects in challenging image sequences.

  1. A meta-analysis based method for prioritizing candidate genes involved in a pre-specific function

    Directory of Open Access Journals (Sweden)

    Jingjing Zhai

    2016-12-01

    Full Text Available The identification of genes associated with a given biological function in plants remains a challenge, although network-based gene prioritization algorithms have been developed for Arabidopsis thaliana and many non-model plant species. Nevertheless, these network-based gene prioritization algorithms have encountered several problems; one in particular is that of unsatisfactory prediction accuracy due to limited network coverage, varying link quality, and/or uncertain network connectivity. Thus a model that integrates complementary biological data may be expected to increase the prediction accuracy of gene prioritization. Towards this goal, we developed a novel gene prioritization method named RafSee, to rank candidate genes using a random forest algorithm that integrates sequence, evolutionary, and epigenetic features of plants. Subsequently, we proposed an integrative approach named RAP (Rank Aggregation-based data fusion for gene Prioritization, in which an order statistics-based meta-analysis was used to aggregate the rank of the network-based gene prioritization method and RafSee, for accurately prioritizing candidate genes involved in a pre-specific biological function. Finally, we showcased the utility of RAP by prioritizing 380 flowering-time genes in Arabidopsis. The ‘leave-one-out’ cross-validation experiment showed that RafSee could work as a complement to a current state-of-art network-based gene prioritization system (AraNet v2. Moreover, RAP ranked 53.68% (204/380 flowering-time genes higher than AraNet v2, resulting in an 39.46% improvement in term of the first quartile rank. Further evaluations also showed that RAP was effective in prioritizing genes-related to different abiotic stresses. To enhance the usability of RAP for Arabidopsis and non-model plant species, an R package implementing the method is freely available at http://bioinfo.nwafu.edu.cn/software.

  2. Evaluating user reputation in online rating systems via an iterative group-based ranking method

    Science.gov (United States)

    Gao, Jian; Zhou, Tao

    2017-05-01

    Reputation is a valuable asset in online social lives and it has drawn increased attention. Due to the existence of noisy ratings and spamming attacks, how to evaluate user reputation in online rating systems is especially significant. However, most of the previous ranking-based methods either follow a debatable assumption or have unsatisfied robustness. In this paper, we propose an iterative group-based ranking method by introducing an iterative reputation-allocation process into the original group-based ranking method. More specifically, the reputation of users is calculated based on the weighted sizes of the user rating groups after grouping all users by their rating similarities, and the high reputation users' ratings have larger weights in dominating the corresponding user rating groups. The reputation of users and the user rating group sizes are iteratively updated until they become stable. Results on two real data sets with artificial spammers suggest that the proposed method has better performance than the state-of-the-art methods and its robustness is considerably improved comparing with the original group-based ranking method. Our work highlights the positive role of considering users' grouping behaviors towards a better online user reputation evaluation.

  3. CT image sequence restoration based on sparse and low-rank decomposition.

    Directory of Open Access Journals (Sweden)

    Shuiping Gou

    Full Text Available Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA, Linearized Alternating Direction Method with Adaptive Penalty (LADMAP and Go Decomposition (GoDec. Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images.

  4. CT image sequence restoration based on sparse and low-rank decomposition.

    Science.gov (United States)

    Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

    2013-01-01

    Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images.

  5. Image restoration via patch orientation-based low-rank matrix approximation and nonlocal means

    Science.gov (United States)

    Zhang, Di; He, Jiazhong; Du, Minghui

    2016-03-01

    Low-rank matrix approximation and nonlocal means (NLM) are two popular techniques for image restoration. Although the basic principle for applying these two techniques is the same, i.e., similar image patches are abundant in the image, previously published related algorithms use either low-rank matrix approximation or NLM because they manipulate the information of similar patches in different ways. We propose a method for image restoration by jointly using low-rank matrix approximation and NLM in a unified minimization framework. To improve the accuracy of determining similar patches, we also propose a patch similarity measurement based on curvelet transform. Extensive experiments on image deblurring and compressive sensing image recovery validate that the proposed method achieves better results than many state-of-the-art algorithms in terms of both quantitative measures and visual perception.

  6. Enhancing Sketch-Based Image Retrieval by Re-Ranking and Relevance Feedback.

    Science.gov (United States)

    Xueming Qian; Xianglong Tan; Yuting Zhang; Richang Hong; Meng Wang

    2016-01-01

    A sketch-based image retrieval often needs to optimize the tradeoff between efficiency and precision. Index structures are typically applied to large-scale databases to realize efficient retrievals. However, the performance can be affected by quantization errors. Moreover, the ambiguousness of user-provided examples may also degrade the performance, when compared with traditional image retrieval methods. Sketch-based image retrieval systems that preserve the index structure are challenging. In this paper, we propose an effective sketch-based image retrieval approach with re-ranking and relevance feedback schemes. Our approach makes full use of the semantics in query sketches and the top ranked images of the initial results. We also apply relevance feedback to find more relevant images for the input query sketch. The integration of the two schemes results in mutual benefits and improves the performance of the sketch-based image retrieval.

  7. Environmental and health hazard ranking and assessment of plastic polymers based on chemical composition

    Energy Technology Data Exchange (ETDEWEB)

    Lithner, Delilah, E-mail: delilah.lithner@gmail.com; Larsson, Ake; Dave, Goeran

    2011-08-15

    Plastics constitute a large material group with a global annual production that has doubled in 15 years (245 million tonnes in 2008). Plastics are present everywhere in society and the environment, especially the marine environment, where large amounts of plastic waste accumulate. The knowledge of human and environmental hazards and risks from chemicals associated with the diversity of plastic products is very limited. Most chemicals used for producing plastic polymers are derived from non-renewable crude oil, and several are hazardous. These may be released during the production, use and disposal of the plastic product. In this study the environmental and health hazards of chemicals used in 55 thermoplastic and thermosetting polymers were identified and compiled. A hazard ranking model was developed for the hazard classes and categories in the EU classification and labelling (CLP) regulation which is based on the UN Globally Harmonized System. The polymers were ranked based on monomer hazard classifications, and initial assessments were made. The polymers that ranked as most hazardous are made of monomers classified as mutagenic and/or carcinogenic (category 1A or 1B). These belong to the polymer families of polyurethanes, polyacrylonitriles, polyvinyl chloride, epoxy resins, and styrenic copolymers. All have a large global annual production (1-37 million tonnes). A considerable number of polymers (31 out of 55) are made of monomers that belong to the two worst of the ranking model's five hazard levels, i.e. levels IV-V. The polymers that are made of level IV monomers and have a large global annual production (1-5 million tonnes) are phenol formaldehyde resins, unsaturated polyesters, polycarbonate, polymethyl methacrylate, and urea-formaldehyde resins. This study has identified hazardous substances used in polymer production for which the risks should be evaluated for decisions on the need for risk reduction measures, substitution, or even phase out

  8. A Multiobjective Programming Method for Ranking All Units Based on Compensatory DEA Model

    Directory of Open Access Journals (Sweden)

    Haifang Cheng

    2014-01-01

    Full Text Available In order to rank all decision making units (DMUs on the same basis, this paper proposes a multiobjective programming (MOP model based on a compensatory data envelopment analysis (DEA model to derive a common set of weights that can be used for the full ranking of all DMUs. We first revisit a compensatory DEA model for ranking all units, point out the existing problem for solving the model, and present an improved algorithm for which an approximate global optimal solution of the model can be obtained by solving a sequence of linear programming. Then, we applied the key idea of the compensatory DEA model to develop the MOP model in which the objectives are to simultaneously maximize all common weights under constraints that the sum of efficiency values of all DMUs is equal to unity and the sum of all common weights is also equal to unity. In order to solve the MOP model, we transform it into a single objective programming (SOP model using a fuzzy programming method and solve the SOP model using the proposed approximation algorithm. To illustrate the ranking method using the proposed method, two numerical examples are solved.

  9. A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.

    Science.gov (United States)

    Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe

    2012-04-01

    We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.

  10. Partial Kernelization for Rank Aggregation: Theory and Experiments

    Science.gov (United States)

    Betzler, Nadja; Bredereck, Robert; Niedermeier, Rolf

    Rank Aggregation is important in many areas ranging from web search over databases to bioinformatics. The underlying decision problem Kemeny Score is NP-complete even in case of four input rankings to be aggregated into a "median ranking". We study efficient polynomial-time data reduction rules that allow us to find optimal median rankings. On the theoretical side, we improve a result for a "partial problem kernel" from quadratic to linear size. On the practical side, we provide encouraging experimental results with data based on web search and sport competitions, e.g., computing optimal median rankings for real-world instances with more than 100 candidates within milliseconds.

  11. Interval estimation for rank correlation coefficients based on the probit transformation with extension to measurement error correction of correlated ranked data.

    Science.gov (United States)

    Rosner, Bernard; Glynn, Robert J

    2007-02-10

    The Spearman (rho(s)) and Kendall (tau) rank correlation coefficient are routinely used as measures of association between non-normally distributed random variables. However, confidence limits for rho(s) are only available under the assumption of bivariate normality and for tau under the assumption of asymptotic normality of tau. In this paper, we introduce another approach for obtaining confidence limits for rho(s) or tau based on the arcsin transformation of sample probit score correlations. This approach is shown to be applicable for an arbitrary bivariate distribution. The arcsin-based estimators for rho(s) and tau (denoted by rho(s,a), tau(a)) are shown to have asymptotic relative efficiency (ARE) of 9/pi2 compared with the usual estimators rho(s) and tau when rho(s) and tau are, respectively, 0. In some nutritional applications, the Spearman rank correlation between nutrient intake as assessed by a reference instrument versus nutrient intake as assessed by a surrogate instrument is used as a measure of validity of the surrogate instrument. However, if only a single replicate (or a few replicates) are available for the reference instrument, then the estimated Spearman rank correlation will be downwardly biased due to measurement error. In this paper, we use the probit transformation as a tool for specifying an ANOVA-type model for replicate ranked data resulting in a point and interval estimate of a measurement error corrected rank correlation. This extends previous work by Rosner and Willett for obtaining point and interval estimates of measurement error corrected Pearson correlations. 2006 John Wiley & Sons, Ltd.

  12. A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model

    OpenAIRE

    Tavana, Madjid; LoPinto, Frank; Smither, James W.

    2007-01-01

    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 differe...

  13. Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error.

    Science.gov (United States)

    Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi

    2016-12-01

    This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that

  14. A note on ranking efficient DMUs based on a single virtual inefficient DMU in DEA

    Directory of Open Access Journals (Sweden)

    Farzad Rezai Balf

    2017-11-01

    Full Text Available In this paper we give a comment on paper by Shetty and Pakkala [U. Shetty, T.P.M. Pakkala, (2010, Ranking efficient DMUs based on single virtual inefficient DMU in DEA. OPSEARCH, 47 (1:50-72]. They proposed an approach to rank the efficient decision making units based on a virtual DMU in the constant return to scale DEA model. The input and output levels of this virtual DMU are the average of input and outputs of all DMUs. We obtain another method for select virtual DMU as negative ideal DMU. Our approach doesn't need to existence at least an inefficient DMU in the set DMUs. In addition, it can be used in constant and variable return to scale DEA models. This brief comment provides an alternative approach for their work.

  15. Personalization by Relevance Ranking Feedback in Impression-based Retrieval for Multimedia Database

    Directory of Open Access Journals (Sweden)

    Tsuyoshi TAKAYAMA

    2005-04-01

    Full Text Available This paper proposes an approach to personalization by relevance `ranking' feedback in impression-based retrieval for a multimedia database. Impression-based retrieval is a kind of ambiguous retrieval, and it enables a database user to find not only a known data but also an unknown data to him/her. Conventional approaches using relevance feedback technique only return a binary information: `relevant' or `not relevant', for his/her retrieval intention. In this paper, he/she returns each relevance ranking to his/her retrieval intention for top n data of a retrieval result. From this feedback information, an adjustment data inherent to him/her is produced, and utilized for personalization. We show its effectiveness by an evaluation using our pilot system.

  16. A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

    Science.gov (United States)

    Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

    2009-11-01

    A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

  17. Ranking of CMIP5-based global climate models for India using compromise programming

    Science.gov (United States)

    Srinivasa Raju, K.; Sonali, P.; Nagesh Kumar, D.

    2017-05-01

    Thirty-six Coupled Model Intercomparison Project-5-based global climate models (GCMs) are explored to evaluate the performance of maximum ( T max) and minimum ( T min) temperature simulations for India covering 40 grid points. Three performance indicators used for evaluating GCMs are correlation coefficient (CC), normalised root mean square error (NRMSE) and skill score (SS). Entropy method is applied to compute the weights of the three indicators employed. However, equal weights are also considered as part of sensitivity analysis studies. Compromise programming (CP), a distance-based decision-making technique, is employed to rank the GCMs. Group decision-making approach is used to aggregate the ranking patterns obtained for individual grid points. A simple but effective ensemble approach is also suggested.

  18. Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting.

    Science.gov (United States)

    Hoshikawa, K; Ono, S

    2017-02-01

    Multicriteria decision analysis (MCDA) has been generally considered a promising decision-making methodology for the assessment of drug benefit-risk profiles. There have been many discussions in both public and private sectors on its feasibility and applicability, but it has not been employed in official decision-makings. For the purpose of examining to what extent MCDA would reflect the first-hand, intuitive preference of evaluators in practical pharmaceutical assessments, we conducted a questionnaire survey involving the participation of employees of pharmaceutical companies. Showing profiles of the efficacy and safety of four hypothetical drugs, each respondent was asked to rank them following the standard MCDA process and then to rank them intuitively (i.e. without applying any analytical framework). These two approaches resulted in substantially different ranking patterns from the same individuals, and the concordance rate was surprisingly low (17%). Although many respondents intuitively showed a preference for mild, balanced risk-benefit profiles over profiles with a conspicuous advantage in either risk or benefit, the ranking orders based on MCDA scores did not reflect the intuitive preference. Observed discrepancies between the rankings seemed to be primarily attributed to the structural characteristics of MCDA, which assumes that evaluation on each benefit and risk component should have monotonic impact on final scores. It would be difficult for MCDA to reflect commonly observed non-monotonic preferences for risk and benefit profiles. Possible drawbacks of MCDA should be further investigated prior to the real-world application of its benefit-risk assessment. © 2016 John Wiley & Sons Ltd.

  19. Ranking Entity Based on Both of Word Frequency and Word Sematic Features

    OpenAIRE

    Jin, Xiao-Bo; Geng, Guang-Gang; Huang, Kaizhu; Yan, Zhi-Wei

    2016-01-01

    Entity search is a new application meeting either precise or vague requirements from the search engines users. Baidu Cup 2016 Challenge just provided such a chance to tackle the problem of the entity search. We achieved the first place with the average MAP scores on 4 tasks including movie, tvShow, celebrity and restaurant. In this paper, we propose a series of similarity features based on both of the word frequency features and the word semantic features and describe our ranking architecture...

  20. A rank based social norms model of how people judge their levels of drunkenness whilst intoxicated.

    Science.gov (United States)

    Moore, Simon C; Wood, Alex M; Moore, Laurence; Shepherd, Jonathan; Murphy, Simon; Brown, Gordon D A

    2016-09-13

    A rank based social norms model predicts that drinkers' judgements about their drinking will be based on the rank of their breath alcohol level amongst that of others in the immediate environment, rather than their actual breath alcohol level, with lower relative rank associated with greater feelings of safety. This study tested this hypothesis and examined how people judge their levels of drunkenness and the health consequences of their drinking whilst they are intoxicated in social drinking environments. Breath alcohol testing of 1,862 people (mean age = 26.96 years; 61.86 % male) in drinking environments. A subset (N = 400) also answered four questions asking about their perceptions of their drunkenness and the health consequences of their drinking (plus background measures). Perceptions of drunkenness and the health consequences of drinking were regressed on: (a) breath alcohol level, (b) the rank of the breath alcohol level amongst that of others in the same environment, and (c) covariates. Only rank of breath alcohol level predicted perceptions: How drunk they felt (b 3.78, 95 % CI 1.69 5.87), how extreme they regarded their drinking that night (b 3.7, 95 % CI 1.3 6.20), how at risk their long-term health was due to their current level of drinking (b 4.1, 95 % CI 0.2 8.0) and how likely they felt they would experience liver cirrhosis (b 4.8. 95 % CI 0.7 8.8). People were more influenced by more sober others than by more drunk others. Whilst intoxicated and in drinking environments, people base judgements regarding their drinking on how their level of intoxication ranks relative to that of others of the same gender around them, not on their actual levels of intoxication. Thus, when in the company of others who are intoxicated, drinkers were found to be more likely to underestimate their own level of drinking, drunkenness and associated risks. The implications of these results, for example that increasing the numbers of sober people in night time

  1. A rank based social norms model of how people judge their levels of drunkenness whilst intoxicated

    Directory of Open Access Journals (Sweden)

    Simon C. Moore

    2016-09-01

    Full Text Available Abstract Background A rank based social norms model predicts that drinkers’ judgements about their drinking will be based on the rank of their breath alcohol level amongst that of others in the immediate environment, rather than their actual breath alcohol level, with lower relative rank associated with greater feelings of safety. This study tested this hypothesis and examined how people judge their levels of drunkenness and the health consequences of their drinking whilst they are intoxicated in social drinking environments. Methods Breath alcohol testing of 1,862 people (mean age = 26.96 years; 61.86 % male in drinking environments. A subset (N = 400 also answered four questions asking about their perceptions of their drunkenness and the health consequences of their drinking (plus background measures. Results Perceptions of drunkenness and the health consequences of drinking were regressed on: (a breath alcohol level, (b the rank of the breath alcohol level amongst that of others in the same environment, and (c covariates. Only rank of breath alcohol level predicted perceptions: How drunk they felt (b 3.78, 95 % CI 1.69 5.87, how extreme they regarded their drinking that night (b 3.7, 95 % CI 1.3 6.20, how at risk their long-term health was due to their current level of drinking (b 4.1, 95 % CI 0.2 8.0 and how likely they felt they would experience liver cirrhosis (b 4.8. 95 % CI 0.7 8.8. People were more influenced by more sober others than by more drunk others. Conclusion Whilst intoxicated and in drinking environments, people base judgements regarding their drinking on how their level of intoxication ranks relative to that of others of the same gender around them, not on their actual levels of intoxication. Thus, when in the company of others who are intoxicated, drinkers were found to be more likely to underestimate their own level of drinking, drunkenness and associated risks. The implications of these results, for example

  2. A computer vision based candidate for functional balance test.

    Science.gov (United States)

    Nalci, Alican; Khodamoradi, Alireza; Balkan, Ozgur; Nahab, Fatta; Garudadri, Harinath

    2015-08-01

    Balance in humans is a motor skill based on complex multimodal sensing, processing and control. Ability to maintain balance in activities of daily living (ADL) is compromised due to aging, diseases, injuries and environmental factors. Center for Disease Control and Prevention (CDC) estimate of the costs of falls among older adults was $34 billion in 2013 and is expected to reach $54.9 billion in 2020. In this paper, we present a brief review of balance impairments followed by subjective and objective tools currently used in clinical settings for human balance assessment. We propose a novel computer vision (CV) based approach as a candidate for functional balance test. The test will take less than a minute to administer and expected to be objective, repeatable and highly discriminative in quantifying ability to maintain posture and balance. We present an informal study with preliminary data from 10 healthy volunteers, and compare performance with a balance assessment system called BTrackS Balance Assessment Board. Our results show high degree of correlation with BTrackS. The proposed system promises to be a good candidate for objective functional balance tests and warrants further investigations to assess validity in clinical settings, including acute care, long term care and assisted living care facilities. Our long term goals include non-intrusive approaches to assess balance competence during ADL in independent living environments.

  3. 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......This paper explores a multi-criteria outranking methodology that is designed to both handle uncertain and imprecise data in describing alternatives as well as treating the decision maker's preference information in a sensible way that re flects the difficulties in articulating preferences. Based...... on fuzzy interval degrees, representing and measuring data imprecision, this procedure obtains a set of semi-equivalence classes assigning an intransitive order on the alternatives. Relevance measures are then explored for ranking alternatives with respect to the semi-equivalence classes, and a final...

  4. ROCIT : a visual object recognition algorithm based on a rank-order coding scheme.

    Energy Technology Data Exchange (ETDEWEB)

    Gonzales, Antonio Ignacio; Reeves, Paul C.; Jones, John J.; Farkas, Benjamin D.

    2004-06-01

    This document describes ROCIT, a neural-inspired object recognition algorithm based on a rank-order coding scheme that uses a light-weight neuron model. ROCIT coarsely simulates a subset of the human ventral visual stream from the retina through the inferior temporal cortex. It was designed to provide an extensible baseline from which to improve the fidelity of the ventral stream model and explore the engineering potential of rank order coding with respect to object recognition. This report describes the baseline algorithm, the model's neural network architecture, the theoretical basis for the approach, and reviews the history of similar implementations. Illustrative results are used to clarify algorithm details. A formal benchmark to the 1998 FERET fafc test shows above average performance, which is encouraging. The report concludes with a brief review of potential algorithmic extensions for obtaining scale and rotational invariance.

  5. Evaluation of Vienna’s World Economic Position Based on Global and World City Rankings

    Directory of Open Access Journals (Sweden)

    Andrea Uszkai

    2016-12-01

    Full Text Available Metropolitan areas play a dominant role in today’s economic, social and environmental processes; therefore the scientific interest has also increased related to the global and world cities. They can be considered as key players of the world economy and a very complex competition takes place among them, which crosses the national state borders. Every city tries to reach the most favorable position and this rivalry has helped the birth of several city rankings. This paper has two important aims. Firstly, it explains the term of the world and global city based on the international literature and it is also looking for the answer, whether the Austrian capital belongs to which category. Secondly, it examines the position of Vienna in the different world and global city rankings.

  6. Assembly line balancing with resource constraints using new rank-based crossovers

    Science.gov (United States)

    Kamarudin, N. H.; Rashid, M. F. F. Ab.

    2017-10-01

    Assembly line balancing (ALB) is about distributing the assembly tasks into workstations with the almost equal workload. Recently, researchers started to consider the resource constraints in ALB such as machine and worker, to make the assembly layout more efficient. This paper presents an ALB with resource constraints (ALB-RC) to minimize the workstation, machine and worker. For the optimization purpose, genetic algorithm (GA) with two new crossovers is introduced. The crossovers are developed using ranking approach and known as rank-based crossover type I and type II (RBC-I and RBC-II). These crossovers are tested against popular combinatorial crossovers using 17 benchmark problems. The computational experiment results indicated that the RBC-II has better overall performance because of the balance between divergence and guidance in the reproduction process. In future, the RBC-I and RBC-II will be tested for different variant of ALB problems.

  7. GLRT-Based Spectrum Sensing with Blindly Learned Feature under Rank-1 Assumption

    CERN Document Server

    Zhang, Peng

    2011-01-01

    Prior knowledge can improve the performance of spectrum sensing. Instead of using universal features as prior knowledge, we propose to blindly learn the localized feature at the secondary user. Motivated by pattern recognition in machine learning, we define signal feature as the leading eigenvector of the signal's sample covariance matrix. Feature learning algorithm (FLA) for blind feature learning and feature template matching algorithm (FTM) for spectrum sensing are proposed. Furthermore, we implement the FLA and FTM in hardware. Simulations and hardware experiments show that signal feature can be learned blindly. In addition, by using signal feature as prior knowledge, the detection performance can be improved by about 2 dB. Motivated by experimental results, we derive several GLRT based spectrum sensing algorithms under rank-1 assumption, considering signal feature, signal power and noise power as the available parameters. The performance of our proposed algorithms is tested on both synthesized rank-1 sig...

  8. Environmental and health hazard ranking and assessment of plastic polymers based on chemical composition.

    Science.gov (United States)

    Lithner, Delilah; Larsson, Ake; Dave, Göran

    2011-08-15

    Plastics constitute a large material group with a global annual production that has doubled in 15 years (245 million tonnes in 2008). Plastics are present everywhere in society and the environment, especially the marine environment, where large amounts of plastic waste accumulate. The knowledge of human and environmental hazards and risks from chemicals associated with the diversity of plastic products is very limited. Most chemicals used for producing plastic polymers are derived from non-renewable crude oil, and several are hazardous. These may be released during the production, use and disposal of the plastic product. In this study the environmental and health hazards of chemicals used in 55 thermoplastic and thermosetting polymers were identified and compiled. A hazard ranking model was developed for the hazard classes and categories in the EU classification and labelling (CLP) regulation which is based on the UN Globally Harmonized System. The polymers were ranked based on monomer hazard classifications, and initial assessments were made. The polymers that ranked as most hazardous are made of monomers classified as mutagenic and/or carcinogenic (category 1A or 1B). These belong to the polymer families of polyurethanes, polyacrylonitriles, polyvinyl chloride, epoxy resins, and styrenic copolymers. All have a large global annual production (1-37 million tonnes). A considerable number of polymers (31 out of 55) are made of monomers that belong to the two worst of the ranking model's five hazard levels, i.e. levels IV-V. The polymers that are made of level IV monomers and have a large global annual production (1-5 million tonnes) are phenol formaldehyde resins, unsaturated polyesters, polycarbonate, polymethyl methacrylate, and urea-formaldehyde resins. This study has identified hazardous substances used in polymer production for which the risks should be evaluated for decisions on the need for risk reduction measures, substitution, or even phase out. Copyright

  9. Academic rankings: an approach to a Portuguese ranking

    OpenAIRE

    Bernardino, Pedro; Marques,Rui

    2009-01-01

    The academic rankings are a controversial subject in higher education. However, despite all the criticism, academic rankings are here to stay and more and more different stakeholders use rankings to obtain information about the institutions’ performance. The two most well-known rankings, The Times and the Shanghai Jiao Tong University rankings have different methodologies. The Times ranking is based on peer review, whereas the Shanghai ranking has only quantitative indicators and is mainly ba...

  10. 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

  11. Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation

    Directory of Open Access Journals (Sweden)

    Pandiarajan K.

    2014-09-01

    Full Text Available This paper presents an effective method of network overload management in power systems. The three competing objectives 1 generation cost 2 transmission line overload and 3 real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO and Differential evolution (DE. Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem

  12. Reference Information Based Remote Sensing Image Reconstruction with Generalized Nonconvex Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Hongyang Lu

    2016-06-01

    Full Text Available Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1 we propose a nonconvex low-rank approximation for reconstructing RSI; (2 we inject reference prior information to overcome over smoothed edges and texture detail losses; (3 on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.

  13. Acceleration of MR parameter mapping using annihilating filter-based low rank hankel matrix (ALOHA).

    Science.gov (United States)

    Lee, Dongwook; Jin, Kyong Hwan; Kim, Eung Yeop; Park, Sung-Hong; Ye, Jong Chul

    2016-12-01

    MR parameter mapping is one of clinically valuable MR imaging techniques. However, increased scan time makes it difficult for routine clinical use. This article aims at developing an accelerated MR parameter mapping technique using annihilating filter based low-rank Hankel matrix approach (ALOHA). When a dynamic sequence can be sparsified using spatial wavelet and temporal Fourier transform, this results in a rank-deficient Hankel structured matrix that is constructed using weighted k-t measurements. ALOHA then utilizes the low rank matrix completion algorithm combined with a multiscale pyramidal decomposition to estimate the missing k-space data. Spin-echo inversion recovery and multiecho spin echo pulse sequences for T1 and T2 mapping, respectively, were redesigned to perform undersampling along the phase encoding direction according to Gaussian distribution. The missing k-space is reconstructed using ALOHA. Then, the parameter maps were constructed using nonlinear regression. Experimental results confirmed that ALOHA outperformed the existing compressed sensing algorithms. Compared with the existing methods, the reconstruction errors appeared scattered throughout the entire images rather than exhibiting systematic distortion along edges and the parameter maps. Given that many diagnostic errors are caused by the systematic distortion of images, ALOHA may have a great potential for clinical applications. Magn Reson Med 76:1848-1864, 2016. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  14. A dose-volume-based tool for evaluating and ranking IMRT treatment plans.

    Science.gov (United States)

    Miften, Moyed M; Das, Shiva K; Su, Min; Marks, Lawrence B

    2004-01-01

    External beam radiotherapy is commonly used for patients with cancer. While tumor shrinkage and palliation are frequently achieved, local control and cure remain elusive for many cancers. With regard to local control, the fundamental problem is that radiotherapy-induced normal tissue injury limits the dose that can be delivered to the tumor. While intensity-modulated radiation therapy (IMRT) allows for the delivery of higher tumor doses and the sparing of proximal critical structures, multiple competing plans can be generated based on dosimetric and/or biological constraints that need to be considered/compared. In this work, an IMRT treatment plan evaluation and ranking tool, based on dosimetric criteria, is presented. The treatment plan with the highest uncomplicated target conformity index (TCI+) is ranked at the top. The TCI+ is a dose-volume-based index that considers both a target conformity index (TCI) and a normal tissue-sparing index (NTSI). TCI+ is designed to assist in the process of judging the merit of a clinical treatment plan. To demonstrate the utility of this tool, several competing lung and prostate IMRT treatment plans are compared. Results show that the plan with the highest TCI+ values accomplished the competing goals of tumor coverage and critical structures sparing best, among rival treatment plans for both treatment sites. The study demonstrates, first, that dose-volume-based indices, which summarize complex dose distributions through a single index, can be used to automatically select the optimal plan among competing plans, and second, that this dose-volume-based index may be appropriate for ranking IMRT dose distributions.

  15. Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  16. Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  17. Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

    Directory of Open Access Journals (Sweden)

    Rakesh Garg

    2015-06-01

    Full Text Available There is a tremendous growth of the use of the component based software engineering (CBSE approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

  18. A Point-Set-Based Footprint Model and Spatial Ranking Method for Geographic Information Retrieval

    Directory of Open Access Journals (Sweden)

    Yong Gao

    2016-07-01

    Full Text Available In the recent big data era, massive spatial related data are continuously generated and scrambled from various sources. Acquiring accurate geographic information is also urgently demanded. How to accurately retrieve desired geographic information has become the prominent issue, needing to be resolved in high priority. The key technologies in geographic information retrieval are modeling document footprints and ranking documents based on their similarity evaluation. The traditional spatial similarity evaluation methods are mainly performed using a MBR (Minimum Bounding Rectangle footprint model. However, due to its nature of simplification and roughness, the results of traditional methods tend to be isotropic and space-redundant. In this paper, a new model that constructs the footprints in the form of point-sets is presented. The point-set-based footprint coincides the nature of place names in web pages, so it is redundancy-free, consistent, accurate, and anisotropic to describe the spatial extents of documents, and can handle multi-scale geographic information. The corresponding spatial ranking method is also presented based on the point-set-based model. The new similarity evaluation algorithm of this method firstly measures multiple distances for the spatial proximity across different scales, and then combines the frequency of place names to improve the accuracy and precision. The experimental results show that the proposed method outperforms the traditional methods with higher accuracies under different searching scenarios.

  19. Pareto-Ranking Based Quantum-Behaved Particle Swarm Optimization for Multiobjective Optimization

    Directory of Open Access Journals (Sweden)

    Na Tian

    2015-01-01

    Full Text Available A study on pareto-ranking based quantum-behaved particle swarm optimization (QPSO for multiobjective optimization problems is presented in this paper. During the iteration, an external repository is maintained to remember the nondominated solutions, from which the global best position is chosen. The comparison between different elitist selection strategies (preference order, sigma value, and random selection is performed on four benchmark functions and two metrics. The results demonstrate that QPSO with preference order has comparative performance with sigma value according to different number of objectives. Finally, QPSO with sigma value is applied to solve multiobjective flexible job-shop scheduling problems.

  20. Facilitating Software Architecting by Ranking Requirements based on their Impact on the Architecture Process

    NARCIS (Netherlands)

    Galster, Matthias; Eberlein, Armin; Sprinkle, J; Sterritt, R; Breitman, K

    2011-01-01

    Ranking software requirements helps decide what requirements to implement during a software development project, and when. Currently, requirements ranking techniques focus on resource constraints or stakeholder priorities and neglect the effect of requirements on the software architecture process.

  1. Tensor Rank

    OpenAIRE

    Erdtman, Elias; Jönsson, Carl

    2012-01-01

    This master's thesis addresses numerical methods of computing the typical ranks of tensors over the real numbers and explores some properties of tensors over finite fields. We present three numerical methods to compute typical tensor rank. Two of these have already been published and can be used to calculate the lowest typical ranks of tensors and an approximate percentage of how many tensors have the lowest typical ranks (for some tensor formats), respectively. The third method was developed...

  2. Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient.

    Science.gov (United States)

    Shi, Fengjian; Su, Xiaoyan; Qian, Hong; Yang, Ning; Han, Wenhua

    2017-10-16

    In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster-Shafer evidence theory (D-S theory) has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D-S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

  3. A New Method for Defuzzification and Ranking of Fuzzy Numbers Based on the Statistical Beta Distribution

    Directory of Open Access Journals (Sweden)

    A. Rahmani

    2016-01-01

    Full Text Available Granular computing is an emerging computing theory and paradigm that deals with the processing of information granules, which are defined as a number of information entities grouped together due to their similarity, physical adjacency, or indistinguishability. In most aspects of human reasoning, these granules have an uncertain formation, so the concept of granularity of fuzzy information could be of special interest for the applications where fuzzy sets must be converted to crisp sets to avoid uncertainty. This paper proposes a novel method of defuzzification based on the mean value of statistical Beta distribution and an algorithm for ranking fuzzy numbers based on the crisp number ranking system on R. The proposed method is quite easy to use, but the main reason for following this approach is the equality of left spread, right spread, and mode of Beta distribution with their corresponding values in fuzzy numbers within (0,1 interval, in addition to the fact that the resulting method can satisfy all reasonable properties of fuzzy quantity ordering defined by Wang et al. The algorithm is illustrated through several numerical examples and it is then compared with some of the other methods provided by literature.

  4. Fuzzy Group Decision Making Approach for Ranking Work Stations Based on Physical Pressure

    Directory of Open Access Journals (Sweden)

    Hamed Salmanzadeh

    2014-06-01

    Full Text Available This paper proposes a Fuzzy Group Decision Making approach for ranking work stations based on physical pressure. Fuzzy group decision making approach allows experts to evaluate different ergonomic factors using linguistic terms such as very high, high, medium, low, very low, rather than precise numerical values. In this way, there is no need to measure parameters and evaluation can be easily made in a group. According to ergonomics much work contents and situations, accompanied with multiple parameters and uncertainties, fuzzy group decision making is the best way to evaluate such a chameleon of concept. A case study was down to utilize the approach and illustrate its application in ergonomic assessment and ranking the work stations based on work pressure and found that this approach provides flexibility, practicality, efficiency in making decision around ergonomics areas. The normalized defuzzification numbers which are resulted from this method are compared with result of quantitative assessment of Automotive Assembly Work Sheet auto, it’s demonstrated that the proposed method result is 10% less than Automotive Assembly Work Sheet, approximately.

  5. Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient

    Directory of Open Access Journals (Sweden)

    Fengjian Shi

    2017-10-01

    Full Text Available In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster–Shafer evidence theory (D–S theory has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D–S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

  6. Hyperspectral Anomaly Detection Based on Low-Rank Representation and Learned Dictionary

    Directory of Open Access Journals (Sweden)

    Yubin Niu

    2016-03-01

    Full Text Available In this paper, a novel hyperspectral anomaly detector based on low-rank representation (LRR and learned dictionary (LD has been proposed. This method assumes that a two-dimensional matrix transformed from a three-dimensional hyperspectral imagery can be decomposed into two parts: a low rank matrix representing the background and a sparse matrix standing for the anomalies. The direct application of LRR model is sensitive to a tradeoff parameter that balances the two parts. To mitigate this problem, a learned dictionary is introduced into the decomposition process. The dictionary is learned from the whole image with a random selection process and therefore can be viewed as the spectra of the background only. It also requires a less computational cost with the learned dictionary. The statistic characteristic of the sparse matrix allows the application of basic anomaly detection method to obtain detection results. Experimental results demonstrate that, compared to other anomaly detection methods, the proposed method based on LRR and LD shows its robustness and has a satisfactory anomaly detection result.

  7. Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance

    Science.gov (United States)

    Chattopadhyaya, Pradip Kumar; Basu, Sushil Kumar; Majumdar, Manik Chandra

    2017-06-01

    In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence `random number simulation' is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.

  8. 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

  9. Prioritizing Disease Candidate Proteins in Cardiomyopathy-Specific Protein-Protein Interaction Networks Based on “Guilt by Association” Analysis

    Science.gov (United States)

    He, Weiming; Li, Weiguo; Qu, Xiaoli; Liang, Binhua; Gao, Qianping; Feng, Chenchen; Jia, Xu; Lv, Yana; Zhang, Siya; Li, Xia

    2013-01-01

    The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial). Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on “guilt by association” analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on “guilt by association” analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way. PMID:23940716

  10. Selection and ranking of occupational safety indicators based on fuzzy AHP: A case study in road construction companies

    OpenAIRE

    Janackovic, Goran Lj.; Suzana M. Savic; Stankovic, Miomir S.

    2013-01-01

    This paper presents the factors, performance, and indicators of occupational safety, as well as a method to select and rank occupational safety indicators based on the expert evaluation method and the fuzzy analytic hierarchy process (fuzzy AHP). A case study is done on road construction companies in Serbia. The key safety performance indicators for the road construction industry are identified and ranked according to the results of a survey that included experts who assessed occupational saf...

  11. Speech Denoising in White Noise Based on Signal Subspace Low-rank Plus Sparse Decomposition

    Directory of Open Access Journals (Sweden)

    yuan Shuai

    2017-01-01

    Full Text Available In this paper, a new subspace speech enhancement method using low-rank and sparse decomposition is presented. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank for the underlying human speech signal. Then the low-rank and sparse decomposition is performed with the guidance of speech rank value to remove the noise. Extensive experiments have been carried out in white Gaussian noise condition, and experimental results show the proposed method performs better than conventional speech enhancement methods, in terms of yielding less residual noise and lower speech distortion.

  12. A new betweenness centrality measure based on an algorithm for ranking the nodes of a network

    OpenAIRE

    Agryzkov, Taras; Oliver, Jose L.; Tortosa Grau, Leandro; Vicent, Jose F.

    2014-01-01

    We propose and discuss a new centrality index for urban street patterns represented as networks in geographical space. This centrality measure, that we call ranking-betweenness centrality, combines the idea behind the random-walk betweenness centrality measure and the idea of ranking the nodes of a network produced by an adapted PageRank algorithm. We initially use a PageRank algorithm in which we are able to transform some information of the network that we want to analyze into numerical val...

  13. A Direct Elliptic Solver Based on Hierarchically Low-Rank Schur Complements

    KAUST Repository

    Chávez, Gustavo

    2017-03-17

    A parallel fast direct solver for rank-compressible block tridiagonal linear systems is presented. Algorithmic synergies between Cyclic Reduction and Hierarchical matrix arithmetic operations result in a solver with O(Nlog2N) arithmetic complexity and O(NlogN) memory footprint. We provide a baseline for performance and applicability by comparing with well-known implementations of the $$\\\\mathcal{H}$$ -LU factorization and algebraic multigrid within a shared-memory parallel environment that leverages the concurrency features of the method. Numerical experiments reveal that this method is comparable with other fast direct solvers based on Hierarchical Matrices such as $$\\\\mathcal{H}$$ -LU and that it can tackle problems where algebraic multigrid fails to converge.

  14. A rank-based sequence aligner with applications in phylogenetic analysis.

    Directory of Open Access Journals (Sweden)

    Liviu P Dinu

    Full Text Available Recent tools for aligning short DNA reads have been designed to optimize the trade-off between correctness and speed. This paper introduces a method for assigning a set of short DNA reads to a reference genome, under Local Rank Distance (LRD. The rank-based aligner proposed in this work aims to improve correctness over speed. However, some indexing strategies to speed up the aligner are also investigated. The LRD aligner is improved in terms of speed by storing [Formula: see text]-mer positions in a hash table for each read. Another improvement, that produces an approximate LRD aligner, is to consider only the positions in the reference that are likely to represent a good positional match of the read. The proposed aligner is evaluated and compared to other state of the art alignment tools in several experiments. A set of experiments are conducted to determine the precision and the recall of the proposed aligner, in the presence of contaminated reads. In another set of experiments, the proposed aligner is used to find the order, the family, or the species of a new (or unknown organism, given only a set of short Next-Generation Sequencing DNA reads. The empirical results show that the aligner proposed in this work is highly accurate from a biological point of view. Compared to the other evaluated tools, the LRD aligner has the important advantage of being very accurate even for a very low base coverage. Thus, the LRD aligner can be considered as a good alternative to standard alignment tools, especially when the accuracy of the aligner is of high importance. Source code and UNIX binaries of the aligner are freely available for future development and use at http://lrd.herokuapp.com/aligners. The software is implemented in C++ and Java, being supported on UNIX and MS Windows.

  15. Whole genome homology-based identification of candidate genes ...

    African Journals Online (AJOL)

    ... and might play some important roles in drought tolerance in sesame. Our results provided genomic resources for further functional analysis and genetic engineering towards drought tolerance improvement in sesame. Keywords: Sesamum indicum, candidate genes, drought tolerance, orthologous gene, whole genome ...

  16. Whole genome homology-based identification of candidate genes ...

    African Journals Online (AJOL)

    Josephine Erhiakporeh

    2016-07-06

    Jul 6, 2016 ... 1,075 from potato and 270 from tomato, comparative analysis against sesame genome led to the identification of a set of 75 candidate genes (42, 22 and 11 from Arabidopsis, potato and tomato, respectively). Mapping results .... applying drought stress by withholding water for 5 days. At this stage, all plants ...

  17. Ranking serials in oceanography: An analysis based on the Indian contributions and their citations

    Digital Repository Service at National Institute of Oceanography (India)

    Tapaswi, M.P.; Maheswarappa, B.S.

    negative correlation with a marginal difference of -0.214 is observed between these two rank lists. This difference is attributed to studies from different geographical areas in these two rank sets. Bradford graphs for all datasets, but one, showed typical...

  18. A heuristic ranking approach on capacity benefit margin determination using Pareto-based evolutionary programming technique.

    Science.gov (United States)

    Othman, Muhammad Murtadha; Abd Rahman, Nurulazmi; Musirin, Ismail; Fotuhi-Firuzabad, Mahmud; Rajabi-Ghahnavieh, Abbas

    2015-01-01

    This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

  19. Efficient Multi-keyword Ranked Search over Outsourced Cloud Data based on Homomorphic Encryption

    Directory of Open Access Journals (Sweden)

    Nie Mengxi

    2016-01-01

    Full Text Available With the development of cloud computing, more and more data owners are motivated to outsource their data to the cloud server for great flexibility and less saving expenditure. Because the security of outsourced data must be guaranteed, some encryption methods should be used which obsoletes traditional data utilization based on plaintext, e.g. keyword search. To solve the search of encrypted data, some schemes were proposed to solve the search of encrypted data, e.g. top-k single or multiple keywords retrieval. However, the efficiency of these proposed schemes is not high enough to be impractical in the cloud computing. In this paper, we propose a new scheme based on homomorphic encryption to solve this challenging problem of privacy-preserving efficient multi-keyword ranked search over outsourced cloud data. In our scheme, the inner product is adopted to measure the relevance scores and the technique of relevance feedback is used to reflect the search preference of the data users. Security analysis shows that the proposed scheme can meet strict privacy requirements for such a secure cloud data utilization system. Performance evaluation demonstrates that the proposed scheme can achieve low overhead on both computation and communication.

  20. Behavioral economics and socio-economics journals: A citation-based ranking

    OpenAIRE

    Azar, Ofer H.

    2006-01-01

    Journal quality is a major consideration for authors, readers, and promotion and tenure committees, among others. Unfortunately, most behavioral economics and socio-economics journals are not included in published rankings or in Journal Citation Reports. Consequently, no objective ranking of these journals exists. To address this need, a list of journals in behavioral economics and socio-economics was compiled, and the number of articles that cited each journal was recorded for the periods 20...

  1. Rank-Based Methods for Selection of Landscape Metrics for Land Cover Pattern Change Detection

    Directory of Open Access Journals (Sweden)

    Priyakant Sinha

    2016-02-01

    Full Text Available Often landscape metrics are not thoroughly evaluated with respect to remote sensing data characteristics, such as their behavior in relation to variation in spatial and temporal resolution, number of land cover classes or dominant land cover categories. In such circumstances, it may be difficult to ascertain whether a change in a metric is due to landscape pattern change or due to the inherent variability in multi-temporal data. This study builds on this important consideration and proposes a rank-based metric selection process through computation of four difference-based indices (β, γ, ξ and θ using a Max–Min/Max normalization approach. Land cover classification was carried out for two contrasting provinces, the Liverpool Range (LR and Liverpool Plains (LP, of the Brigalow Belt South Bioregion (BBSB of NSW, Australia. Landsat images, Multi Spectral Scanner (MSS of 1972–1973 and TM of 1987–1988, 1993–1994, 1999–2000 and 2009–2010 were classified using object-based image analysis methods. A total of 30 landscape metrics were computed and their sensitivities towards variation in spatial and temporal resolutions, number of land cover classes and dominant land cover categories were evaluated by computing a score based on Max–Min/Max normalization. The landscape metrics selected on the basis of the proposed methods (Diversity index (MSIDI, Area weighted mean patch fractal dimension (SHAPE_AM, Mean core area (CORE_MN, Total edge (TE, No. of patches (NP, Contagion index (CONTAG, Mean nearest neighbor index (ENN_MN and Mean patch fractal dimension (FRAC_MN were successful and effective in identifying changes over five different change periods. Major changes in land cover pattern after 1993 were observed, and though the trends were similar in both cases, the LP region became more fragmented than the LR. The proposed method was straightforward to apply, and can deal with multiple metrics when selection of an appropriate set can become

  2. Automated confidence ranked classification of randomized controlled trial articles: an aid to evidence-based medicine

    Science.gov (United States)

    Smalheiser, Neil R; McDonagh, Marian S; Yu, Clement; Adams, Clive E; Davis, John M; Yu, Philip S

    2015-01-01

    Objective: For many literature review tasks, including systematic review (SR) and other aspects of evidence-based medicine, it is important to know whether an article describes a randomized controlled trial (RCT). Current manual annotation is not complete or flexible enough for the SR process. In this work, highly accurate machine learning predictive models were built that include confidence predictions of whether an article is an RCT. Materials and Methods: The LibSVM classifier was used with forward selection of potential feature sets on a large human-related subset of MEDLINE to create a classification model requiring only the citation, abstract, and MeSH terms for each article. Results: The model achieved an area under the receiver operating characteristic curve of 0.973 and mean squared error of 0.013 on the held out year 2011 data. Accurate confidence estimates were confirmed on a manually reviewed set of test articles. A second model not requiring MeSH terms was also created, and performs almost as well. Discussion: Both models accurately rank and predict article RCT confidence. Using the model and the manually reviewed samples, it is estimated that about 8000 (3%) additional RCTs can be identified in MEDLINE, and that 5% of articles tagged as RCTs in Medline may not be identified. Conclusion: Retagging human-related studies with a continuously valued RCT confidence is potentially more useful for article ranking and review than a simple yes/no prediction. The automated RCT tagging tool should offer significant savings of time and effort during the process of writing SRs, and is a key component of a multistep text mining pipeline that we are building to streamline SR workflow. In addition, the model may be useful for identifying errors in MEDLINE publication types. The RCT confidence predictions described here have been made available to users as a web service with a user query form front end at: http://arrowsmith.psych

  3. Conflict-cost based random sampling design for parallel MRI with low rank constraints

    Science.gov (United States)

    Kim, Wan; Zhou, Yihang; Lyu, Jingyuan; Ying, Leslie

    2015-05-01

    In compressed sensing MRI, it is very important to design sampling pattern for random sampling. For example, SAKE (simultaneous auto-calibrating and k-space estimation) is a parallel MRI reconstruction method using random undersampling. It formulates image reconstruction as a structured low-rank matrix completion problem. Variable density (VD) Poisson discs are typically adopted for 2D random sampling. The basic concept of Poisson disc generation is to guarantee samples are neither too close to nor too far away from each other. However, it is difficult to meet such a condition especially in the high density region. Therefore the sampling becomes inefficient. In this paper, we present an improved random sampling pattern for SAKE reconstruction. The pattern is generated based on a conflict cost with a probability model. The conflict cost measures how many dense samples already assigned are around a target location, while the probability model adopts the generalized Gaussian distribution which includes uniform and Gaussian-like distributions as special cases. Our method preferentially assigns a sample to a k-space location with the least conflict cost on the circle of the highest probability. To evaluate the effectiveness of the proposed random pattern, we compare the performance of SAKEs using both VD Poisson discs and the proposed pattern. Experimental results for brain data show that the proposed pattern yields lower normalized mean square error (NMSE) than VD Poisson discs.

  4. Data depth and rank-based tests for covariance and spectral density matrices

    KAUST Repository

    Chau, Joris

    2017-06-26

    In multivariate time series analysis, objects of primary interest to study cross-dependences in the time series are the autocovariance or spectral density matrices. Non-degenerate covariance and spectral density matrices are necessarily Hermitian and positive definite, and our primary goal is to develop new methods to analyze samples of such matrices. The main contribution of this paper is the generalization of the concept of statistical data depth for collections of covariance or spectral density matrices by exploiting the geometric properties of the space of Hermitian positive definite matrices as a Riemannian manifold. This allows one to naturally characterize most central or outlying matrices, but also provides a practical framework for rank-based hypothesis testing in the context of samples of covariance or spectral density matrices. First, the desired properties of a data depth function acting on the space of Hermitian positive definite matrices are presented. Second, we propose two computationally efficient pointwise and integrated data depth functions that satisfy each of these requirements. Several applications of the developed methodology are illustrated by the analysis of collections of spectral matrices in multivariate brain signal time series datasets.

  5. TERM WEIGHTING BASED ON POSITIVE IMPACT FACTOR QUERY FOR ARABIC FIQH DOCUMENT RANKING

    Directory of Open Access Journals (Sweden)

    Rizka Sholikah

    2017-02-01

    Full Text Available Query becomes one of the most decisive factor on documents searching. A query contains several words, where one of them will become a key term. Key term is a word that has higher information and value than the others in query. It can be used in any kind of text documents, including Arabic Fiqh documents. Using key term in term weighting process could led to an improvement on result’s relevancy. In Arabic Fiqh document searching, not using the proper method in term weighting will relieve important value of key term. In this paper, we propose a new term weighting method based on Positive Impact Factor Query (PIFQ for Arabic Fiqh documents ranking. PIFQ calculated using key term’s frequency on each category (mazhab on Fiqh. The key term that frequently appear on a certain mazhab will get higher score on that mazhab, and vice versa. After PIFQ values are acquired, TF.IDF calculation will be done to each words. Then, PIFQ weight will be combine with the result from TF.IDF so that the new weight values for each words will be produced. Experimental result performed on a number of queries using 143 Arabic Fiqh documents show that the proposed method is better than traditional TF.IDF, with 77.9%, 83.1%, and 80.1% of precision, recall, and F-measure respectively.

  6. Rank-based biomarker index to assess cadmium ecotoxicity on the earthworm Eisenia andrei.

    Science.gov (United States)

    Panzarino, O; Hyršl, P; Dobeš, P; Vojtek, L; Vernile, P; Bari, G; Terzano, R; Spagnuolo, M; de Lillo, E

    2016-02-01

    A proper soil risk assessment needs to estimate the processes that affect the fate and the behaviour of a contaminant, which are influenced by soil biotic and abiotic components. For this reason, the measurement of biomarkers in soil bioindicator organisms, such as earthworms, has recently received increasing attention. In this study, the earthworm Eisenia andrei was used to assess the pollutant-induced stress syndrome after exposure to sublethal concentrations of Cd (10 or 100 μg g(-1)) in OECD soil, after 14 d of exposure. Cadmium bioaccumulation and potential biomarkers such as catalase (CAT), hydrogen peroxide (H2O2), glutathione-S-transferase (GST), malondialdehyde (MDA), phenoloxidase (PO), metallothioneins (MTs) and genotoxic damage were determined. Results suggested that the exposure to 10 and 100 μg g(-1) Cd significantly increased Cd bioaccumulation, MTs and MDA; 100 μg g(-1) Cd contamination evidenced significantly higher values of H2O2 content and PO activity; CAT activity was inhibited at the higher concentration while GST and Comet assay did not show any significant differences from the control. Rank-based biomarker index showed that both different contaminated soils had an effect on the earthworms and allowed to validate the ecotoxicological relevance of this battery of biomarkers for a promising integrated multi-marker approach in soil monitoring and assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Ranking system for national regulatory jurisdictions based on pesticide standard values in major exposures

    Directory of Open Access Journals (Sweden)

    Zijian Li

    2017-07-01

    Full Text Available To control the risk of human exposure to pesticides, about 50 nations have promulgated pesticide soil regulatory guidance values (RGVs, and 104 nations have provided pesticide drinking water maximum concentration levels (MCLs. In addition, 90 nations have regulated pesticide agricultural commodity maximum residue limits (MRLs. Pesticide standard values (PSVs for one single pesticide varied in a range of six, seven, or even eight orders of magnitude. Some PSVs are too large to prevent the impact of pesticides on human health. Many nations have not provided PSVs for some commonly used pesticides until now. This research has introduced several completeness values and numerical values methods to evaluate the national jurisdiction’s performance on PSVs on a nation base. The national jurisdiction ranking system developed by these methods will be beneficial to the environmental regulation makers in the management of PSVs. Results also indicate that European countries perform better in the regulation of pesticide soil RGVs, drinking water MCLs, and agricultural commodity MRLs.

  8. An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context

    Science.gov (United States)

    James Wickham; Kurt Riitters; Peter Vogt; Jennifer Costanza; Anne Neale

    2017-01-01

    Landscape context is an important factor in restoration ecology, but the use of landscape context for site prioritization has not been as fully developed.We used morphological image processing to identify candidate ecological restoration areas based on their proximity to existing natural vegetation. We identified 1,102,720 candidate ecological restoration areas across...

  9. 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.

  10. Ranking REACH registered neutral, ionizable and ionic organic chemicals based on their aquatic persistency and mobility.

    Science.gov (United States)

    Arp, H P H; Brown, T N; Berger, U; Hale, S E

    2017-07-19

    The contaminants that have the greatest chances of appearing in drinking water are those that are mobile enough in the aquatic environment to enter drinking water sources and persistent enough to survive treatment processes. Herein a screening procedure to rank neutral, ionizable and ionic organic compounds for being persistent and mobile organic compounds (PMOCs) is presented and applied to the list of industrial substances registered under the EU REACH legislation as of December 2014. This comprised 5155 identifiable, unique organic structures. The minimum cut-off criteria considered for PMOC classification herein are a freshwater half-life >40 days, which is consistent with the REACH definition of freshwater persistency, and a log Doc organic carbon-water distribution coefficient). Experimental data were given the highest priority, followed by data from an array of available quantitative structure-activity relationships (QSARs), and as a third resort, an original Iterative Fragment Selection (IFS) QSAR. In total, 52% of the unique REACH structures made the minimum criteria to be considered a PMOC, and 21% achieved the highest PMOC ranking (half-life > 40 days, log Doc < 1.0 between pH 4-10). Only 9% of neutral substances received the highest PMOC ranking, compared to 30% of ionizable compounds and 44% of ionic compounds. Predicted hydrolysis products for all REACH parents (contributing 5043 additional structures) were found to have higher PMOC rankings than their parents, due to increased mobility but not persistence. The fewest experimental data available were for ionic compounds; therefore, their ranking is more uncertain than neutral and ionizable compounds. The most sensitive parameter for the PMOC ranking was freshwater persistency, which was also the parameter that QSARs performed the most poorly at predicting. Several prioritized drinking water contaminants in the EU and USA, and other contaminants of concern, were identified as PMOCs. This

  11. Selection and ranking of occupational safety indicators based on fuzzy AHP: A case study in road construction companies

    Directory of Open Access Journals (Sweden)

    Janackovic, Goran Lj.

    2013-11-01

    Full Text Available This paper presents the factors, performance, and indicators of occupational safety, as well as a method to select and rank occupational safety indicators based on the expert evaluation method and the fuzzy analytic hierarchy process (fuzzy AHP. A case study is done on road construction companies in Serbia. The key safety performance indicators for the road construction industry are identified and ranked according to the results of a survey that included experts who assessed occupational safety risks in these companies. The case study confirmed that organisational factors have a dominant effect on the quality of the occupational health and safety management system in Serbian road construction companies.

  12. Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types

    Science.gov (United States)

    Li, Qiyuan; Stram, Alexander; Chen, Constance; Kar, Siddhartha; Gayther, Simon; Pharoah, Paul; Haiman, Christopher; Stranger, Barbara; Kraft, Peter; Freedman, Matthew L.

    2014-01-01

    The majority of trait-associated loci discovered through genome-wide association studies are located outside of known protein coding regions. Consequently, it is difficult to ascertain the mechanism underlying these variants and to pinpoint the causal alleles. Expression quantitative trait loci (eQTLs) provide an organizing principle to address both of these issues. eQTLs are genetic loci that correlate with RNA transcript levels. Large-scale data sets such as the Cancer Genome Atlas (TCGA) provide an ideal opportunity to systematically evaluate eQTLs as they have generated multiple data types on hundreds of samples. We evaluated the determinants of gene expression (germline variants and somatic copy number and methylation) and performed cis-eQTL analyses for mRNA expression and miRNA expression in five tumor types (breast, colon, kidney, lung and prostate). We next tested 149 known cancer risk loci for eQTL effects, and observed that 42 (28.2%) were significantly associated with at least one transcript. Lastly, we described a fine-mapping strategy for these 42 eQTL target–gene associations based on an integrated strategy that combines the eQTL level of significance and the regulatory potential as measured by DNaseI hypersensitivity. For each of the risk loci, our analyses suggested 1 to 81 candidate causal variants that may be prioritized for downstream functional analysis. In summary, our study provided a comprehensive landscape of the genetic determinants of gene expression in different tumor types and ranked the genes and loci for further functional assessment of known cancer risk loci. PMID:24907074

  13. CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts

    KAUST Repository

    Chermak, Edrisse

    2014-12-21

    Summary: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein–protein and protein–nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.

  14. Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition.

    Science.gov (United States)

    Lu, Lijun; Ma, Xiaomian; Mohy-Ud-Din, Hassan; Ma, Jianhua; Feng, Qianjin; Rahmim, Arman; Chen, Wufan

    2018-02-01

    The absolute quantification of dynamic myocardial perfusion (MP) PET imaging is challenged by the limited spatial resolution of individual frame images due to division of the data into shorter frames. This study aims to develop a method for restoration and enhancement of dynamic PET images. We propose that the image restoration model should be based on multiple constraints rather than a single constraint, given the fact that the image characteristic is hardly described by a single constraint alone. At the same time, it may be possible, but not optimal, to regularize the image with multiple constraints simultaneously. Fortunately, MP PET images can be decomposed into a superposition of background vs. dynamic components via low-rank plus sparse (L + S) decomposition. Thus, we propose an L + S decomposition based MP PET image restoration model and express it as a convex optimization problem. An iterative soft thresholding algorithm was developed to solve the problem. Using realistic dynamic 82Rb MP PET scan data, we optimized and compared its performance with other restoration methods. The proposed method resulted in substantial visual as well as quantitative accuracy improvements in terms of noise versus bias performance, as demonstrated in extensive 82Rb MP PET simulations. In particular, the myocardium defect in the MP PET images had improved visual as well as contrast versus noise tradeoff. The proposed algorithm was also applied on an 8-min clinical cardiac 82Rb MP PET study performed on the GE Discovery PET/CT, and demonstrated improved quantitative accuracy (CNR and SNR) compared to other algorithms. The proposed method is effective for restoration and enhancement of dynamic PET images. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Methodological Bases for Ranking the European Union Countries in Terms of Macroeconomic Security

    Directory of Open Access Journals (Sweden)

    Tymoshenko Olena V.

    2015-11-01

    Full Text Available The fundamental contradictions of existing methodical approaches to assessing the level of the state economic security have been substantiated and proposals on the introduction of a unified methodology for its assessment, which would be acceptable for use at the international level or for a specific cluster of countries, have been developed. Based on the conducted researches it has been found that the there are no unified signs for such classification of countries. To determine the most significant coefficients and critical values of the indicators of economic security, it is appropriate that the countries should be grouped in terms of the level of the economic development proposed by the UN Commission and the IMF. Analysis of the economic security level has been conducted for the countries-members of the European Union as a separate cluster of countries on the example of macroeconomic security indicators. Based on the evaluation it has been found that the proposed list of indicators and their critical values is economically sound and built on the principle of adequacy, representativeness and comprehensiveness. In 2004 the most secure countries of the EU corresponding to the macroeconomic security standards were Austria, Denmark, Sweden, Finland, and as in 2014 the percentage of absolutely secure countries decreased from 14.3 to 7.1%, only Denmark and Sweden remained in the ranking. During the analyzed period Bulgaria and Croatia got into the risk zone, Estonia, Lithuania, Latvia, Romania were in a danger zone. In 2014 Ukraine in terms of its macroeconomic security was in a critical state, which testified about serious structural and system imbalances in its development.

  16. Interpretation of personal genome sequencing data in terms of disease ranks based on mutual information.

    Science.gov (United States)

    Na, Young-Ji; Sohn, Kyung-Ah; Kim, Ju Han

    2015-01-01

    The rapid advances in genome sequencing technologies have resulted in an unprecedented number of genome variations being discovered in humans. However, there has been very limited coverage of interpretation of the personal genome sequencing data in terms of diseases. In this paper we present the first computational analysis scheme for interpreting personal genome data by simultaneously considering the functional impact of damaging variants and curated disease-gene association data. This method is based on mutual information as a measure of the relative closeness between the personal genome and diseases. We hypothesize that a higher mutual information score implies that the personal genome is more susceptible to a particular disease than other diseases. The method was applied to the sequencing data of 50 acute myeloid leukemia (AML) patients in The Cancer Genome Atlas. The utility of associations between a disease and the personal genome was explored using data of healthy (control) people obtained from the 1000 Genomes Project. The ranks of the disease terms in the AML patient group were compared with those in the healthy control group using "Leukemia, Myeloid, Acute" (C04.557.337.539.550) as the corresponding MeSH disease term. Overall, the area under the receiver operating characteristics curve was significantly larger for the AML patient data than for the healthy controls. This methodology could contribute to consequential discoveries and explanations for mining personal genome sequencing data in terms of diseases, and have versatility with respect to genomic-based knowledge such as drug-gene and environmental-factor-gene interactions.

  17. A fuzzy rule based remedial priority ranking system for contaminated sites.

    Science.gov (United States)

    Polat, Sener; Aksoy, Aysegul; Unlu, Kahraman

    2015-01-01

    Contaminated site remediation is generally difficult, time consuming, and expensive. As a result ranking may aid in efficient allocation of resources. In order to rank the priorities of contaminated sites, input parameters relevant to contaminant fate and transport, and exposure assessment should be as accurate as possible. Yet, in most cases these parameters are vague or not precise. Most of the current remediation priority ranking methodologies overlook the vagueness in parameter values or do not go beyond assigning a contaminated site to a risk class. The main objective of this study is to develop an alternative remedial priority ranking system (RPRS) for contaminated sites in which vagueness in parameter values is considered. RPRS aims to evaluate potential human health risks due to contamination using sufficiently comprehensive and readily available parameters in describing the fate and transport of contaminants in air, soil, and groundwater. Vagueness in parameter values is considered by means of fuzzy set theory. A fuzzy expert system is proposed for the evaluation of contaminated sites and a software (ConSiteRPRS) is developed in Microsoft Office Excel 2007 platform. Rankings are employed for hypothetical and real sites. Results show that RPRS is successful in distinguishing between the higher and lower risk cases. © 2014, National Ground Water Association.

  18. 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.

  19. Ranking provinces based on development scale in agriculture sector using taxonomy technique

    Directory of Open Access Journals (Sweden)

    Shahram Rostampour

    2012-08-01

    Full Text Available The purpose of this paper is to determine comparative ranking of agricultural development in different provinces of Iran using taxonomy technique. The independent variables are amount of annual rainfall amount, the number of permanent rivers, the width of pastures and forest, cultivated level of agricultural harvests and garden harvests, number of beehives, the number of fish farming ranches, the number of tractors and combines, the number of cooperative production societies, the number of industrial cattle breeding and aviculture. The results indicate that the maximum development coefficient value is associated with Razavi Khorasan province followed by Mazandaran, East Azarbayjan while the minimum ranking value belongs to Bushehr province.

  20. Web based collaborative decision making in flood risk management: Application of TOPSIS and visualisation techniques for ranking of alternatives

    Science.gov (United States)

    Evers, Mariele; Almoradie, Adrian; Jonoski, Andreja

    2014-05-01

    Development of flood risk management (FRM) plans is ideally carried out in a participatory process with relevant stakeholders. Integrating stakeholders knowledge and information in the decision making process creates trust amongst decision makers and stakeholders that often leads to a successful implementation of measures. Stakeholder participation however does not come without challenges and hindrances (e.g. limitation of resources, spatial distribution and interest to participate). The most challenging type of participation is Collaborative decision making (CDM). A web-based mobile or computer-aided environment offers an innovative approach to address these challenges and hindrances. Moreover, this also enhances participation. Different phases or steps of a CDM process are addressing relevant management objectives, identify scenarios and sets of proposed alternatives, individually rank these alternatives in order of preference and present an aggregated rank to view the groups position. In individual ranking, formulation of judgement should combine scientific facts with stakeholders' beliefs and attitudes. This paper presents a developed web-based CDM framework and its implementation, highlighting the application of a Muti-Criteria Decision Making (MCDM) method for individual ranking of alternative, the method Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with Fuzzy logic. Moreover, an innovative visualisation technique for stakeholders' group ranking is also presented. Case studies are the Alster catchment (Hamburg, Germany) and Cranbrook catchment, (London, UK). A series of stakeholders' workshops was done to test and evaluate the environments. It shows that the TOPSIS method provides a close representation of the stakeholders' preferences regarding the measures and alternatives. Overall the evaluation shows that web-based environments can address the challenges and hindrances and it enhances participation in flood risk management. The

  1. Stakeholder Perspectives on Citation and Peer-Based Rankings of Higher Education Journals

    Science.gov (United States)

    Wilkins, Stephen; Huisman, Jeroen

    2015-01-01

    The purpose of this article is to identify and discuss the possible uses of higher education journal rankings, and the associated advantages and disadvantages of using them. The research involved 40 individuals--lecturers, university managers, journal editors and publishers--who represented a range of stakeholders involved with research into…

  2. Ranking multiple docking solutions based on the conservation of inter-residue contacts

    KAUST Repository

    Oliva, Romina M.

    2013-06-17

    Molecular docking is the method of choice for investigating the molecular basis of recognition in a large number of functional protein complexes. However, correctly scoring the obtained docking solutions (decoys) to rank native-like (NL) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First it calculates a conservation rate for each inter-residue contact, then it ranks decoys according to their ability to match the more frequently observed contacts. We applied CONSRANK to 102 targets from three different benchmarks, RosettaDock, DOCKGROUND, and Critical Assessment of PRedicted Interactions (CAPRI). The method performs consistently well, both in terms of NL solutions ranked in the top positions and of values of the area under the receiver operating characteristic curve. Its ideal application is to solutions coming from different docking programs and procedures, as in the case of CAPRI targets. For all the analyzed CAPRI targets where a comparison is feasible, CONSRANK outperforms the CAPRI scorers. The fraction of NL solutions in the top ten positions in the RosettaDock, DOCKGROUND, and CAPRI benchmarks is enriched on average by a factor of 3.0, 1.9, and 9.9, respectively. Interestingly, CONSRANK is also able to specifically single out the high/medium quality (HMQ) solutions from the docking decoys ensemble: it ranks 46.2 and 70.8% of the total HMQ solutions available for the RosettaDock and CAPRI targets, respectively, within the top 20 positions. © 2013 Wiley Periodicals, Inc.

  3. New Candidates for Plant-Based Repellents Against Aedes aegypti.

    Science.gov (United States)

    Misni, Norashiqin; Nor, Zurainee Mohamed; Ahmad, Rohani

    2016-06-01

    Based on an ethnobotanical study on use for plant species against mosquito bites in the Kota Tinggi District, Johor State, Malaysia, 3 plants selected for study, Citrus aurantifolia (leaves), Citrus grandis (fruit peel), and Alpinia galanga (rhizome), were extracted using hydrodistillation to produce essential oils. These essential oils were then formulated as a lotion using a microencapsulation process and then tested for their repellent effect against Aedes aegypti. N,N-diethyl-m-toluamide (deet) was also prepared in the same formulation and tested for repellency as controls. Four commercial plant-based repellent (KAPS(®), MozAway(®), BioZ Natural(®), and Mosiquard(®)) also were incorporated in the bioassay for comparison purposes. Bioassays revealed that at 20% concentration all repellent formulations demonstrated complete protection for 2 h and >90% for 4 h post-application. The A. galanga-based formulation provided the greatest level of protection (98.91%), which extended for 4 h post-application and was not significantly different from deet at similar concentration. When compared with commercial plant-based repellents (KAPS(®), MozAway(®), and BioZ Natural(®)), the 3 lotion formulations showed significantly better protection against Ae. aegypti bites, providing >90% protection for 4 h. In conclusion, our 3 plant-based lotion formulations provided acceptable levels of protection against host-seeking Ae. aegypti and should be developed.

  4. Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining.

    Science.gov (United States)

    Cheng, Wenlong; Zhao, Mingbo; Xiong, Naixue; Chui, Kwok Tai

    2017-07-15

    Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptimal to solutions of original sparse or low-rank problems. In this paper, a novel robust subspace segmentation algorithm has been proposed by integrating lp-norm and Schatten p-norm constraints. Our so-obtained affinity graph can better capture local geometrical structure and the global information of the data. As a consequence, our algorithm is more generative, discriminative and robust. An efficient linearized alternating direction method is derived to realize our model. Extensive segmentation experiments are conducted on public datasets. The proposed algorithm is revealed to be more effective and robust compared to five existing algorithms.

  5. A collaborative filtering recommendation algorithm based on weighted SimRank and social trust

    Science.gov (United States)

    Su, Chang; Zhang, Butao

    2017-05-01

    Collaborative filtering is one of the most widely used recommendation technologies, but the data sparsity and cold start problem of collaborative filtering algorithms are difficult to solve effectively. In order to alleviate the problem of data sparsity in collaborative filtering algorithm, firstly, a weighted improved SimRank algorithm is proposed to compute the rating similarity between users in rating data set. The improved SimRank can find more nearest neighbors for target users according to the transmissibility of rating similarity. Then, we build trust network and introduce the calculation of trust degree in the trust relationship data set. Finally, we combine rating similarity and trust to build a comprehensive similarity in order to find more appropriate nearest neighbors for target user. Experimental results show that the algorithm proposed in this paper improves the recommendation precision of the Collaborative algorithm effectively.

  6. Microseismic Event Grouping Based on PageRank Linkage at the Newberry Volcano Geothermal Site

    Science.gov (United States)

    Aguiar, A. C.; Myers, S. C.

    2016-12-01

    The Newberry Volcano DOE FORGE site in Central Oregon has been stimulated two times using high-pressure fluid injection to study the Enhanced Geothermal Systems (EGS) technology. Several hundred microseismic events were generated during the first stimulation in the fall of 2012. Initial locations of this microseismicity do not show well defined subsurface structure in part because event location uncertainties are large (Foulger and Julian, 2013). We focus on this stimulation to explore the spatial and temporal development of microseismicity, which is key to understanding how subsurface stimulation modifies stress, fractures rock, and increases permeability. We use PageRank, Google's initial search algorithm, to determine connectivity within the events (Aguiar and Beroza, 2014) and assess signal-correlation topology for the micro-earthquakes. We then use this information to create signal families and compare these to the spatial and temporal proximity of associated earthquakes. We relocate events within families (identified by PageRank linkage) using the Bayesloc approach (Myers et al., 2007). Preliminary relocations show tight spatial clustering of event families as well as evidence of events relocating to a different cluster than originally reported. We also find that signal similarity (linkage) at several stations, not just one or two, is needed in order to determine that events are in close proximity to one another. We show that indirect linkage of signals using PageRank is a reliable way to increase the number of events that are confidently determined to be similar to one another, which may lead to efficient and effective grouping of earthquakes with similar physical characteristics, such as focal mechanisms and stress drop. Our ultimate goal is to determine whether changes in the state of stress and/or changes in the generation of subsurface fracture networks can be detected using PageRank topology as well as aid in the event relocation to obtain more accurate

  7. Citation-Based Journal Rankings for AI Research A Business Perspective

    OpenAIRE

    Cheng, Chun Hung; Clyde W. Holsapple; Lee, Anita

    1996-01-01

    A significant and growing area of business-computing research is concerned with AI. Knowledge about which journals are the most influential forums for disseminating AI research is important for business school faculty, students, administrators, and librarians. To date, there has been only one study attempting to rank AI journals from a business-computing perspective. It used a subjective methodology, surveying opinions of business faculty about a prespecified list of 30 journals. Here, we rep...

  8. A Distributed Taxation Based Rank Adaptation Scheme for 5G Small Cells

    DEFF Research Database (Denmark)

    Catania, Davide; Cattoni, Andrea Fabio; Mahmood, Nurul Huda

    2015-01-01

    approach is to discourage the choice of transmitting with multiple spatial streams in highly interfered scenarios, and to exploit and encourage the usage of multiple spatial transmission streams in low interference scenarios. We show that our proposed algorithm can be adjusted to preserve and guarantee...... a good outage performance, while providing the benefit of higher average throughputs, in both low and highly interfered scenarios, when compared to fixed rank configurations, and distributed selfish schemes....

  9. Color correction with blind image restoration based on multiple images using a low-rank model

    Science.gov (United States)

    Li, Dong; Xie, Xudong; Lam, Kin-Man

    2014-03-01

    We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

  10. Rankings of High School Sports Injury Rates Differ Based on Time Loss Assessments.

    Science.gov (United States)

    Kerr, Zachary Y; Roos, Karen G; Djoko, Aristarque; Dompier, Thomas P; Marshall, Stephen W

    2017-11-01

    To examine how injury definition inclusiveness affects the rank order of injury rates in 27 high school (HS) sports. The National Athletic Treatment, Injury and Outcomes Network (NATION) used certified athletic trainers (ATs) to collect injury and athlete-exposure (AE) data in practices and competitions for 27 HS sports during the 2011/2012 to 2013/2014 academic years. Time loss (TL) injuries resulted in ≥24 hours of participation restriction. Nontime loss (NTL) injuries resulted in sports. High school student-athletes. Sports injury data from the National Athletic Treatment, Injury and Outcomes Network. Time loss and TL + NTL injury rates were calculated. Sport-specific rates were placed in rank order, stratified by gender. Most of the 47 014 injuries reported were NTL (82.8%). Among boys' sports, TL injury rates were greatest in football (3.27/1000AE) and wrestling (2.43/1000AE); TL + NTL injury rates were greatest also in football (15.29/1000AE) and wrestling (11.62/1000AE). Among girls' sports, TL injury rates were greatest in soccer (1.97/1000AE) and basketball (1.76/1000AE); TL + NTL injury rates were greatest in field hockey and lacrosse (both 11.32/1000AE). The rank order of injury rates and the resulting injury prevention priorities may depend on injury definition inclusiveness, particularly in female HS sports.

  11. 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...

  12. 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...

  13. Development of gold based solder candidates for flip chip assembly

    DEFF Research Database (Denmark)

    Chidambaram, Vivek; Hald, John; Hattel, Jesper Henri

    2009-01-01

    based on its notorious legacy as a major health hazard across the spectrum of human generations and cultures. Flip chip assembly is also now increasingly being used for the high-performance (H-P) systems. These H-P systems perform mission-critical operations and are expected to experience virtually......Flip chip technology is now rapidly replacing the traditional wire bonding interconnection technology in the first level packaging applications due to the miniaturization drive in the microelectronics industry. Flip chip assembly currently involves the use of high lead containing solders...... for interconnecting the chip to a carrier in certain applications due to the unique properties of lead. Despite of all the beneficial attributes of lead, its potential environmental impact when the products are discarded to land fills has resulted in various legislatives to eliminate lead from the electronic products...

  14. Rankings from Fuzzy Pairwise Comparisons

    NARCIS (Netherlands)

    van den Broek, P.M.; Noppen, J.A.R.; Mohammadian, M.

    2006-01-01

    We propose a new method for deriving rankings from fuzzy pairwise comparisons. It is based on the observation that quantification of the uncertainty of the pairwise comparisons should be used to obtain a better crisp ranking, instead of a fuzzified version of the ranking obtained from crisp pairwise

  15. Candidate genes and cerebral palsy: a population-based study.

    Science.gov (United States)

    Gibson, Catherine S; Maclennan, Alastair H; Dekker, Gustaaf A; Goldwater, Paul N; Sullivan, Thomas R; Munroe, David J; Tsang, Shirley; Stewart, Claudia; Nelson, Karin B

    2008-11-01

    The objective of this study was to examine whether selected genetic polymorphisms in the infant are associated with later-diagnosed cerebral palsy. A population-based case-control study was conducted of 28 single-nucleotide polymorphisms measured in newborn screening blood spots. A total of 413 children with later-diagnosed cerebral palsy were born to white women in South Australia in 1986-1999, and there were 856 control children. Distributions of genotypic frequencies were examined in total cerebral palsy, in gestational age groups, and by types of cerebral palsy and gender. Genotyping was performed by using a TaqMan assay. For inducible nitric-oxide synthase, possession of the T allele was more common in all children with cerebral palsy and for heterozygotes who were born at term. For lymphotoxin alpha, homozygous variant status was associated with risk for cerebral palsy and with spastic hemiplegic or quadriplegic cerebral palsy. Among term infants, heterozygosity for the endothelial protein C receptor single-nucleotide polymorphism was more frequent in children with cerebral palsy. In preterm infants, the variant A allele of interleukin 8 and heterozygosity for the beta-2 adrenergic receptor were associated with cerebral palsy risk. Interleukin 8 heterozygote status was associated with spastic diplegia. Variants of several genes were associated with cerebral palsy in girls but not in boys. Two of the 28 single-nucleotide polymorphisms examined were associated with all types of spastic cerebral palsy in both gestational age groups and others with cerebral palsy in gestational age or cerebral palsy subgroups. Some of these associations support previous findings. There may be a genetic contribution to cerebral palsy risk, and additional investigation is warranted of genes and gene-environment interactions in cerebral palsy.

  16. Validation of a model for ranking aquaculture facilities for risk-based disease surveillance.

    Science.gov (United States)

    Diserens, Nicolas; Falzon, Laura Cristina; von Siebenthal, Beat; Schüpbach-Regula, Gertraud; Wahli, Thomas

    2017-09-15

    A semi-quantitative model for risk ranking of aquaculture facilities in Switzerland with regard to the introduction and spread of Viral Haemorrhagic Septicaemia (VHS) and Infectious Haematopoietic Necrosis (IHN) was developed in a previous study (Diserens et al., 2013). The objective of the present study was to validate this model using data collected during field visits on aquaculture sites in four Swiss cantons compared to data collected through a questionnaire in the previous study. A discrepancy between the values obtained with the two different methods was found in 32.8% of the parameters, resulting in a significant difference (psystem could be advantageous for the factors which were identified as being more likely to vary over time, in particular for factors considering fish movements, which showed a marginally significant difference in their risk scores (p≥0.1) within a six- month period. Nevertheless, the model proved to be stable over the considered period of time as no substantial fluctuations in the risk categorisation were observed (Kappa agreement of 0.77).Finally, the model proved to be suitable to deliver a reliable risk ranking of Swiss aquaculture facilities according to their risk of getting infected with or spreading of VHS and IHN, as the five facilities that tested positive for these diseases in the last ten years were ranked as medium or high risk. Moreover, because the seven fish farms that were infected with Infectious Pancreatic Necrosis (IPN) during the same period also belonged to the risk categories medium and high, the classification appeared to correlate with the occurrence of this third viral fish disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Dual channel rank-based intensity weighting for quantitative co-localization of microscopy images

    LENUS (Irish Health Repository)

    Singan, Vasanth R

    2011-10-21

    Abstract Background Accurate quantitative co-localization is a key parameter in the context of understanding the spatial co-ordination of molecules and therefore their function in cells. Existing co-localization algorithms consider either the presence of co-occurring pixels or correlations of intensity in regions of interest. Depending on the image source, and the algorithm selected, the co-localization coefficients determined can be highly variable, and often inaccurate. Furthermore, this choice of whether co-occurrence or correlation is the best approach for quantifying co-localization remains controversial. Results We have developed a novel algorithm to quantify co-localization that improves on and addresses the major shortcomings of existing co-localization measures. This algorithm uses a non-parametric ranking of pixel intensities in each channel, and the difference in ranks of co-localizing pixel positions in the two channels is used to weight the coefficient. This weighting is applied to co-occurring pixels thereby efficiently combining both co-occurrence and correlation. Tests with synthetic data sets show that the algorithm is sensitive to both co-occurrence and correlation at varying levels of intensity. Analysis of biological data sets demonstrate that this new algorithm offers high sensitivity, and that it is capable of detecting subtle changes in co-localization, exemplified by studies on a well characterized cargo protein that moves through the secretory pathway of cells. Conclusions This algorithm provides a novel way to efficiently combine co-occurrence and correlation components in biological images, thereby generating an accurate measure of co-localization. This approach of rank weighting of intensities also eliminates the need for manual thresholding of the image, which is often a cause of error in co-localization quantification. We envisage that this tool will facilitate the quantitative analysis of a wide range of biological data sets

  18. A least square support vector machine-based approach for contingency classification and ranking in a large power system

    Directory of Open Access Journals (Sweden)

    Bhanu Pratap Soni

    2016-12-01

    Full Text Available This paper proposes an effective supervised learning approach for static security assessment of a large power system. Supervised learning approach employs least square support vector machine (LS-SVM to rank the contingencies and predict the system severity level. The severity of the contingency is measured by two scalar performance indices (PIs: line MVA performance index (PIMVA and Voltage-reactive power performance index (PIVQ. SVM works in two steps. Step I is the estimation of both standard indices (PIMVA and PIVQ that is carried out under different operating scenarios and Step II contingency ranking is carried out based on the values of PIs. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus (New England system. The approach can be beneficial tool which is less time consuming and accurate security assessment and contingency analysis at energy management center.

  19. 3D Forest Structure Estimation from SAR Tomography by Means of a Full Rank Polarimetric Inversion Based on Compressive Sensing

    Science.gov (United States)

    Cazcarra Bes, Victor; Tello-Alonso, Maria; Papathanassiou, Kostas

    2015-04-01

    SAR tomography (TomoSAR) techniques allow a direct 3D imaging by exploiting angular diversity with different passes of the sensor. One of the main drawbacks of SAR tomography is that the estimation of the vertical reflectivity profile has to be performed through a limited set of multibaseline acquisitions, which requires solving a highly underdetermined system of equations. In TomoSAR literature, the Capon and the Fourier beamforming spectral estimators are widely employed. As an alternative, the application of Compressive Sensing (CS) techniques to the estimation of forest profiles has been recently introduced. In this paper, a different algorithm based on CS is proposed. It performs a full rank polarimetric inversion, allowing thus an estimation of the 3D coherency matrices. To study the full rank polarimetric TomoSAR inversion, a temporal series of airborne data is used. The results of the 3D polarimetric inversion will be contrasted to in situ measurements and LIDAR data.

  20. An Efficient Normalized Rank Based SVM for Room Level Indoor WiFi Localization with Diverse Devices

    Directory of Open Access Journals (Sweden)

    Yasmine Rezgui

    2017-01-01

    Full Text Available This paper proposes an efficient and effective WiFi fingerprinting-based indoor localization algorithm, which uses the Received Signal Strength Indicator (RSSI of WiFi signals. In practical harsh indoor environments, RSSI variation and hardware variance can significantly degrade the performance of fingerprinting-based localization methods. To address the problem of hardware variance and signal fluctuation in WiFi fingerprinting-based localization, we propose a novel normalized rank based Support Vector Machine classifier (NR-SVM. Moving from RSSI value based analysis to the normalized rank transformation based analysis, the principal features are prioritized and the dimensionalities of signature vectors are taken into account. The proposed method has been tested using sixteen different devices in a shopping mall with 88 shops. The experimental results demonstrate its robustness with no less than 98.75% correct estimation in 93.75% of the tested cases and 100% correct rate in 56.25% of cases. In the experiments, the new method shows better performance over the KNN, Naïve Bayes, Random Forest, and Neural Network algorithms. Furthermore, we have compared the proposed approach with three popular calibration-free transformation based methods, including difference method (DIFF, Signal Strength Difference (SSD, and the Hyperbolic Location Fingerprinting (HLF based SVM. The results show that the NR-SVM outperforms these popular methods.

  1. KaM_CRK: Clustering and Ranking Knowledge for Reasonable Results Based on Behaviors and Contexts

    Directory of Open Access Journals (Sweden)

    Changhong Hu

    2013-01-01

    Full Text Available A model named KaM_CRK is proposed, which can supply the clustered and ranked knowledge to the users on different contexts. By comparing the attributes of contexts and JANs, our findings indicate that our model can accumulate the JANs, whose attributes are similar with the user’s contexts, together. By applying the KaM_CLU algorithm and Centre rank strategy into the KaM_CRK model, the model boosts a significant promotion on the accuracy of provision of user's knowledge. By analyzing the users' behaviors, the dynamic coefficient BehaviorF is first presented in KaM_CLU. Compared to traditional approaches of K_means and DBSCAN, the KaM_CLU algorithm does not need to initialize the number of clusters. Additionally, its synthetic results are more accurate, reasonable, and fit than other approaches for users. It is known from our evaluation through real data that our strategy performs better on time efficiency and user's satisfaction, which will save by 30% and promote by 5%, respectively.

  2. New approach for evaluating risk and ranking spillways based on operational safety

    Energy Technology Data Exchange (ETDEWEB)

    Briand, M.H.; Huard, M.O.; Hanno, H. [RSW Inc., Montreal, PQ (Canada); Manescu, D.; Morin, J.P. [Hydro-Quebec, Montreal, PQ (Canada). Dept. of Dam Safety

    2009-07-01

    This paper discussed a method developed by Hydro-Quebec to rank dam spillways according to their ability to react safely to mechanical or electrical component failures, uncertainties in hydrological conditions; unexpected human responses; and spillway component degradation. A computer simulation was used to model assess the impact of the various scenarios of reservoir levels. Four case studies were used to investigate a wide variety of spillway characteristics and hydrological conditions. Results from power plant tripping events using functional equipment were used as an index of the spillway's safety. Results from the sensitivity analyses of equipment failures and modified hydrology simulations were then used to build a vulnerability index for the development of inspection and maintenance priorities. Spillway conditions during flood routing conditions from inspection reports were then used to prepare a functionality index. A sensitivity matrix was then developed to produce a global ranking index for each spillway in the study. The method is now being applied to existing hydro-electric developments as a validation procedure. 3 refs., 11 tabs., 2 figs.

  3. A Simple Model to Rank Shellfish Farming Areas Based on the Risk of Disease Introduction and Spread.

    Science.gov (United States)

    Thrush, M A; Pearce, F M; Gubbins, M J; Oidtmann, B C; Peeler, E J

    2017-08-01

    The European Union Council Directive 2006/88/EC requires that risk-based surveillance (RBS) for listed aquatic animal diseases is applied to all aquaculture production businesses. The principle behind this is the efficient use of resources directed towards high-risk farm categories, animal types and geographic areas. To achieve this requirement, fish and shellfish farms must be ranked according to their risk of disease introduction and spread. We present a method to risk rank shellfish farming areas based on the risk of disease introduction and spread and demonstrate how the approach was applied in 45 shellfish farming areas in England and Wales. Ten parameters were used to inform the risk model, which were grouped into four risk themes based on related pathways for transmission of pathogens: (i) live animal movement, (ii) transmission via water, (iii) short distance mechanical spread (birds) and (iv) long distance mechanical spread (vessels). Weights (informed by expert knowledge) were applied both to individual parameters and to risk themes for introduction and spread to reflect their relative importance. A spreadsheet model was developed to determine quantitative scores for the risk of pathogen introduction and risk of pathogen spread for each shellfish farming area. These scores were used to independently rank areas for risk of introduction and for risk of spread. Thresholds were set to establish risk categories (low, medium and high) for introduction and spread based on risk scores. Risk categories for introduction and spread for each area were combined to provide overall risk categories to inform a risk-based surveillance programme directed at the area level. Applying the combined risk category designation framework for risk of introduction and spread suggested by European Commission guidance for risk-based surveillance, 4, 10 and 31 areas were classified as high, medium and low risk, respectively. © 2016 Crown copyright.

  4. A Topology Evolution Model Based on Revised PageRank Algorithm and Node Importance for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaogang Qi

    2015-01-01

    Full Text Available Wireless sensor network (WSN is a classical self-organizing communication network, and its topology evolution currently becomes one of the attractive issues in this research field. Accordingly, the problem is divided into two subproblems: one is to design a new preferential attachment method and the other is to analyze the dynamics of the network topology evolution. To solve the first subproblem, a revised PageRank algorithm, called Con-rank, is proposed to evaluate the node importance upon the existing node contraction, and then a novel preferential attachment is designed based on the node importance calculated by the proposed Con-rank algorithm. To solve the second one, we firstly analyze the network topology evolution dynamics in a theoretical way and then simulate the evolution process. Theoretical analysis proves that the network topology evolution of our model agrees with power-law distribution, and simulation results are well consistent with our conclusions obtained from the theoretical analysis and simultaneously show that our topology evolution model is superior to the classic BA model in the average path length and the clustering coefficient, and the network topology is more robust and can tolerate the random attacks.

  5. Using a consensus approach based on the conservation of inter-residue contacts to rank CAPRI models

    KAUST Repository

    Vangone, Anna

    2013-10-17

    Herein we propose the use of a consensus approach, CONSRANK, for ranking CAPRI models. CONSRANK relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. Models are ranked according to their ability to match the most frequently observed contacts. We applied CONSRANK to 19 CAPRI protein-protein targets, covering a wide range of prediction difficulty and involved in a variety of biological functions. CONSRANK results are consistently good, both in terms of native-like (NL) solutions ranked in the top positions and of values of the Area Under the receiver operating characteristic Curve (AUC). For targets having a percentage of NL solutions above 3%, an excellent performance is found, with AUC values approaching 1. For the difficult target T46, having only 3.4% NL solutions, the number of NL solutions in the top 5 and 10 ranked positions is enriched by a factor 30, and the AUC value is as high as 0.997. AUC values below 0.8 are only found for targets featuring a percentage of NL solutions within 1.1%. Remarkably, a false consensus emerges only in one case, T42, which happens to be an artificial protein, whose assembly details remain uncertain, based on controversial experimental data. We also show that CONSRANK still performs very well on a limited number of models, provided that more than 1 NL solution is included in the ensemble, thus extending its applicability to cases where few dozens of models are available.© 2013 Wiley Periodicals, Inc.

  6. Development of New Candidate Gene and EST-Based Molecular Markers for Gossypium Species.

    Science.gov (United States)

    Buyyarapu, Ramesh; Kantety, Ramesh V; Yu, John Z; Saha, Sukumar; Sharma, Govind C

    2011-01-01

    New source of molecular markers accelerate the efforts in improving cotton fiber traits and aid in developing high-density integrated genetic maps. We developed new markers based on candidate genes and G. arboreum EST sequences that were used for polymorphism detection followed by genetic and physical mapping. Nineteen gene-based markers were surveyed for polymorphism detection in 26 Gossypium species. Cluster analysis generated a phylogenetic tree with four major sub-clusters for 23 species while three species branched out individually. CAP method enhanced the rate of polymorphism of candidate gene-based markers between G. hirsutum and G. barbadense. Two hundred A-genome based SSR markers were designed after datamining of G. arboreum EST sequences (Mississippi Gossypium arboreum  EST-SSR: MGAES). Over 70% of MGAES markers successfully produced amplicons while 65 of them demonstrated polymorphism between the parents of G. hirsutum and G. barbadense RIL population and formed 14 linkage groups. Chromosomal localization of both candidate gene-based and MGAES markers was assisted by euploid and hypoaneuploid CS-B analysis. Gene-based and MGAES markers were highly informative as they were designed from candidate genes and fiber transcriptome with a potential to be integrated into the existing cotton genetic and physical maps.

  7. Daughter performance based buffalo bull ranking for boosting milk production in Pakistan

    Directory of Open Access Journals (Sweden)

    A. Ghaffar

    2010-02-01

    Full Text Available The first lactation milk yield records of 2329 daughters of 180 bulls, (11 batches during 1983-2005 were used in this study. BLUP breeding values for male and female were computed using DFREML. The fixed effects like herd-year-season and batch number of bulls had significant effect on milk yield as determined by HARVEY Model-1. In addition to these fixed effects, age at first calving was included in the model as covariate to estimate the BLUP breeding values (EBV for milk yield. The year-wise least square means of milk yield for Nili Ravi buffaloes showed a sharp increase from 1984 to 1989 and then a significant yearly variation with the slight decrease in overall milk production under field conditions at private farmers door step. Among these candidate bulls 92 bulls were positive for milk yield EBV. The overall milk production was (Mean±S.E 2481.82±493.33 Kg. The heritability of milk yield was 0.15. There is wide variation over the years making the over all regression line (Y = - 146944 + 74.349X for milk yield negative. This emphasizes to review the policy of semen usage and production of candidate young bulls for future generations. Recently born male calves had better breeding values showing the positive regression line ( Y = 142.77 + 22.065X.

  8. Validation of SmartRank: A likelihood ratio software for searching national DNA databases with complex DNA profiles.

    Science.gov (United States)

    Benschop, Corina C G; van de Merwe, Linda; de Jong, Jeroen; Vanvooren, Vanessa; Kempenaers, Morgane; Kees van der Beek, C P; Barni, Filippo; Reyes, Eusebio López; Moulin, Léa; Pene, Laurent; Haned, Hinda; Sijen, Titia

    2017-07-01

    Searching a national DNA database with complex and incomplete profiles usually yields very large numbers of possible matches that can present many candidate suspects to be further investigated by the forensic scientist and/or police. Current practice in most forensic laboratories consists of ordering these 'hits' based on the number of matching alleles with the searched profile. Thus, candidate profiles that share the same number of matching alleles are not differentiated and due to the lack of other ranking criteria for the candidate list it may be difficult to discern a true match from the false positives or notice that all candidates are in fact false positives. SmartRank was developed to put forward only relevant candidates and rank them accordingly. The SmartRank software computes a likelihood ratio (LR) for the searched profile and each profile in the DNA database and ranks database entries above a defined LR threshold according to the calculated LR. In this study, we examined for mixed DNA profiles of variable complexity whether the true donors are retrieved, what the number of false positives above an LR threshold is and the ranking position of the true donors. Using 343 mixed DNA profiles over 750 SmartRank searches were performed. In addition, the performance of SmartRank and CODIS were compared regarding DNA database searches and SmartRank was found complementary to CODIS. We also describe the applicable domain of SmartRank and provide guidelines. The SmartRank software is open-source and freely available. Using the best practice guidelines, SmartRank enables obtaining investigative leads in criminal cases lacking a suspect. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Development of new candidate gene and EST-based molecular markers for Gossypium species

    Science.gov (United States)

    New source of molecular markers accelerates the efforts in improving cotton fiber traits and aid in developing high-density integrated genetic maps. We developed new markers based on candidate genes and G. arboreum expressed sequence tag (EST) sequences, and validated them through amplification, ge...

  10. An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context

    Science.gov (United States)

    Landscape context is an important factor in restoration ecology, but the use of landscape context for site prioritization has not been as fully developed. We used morphological image processing to identify candidate ecological restoration areas based on their proximity to existin...

  11. Utility-based Recommendation of Candidate Coalitions in Virtual Creativity Teams

    NARCIS (Netherlands)

    Sie, Rory; Bitter-Rijpkema, Marlies; Sloep, Peter

    2010-01-01

    Sie, R. L. L., Bitter-Rijpkema, M. E., & Sloep, P. B. (2010, 28-30 September). Utility-based Recommendation of Candidate Coalitions in Virtual Creativity Teams. Presentation at the first Workshop on Recommender Systems in Technology Enhanced Learning (RecSysTEL 2010), Barcelona, Spain.

  12. 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. PMID:28713181

  13. Compression and Combining Based on Channel Shortening and Rank Reduction Technique for Cooperative Wireless Sensor Networks

    KAUST Repository

    Ahmed, Qasim Zeeshan

    2013-12-18

    This paper investigates and compares the performance of wireless sensor networks where sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of L sensors. As the destination has the capacity of processing only U out of these L signals, the strongest U signals are selected while the remaining (L?U) signals are suppressed. A preprocessing block similar to channel-shortening is proposed in this contribution. However, this preprocessing block employs a rank-reduction technique instead of channel-shortening. By employing this preprocessing, we are able to decrease the computational complexity of the system without affecting the bit error rate (BER) performance. From our simulations, it can be shown that these schemes outperform the channel-shortening schemes in terms of computational complexity. In addition, the proposed schemes have a superior BER performance as compared to channel-shortening schemes when sensors employ fixed gain amplification. However, for sensors which employ variable gain amplification, a tradeoff exists in terms of BER performance between the channel-shortening and these schemes. These schemes outperform channel-shortening scheme for lower signal-to-noise ratio.

  14. Personalized PageRank Clustering: A graph clustering algorithm based on random walks

    Science.gov (United States)

    A. Tabrizi, Shayan; Shakery, Azadeh; Asadpour, Masoud; Abbasi, Maziar; Tavallaie, Mohammad Ali

    2013-11-01

    Graph clustering has been an essential part in many methods and thus its accuracy has a significant effect on many applications. In addition, exponential growth of real-world graphs such as social networks, biological networks and electrical circuits demands clustering algorithms with nearly-linear time and space complexity. In this paper we propose Personalized PageRank Clustering (PPC) that employs the inherent cluster exploratory property of random walks to reveal the clusters of a given graph. We combine random walks and modularity to precisely and efficiently reveal the clusters of a graph. PPC is a top-down algorithm so it can reveal inherent clusters of a graph more accurately than other nearly-linear approaches that are mainly bottom-up. It also gives a hierarchy of clusters that is useful in many applications. PPC has a linear time and space complexity and has been superior to most of the available clustering algorithms on many datasets. Furthermore, its top-down approach makes it a flexible solution for clustering problems with different requirements.

  15. Reservoir characterization based on tracer response and rank analysis of production and injection rates

    Energy Technology Data Exchange (ETDEWEB)

    Refunjol, B.T. [Lagoven, S.A., Pdvsa (Venezuela); Lake, L.W. [Univ. of Texas, Austin, TX (United States)

    1997-08-01

    Quantification of the spatial distribution of properties is important for many reservoir-engineering applications. But, before applying any reservoir-characterization technique, the type of problem to be tackled and the information available should be analyzed. This is important because difficulties arise in reservoirs where production records are the only information for analysis. This paper presents the results of a practical technique to determine preferential flow trends in a reservoir. The technique is a combination of reservoir geology, tracer data, and Spearman rank correlation coefficient analysis. The Spearman analysis, in particular, will prove to be important because it appears to be insightful and uses injection/production data that are prevalent in circumstances where other data are nonexistent. The technique is applied to the North Buck Draw field, Campbell County, Wyoming. This work provides guidelines to assess information about reservoir continuity in interwell regions from widely available measurements of production and injection rates at existing wells. The information gained from the application of this technique can contribute to both the daily reservoir management and the future design, control, and interpretation of subsequent projects in the reservoir, without the need for additional data.

  16. A frequency-based technique to improve the spelling suggestion rank in medical queries.

    Science.gov (United States)

    Crowell, Jonathan; Zeng, Qing; Ngo, Long; Lacroix, Eve-Marie

    2004-01-01

    There is an abundance of health-related information online, and millions of consumers search for such information. Spell checking is of crucial importance in returning pertinent results, so the authors propose a technique for increasing the effectiveness of spell-checking tools used for health-related information retrieval. A sample of incorrectly spelled medical terms was submitted to two different spell-checking tools, and the resulting suggestions, derived under two different dictionary configurations, were re-sorted according to how frequently each term appeared in log data from a medical search engine. Univariable analysis was carried out to assess the effect of each factor (spell-checking tool, dictionary type, re-sort, or no re-sort) on the probability of success. The factors that were statistically significant in the univariable analysis were then used in multivariable analysis to evaluate the independent effect of each of the factors. The re-sorted suggestions proved to be significantly more accurate than the original list returned by the spell-checking tool. The odds of finding the correct suggestion in the number one rank were increased by 63% after re-sorting using the authors' method. This effect was independent of both the dictionary and the spell-checking tools that were used. Using knowledge about the frequency of a given word's occurrence in the medical domain can significantly improve spelling correction for medical queries.

  17. A comparison of sequential and information-based methods for determining the co-integration rank in heteroskedastic VAR MODELS

    DEFF Research Database (Denmark)

    Cavaliere, Giuseppe; Angelis, Luca De; Rahbek, Anders

    2015-01-01

    In this article, we investigate the behaviour of a number of methods for estimating the co-integration rank in VAR systems characterized by heteroskedastic innovation processes. In particular, we compare the efficacy of the most widely used information criteria, such as Akaike Information Criterion...... (AIC) and Bayesian Information Criterion (BIC) , with the commonly used sequential approach of Johansen [Likelihood-based Inference in Cointegrated Vector Autoregressive Models (1996)] based around the use of either asymptotic or wild bootstrap-based likelihood ratio type tests. Complementing recent...... work done for the latter in Cavaliere, Rahbek and Taylor [Econometric Reviews (2014) forthcoming], we establish the asymptotic properties of the procedures based on information criteria in the presence of heteroskedasticity (conditional or unconditional) of a quite general and unknown form...

  18. Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR

    Science.gov (United States)

    Westermaier, Yvonne; Ruiz-Carmona, Sergio; Theret, Isabelle; Perron-Sierra, Françoise; Poissonnet, Guillaume; Dacquet, Catherine; Boutin, Jean A.; Ducrot, Pierre; Barril, Xavier

    2017-08-01

    The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

  19. 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.

  20. A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

    Science.gov (United States)

    Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

    2017-07-01

    Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

  1. From rankings to mission.

    Science.gov (United States)

    Kirch, Darrell G; Prescott, John E

    2013-08-01

    Since the 1980s, school ranking systems have been a topic of discussion among leaders of higher education. Various ranking systems are based on inadequate data that fail to illustrate the complex nature and special contributions of the institutions they purport to rank, including U.S. medical schools, each of which contributes uniquely to meeting national health care needs. A study by Tancredi and colleagues in this issue of Academic Medicine illustrates the limitations of rankings specific to primary care training programs. This commentary discusses, first, how each school's mission and strengths, as well as the impact it has on the community it serves, are distinct, and, second, how these schools, which are each unique, are poorly represented by overly subjective ranking methodologies. Because academic leaders need data that are more objective to guide institutional development, the Association of American Medical Colleges (AAMC) has been developing tools to provide valid data that are applicable to each medical school. Specifically, the AAMC's Medical School Admissions Requirements and its Missions Management Tool each provide a comprehensive assessment of medical schools that leaders are using to drive institutional capacity building. This commentary affirms the importance of mission while challenging the leaders of medical schools, teaching hospitals, and universities to use reliable data to continually improve the quality of their training programs to improve the health of all.

  2. 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;}    

  3. Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction

    Science.gov (United States)

    Fang, Shiting; Wang, Huafeng; Liu, Yueliang; Zhang, Minghui; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

    2017-10-01

    Lung 4D computed tomography (4D-CT), which is a time-resolved CT data acquisition, performs an important role in explicitly including respiratory motion in treatment planning and delivery. However, the radiation dose is usually reduced at the expense of inter-slice spatial resolution to minimize radiation-related health risk. Therefore, resolution enhancement along the superior-inferior direction is necessary. In this paper, a super-resolution (SR) reconstruction method based on a patch low-rank matrix reconstruction is proposed to improve the resolution of lung 4D-CT images. Specifically, a low-rank matrix related to every patch is constructed by using a patch searching strategy. Thereafter, the singular value shrinkage is employed to recover the high-resolution patch under the constraints of the image degradation model. The output high-resolution patches are finally assembled to output the entire image. This method is extensively evaluated using two public data sets. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 9.7%-33.4% and the edge width by 11.4%-24.3%, relative to linear interpolation, back projection (BP) and Zhang et al’s algorithm. A new algorithm has been developed to improve the resolution of 4D-CT. In all experiments, the proposed method outperforms various interpolation methods, as well as BP and Zhang et al’s method, thus indicating the effectivity and competitiveness of the proposed algorithm.

  4. High-Accuracy Approximation of High-Rank Derivatives: Isotropic Finite Differences Based on Lattice-Boltzmann Stencils

    Directory of Open Access Journals (Sweden)

    Keijo Kalervo Mattila

    2014-01-01

    Full Text Available We propose isotropic finite differences for high-accuracy approximation of high-rank derivatives. These finite differences are based on direct application of lattice-Boltzmann stencils. The presented finite-difference expressions are valid in any dimension, particularly in two and three dimensions, and any lattice-Boltzmann stencil isotropic enough can be utilized. A theoretical basis for the proposed utilization of lattice-Boltzmann stencils in the approximation of high-rank derivatives is established. In particular, the isotropy and accuracy properties of the proposed approximations are derived directly from this basis. Furthermore, in this formal development, we extend the theory of Hermite polynomial tensors in the case of discrete spaces and present expressions for the discrete inner products between monomials and Hermite polynomial tensors. In addition, we prove an equivalency between two approaches for constructing lattice-Boltzmann stencils. For the numerical verification of the presented finite differences, we introduce 5th-, 6th-, and 8th-order two-dimensional lattice-Boltzmann stencils.

  5. High-accuracy approximation of high-rank derivatives: isotropic finite differences based on lattice-Boltzmann stencils.

    Science.gov (United States)

    Mattila, Keijo Kalervo; Hegele Júnior, Luiz Adolfo; Philippi, Paulo Cesar

    2014-01-01

    We propose isotropic finite differences for high-accuracy approximation of high-rank derivatives. These finite differences are based on direct application of lattice-Boltzmann stencils. The presented finite-difference expressions are valid in any dimension, particularly in two and three dimensions, and any lattice-Boltzmann stencil isotropic enough can be utilized. A theoretical basis for the proposed utilization of lattice-Boltzmann stencils in the approximation of high-rank derivatives is established. In particular, the isotropy and accuracy properties of the proposed approximations are derived directly from this basis. Furthermore, in this formal development, we extend the theory of Hermite polynomial tensors in the case of discrete spaces and present expressions for the discrete inner products between monomials and Hermite polynomial tensors. In addition, we prove an equivalency between two approaches for constructing lattice-Boltzmann stencils. For the numerical verification of the presented finite differences, we introduce 5th-, 6th-, and 8th-order two-dimensional lattice-Boltzmann stencils.

  6. Fast live cell imaging at nanometer scale using annihilating filter-based low-rank Hankel matrix approach

    Science.gov (United States)

    Min, Junhong; Carlini, Lina; Unser, Michael; Manley, Suliana; Ye, Jong Chul

    2015-09-01

    Localization microscopy such as STORM/PALM can achieve a nanometer scale spatial resolution by iteratively localizing fluorescence molecules. It was shown that imaging of densely activated molecules can accelerate temporal resolution which was considered as major limitation of localization microscopy. However, this higher density imaging needs to incorporate advanced localization algorithms to deal with overlapping point spread functions (PSFs). In order to address this technical challenges, previously we developed a localization algorithm called FALCON1, 2 using a quasi-continuous localization model with sparsity prior on image space. It was demonstrated in both 2D/3D live cell imaging. However, it has several disadvantages to be further improved. Here, we proposed a new localization algorithm using annihilating filter-based low rank Hankel structured matrix approach (ALOHA). According to ALOHA principle, sparsity in image domain implies the existence of rank-deficient Hankel structured matrix in Fourier space. Thanks to this fundamental duality, our new algorithm can perform data-adaptive PSF estimation and deconvolution of Fourier spectrum, followed by truly grid-free localization using spectral estimation technique. Furthermore, all these optimizations are conducted on Fourier space only. We validated the performance of the new method with numerical experiments and live cell imaging experiment. The results confirmed that it has the higher localization performances in both experiments in terms of accuracy and detection rate.

  7. Reference-free single-pass EPI Nyquist ghost correction using annihilating filter-based low rank Hankel matrix (ALOHA).

    Science.gov (United States)

    Lee, Juyoung; Jin, Kyong Hwan; Ye, Jong Chul

    2016-12-01

    MR measurements from an echo-planar imaging (EPI) sequence produce Nyquist ghost artifacts that originate from inconsistencies between odd and even echoes. Several reconstruction algorithms have been proposed to reduce such artifacts, but most of these methods require either additional reference scans or multipass EPI acquisition. This article proposes a novel and accurate single-pass EPI ghost artifact correction method that does not require any additional reference data. After converting a ghost correction problem into separate k-space data interpolation problems for even and odd phase encoding, our algorithm exploits an observation that the differential k-space data between the even and odd echoes is a Fourier transform of an underlying sparse image. Accordingly, we can construct a rank-deficient Hankel structured matrix, whose missing data can be recovered using an annihilating filter-based low rank Hankel structured matrix completion approach. The proposed method was applied to EPI data for both single and multicoil acquisitions. Experimental results using in vivo data confirmed that the proposed method can completely remove ghost artifacts successfully without prescan echoes. Owing to the discovery of the annihilating filter relationship from the intrinsic EPI image property, the proposed method successfully suppresses ghost artifacts without a prescan step. Magn Reson Med 76:1775-1789, 2016. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  8. Disease candidate gene identification and prioritization using protein interaction networks

    Directory of Open Access Journals (Sweden)

    Aronow Bruce J

    2009-02-01

    Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

  9. Drogue detection for vision-based autonomous aerial refueling via low rank and sparse decomposition with multiple features

    Science.gov (United States)

    Gao, Shibo; Cheng, Yongmei; Song, Chunhua

    2013-09-01

    The technology of vision-based probe-and-drogue autonomous aerial refueling is an amazing task in modern aviation for both manned and unmanned aircraft. A key issue is to determine the relative orientation and position of the drogue and the probe accurately for relative navigation system during the approach phase, which requires locating the drogue precisely. Drogue detection is a challenging task due to disorderly motion of drogue caused by both the tanker wake vortex and atmospheric turbulence. In this paper, the problem of drogue detection is considered as a problem of moving object detection. A drogue detection algorithm based on low rank and sparse decomposition with local multiple features is proposed. The global and local information of drogue is introduced into the detection model in a unified way. The experimental results on real autonomous aerial refueling videos show that the proposed drogue detection algorithm is effective.

  10. Inhibitor Ranking Through QM based Chelation Calculations for Virtual Screening of HIV-1 RNase H inhibition

    DEFF Research Database (Denmark)

    Poongavanam, Vasanthanathan; Svendsen, Casper Steinmann; Kongsted, Jacob

    2014-01-01

    Quantum mechanical (QM) calculations have been used to predict the binding affinity of a set of ligands towards HIV-1 RT associated RNase H (RNH). The QM based chelation calculations show improved binding affinity prediction for the inhibitors compared to using an empirical scoring function...... of the methods based on the use of a training set of molecules, QM based chelation calculations were used as filter in virtual screening of compounds in the ZINC database. By this, we find, compared to regular docking, QM based chelation calculations to significantly reduce the large number of false positives...

  11. Ranking procedure based on mechanical, durability and thermal behavior of mortars with incorporation of phase change materials

    Directory of Open Access Journals (Sweden)

    Cunha, S.

    2015-12-01

    Full Text Available Nowadays, considering the high variety of construction products, adequate material selection, based on their properties and function, becomes increasingly important. In this research, a ranking procedure developed by Czarnecki and Lukowski is applied in mortars with incorporation of phase change materials (PCM. The ranking procedure transforms experimental results of properties into one numerical value. The products can be classified according to their individual properties or even an optimized combination of different properties. The main purpose of this study was the ranking of mortars with incorporation of different contents of PCM based in different binders. Aerial lime, hydraulic lime, gypsum and cement were the binders studied. For each binder, three different mortars were developed. Reference mortars, mortars with incorporation of 40% of PCM and mortars with incorporation of 40% of PCM and 1% of fibers, were tested. Results show that the incorporation of PCM in mortars changes their global performance.Actualmente, existen varios productos de construcción, siendo importante una adecuada selección, con base en sus principales propiedades y funciones. En esta investigación se aplicó un procedimiento de clasificación desarrollado por Czarnecki y Lukowski, en morteros con incorporación de materiales de cambio de fase (PCM. Este procedimiento transforma los resultados experimentales de las propiedades en un único valor numérico. Los productos se clasifican de acuerdo con sus propiedades individuales o en una combinación optimizada de diferentes propiedades. El principal objetivo de este estudio fue la clasificación de morteros basado en los diferentes aglutinantes con incorporación de diferentes cantidades de PCM. Los aglutinantes utilizados fueran la cal aérea, cal hidráulica, yeso y cemento. Para cada aglutinante se han desarrollado tres morteros, siendo morteros de referencia, con incorporación de 40% de PCM y con incorporaci

  12. Using Bayesian Networks for Candidate Generation in Consistency-based Diagnosis

    Science.gov (United States)

    Narasimhan, Sriram; Mengshoel, Ole

    2008-01-01

    Consistency-based diagnosis relies heavily on the assumption that discrepancies between model predictions and sensor observations can be detected accurately. When sources of uncertainty like sensor noise and model abstraction exist robust schemes have to be designed to make a binary decision on whether predictions are consistent with observations. This risks the occurrence of false alarms and missed alarms when an erroneous decision is made. Moreover when multiple sensors (with differing sensing properties) are available the degree of match between predictions and observations can be used to guide the search for fault candidates. In this paper we propose a novel approach to handle this problem using Bayesian networks. In the consistency- based diagnosis formulation, automatically generated Bayesian networks are used to encode a probabilistic measure of fit between predictions and observations. A Bayesian network inference algorithm is used to compute most probable fault candidates.

  13. In Silico target fishing: addressing a “Big Data” problem by ligand-based similarity rankings with data fusion

    Science.gov (United States)

    2014-01-01

    Background Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound. Results We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each target, for which individual searches utilizing multiple reference structures are then fused into a single ranking list representing the potential target interaction profile of the query compound. The proposed approach was validated by 10-fold cross validation and two external tests using data from DrugBank and Therapeutic Target Database (TTD). The use of the approach was further demonstrated with some examples concerning the drug repositioning and drug side-effects prediction. The promising results suggest that the proposed method is useful for not only finding promiscuous drugs for their new usages, but also predicting some important toxic liabilities. Conclusions With the rapid increasing volume and diversity of data concerning drug related targets and their ligands, the simple ligand-based target fishing approach would play an important role in assisting future drug design and discovery. PMID:24976868

  14. Ranking the quality of protein structure models using sidechain based network properties [v1; ref status: indexed, http://f1000r.es/2eu

    Directory of Open Access Journals (Sweden)

    Soma Ghosh

    2014-01-01

    Full Text Available Determining the correct structure of a protein given its sequence still remains an arduous task with many researchers working towards this goal. Most structure prediction methodologies result in the generation of a large number of probable candidates with the final challenge being to select the best amongst these. In this work, we have used Protein Structure Networks of native and modeled proteins in combination with Support Vector Machines to estimate the quality of a protein structure model and finally to provide ranks for these models. Model ranking is performed using regression analysis and helps in model selection from a group of many similar and good quality structures. Our results show that structures with a rank greater than 16 exhibit native protein-like properties while those below 10 are non-native like. The tool is also made available as a web-server (http://vishgraph.mbu.iisc.ernet.in/GraProStr/native_non_native_ranking.html, where, 5 modelled structures can be evaluated at a given time.

  15. A multicriteria model for ranking of improvement approaches in construction companies based on the PROMETHÉE II method

    Directory of Open Access Journals (Sweden)

    Renata Maciel de Melo

    2015-03-01

    Full Text Available The quality of the construction production process may be improved using several different methods such as Lean Construction, ISO 9001, ISO 14001 or ISO 18001. Construction companies need a preliminary study and systematic implementation of changes to become more competitive and efficient. This paper presents a multicriteria decision model for the selection and ranking of such alternatives for improvement approaches regarding the aspects of quality, sustainability and safety, based on the PROMETHEE II method. The adoption of this model provides more confidence and visibility for decision makers. One of the differentiators of this model is the use of a fragmented set of improvement alternatives. These alternatives were combined with some restrictions to create a global set of alternatives. An application to three scenarios, considering realistic data, was developed. The results of the application show that the model should be incorporated into the strategic planning process of organizations.

  16. Manifold ranking based scoring system with its application to cardiac arrest prediction: A retrospective study in emergency department patients.

    Science.gov (United States)

    Liu, Tianchi; Lin, Zhiping; Ong, Marcus Eng Hock; Koh, Zhi Xiong; Pek, Pin Pin; Yeo, Yong Kiang; Oh, Beom-Seok; Ho, Andrew Fu Wah; Liu, Nan

    2015-12-01

    The recently developed geometric distance scoring system has shown the effectiveness of scoring systems in predicting cardiac arrest within 72h and the potential to predict other clinical outcomes. However, the geometric distance scoring system predicts scores based on only local structure embedded by the data, thus leaving much room for improvement in terms of prediction accuracy. We developed a novel scoring system for predicting cardiac arrest within 72h. The scoring system was developed based on a semi-supervised learning algorithm, manifold ranking, which explores both the local and global consistency of the data. System evaluation was conducted on emergency department patients׳ data, including both vital signs and heart rate variability (HRV) parameters. Comparison of the proposed scoring system with previous work was given in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). Out of 1025 patients, 52 (5.1%) met the primary outcome. Experimental results show that the proposed scoring system was able to achieve higher area under the curve (AUC) on both the balanced dataset (0.907 vs. 0.824) and the imbalanced dataset (0.774 vs. 0.734) compared to the geometric distance scoring system. The proposed scoring system improved the prediction accuracy by utilizing the global consistency of the training data. We foresee the potential of extending this scoring system, as well as manifold ranking algorithm, to other medical decision making problems. Furthermore, we will investigate the parameter selection process and other techniques to improve performance on the imbalanced dataset. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. A consensus-based tool for ranking the risk of blood-transmissible infections

    NARCIS (Netherlands)

    Oei, Welling; Neslo, Rabin; Janssen, Mart P.|info:eu-repo/dai/nl/304818208

    2016-01-01

    BACKGROUND: Emerging infectious diseases (EIDs) pose a threat to blood transfusion safety. Despite a lack of evidence, safety interventions may be required. However, what should decision makers base their decisions on? A model was developed that allows valuing the perceived risk of an EID for blood

  18. Using gradient-based ray and candidate shadow maps for environmental illumination distribution estimation

    Science.gov (United States)

    Eem, Changkyoung; Kim, Iksu; Hong, Hyunki

    2015-07-01

    A method to estimate the environmental illumination distribution of a scene with gradient-based ray and candidate shadow maps is presented. In the shadow segmentation stage, we apply a Canny edge detector to the shadowed image by using a three-dimensional (3-D) augmented reality (AR) marker of a known size and shape. Then the hierarchical tree of the connected edge components representing the topological relation is constructed, and the connected components are merged, taking their hierarchical structures into consideration. A gradient-based ray that is perpendicular to the gradient of the edge pixel in the shadow image can be used to extract the shadow regions. In the light source detection stage, shadow regions with both a 3-D AR marker and the light sources are partitioned into candidate shadow maps. A simple logic operation between each candidate shadow map and the segmented shadow is used to efficiently compute the area ratio between them. The proposed method successively extracts the main light sources according to their relative contributions on the segmented shadows. The proposed method can reduce unwanted effects due to the sampling positions in the shadow region and the threshold values in the shadow edge detection.

  19. Au-Ge based Candidate Alloys for High-Temperature Lead-Free Solder Alternatives

    DEFF Research Database (Denmark)

    Chidambaram, Vivek; Hald, John; Hattel, Jesper Henri

    2009-01-01

    Au-Ge based candidate alloys have been proposed as an alternative to high-lead content solders that are currently being used for high-temperature applications. The influence of the low melting point metals namely In, Sb and Sn to the Au-Ge eutectic with respect to the microstructure...... was primarily strengthened by the refined (Ge) dispersed phase. The distribution of phases played a relatively more crucial role in determining the ductility of the bulk solder alloy. In the present work it was found that among the low melting point metals, the addition of Sb to the Au-Ge eutectic would...... and microhardness has been extensively reported. Furthermore, the effects of thermal aging on the microstructure and its corresponding microhardness of these promising candidate alloys have been investigated in this work. After thermal aging at 200°C for different durations ranging from 1 day to 3 weeks...

  20. An AHP-based methodology to rank Critical Success Factors of Executive Information Systems

    OpenAIRE

    Salmerón, Jose L.; Herrero, Inés

    2005-01-01

    For academics and practitioners concerned with computer-based Information Systems, one central issue is the study of Critical Success Factors of Information Systems development and implementation. Whereas several Critical Success Factors analyses appear in the literature, most of them do not have any technical background. In this paper we propose the use of the Analytic Hierarchy Process to set Critical Success Factors priorities. Results suggest that technical elements are less critical than...

  1. Sequential Validation of Blood-Based Protein Biomarker Candidates for Early-Stage Pancreatic Cancer.

    Science.gov (United States)

    Capello, Michela; Bantis, Leonidas E; Scelo, Ghislaine; Zhao, Yang; Li, Peng; Dhillon, Dilsher S; Patel, Nikul J; Kundnani, Deepali L; Wang, Hong; Abbruzzese, James L; Maitra, Anirban; Tempero, Margaret A; Brand, Randall; Firpo, Matthew A; Mulvihill, Sean J; Katz, Matthew H; Brennan, Paul; Feng, Ziding; Taguchi, Ayumu; Hanash, Samir M

    2017-04-01

    CA19-9, which is currently in clinical use as a pancreatic ductal adenocarcinoma (PDAC) biomarker, has limited performance in detecting early-stage disease. We and others have identified protein biomarker candidates that have the potential to complement CA19-9. We have carried out sequential validations starting with 17 protein biomarker candidates to determine which markers and marker combination would improve detection of early-stage disease compared with CA19-9 alone. Candidate biomarkers were subjected to enzyme-linked immunosorbent assay based sequential validation using independent multiple sample cohorts consisting of PDAC cases (n = 187), benign pancreatic disease (n = 93), and healthy controls (n = 169). A biomarker panel for early-stage PDAC was developed based on a logistic regression model. All statistical tests for the results presented below were one-sided. Six out of the 17 biomarker candidates and CA19-9 were validated in a sample set consisting of 75 PDAC patients, 27 healthy subjects, and 19 chronic pancreatitis patients. A second independent set of 73 early-stage PDAC patients, 60 healthy subjects, and 74 benign pancreatic disease patients (combined validation set) yielded a model that consisted of TIMP1, LRG1, and CA19-9. Additional blinded testing of the model was done using an independent set of plasma samples from 39 resectable PDAC patients and 82 matched healthy subjects (test set). The model yielded areas under the curve (AUCs) of 0.949 (95% confidence interval [CI] = 0.917 to 0.981) and 0.887 (95% CI = 0.817 to 0.957) with sensitivities of 0.849 and 0.667 at 95% specificity in discriminating early-stage PDAC vs healthy subjects in the combined validation and test sets, respectively. The performance of the biomarker panel was statistically significantly improved compared with CA19-9 alone (P early-stage PDAC.

  2. 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.

  3. 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.

  4. Application of fuzzy-MOORA method: Ranking of components for reliability estimation of component-based software systems

    Directory of Open Access Journals (Sweden)

    Zeeshan Ali Siddiqui

    2016-01-01

    Full Text Available Component-based software system (CBSS development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.

  5. Phylogeny, historical biogeography, and taxonomic ranking of Parnassiinae (Lepidoptera, Papilionidae) based on morphology and seven genes.

    Science.gov (United States)

    Nazari, Vazrick; Zakharov, Evgueni V; Sperling, Felix A H

    2007-01-01

    We tested the taxonomic utility of morphology and seven mitochondrial or nuclear genes in a phylogenetic reconstruction of swallowtail butterflies in the subfamily Parnassiinae. Our data included 236 morphological characters and DNA sequences for seven genes that are commonly used to infer lepidopteran relationships (COI+COII, ND5, ND1, 16S, EF-1alpha, and wg; total 5775 bp). Nuclear genes performed best for inferring phylogenies, particularly at higher taxonomic levels, while there was substantial variation in performance among mitochondrial genes. Multiple analyses of molecular data (MP, ML and Bayesian) consistently produced a tree topology different from that obtained by morphology alone. Based on molecular evidence, sister-group relationships were confirmed between the genera Hypermnestra and Parnassius, as well as between Archon and Luehdorfia, while the monophyly of the subfamily was weakly supported. We recognize three tribes within Parnassiinae, with Archon and Luehdorfia forming the tribe Luehdorfiini Tutt, 1896 [stat. rev.]. Three fossil taxa were incorporated into a molecular clock analysis with biogeographic time constraints. Based on dispersal-vicariance (DIVA) analysis, the most recent common ancestor of Parnassiinae occurred in the Iranian Plateau and Central Asia to China. Early diversification of Parnassiinae took place at the same time that India collided into Eurasia, 65-42 million years ago.

  6. Diminishing Marginal Returns From Genomic Selection As More Selection Candidates Are Phenotyped

    DEFF Research Database (Denmark)

    Okeno, Tobias O; Henryon, Mark; Sørensen, Anders Christian

    We used stochastic simulation to test hypotheses that, (i) phenotyping proportion of high ranking selection candidates based on estimated breeding values (EBV) before genotyping could realize as much genetic gains as phenotyping all candidates, and (ii) there is diminishing return to selection...

  7. 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.

  8. 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.

  9. Identifying and ranking implicit leadership strategies to promote evidence-based practice implementation in addiction health services.

    Science.gov (United States)

    Guerrero, Erick G; Padwa, Howard; Fenwick, Karissa; Harris, Lesley M; Aarons, Gregory A

    2016-05-14

    Despite a solid research base supporting evidence-based practices (EBPs) for addiction treatment such as contingency management and medication-assisted treatment, these services are rarely implemented and delivered in community-based addiction treatment programs in the USA. As a result, many clients do not benefit from the most current and efficacious treatments, resulting in reduced quality of care and compromised treatment outcomes. Previous research indicates that addiction program leaders play a key role in supporting EBP adoption and use. The present study expanded on this previous work to identify strategies that addiction treatment program leaders report using to implement new practices. We relied on a staged and iterative mixed-methods approach to achieve the following four goals: (a) collect data using focus groups and semistructured interviews and conduct analyses to identify implicit managerial strategies for implementation, (b) use surveys to quantitatively rank strategy effectiveness, (c) determine how strategies fit with existing theories of organizational management and change, and (d) use a consensus group to corroborate and expand on the results of the previous three stages. Each goal corresponded to a methodological phase, which included data collection and analytic approaches to identify and evaluate leadership interventions that facilitate EBP implementation in community-based addiction treatment programs. Findings show that the top-ranked strategies involved the recruitment and selection of staff members receptive to change, offering support and requesting feedback during the implementation process, and offering in vivo and hands-on training. Most strategies corresponded to emergent implementation leadership approaches that also utilize principles of transformational and transactional leadership styles. Leadership behaviors represented orientations such as being proactive to respond to implementation needs, supportive to assist staff members

  10. Design and Analysis of a Ranking Approach to Private Location-Based Services

    DEFF Research Database (Denmark)

    Yiu, Man Lung; Jensen, Christian Søndergaard; Møller, Jesper

    2011-01-01

    Users of mobile services wish to retrieve nearby points of interest without disclosing their locations to the services. This article addresses the challenge of optimizing the query performance while satisfying given location privacy and query accuracy requirements. The article's proposal, Space......Twist, aims to offer location privacy for k nearest neighbor (kNN) queries at low communication cost without requiring a trusted anonymizer. The solution can be used with a conventional DBMS as well as with a server optimized for location-based services. In particular, we believe that this is the first...... solution that expresses the server-side functionality in a single SQL statement. In its basic form, SpaceTwist utilizes well-known incremental NN query processing on the server. When augmented with a server-side granular search technique, SpaceTwist is capable of exploiting relaxed query accuracy...

  11. Social norm influences on evaluations of the risks associated with alcohol consumption: applying the rank-based decision by sampling model to health judgments.

    Science.gov (United States)

    Wood, Alex M; Brown, Gordon D A; Maltby, John

    2012-01-01

    The research first tested whether perceptions of other people's alcohol consumption influenced drinkers' perceptions of the riskiness of their own consumption. Second, the research tested how such comparisons are made-whether, for example, people compare their drinking to the 'average' drinker's or 'rank' their consumption amongst other people's. The latter untested possibility, suggested by the recent Decision by Sampling Model of judgment, would imply different cognitive mechanisms and suggest that information should be presented differently to people in social norm interventions. Study 1 surveyed students who provided information on (a) their own drinking, (b) their perceptions of the distribution of drinking in the UK and (c) their perceived risk of various alcohol-related disorders. Study 2 experimentally manipulated the rank of 'target' units of alcohol within the context of units viewed simultaneously. In both studies, the rank of an individual's drinking in a context of other drinkers predicted perceptions of developing alcohol-related disorders. There was no evidence for the alternative hypothesis that people compared with the average of other drinkers' consumptions. The position that subjects believed they occupied in the ranking of other drinkers predicted their perceived risk, and did so as strongly as how much they actually drank. Drinking comparisons are rank-based, which is consistent with other judgments in social, emotional and psychophysical domains. Interventions should be designed to work with people's natural ways of information processing, through providing clients with information on their drinking rank rather than how their drinking differs from the average.

  12. U.S. Natural Gas Storage Risk-Based Ranking Methodology and Results

    Energy Technology Data Exchange (ETDEWEB)

    Folga, Steve [Argonne National Lab. (ANL), Argonne, IL (United States); Portante, Edgar [Argonne National Lab. (ANL), Argonne, IL (United States); Shamsuddin, Shabbir [Argonne National Lab. (ANL), Argonne, IL (United States); Tompkins, Angeli [Argonne National Lab. (ANL), Argonne, IL (United States); Talaber, Leah [Argonne National Lab. (ANL), Argonne, IL (United States); McLamore, Mike [Argonne National Lab. (ANL), Argonne, IL (United States); Kavicky, Jim [Argonne National Lab. (ANL), Argonne, IL (United States); Conzelmann, Guenter [Argonne National Lab. (ANL), Argonne, IL (United States); Levin, Todd [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-10-01

    This report summarizes the methodology and models developed to assess the risk to energy delivery from the potential loss of underground gas storage (UGS) facilities located within the United States. The U.S. has a total of 418 existing storage fields, of which 390 are currently active. The models estimate the impacts of a disruption of each of the active UGS facilities on their owners/operators, including (1) local distribution companies (LDCs), (2) directly connected transporting pipelines and thus on the customers in downstream States, and (3) third-party entities and thus on contracted customers expecting the gas shipment. Impacts are measured across all natural gas customer classes. For the electric sector, impacts are quantified in terms of natural gas-fired electric generation capacity potentially affected from the loss of a UGS facility. For the purpose of calculating the overall supply risk, the overall consequence of the disruption of an UGS facility across all customer classes is expressed in terms of the number of expected equivalent residential customer outages per year, which combines the unit business interruption cost per customer class and the estimated number of affected natural gas customers with estimated probabilities of UGS disruptions. All models and analyses are based on publicly available data. The report presents a set of findings and recommendations in terms of data, further analyses, regulatory requirements and standards, and needs to improve gas/electric industry coordination for electric reliability.

  13. Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory

    Directory of Open Access Journals (Sweden)

    Yaqin Zhao

    2015-01-01

    Full Text Available Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to exclude the interference of static smoke-color objects, such as blue sky. Second, in RGB color space smoke regions are segmented by defining the upper approximation, lower approximation, and roughness of smoke-color distribution. Finally, in HSV color space small smoke regions are merged by the definition of equivalence relation so as to distinguish smoke images from heavy fog images in terms of V component value variety from center to edge of smoke region. The experimental results on smoke region segmentation demonstrated the effectiveness and usefulness of the proposed scheme.

  14. Hazard ranking system evaluation of CERCLA inactive waste sites at Hanford: Volume 2: Engineered-facility sites (HISS data base)

    Energy Technology Data Exchange (ETDEWEB)

    Jette, S.J.; Lamar, D.A.; McLaughlin, T.J.; Sherwood, D.R.; Van Houten, N.C.; Stenner, R.D.; Cramer, K.H.; Higley, K.A.

    1988-10-01

    The purpose of this report is to formally document the assessment activities at the US Department of Energy (DOE) Hanford Site. These activities were carried out pursuant to the DOE orders that address the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Program for the cleanup of inactive waste sites. The DOE orders incorporate the US Environmental Protection Agency methodology, which is based on the Superfund Amendments and Reauthorization Act of 1986. This methodology includes: PA/SI, remedial investigation/feasibility study, record of decision, design and implementation of remedial action, operation and monitoring, and verification monitoring. Volume 1 of this report discusses the CERCLA inactive waste-site evaluation process, assumptions, and results of the Hazard Ranking System methodology employed. Volume 2 presents the data on the individual CERCLA engineered-facility sites at Hanford, as contained in the Hanford Inactive Site Surveillance (HISS) Data Base. Volume 3 presents the data on the individual CERCLA unplanned-release sites at Hanford, as contained in the HISS Data Base. 13 refs.

  15. An improved Bayesian network method for reconstructing gene regulatory network based on candidate auto selection.

    Science.gov (United States)

    Xing, Linlin; Guo, Maozu; Liu, Xiaoyan; Wang, Chunyu; Wang, Lei; Zhang, Yin

    2017-11-17

    The reconstruction of gene regulatory network (GRN) from gene expression data can discover regulatory relationships among genes and gain deep insights into the complicated regulation mechanism of life. However, it is still a great challenge in systems biology and bioinformatics. During the past years, numerous computational approaches have been developed for this goal, and Bayesian network (BN) methods draw most of attention among these methods because of its inherent probability characteristics. However, Bayesian network methods are time consuming and cannot handle large-scale networks due to their high computational complexity, while the mutual information-based methods are highly effective but directionless and have a high false-positive rate. To solve these problems, we propose a Candidate Auto Selection algorithm (CAS) based on mutual information and breakpoint detection to restrict the search space in order to accelerate the learning process of Bayesian network. First, the proposed CAS algorithm automatically selects the neighbor candidates of each node before searching the best structure of GRN. Then based on CAS algorithm, we propose a globally optimal greedy search method (CAS + G), which focuses on finding the highest rated network structure, and a local learning method (CAS + L), which focuses on faster learning the structure with little loss of quality. Results show that the proposed CAS algorithm can effectively reduce the search space of Bayesian networks through identifying the neighbor candidates of each node. In our experiments, the CAS + G method outperforms the state-of-the-art method on simulation data for inferring GRNs, and the CAS + L method is significantly faster than the state-of-the-art method with little loss of accuracy. Hence, the CAS based methods effectively decrease the computational complexity of Bayesian network and are more suitable for GRN inference.

  16. Efficient l1 -norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method.

    Science.gov (United States)

    Kim, Eunwoo; Lee, Minsik; Choi, Chong-Ho; Kwak, Nojun; Oh, Songhwai

    2015-02-01

    Low-rank matrix approximation plays an important role in the area of computer vision and image processing. Most of the conventional low-rank matrix approximation methods are based on the l2 -norm (Frobenius norm) with principal component analysis (PCA) being the most popular among them. However, this can give a poor approximation for data contaminated by outliers (including missing data), because the l2 -norm exaggerates the negative effect of outliers. Recently, to overcome this problem, various methods based on the l1 -norm, such as robust PCA methods, have been proposed for low-rank matrix approximation. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. In this paper, we propose two efficient low-rank factorization methods based on the l1 -norm that find proper projection and coefficient matrices using the alternating rectified gradient method. The proposed methods are applied to a number of low-rank matrix approximation problems to demonstrate their efficiency and robustness. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods.

  17. Association study of 167 candidate genes for schizophrenia selected by a multi-domain evidence-based prioritization algorithm and neurodevelopmental hypothesis.

    Directory of Open Access Journals (Sweden)

    Zhongming Zhao

    Full Text Available Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n=3819 under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1 a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2 a schizophrenia protein-protein interaction network, and 3 a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1 while 42 and 52 genes were exclusive to neurodevelopment (category 2 or highly ranked (category 3, respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is

  18. 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

  19. Does an expert-based evaluation allow us to go beyond the Impact Factor? Experiences from building a ranking of national journals in Poland.

    Science.gov (United States)

    Kulczycki, Emanuel; Rozkosz, Ewa A

    2017-01-01

    This article discusses the Polish Journal Ranking, which is used in the research evaluation system in Poland. In 2015, the ranking, which represents all disciplines, allocated 17,437 journals into three lists: A, B, and C. The B list constitutes a ranking of Polish journals that are indexed neither in the Web of Science nor the European Reference Index for the Humanities. This ranking was built by evaluating journals in three dimensions: formal, bibliometric, and expert-based. We have analysed data on 2035 Polish journals from the B list. Our study aims to determine how an expert-based evaluation influenced the results of final evaluation. In our study, we used structural equation modelling, which is regression based, and we designed three pairs of theoretical models for three fields of science: (1) humanities, (2) social sciences, and (3) engineering, natural sciences, and medical sciences. Each pair consisted of the full model and the reduced model (i.e., the model without the expert-based evaluation). Our analysis revealed that the multidimensional evaluation of local journals should not rely only on the bibliometric indicators, which are based on the Web of Science or Scopus. Moreover, we have shown that the expert-based evaluation plays a major role in all fields of science. We conclude with recommendations that the formal evaluation should be reduced to verifiable parameters and that the expert-based evaluation should be based on common guidelines for the experts.

  20. Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling

    Directory of Open Access Journals (Sweden)

    Xinglin Piao

    2014-12-01

    Full Text Available The emerging low rank matrix approximation (LRMA method provides an energy efficient scheme for data collection in wireless sensor networks (WSNs by randomly sampling a subset of sensor nodes for data sensing. However, the existing LRMA based methods generally underutilize the spatial or temporal correlation of the sensing data, resulting in uneven energy consumption and thus shortening the network lifetime. In this paper, we propose a correlated spatio-temporal data collection method for WSNs based on LRMA. In the proposed method, both the temporal consistence and the spatial correlation of the sensing data are simultaneously integrated under a new LRMA model. Moreover, the network energy consumption issue is considered in the node sampling procedure. We use Gini index to measure both the spatial distribution of the selected nodes and the evenness of the network energy status, then formulate and resolve an optimization problem to achieve optimized node sampling. The proposed method is evaluated on both the simulated and real wireless networks and compared with state-of-the-art methods. The experimental results show the proposed method efficiently reduces the energy consumption of network and prolongs the network lifetime with high data recovery accuracy and good stability.

  1. Selection and ranking of occupational safety indicators based on fuzzy AHP: A case study in road construction companies

    National Research Council Canada - National Science Library

    Janackovic, Goran Lj; Savic, Suzana M; Stankovic, Miomir S

    2013-01-01

    .... The key safety performance indicators for the road construction industry are identified and ranked according to the results of a survey that included experts who assessed occupational safety risks in these companies...

  2. Immunogenicity of multi-epitope-based vaccine candidates administered with the adjuvant Gp96 against rabies.

    Science.gov (United States)

    Niu, Yange; Liu, Ye; Yang, Limin; Qu, Hongren; Zhao, Jingyi; Hu, Rongliang; Li, Jing; Liu, Wenjun

    2016-04-01

    Rabies, a zoonotic disease, causes > 55,000 human deaths globally and results in at least 500 million dollars in losses every year. The currently available rabies vaccines are mainly inactivated and attenuated vaccines, which have been linked with clinical diseases in animals. Thus, a rabies vaccine with high safety and efficacy is urgently needed. Peptide vaccines are known for their low cost, simple production procedures and high safety. Therefore, in this study, we examined the efficacy of multi-epitope-based vaccine candidates against rabies virus. The ability of various peptides to induce epitope-specific responses was examined, and the two peptides that possessed the highest antigenicity and conservation, i.e., AR16 and hPAB, were coated with adjuvant canine-Gp96 and used to prepare vaccines. The peptides were prepared as an emulsion of oil in water (O/W) to create three batches of bivalent vaccine products. The vaccine candidates possessed high safety. Virus neutralizing antibodies were detected on the day 14 after the first immunization in mice and beagles, reaching 5-6 IU/mL in mice and 7-9 IU/mL in beagles by day 28. The protective efficacy of the vaccine candidates was about 70%-80% in mice challenged by a virulent strain of rabies virus. Thus, a novel multi-epitope-based rabies vaccine with Gp96 as an adjuvant was developed and validated in mice and dogs. Our results suggest that synthetic peptides hold promise for the development of novel vaccines against rabies.

  3. Screening and ranking of POPs for global half-life: QSAR approaches for prioritization based on molecular structure.

    Science.gov (United States)

    Gramatica, Paola; Papa, Ester

    2007-04-15

    Persistence in the environment is an important criterion in prioritizing hazardous chemicals and in identifying new persistent organic pollutants (POPs). Degradation half-life in various compartments is among the more commonly used criteria for studying environmental persistence, but the limited availability of experimental data or reliable estimates is a serious problem. Available half-life data for degradation in air, water, sediment, and soil, for a set of 250 organic POP-type chemicals, were combined in a multivariate approach by principal component analysis to obtain a ranking of the studied organic pollutants according to their relative overall half-life. A global half-life index (GHLI) applicable for POP screening purposes is proposed. The reliability of this index was verified in comparison with multimedia model results. This global index was then modeled as a cumulative end-point using a QSAR approach based on few theoretical molecular descriptors, and a simple and robust regression model externally validated for its predictive ability was derived. The application of this model could allow a fast preliminary identification and prioritization of not yet known POPs, just from the knowledge of their molecular structure. This model can be applied a priori also in the chemical design of safer and alternative non-POP compounds.

  4. Ecological Efficiency Based Ranking of Cities: A Combined DEA Cross-Efficiency and Shannon’s Entropy Method

    Directory of Open Access Journals (Sweden)

    Corrado lo Storto

    2016-01-01

    Full Text Available In this paper, a method is proposed to calculate a comprehensive index that calculates the ecological efficiency of a city by combining together the measurements provided by some Data Envelopment Analysis (DEA cross-efficiency models using the Shannon’s entropy index. The DEA models include non-discretionary uncontrollable inputs, desirable and undesirable outputs. The method is implemented to compute the ecological efficiency of a sample of 116 Italian provincial capital cities in 2011 as a case study. Results emerging from the case study show that the proposed index has a good discrimination power and performs better than the ranking provided by the Sole24Ore, which is generally used in Italy to conduct benchmarking studies. While the sustainability index proposed by the Sole24Ore utilizes a set of subjective weights to aggregate individual indicators, the adoption of the DEA based method limits the subjectivity to the selection of the models. The ecological efficiency measurements generated by the implementation of the method for the Italian cities indicate that they perform very differently, and generally largest cities in terms of population size achieve a higher efficiency score.

  5. Complex step-based low-rank extended Kalman filtering for state-parameter estimation in subsurface transport models

    KAUST Repository

    El Gharamti, Mohamad

    2014-02-01

    The accuracy of groundwater flow and transport model predictions highly depends on our knowledge of subsurface physical parameters. Assimilation of contaminant concentration data from shallow dug wells could help improving model behavior, eventually resulting in better forecasts. In this paper, we propose a joint state-parameter estimation scheme which efficiently integrates a low-rank extended Kalman filtering technique, namely the Singular Evolutive Extended Kalman (SEEK) filter, with the prominent complex-step method (CSM). The SEEK filter avoids the prohibitive computational burden of the Extended Kalman filter by updating the forecast along the directions of error growth only, called filter correction directions. CSM is used within the SEEK filter to efficiently compute model derivatives with respect to the state and parameters along the filter correction directions. CSM is derived using complex Taylor expansion and is second order accurate. It is proven to guarantee accurate gradient computations with zero numerical round-off errors, but requires complexifying the numerical code. We perform twin-experiments to test the performance of the CSM-based SEEK for estimating the state and parameters of a subsurface contaminant transport model. We compare the efficiency and the accuracy of the proposed scheme with two standard finite difference-based SEEK filters as well as with the ensemble Kalman filter (EnKF). Assimilation results suggest that the use of the CSM in the context of the SEEK filter may provide up to 80% more accurate solutions when compared to standard finite difference schemes and is competitive with the EnKF, even providing more accurate results in certain situations. We analyze the results based on two different observation strategies. We also discuss the complexification of the numerical code and show that this could be efficiently implemented in the context of subsurface flow models. © 2013 Elsevier B.V.

  6. Ovine rotavirus strain LLR-85-based bovine rotavirus candidate vaccines: construction, characterization and immunogenicity evaluation.

    Science.gov (United States)

    Chang, Ji-Tao; Li, Xin; Liu, Hai-Jun; Yu, Li

    2010-11-20

    Group A bovine rotaviruses (BRVs) are the most important cause of diarrheal diseases in neonatal calves and cause significant morbidity and mortality in the young animals, and epidemiologic surveillance of bovine rotavirus G genotypes conducted in various cattle populations throughout the world has shown that approximately 90% of the bovine rotavirus isolates belong to G6 and G10. Based on the modified Jennerian approach to immunization, we constructed and characterized a reassortant rotavirus stain, which bears a single bovine rotavirus VP7 gene encoding G genotype 6 specificity while the remaining 10 genes are derived from the ovine attenuated rotavirus LLR-85. The reassortant rotavirus strain, named as R191, and its parental virus strain LLR-85 were combined as bivalent vaccine candidates to inoculate the colostrums-deprived neonatal calves for evaluation of the immunogenicity. The calves were orally inoculated with the reassortant R191 (group 1), the parental rotavirus LLR-85 (group 2), or combined the R191 and LLR-85 (group 3), and serum specimens were detected to determine the immune response of IgG and IgA antibodies. Results showed that seroconversion to positivity for IgG and IgA antibodies occurred at postinoculation day (PID) 10 in all of the inoculated calves, and the highest titers of the serum IgG (range 1:800 to 1:6400) and IgA (range 1:800 to 1:3200) antibodies were obtained at PID 21 for all calves. Meanwhile, virus shedding was detected after inoculation, showing that the inoculated virus was positive in 2 of 77 fecal specimens (2.6%) collected from the inoculated calves during the first 7 days of oral inoculation with the rotavirus vaccine candidates. The results suggested that the rotavirus strains R191 and LLR-85 are promising bivalent vaccine candidates for the prevention of bovine G6 and G10 rotavirus infection. Copyright © 2010 Elsevier B.V. All rights reserved.

  7. Candidate List of yoUr Biomarker (CLUB: A Web-based Platform to Aid Cancer Biomarker Research

    Directory of Open Access Journals (Sweden)

    N. Leigh Anderson

    2008-01-01

    Full Text Available CLUB (“Candidate List of yoUr Biomarkers” is a freely available, web-based resource designed to support Cancer biomarker research. It is targeted to provide a comprehensive list of candidate biomarkers for various cancers that have been reported by the research community. CLUB provides tools for comparison of marker candidates from different experimental platforms, with the ability to filter, search, query and explore, molecular interaction networks associated with cancer biomarkers from the published literature and from data uploaded by the community. This complex and ambitious project is implemented in phases. As a first step, we have compiled from the literature an initial set of differentially expressed human candidate cancer biomarkers. Each candidate is annotated with information from publicly available databases such as Gene Ontology, Swiss-Prot database, National Center for Biotechnology Information’s reference sequences, Biomolecular Interaction Network Database and IntAct interaction. The user has the option to maintain private lists of biomarker candidates or share and export these for use by the community. Furthermore, users may customize and combine commonly used sets of selection procedures and apply them as a stored workflow using selected candidate lists. To enable an assessment by the user before taking a candidate biomarker to the experimental validation stage, the platform contains the functionality to identify pathways associated with cancer risk, staging, prognosis, outcome in cancer and other clinically associated phenotypes. The system is available at http://club.bii.a-star.edu.sg.

  8. 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.

  9. A classification and ranking system on the H2 gas sensing capabilities of nanomaterials based on proposed coefficients of sensor performance and sensor efficiency equations

    CSIR Research Space (South Africa)

    Mwakikunga, BW

    2013-07-01

    Full Text Available Sensors and Actuators B 184 (2013) 170– 178 A classification and ranking system on the H2 gas sensing capabilities of nanomaterials based on proposed coefficients of sensor performance and sensor efficiency equations Bonex W. Mwakikungaa,b,∗, Sarah...

  10. Porcine rotavirus strain Gottfried-based human rotavirus candidate vaccines: construction and characterization.

    Science.gov (United States)

    Hoshino, Yasutaka; Jones, Ronald W; Ross, Jerri; Kapikian, Albert Z

    2005-05-31

    Rotavirus gastroenteritis remains the leading cause of severe diarrheal disease in infants and young children worldwide, and thus, a safe and effective rotavirus vaccine is urgently needed in both developing and developed countries. Various candidate rotavirus vaccines that were developed by us and others have been or are being evaluated in different populations in various parts of the world. We have recently confirmed that a porcine rotavirus Gottfried strain bears a P (VP4) serotype (P2B[6]) closely related to human rotavirus P serotype 2A[6] which is of epidemiologic importance in some regions of the world. Based on the modified Jennerian approach to immunization, we have constructed 11 Gottfried-based single VP7 or VP4 gene substitution reassortant vaccine candidates which could provide: (i) an attenuation phenotype of a porcine rotavirus in humans; and (ii) antigenic coverage for G serotypes 1-6 and 8-10 and P serotype 1A[8], 1B[4] and 2A[6]. In addition, following immunization of guinea pigs with Gottfried VP4, we found low but consistent levels of neutralizing antibodies to VP4 with P1A[8] or P1B[4] specificity, both of which are of global epidemiologic importance. Thus, porcine-based VP7 reassortant rotavirus vaccines may provide an advantage over rhesus- or bovine-based VP7 reassortant vaccines since the VP4s of the latter vaccines do not evoke antibodies capable of neutralizing the viruses bearing P1A[8], P1B[4] or P2A[6] VP4.

  11. Addictions biology: haplotype-based analysis for 130 candidate genes on a single array.

    Science.gov (United States)

    Hodgkinson, Colin A; Yuan, Qiaoping; Xu, Ke; Shen, Pei-Hong; Heinz, Elizabeth; Lobos, Elizabeth A; Binder, Elizabeth B; Cubells, Joe; Ehlers, Cindy L; Gelernter, Joel; Mann, John; Riley, Brien; Roy, Alec; Tabakoff, Boris; Todd, Richard D; Zhou, Zhifeng; Goldman, David

    2008-01-01

    To develop a panel of markers able to extract full haplotype information for candidate genes in alcoholism, other addictions and disorders of mood and anxiety. A total of 130 genes were haplotype tagged and genotyped in 7 case/control populations and 51 reference populations using Illumina GoldenGate SNP genotyping technology, determining haplotype coverage. We also constructed and determined the efficacy of a panel of 186 ancestry informative markers. An average of 1465 loci were genotyped at an average completion rate of 91.3%, with an average call rate of 98.3% and replication rate of 99.7%. Completion and call rates were lowered by the performance of two datasets, highlighting the importance of the DNA quality in high throughput assays. A comparison of haplotypes captured by the Addictions Array tagging SNPs and commercially available whole-genome arrays from Illumina and Affymetrix shows comparable performance of the tag SNPs to the best whole-genome array in all populations for which data are available. Arrays of haplotype-tagged candidate genes, such as this addictions-focused array, represent a cost-effective approach to generate high-quality SNP genotyping data useful for the haplotype-based analysis of panels of genes such as these 130 genes of interest to alcohol and addictions researchers. The inclusion of the 186 ancestry informative markers allows for the detection and correction for admixture and further enhances the utility of the array.

  12. ReCGiP, a database of reproduction candidate genes in pigs based on bibliomics.

    Science.gov (United States)

    Yang, Lun; Zhang, Xiangzhe; Chen, Jian; Wang, Qishan; Wang, Lishan; Jiang, Yue; Pan, Yuchun

    2010-08-14

    Reproduction in pigs is one of the most economically important traits. To improve the reproductive performances, numerous studies have focused on the identification of candidate genes. However, it is hard for one to read all literatures thoroughly to get information. So we have developed a database providing candidate genes for reproductive researches in pig by mining and processing existing biological literatures in human and pigs, named as ReCGiP. Based on text-mining and comparative genomics, ReCGiP presents diverse information of reproduction-relevant genes in human and pig. The genes were sorted by the degree of relevance with the reproduction topics and were visualized in a gene's co-occurrence network where two genes were connected if they were co-cited in a PubMed abstract. The 'hub' genes which had more 'neighbors' were thought to be have more important functions and could be identified by the user in their web browser. In addition, ReCGiP provided integrated GO annotation, OMIM and biological pathway information collected from the Internet. Both pig and human gene information can be found in the database, which is now available. ReCGiP is a unique database providing information on reproduction related genes for pig. It can be used in the area of the molecular genetics, the genetic linkage map, and the breeding of the pig and other livestock. Moreover, it can be used as a reference for human reproduction research.

  13. ReCGiP, a database of reproduction candidate genes in pigs based on bibliomics

    Directory of Open Access Journals (Sweden)

    Yang Lun

    2010-08-01

    Full Text Available Abstract Background Reproduction in pigs is one of the most economically important traits. To improve the reproductive performances, numerous studies have focused on the identification of candidate genes. However, it is hard for one to read all literatures thoroughly to get information. So we have developed a database providing candidate genes for reproductive researches in pig by mining and processing existing biological literatures in human and pigs, named as ReCGiP. Description Based on text-mining and comparative genomics, ReCGiP presents diverse information of reproduction-relevant genes in human and pig. The genes were sorted by the degree of relevance with the reproduction topics and were visualized in a gene's co-occurrence network where two genes were connected if they were co-cited in a PubMed abstract. The 'hub' genes which had more 'neighbors' were thought to be have more important functions and could be identified by the user in their web browser. In addition, ReCGiP provided integrated GO annotation, OMIM and biological pathway information collected from the Internet. Both pig and human gene information can be found in the database, which is now available. Conclusions ReCGiP is a unique database providing information on reproduction related genes for pig. It can be used in the area of the molecular genetics, the genetic linkage map, and the breeding of the pig and other livestock. Moreover, it can be used as a reference for human reproduction research.

  14. Machine Learning-Based Gene Prioritization Identifies Novel Candidate Risk Genes for Inflammatory Bowel Disease.

    Science.gov (United States)

    Isakov, Ofer; Dotan, Iris; Ben-Shachar, Shay

    2017-09-01

    The inflammatory bowel diseases (IBDs) are chronic inflammatory disorders, associated with genetic, immunologic, and environmental factors. Although hundreds of genes are implicated in IBD etiology, it is likely that additional genes play a role in the disease process. We developed a machine learning-based gene prioritization method to identify novel IBD-risk genes. Known IBD genes were collected from genome-wide association studies and annotated with expression and pathway information. Using these genes, a model was trained to identify IBD-risk genes. A comprehensive list of 16,390 genes was then scored and classified. Immune and inflammatory responses, as well as pathways such as cell adhesion, cytokine-cytokine receptor interaction, and sulfur metabolism were identified to be related to IBD. Scores predicted for IBD genes were significantly higher than those for non-IBD genes (P genes had a high prediction score (>0.8). A literature review of the genes, excluding those used to train the model, identified 67 genes without any publication concerning IBD. These genes represent novel candidate IBD-risk genes, which can be targeted in future studies. Our method successfully differentiated IBD-risk genes from non-IBD genes by using information from expression data and a multitude of gene annotations. Crucial features were defined, and we were able to detect novel candidate risk genes for IBD. These findings may help detect new IBD-risk genes and improve the understanding of IBD pathogenesis.

  15. 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 e...... eigenvalues and eigenvectors. We give a number of different applications to regression and time series analysis, and show how the reduced rank regression estimator can be derived as a Gaussian maximum likelihood estimator. We briefly mention asymptotic results......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...

  16. PEACE: pulsar evaluation algorithm for candidate extraction - a software package for post-analysis processing of pulsar survey candidates

    Science.gov (United States)

    Lee, K. J.; Stovall, K.; Jenet, F. A.; Martinez, J.; Dartez, L. P.; Mata, A.; Lunsford, G.; Cohen, S.; Biwer, C. M.; Rohr, M.; Flanigan, J.; Walker, A.; Banaszak, S.; Allen, B.; Barr, E. D.; Bhat, N. D. R.; Bogdanov, S.; Brazier, A.; Camilo, F.; Champion, D. J.; Chatterjee, S.; Cordes, J.; Crawford, F.; Deneva, J.; Desvignes, G.; Ferdman, R. D.; Freire, P.; Hessels, J. W. T.; Karuppusamy, R.; Kaspi, V. M.; Knispel, B.; Kramer, M.; Lazarus, P.; Lynch, R.; Lyne, A.; McLaughlin, M.; Ransom, S.; Scholz, P.; Siemens, X.; Spitler, L.; Stairs, I.; Tan, M.; van Leeuwen, J.; Zhu, W. W.

    2013-07-01

    Modern radio pulsar surveys produce a large volume of prospective candidates, the majority of which are polluted by human-created radio frequency interference or other forms of noise. Typically, large numbers of candidates need to be visually inspected in order to determine if they are real pulsars. This process can be labour intensive. In this paper, we introduce an algorithm called Pulsar Evaluation Algorithm for Candidate Extraction (PEACE) which improves the efficiency of identifying pulsar signals. The algorithm ranks the candidates based on a score function. Unlike popular machine-learning-based algorithms, no prior training data sets are required. This algorithm has been applied to data from several large-scale radio pulsar surveys. Using the human-based ranking results generated by students in the Arecibo Remote Command Center programme, the statistical performance of PEACE was evaluated. It was found that PEACE ranked 68 per cent of the student-identified pulsars within the top 0.17 per cent of sorted candidates, 95 per cent within the top 0.34 per cent and 100 per cent within the top 3.7 per cent. This clearly demonstrates that PEACE significantly increases the pulsar identification rate by a factor of about 50 to 1000. To date, PEACE has been directly responsible for the discovery of 47 new pulsars, 5 of which are millisecond pulsars that may be useful for pulsar timing based gravitational-wave detection projects.

  17. Correlation between trainee candidate selection criteria and subsequent performance.

    Science.gov (United States)

    Selber, Jesse C; Tong, Winnie; Koshy, John; Ibrahim, Amir; Liu, Jun; Butler, Charles

    2014-11-01

    The objective of trainee recruitment is to identify candidates likely to perform well as trainees and subsequent faculty. The effectiveness of this process has not been established. The goal of this study was to identify trainee selection criteria predictive of excellent performance. Twenty-nine microsurgery fellows were enrolled from 2008 to 2012. Each candidate was interviewed and rated based on presentation, plastic surgery (PS) training experience, academic potential, personality, social skills, communication skills, and ability to be a team player. An unadjusted rank list was generated based on weighted averages, and an adjusted rank list was then generated at a faculty meeting. At the conclusion of fellowship, each fellow was rated based on the ACGME core competencies. Spearman correlation coefficients (r) were used to measure the correlations between fellow selection criteria and fellow performance. Plastic surgery training and academic potential had, by far, the strongest correlation to overall performance (r: 0.678, p competencies. When reformulated to weight PS training and academic potential more heavily than subjective criteria, the scoring system was significantly more predictive of excellent performance (r: 0.49 vs 0.70). The unadjusted rank list was more predictive of excellent performance than the adjusted rank list (r: 0.45 vs 0.65). Plastic surgery training experience and academic potential were better predictors of performance than any subjective information ascertained during the interview. Adjustments to the rank list based on faculty discussion resulted in lower performance candidates moving up in ranking. Ranking criteria and interview techniques must be refined to improve predictive power. It may be beneficial for semi-objective criteria to carry more weight than subjective criteria and raw scores to remain unadjusted by extraneous information. Copyright © 2014 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  18. Universal scaling in sports ranking

    Science.gov (United States)

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

    2012-09-01

    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.

  19. Universal scaling in sports ranking

    CERN Document Server

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

    2011-01-01

    Ranking is a ubiquitous phenomenon in the human society. By clicking the web pages of Forbes, you may find all kinds of rankings, such as world's most powerful people, world's richest people, top-paid tennis stars, and so on and so forth. Herewith, we study a specific kind, sports ranking systems in which players' scores and prize money are calculated based on their performances in attending various tournaments. A typical example is tennis. It is found that the distributions of both scores and prize money follow universal power laws, with exponents nearly identical for most sports fields. 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 will top 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 simul...

  20. A Review of Outcomes of Seven World University Ranking Systems

    National Research Council Canada - National Science Library

    Mahmood Khosrowjerdi; Neda Zeraatkar

    2012-01-01

    There are many national and international ranking systems rank the universities and higher education institutions of the world, nationally or internationally, based on the same or different criteria...

  1. Framing the Candidate: A Corpus-based Rhetorical Analysis of the 2016 Democratic Primaries in the USA

    OpenAIRE

    Biondi, Alberto

    2017-01-01

    Framing the Candidate: A Corpus-Based Rhetorical Analysis of the 2016 Democratic Primaries in the USA analyzes the rhetoric of the two main Democratic candidates running in the 2016 election cycle: Hillary Rodham Clinton and Bernard ‘Bernie’ Sanders. In order to identify the main persuasive strategies employed, we used the tools of corpus linguistics to study their campaign speeches and interventions during the televised debates. The transcripts of the speeches were collected both online and ...

  2. Sequence-Based Introgression Mapping Identifies Candidate White Mold Tolerance Genes in Common Bean

    Directory of Open Access Journals (Sweden)

    Sujan Mamidi

    2016-07-01

    Full Text Available White mold, caused by the necrotrophic fungus (Lib. de Bary, is a major disease of common bean ( L.. WM7.1 and WM8.3 are two quantitative trait loci (QTL with major effects on tolerance to the pathogen. Advanced backcross populations segregating individually for either of the two QTL, and a recombinant inbred (RI population segregating for both QTL were used to fine map and confirm the genetic location of the QTL. The QTL intervals were physically mapped using the reference common bean genome sequence, and the physical intervals for each QTL were further confirmed by sequence-based introgression mapping. Using whole-genome sequence data from susceptible and tolerant DNA pools, introgressed regions were identified as those with significantly higher numbers of single-nucleotide polymorphisms (SNPs relative to the whole genome. By combining the QTL and SNP data, WM7.1 was located to a 660-kb region that contained 41 gene models on the proximal end of chromosome Pv07, while the WM8.3 introgression was narrowed to a 1.36-Mb region containing 70 gene models. The most polymorphic candidate gene in the WM7.1 region encodes a BEACH-domain protein associated with apoptosis. Within the WM8.3 interval, a receptor-like protein with the potential to recognize pathogen effectors was the most polymorphic gene. The use of gene and sequence-based mapping identified two candidate genes whose putative functions are consistent with the current model of pathogenicity.

  3. Identification of fungal candidates for asthma protection in a large population-based study.

    Science.gov (United States)

    Mueller-Rompa, Susanne; Janke, Tobias; Schwaiger, Karin; Mayer, Melanie; Bauer, Johann; Genuneit, Jon; Braun-Fahrlaender, Charlotte; Horak, Elisabeth; Boznanski, Andrzej; von Mutius, Erika; Ege, Markus J

    2017-02-01

    Exposure to molds has been related to asthma risk both positively and negatively, depending on the environmental setting. The pertinent results are based on generic markers or culturing methods although the majority of present fungi cannot be cultured under laboratory conditions. The aim of the present analysis was to assess environmental dust samples for asthma-protective fungal candidates with a comprehensive molecular technique covering also non-cultivable and non-viable fungi. Mattress dust samples of 844 children from the GABRIELA study were analyzed by polymerase chain reaction-single-strand conformation polymorphism (PCR-SSCP) of the fungus-specific internal transcribed spacer (ITS) region. Known asthma candidate species were tested for their associations with asthma, and further gel positions were sought to explain the above. As a second, data-driven, analysis, we tested the association of each individual gel position with asthma. In the hypothesis-driven approach, Penicillium chrysogenum emerged with an odds ratio of 0.80 (95% confidence interval 0.66-0.96; p = 0.020). The effect size was changed by 39% toward the null when adjusting for the two bands 683 (DNA of Metschnikowia sp., Aureobasidium spp.) and 978 (DNA of Epicoccum spp., Galactomyces spp., uncultured Penicillium). The data-driven approach yielded an additional band (containing DNA of Pseudotaeniolina globosa) with reduced risk of asthma (OR = 0.80 [0.66-0.96], p = 0.012). A large population-based study revealed several fungal taxa with inverse associations with childhood asthma. Molds produce a variety of bioactive compounds with detrimental but also beneficial immunoregulatory capacities, which renders them promising targets for further asthma research. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Ranking Baltic States Researchers

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2017-10-01

    Full Text Available In this article, using the h-index and the total number of citations, the best 10 Lithuanian, Latvian and Estonian researchers from several disciplines are ranked. The list may be formed based on the h-index and the total number of citations, given in Web of Science, Scopus, Publish or Perish Program and Google Scholar database. Data for the first 10 researchers are presented. Google Scholar is the most complete. Therefore, to define a single indicator, h-index calculated by Google Scholar may be a good and simple one. The author chooses the Google Scholar database as it is the broadest one.

  5. A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

    Directory of Open Access Journals (Sweden)

    Vassal Aurélien

    2008-01-01

    Full Text Available Abstract Background The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM patients. Results After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM. Conclusion This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with

  6. Local constructions of gender-based violence amongst IDPs in northern Uganda: analysis of archival data collected using a gender- and age-segmented participatory ranking methodology.

    Science.gov (United States)

    Ager, Alastair; Bancroft, Carolyn; Berger, Elizabeth; Stark, Lindsay

    2018-01-01

    Gender-based violence (GBV) is a significant problem in conflict-affected settings. Understanding local constructions of such violence is crucial to developing preventive and responsive interventions to address this issue. This study reports on a secondary analysis of archived data collected as part of formative qualitative work - using a group participatory ranking methodology (PRM) - informing research on the prevalence of GBV amongst IDPs in northern Uganda in 2006. Sixty-four PRM group discussions were held with women, with men, with girls (aged 14 to 18 years), and with boys (aged 14 to 18 years) selected on a randomized basis across four internally displaced persons (IDP) camps in Lira District. Discussions elicited problems facing women in the camps, and - through structured participatory methods - consensus ranking of their importance and narrative accounts explaining these judgments. Amongst forms of GBV faced by women, rape was ranked as the greatest concern amongst participants (with a mean problem rank of 3.4), followed by marital rape (mean problem rank of 4.5) and intimate partner violence (mean problem rank of 4.9). Girls ranked all forms of GBV as higher priority concerns than other participants. Discussions indicated that these forms of GBV were generally considered normalized within the camp. Gender roles and power, economic deprivation, and physical and social characteristics of the camp setting emerged as key explanatory factors in accounts of GBV prevalence, although these played out in different ways with respect to differing forms of violence. All groups acknowledged GBV to represent a significant threat - among other major concerns such as transportation, water, shelter, food and security - for women residing in the camps. Given evidence of the significantly higher risk in the camp of intimate partner violence and marital rape, the relative prominence of the issue of rape in all rankings suggests normalization of violence within the home

  7. 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.

    2017-01-01

    -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...

  8. Unique Nanoparticle Optical Properties Confound Fluorescent Based Assays Widely Employed in Their In Vitro Toxicity Screening and Ranking

    Science.gov (United States)

    Nanoparticles (NPs) are novel materials having at least one dimension less than 100 nm and display unique physicochemical properties due to their nanoscale size. An emphasis has been placed on developing high throughput screening (HTS) assays to characterize and rank the toxiciti...

  9. The Extremely Luminous Quasar Survey in the SDSS Footprint. I. Infrared-based Candidate Selection

    Science.gov (United States)

    Schindler, Jan-Torge; Fan, Xiaohui; McGreer, Ian D.; Yang, Qian; Wu, Jin; Jiang, Linhua; Green, Richard

    2017-12-01

    Studies of the most luminous quasars at high redshift directly probe the evolution of the most massive black holes in the early universe and their connection to massive galaxy formation. However, extremely luminous quasars at high redshift are very rare objects. Only wide-area surveys have a chance to constrain their population. The Sloan Digital Sky Survey (SDSS) has so far provided the most widely adopted measurements of the quasar luminosity function at z> 3. However, a careful re-examination of the SDSS quasar sample revealed that the SDSS quasar selection is in fact missing a significant fraction of z≳ 3 quasars at the brightest end. We identified the purely optical-color selection of SDSS, where quasars at these redshifts are strongly contaminated by late-type dwarfs, and the spectroscopic incompleteness of the SDSS footprint as the main reasons. Therefore, we designed the Extremely Luminous Quasar Survey (ELQS), based on a novel near-infrared JKW2 color cut using Wide-field Infrared Survey Explorer mission (WISE) AllWISE and 2MASS all-sky photometry, to yield high completeness for very bright ({m}{{i}}learning algorithms on SDSS and WISE photometry for quasar-star classification and photometric redshift estimation. The ELQS will spectroscopically follow-up ˜230 new quasar candidates in an area of ˜12,000 deg2 in the SDSS footprint to obtain a well-defined and complete quasar sample for an accurate measurement of the bright-end quasar luminosity function (QLF) at 3.0≤slant z≤slant 5.0. In this paper, we present the quasar selection algorithm and the quasar candidate catalog.

  10. Development of Au-Ge based candidate alloys as an alternative to high-lead content solders

    DEFF Research Database (Denmark)

    Chidambaram, Vivek; Hald, John; Hattel, Jesper Henri

    2010-01-01

    Au-Ge based candidate alloys have been proposed as an alternative to high-lead content solders that are currently being used for high-temperature applications. The changes in microstructure and microhardness associated with the addition of low melting point metals namely In, Sb and Sn to the Au......-Ge eutectic were investigated in this work. Furthermore, the effects of thermal aging on the microstructure and its corresponding microhardness of these promising candidate alloys have been extensively reported. To investigate the effects of aging temperature, candidate alloys were aged at a lower temperature......, 150°C for up to 3 weeks and compared with aging at 200°C. After being subjected to high-temperature aging, the microstructure varied a lot in morphology in the case of both Au-Ge-Sb and Au-Ge-Sn candidate alloys while the microstructure remained relatively stable even after long-term thermal aging...

  11. Ranking structures and Rank-Rank Correlations of Countries. The FIFA and UEFA cases

    CERN Document Server

    Ausloos, Marcel; Gadomski, Adam; Vitanov, Nikolay K

    2014-01-01

    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.

  12. 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.

  13. 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.

  14. Solid particle erosion of steels and nickel based alloys candidates for USC steam turbine blading

    Energy Technology Data Exchange (ETDEWEB)

    Cernuschi, Federico; Guardamagna, Cristina; Lorenzoni, Lorenzo [ERSE SpA, Milan (Italy); Robba, Davide [CESI, Milan (Italy)

    2010-07-01

    The main objective of COST536 Action is to develop highly efficient steam power plant with low emissions, from innovative alloy development to validation of component integrity. In this perspective, to improve the operating efficiency, materials capable of withstanding higher operating temperatures are required. For the manufacturing of components for steam power plants with higher efficiency steels and nickel-based alloys with improved oxidation resistance and creep strength at temperature as high as 650 C - 700 C have to be developed. Candidate alloys for manufacturing high pressure steam turbine diaphragms, buckets, radial seals and control valves should exhibit, among other properties, a good resistance at the erosion phenomena induced by hard solid particles. Ferric oxide (magnetite) scales cause SPE by exfoliating from boiler tubes and steam pipes (mainly super-heaters and re-heaters) and being transported within the steam flow to the turbine. In order to comparatively study the erosion behaviour of different materials in relatively short times, an accelerated experimental simulation of the erosion phenomena must be carried out. Among different techniques to induce erosion on material targets, the use of an air jet tester is well recognised to be one of the most valid and reliable. In this work the results of SPE comparative tests performed at high temperatures (550 C, 600 C and 650 C) at different impaction angles on some steels and nickel based alloys samples are reported. (orig.)

  15. In Silico Analysis of Epitope-Based Vaccine Candidates against Hepatitis B Virus Polymerase Protein.

    Science.gov (United States)

    Zheng, Juzeng; Lin, Xianfan; Wang, Xiuyan; Zheng, Liyu; Lan, Songsong; Jin, Sisi; Ou, Zhanfan; Wu, Jinming

    2017-05-16

    Hepatitis B virus (HBV) infection has persisted as a major public health problem due to the lack of an effective treatment for those chronically infected. Therapeutic vaccination holds promise, and targeting HBV polymerase is pivotal for viral eradication. In this research, a computational approach was employed to predict suitable HBV polymerase targeting multi-peptides for vaccine candidate selection. We then performed in-depth computational analysis to evaluate the predicted epitopes' immunogenicity, conservation, population coverage, and toxicity. Lastly, molecular docking and MHC-peptide complex stabilization assay were utilized to determine the binding energy and affinity of epitopes to the HLA-A0201 molecule. Criteria-based analysis provided four predicted epitopes, RVTGGVFLV, VSIPWTHKV, YMDDVVLGA and HLYSHPIIL. Assay results indicated the lowest binding energy and high affinity to the HLA-A0201 molecule for epitopes VSIPWTHKV and YMDDVVLGA and epitopes RVTGGVFLV and VSIPWTHKV, respectively. Regions 307 to 320 and 377 to 387 were considered to have the highest probability to be involved in B cell epitopes. The T cell and B cell epitopes identified in this study are promising targets for an epitope-focused, peptide-based HBV vaccine, and provide insight into HBV-induced immune response.

  16. A Sub-Pathway Based Method to Identify Candidate Agents for Ankylosing Spondylitis

    Directory of Open Access Journals (Sweden)

    Ming Li

    2012-10-01

    Full Text Available The need for new therapeutics for Ankylosing Spondylitis (AS is highlighted by the general lack of efficacy for most agents currently available for this disease. Many recent studies have detailed molecular pathways in AS, and several molecule-targeting agents are undergoing evaluation. We aimed to explore the mechanism of AS and identify biologically active small molecules capable of targeting the sub-pathways which were disregulated in the development of AS. By using the GSE25101 microarray data accessible from the Gene Expression Omnibus database, we first identified the differentially expressed genes (DEGs between AS samples and healthy controls, followed by the sub-pathway enrichment analysis of the DEGs. In addition, we propose the use of an approach based on targeting sub-pathways to identify potential agents for AS. A total of 3,280 genes were identified as being significantly different between patients and controls with p-values < 0.1. Our study showed that neurotrophic signaling pathway and some immune-associated pathways may be involved in the development of AS. Besides, our bioinformatics analysis revealed a total of 15 small molecules which may play a role in perturbing the development of AS. Our study proposes the use of an approach based on targeting sub-pathways to identify potential agents for AS. Candidate agents identified by our approach may provide the groundwork for a combination therapy approach for AS.

  17. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Science.gov (United States)

    Bánky, Dániel; Iván, Gábor; Grolmusz, Vince

    2013-01-01

    Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks) that compensates for the low degree (non-hub) vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges) of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well), but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus), and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures importance in the

  18. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Directory of Open Access Journals (Sweden)

    Dániel Bánky

    Full Text Available Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks that compensates for the low degree (non-hub vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well, but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus, and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures

  19. UNIVERSITY RANKINGS BY COST OF LIVING ADJUSTED FACULTY COMPENSATION

    OpenAIRE

    Terrance Jalbert; Mercedes Jalbert; Karla Hayashi

    2010-01-01

    In this paper we rank 574 universities based on compensation paid to their faculty. The analysis examines universities both on a raw basis and on a cost of living adjusted basis. Rankings based on salary data and benefit data are presented. In addition rankings based on total compensation are presented. Separate rankings are provided for universities offering different degrees. The results indicate that rankings of universities based on raw and cost of living adjusted data are markedly differ...

  20. Candidate Gene Analysis Suggests Untapped Genetic Complexity in Melanin-Based Pigmentation in Birds.

    Science.gov (United States)

    Bourgeois, Yann X C; Bertrand, Joris A M; Delahaie, Boris; Cornuault, Josselin; Duval, Thomas; Milá, Borja; Thébaud, Christophe

    2016-07-01

    Studies on melanin-based color variation in a context of natural selection have provided a wealth of information on the link between phenotypic and genetic variation. Here, we evaluated associations between melanic plumage patterns and genetic polymorphism in the Réunion grey white-eye (Zosterops borbonicus), a species in which mutations on MC1R do not seem to play any role in explaining melanic variation. This species exhibits 5 plumage color variants that can be grouped into 3 color forms which occupy discrete geographic regions in the lowlands of Réunion, and a fourth high-elevation form which comprises 2 color morphs (grey and brown) and represents a true color polymorphism. We conducted a comprehensive survey of sequence variation in 96 individuals at a series of 7 candidate genes other than MC1R that have been previously shown to influence melanin-based color patterns in vertebrates, including genes that have rarely been studied in a wild bird species before: POMC, Agouti, TYR, TYRP1, DCT, Corin, and SLC24A5 Of these 7 genes, 2 (Corin and TYRP1) displayed an interesting shift in allele frequencies between lowland and highland forms and a departure from mutation-drift equilibrium consistent with balancing selection in the polymorphic highland form only. Sequence variation at Agouti, a gene frequently involved in melanin-based pigmentation patterning, was not associated with color forms or morphs. Thus, we suggest that functionally important changes in loci other than those classically studied are involved in the color polymorphism exhibited by the Réunion grey white-eye and possibly many other nonmodel species. © The American Genetic Association. 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Whole Genome Sequencing-Based Mapping and Candidate Identification of Mutations from Fixed Zebrafish Tissue

    Directory of Open Access Journals (Sweden)

    Nicholas E. Sanchez

    2017-10-01

    Full Text Available As forward genetic screens in zebrafish become more common, the number of mutants that cannot be identified by gross morphology or through transgenic approaches, such as many nervous system defects, has also increased. Screening for these difficult-to-visualize phenotypes demands techniques such as whole-mount in situ hybridization (WISH or antibody staining, which require tissue fixation. To date, fixed tissue has not been amenable for generating libraries for whole genome sequencing (WGS. Here, we describe a method for using genomic DNA from fixed tissue and a bioinformatics suite for WGS-based mapping of zebrafish mutants. We tested our protocol using two known zebrafish mutant alleles, gpr126st49 and egr2bfh227, both of which cause myelin defects. As further proof of concept we mapped a novel mutation, stl64, identified in a zebrafish WISH screen for myelination defects. We linked stl64 to chromosome 1 and identified a candidate nonsense mutation in the F-box and WD repeat domain containing 7 (fbxw7 gene. Importantly, stl64 mutants phenocopy previously described fbxw7vu56 mutants, and knockdown of fbxw7 in wild-type animals produced similar defects, demonstrating that stl64 disrupts fbxw7. Together, these data show that our mapping protocol can map and identify causative lesions in mutant screens that require tissue fixation for phenotypic analysis.

  2. Cell-Based Assay Design for High-Content Screening of Drug Candidates.

    Science.gov (United States)

    Nierode, Gregory; Kwon, Paul S; Dordick, Jonathan S; Kwon, Seok-Joon

    2016-02-01

    To reduce attrition in drug development, it is crucial to consider the development and implementation of translational phenotypic assays as well as decipher diverse molecular mechanisms of action for new molecular entities. High-throughput fluorescence and confocal microscopes with advanced analysis software have simplified the simultaneous identification and quantification of various cellular processes through what is now referred to as highcontent screening (HCS). HCS permits automated identification of modifiers of accessible and biologically relevant targets and can thus be used to detect gene interactions or identify toxic pathways of drug candidates to improve drug discovery and development processes. In this review, we summarize several HCS-compatible, biochemical, and molecular biology-driven assays, including immunohistochemistry, RNAi, reporter gene assay, CRISPR-Cas9 system, and protein-protein interactions to assess a variety of cellular processes, including proliferation, morphological changes, protein expression, localization, post-translational modifications, and protein-protein interactions. These cell-based assay methods can be applied to not only 2D cell culture but also 3D cell culture systems in a high-throughput manner.

  3. Trust Based Algorithm for Candidate Node Selection in Hybrid MANET-DTN

    Directory of Open Access Journals (Sweden)

    Jan Papaj

    2014-01-01

    Full Text Available The hybrid MANET - DTN is a mobile network that enables transport of the data between groups of the disconnected mobile nodes. The network provides benefits of the Mobile Ad-Hoc Networks (MANET and Delay Tolerant Network (DTN. The main problem of the MANET occurs if the communication path is broken or disconnected for some short time period. On the other side, DTN allows sending data in the disconnected environment with respect to higher tolerance to delay. Hybrid MANET - DTN provides optimal solution for emergency situation in order to transport information. Moreover, the security is the critical factor because the data are transported by mobile devices. In this paper, we investigate the issue of secure candidate node selection for transportation of the data in a disconnected environment for hybrid MANET- DTN. To achieve the secure selection of the reliable mobile nodes, the trust algorithm is introduced. The algorithm enables select reliable nodes based on collecting routing information. This algorithm is implemented to the simulator OPNET modeler.

  4. Synthesis of 1,2,3-Thiadiazole and Thiazole-Based Strobilurins as Potent Fungicide Candidates.

    Science.gov (United States)

    Chen, Lai; Zhu, Yu-Jie; Fan, Zhi-Jin; Guo, Xiao-Feng; Zhang, Zhi-Ming; Xu, Jing-Hua; Song, Ying-Qi; Yurievich, Morzherin Y; Belskaya, Nataliya P; Bakulev, Vasiliy A

    2017-02-01

    Strobilurin fungicides play a crucial role in protecting plants against different pathogens and securing food supplies. A series of 1,2,3-thiadiazole and thiazole-based strobilurins were rationally designed, synthesized, characterized, and tested against various fungi. Introduction of 1,2,3-thiadiazole greatly improved the fungicidal activity of the target molecules. Compounds 8a, 8c, 8d, and 10i exhibited a relatively broad spectrum of fungicidal activity. Compound 8a showed excellent activities against Gibberella zeae, Sclerotinia sclerotiorum, and Rhizoctonia cerealis with median effective concentrations (EC50) of 2.68, 0.44, and 0.01 μg/mL, respectively; it was much more active than positive controls enestroburin, kresoxim-methyl, and azoxystrobin with EC50 between 0.06 and 15.12 μg/mL. Comparable or better fungicidal efficacy of compound 8a compared with azoxystrobin and trifloxystrobin against Sphaerotheca fuliginea and Pseudoperonspera cubensis was validated in cucumber fields at the same application dosages. Therefore, compound 8a is a promising fungicidal candidate worthy of further development.

  5. Synthesis and Characterization of Acrylic-Based Photopolymer as a Candidate for Denture Base Material

    Science.gov (United States)

    Wicaksono, S. T.; Rasyida; Ardhyananta, H.

    2017-05-01

    Denture base is a denture part that rests on the soft tissue covering the jawbone and becomes an anchor of a denture. The material that commonly used for this purpose is poly (methyl methacrylate). However, it lacks in mechanical properties due to high water absorption. The aim of this research was to improve the physical and mechanical properties of poly (methyl methacrylate) by making a copolymer with styrene via photopolymerization process. In this method was used the addition of styrene monomer at 10, 20, 30, 40, and 50 wt% into the acrylic resin to form copolymer materials via photopolymerization process. The amount of 1.5 wt% Irgacure 784’s photoinitiator was added as a photoinitiator. The results showed that the addition of 40% by weight of styrene copolymer is the best performance compare to the addition styrene of 10, 20, 30, and 50%. The samples with an addition styrene of 40 wt% showed excellent properties such as high water absorption value of 2.405 μg/mm3, the solubility of 0.434 μg/mm3, the flexural strength of 69.336 MPa, a flexural modulus of 1.236 GPa, and a hardness value of 82.583 HD. Poly (methyl methacrylate-co-styrene) copolymer with the addition of styrene 40 wt% has the closest value to the requirements for a denture base material.

  6. Robust Visual Tracking Via Consistent Low-Rank Sparse Learning

    KAUST Repository

    Zhang, Tianzhu

    2014-06-19

    Object tracking is the process of determining the states of a target in consecutive video frames based on properties of motion and appearance consistency. In this paper, we propose a consistent low-rank sparse tracker (CLRST) that builds upon the particle filter framework for tracking. By exploiting temporal consistency, the proposed CLRST algorithm adaptively prunes and selects candidate particles. By using linear sparse combinations of dictionary templates, the proposed method learns the sparse representations of image regions corresponding to candidate particles jointly by exploiting the underlying low-rank constraints. In addition, the proposed CLRST algorithm is computationally attractive since temporal consistency property helps prune particles and the low-rank minimization problem for learning joint sparse representations can be efficiently solved by a sequence of closed form update operations. We evaluate the proposed CLRST algorithm against 14 state-of-the-art tracking methods on a set of 25 challenging image sequences. Experimental results show that the CLRST algorithm performs favorably against state-of-the-art tracking methods in terms of accuracy and execution time.

  7. Power System Event Ranking Using a New Linear Parameter-Varying Modeling with a Wide Area Measurement System-Based Approach

    Directory of Open Access Journals (Sweden)

    Mohammad Bagher Abolhasani Jabali

    2017-07-01

    Full Text Available Detecting critical power system events for Dynamic Security Assessment (DSA is required for reliability improvement. The approach proposed in this paper investigates the effects of events on dynamic behavior during nonlinear system response while common approaches use steady-state conditions after events. This paper presents some new and enhanced indices for event ranking based on time-domain simulation and polytopic linear parameter-varying (LPV modeling of a power system. In the proposed approach, a polytopic LPV representation is generated via linearization about some points of the nonlinear dynamic behavior of power system using wide-area measurement system (WAMS concepts and then event ranking is done based on the frequency response of the system models on the vertices. Therefore, the nonlinear behaviors of the system in the time of fault occurrence are considered for events ranking. The proposed algorithm is applied to a power system using nonlinear simulation. The comparison of the results especially in different fault conditions shows the advantages of the proposed approach and indices.

  8. A candidate gene-based association study of tocopherol content and composition in rapeseed (Brassica napus

    Directory of Open Access Journals (Sweden)

    Steffi eFritsche

    2012-06-01

    Full Text Available Rapeseed (Brassica napus L. is the most important oil crop of temperate climates. Rapeseed oil contains tocopherols, also known as vitamin E, which is an indispensable nutrient for humans and animals due to its antioxidant and radical scavenging abilities. Moreover, tocopherols are also important for the oxidative stability of vegetable oils. Therefore, seed oil with increased tocopherol content or altered tocopherol composition is a target for breeding. We investigated the role of nucleotide variations within candidate genes from the tocopherol biosynthesis pathway. Field trials were carried out with 229 accessions from a worldwide B. napus collection which was divided into two panels of 96 and 133 accessions. Seed tocopherol content and composition were measured by HPLC. High heritabilities were found for both traits, ranging from 0.62 to 0.94. We identified polymorphisms by sequencing selected regions of the tocopherol genes from the 96 accession panel. Subsequently, we determined the population structure (Q and relative kinship (K as detected by genotyping with genome-wide distributed SSR markers. Association studies were performed using two models, the structure-based GLM+Q and the PK mixed model. Between 26 and 12 polymorphisms within two genes (BnaX.VTE3.a, BnaA.PDS1.c were significantly associated with tocopherol traits. The SNPs explained up to 16.93 % of the genetic variance for tocopherol composition and up to 10.48 % for total tocopherol content. Based on the sequence information we designed CAPS markers for genotyping the 133 accessions from the 2nd panel. Significant associations with various tocopherol traits confirmed the results from the first experiment. We demonstrate that the polymorphisms within the tocopherol genes clearly impact tocopherol content and composition in B. napus seeds. We suggest that these nucleotide variations may be used as selectable markers for breeding rapeseed with enhanced tocopherol quality.

  9. Detection of colonic polyp candidates with level set-based thickness mapping over the colon wall

    Science.gov (United States)

    Han, Hao; Li, Lihong; Duan, Chaijie; Zhao, Yang; Wang, Huafeng; Liang, Zhengrong

    2015-03-01

    Further improvement of computer-aided detection (CADe) of colonic polyps is vital to advance computed tomographic colonography (CTC) toward a screening modality, where the detection of flat polyps is especially challenging because limited image features can be extracted from flat polyps, and the traditional geometric features-based CADe methods usually fail to detect such polyps. In this paper, we present a novel pipeline to automatically detect initial polyp candidates (IPCs), especially flat polyps, from CTC images. First, the colon wall mucosa was extracted via a partial volume segmentation approach as a volumetric layer, where the inner border of colon wall can be obtained by shrinking the volumetric layer using level set based adaptive convolution. Then the outer border of colon wall (or the colon wall serosa) was segmented via a combined implementation of geodesic active contour and Mumford-Shah functional in a coarse-to-fine manner. Finally, the wall thickness was estimated along a unique path between the segmented inner and outer borders with consideration of the volumetric layers and was mapped onto a patient-specific three-dimensional (3D) colon wall model. The IPC detection results can usually be better visualized in a 2D image flattened from the 3D model, where abnormalities were detected by Z-score transformation of the thickness values. The proposed IPC detection approach was validated on 11 patients with 22 CTC scans, and each scan has at least one flat poly annotation. The above presented novel pipeline was effective to detect some flat polyps that were missed by our CADe system while keeping false detections in a relative low level. This preliminary study indicates that the presented pipeline can be incorporated into an existing CADe system to enhance the polyp detection power, especially for flat polyps.

  10. Detection of the early keratoconus based on corneal biomechanical properties in the refractive surgery candidates

    Directory of Open Access Journals (Sweden)

    Zofia Pniakowska

    2016-01-01

    Full Text Available Context: Subclinical keratoconus is contraindication to refractive surgery. The currently used methods of preoperative screening do not always allow differentiating between healthy eyes and those with subclinical keratoconus. Aim: To evaluate biomechanical parameters of the cornea, waveform score (WS, and intraocular pressure (IOP as potentially useful adjuncts to the diagnostic algorithm for precise detection of the early keratoconus stages and selection of refractive surgery candidates. Settings and Design: Department of Ophthalmology and prospective cross-sectional study. Patients and Methods: Patients enrolled in the study were diagnosed with refractive disorders. We assessed parameters of corneal biomechanics such as corneal hysteresis (CH, corneal resistance factor (CRF, Goldman-correlated IOP (IOPg, corneal compensated IOP, WS, and keratoconus match index (KMI. They were classified into one of three groups based on the predefined KMI range: Group 1 (from 0.352 to 0.757 – 45 eyes, Group 2 (from −0.08 to 0.313 – 52 eyes, and Group 0 - control group (from 0.761 to 1.642 – 80 eyes. Results: In both study groups, IOPg, CRF, and CH were decreased when compared to control (P < 0.0001. In control group, there was positive correlation between CH and KMI (P < 0.05, with no correlations in any of the two study groups. CRF correlated positively with KMI in control (P < 0.0001 and in Group 2 (P < 0.05. Conclusions: CH and CRF, together with WS and IOPg, consist a clinically useful adjunct to detect subclinical keratoconus in patients referred for refractive surgery when based on KMI staging.

  11. PROTECTIVE ACTIVITY STUDY OF A CANDIDATE VACCINE AGAINST ROTAVIRUS INFECTION BASED ON RECOMBINANT PROTEIN FliCVP6VP8

    Directory of Open Access Journals (Sweden)

    I. V. Dukhovlinov

    2016-01-01

    Full Text Available Rotavirus infection is among leading causes of severe diarrhea which often leads to severe dehydration, especially, in children under 5 years old. In Russia, the incidence of rotavirus infection is constantly increased, due to higher rates of actual rotavirus infection cases and improved diagnostics of the disease. Immunity to rotavirus is unstable, thus causing repeated infections intra vitam. Anti-infectious resistance in reconvalescents is explained by induction of specific IgM, IgG, and, notably, IgA antibodies. Due to absence of market drugs with direct action against rotavirus, a rational vaccination is considered the most effective way to control the disease. Currently available vaccines for prevention of rotavirus infection are based on live attenuated rotavirus strains, human and/or animal origin, which replicate in human gut. Their implementation may result into different complications. Meanwhile, usage of vaccines based on recombinant proteins is aimed to avoid risks associated with introduction of a complete virus into humans. In this paper, we studied protective activity of candidate vaccines against rotavirus.In this work we studied protective activity of a candidate vaccine against rotavirus infection based on recombinant FliCVP6VP8 protein which includes VP6 and VP8, as well as components of Salmonella typhimurium flagellin (FliC as an adjuvant. Different components are joined by flexible bridges. Efficiency of the candidate vaccine was studied in animal model using Balb/c mice. We have shown high level of protection which occurs when the candidate vaccine is administered twice intramuscularly. Complete protection of animals against mouse rotavirus EDC after intramuscular immunization with a candidate vaccine was associated with arising rotavirus-specific IgA and IgG antibodies in serum and intestine of immunized animals. The efficacy of candidate vaccine based on recombinant protein FliCVP6VP8 against rotavirus infection was

  12. 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.

  13. Incorporation of Socio-Economic Features' Ranking in Multicriteria Analysis Based on Ecosystem Services for Marine Protected Area Planning.

    Science.gov (United States)

    Portman, Michelle E; Shabtay-Yanai, Ateret; Zanzuri, Asaf

    2016-01-01

    Developed decades ago for spatial choice problems related to zoning in the urban planning field, multicriteria analysis (MCA) has more recently been applied to environmental conflicts and presented in several documented cases for the creation of protected area management plans. Its application is considered here for the development of zoning as part of a proposed marine protected area management plan. The case study incorporates specially-explicit conservation features while considering stakeholder preferences, expert opinion and characteristics of data quality. It involves the weighting of criteria using a modified analytical hierarchy process. Experts ranked physical attributes which include socio-economically valued physical features. The parameters used for the ranking of (physical) attributes important for socio-economic reasons are derived from the field of ecosystem services assessment. Inclusion of these feature values results in protection that emphasizes those areas closest to shore, most likely because of accessibility and familiarity parameters and because of data biases. Therefore, other spatial conservation prioritization methods should be considered to supplement the MCA and efforts should be made to improve data about ecosystem service values farther from shore. Otherwise, the MCA method allows incorporation of expert and stakeholder preferences and ecosystem services values while maintaining the advantages of simplicity and clarity.

  14. Incorporation of Socio-Economic Features' Ranking in Multicriteria Analysis Based on Ecosystem Services for Marine Protected Area Planning.

    Directory of Open Access Journals (Sweden)

    Michelle E Portman

    Full Text Available Developed decades ago for spatial choice problems related to zoning in the urban planning field, multicriteria analysis (MCA has more recently been applied to environmental conflicts and presented in several documented cases for the creation of protected area management plans. Its application is considered here for the development of zoning as part of a proposed marine protected area management plan. The case study incorporates specially-explicit conservation features while considering stakeholder preferences, expert opinion and characteristics of data quality. It involves the weighting of criteria using a modified analytical hierarchy process. Experts ranked physical attributes which include socio-economically valued physical features. The parameters used for the ranking of (physical attributes important for socio-economic reasons are derived from the field of ecosystem services assessment. Inclusion of these feature values results in protection that emphasizes those areas closest to shore, most likely because of accessibility and familiarity parameters and because of data biases. Therefore, other spatial conservation prioritization methods should be considered to supplement the MCA and efforts should be made to improve data about ecosystem service values farther from shore. Otherwise, the MCA method allows incorporation of expert and stakeholder preferences and ecosystem services values while maintaining the advantages of simplicity and clarity.

  15. Maximum Waring ranks of monomials

    OpenAIRE

    Holmes, Erik; Plummer, Paul; Siegert, Jeremy; Teitler, Zach

    2013-01-01

    We show that monomials and sums of pairwise coprime monomials in four or more variables have Waring rank less than the generic rank, with a short list of exceptions. We asymptotically compare their ranks with the generic rank.

  16. University ranking methodologies. An interview with Ben Sowter about the Quacquarelli Symonds World University Ranking

    OpenAIRE

    Alberto Baccini; Antono Banfi; Giuseppe De Nicolao; Paola Galimberti

    2015-01-01

    University rankings represent a controversial issue in the debate about higher education policy. One of the best known university ranking is the Quacquarelli Symonds World University Rankings (QS), published annually since 2004 by Quacquarelli Symonds ltd, a company founded in 1990 and headquartered in London. QS provides a ranking based on a score calculated by weighting six different indicators. The 2015 edition, published in October 2015, introduced major methodological innovations and, as...

  17. Design of lead-free candidate alloys for high-temperature soldering based on the Au–Sn system

    DEFF Research Database (Denmark)

    Chidambaram, Vivek; Hattel, Jesper Henri; Hald, John

    2010-01-01

    of the Au–Sn binary system were explored in this work. Furthermore, the effects of thermal aging on the microstructure and microhardness of these promising Au–Sn based ternary alloys were investigated. For this purpose, the candidate alloys were aged at a lower temperature, 150°C for up to 1week...

  18. Low-rank sparse learning for robust visual tracking

    KAUST Repository

    Zhang, Tianzhu

    2012-01-01

    In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm capitalizes on the inherent low-rank structure of particle representations that are learned jointly. As such, it casts the tracking problem as a low-rank matrix learning problem. This low-rank sparse tracker (LRST) has a number of attractive properties. (1) Since LRST adaptively updates dictionary templates, it can handle significant changes in appearance due to variations in illumination, pose, scale, etc. (2) The linear representation in LRST explicitly incorporates background templates in the dictionary and a sparse error term, which enables LRST to address the tracking drift problem and to be robust against occlusion respectively. (3) LRST is computationally attractive, since the low-rank learning problem can be efficiently solved as a sequence of closed form update operations, which yield a time complexity that is linear in the number of particles and the template size. We evaluate the performance of LRST by applying it to a set of challenging video sequences and comparing it to 6 popular tracking methods. Our experiments show that by representing particles jointly, LRST not only outperforms the state-of-the-art in tracking accuracy but also significantly improves the time complexity of methods that use a similar sparse linear representation model for particles [1]. © 2012 Springer-Verlag.

  19. Chest Fat Quantification via CT Based on Standardized Anatomy Space in Adult Lung Transplant Candidates.

    Directory of Open Access Journals (Sweden)

    Yubing Tong

    Full Text Available Overweight and underweight conditions are considered relative contraindications to lung transplantation due to their association with excess mortality. Yet, recent work suggests that body mass index (BMI does not accurately reflect adipose tissue mass in adults with advanced lung diseases. Alternative and more accurate measures of adiposity are needed. Chest fat estimation by routine computed tomography (CT imaging may therefore be important for identifying high-risk lung transplant candidates. In this paper, an approach to chest fat quantification and quality assessment based on a recently formulated concept of standardized anatomic space (SAS is presented. The goal of the paper is to seek answers to several key questions related to chest fat quantity and quality assessment based on a single slice CT (whether in the chest, abdomen, or thigh versus a volumetric CT, which have not been addressed in the literature.Unenhanced chest CT image data sets from 40 adult lung transplant candidates (age 58 ± 12 yrs and BMI 26.4 ± 4.3 kg/m2, 16 with chronic obstructive pulmonary disease (COPD, 16 with idiopathic pulmonary fibrosis (IPF, and the remainder with other conditions were analyzed together with a single slice acquired for each patient at the L5 vertebral level and mid-thigh level. The thoracic body region and the interface between subcutaneous adipose tissue (SAT and visceral adipose tissue (VAT in the chest were consistently defined in all patients and delineated using Live Wire tools. The SAT and VAT components of chest were then segmented guided by this interface. The SAS approach was used to identify the corresponding anatomic slices in each chest CT study, and SAT and VAT areas in each slice as well as their whole volumes were quantified. Similarly, the SAT and VAT components were segmented in the abdomen and thigh slices. Key parameters of the attenuation (Hounsfield unit (HU distributions were determined from each chest slice and from the

  20. A cell wall protein-based vaccine candidate induce protective immune response against Sporothrix schenckii infection.

    Science.gov (United States)

    Portuondo, Deivys Leandro; Batista-Duharte, Alexander; Ferreira, Lucas Souza; Martínez, Damiana Téllez; Polesi, Marisa Campos; Duarte, Roberta Aparecida; de Paula E Silva, Ana Carolina Alves; Marcos, Caroline Maria; Almeida, Ana Marisa Fusco de; Carlos, Iracilda Zeppone

    2016-02-01

    Sporotrichosis is a subcutaneous mycosis caused by several closely related thermo-dimorphic fungi of the Sporothrix schenckii species complex, affecting humans and other mammals. In the last few years, new strategies have been proposed for controlling sporotrichosis owning to concerns about its growing incidence in humans, cats, and dogs in Brazil, as well as the toxicity and limited efficacy of conventional antifungal drugs. In this study, we assessed the immunogenicity and protective properties of two aluminum hydroxide (AH)-adsorbed S. schenckii cell wall protein (ssCWP)-based vaccine formulations in a mouse model of systemic S. schenckii infection. Fractioning by SDS-PAGE revealed nine protein bands, two of which were functionally characterized: a 44kDa peptide hydrolase and a 47kDa enolase, which was predicted to be an adhesin. Sera from immunized mice recognized the 47kDa enolase and another unidentified 71kDa protein, whereas serum from S. schenckii-infected mice recognized both these proteins plus another unidentified 9.4kDa protein. Furthermore, opsonization with the anti-ssCWP sera led to markedly increased phagocytosis and was able to strongly inhibit the fungus' adhesion to fibroblasts. Immunization with the higher-dose AH-adjuvanted formulation led to increased ex vivo release of IL-12, IFN-γ, IL-4, and IL-17, whereas only IL-12 and IFN-γ were induced by the higher-dose non-adjuvanted formulation. Lastly, passive transference of the higher-dose AH-adjuvanted formulation's anti-ssCWP serum was able to afford in vivo protection in a subsequent challenge with S. schenckii, becoming a viable vaccine candidate for further testing. Copyright © 2015 Elsevier GmbH. All rights reserved.

  1. A chimeric protein-based malaria vaccine candidate induces robust T cell responses against Plasmodium vivax MSP119.

    Science.gov (United States)

    Fonseca, Jairo Andres; Cabrera-Mora, Monica; Singh, Balwan; Oliveira-Ferreira, Joseli; da Costa Lima-Junior, Josué; Calvo-Calle, J Mauricio; Lozano, Jose Manuel; Moreno, Alberto

    2016-10-06

    The most widespread Plasmodium species, Plasmodium vivax, poses a significant public health threat. An effective vaccine is needed to reduce global malaria burden. Of the erythrocytic stage vaccine candidates, the 19 kDa fragment of the P. vivax Merozoite Surface Protein 1 (PvMSP119) is one of the most promising. Our group has previously defined several promiscuous T helper epitopes within the PvMSP1 protein, with features that allow them to bind multiple MHC class II alleles. We describe here a P. vivax recombinant modular chimera based on MSP1 (PvRMC-MSP1) that includes defined T cell epitopes genetically fused to PvMSP119. This vaccine candidate preserved structural elements of the native PvMSP119 and elicited cytophilic antibody responses, and CD4+ and CD8+ T cells capable of recognizing PvMSP119. Although CD8+ T cells that recognize blood stage antigens have been reported to control blood infection, CD8+ T cell responses induced by P. falciparum or P. vivax vaccine candidates based on MSP119 have not been reported. To our knowledge, this is the first time a protein based subunit vaccine has been able to induce CD8+ T cell against PvMSP119. The PvRMC-MSP1 protein was also recognized by naturally acquired antibodies from individuals living in malaria endemic areas with an antibody profile associated with protection from infection. These features make PvRMC-MSP1 a promising vaccine candidate.

  2. CONSTRUCTION OF REGULAR LDPC LIKE CODES BASED ON FULL RANK CODES AND THEIR ITERATIVE DECODING USING A PARITY CHECK TREE

    Directory of Open Access Journals (Sweden)

    H. Prashantha Kumar

    2011-09-01

    Full Text Available Low density parity check (LDPC codes are capacity-approaching codes, which means that practical constructions exist that allow the noise threshold to be set very close to the theoretical Shannon limit for a memory less channel. LDPC codes are finding increasing use in applications like LTE-Networks, digital television, high density data storage systems, deep space communication systems etc. Several algebraic and combinatorial methods are available for constructing LDPC codes. In this paper we discuss a novel low complexity algebraic method for constructing regular LDPC like codes derived from full rank codes. We demonstrate that by employing these codes over AWGN channels, coding gains in excess of 2dB over un-coded systems can be realized when soft iterative decoding using a parity check tree is employed.

  3. Rankings Methodology Hurts Public Institutions

    Science.gov (United States)

    Van Der Werf, Martin

    2007-01-01

    In the 1980s, when the "U.S. News & World Report" rankings of colleges were based solely on reputation, the nation's public universities were well represented at the top. However, as soon as the magazine began including its "measures of excellence," statistics intended to define quality, public universities nearly disappeared from the top. As the…

  4. 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

  5. Using a Candidate Gene-Based Genetic Linkage Map to Identify QTL for Winter Survival in Perennial Ryegrass.

    Directory of Open Access Journals (Sweden)

    Cristiana Paina

    Full Text Available Important agronomical traits in perennial ryegrass (Lolium perenne breeding programs such as winter survival and heading date, are quantitative traits that are generally controlled by multiple loci. Individually, these loci have relatively small effects. The aim of this study was to develop a candidate gene based Illumina GoldenGate 1,536-plex assay, containing single nucleotide polymorphism markers designed from transcripts involved in response to cold acclimation, vernalization, and induction of flowering. The assay was used to genotype a mapping population that we have also phenotyped for winter survival to complement the heading date trait previously mapped in this population. A positive correlation was observed between strong vernalization requirement and winter survival, and some QTL for winter survival and heading date overlapped on the genetic map. Candidate genes were located in clusters along the genetic map, some of which co-localized with QTL for winter survival and heading date. These clusters of candidate genes may be used in candidate gene based association studies to identify alleles associated with winter survival and heading date.

  6. Ranking in Swiss system chess team tournaments

    OpenAIRE

    Csató, László

    2015-01-01

    The paper uses paired comparison-based scoring procedures for ranking the participants of a Swiss system chess team tournament. We present the main challenges of ranking in Swiss system, the features of individual and team competitions as well as the failures of official lexicographical orders. The tournament is represented as a ranking problem, our model is discussed with respect to the properties of the score, generalized row sum and least squares methods. The proposed procedure is illustra...

  7. A universal rank-size law

    CERN Document Server

    Ausloos, Marcel

    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.

  8. Candidate lesion-based criteria for defining a positive sacroiliac joint MRI in two cohorts of patients with axial spondyloarthritis

    DEFF Research Database (Denmark)

    Weber, Ulrich; Østergaard, Mikkel; Lambert, Robert G W

    2015-01-01

    OBJECTIVE: To determine candidate lesion-based criteria for a positive sacroiliac joint (SIJ) MRI based on bone marrow oedema (BMO) and/or erosion in non-radiographic axial spondyloarthritis (nr-axSpA); to compare the performance of lesion-based criteria with global evaluation by expert readers...... were associated with comparably high sensitivity to global assessment without affecting specificity. These combined criteria showed both higher sensitivity and specificity than the ASAS definition. CONCLUSIONS: Lesion-based criteria for a positive SIJ MRI based on both BMO and/or erosion performed best...

  9. 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.

  10. 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.

  11. University ranking methodologies. An interview with Ben Sowter about the Quacquarelli Symonds World University Ranking

    Directory of Open Access Journals (Sweden)

    Alberto Baccini

    2015-10-01

    Full Text Available University rankings represent a controversial issue in the debate about higher education policy. One of the best known university ranking is the Quacquarelli Symonds World University Rankings (QS, published annually since 2004 by Quacquarelli Symonds ltd, a company founded in 1990 and headquartered in London. QS provides a ranking based on a score calculated by weighting six different indicators. The 2015 edition, published in October 2015, introduced major methodological innovations and, as a consequence, many universities worldwide underwent major changes of their scores and ranks. Ben Sowter, head of division of intelligence unit of Quacquarelli Symonds, responds to 15 questions about the new QS methodology.

  12. 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.

  13. Identification of putative vaccine candidates against Helicobacter pylori exploiting exoproteome and secretome: a reverse vaccinology based approach.

    Science.gov (United States)

    Naz, Anam; Awan, Faryal Mehwish; Obaid, Ayesha; Muhammad, Syed Aun; Paracha, Rehan Zafar; Ahmad, Jamil; Ali, Amjad

    2015-06-01

    Helicobacter pylori (H. pylori) is an important pathogen associated with diverse gastric disorders ranging from peptic ulcer to malignancy. It has also been recognized by the World Health Organization (WHO) as class I carcinogen. Conventional treatment regimens for H. pylori seem to be ineffective, possibly due to antibiotic resistance mechanisms acquired by the pathogen. In this study we have successfully employed a reverse vaccinology approach to predict the potential vaccine candidates against H. pylori. The predicted potential vaccine candidates include vacA, babA, sabA, fecA and omp16. Host-pathogen interactions analysis elaborated their direct or indirect role in the specific signaling pathways including epithelial cell polarity, metabolism, secretion system and transport. Furthermore, surface-exposed antigenic epitopes were predicted and analyzed for conservation among 39 complete genomes of H. pylori (Genbank) for all the candidate proteins. These epitopes may serve as a base for the development of broad spectrum peptide or multi-component vaccines against H. pylori. We also believe that the proposed pipeline can be extended to other pathogens and for the identification of novel candidates for the development of effective vaccines. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Fully Pipelined Parallel Architecture for Candidate Block and Pixel-Subsampling-Based Motion Estimation

    Directory of Open Access Journals (Sweden)

    Reeba Korah

    2008-01-01

    Full Text Available This paper presents a low power and high speed architecture for motion estimation with Candidate Block and Pixel Subsampling (CBPS Algorithm. Coarse-to-fine search approach is employed to find the motion vector so that the local minima problem is totally eliminated. Pixel subsampling is performed in the selected candidate blocks which significantly reduces computational cost with low quality degradation. The architecture developed is a fully pipelined parallel design with 9 processing elements. Two different methods are deployed to reduce the power consumption, parallel and pipelined implementation and parallel accessing to memory. For processing 30 CIF frames per second our architecture requires a clock frequency of 4.5 MHz.

  15. Characterization nanoparticles-based vaccines and vaccine candidates: a Transmission Electron Microscopy study

    Directory of Open Access Journals (Sweden)

    I. Menéndez I

    2016-05-01

    Full Text Available Transmission Electron Microscopy (TEM is a valuable tool for the biotech industry. This paper summarizes some of the contributions of MET in the characterization of the recombinant antigens are part of vaccines or vaccine candidates obtained in the CIGB. It mentions the use of complementary techniques MET (Negative staining, and immunoelectron that enhance visualization and ultrastructural characterization of the recombinant proteins obtained by Genetic Engineering.

  16. Identification of Novel Potential Vaccine Candidates against Tuberculosis Based on Reverse Vaccinology

    Directory of Open Access Journals (Sweden)

    Gloria P. Monterrubio-López

    2015-01-01

    Full Text Available Tuberculosis (TB is a chronic infectious disease, considered as the second leading cause of death worldwide, caused by Mycobacterium tuberculosis. The limited efficacy of the bacillus Calmette-Guérin (BCG vaccine against pulmonary TB and the emergence of multidrug-resistant TB warrants the need for more efficacious vaccines. Reverse vaccinology uses the entire proteome of a pathogen to select the best vaccine antigens by in silico approaches. M. tuberculosis H37Rv proteome was analyzed with NERVE (New Enhanced Reverse Vaccinology Environment prediction software to identify potential vaccine targets; these 331 proteins were further analyzed with VaxiJen for the determination of their antigenicity value. Only candidates with values ≥0.5 of antigenicity and 50% of adhesin probability and without homology with human proteins or transmembrane regions were selected, resulting in 73 antigens. These proteins were grouped by families in seven groups and analyzed by amino acid sequence alignments, selecting 16 representative proteins. For each candidate, a search of the literature and protein analysis with different bioinformatics tools, as well as a simulation of the immune response, was conducted. Finally, we selected six novel vaccine candidates, EsxL, PE26, PPE65, PE_PGRS49, PBP1, and Erp, from M. tuberculosis that can be used to improve or design new TB vaccines.

  17. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  18. Nicotinic acetylcholine receptor β2 subunit gene implicated in a systems-based candidate gene study of smoking cessation

    OpenAIRE

    Conti, DV; Lee, W.; D. Li; Liu, J.; Van Den Berg, D.; Thomas, PD; Bergen, AW; Swan, GE; Tyndale, RF; Benowitz, NL; Lerman, C

    2008-01-01

    Although the efficacy of pharmacotherapy for tobacco dependence has been previously demonstrated, there is substantial variability among individuals in treatment response. We performed a systems-based candidate gene study of 1295 single nucleotide polymorphisms (SNPs) in 58 genes within the neuronal nicotinic receptor and dopamine systems to investigate their role in smoking cessation in a bupropion placebo-controlled randomized clinical trial. Putative functional variants were supplemented w...

  19. Academic rankings: an approach to rank portuguese universities Rankings académicos: un abordaje para clasificar las universidades portuguesas Rankings acadêmicos: uma abordagem ao ranking das universidades portuguesas

    Directory of Open Access Journals (Sweden)

    Pedro Bernardino

    2010-03-01

    Full Text Available The academic rankings are a controversial subject in higher education. However, despite all the criticism, academic rankings are here to stay and more and more different stakeholders use rankings to obtain information about the institutions' performance. The two most well-known rankings, The Times and the Shanghai Jiao Tong University rankings have different methodologies. The Times ranking is based on peer review, whereas the Shanghai ranking has only quantitative indicators and is mainly based on research outputs. In Germany, the CHE ranking uses a different methodology from the traditional rankings, allowing the users to choose criteria and weights. The Portuguese higher education institutions are performing below their European peers, and the Government believes that an academic ranking could improve both performance and competitiveness between institutions. The purpose of this paper is to analyse the advantages and problems of academic rankings and provide guidance to a new Portuguese ranking.Los rankings académicos son un tema muy contradictorio en la enseñanza superior. Todavía, además de todas las críticas los rankings están para quedarse entre nosotros. Y cada vez más, diferentes stakeholders utilizan los rankings para obtener información sobre el desempeño de las instituciones. Dos de los rankings más conocidos, el The Times y el ranking de la universidad de Shangai Jiao Tong tienen métodos distintos. El The Times se basa en la opinión de expertos mientras el ranking de la universidad de Shangai presenta solamente indicadores cuantitativos y mayoritariamente basados en los resultados de actividades de investigación. En Alemania el ranking CHE usa un método distinto permitiendo al utilizador elegir los criterios y su importancia. Las instituciones de enseñanza superior portuguesas tienen un desempeño abajo de las europeas y el gobierno cree que un ranking académico podría contribuir para mejorar su desempeño y

  20. Candidate genes and genetic architecture of symbiotic and agronomic traits revealed by whole-genome, sequence-based association genetics in Medicago truncatula.

    Directory of Open Access Journals (Sweden)

    John Stanton-Geddes

    Full Text Available Genome-wide association study (GWAS has revolutionized the search for the genetic basis of complex traits. To date, GWAS have generally relied on relatively sparse sampling of nucleotide diversity, which is likely to bias results by preferentially sampling high-frequency SNPs not in complete linkage disequilibrium (LD with causative SNPs. To avoid these limitations we conducted GWAS with >6 million SNPs identified by sequencing the genomes of 226 accessions of the model legume Medicago truncatula. We used these data to identify candidate genes and the genetic architecture underlying phenotypic variation in plant height, trichome density, flowering time, and nodulation. The characteristics of candidate SNPs differed among traits, with candidates for flowering time and trichome density in distinct clusters of high linkage disequilibrium (LD and the minor allele frequencies (MAF of candidates underlying variation in flowering time and height significantly greater than MAF of candidates underlying variation in other traits. Candidate SNPs tagged several characterized genes including nodulation related genes SERK2, MtnodGRP3, MtMMPL1, NFP, CaML3, MtnodGRP3A and flowering time gene MtFD as well as uncharacterized genes that become candidates for further molecular characterization. By comparing sequence-based candidates to candidates identified by in silico 250K SNP arrays, we provide an empirical example of how reliance on even high-density reduced representation genomic makers can bias GWAS results. Depending on the trait, only 30-70% of the top 20 in silico array candidates were within 1 kb of sequence-based candidates. Moreover, the sequence-based candidates tagged by array candidates were heavily biased towards common variants; these comparisons underscore the need for caution when interpreting results from GWAS conducted with sparsely covered genomes.

  1. Biplots in Reduced-Rank Regression

    NARCIS (Netherlands)

    Braak, ter C.J.F.; Looman, C.W.N.

    1994-01-01

    Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced-rank regression. Reduced-rank regression combines multiple regression and principal

  2. PageRank versatility analysis of multilayer modality-based network for exploring the evolution of oil-water slug flow.

    Science.gov (United States)

    Gao, Zhong-Ke; Dang, Wei-Dong; Li, Shan; Yang, Yu-Xuan; Wang, Hong-Tao; Sheng, Jing-Ran; Wang, Xiao-Fan

    2017-07-14

    Numerous irregular flow structures exist in the complicated multiphase flow and result in lots of disparate spatial dynamical flow behaviors. The vertical oil-water slug flow continually attracts plenty of research interests on account of its significant importance. Based on the spatial transient flow information acquired through our designed double-layer distributed-sector conductance sensor, we construct multilayer modality-based network to encode the intricate spatial flow behavior. Particularly, we calculate the PageRank versatility and multilayer weighted clustering coefficient to quantitatively explore the inferred multilayer modality-based networks. Our analysis allows characterizing the complicated evolution of oil-water slug flow, from the opening formation of oil slugs, to the succedent inter-collision and coalescence among oil slugs, and then to the dispersed oil bubbles. These properties render our developed method particularly powerful for mining the essential flow features from the multilayer sensor measurements.

  3. Asset ranking manager (ranking index of components)

    Energy Technology Data Exchange (ETDEWEB)

    Maloney, S.M.; Engle, A.M.; Morgan, T.A. [Applied Reliability, Maracor Software and Engineering (United States)

    2004-07-01

    The Ranking Index of Components (RIC) is an Asset Reliability Manager (ARM), which itself is a Web Enabled front end where plant database information fields from several disparate databases are combined. That information is used to create a specific weighted number (Ranking Index) relating to that components health and risk to the site. The higher the number, the higher priority that any work associated with that component receives. ARM provides site Engineering, Maintenance and Work Control personnel with a composite real time - (current condition) look at the components 'risk of not working' to the plant. Information is extracted from the existing Computerized Maintenance management System (CMMS) and specific site applications and processed nightly. ARM helps to ensure that the most important work is placed into the workweeks and the non value added work is either deferred, frequency changed or deleted. This information is on the web, updated each night, and available for all employees to use. This effort assists the work management specialist when allocating limited resources to the most important work. The use of this tool has maximized resource usage, performing the most critical work with available resources. The ARM numbers are valued inputs into work scoping for the workweek managers. System and Component Engineers are using ARM to identify the components that are at 'risk of failure' and therefore should be placed into the appropriate work week schedule.

  4. Fast-Solving Quasi-Optimal LS-S$³$VM Based on an Extended Candidate Set.

    Science.gov (United States)

    Ma, Yuefeng; Liang, Xun; Kwok, James T; Li, Jianping; Zhou, Xiaoping; Zhang, Haiyan

    2017-02-14

    The semisupervised least squares support vector machine (LS-S³VM) is an important enhancement of least squares support vector machines in semisupervised learning. Given that most data collected from the real world are without labels, semisupervised approaches are more applicable than standard supervised approaches. Although a few training methods for LS-S³VM exist, the problem of deriving the optimal decision hyperplane efficiently and effectually has not been solved. In this paper, a fully weighted model of LS-S³VM is proposed, and a simple integer programming (IP) model is introduced through an equivalent transformation to solve the model. Based on the distances between the unlabeled data and the decision hyperplane, a new indicator is designed to represent the possibility that the label of an unlabeled datum should be reversed in each iteration during training. Using the indicator, we construct an extended candidate set consisting of the indices of unlabeled data with high possibilities, which integrates more information from unlabeled data. Our algorithm is degenerated into a special scenario of the previous algorithm when the extended candidate set is reduced into a set with only one element. Two strategies are utilized to determine the descent directions based on the extended candidate set. Furthermore, we developed a novel method for locating a good starting point based on the properties of the equivalent IP model. Combined with the extended candidate set and the carefully computed starting point, a fast algorithm to solve LS-S³VM quasi-optimally is proposed. The choice of quasi-optimal solutions results in low computational cost and avoidance of overfitting. Experiments show that our algorithm equipped with the two designed strategies is more effective than other algorithms in at least one of the following three aspects: 1) computational complexity; 2) generalization ability; and 3) flexibility. However, our algorithm and other algorithms have similar

  5. 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.

  6. 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.

  7. Ranking of Rankings: Benchmarking Twenty-Five Higher Education Ranking Systems in Europe

    Science.gov (United States)

    Stolz, Ingo; Hendel, Darwin D.; Horn, Aaron S.

    2010-01-01

    The purpose of this study is to evaluate the ranking practices of 25 European higher education ranking systems (HERSs). Ranking practices were assessed with 14 quantitative measures derived from the Berlin Principles on Ranking of Higher Education Institutions (BPs). HERSs were then ranked according to their degree of congruence with the BPs.…

  8. Extending the interview to all medical school candidates--Computer-Based Multiple Sample Evaluation of Noncognitive Skills (CMSENS).

    Science.gov (United States)

    Dore, Kelly L; Reiter, Harold I; Eva, Kevin W; Krueger, Sharyn; Scriven, Edward; Siu, Eric; Hilsden, Shannon; Thomas, Jennifer; Norman, Geoffrey R

    2009-10-01

    Most medical school candidates are excluded without benefit of noncognitive skills assessment. Is development of a noncognitive preinterview screening test that correlates with the well-validated Multiple Mini-Interview (MMI) possible? Study 1: 110 medical school candidates completed MMI and Computer-based Multiple Sample Evaluation of Noncognitive Skills (CMSENS)-eight 1-minute video-based scenarios and four self-descriptive questions, with short-answer-response format. Seventy-eight responses were audiotaped, 32 typewritten; all were scored by two independent raters. Study 2: 167 candidates completed CMSENS-eight videos, six self-descriptive questions, typewritten responses only, scored by two raters; 88 of 167 underwent the MMI. Results for overall test generalizability, interrater reliability, and correlation with MMI, respectively, were, for Study 1, audio-responders: 0.86, 0.82, 0.15; typewritten-responders: 0.72, 0.81, 0.51; and for Study 2, 0.83, 0.95, 0.46 (correlation with disattenuation was 0.60). Strong psychometric properties, including MMI correlation, of CMSENS warrant investigation into future widespread implementation as a preinterview noncognitive screening test.

  9. An Investigation of Immunogenicity of Chitosan-Based Botulinum Neurotoxin E Binding Domain Recombinant Candidate Vaccine via Mucosal Route

    Directory of Open Access Journals (Sweden)

    Mohammad Javad Bagheripour

    2017-01-01

    Full Text Available Background and Objectives: Botulism syndrome is caused by serotypes A-G of neurotoxins of Clostridium genus. Neurotoxin binding domain is an appropriate vaccine candidate due to its immunogenic activity. In this study, the immunogenicity of chitosan-based botulinum neurotoxin E binding domain recombinant candidate vaccine was investigated via mucosal route of administration. Methods: In this experimental study, chitosan nanoparticles containing rBoNT/E protein were synthesized by ionic gelation method and were administered orally and intranasally to mice. After each administration, IgG antibody titer was measured by ELISA method. Finally, all groups were challenged with active botulinum neurotoxin type E. Data were analyzed using Duncan and repeated ANOVA tests. The significance level was considered as p0.05, even intranasal route reduced the immunogenicity.

  10. A highly pathogenic porcine reproductive and respiratory syndrome virus candidate vaccine based on Japanese encephalitis virus replicon system.

    Science.gov (United States)

    Hu, Pingsheng; Chen, Xiaoming; Huang, Lihong; Liu, Shukai; Zang, Fuyu; Xing, Jinchao; Zhang, Youyue; Liang, Jiaqi; Zhang, Guihong; Liao, Ming; Qi, Wenbao

    2017-01-01

    In the swine industry, porcine reproductive and respiratory syndrome (PRRS) is a highly contagious disease which causes heavy economic losses worldwide. Effective prevention and disease control is an important issue. In this study, we described the construction of a Japanese encephalitis virus (JEV) DNA-based replicon with a cytomegalovirus (CMV) promoter based on the genome of Japanese encephalitis live vaccine virus SA14-14-2, which is capable of offering a potentially novel way to develop and produce vaccines against a major pathogen of global health. This JEV DNA-based replicon contains a large deletion in the structural genes (C-prM-E). A PRRSV GP5/M was inserted into the deletion position of JEV DNA-based replicons to develop a chimeric replicon vaccine candidate for PRRSV. The results showed that BALB/c mice models with the replicon vaccines pJEV-REP-G-2A-M-IRES and pJEV-REP-G-2A-M stimulated antibody responses and induced a cellular immune response. Analysis of ELSA data showed that vaccination with the replicon vaccine expressing GP5/M induced a better antibodies response than traditional DNA vaccines. Therefore, the results suggested that this ectopic expression system based on JEV DNA-based replicons may represent a useful molecular platform for various biological applications, and the JEV DNA-based replicons expressing GP5/M can be further developed into a novel, safe vaccine candidate for PRRS.

  11. Imputation-based analysis of association studies: candidate regions and quantitative traits.

    Directory of Open Access Journals (Sweden)

    Bertrand Servin

    2007-07-01

    Full Text Available We introduce a new framework for the analysis of association studies, designed to allow untyped variants to be more effectively and directly tested for association with a phenotype. The idea is to combine knowledge on patterns of correlation among SNPs (e.g., from the International HapMap project or resequencing data in a candidate region of interest with genotype data at tag SNPs collected on a phenotyped study sample, to estimate ("impute" unmeasured genotypes, and then assess association between the phenotype and these estimated genotypes. Compared with standard single-SNP tests, this approach results in increased power to detect association, even in cases in which the causal variant is typed, with the greatest gain occurring when multiple causal variants are present. It also provides more interpretable explanations for observed associations, including assessing, for each SNP, the strength of the evidence that it (rather than another correlated SNP is causal. Although we focus on association studies with quantitative phenotype and a relatively restricted region (e.g., a candidate gene, the framework is applicable and computationally practical for whole genome association studies. Methods described here are implemented in a software package, Bim-Bam, available from the Stephens Lab website http://stephenslab.uchicago.edu/software.html.

  12. Finding candidate drugs for hepatitis C based on chemical-chemical and chemical-protein interactions.

    Directory of Open Access Journals (Sweden)

    Lei Chen

    Full Text Available Hepatitis C virus (HCV is an infectious virus that can cause serious illnesses. Only a few drugs have been reported to effectively treat hepatitis C. To have greater diversity in drug choice and better treatment options, it is necessary to develop more drugs to treat the infection. However, it is time-consuming and expensive to discover candidate drugs using experimental methods, and computational methods may complement experimental approaches as a preliminary filtering process. This type of approach was proposed by using known chemical-chemical interactions to extract interactive compounds with three known drug compounds of HCV, and the probabilities of these drug compounds being able to treat hepatitis C were calculated using chemical-protein interactions between the interactive compounds and HCV target genes. Moreover, the randomization test and expectation-maximization (EM algorithm were both employed to exclude false discoveries. Analysis of the selected compounds, including acyclovir and ganciclovir, indicated that some of these compounds had potential to treat the HCV. Hopefully, this proposed method could provide new insights into the discovery of candidate drugs for the treatment of HCV and other diseases.

  13. Optimal Combination of Classification Algorithms and Feature Ranking Methods for Object-Based Classification of Submeter Resolution Z/I-Imaging DMC Imagery

    Directory of Open Access Journals (Sweden)

    Fulgencio Cánovas-García

    2015-04-01

    Full Text Available Object-based image analysis allows several different features to be calculated for the resulting objects. However, a large number of features means longer computing times and might even result in a loss of classification accuracy. In this study, we use four feature ranking methods (maximum correlation, average correlation, Jeffries–Matusita distance and mean decrease in the Gini index and five classification algorithms (linear discriminant analysis, naive Bayes, weighted k-nearest neighbors, support vector machines and random forest. The objective is to discover the optimal algorithm and feature subset to maximize accuracy when classifying a set of 1,076,937 objects, produced by the prior segmentation of a 0.45-m resolution multispectral image, with 356 features calculated on each object. The study area is both large (9070 ha and diverse, which increases the possibility to generalize the results. The mean decrease in the Gini index was found to be the feature ranking method that provided highest accuracy for all of the classification algorithms. In addition, support vector machines and random forest obtained the highest accuracy in the classification, both using their default parameters. This is a useful result that could be taken into account in the processing of high-resolution images in large and diverse areas to obtain a land cover classification.

  14. 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.

  15. Mucus can change the permeation rank order of drug candidates

    DEFF Research Database (Denmark)

    Hagesaether, Ellen; Christiansen, Elisabeth; Due-Hansen, Maria Elisabeth

    2013-01-01

    The aim of the study was to test the effect of mucus on the permeability of newly developed structurally related free fatty acid receptor 1-agonists TUG-488, TUG-499 and TUG-424, which were compared to the more hydrophilic ketoprofen and the more hydrophobic testosterone as reference drugs...

  16. 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.

  17. 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.

  18. 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....

  19. ARWU vs. Alternative ARWU Ranking: What are the Consequences for Lower Ranked Universities?

    Directory of Open Access Journals (Sweden)

    Milica Maričić

    2017-05-01

    Full Text Available The ARWU ranking has been a source of academic debate since its development in 2003, but the same does not account for the Alternative ARWU ranking. Namely, the Alternative ARWU ranking attempts to reduce the influence of the prestigious indicators Alumni and Award which are based on the number of received Nobel Prizes and Fields Medals by alumni or university staff. However, the consequences of the reduction of the two indicators have not been scrutinized in detail. Therefore, we propose a statistical approach to the comparison of the two rankings and an in-depth analysis of the Alternative ARWU groups. The obtained results, which are based on the official data, can provide new insights into the nature of the Alternative ARWU ranking. The presented approach might initiate further research on the Alternative ARWU ranking and on the impact of university ranking’s list length. JEL Classification: C10, C38, I23

  20. Administrative Process and Criteria Ranking for Drug Entering Health Insurance List in Iran-TOPSIS-Based Consensus Model

    National Research Council Canada - National Science Library

    Viyanchi, Amir; Rajabzadeh Ghatari, Ali; Rasekh, Hamid Reza; SafiKhani, HamidReza

    2016-01-01

    The purposes of our study were to identify a drug entry process, collect, and prioritize criteria for selecting drugs for the list of basic health insurance commitments to prepare an "evidence based...

  1. Reliability of journal impact factor rankings

    Science.gov (United States)

    Greenwood, Darren C

    2007-01-01

    Background Journal impact factors and their ranks are used widely by journals, researchers, and research assessment exercises. Methods Based on citations to journals in research and experimental medicine in 2005, Bayesian Markov chain Monte Carlo methods were used to estimate the uncertainty associated with these journal performance indicators. Results Intervals representing plausible ranges of values for journal impact factor ranks indicated that most journals cannot be ranked with great precision. Only the top and bottom few journals could place any confidence in their rank position. Intervals were wider and overlapping for most journals. Conclusion Decisions placed on journal impact factors are potentially misleading where the uncertainty associated with the measure is ignored. This article proposes that caution should be exercised in the interpretation of journal impact factors and their ranks, and specifically that a measure of uncertainty should be routinely presented alongside the point estimate. PMID:18005435

  2. Reliability of journal impact factor rankings

    Directory of Open Access Journals (Sweden)

    Greenwood Darren C

    2007-11-01

    Full Text Available Abstract Background Journal impact factors and their ranks are used widely by journals, researchers, and research assessment exercises. Methods Based on citations to journals in research and experimental medicine in 2005, Bayesian Markov chain Monte Carlo methods were used to estimate the uncertainty associated with these journal performance indicators. Results Intervals representing plausible ranges of values for journal impact factor ranks indicated that most journals cannot be ranked with great precision. Only the top and bottom few journals could place any confidence in their rank position. Intervals were wider and overlapping for most journals. Conclusion Decisions placed on journal impact factors are potentially misleading where the uncertainty associated with the measure is ignored. This article proposes that caution should be exercised in the interpretation of journal impact factors and their ranks, and specifically that a measure of uncertainty should be routinely presented alongside the point estimate.

  3. Cointegration rank testing under conditional heteroskedasticity

    DEFF Research Database (Denmark)

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

    2010-01-01

    (martingale difference) innovations. We first demonstrate that the limiting null distributions of the rank statistics coincide with those derived by previous authors who assume either independent and identically distributed (i.i.d.) or (strict and covariance) stationary martingale difference innovations. We...... then propose wild bootstrap implementations of the cointegrating rank tests and demonstrate that the associated bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show that the same is also true of the corresponding rank tests based on the i.......i.d. bootstrap of Swensen (2006, Econometrica 74, 1699-1714). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap, it preserves in the resampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence suggests that...

  4. Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

    Directory of Open Access Journals (Sweden)

    Guohua Wang

    2015-12-01

    Full Text Available Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

  5. 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...

  6. Application of the Simplified Dow Chemical Company Relative Ranking Hazard Assessment Method for Air Combat Command Bases

    Science.gov (United States)

    1993-09-01

    and Operability Studies { HAZOP ) . Both of these methods use systematic ways of considering the consequences of unexpected events. In the What-If Method...problems and all probable consequences, assigning a probability of hazard to each consequence based on the probability of occurrence. (Davis 1987:50) HAZOP

  7. Characterizing Microseismicity at the Newberry Volcano Geothermal Site using PageRank

    Science.gov (United States)

    Aguiar, A. C.; Myers, S. C.

    2015-12-01

    The Newberry Volcano, within the Deschutes National Forest in Oregon, has been designated as a candidate site for the Department of Energy's Frontier Observatory for Research in Geothermal Energy (FORGE) program. This site was stimulated using high-pressure fluid injection during the fall of 2012, which generated several hundred microseismic events. Exploring the spatial and temporal development of microseismicity is key to understanding how subsurface stimulation modifies stress, fractures rock, and increases permeability. We analyze Newberry seismicity using both surface and borehole seismometers from the AltaRock and LLNL seismic networks. For our analysis we adapt PageRank, Google's initial search algorithm, to evaluate microseismicity during the 2012 stimulation. PageRank is a measure of connectivity, where higher ranking represents highly connected windows. In seismic applications connectivity is measured by the cross correlation of 2 time windows recorded on a common seismic station and channel. Aguiar and Beroza (2014) used PageRank based on cross correlation to detect low-frequency earthquakes, which are highly repetitive but difficult to detect. We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes, including the identification of signals that are connected to the largest number of other signals. We then use this information to create signal families and compare PageRank families to the spatial and temporal proximity of associated earthquakes. Studying signal PageRank will potentially allow us to efficiently group earthquakes with similar physical characteristics, such as focal mechanisms and stress drop. Our ultimate goal is to determine whether changes in the state of stress and/or changes in the generation of subsurface fracture networks can be detected using PageRank topology. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under

  8. Web document ranking via active learning and kernel principal component analysis

    Science.gov (United States)

    Cai, Fei; Chen, Honghui; Shu, Zhen

    2015-09-01

    Web document ranking arises in many information retrieval (IR) applications, such as the search engine, recommendation system and online advertising. A challenging issue is how to select the representative query-document pairs and informative features as well for better learning and exploring new ranking models to produce an acceptable ranking list of candidate documents of each query. In this study, we propose an active sampling (AS) plus kernel principal component analysis (KPCA) based ranking model, viz. AS-KPCA Regression, to study the document ranking for a retrieval system, i.e. how to choose the representative query-document pairs and features for learning. More precisely, we fill those documents gradually into the training set by AS such that each of which will incur the highest expected DCG loss if unselected. Then, the KPCA is performed via projecting the selected query-document pairs onto p-principal components in the feature space to complete the regression. Hence, we can cut down the computational overhead and depress the impact incurred by noise simultaneously. To the best of our knowledge, we are the first to perform the document ranking via dimension reductions in two dimensions, namely, the number of documents and features simultaneously. Our experiments demonstrate that the performance of our approach is better than that of the baseline methods on the public LETOR 4.0 datasets. Our approach brings an improvement against RankBoost as well as other baselines near 20% in terms of MAP metric and less improvements using P@K and NDCG@K, respectively. Moreover, our approach is particularly suitable for document ranking on the noisy dataset in practice.

  9. The (w)hole survey: An unbiased sample study of transition disk candidates based on Spitzer catalogs

    Science.gov (United States)

    van der Marel, N.; Verhaar, B. W.; van Terwisga, S.; Merín, B.; Herczeg, G.; Ligterink, N. F. W.; van Dishoeck, E. F.

    2016-08-01

    Understanding disk evolution and dissipation is essential for studies of planet formation. Transition disks, I.e., disks with large dust cavities and gaps, are promising candidates of active evolution. About two dozen candidates, selected by their spectral energy distribution (SED), have been confirmed to have dust cavities through millimeter interferometric imaging, but this sample is biased toward the brightest disks. The Spitzer surveys of nearby low-mass star-forming regions have resulted in more than 4000 young stellar objects. Using color criteria, we selected a sample of ~150 candidates and an additional 40 candidates and known transition disks from the literature. The Spitzer data were complemented by new observations at longer wavelengths, including new JCMT and APEX submillimeter photometry, and WISE and Herschel-PACS mid- and far-infrared photometry. Furthermore, optical spectroscopy was obtained and stellar types were derived for 85% of the sample, including information from the literature. The SEDs were fit to a grid of RADMC-3D disk models with a limited number of parameters: disk mass, inner disk mass, scale height and flaring, and disk cavity radius, where the latter is the main parameter of interest. About 72% of our targets possibly have dust cavities based on the SED. The derived cavity sizes are consistent with imaging/modeling results in the literature, where available. Trends are found with Ldisk over L∗ ratio and stellar mass and a possible connection with exoplanet orbital radii. A comparison with a previous study where color observables are used reveals large overlap between their category of planet-forming disks and our transition disks with cavities. A large number of the new transition disk candidates are suitable for follow-up observations with ALMA. Full Tables 4, 5, A.1-A.3, C.1, and D.1 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc

  10. A Plasmodium falciparum candidate vaccine based on a six-antigen polyprotein encoded by recombinant poxviruses.

    Science.gov (United States)

    Prieur, Eric; Gilbert, Sarah C; Schneider, Joerg; Moore, Anne C; Sheu, Eric G; Goonetilleke, Nilu; Robson, Kathryn J H; Hill, Adrian V S

    2004-01-06

    To generate broadly protective T cell responses more similar to those acquired after vaccination with radiation-attenuated Plasmodium falciparum sporozoites, we have constructed candidate subunit malaria vaccines expressing six preerythrocytic antigens linked together to produce a 3240-aa-long polyprotein (L3SEPTL). This polyprotein was expressed by a plasmid DNA vaccine vector (DNA) and by two attenuated poxvirus vectors, modified vaccinia virus Ankara (MVA) and fowlpox virus of the FP9 strain. MVAL3SEPTL boosted anti-thrombospondin-related adhesive protein (anti-TRAP) and anti-liver stage antigen 1 (anti-LSA1) CD8(+) T cell responses when primed by single antigen TRAP- or LSA1-expressing DNAs, respectively, but not by DNA-L3SEPTL. However, prime boost regimes involving two heterologous viral vectors expressing L3SEPTL induced a strong cellular response directed against an LSA1 peptide located in the C-terminal region of the polyprotein. Peptide-specific T cells secreted IFN-gamma and were cytotoxic. IFN-gamma-secreting T cells specific for each of the six antigens were induced after vaccination with L3SEPTL, supporting the use of polyprotein inserts to induce multispecific T cells against P. falciparum. The use of polyprotein constructs in nonreplicating poxviruses should broaden the target antigen range of vaccine-induced immunity and increase the number of potential epitopes available for immunogenetically diverse human populations.

  11. Synthesis and Characterization of Lipooligosaccharide-Based Conjugates as Vaccine Candidates for Moraxella (Branhamella) catarrhalis

    Science.gov (United States)

    Gu, Xin-Xing; Chen, Jing; Barenkamp, Stephen J.; Robbins, John B.; Tsai, Chao-Ming; Lim, David J.; Battey, James

    1998-01-01

    Moraxella (Branhamella) catarrhalis is an important cause of otitis media and sinusitis in children and of lower respiratory tract infections in adults. Lipooligosaccharide (LOS) is a major surface antigen of the bacterium and elicits bactericidal antibodies. Treatment of the LOS from strain ATCC 25238 with anhydrous hydrazine reduced its toxicity 20,000-fold, as assayed in the Limulus amebocyte lysate (LAL) test. The detoxified LOS (dLOS) was coupled to tetanus toxoid (TT) or high-molecular-weight proteins (HMP) from nontypeable Haemophilus influenzae through a linker of adipic acid dihydrazide to form dLOS-TT or dLOS-HMP. The molar ratios of dLOS to TT and HMP conjugates were 19:1 and 31:1, respectively. The antigenicity of the two conjugates was similar to that of the LOS, as determined by double immunodiffusion. Subcutaneous or intramuscular injection of both conjugates elicited a 50- to 100-fold rise in the geometric mean of immunoglobulin G (IgG) to the homologous LOS in mice after three injections and a 350- to 700-fold rise of anti-LOS IgG in rabbits after two injections. The immunogenicity of the conjugate was enhanced by formulation with monophosphoryl lipid A plus trehalose dimycolate. In rabbits, conjugate-induced antisera had complement-mediated bactericidal activity against the homologous strain and heterologous strains of M. catarrhalis. These results indicate that a detoxified LOS-protein conjugate is a candidate for immunization against M. catarrhalis diseases. PMID:9573066

  12. 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 ...

  13. Person Re-Identification by Iterative Re-Weighted Sparse Ranking.

    Science.gov (United States)

    Lisanti, Giuseppe; Masi, Iacopo; Bagdanov, Andrew D; Del Bimbo, Alberto

    2015-08-01

    In this paper we introduce a method for person re-identification based on discriminative, sparse basis expansions of targets in terms of a labeled gallery of known individuals. We propose an iterative extension to sparse discriminative classifiers capable of ranking many candidate targets. The approach makes use of soft- and hard- re-weighting to redistribute energy among the most relevant contributing elements and to ensure that the best candidates are ranked at each iteration. Our approach also leverages a novel visual descriptor which we show to be discriminative while remaining robust to pose and illumination variations. An extensive comparative evaluation is given demonstrating that our approach achieves state-of-the-art performance on single- and multi-shot person re-identification scenarios on the VIPeR, i-LIDS, ETHZ, and CAVIAR4REID datasets. The combination of our descriptor and iterative sparse basis expansion improves state-of-the-art rank-1 performance by six percentage points on VIPeR and by 20 on CAVIAR4REID compared to other methods with a single gallery image per person. With multiple gallery and probe images per person our approach improves by 17 percentage points the state-of-the-art on i-LIDS and by 72 on CAVIAR4REID at rank-1. The approach is also quite efficient, capable of single-shot person re-identification over galleries containing hundreds of individuals at about 30 re-identifications per second.

  14. Proteome scale census of major facilitator superfamily transporters in Trichoderma reesei using protein sequence and structure based classification enhanced ranking.

    Science.gov (United States)

    Chaudhary, Nitika; Kumari, Indu; Sandhu, Padmani; Ahmed, Mushtaq; Akhter, Yusuf

    2016-07-01

    Trichoderma spp. have been acknowledged as potent bio-control agents against microbial pathogens and also as plant growth promoters. Various secondary metabolites are attributed for these beneficial activities. Major facilitator superfamily (MFS) includes the large proportion of efflux-pumps which are linked with membrane transport of these secondary metabolites. We have carried out a proteome-wide identification of MFS transporters using protein sequence and structure based hierarchical method in Trichoderma reesei. 448 proteins out of 9115 were detected to carry transmembrane helices. MFS specific intragenic gene duplication and its context with transport function have been presented. Finally, using homology based techniques, domains and motifs of MFS families have been identified and utilized to classify them. From query dataset of 448 transmembrane proteins, 148 proteins are identified as potential MFS transporters. Sugar porter, drug: H(+) antiporter-1, monocarboxylate porter and anion: cation symporter emerged as major MFS families with 51, 35, 17 and 11 members respectively. Representative protein tertiary structures of these families are homology modeled for structure-function analysis. This study may help to understand the molecular basis of secretion and transport of agriculturally valuable secondary metabolites produced by these bio-control fungal agents which may be exploited in future for enhancing its biotechnological applications in eco-friendly sustainable development. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. 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.

  16. Phylogeography, salinity adaptations and metabolic potential of the Candidate Division KB1 Bacteria based on a partial single cell genome.

    Directory of Open Access Journals (Sweden)

    Lisa M Nigro

    2016-08-01

    Full Text Available Deep-sea hypersaline anoxic basins (DHABs and other hypersaline environments contain abundant and diverse microbial life that has adapted to these extreme conditions. The bacterial Candidate Division KB1 represents one of several uncultured groups that has been consistently observed in hypersaline microbial diversity studies. Here we report the phylogeography of KB1, its phylogenetic relationships to Candidate Division OP1 Bacteria, and its potential metabolic and osmotic stress adaptations based on a partial single cell amplified genome (SAG of KB1 from Orca Basin, the largest hypersaline seafloor brine basin in the Gulf of Mexico. Our results are consistent with the hypothesis – previously developed based on 14C incorporation experiments with mixed-species enrichments from Mediterranean seafloor brines - that KB1 has adapted its proteins to elevated intracellular salinity, but at the same time KB1 apparently imports glycine betaine; this compatible solute is potentially not limited to osmoregulation but could also serve as a carbon and energy source.

  17. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The fi…rst step consists in estimating the parame......We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The fi…rst step consists in estimating...... to control for stochastic trend estimation effects from the first step. The critical values of the tests proposed depend only on the number of common trends under the null, p - r, and on the interval of the cointegration degrees b allowed, but not on the true cointegration degree b0. Hence, no additional...

  18. Tsunami-HySEA: A GPU based model for the Italian candidate Tsunami Service Provider

    Science.gov (United States)

    Gonzalez Vida, Jose Manuel; Macias, Jorge; Castro, Manuel; de la Asuncion, Marc; Melini, Daniele; Romano, Fabrizio; Tonini, Roberto; Lorito, Stefano; Piatanesi, Alessio; Molinari, Irene

    2015-04-01

    Tsunami Service Providers (TSP), providing tsunami warnings in the framework of the systems coordinated by IOC/UNESCO worldwide, and other national tsunami warning centers, are striving to complement, or replace, decision matrices and pre-calculated tsunami scenario databases with FTRT (Faster Than Real Time) tsunami simulations. The aim is to increase the accuracy of tsunami forecast by assimilating the largest possible amount of data in quasi real time, and performing simulations in a few minutes wall-clock time, possibly including the coastal inundation stage. This strategy of direct real time computation, that could seem unfeasible a decade ago, it is now foreseeable thanks to the astonishingly recent increase in the computational power and bandwidth evolution of modern GPUs. The INGV in collaboration with the EDANYA Group (University of Málaga) are developing and implementing a FTRT Tsunami Simulation approach for the Italian candidate TSP, namely the Centro Allerta Tsunami (CAT), which is in pre-operational stage starting from 1 October 2014, in the 24/7 seismic monitoring room at INGV. The mandate of CAT is to provide warnings for potential tsunamis within the Mediterranean basin to its subscribers, in the framework of NEAMTWS (http://www.ioc-tsunami.org/index.php?option=com_content&view=article&id=70:neamtws-home&catid=9&Itemid=14&lang=es). CAT also performs global monitoring, for continuous testing, training, and validation purposes. The tsunami-HySEA model, developed by EDANYA Group, implements in the same code the three phases of an earthquake generated tsunami: generation, propagation and coastal inundation. At the same time it is implemented in nested meshes with different resolution and multi-GPU environment, which allows much faster than real time simulations. The challenge set by the Italian TSP for warning in the NEAMTWS region is twofold: to be able to reasonably constrain the earthquake source in the absence of deep sea tsunami sensors, and to

  19. Predicting Dissertation Methodology Choice among Doctoral Candidates at a Faith-Based University

    Science.gov (United States)

    Lunde, Rebecca

    2017-01-01

    Limited research has investigated dissertation methodology choice and the factors that contribute to this choice. Quantitative research is based in mathematics and scientific positivism, and qualitative research is based in constructivism. These underlying philosophical differences posit the question if certain factors predict dissertation…

  20. Optimized candidal biofilm microtiter assay

    NARCIS (Netherlands)

    Krom, Bastiaan P.; Cohen, Jesse B.; Feser, Gail E. McElhaney; Cihlar, Ronald L.

    Microtiter based candidal biofilm formation is commonly being used. Here we describe the analysis of factors influencing the development of candidal biofilms such as the coating with serum, growth medium and pH. The data reported here show that optimal candidal biofilm formation is obtained when

  1. A Novel Image Recuperation Approach for Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image

    Science.gov (United States)

    2015-01-01

    Retinal fundus images are widely used in diagnosing and providing treatment for several eye diseases. Prior works using retinal fundus images detected the presence of exudation with the aid of publicly available dataset using extensive segmentation process. Though it was proved to be computationally efficient, it failed to create a diabetic retinopathy feature selection system for transparently diagnosing the disease state. Also the diagnosis of diseases did not employ machine learning methods to categorize candidate fundus images into true positive and true negative ratio. Several candidate fundus images did not include more detailed feature selection technique for diabetic retinopathy. To apply machine learning methods and classify the candidate fundus images on the basis of sliding window a method called, Diabetic Fundus Image Recuperation (DFIR) is designed in this paper. The initial phase of DFIR method select the feature of optic cup in digital retinal fundus images based on Sliding Window Approach. With this, the disease state for diabetic retinopathy is assessed. The feature selection in DFIR method uses collection of sliding windows to obtain the features based on the histogram value. The histogram based feature selection with the aid of Group Sparsity Non-overlapping function provides more detailed information of features. Using Support Vector Model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy diseases. The ranking of disease level for each candidate set provides a much promising result for developing practically automated diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, specificity rate, ranking efficiency and feature selection time. PMID:25974230

  2. 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…

  3. Calibrating Canadian Universities: Rankings for Sale Once Again

    Science.gov (United States)

    Cramer, Kenneth M.; Page, Stewart

    2007-01-01

    A summary and update on recent research by the authors and others concerning rankings of Canadian universities is presented. Some specific data are reported in regard to the 2005 and 2006 ranking data published by "Maclean's" magazine. Some criticisms and difficulties with the use of rank-based data are outlined with regard to the issues…

  4. 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.

  5. Inferior immunogenicity and efficacy of respiratory syncytial virus fusion protein-based subunit vaccine candidates in aged versus young mice.

    Directory of Open Access Journals (Sweden)

    Corinne Cayatte

    Full Text Available Respiratory syncytial virus (RSV is recognized as an important cause of lower and upper respiratory tract infections in older adults, and a successful vaccine would substantially lower morbidity and mortality in this age group. Recently, two vaccine candidates based on soluble purified glycoprotein F (RSV F, either alone or adjuvanted with glucopyranosyl lipid A formulated in a stable emulsion (GLA-SE, failed to reach their primary endpoints in clinical efficacy studies, despite demonstrating the desired immunogenicity profile and efficacy in young rodent models. Here, one of the RSV F vaccine candidates (post-fusion conformation, RSV post-F, and a stabilized pre-fusion form of RSV F (RSV pre-F, DS-Cav1 were evaluated in aged BALB/c mice. Humoral and cellular immunogenicity elicited after immunization of naïve, aged mice was generally lower compared to young animals. In aged mice, RSV post-F vaccination without adjuvant poorly protected the respiratory tract from virus replication, and addition of GLA-SE only improved protection in the lungs, but not in nasal turbinates. RSV pre-F induced higher neutralizing antibody titers compared to RSV post-F (as previously reported but interestingly, RSV F-specific CD8 T cell responses were lower compared to RSV post-F responses regardless of age. The vaccines were also tested in RSV seropositive aged mice, in which both antigen forms similarly boosted neutralizing antibody titers, although GLA-SE addition boosted neutralizing activity only in RSV pre-F immunized animals. Cell-mediated immune responses in the aged mice were only slightly boosted and well below levels induced in seronegative young mice. Taken together, the findings suggest that the vaccine candidates were not able to induce a strong anti-RSV immune response in recipient mice with an aged immune system, in agreement with recent human clinical trial results. Therefore, the aged mouse model could be a useful tool to evaluate improved vaccine

  6. 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.

  7. 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.

  8. Biotransformation of prednisone and dexamethasone by cytochrome P450 based systems - Identification of new potential drug candidates.

    Science.gov (United States)

    Putkaradze, Natalia; Kiss, Flora Marta; Schmitz, Daniela; Zapp, Josef; Hutter, Michael C; Bernhardt, Rita

    2017-01-20

    Prednisone and dexamethasone are synthetic glucocorticoids widely used as anti-inflammatory and immunosuppressive drugs. Since their hydroxylated derivatives could serve as novel potential drug candidates, our aim was to investigate their biotransformation by the steroid hydroxylase CYP106A2 from Bacillus megaterium ATCC13368. In vitro we were able to demonstrate highly selective 15β-hydroxylation of the steroids with a reconstituted CYP106A2 system. The reactions were thoroughly characterized, determining the kinetic parameters and the equilibrium dissociation constant. The observed lower conversion rate in the case of dexamethasone hydroxylation was clarified by quantum chemical calculations, which suggest a rearrangement of the intermediately formed radical species. To identify the obtained conversion products with NMR, CYP106A2-based Bacillus megaterium whole-cell systems were applied resulting in an altered product pattern for prednisone, yet no significant change for dexamethasone conversion compared to in vitro. Even the MS941 control strain performed a highly selective biotransformation of prednisone producing the known metabolite 20β-dihydrocortisone. The identified novel prednisone derivatives 15β, 17, 20β, 21-tetrahydroxy-preg-4-en-3,11-dione and 15β, 17, 20β, 21-tetrahydroxy-preg-1,4-dien-3,11-dione as well as the 15β-hydroxylated variants of both drugs are promising candidates for drug-design and development approaches. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Augmenting the Deliberative Method for Ranking Risks.

    Science.gov (United States)

    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.

  10. Hierarchical Rank Aggregation with Applications to Nanotoxicology.

    Science.gov (United States)

    Patel, Trina; Telesca, Donatello; Rallo, Robert; George, Saji; Xia, Tian; Nel, André E

    2013-06-01

    The development of high throughput screening (HTS) assays in the field of nanotoxicology provide new opportunities for the hazard assessment and ranking of engineered nanomaterials (ENMs). It is often necessary to rank lists of materials based on multiple risk assessment parameters, often aggregated across several measures of toxicity and possibly spanning an array of experimental platforms. Bayesian models coupled with the optimization of loss functions have been shown to provide an effective framework for conducting inference on ranks. In this article we present various loss-function-based ranking approaches for comparing ENM within experiments and toxicity parameters. Additionally, we propose a framework for the aggregation of ranks across different sources of evidence while allowing for differential weighting of this evidence based on its reliability and importance in risk ranking. We apply these methods to high throughput toxicity data on two human cell-lines, exposed to eight different nanomaterials, and measured in relation to four cytotoxicity outcomes. This article has supplementary material online.

  11. Problem-Based Learning in the Educational Psychology Classroom: Bahraini Teacher Candidates' Experience

    Science.gov (United States)

    Razzak, Nina Abdul

    2012-01-01

    There was a concern from faculty at Bahrain Teachers' College that undergraduate Bahraini students lack the necessary competencies needed for success in educational contexts that are conducive to active, student-centered learning. It was decided that the students be introduced to a problem-based learning (PBL) strategy in one of their educational…

  12. Usability of a Web-Based School Experience System: Opinions of IT Teachers and Teacher Candidates

    Science.gov (United States)

    Genç, Zülfü

    2015-01-01

    With advances in information and communication technologies, the classical nature of educational institutions has changed. One innovative effort within teacher training is the Web-Based School Experience System (WBSES) developed by the researcher. In this study, the usability of an existing WBSES is evaluated from both teachers' (n = 13) and…

  13. A Study of the Effects of Rank and Gender on Officers' Club Membership and Club Usage at U.S. Air Force Bases in the Continental United States

    National Research Council Canada - National Science Library

    Smith, C

    1999-01-01

    Scope and Method of Study: The purpose of this study was to examine relationships between both officer rank and officer gender and both club membership and member usage at Air Force officers' clubs in the Continental United States (CONUS...

  14. Can College Rankings Be Believed?

    Directory of Open Access Journals (Sweden)

    Meredith Davis

    Full Text Available The article summarizes literature on college and university rankings worldwide and the strategies used by various ranking organizations, including those of government and popular media. It traces the history of national and global rankings, indicators used by ranking systems, and the effect of rankings on academic programs and their institutions. Although ranking systems employ diverse criteria and most weight certain indicators over others, there is considerable skepticism that most actually measure educational quality. At the same time, students and their families increasingly consult these evaluations when making college decisions, and sponsors of faculty research consider reputation when forming academic partnerships. While there are serious concerns regarding the validity of ranking institutions when so little data can support differences between one institution and another, college rankings appear to be here to stay.

  15. Tool for Ranking Research Options

    Science.gov (United States)

    Ortiz, James N.; Scott, Kelly; Smith, Harold

    2005-01-01

    Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

  16. Sync-rank: Robust Ranking, Constrained Ranking and Rank Aggregation via Eigenvector and SDP Synchronization

    Science.gov (United States)

    2015-04-28

    eigenvector of the associated Laplacian matrix (i.e., the Fiedler vector) matches that of the variables. In other words, this approach (reminiscent of...S1), i.e., Dii = ∑n j=1Gi,j is the degree of node i in the measurement graph G. 3: Compute the Fiedler vector of S (eigenvector corresponding to the...smallest nonzero eigenvalue of LS). 4: Output the ranking induced by sorting the Fiedler vector of S, with the global ordering (increasing or decreasing

  17. Pharmacokinetics of the phage endolysin-based candidate drug SAL200 in monkeys and its appropriate intravenous dosing period.

    Science.gov (United States)

    Jun, Soo Youn; Jung, Gi Mo; Yoon, Seong Jun; Youm, So Young; Han, Hyoung-Yun; Lee, Jong-Hwa; Kang, Sang Hyeon

    2016-10-01

    SAL200 is a new phage endolysin-based candidate drug for the treatment of staphylococcal infections. An intravenous administration study was conducted in monkeys to obtain pharmacokinetic information on SAL200 and to assess the safety of a short SAL200 dosing period (<1 week). Maximum serum drug concentrations and systemic SAL200 exposure were proportional to the dose and comparable in male and female monkeys. SAL200 was well tolerated, and no adverse events or laboratory abnormalities were detected after injection of a single dose of up to 80 mg/kg per day, or injection of multiple doses of up to 40 mg/kg per day. © 2016 John Wiley & Sons Australia, Ltd.

  18. The Effect of Genre-based Scaffolding on Research Paper Writing of MA Candidates in an EFL Context

    Directory of Open Access Journals (Sweden)

    Sara Salehpour

    2014-11-01

    Full Text Available In recent years, there has been an increasing amount of literature on genre-based approaches to writing instruction. However, scant attention has been paid to the use of genre-based scaffolding in the realm of academic writing. Hence, in an attempt to tackle the problems prevalent in academic writing, this study set out to investigate the effect of genre-based scaffolding through sentence starters and writing frames on MA candidates’ research paper writing. To this end, twenty MA candidates majoring in ELT were randomly assigned to two homogenous groups, one control and one experimental group, each including 10 participants. Both groups were exposed to a five-session genre-based instruction while the experimental group benefitted from the additional provision of sentence starters and writing frames relevant to different sections of a research paper. The analysis of the results, using independent sample of t-test, reveals that genre-based instruction can be a useful tool in improving academic writing. Moreover, the outperformance of the participants of the experimental group is indicative of the beneficial effect of scaffolding through starters and frames.

  19. Investigation of candidate data structures and search algorithms to support a knowledge based fault diagnosis system

    Science.gov (United States)

    Bosworth, Edward L., Jr.

    1987-01-01

    The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

  20. PageRank (II): Mathematics

    African Journals Online (AJOL)

    maths/stats

    INTRODUCTION. PageRank is Google's system for ranking web pages. A page with a higher PageRank is deemed more important and is more likely to be listed above a ... Felix U. Ogban, Department of Mathematics/Statistics and Computer Science, Faculty of Science, University of ..... probability, 2004, 41, (3): 721-734.

  1. 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…

  2. 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.

  3. Investigation of oxidation and tautomerization of a recently synthesized Schiff base in micellar media using multivariate curve resolution alternative least squares and rank annihilation factor analysis methods.

    Science.gov (United States)

    Afkhami, Abbas; Khajavi, Farzad; Khanmohammadi, Hamid

    2009-08-11

    The oxidation of the recently synthesized Schiff base 3,6-bis((2-aminoethyl-5-Br-salicyliden)thio)pyridazine (PABST) with hydrogen peroxide was investigated using spectrophotometric studies. The reaction rate order and observed rate constant of the oxidation reaction was obtained in the mixture of N,N-dimethylformamide (DMF):water (30:70, v/v) at pH 10 using multivariate cure resolution alternative least squares (MCR-ALS) method and rank annihilation factor analysis (RAFA). The effective parameters on the oxidation rate constant such as percents of DMF, the effect of transition metals like Cu(2+), Zn(2+), Mn(2+) and Hg(2+) and the presence of surfactants were investigated. The keto-enol equilibria in DMF:water (30:70, v/v) solution at pH 7.6 was also investigated in the presence of surfactants. At concentrations above critical micelle concentration (cmc) of cationic surfactant cetyltrimethylammonium bromide (CTAB), the keto form was the predominant species, while at concentrations above cmc of anionic surfactant sodium dodecyl sulfate (SDS), the enol form was the predominant species. The kinetic reaction order and the rate constant of tautomerization in micellar medium were obtained using MCR-ALS and RAFA. The results obtained by both the methods were in a good agreement with each other. Also the effect of different volume percents of DMF on the rate constant of tautomerization was investigated. The neutral surfactant (Triton X-100) had no effect on tautomerization equilibrium.

  4. Second-order differential equations for bosons with spin j ≥ 1 and in the bases of general tensor-spinors of rank 2j

    Science.gov (United States)

    Banda Guzmán, V. M.; Kirchbach, M.

    2016-09-01

    A boson of spin j≥ 1 can be described in one of the possibilities within the Bargmann-Wigner framework by means of one sole differential equation of order twice the spin, which however is known to be inconsistent as it allows for non-local, ghost and acausally propagating solutions, all problems which are difficult to tackle. The other possibility is provided by the Fierz-Pauli framework which is based on the more comfortable to deal with second-order Klein-Gordon equation, but it needs to be supplemented by an auxiliary condition. Although the latter formalism avoids some of the pathologies of the high-order equations, it still remains plagued by some inconsistencies such as the acausal propagation of the wave fronts of the (classical) solutions within an electromagnetic environment. We here suggest a method alternative to the above two that combines their advantages while avoiding the related difficulties. Namely, we suggest one sole strictly D^{(j,0)oplus (0,j)} representation specific second-order differential equation, which is derivable from a Lagrangian and whose solutions do not violate causality. The equation under discussion presents itself as the product of the Klein-Gordon operator with a momentum-independent projector on Lorentz irreducible representation spaces constructed from one of the Casimir invariants of the spin-Lorentz group. The basis used is that of general tensor-spinors of rank 2 j.

  5. Sequential rank agreement methods for comparison of ranked lists

    DEFF Research Database (Denmark)

    Ekstrøm, Claus Thorn; Gerds, Thomas Alexander; Jensen, Andreas Kryger

    2015-01-01

    The comparison of alternative rankings of a set of items is a general and prominent task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies...... are illustrated using gene rankings, and using data from two Danish ovarian cancer studies where we assess the within and between agreement of different statistical classification methods.......The comparison of alternative rankings of a set of items is a general and prominent task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies...

  6. Investigation of candidate genes for osteoarthritis based on gene expression profiles.

    Science.gov (United States)

    Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei

    2016-12-01

    To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor

  7. Issue Management Risk Ranking Systems

    Energy Technology Data Exchange (ETDEWEB)

    Novack, Steven David; Marshall, Frances Mc Clellan; Stromberg, Howard Merion; Grant, Gary Michael

    1999-06-01

    Thousands of safety issues have been collected on-line at the Idaho National Engineering and Environmental Laboratory (INEEL) as part of the Issue Management Plan. However, there has been no established approach to prioritize collected and future issues. The authors developed a methodology, based on hazards assessment, to identify and risk rank over 5000 safety issues collected at INEEL. This approach required that it was easily applied and understandable for site adaptation and commensurate with the Integrated Safety Plan. High-risk issues were investigated and mitigative/preventive measures were suggested and ranked based on a cost-benefit scheme to provide risk-informed safety measures. This methodology was consistent with other integrated safety management goals and tasks providing a site-wide risk informed decision tool to reduce hazardous conditions and focus resources on high-risk safety issues. As part of the issue management plan, this methodology was incorporated at the issue collection level and training was provided to management to better familiarize decision-makers with concepts of safety and risk. This prioritization methodology and issue dissemination procedure will be discussed. Results of issue prioritization and training efforts will be summarized. Difficulties and advantages of the process will be reported. Development and incorporation of this process into INEELs lessons learned reporting and the site-wide integrated safety management program will be shown with an emphasis on establishing self reliance and ownership of safety issues.

  8. Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

    Directory of Open Access Journals (Sweden)

    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.

  9. Key enzymes and proteins of crop insects as candidate for RNAi based gene silencing

    Science.gov (United States)

    Kola, Vijaya Sudhakara Rao; Renuka, P.; Madhav, Maganti Sheshu; Mangrauthia, Satendra K.

    2015-01-01

    RNA interference (RNAi) is a mechanism of homology dependent gene silencing present in plants and animals. It operates through 21–24 nucleotides small RNAs which are processed through a set of core enzymatic machinery that involves Dicer and Argonaute proteins. In recent past, the technology has been well appreciated toward the control of plant pathogens and insects through suppression of key genes/proteins of infecting organisms. The genes encoding key enzymes/proteins with the great potential for developing an effective insect control by RNAi approach are actylcholinesterase, cytochrome P450 enzymes, amino peptidase N, allatostatin, allatotropin, tryptophan oxygenase, arginine kinase, vacuolar ATPase, chitin synthase, glutathione-S-transferase, catalase, trehalose phosphate synthase, vitellogenin, hydroxy-3-methylglutaryl coenzyme A reductase, and hormone receptor genes. Through various studies, it is demonstrated that RNAi is a reliable molecular tool which offers great promises in meeting the challenges imposed by crop insects with careful selection of key enzymes/proteins. Utilization of RNAi tool to target some of these key proteins of crop insects through various approaches is described here. The major challenges of RNAi based insect control such as identifying potential targets, delivery methods of silencing trigger, off target effects, and complexity of insect biology are very well illustrated. Further, required efforts to address these challenges are also discussed. PMID:25954206

  10. Exploration of candidate biomarkers for human psoriasis based on gas chromatography-mass spectrometry serum metabolomics.

    Science.gov (United States)

    Kang, H; Li, X; Zhou, Q; Quan, C; Xue, F; Zheng, J; Yu, Y

    2017-03-01

    Recent studies have shown that dysregulated metabolic pathways are linked to psoriasis pathogenesis. However, an extensive, unbiased metabolic analysis in patients with psoriasis has not been completely explored. The metabolome represents the end products of proteomics or cellular processes that may be closely associated with the pathogenesis of psoriasis. To determine the differences in serum metabolomic profiles among patients with psoriasis and healthy controls with the goal of identifying potential biomarkers in patients with psoriasis. Serum metabolomic profiles from 29 subjects (14 patients with psoriasis and 15 sex- and age-matched healthy controls). The serum metabolites were analysed by gas chromatography-mass spectrometry based on a combined full scan and selected-ion monitoring mode. Multivariate statistical analysis of metabolomics data revealed altered serum metabolites between the patients with psoriasis and healthy individuals. Compared with healthy individuals, patients with psoriasis had higher levels of amino acids including asparagine, aspartic acid, isoleucine, phenylalanine, ornithine and proline; higher levels of lactic acid and urea; and lower levels of crotonic acid, azelaic acid, ethanolamine and cholesterol. It appears that the glycolysis pathway and amino acid metabolic activity are increased in patients with psoriasis. These metabolic perturbations may stem from increased demand for protein biosynthesis and keratinocyte hyperproliferation. Our findings may help to elucidate the pathogenesis of psoriasis and provide insights into early diagnosis and therapeutic intervention. © 2016 British Association of Dermatologists.

  11. A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears.

    Science.gov (United States)

    Linder, Nina; Turkki, Riku; Walliander, Margarita; Mårtensson, Andreas; Diwan, Vinod; Rahtu, Esa; Pietikäinen, Matti; Lundin, Mikael; Lundin, Johan

    2014-01-01

    Microscopy is the gold standard for diagnosis of malaria, however, manual evaluation of blood films is highly dependent on skilled personnel in a time-consuming, error-prone and repetitive process. In this study we propose a method using computer vision detection and visualization of only the diagnostically most relevant sample regions in digitized blood smears. Giemsa-stained thin blood films with P. falciparum ring-stage trophozoites (n = 27) and uninfected controls (n = 20) were digitally scanned with an oil immersion objective (0.1 µm/pixel) to capture approximately 50,000 erythrocytes per sample. Parasite candidate regions were identified based on color and object size, followed by extraction of image features (local binary patterns, local contrast and Scale-invariant feature transform descriptors) used as input to a support vector machine classifier. The classifier was trained on digital slides from ten patients and validated on six samples. The diagnostic accuracy was tested on 31 samples (19 infected and 12 controls). From each digitized area of a blood smear, a panel with the 128 most probable parasite candidate regions was generated. Two expert microscopists were asked to visually inspect the panel on a tablet computer and to judge whether the patient was infected with P. falciparum. The method achieved a diagnostic sensitivity and specificity of 95% and 100% as well as 90% and 100% for the two readers respectively using the diagnostic tool. Parasitemia was separately calculated by the automated system and the correlation coefficient between manual and automated parasitemia counts was 0.97. We developed a decision support system for detecting malaria parasites using a computer vision algorithm combined with visualization of sample areas with the highest probability of malaria infection. The system provides a novel method for blood smear screening with a significantly reduced need for visual examination and has a potential to increase the

  12. A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears.

    Directory of Open Access Journals (Sweden)

    Nina Linder

    Full Text Available INTRODUCTION: Microscopy is the gold standard for diagnosis of malaria, however, manual evaluation of blood films is highly dependent on skilled personnel in a time-consuming, error-prone and repetitive process. In this study we propose a method using computer vision detection and visualization of only the diagnostically most relevant sample regions in digitized blood smears. METHODS: Giemsa-stained thin blood films with P. falciparum ring-stage trophozoites (n = 27 and uninfected controls (n = 20 were digitally scanned with an oil immersion objective (0.1 µm/pixel to capture approximately 50,000 erythrocytes per sample. Parasite candidate regions were identified based on color and object size, followed by extraction of image features (local binary patterns, local contrast and Scale-invariant feature transform descriptors used as input to a support vector machine classifier. The classifier was trained on digital slides from ten patients and validated on six samples. RESULTS: The diagnostic accuracy was tested on 31 samples (19 infected and 12 controls. From each digitized area of a blood smear, a panel with the 128 most probable parasite candidate regions was generated. Two expert microscopists were asked to visually inspect the panel on a tablet computer and to judge whether the patient was infected with P. falciparum. The method achieved a diagnostic sensitivity and specificity of 95% and 100% as well as 90% and 100% for the two readers respectively using the diagnostic tool. Parasitemia was separately calculated by the automated system and the correlation coefficient between manual and automated parasitemia counts was 0.97. CONCLUSION: We developed a decision support system for detecting malaria parasites using a computer vision algorithm combined with visualization of sample areas with the highest probability of malaria infection. The system provides a novel method for blood smear screening with a significantly reduced need for

  13. Losing on all fronts: the effects of negative versus positive person-based campaigns on implicit and explicit evaluations of political candidates.

    Science.gov (United States)

    Carraro, Luciana; Gawronski, Bertram; Castelli, Luigi

    2010-09-01

    The current research investigated the effects of negative as compared to positive person-based political campaigns on explicit and implicit evaluations of the involved candidates. Participants were presented with two political candidates and statements that one of them ostensibly said during the last political campaign. For half of the participants, the campaign included positive remarks about the source of the statement (positive campaign); for the remaining half, the campaign included negative remarks about the opponent (negative campaign). Afterwards, participants completed measures of explicit and implicit evaluations of both candidates. Results indicate that explicit evaluations of the source, but not the opponent, were less favourable after negative as compared to positive campaigns. In contrast, implicit evaluations were less favourable for both candidates after negative campaigns. The results are discussed in terms of associative and propositional processes, highlighting the importance of associative processes in political decision making.

  14. A STUDY ON RANKING METHOD IN RETRIEVING WEB PAGES BASED ON CONTENT AND LINK ANALYSIS: COMBINATION OF FOURIER DOMAIN SCORING AND PAGERANK SCORING

    Directory of Open Access Journals (Sweden)

    Diana Purwitasari

    2008-01-01

    Full Text Available Ranking module is an important component of search process which sorts through relevant pages. Since collection of Web pages has additional information inherent in the hyperlink structure of the Web, it can be represented as link score and then combined with the usual information retrieval techniques of content score. In this paper we report our studies about ranking score of Web pages combined from link analysis, PageRank Scoring, and content analysis, Fourier Domain Scoring. Our experiments use collection of Web pages relate to Statistic subject from Wikipedia with objectives to check correctness and performance evaluation of combination ranking method. Evaluation of PageRank Scoring show that the highest score does not always relate to Statistic. Since the links within Wikipedia articles exists so that users are always one click away from more information on any point that has a link attached, it it possible that unrelated topics to Statistic are most likely frequently mentioned in the collection. While the combination method show link score which is given proportional weight to content score of Web pages does effect the retrieval results.

  15. Exploring the Altruistic Expectations of Teacher Candidates Enrolled in Faith-Based Colleges and Universities: A Mixed Methods Investigation

    Science.gov (United States)

    Buel, Christine M.

    2011-01-01

    This mixed-methods research design, crafted as a phenomenological study, and developed through a lens of critical social theory, was conducted to explore the altruistic expectation level of teacher candidates. Further, the research questions and hypotheses reflect the problem that many well-meaning teacher candidates enter the teaching profession…

  16. School background and university selection: ranking performance as an inclusion factor to higher education

    Directory of Open Access Journals (Sweden)

    Carlos René Rodríguez Garcés

    2016-07-01

    Full Text Available Using databases of Admission to Higher Education in Chile in 2013, the behavior of components that have school career (NEM and Ranking and PSU scores (Mathematics and Language is analyzed based variables segmentation of socio applicants. But both factors in theory be aligned with the curriculum, scores report a reduced correlation between them. The aim is to explore and analyze the distribution of the scores obtained by the candidates in various selection factors based on their socioeconomic and educational characteristics, and the impact of incorporating the Ranking of Scores on diversification and inclusion of the population students annually participates in the selection process. School career components, especially Ranking establishing the relative position within their respective student accommodation have less biased and with a higher concentration toward higher scores compared to the PSU component distributions, and show less influenced by variables sociofamiliar or economic. Ranking as an expression of good school performance, effort and dedication to study by the student, compensates for unwanted selection bias doing more inclusive university choice, whose effects on the modification of the student profile selected will depend on the valuation assigned the university institution to the school career the detriment of traditional PSU component.

  17. An LC-MS/MS based candidate reference method for the quantification of carbamazepine in human serum.

    Science.gov (United States)

    Taibon, Judith; Schmid, Rupert; Lucha, Stephanie; Pongratz, Stephan; Tarasov, Kirill; Seger, Christoph; Timm, Christian; Thiele, Roland; Herlan, Joachim Mark; Kobold, Uwe

    2017-09-01

    A validated LC-MS/MS-based candidate reference measurement procedure for the quantification of carbamazepine is presented in order to be used for standardization and harmonization of routine assays applied for therapeutic drug monitoring. Sample preparation was based on protein precipitation using acetonitrile followed by sample dilution. Since the previously listed certified reference material (CRM) SRM 1599 (anticonvulsant drug level assay standard) is no longer available, an ISO certified calibration material was used in this assay. As internal standards deuterated analyte congeners were applied. The method allows the measurement of carbamazepine, carbamazepine-10,11-epoxide and 10-hydroxy-10,11-dihydrocarbamazepine in the concentration range of 0.1 to 22.0μg/ml with LODs and LOQs of <0.1μg/ml and 0.1μg/ml, respectively. Comparative measurement of 105 native patient samples using the here presented method showed a good agreement between two independent laboratories with a mean bias of 0.6%. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Identifying potential exposure reduction priorities using regional rankings based on emissions of known and suspected carcinogens to outdoor air in Canada.

    Science.gov (United States)

    Setton, Eleanor M; Veerman, Basil; Erickson, Anders; Deschenes, Steeve; Cheasley, Roz; Poplawski, Karla; Demers, Paul A; Keller, C Peter

    2015-08-22

    Emissions inventories aid in understanding the sources of hazardous air pollutants and how these vary regionally, supporting targeted reduction actions. Integrating information on the relative toxicity of emitted pollutants with respect to cancer in humans helps to further refine reduction actions or recommendations, but few national programs exist in North America that use emissions estimates in this way. The CAREX Canada Emissions Mapping Project provides key regional indicators of emissions (total annual and total annual toxic equivalent, circa 2011) of 21 selected known and suspected carcinogens. The indicators were calculated from industrial emissions reported to the National Pollutant Release Inventory (NPRI) and estimates of emissions from transportation (airports, trains, and car and truck traffic) and residential heating (oil, gas and wood), in conjunction with human toxicity potential factors. We also include substance-specific annual emissions in toxic equivalent kilograms and annual emissions in kilograms, to allow for ranking substances within any region. For provinces and territories in Canada, the indicators suggest the top five substances contributing to the total toxic equivalent emissions in any region could be prioritized for further investigation. Residents of Quebec and New Brunswick may be more at risk of exposure to industrial emissions than those in other regions, suggesting that a more detailed study of exposure to industrial emissions in these provinces is warranted. Residential wood smoke may be an important emission to control, particularly in the north and eastern regions of Canada. Residential oil and gas heating, along with rail emissions contribute little to regional emissions and therefore may not be an immediate regional priority. The developed indicators support the identification of pollutants and sources for additional investigation when planning exposure reduction actions among Canadian provinces and territories, but have

  19. Social class rank, essentialism, and punitive judgment.

    Science.gov (United States)

    Kraus, Michael W; Keltner, Dacher

    2013-08-01

    Recent evidence suggests that perceptions of social class rank influence a variety of social cognitive tendencies, from patterns of causal attribution to moral judgment. In the present studies we tested the hypotheses that upper-class rank individuals would be more likely to endorse essentialist lay theories of social class categories (i.e., that social class is founded in genetically based, biological differences) than would lower-class rank individuals and that these beliefs would decrease support for restorative justice--which seeks to rehabilitate offenders, rather than punish unlawful action. Across studies, higher social class rank was associated with increased essentialism of social class categories (Studies 1, 2, and 4) and decreased support for restorative justice (Study 4). Moreover, manipulated essentialist beliefs decreased preferences for restorative justice (Study 3), and the association between social class rank and class-based essentialist theories was explained by the tendency to endorse beliefs in a just world (Study 2). Implications for how class-based essentialist beliefs potentially constrain social opportunity and mobility are discussed.

  20. Using Weighted Entropy to Rank Chemicals in Quantitative High Throughput Screening Experiments

    Science.gov (United States)

    Shockley, Keith R.

    2014-01-01

    Quantitative high throughput screening (qHTS) experiments can simultaneously produce concentration-response profiles for thousands of chemicals. In a typical qHTS study, a large chemical library is subjected to a primary screen in order to identify candidate hits for secondary screening, validation studies or prediction modeling. Different algorithms, usually based on the Hill equation logistic model, have been used to classify compounds as active or inactive (or inconclusive). However, observed concentration-response activity relationships may not adequately fit a sigmoidal curve. Furthermore, it is unclear how to prioritize chemicals for follow-up studies given the large uncertainties that often accompany parameter estimates from nonlinear models. Weighted Shannon entropy can address these concerns by ranking compounds according to profile-specific statistics derived from estimates of the probability mass distribution of response at the tested concentration levels. This strategy can be used to rank all tested chemicals in the absence of a pre-specified model structure or the approach can complement existing activity call algorithms by ranking the returned candidate hits. The weighted entropy approach was evaluated here using data simulated from the Hill equation model. The procedure was then applied to a chemical genomics profiling data set interrogating compounds for androgen receptor agonist activity. PMID:24056003

  1. Ranking de universidades chilenas: un análisis multivariado

    Directory of Open Access Journals (Sweden)

    Firinguetti Limone, Luis

    2015-06-01

    Full Text Available In this work a ranking of Chilean universities on the basis of publicly available information is developed. This ranking takes into account the multivariate character of these institutions. Also, it is noted that the results are consistent with those of a well-known international ranking that uses a different set of data, as well as with several multivariate analyses of the data considered in this study.En este trabajo se elabora un ranking de las universidades chilenas en base a información pública disponible. Dicho ranking toma en cuenta el carácter multivariado de estas instituciones. Además, se ha comprobado que los resultados del ranking son consistentes con un conocido ranking internacional construido a partir de un conjunto diferente de datos y con varios análisis multivariados realizados de la información tratada en este estudio.

  2. Comparative testing of six antigen-based malaria vaccine candidates directed toward merozoite-stage Plasmodium falciparum

    DEFF Research Database (Denmark)

    Arnot, David E; Cavanagh, David R; Remarque, Edmond J

    2008-01-01

    Immunogenicity testing of Plasmodium falciparum antigens being considered as malaria vaccine candidates was undertaken in rabbits. The antigens compared were recombinant baculovirus MSP-1(19) and five Pichia pastoris candidates, including two versions of MSP-1(19), AMA-1 (domains I and II), AMA-1......G concentrations. The two P. pastoris-produced MSP-1(19)-induced IgGs conferred the lowest growth inhibition. Comparative analysis of immunogenicity of vaccine antigens can be used to prioritize candidates before moving to expensive GMP production and clinical testing. The assays used have given discriminating...

  3. 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.

  4. 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).

  5. Diffusion of scientific credits and the ranking of scientists

    OpenAIRE

    Radicchi, Filippo; Fortunato, Santo; Markines, Benjamin; Vespignani, Alessandro

    2009-01-01

    Recently, the abundance of digital data enabled the implementation of graph based ranking algorithms that provide system level analysis for ranking publications and authors. Here we take advantage of the entire Physical Review publication archive (1893-2006) to construct authors' networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. On this network we define a ranking method based on a diffusion ...

  6. Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining

    NARCIS (Netherlands)

    Hulsegge, B.; Woelders, H.; Smits, M.A.; Schokker, D.; Jiang, L.; Sorensen, P.

    2013-01-01

    Reproduction is of significant economic importance in dairy cattle. Improved understanding of mechanisms that control estrous behavior and other reproduction traits could help in developing strategies to improve and/or monitor these traits. The objective of this study was to predict and rank genes

  7. Extreme learning machine for ranking: generalization analysis and applications.

    Science.gov (United States)

    Chen, Hong; Peng, Jiangtao; Zhou, Yicong; Li, Luoqing; Pan, Zhibin

    2014-05-01

    The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. 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.

  9. Glutathione transferase (GST) as a candidate molecular-based biomarker for soil toxin exposure in the earthworm Lumbricus rubellus

    Energy Technology Data Exchange (ETDEWEB)

    LaCourse, E. James, E-mail: james.la-course@liverpool.ac.u [Institute of Biological, Environmental, and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3DA (United Kingdom); Hernandez-Viadel, Mariluz; Jefferies, James R. [Institute of Biological, Environmental, and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3DA (United Kingdom); Svendsen, Claus; Spurgeon, David J. [Centre for Ecology and Hydrology, Huntingdon PE28 2LS (United Kingdom); Barrett, John [Institute of Biological, Environmental, and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3DA (United Kingdom); John Morgan, A.; Kille, Peter [Biosciences, University of Cardiff, Cardiff CF10 3TL (United Kingdom); Brophy, Peter M. [Institute of Biological, Environmental, and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3DA (United Kingdom)

    2009-08-15

    The earthworm Lumbricus rubellus (Hoffmeister, 1843) is a terrestrial pollution sentinel. Enzyme activity and transcription of phase II detoxification superfamily glutathione transferases (GST) is known to respond in earthworms after soil toxin exposure, suggesting GST as a candidate molecular-based pollution biomarker. This study combined sub-proteomics, bioinformatics and biochemical assay to characterise the L. rubellus GST complement as pre-requisite to initialise assessment of the applicability of GST as a biomarker. L. rubellus possesses a range of GSTs related to known classes, with evidence of tissue-specific synthesis. Two affinity-purified GSTs dominating GST protein synthesis (Sigma and Pi class) were cloned, expressed and characterised for enzyme activity with various substrates. Electrospray ionisation mass spectrometry (ESI-MS) and tandem mass spectrometry (MS/MS) following SDS-PAGE were superior in retaining subunit stability relative to two-dimensional gel electrophoresis (2-DE). This study provides greater understanding of Phase II detoxification GST superfamily status of an important environmental pollution sentinel organism. - This study currently provides the most comprehensive view of the Phase II detoxification enzyme superfamily of glutathione transferases within the important environmental pollution sentinel earthworm Lumbricus rubellus.

  10. Jenner-predict server: prediction of protein vaccine candidates (PVCs) in bacteria based on host-pathogen interactions

    Science.gov (United States)

    2013-01-01

    Background Subunit vaccines based on recombinant proteins have been effective in preventing infectious diseases and are expected to meet the demands of future vaccine development. Computational approach, especially reverse vaccinology (RV) method has enormous potential for identification of protein vaccine candidates (PVCs) from a proteome. The existing protective antigen prediction software and web servers have low prediction accuracy leading to limited applications for vaccine development. Besides machine learning techniques, those software and web servers have considered only protein’s adhesin-likeliness as criterion for identification of PVCs. Several non-adhesin functional classes of proteins involved in host-pathogen interactions and pathogenesis are known to provide protection against bacterial infections. Therefore, knowledge of bacterial pathogenesis has potential to identify PVCs. Results A web server, Jenner-Predict, has been developed for prediction of PVCs from proteomes of bacterial pathogens. The web server targets host-pathogen interactions and pathogenesis by considering known functional domains from protein classes such as adhesin, virulence, invasin, porin, flagellin, colonization, toxin, choline-binding, penicillin-binding, transferring-binding, fibronectin-binding and solute-binding. It predicts non-cytosolic proteins containing above domains as PVCs. It also provides vaccine potential of PVCs in terms of their possible immunogenicity by comparing with experimentally known IEDB epitopes, absence of autoimmunity and conservation in different strains. Predicted PVCs are prioritized so that only few prospective PVCs could be validated experimentally. The performance of web server was evaluated against known protective antigens from diverse classes of bacteria reported in Protegen database and datasets used for VaxiJen server development. The web server efficiently predicted known vaccine candidates reported from Streptococcus pneumoniae and

  11. Jenner-predict server: prediction of protein vaccine candidates (PVCs) in bacteria based on host-pathogen interactions.

    Science.gov (United States)

    Jaiswal, Varun; Chanumolu, Sree Krishna; Gupta, Ankit; Chauhan, Rajinder S; Rout, Chittaranjan

    2013-07-01

    Subunit vaccines based on recombinant proteins have been effective in preventing infectious diseases and are expected to meet the demands of future vaccine development. Computational approach, especially reverse vaccinology (RV) method has enormous potential for identification of protein vaccine candidates (PVCs) from a proteome. The existing protective antigen prediction software and web servers have low prediction accuracy leading to limited applications for vaccine development. Besides machine learning techniques, those software and web servers have considered only protein's adhesin-likeliness as criterion for identification of PVCs. Several non-adhesin functional classes of proteins involved in host-pathogen interactions and pathogenesis are known to provide protection against bacterial infections. Therefore, knowledge of bacterial pathogenesis has potential to identify PVCs. A web server, Jenner-Predict, has been developed for prediction of PVCs from proteomes of bacterial pathogens. The web server targets host-pathogen interactions and pathogenesis by considering known functional domains from protein classes such as adhesin, virulence, invasin, porin, flagellin, colonization, toxin, choline-binding, penicillin-binding, transferring-binding, fibronectin-binding and solute-binding. It predicts non-cytosolic proteins containing above domains as PVCs. It also provides vaccine potential of PVCs in terms of their possible immunogenicity by comparing with experimentally known IEDB epitopes, absence of autoimmunity and conservation in different strains. Predicted PVCs are prioritized so that only few prospective PVCs could be validated experimentally. The performance of web server was evaluated against known protective antigens from diverse classes of bacteria reported in Protegen database and datasets used for VaxiJen server development. The web server efficiently predicted known vaccine candidates reported from Streptococcus pneumoniae and Escherichia coli

  12. Google Internet searches on residency applicants do not facilitate the ranking process.

    Science.gov (United States)

    Shin, Nara C; Ramoska, Edward A; Garg, Manish; Rowh, Adam; Nyce, Drew; Deroos, Francis; Carter, Merle; Hall, Ronald V; Lopez, Bernard L

    2013-05-01

    Information used by program directors (PDs) to evaluate and rank residency applicants is largely limited to the Electronic Residency Application Service and the interview day. The Internet represents a potential source of additional data on applicants. Recent surveys reveal that up to 90% of United States (US) companies are already using the Internet to post jobs and to screen candidates. However, its use in residency applicant evaluation is not well studied. We hypothesize that the Internet, through the use of a Google search, will provide useful information to PDs in ranking applicants. This prospective observational study was completed by six Accreditation Council for Graduate Medical Education-accredited Emergency Medicine residency programs. After the interview process, programs formed their rank order list in their usual fashion. Then participating programs performed a Google search on applicants from their list. A standardized search was used and information reviewed was limited to the first two Google pages. The main outcome measure was change in an applicant's status on the rank order list. Change in status was based on the judgment of the individual program's PD. A total of 547 applicants were reviewed. The time for review of information was 4,386 min total and a mean of 7.2 min per resident. Position on the rank order list was changed for three applicants; two moved up on the list and one moved down. Four programs made no changes. No applicants were removed. The Internet, through the use of a Google search, did not appear to provide useful information in a time-effective manner to PDs in ranking applicants. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. University Rankings in Critical Perspective

    Science.gov (United States)

    Pusser, Brian; Marginson, Simon

    2013-01-01

    This article addresses global postsecondary ranking systems by using critical-theoretical perspectives on power. This research suggests rankings are at once a useful lens for studying power in higher education and an important instrument for the exercise of power in service of dominant norms in global higher education. (Contains 1 table and 1…

  14. University Ranking as Social Exclusion

    Science.gov (United States)

    Amsler, Sarah S.; Bolsmann, Chris

    2012-01-01

    In this article we explore the dual role of global university rankings in the creation of a new, knowledge-identified, transnational capitalist class and in facilitating new forms of social exclusion. We examine how and why the practice of ranking universities has become widely defined by national and international organisations as an important…

  15. Ranking beta sheet topologies of proteins

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

    2010-01-01

    One of the challenges of protein structure prediction is to identify long-range interactions between amino acids. To reliably predict such interactions, we enumerate, score and rank all beta-topologies (partitions of beta-strands into sheets, orderings of strands within sheets and orientations...... of paired strands) of a given protein. We show that the beta-topology corresponding to the native structure is, with high probability, among the top-ranked. Since full enumeration is very time-consuming, we also suggest a method to deal with proteins with many beta-strands. The results reported...... in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. The top-ranked beta-topologies can be used to find initial conformations from which conformational searches can be started. They can also be used to filter decoys by removing those with poorly...

  16. Novel Plasmodium falciparum malaria vaccines: evidence-based searching for variant surface antigens as candidates for vaccination against pregnancy-associated malaria

    DEFF Research Database (Denmark)

    Staalsoe, Trine; Jensen, Anja T R; Theander, Thor G

    2002-01-01

    Malaria vaccine development has traditionally concentrated on careful molecular, biochemical, and immunological characterisation of candidate antigens. In contrast, evidence of the importance of identified antigens in immunity to human infection and disease has generally been limited......) in particular, to provide robust evidence of a causal link between the two in order to allow efficient and evidence-based identification of candidate antigens for malaria vaccine development....... to statistically significant co-variation with protection rather than on demonstration of causal relationships. We have studied the relationship between variant surface antigen-specific antibodies and clinical protection from Plasmodium falciparum malaria in general, and from pregnancy-associated malaria (PAM...

  17. 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.

  18. Ranking health between countries in international comparisons

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    2014-01-01

    Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions...

  19. Identification of HSPA8 as a candidate biomarker for endometrial carcinoma by using iTRAQ-based proteomic analysis

    Directory of Open Access Journals (Sweden)

    Shan N

    2016-04-01

    Full Text Available Nianchun Shan,1 Wei Zhou,2 Shufen Zhang,1 Yu Zhang1 1Department of Obstetric and Gynecology, 2Health Management Center, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China Abstract: Although there are advances in diagnostic, predictive, and therapeutic strategies, discovering protein biomarker for early detection is required for improving the survival rate of the patients with endometrial carcinoma. In this study, we identify proteins that are differentially expressed between the Stage I endometrial carcinoma and the normal pericarcinous tissues by using isobaric tags for relative and absolute quantitation (iTRAQ-based proteomic analysis. Totally, we screened 1,266 proteins. Among them, 103 proteins were significantly overexpressed, and 30 were significantly downexpressed in endometrial carcinoma. Using the bioinformatics analysis, we identified a list of proteins that might be closely associated with endometrial carcinoma, including CCT7, HSPA8, PCBP2, LONP1, PFN1, and EEF2. We validated the gene overexpression of these molecules in the endometrial carcinoma tissues and found that HSPA8 was most significantly upregulated. We further validated the overexpression of HSPA8 by using immunoblot analysis. Then, HSPA8 siRNA was transferred into the endometrial cancer cells RL-95-2 and HEC-1B. The depletion of HSPA8 siRNAs significantly reduced cell proliferation, promoted cell apoptosis, and suppressed cell growth in both cell lines. Taken together, HSPA8 plays a vital role in the development of endometrial carcinoma. HSPA8 is a candidate biomarker for early diagnosis and therapy of Stage I endometrial carcinoma. Keywords: iTRAQ, HSPA8, endometrial carcinoma, RL-95-2 cells

  20. A cross-benchmark comparison of 87 learning to rank methods

    NARCIS (Netherlands)

    Tax, Niek; Bockting, Sander; Hiemstra, Djoerd

    2015-01-01

    Learning to rank is an increasingly important scientific field that comprises the use of machine learning for the ranking task. New learning to rank methods are generally evaluated on benchmark test collections. However, comparison of learning to rank methods based on evaluation results is hindered

  1. Enthalpy screen of drug candidates.

    Science.gov (United States)

    Schön, Arne; Freire, Ernesto

    2016-11-15

    The enthalpic and entropic contributions to the binding affinity of drug candidates have been acknowledged to be important determinants of the quality of a drug molecule. These quantities, usually summarized in the thermodynamic signature, provide a rapid assessment of the forces that drive the binding of a ligand. Having access to the thermodynamic signature in the early stages of the drug discovery process will provide critical information towards the selection of the best drug candidates for development. In this paper, the Enthalpy Screen technique is presented. The enthalpy screen allows fast and accurate determination of the binding enthalpy for hundreds of ligands. As such, it appears to be ideally suited to aid in the ranking of the hundreds of hits that are usually identified after standard high throughput screening. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

    Science.gov (United States)

    Somasundaram, K.; Alli Rajendran, P.

    2015-01-01

    Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time. PMID:25945362

  3. The effects of CpG-ODNs and Chitosan adjuvants on the elicitation of immune responses induced by the HIV-1-Tat-based candidate vaccines in mice.

    Science.gov (United States)

    Alipour, Samira; Mahdavi, Atiyeh; Abdoli, Asghar

    2017-03-01

    HIV1-Tat-based vaccines could elicit broad, durable and neutralizing immune responses and are considered as potential AIDS vaccines. The present study aims to formulate CpG-ODNs adjuvant and Chitosan with Tat protein to enhance the immunogenicity of HIV-1-Tat-based candidate vaccines and to investigate their efficacies in mice. To this end, we added CpG-ODNs, Chitosan and Alum as adjuvants to the Tat-based candidate vaccine formulations. Then, we compared frequency and magnitude of both humoral and cellular immune responses from mice immunized with the adjuvant-formulated Tat candidate vaccines against those obtained from mice immunized with recombinant Tat protein alone. Mice were subcutaneously immunized three times at 2-week intervals with the candidate vaccines. Measurements of anti-Tat immune responses showed that all vaccinated groups had a good immunity compared to the control groups and developed high levels of both humoral and cellular responses. However, immunized mice with CpG-ODNs, and Chitosan-adjuvanted Tat vaccines elicited stronger T-cell responses (both humoral and cellular immunity) compared to the others. These data suggest that co-administration of recombinant Tat protein with CpG-ODNs and Chitosan may serve as a potential formulation for enhancing of the Tat vaccine-induced immunity and might have effects on shaping Th polarization induced by HIV1-Tat protein vaccines. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  4. Kriging for Simulation Metamodeling: Experimental Design, Reduced Rank Kriging, and Omni-Rank Kriging

    Science.gov (United States)

    Hosking, Michael Robert

    This dissertation improves an analyst's use of simulation by offering improvements in the utilization of kriging metamodels. There are three main contributions. First an analysis is performed of what comprises good experimental designs for practical (non-toy) problems when using a kriging metamodel. Second is an explanation and demonstration of how reduced rank decompositions can improve the performance of kriging, now referred to as reduced rank kriging. Third is the development of an extension of reduced rank kriging which solves an open question regarding the usage of reduced rank kriging in practice. This extension is called omni-rank kriging. Finally these results are demonstrated on two case studies. The first contribution focuses on experimental design. Sequential designs are generally known to be more efficient than "one shot" designs. However, sequential designs require some sort of pilot design from which the sequential stage can be based. We seek to find good initial designs for these pilot studies, as well as designs which will be effective if there is no following sequential stage. We test a wide variety of designs over a small set of test-bed problems. Our findings indicate that analysts should take advantage of any prior information they have about their problem's shape and/or their goals in metamodeling. In the event of a total lack of information we find that Latin hypercube designs are robust default choices. Our work is most distinguished by its attention to the higher levels of dimensionality. The second contribution introduces and explains an alternative method for kriging when there is noise in the data, which we call reduced rank kriging. Reduced rank kriging is based on using a reduced rank decomposition which artificially smoothes the kriging weights similar to a nugget effect. Our primary focus will be showing how the reduced rank decomposition propagates through kriging empirically. In addition, we show further evidence for our

  5. Quality indicators in the mobile industry rankings based on indicators of customer satisfaction with the hybrid approach DEMATEL and ANP appropriate strategy based on gray system

    Directory of Open Access Journals (Sweden)

    Ashouri Fatemeh

    2016-01-01

    Full Text Available The quality of services as a vital element in the strategic competitiveness and commercial success are various methods have been developed to evaluate it. Prioritizing qualitative indicators based on the quality of mobile phone services enables the company gives top priority due to the higher percentage of satisfied customers provide. This study tries to customer satisfaction according to criteria to prioritize mobile operators pay qualitative characteristics. A sample consisted of 450 individuals (46% women, 54% men from IRANCELL operator (Iran in 2015 which selected randomly. Results shows between four considered strategies maximum priorities belong to S1 which is denote to more services beyond customer expectations.

  6. Sign rank versus Vapnik-Chervonenkis dimension

    Science.gov (United States)

    Alon, N.; Moran, Sh; Yehudayoff, A.

    2017-12-01

    This work studies the maximum possible sign rank of sign (N × N)-matrices with a given Vapnik-Chervonenkis dimension d. For d=1, this maximum is three. For d=2, this maximum is \\widetilde{\\Theta}(N1/2). For d >2, similar but slightly less accurate statements hold. The lower bounds improve on previous ones by Ben-David et al., and the upper bounds are novel. The lower bounds are obtained by probabilistic constructions, using a theorem of Warren in real algebraic topology. The upper bounds are obtained using a result of Welzl about spanning trees with low stabbing number, and using the moment curve. The upper bound technique is also used to: (i) provide estimates on the number of classes of a given Vapnik-Chervonenkis dimension, and the number of maximum classes of a given Vapnik-Chervonenkis dimension--answering a question of Frankl from 1989, and (ii) design an efficient algorithm that provides an O(N/log(N)) multiplicative approximation for the sign rank. We also observe a general connection between sign rank and spectral gaps which is based on Forster's argument. Consider the adjacency (N × N)-matrix of a Δ-regular graph with a second eigenvalue of absolute value λ and Δ ≤ N/2. We show that the sign rank of the signed version of this matrix is at least Δ/λ. We use this connection to prove the existence of a maximum class C\\subseteq\\{+/- 1\\}^N with Vapnik-Chervonenkis dimension 2 and sign rank \\widetilde{\\Theta}(N1/2). This answers a question of Ben-David et al. regarding the sign rank of large Vapnik-Chervonenkis classes. We also describe limitations of this approach, in the spirit of the Alon-Boppana theorem. We further describe connections to communication complexity, geometry, learning theory, and combinatorics. Bibliography: 69 titles.

  7. Calculating life years from transplant (LYFT): methods for kidney and kidney-pancreas candidates.

    Science.gov (United States)

    Wolfe, R A; McCullough, K P; Schaubel, D E; Kalbfleisch, J D; Murray, S; Stegall, M D; Leichtman, A B

    2008-04-01

    The Organ Procurement and Transplantation Network (OPTN) Kidney Committee is considering a proposal for a new deceased donor kidney allocation system. Among the components under consideration is a strategy to rank candidates in part by the estimated incremental years of life that are expected to be achieved with a transplant from a specific available deceased donor, computed as the difference in expected median lifespan with that transplant compared with remaining on dialysis. This concept has been termed life years from transplant or LYFT. Median lifespans could be calculated, based on objective medical criteria, for each candidate when a deceased donor kidney becomes available, based on Cox regression models using current candidate and donor medical information. The distribution of the calculated LYFT scores for an average nonexpanded criteria donor kidney is similar across candidate sex, race/ethnicity, insurance status and, with the exception of diabetes, diagnosis. LYFT scores tend to be higher for younger candidates and lower for diabetics receiving a kidney-alone rather than a simultaneous kidney-pancreas transplant. Prioritizing candidates with higher LYFT scores for each available kidney could substantially increase total years of life among both transplant candidates and recipients. LYFT is also a powerful metric for assessing trends in allocation outcomes and for comparing alternative allocation systems.

  8. Candidate Genes Within Tissue Culture Regeneration QTL Revisited with a Linkage Map Based on Transcript Derived Markers

    Science.gov (United States)

    Green plant regeneration from tissue culture is under the genetic control of multiple genes. Candidate genes for regeneration have been identified in multiple species using QTL and microarray analyses, and some of these genes have been verified as improving regeneration through transformation. Multi...

  9. LogDet Rank Minimization with Application to Subspace Clustering.

    Science.gov (United States)

    Kang, Zhao; Peng, Chong; Cheng, Jie; Cheng, Qiang

    2015-01-01

    Low-rank matrix is desired in many machine learning and computer vision problems. Most of the recent studies use the nuclear norm as a convex surrogate of the rank operator. However, all singular values are simply added together by the nuclear norm, and thus the rank may not be well approximated in practical problems. In this paper, we propose using a log-determinant (LogDet) function as a smooth and closer, though nonconvex, approximation to rank for obtaining a low-rank representation in subspace clustering. Augmented Lagrange multipliers strategy is applied to iteratively optimize the LogDet-based nonconvex objective function on potentially large-scale data. By making use of the angular information of principal directions of the resultant low-rank representation, an affinity graph matrix is constructed for spectral clustering. Experimental results on motion segmentation and face clustering data demonstrate that the proposed method often outperforms state-of-the-art subspace clustering algorithms.

  10. Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment

    Directory of Open Access Journals (Sweden)

    Benjamin Siart

    2016-11-01

    Full Text Available Status within social hierarchies has great effects on the lives of socially organized mammals. Its effects on human behavior and related physiology however is relatively little studied. The present study investigated the impact of military rank on fairness and behavior in relation to salivary cortisol (C and testosterone (T levels in male soldiers. For this purpose 180 members of the Austrian Armed Forces belonging to two distinct rank groups participated in two variations of a computer-based guard duty allocation experiment. The rank groups were 1 warrant officers (High Rank, HR and 2 enlisted men (Low Rank, LR. One soldier from each rank group participated in every experiment. At the beginning of the experiment, one participant was assigned to start standing guard and the other participant at rest. The participant who started at rest could choose if and when to relieve his fellow soldier and therefore had control over the experiment. In order to trigger perception of unfair behavior, an additional experiment was conducted which was manipulated by the experimenter. In the manipulated version both soldiers started in the standing guard position and were never relieved, believing that their opponent was at rest, not relieving them. Our aim was to test whether unfair behavior causes a physiological reaction. Saliva samples for hormone analysis were collected at regular intervals throughout the experiment.We found that in the un-manipulated setup high-ranking soldiers spent less time standing guard than lower ranking individuals. Rank was a significant predictor for C but not for T levels during the experiment. C levels in the HR group were higher than in LR group. C levels were also elevated in the manipulated experiment compared to the un-manipulated experiment, especially in LR. We assume that the elevated C levels in HR were caused by HR feeling their status challenged by the situation of having to negotiate with an individual of lower military

  11. Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment.

    Science.gov (United States)

    Siart, Benjamin; Pflüger, Lena S; Wallner, Bernard

    2016-01-01

    Status within social hierarchies has great effects on the lives of socially organized mammals. Its effects on human behavior and related physiology, however, is relatively little studied. The present study investigated the impact of military rank on fairness and behavior in relation to salivary cortisol (C) and testosterone (T) levels in male soldiers. For this purpose 180 members of the Austrian Armed Forces belonging to two distinct rank groups participated in two variations of a computer-based guard duty allocation experiment. The rank groups were (1) warrant officers (high rank, HR) and (2) enlisted men (low rank, LR). One soldier from each rank group participated in every experiment. At the beginning of the experiment, one participant was assigned to start standing guard and the other participant at rest. The participant who started at rest could choose if and when to relieve his fellow soldier and therefore had control over the experiment. In order to trigger perception of unfair behavior, an additional experiment was conducted which was manipulated by the experimenter. In the manipulated version both soldiers started in the standing guard position and were never relieved, believing that their opponent was at rest, not relieving them. Our aim was to test whether unfair behavior causes a physiological reaction. Saliva samples for hormone analysis were collected at regular intervals throughout the experiment. We found that in the un-manipulated setup high-ranking soldiers spent less time standing guard than lower ranking individuals. Rank was a significant predictor for C but not for T levels during the experiment. C levels in the HR group were higher than in the LR group. C levels were also elevated in the manipulated experiment compared to the un-manipulated experiment, especially in LR. We assume that the elevated C levels in HR were caused by HR feeling their status challenged by the situation of having to negotiate with an individual of lower military rank

  12. A Modification on the Hesitant Fuzzy Set Lexicographical Ranking Method

    Directory of Open Access Journals (Sweden)

    Xiaodi Liu

    2016-12-01

    Full Text Available Recently, a novel hesitant fuzzy set (HFS ranking technique based on the idea of lexicographical ordering is proposed and an example is presented to demonstrate that the proposed ranking method is invariant with multiple occurrences of any element of a hesitant fuzzy element (HFE. In this paper, we show by examples that the HFS lexicographical ordering method is sometimes invalid, and a modified ranking method is presented. In comparison with the HFS lexicographical ordering method, the modified ranking method is more reasonable in more general cases.

  13. Smokes and obscurants: A health and environmental effects data base assessment: A first-order, environmental screening and ranking of Army smokes and obscurants: Phase 1 report

    Energy Technology Data Exchange (ETDEWEB)

    Shinn, J.H.; Martins, S.A.; Cederwall, P.L.; Gratt, L.B.

    1985-03-01

    An initial environmental screening and ranking is provided for each Army smoke and obscurant (S and O) depending on smoke type and smoke-generating device. This was done according to the magnitude of the impact area, the characteristic environmental concentration, the relative inhalation toxicity, the relative toxicity when ingested by animals, the aquatic toxicity, the environmental mobility when freshly deposited, and the ultimate mobility and fate in the environment. The major smoke types considered were various forms of white phosphorus (WP), red phosphorus (RP), hexachloroethane-derived smokes (HC), fog oil (SGF-2), diesel fuel smokes (DF), and some infrared obscuring agents (IR).

  14. 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.

  15. Long-term creep rupture strength of weldment of Fe-Ni based alloy as candidate tube and pipe for advanced USC boilers

    Energy Technology Data Exchange (ETDEWEB)

    Bao, Gang; Sato, Takashi [Babcok-Hitachi K.K., Hiroshima (Japan). Kure Research Laboratory; Marumoto, Yoshihide [Babcok-Hitachi K.K., Hiroshima (Japan). Kure Div.

    2010-07-01

    A lot of works have been going to develop 700C USC power plant in Europe and Japan. High strength Ni based alloys such as Alloy 617, Alloy 740 and Alloy 263 were the candidates for boiler tube and pipe in Europe, and Fe-Ni based alloy HR6W (45Ni-24Fe-23Cr-7W-Ti) is also a candidate for tube and pipe in Japan. One of the Key issues to achieve 700 C boilers is the welding process of these alloys. Authors investigated the weldability and the long-term creep rupture strength of HR6W tube. The weldments were investigated metallurgically to find proper welding procedure and creep rupture tests are ongoing exceed 38,000 hours. The long-term creep rupture strengths of the HST weld joints are similar to those of parent metals and integrity of the weldments was confirmed based on with other mechanical testing results. (orig.)

  16. PageRank of integers

    Science.gov (United States)

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

    2012-10-01

    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.

  17. Immunogenicity and protective efficacy of candidate universal influenza A nanovaccines produced in plants by Tobacco mosaic virus-based vectors.

    Science.gov (United States)

    Petukhova, Natalia V; Gasanova, Tatiana V; Stepanova, Liudmila A; Rusova, Oxana A; Potapchuk, Marina V; Korotkov, Alexandr V; Skurat, Eugene V; Tsybalova, Liudmila M; Kiselev, Oleg I; Ivanov, Peter A; Atabekov, Joseph G

    2013-01-01

    A new approach for super-expression of the influenza virus epitope M2e in plants has been developed on the basis of a recombinant Tobacco mosaic virus (TMV, strain U1) genome designed for Agrobacterium-mediated delivery into the plant cell nucleus. The TMV coat protein (CP) served as a carrier and three versions of the M2e sequence were inserted into the surface loop between amino acid residues 155 and 156. Cysteine residues in the heterologous peptide were thought likely to impede efficient assembly of chimeric particles. Therefore, viral vectors TMV-M2e-ala and TMV-M2e-ser were constructed in which cysteine codons 17 and 19 of the M2e epitope were substituted by codons for serine or alanine. Agroinfiltration experiments proved that the chimeric viruses were capable of systemically infecting Nicotiana benthamiana plants. Antisera raised against TMV-M2e-ala virions appear to contain far more antibodies specific to influenza virus M2e than those specific to TMV carrier particle (ratio 5:1). Immunogold electron microscopy showed that the 2-epitopes were uniformly distributed and tightly packed on the surface of the chimeric TMV virions. Apparently, the majority of the TMV CP-specific epitopes in the chimeric TMV-M2e particles are hidden from the immune system by the M2e epitopes exposed on the particle surface. The profile of IgG subclasses after immunization of mice with TMV-M2e-ser and TMV-M2e-ala was evaluated. Immunization with TMV-M2e-ala induced a significant difference between the levels of IgG1 and IgG2a (IgG1/IgG2a=3.2). Mice immunized with the chimeric viruses were resistant to five lethal doses (LD50) of the homologous influenza virus strain, A/PR/8/34 (H1N1) and TMV-M2e-ala also gave partial protection (5LD50, 70% of survival rate) against a heterologous strain influenza A/California/04/2009 (H1N1) (4 amino acid changes in M2e). These results indicate that a new generation candidate universal nanovaccine against influenza based on a recombinant TMV

  18. Computational Ranking of Yerba Mate Small Molecules Based on Their Predicted Contribution to Antibacterial Activity against Methicillin-Resistant Staphylococcus aureus.

    Directory of Open Access Journals (Sweden)

    Caroline S Rempe

    Full Text Available The aqueous extract of yerba mate, a South American tea beverage made from Ilex paraguariensis leaves, has demonstrated bactericidal and inhibitory activity against bacterial pathogens, including methicillin-resistant Staphylococcus aureus (MRSA. The gas chromatography-mass spectrometry (GC-MS analysis of two unique fractions of yerba mate aqueous extract revealed 8 identifiable small molecules in those fractions with antimicrobial activity. For a more comprehensive analysis, a data analysis pipeline was assembled to prioritize compounds for antimicrobial testing against both MRSA and methicillin-sensitive S. aureus using forty-two unique fractions of the tea extract that were generated in duplicate, assayed for activity, and analyzed with GC-MS. As validation of our automated analysis, we checked our predicted active compounds for activity in literature references and used authentic standards to test for antimicrobial activity. 3,4-dihydroxybenzaldehyde showed the most antibacterial activity against MRSA at low concentrations in our bioassays. In addition, quinic acid and quercetin were identified using random forests analysis and 5-hydroxy pipecolic acid was identified using linear discriminant analysis. We also generated a ranked list of unidentified compounds that may contribute to the antimicrobial activity of yerba mate against MRSA. Here we utilized GC-MS data to implement an automated analysis that resulted in a ranked list of compounds that likely contribute to the antimicrobial activity of aqueous yerba mate extract against MRSA.

  19. 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.

  20. Aggregate Interview Method of ranking orthopedic applicants predicts future performance.

    Science.gov (United States)

    Geissler, Jacqueline; VanHeest, Ann; Tatman, Penny; Gioe, Terence

    2013-07-01

    This article evaluates and describes a process of ranking orthopedic applicants using what the authors term the Aggregate Interview Method. The authors hypothesized that higher-ranking applicants using this method at their institution would perform better than those ranked lower using multiple measures of resident performance. A retrospective review of 115 orthopedic residents was performed at the authors' institution. Residents were grouped into 3 categories by matching rank numbers: 1-5, 6-14, and 15 or higher. Each rank group was compared with resident performance as measured by faculty evaluations, the Orthopaedic In-Training Examination (OITE), and American Board of Orthopaedic Surgery (ABOS) test results. Residents ranked 1-5 scored significantly better on patient care, behavior, and overall competence by faculty evaluation (Porthopedic resident candidates who scored highly on the Accreditation Council for Graduate Medical Education resident core competencies as measured by faculty evaluations, performed above the national average on the OITE, and passed the ABOS part 1 examination at rates exceeding the national average. Copyright 2013, SLACK Incorporated.

  1. Ranking production units according to marginal efficiency contribution

    DEFF Research Database (Denmark)

    Ghiyasi, Mojtaba; Hougaard, Jens Leth

    League tables associated with various forms of service activities from schools to hospitals illustrate the public need for ranking institutions by their productive performance. We present a new method for ranking production units which is based on each units marginal contribution to the technical...

  2. WISER ranking of the African national libraries' websites | Gupta ...

    African Journals Online (AJOL)

    Data collection has been done with the help of Google search engine and Check Page Rank tool. This study highlighted the fact that the ranking based on web impact factor was not much reliable and it is biased towards the small number of webpages and in-links. In the present study WISER, a combined web indicator was ...

  3. Monte Carlo methods of PageRank computation

    NARCIS (Netherlands)

    Litvak, Nelli

    2004-01-01

    We describe and analyze an on-line Monte Carlo method of PageRank computation. The PageRank is being estimated basing on results of a large number of short independent simulation runs initiated from each page that contains outgoing hyperlinks. The method does not require any storage of the hyperlink

  4. Economic Research at National Liberal Arts Colleges: School Rankings.

    Science.gov (United States)

    Hartley, James E.; Robinson, Michael D.

    1997-01-01

    Presents a comprehensive ranking of all national liberal arts colleges based on publications cataloged by the "Journal of Economic Literature" (JEL) from 1989-1994. Concludes that, although economics research is important at the highest ranked colleges, it remains a secondary consideration at the rest. Briefly discusses previous rankings…

  5. Bioinformatics Approach Based Research of Profile Protein Carbonic Anhydrase II Analysis as a Potential Candidate Cause Autism for The Variation of Learning Subjects Biotechnology

    Directory of Open Access Journals (Sweden)

    Dian Eka A. F. Ningrum

    2017-03-01

    Full Text Available This study aims to determine the needs of learning variations on Biotechnology courses using bioinformatics approaches. One example of applied use of bioinformatics in biotechnology course is the analysis of protein profiles carbonic anhydrase II as a potential cause of autism candidate. This research is a qualitative descriptive study consisted of two phases. The first phase of the data obtained from observations of learning, student questionnaires, and questionnaires lecturer. Results from the first phase, namely the need for variations learning in Biotechnology course using bioinformatics. Collecting data on the second stage uses three webserver to predict the target protein and scientific articles. Visualization of proteins using PyMOL software. 3 based webserver which is used, the candidate of target proteins associated with autism is carbonic anhydrase II. The survey results revealed that the protein carbonic anhydrase II as a potential candidate for the cause of autism classified metaloenzim are able to bind with heavy metals. The content of heavy metals in autistic patients high that affect metabolism. This prediction of protein candidate cause autism is applied use to solve the problem in society, so that can achieve the learning outcome in biotechnology course.

  6. Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients

    DEFF Research Database (Denmark)

    Overgaard, Anne Julie; Thingholm, Tine Engberg; Larsen, Martin R

    2010-01-01

    immunoassay confirmed the overall protein expression patterns observed by the iTRAQ analysis. CONCLUSION: The candidate biomarkers discovered in this cross-sectional cohort may turn out to be progression biomarkers and might have several clinical applications in the treatment and monitoring of diabetic......INTRODUCTION: As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy. METHODS: Proteins derived from plasma from a cross......-sectional cohort of 123 type 1 diabetic patients previously diagnosed as normoalbuminuric, microalbuminuric or macroalbuminuric were enriched with hexapeptide library beads and subsequently pooled within three groups. Proteins from the three groups were compared by online liquid chromatography and tandem mass...

  7. 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.

  8. 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.

  9. 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.

  10. University Ranking Systems; Criteria and Critiques

    OpenAIRE

    Saka, Yavuz; YAMAN, Süleyman

    2011-01-01

    The purpose of this paper is to explore international university ranking systems. As a compilation study this paper provides specific criteria that each ranking system uses and main critiques regarding these ranking systems. Since there are many ranking systems in this area of research, this study focused on only most cited and referred ranking systems. As there is no consensus in terms of the criteria that these systems use, this paper has no intention of identifying the best ranking system ...

  11. Biology of RANK, RANKL, and osteoprotegerin

    Science.gov (United States)

    Boyce, Brendan F; Xing, Lianping

    2007-01-01

    The discovery of the receptor activator of nuclear factor-κB ligand (RANKL)/RANK/osteoprotegerin (OPG) system and its role in the regulation of bone resorption exemplifies how both serendipity and a logic-based approach can identify factors that regulate cell function. Before this discovery in the mid to late 1990s, it had long been recognized that osteoclast formation was regulated by factors expressed by osteoblast/stromal cells, but it had not been anticipated that members of the tumor necrosis factor superfamily of ligands and receptors would be involved or that the factors involved would have extensive functions beyond bone remodeling. RANKL/RANK signaling regulates the formation of multinucleated osteoclasts from their precursors as well as their activation and survival in normal bone remodeling and in a variety of pathologic conditions. OPG protects the skeleton from excessive bone resorption by binding to RANKL and preventing it from binding to its receptor, RANK. Thus, RANKL/OPG ratio is an important determinant of bone mass and skeletal integrity. Genetic studies in mice indicate that RANKL/RANK signaling is also required for lymph node formation and mammary gland lactational hyperplasia, and that OPG also protects arteries from medial calcification. Thus, these tumor necrosis factor superfamily members have important functions outside bone. Although our understanding of the mechanisms whereby they regulate osteoclast formation has advanced rapidly during the past 10 years, many questions remain about their roles in health and disease. Here we review our current understanding of the role of the RANKL/RANK/OPG system in bone and other tissues. PMID:17634140

  12. Regression Estimator Using Double Ranked Set Sampling

    Directory of Open Access Journals (Sweden)

    Hani M. Samawi

    2002-06-01

    Full Text Available The performance of a regression estimator based on the double ranked set sample (DRSS scheme, introduced by Al-Saleh and Al-Kadiri (2000, is investigated when the mean of the auxiliary variable X is unknown. Our primary analysis and simulation indicates that using the DRSS regression estimator for estimating the population mean substantially increases relative efficiency compared to using regression estimator based on simple random sampling (SRS or ranked set sampling (RSS (Yu and Lam, 1997 regression estimator.  Moreover, the regression estimator using DRSS is also more efficient than the naïve estimators of the population mean using SRS, RSS (when the correlation coefficient is at least 0.4 and DRSS for high correlation coefficient (at least 0.91. The theory is illustrated using a real data set of trees.

  13. Identification of candidate domestication regions in the radish genome based on high-depth resequencing analysis of 17 genotypes.

    Science.gov (United States)

    Kim, Namshin; Jeong, Young-Min; Jeong, Seongmun; Kim, Goon-Bo; Baek, Seunghoon; Kwon, Young-Eun; Cho, Ara; Choi, Sang-Bong; Kim, Jiwoong; Lim, Won-Jun; Kim, Kyoung Hyoun; Park, Won; Kim, Jae-Yoon; Kim, Jin-Hyun; Yim, Bomi; Lee, Young Joon; Chun, Byung-Moon; Lee, Young-Pyo; Park, Beom-Seok; Yu, Hee-Ju; Mun, Jeong-Hwan

    2016-09-01

    This study provides high-quality variation data of diverse radish genotypes. Genome-wide SNP comparison along with RNA-seq analysis identified candidate genes related to domestication that have potential as trait-related markers for genetics and breeding of radish. Radish (Raphanus sativus L.) is an annual root vegetable crop that also encompasses diverse wild species. Radish has a long history of domestication, but the origins and selective sweep of cultivated radishes remain controversial. Here, we present comprehensive whole-genome resequencing analysis of radish to explore genomic variation between the radish genotypes and to identify genetic bottlenecks due to domestication in Asian cultivars. High-depth resequencing and multi-sample genotyping analysis of ten cultivated and seven wild accessions obtained 4.0 million high-quality homozygous single-nucleotide polymorphisms (SNPs)/insertions or deletions. Variation analysis revealed that Asian cultivated radish types are closely related to wild Asian accessions, but are distinct from European/American cultivated radishes, supporting the notion that Asian cultivars were domesticated from wild Asian genotypes. SNP comparison between Asian genotypes identified 153 candidate domestication regions (CDRs) containing 512 genes. Network analysis of the genes in CDRs functioning in plant signaling pathways and biochemical processes identified group of genes related to root architecture, cell wall, sugar metabolism, and glucosinolate biosynthesis. Expression profiling of the genes during root development suggested that domestication-related selective advantages included a main taproot with few branched lateral roots, reduced cell wall rigidity and favorable taste. Overall, this study provides evolutionary insights into domestication-related genetic selection in radish as well as identification of gene candidates with the potential to act as trait-related markers for background selection of elite lines in molecular

  14. Low-rank approximation pursuit for matrix completion

    Science.gov (United States)

    Xu, An-Bao; Xie, Dongxiu

    2017-10-01

    We consider the matrix completion problem that aims to construct a low rank matrix X that approximates a given large matrix Y from partially known sample data in Y . In this paper we introduce an efficient greedy algorithm for such matrix completions. The greedy algorithm generalizes the orthogonal rank-one matrix pursuit method (OR1MP) by creating s ⩾ 1 candidates per iteration by low-rank matrix approximation. Due to selecting s ⩾ 1 candidates in each iteration step, our approach uses fewer iterations than OR1MP to achieve the same results. Our algorithm is a randomized low-rank approximation method which makes it computationally inexpensive. The algorithm comes in two forms, the standard one which uses the Lanzcos algorithm to find partial SVDs, and another that uses a randomized approach for this part of its work. The storage complexity of this algorithm can be reduced by using an weight updating rule as an economic version algorithm. We prove that all our algorithms are linearly convergent. Numerical experiments on image reconstruction and recommendation problems are included that illustrate the accuracy and efficiency of our algorithms.

  15. Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining

    DEFF Research Database (Denmark)

    Hulsegge, Ina; Woelders, Henri; Smits, Mari

    2013-01-01

    and processes in brain areas and pituitary involved in reproductive traits in cattle using information derived from three different data sources: gene expression, protein-protein interactions, and literature. We identified 59, 89, 53, 23, and 71 genes in bovine amygdala, dorsal hypothalamus, hippocampus......, pituitary, and ventral hypothalamus, respectively, potentially involved in processes underlying estrus and estrous behavior. Functional annotation of the candidate genes points to a number of tissue-specific processes of which the "neurotransmitter/ion channel/synapse" process in the amygdala, "steroid...

  16. Ciudad: Identidad y rankings

    Directory of Open Access Journals (Sweden)

    ELÍAS MAS SERRA

    2009-12-01

    Full Text Available A La ciudad, o a la forma de hacerla, se le han otorgado a lo largo de la historia diversos adjetivos, más o menos justificados. Hoy se habla de la ciudad del conocimiento y la innovación como factores determinantes de la evolución de la urbe. Ya se ha reconocido que muchas de estas expresiones no se quedan más que en metáforas. Pero es importante profundizar en el valor añadido que aporta una conceptuación de este tipo en el ámbito de la gestión económica y de la obtención de plusvalías. También importa reconocer que el hecho de la ciudad es algo independiente y que la mejor valoración de una ciudad, en un amplio contexto, reside en los valores que le aporta su identidad; por ello, el conocimiento o la innovación supuestos no deben pasar por la mediatización, vía globalización, o el olvido de la realidad histórica constituida y construida.For cities, and forms of constructingthem through history, diverse adjectives, some more and some less justified, have been provided. Nowadays, much is made of the city of knowledge and of innovation in the evolution of urban forms. It is recognised that many of these expressions remain metaphorical, but it is important to establish the added value generated by a conceptualization of this kind in the field of economic management and the generation of capital gains. Also important is the recognition that the city is something independent and that an improved valuation of a city, in a broad sense, is based on the values provided by its identity; as such, supposed knowledge or innovation should not be overly managed through the media, via globalization, or through forgetting its constituted and constructed historical reality.

  17. Ranking species in mutualistic networks.

    Science.gov (United States)

    Domínguez-García, Virginia; Muñoz, Miguel A

    2015-02-02

    Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic "nested" structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm--similar in spirit to Google's PageRank but with a built-in non-linearity--here we propose a method which--by exploiting their nested architecture--allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made.

  18. 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...

  19. VennPainter: A Tool for the Comparison and Identification of Candidate Genes Based on Venn Diagrams.

    Directory of Open Access Journals (Sweden)

    Guoliang Lin

    Full Text Available VennPainter is a program for depicting unique and shared sets of genes lists and generating Venn diagrams, by using the Qt C++ framework. The software produces Classic Venn, Edwards' Venn and Nested Venn diagrams and allows for eight sets in a graph mode and 31 sets in data processing mode only. In comparison, previous programs produce Classic Venn and Edwards' Venn diagrams and allow for a maximum of six sets. The software incorporates user-friendly features and works in Windows, Linux and Mac OS. Its graphical interface does not require a user to have programing skills. Users can modify diagram content for up to eight datasets because of the Scalable Vector Graphics output. VennPainter can provide output results in vertical, horizontal and matrix formats, which facilitates sharing datasets as required for further identification of candidate genes. Users can obtain gene lists from shared sets by clicking the numbers on the diagram. Thus, VennPainter is an easy-to-use, highly efficient, cross-platform and powerful program that provides a more comprehensive tool for identifying candidate genes and visualizing the relationships among genes or gene families in comparative analysis.

  20. 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.

  1. The use of TCP based EUD to rank and compare lung radiotherapy plans: in-silico study to evaluate the correlation between TCP with physical quality indices.

    Science.gov (United States)

    Chaikh, Abdulhamid; Balosso, Jacques

    2017-06-01

    To apply the equivalent uniform dose (EUD) radiobiological model to estimate the tumor control probability (TCP) scores for treatment plans using different radiobiological parameter settings, and to evaluate the correlation between TCP and physical quality indices of the treatment plans. Ten radiotherapy treatment plans for lung cancer were generated. The dose distributions were calculated using anisotropic analytical algorithm (AAA). Dose parameters and quality indices derived from dose volume histograms (DVH) for target volumes were evaluated. The predicted TCP was computed using EUD model with tissue-specific parameter (a=-10). The assumed radiobiological parameter setting for adjuvant therapy [tumor dose to control 50% of the tumor (TCD50) =36.5 Gy and γ50=0.72] and curative intent (TCD50=51.24 Gy and γ50=0.83) were used. The bootstrap method was used to estimate the 95% confidence interval (95% CI). The coefficients (ρ) from Spearman's rank test were calculated to assess the correlation between quality indices with TCP. Wilcoxon paired test was used to calculate P value. The 95% CI of TCP were 70.6-81.5 and 46.6-64.7, respectively, for adjuvant radiotherapy and curative intent. The TCP outcome showed a positive and good correlation with calculated dose to 95% of the target volume (D95%) and minimum dose (Dmin). Consistently, TCP correlate negatively with heterogeneity indices. This study confirms that more relevant and robust radiobiological parameters setting should be integrated according to cancer type. The positive correlation with quality indices gives chance to improve the clinical out-come by optimizing the treatment plans to maximize the Dmin and D95%. This attempt to increase the TCP should be carried out with the respect of dose constraints for organs at risks. However, the negative correlation with heterogeneity indices shows that the optimization of beam arrangements could be also useful. Attention should be paid to obtain an appropriate

  2. Filtering and ranking techniques for automated selection of high-quality 16S rRNA gene sequences.

    Science.gov (United States)

    De Smet, Wim; De Loof, Karel; De Vos, Paul; Dawyndt, Peter; De Baets, Bernard

    2013-12-01

    StrainInfo has augmented its type strain and species/subspecies passports with a recommendation for a high-quality 16S rRNA gene sequence available from the public sequence databases. These recommendations are generated by an automated pipeline that collects all candidate 16S rRNA gene sequences for a prokaryotic type strain, filters out low-quality sequences and retains a high-quality sequence from the remaining pool. Due to thorough automation, recommendations can be renewed daily using the latest updates of the public sequence databases and the latest species descriptions. We discuss the quality criteria constructed to filter and rank available 16S rRNA gene sequences, and show how a partially ordered set (poset) ranking algorithm can be applied to solve the multi-criteria ranking problem of selecting the best candidate sequence. The proof of concept of the recommender system is validated by comparing the results of automated selection with an expert selection made in the All-Species Living Tree Project. Based on these validation results, the pipeline may reliably be applied for non-type strains and developed further for the automated selection of housekeeping genes. Copyright © 2013 Elsevier GmbH. All rights reserved.

  3. 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.

  4. Generation and Characterization of Live Attenuated Influenza A(H7N9 Candidate Vaccine Virus Based on Russian Donor of Attenuation.

    Directory of Open Access Journals (Sweden)

    Svetlana Shcherbik

    Full Text Available Avian influenza A (H7N9 virus has emerged recently and continues to cause severe disease with a high mortality rate in humans prompting the development of candidate vaccine viruses. Live attenuated influenza vaccines (LAIV are 6:2 reassortant viruses containing the HA and NA gene segments from wild type influenza viruses to induce protective immune responses and the six internal genes from Master Donor Viruses (MDV to provide temperature sensitive, cold-adapted and attenuated phenotypes.LAIV candidate A/Anhui/1/2013(H7N9-CDC-LV7A (abbreviated as CDC-LV7A, based on the Russian MDV, A/Leningrad/134/17/57 (H2N2, was generated by classical reassortment in eggs and retained MDV temperature-sensitive and cold-adapted phenotypes. CDC-LV7A had two amino acid substitutions N123D and N149D (H7 numbering in HA and one substitution T10I in NA. To evaluate the role of these mutations on the replication capacity of the reassortants in eggs, the recombinant viruses A(H7N9RG-LV1 and A(H7N9RG-LV2 were generated by reverse genetics. These changes did not alter virus antigenicity as ferret antiserum to CDC-LV7A vaccine candidate inhibited hemagglutination by homologous A(H7N9 virus efficiently. Safety studies in ferrets confirmed that CDC-LV7A was attenuated compared to wild-type A/Anhui/1/2013. In addition, the genetic stability of this vaccine candidate was examined in eggs and ferrets by monitoring sequence changes acquired during virus replication in the two host models. No changes in the viral genome were detected after five passages in eggs. However, after ten passages additional mutations were detected in the HA gene. The vaccine candidate was shown to be stable in the ferret model; post-vaccination sequence data analysis showed no changes in viruses collected in nasal washes present at day 5 or day 7.Our data indicate that the A/Anhui/1/2013(H7N9-CDC-LV7A reassortant virus is a safe and genetically stable candidate vaccine virus that is now available for

  5. The Chemistry Scoring Index (CSI: A Hazard-Based Scoring and Ranking Tool for Chemicals and Products Used in the Oil and Gas Industry

    Directory of Open Access Journals (Sweden)

    Tim Verslycke

    2014-06-01

    Full Text Available A large portfolio of chemicals and products is needed to meet the wide range of performance requirements of the oil and gas industry. The oil and gas industry is under increased scrutiny from regulators, environmental groups, the public, and other stakeholders for use of their chemicals. In response, industry is increasingly incorporating “greener” products and practices but is struggling to define and quantify what exactly constitutes “green” in the absence of a universally accepted definition. We recently developed the Chemistry Scoring Index (CSI which is ultimately intended to be a globally implementable tool that comprehensively scores and ranks hazards to human health, safety, and the environment for products used in oil and gas operations. CSI scores are assigned to products designed for the same use (e.g., surfactants, catalysts on the basis of product composition as well as intrinsic hazard properties and data availability for each product component. As such, products with a lower CSI score within a product use group are considered to have a lower intrinsic hazard compared to other products within the same use group. The CSI provides a powerful tool to evaluate relative product hazards; to review and assess product portfolios; and to aid in the formulation of products.

  6. Fast alogorithms for Bayesian uncertainty quantification in large-scale linear inverse problems based on low-rank partial Hessian approximations

    Energy Technology Data Exchange (ETDEWEB)

    Akcelik, Volkan [ORNL; Flath, Pearl [University of Texas, Austin; Ghattas, Omar [University of Texas, Austin; Hill, Judith C [ORNL; Van Bloemen Waanders, Bart [Sandia National Laboratories (SNL); Wilcox, Lucas [University of Texas, Austin

    2011-01-01

    We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inference. When the noise and prior probability densities are Gaussian, the solution to the inverse problem is also Gaussian, and is thus characterized by the mean and covariance matrix of the posterior probability density. Unfortunately, explicitly computing the posterior covariance matrix requires as many forward solutions as there are parameters, and is thus prohibitive when the forward problem is expensive and the parameter dimension is large. However, for many ill-posed inverse problems, the Hessian matrix of the data misfit term has a spectrum that collapses rapidly to zero. We present a fast method for computation of an approximation to the posterior covariance that exploits the lowrank structure of the preconditioned (by the prior covariance) Hessian of the data misfit. Analysis of an infinite-dimensional model convection-diffusion problem, and numerical experiments on large-scale 3D convection-diffusion inverse problems with up to 1.5 million parameters, demonstrate that the number of forward PDE solves required for an accurate low-rank approximation is independent of the problem dimension. This permits scalable estimation of the uncertainty in large-scale ill-posed linear inverse problems at a small multiple (independent of the problem dimension) of the cost of solving the forward problem.

  7. Rankings Scientists, Journals and Countries using h-Index

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2016-01-01

    Full Text Available Indexes in scientometrics are based on citations. However, in contrast to the journal impact factor, which gives only the ranking of the scientific journals, ordered by impact factor, indexes in scientometrics are suitable for ranking of scientists, scientific journals and countries. In this paper the h-index, h5-index, the World ranking the top of 25 Highly Cited Researchers (h > 100 and the ranking of 25 scientists in Hungarian Institutions according to their Google Scholar Citations public profiles are considered. These indexes (h5-index are applied for making of the list of top 20 publications (journals and proceedings in the field of Robotics. The World ranking is done of the best 50 countries according to h-index in year 2014. Data are obtained from the portal Scimago.

  8. Integration of gene-based markers in a pearl millet genetic map for identification of candidate genes underlying drought tolerance quantitative trait loci

    Directory of Open Access Journals (Sweden)

    Sehgal Deepmala

    2012-01-01

    Full Text Available Abstract Background Identification of genes underlying drought tolerance (DT quantitative trait loci (QTLs will facilitate understanding of molecular mechanisms of drought tolerance, and also will accelerate genetic improvement of pearl millet through marker-assisted selection. We report a map based on genes with assigned functional roles in plant adaptation to drought and other abiotic stresses and demonstrate its use in identifying candidate genes underlying a major DT-QTL. Results Seventy five single nucleotide polymorphism (SNP and conserved intron spanning primer (CISP markers were developed from available expressed sequence tags (ESTs using four genotypes, H 77/833-2, PRLT 2/89-33, ICMR 01029 and ICMR 01004, representing parents of two mapping populations. A total of 228 SNPs were obtained from 30.5 kb sequenced region resulting in a SNP frequency of 1/134 bp. The positions of major pearl millet linkage group (LG 2 DT-QTLs (reported from crosses H 77/833-2 × PRLT 2/89-33 and 841B × 863B were added to the present consensus function map which identified 18 genes, coding for PSI reaction center subunit III, PHYC, actin, alanine glyoxylate aminotransferase, uridylate kinase, acyl-CoA oxidase, dipeptidyl peptidase IV, MADS-box, serine/threonine protein kinase, ubiquitin conjugating enzyme, zinc finger C- × 8-C × 5-C × 3-H type, Hd3, acetyl CoA carboxylase, chlorophyll a/b binding protein, photolyase, protein phosphatase1 regulatory subunit SDS22 and two hypothetical proteins, co-mapping in this DT-QTL interval. Many of these candidate genes were found to have significant association with QTLs of grain yield, flowering time and leaf rolling under drought stress conditions. Conclusions We have exploited available pearl millet EST sequences to generate a mapped resource of seventy five new gene-based markers for pearl millet and demonstrated its use in identifying candidate genes underlying a major DT-QTL in this species. The reported gene-based

  9. Classification of rank 2 cluster varieties

    DEFF Research Database (Denmark)

    Mandel, Travis

    We classify rank 2 cluster varieties (those whose corresponding skew-form has rank 2) according to the deformation type of a generic fiber U of their X-spaces, as defined by Fock and Goncharov. Our approach is based on the work of Gross, Hacking, and Keel for cluster varieties and log Calabi......-Yau surfaces. We find, for example, that U is "positive" (i.e., nearly affine) and either finite-type or non-acyclic (in the cluster sense) if and only if the monodromy of the tropicalization of U is one of Kodaira's matrices for the monodromy of an ellpitic fibration. In the positive cases, we also describe...... the action of the cluster modular group on the tropicalization of U....

  10. Association between Metabolic Syndrome and Job Rank.

    Science.gov (United States)

    Mehrdad, Ramin; Pouryaghoub, Gholamreza; Moradi, Mahboubeh

    2018-01-01

    The occupation of the people can influence the development of metabolic syndrome. To determine the association between metabolic syndrome and its determinants with the job rank in workers of a large car factory in Iran. 3989 male workers at a large car manufacturing company were invited to participate in this cross-sectional study. Demographic and anthropometric data of the participants, including age, height, weight, and abdominal circumference were measured. Blood samples were taken to measure lipid profile and blood glucose level. Metabolic syndrome was diagnosed in each participant based on ATPIII 2001 criteria. The workers were categorized based on their job rank into 3 groups of (1) office workers, (2) workers with physical exertion, and (3) workers with chemical exposure. The study characteristics, particularly the frequency of metabolic syndrome and its determinants were compared among the study groups. The prevalence of metabolic syndrome in our study was 7.7% (95% CI 6.9 to 8.5). HDL levels were significantly lower in those who had chemical exposure (p=0.045). Diastolic blood pressure was significantly higher in those who had mechanical exertion (p=0.026). The frequency of metabolic syndrome in the office workers, workers with physical exertion, and workers with chemical exposure was 7.3%, 7.9%, and 7.8%, respectively (p=0.836). Seemingly, there is no association between metabolic syndrome and job rank.

  11. An Efficient PageRank Approach for Urban Traffic Optimization

    Directory of Open Access Journals (Sweden)

    Florin Pop

    2012-01-01

    to determine optimal decisions for each traffic light, based on the solution given by Larry Page for page ranking in Web environment (Page et al. (1999. Our approach is similar with work presented by Sheng-Chung et al. (2009 and Yousef et al. (2010. We consider that the traffic lights are controlled by servers and a score for each road is computed based on efficient PageRank approach and is used in cost function to determine optimal decisions. We demonstrate that the cumulative contribution of each car in the traffic respects the main constrain of PageRank approach, preserving all the properties of matrix consider in our model.

  12. Where Are the Global Rankings Leading Us? An Analysis of Recent Methodological Changes and New Developments

    Science.gov (United States)

    Rauhvargers, Andrejs

    2014-01-01

    This article is based on the analysis of the changes in global university rankings and the new "products" based on rankings data in the period since mid-2011. It is a summary and continuation of the European University Association (EUA)-commissioned report "Global University Rankings Their Impact, Report II" which was launched…

  13. Rank distributions: Frequency vs. magnitude.

    Science.gov (United States)

    Velarde, Carlos; Robledo, Alberto

    2017-01-01

    We examine the relationship between two different types of ranked data, frequencies and magnitudes. We consider data that can be sorted out either way, through numbers of occurrences or size of the measures, as it is the case, say, of moon craters, earthquakes, billionaires, etc. We indicate that these two types of distributions are functional inverses of each other, and specify this link, first in terms of the assumed parent probability distribution that generates the data samples, and then in terms of an analog (deterministic) nonlinear iterated map that reproduces them. For the particular case of hyperbolic decay with rank the distributions are identical, that is, the classical Zipf plot, a pure power law. But their difference is largest when one displays logarithmic decay and its counterpart shows the inverse exponential decay, as it is the case of Benford law, or viceversa. For all intermediate decay rates generic differences appear not only between the power-law exponents for the midway rank decline but also for small and large rank. We extend the theoretical framework to include thermodynamic and statistical-mechanical concepts, such as entropies and configuration.

  14. Let Us Rank Journalism Programs

    Science.gov (United States)

    Weber, Joseph

    2014-01-01

    Unlike law, business, and medical schools, as well as universities in general, journalism schools and journalism programs have rarely been ranked. Publishers such as "U.S. News & World Report," "Forbes," "Bloomberg Businessweek," and "Washington Monthly" do not pay them much mind. What is the best…

  15. Predicted Coverage and Immuno-Safety of a Recombinant C-Repeat Region Based Streptococcus pyogenes Vaccine Candidate.

    Science.gov (United States)

    McNeilly, Celia; Cosh, Samantha; Vu, Therese; Nichols, Jemma; Henningham, Anna; Hofmann, Andreas; Fane, Anne; Smeesters, Pierre R; Rush, Catherine M; Hafner, Louise M; Ketheesan, Natkuman; Sriprakash, Kadaba S; McMillan, David J

    2016-01-01

    The C-terminal region of the M-protein of Streptococcus pyogenes is a major target for vaccine development. The major feature is the C-repeat region, consisting of 35-42 amino acid repeat units that display high but not perfect identity. SV1 is a S. pyogenes vaccine candidate that incorporates five 14mer amino acid sequences (called J14i variants) from differing C-repeat units in a single recombinant construct. Here we show that the J14i variants chosen for inclusion in SV1 are the most common variants in a dataset of 176 unique M-proteins. Murine antibodies raised against SV1 were shown to bind to each of the J14i variants present in SV1, as well as variants not present in the vaccine. Antibodies raised to the individual J14i variants were also shown to bind to multiple but different combinations of J14i variants, supporting the underlying rationale for the design of SV1. A Lewis Rat Model of valvulitis was then used to assess the capacity of SV1 to induce deleterious immune response associated with rheumatic heart disease. In this model, both SV1 and the M5 positive control protein were immunogenic. Neither of these antibodies were cross-reactive with cardiac myosin or collagen. Splenic T cells from SV1/CFA and SV1/alum immunized rats did not proliferate in response to cardiac myosin or collagen. Subsequent histological examination of heart tissue showed that 4 of 5 mice from the M5/CFA group had valvulitis and inflammatory cell infiltration into valvular tissue, whereas mice immunised with SV1/CFA, SV1/alum showed no sign of valvulitis. These results suggest that SV1 is a safe vaccine candidate that will elicit antibodies that recognise the vast majority of circulating GAS M-types.

  16. The Globalization of College and University Rankings

    Science.gov (United States)

    Altbach, Philip G.

    2012-01-01

    In the era of globalization, accountability, and benchmarking, university rankings have achieved a kind of iconic status. The major ones--the Academic Ranking of World Universities (ARWU, or the "Shanghai rankings"), the QS (Quacquarelli Symonds Limited) World University Rankings, and the "Times Higher Education" World…

  17. Locating Leaks with TrustRank Algorithm Support

    National Research Council Canada - National Science Library

    Luísa Ribeiro; Joaquim Sousa; Alfeu Sa Marques; Nuno E Simões

    2015-01-01

      This paper presents a methodology to quantify and to locate leaks. The original contribution is the use of a tool based on the TrustRank algorithm for the selection of nodes for pressure monitoring...

  18. A Feasibility Assessment of Behavioral-based Interviewing to Improve Candidate Selection for a Pulmonary and Critical Care Medicine Fellowship Program.

    Science.gov (United States)

    Tatem, Geneva; Kokas, Maria; Smith, Cathy L; DiGiovine, Bruno

    2017-04-01

    Traditional interviews for residency and fellowship training programs are an important component in the selection process, but can be of variable value due to a nonstandardized approach. We redesigned the candidate interview process for our large pulmonary and critical care medicine fellowship program in the United States using a behavioral-based interview (BBI) structure. The primary goal of this approach was to standardize the assessment of candidates within noncognitive domains with the goal of selecting those with the best fit for our institution's fellowship program. Eight faculty members attended two BBI workshops. The first workshop identified our program's "best fit" criteria using the framework of the Accreditation Council for Graduate Medical Education's six core competencies and additional behaviors that fit within our programs. BBI questions were then selected from a national database and refined based on the attributes deemed most important by our faculty. In the second workshop, faculty practiced the BBI format in mock interviews with third-year fellows. The interview process was further refined based on feedback from the interviewees, and then applied with fellowship candidates for the 2014 recruitment season. The 1-year pilot of behavioral-based interviewing allowed us to achieve consensus on the traits sought for our incoming fellows and to standardize the interview process for our program using the framework of the Accreditation Council for Graduate Medical Education core competencies. Although the effects of this change on the clinical performance of our fellows have not yet been assessed, this description of our development and implementation processes may be helpful for programs seeking to redesign their applicant interviews.

  19. 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.

  20. Social ranking effects on tooth-brushing behaviour.

    Science.gov (United States)

    Maltby, John; Paterson, Kevin; Day, Liz; Jones, Ceri; Kinnear, Hayley; Buchanan, Heather

    2016-05-01

    A tooth-brushing social rank hypothesis is tested suggesting tooth-brushing duration is influenced when individuals position their behaviour in a rank when comparing their behaviour with other individuals. Study 1 used a correlation design, Study 2 used a semi-experimental design, and Study 3 used a randomized intervention design to examine the tooth-brushing social rank hypothesis in terms of self-reported attitudes, cognitions, and behaviour towards tooth-brushing duration. Study 1 surveyed participants to examine whether the perceived health benefits of tooth-brushing duration could be predicted from the ranking of each person's tooth-brushing duration. Study 2 tested whether manipulating the rank position of the tooth-brushing duration influenced participant-perceived health benefits of tooth-brushing duration. Study 3 used a longitudinal intervention method to examine whether messages relating to the rank positions of tooth-brushing durations causally influenced the self-report tooth-brushing duration. Study 1 demonstrates that perceptions of the health benefits from tooth-brushing duration are predicted by the perceptions of how that behaviour ranks in comparison to other people's behaviour. Study 2 demonstrates that the perceptions of the health benefits of tooth-brushing duration can be manipulated experimentally by changing the ranked position of a person's tooth-brushing duration. Study 3 experimentally demonstrates the possibility of increasing the length of time for which individuals clean their teeth by focusing on how they rank among their peers in terms of tooth-brushing duration. The effectiveness of interventions using social-ranking methods relative to those that emphasize comparisons made against group averages or normative guidelines are discussed. What is already known on this subject? Individual make judgements based on social rank information. Social rank information has been shown to influence positive health behaviours such as exercise

  1. Identification of candidate categories of the International Classification of Functioning Disability and Health (ICF for a Generic ICF Core Set based on regression modelling

    Directory of Open Access Journals (Sweden)

    Üstün Bedirhan T

    2006-07-01

    Full Text Available Abstract Background The International Classification of Functioning, Disability and Health (ICF is the framework developed by WHO to describe functioning and disability at both the individual and population levels. While condition-specific ICF Core Sets are useful, a Generic ICF Core Set is needed to describe and compare problems in functioning across health conditions. Methods The aims of the multi-centre, cross-sectional study presented here were: a to propose a method to select ICF categories when a large amount of ICF-based data have to be handled, and b to identify candidate ICF categories for a Generic ICF Core Set by examining their explanatory power in relation to item one of the SF-36. The data were collected from 1039 patients using the ICF checklist, the SF-36 and a Comorbidity Questionnaire. ICF categories to be entered in an initial regression model were selected following systematic steps in accordance with the ICF structure. Based on an initial regression model, additional models were designed by systematically substituting the ICF categories included in it with ICF categories with which they were highly correlated. Results Fourteen different regression models were performed. The variance the performed models account for ranged from 22.27% to 24.0%. The ICF category that explained the highest amount of variance in all the models was sensation of pain. In total, thirteen candidate ICF categories for a Generic ICF Core Set were proposed. Conclusion The selection strategy based on the ICF structure and the examination of the best possible alternative models does not provide a final answer about which ICF categories must be considered, but leads to a selection of suitable candidates which needs further consideration and comparison with the results of other selection strategies in developing a Generic ICF Core Set.

  2. Identification of candidate categories of the International Classification of Functioning Disability and Health (ICF) for a Generic ICF Core Set based on regression modelling.

    Science.gov (United States)

    Cieza, Alarcos; Geyh, Szilvia; Chatterji, Somnath; Kostanjsek, Nenad; Ustün, Bedirhan T; Stucki, Gerold

    2006-07-27

    The International Classification of Functioning, Disability and Health (ICF) is the framework developed by WHO to describe functioning and disability at both the individual and population levels.While condition-specific ICF Core Sets are useful, a Generic ICF Core Set is needed to describe and compare problems in functioning across health conditions. The aims of the multi-centre, cross-sectional study presented here were: a) to propose a method to select ICF categories when a large amount of ICF-based data have to be handled, and b) to identify candidate ICF categories for a Generic ICF Core Set by examining their explanatory power in relation to item one of the SF-36. The data were collected from 1039 patients using the ICF checklist, the SF-36 and a Comorbidity Questionnaire.ICF categories to be entered in an initial regression model were selected following systematic steps in accordance with the ICF structure. Based on an initial regression model, additional models were designed by systematically substituting the ICF categories included in it with ICF categories with which they were highly correlated. Fourteen different regression models were performed. The variance the performed models account for ranged from 22.27% to 24.0%. The ICF category that explained the highest amount of variance in all the models was sensation of pain. In total, thirteen candidate ICF categories for a Generic ICF Core Set were proposed. The selection strategy based on the ICF structure and the examination of the best possible alternative models does not provide a final answer about which ICF categories must be considered, but leads to a selection of suitable candidates which needs further consideration and comparison with the results of other selection strategies in developing a Generic ICF Core Set.

  3. Estimation of rank correlation for clustered data.

    Science.gov (United States)

    Rosner, Bernard; Glynn, Robert J

    2017-06-30

    It is well known that the sample correlation coefficient (Rxy ) is the maximum likelihood estimator of the Pearson correlation (ρxy ) for independent and identically distributed (i.i.d.) bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the maximum likelihood estimator of ρxy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U_ of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (i) converting ranks of both X and Y to the probit scale, (ii) estimating the Pearson correlation between probit scores for X and Y, and (iii) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  4. Reducing Excessive Amounts of Data: Multiple Web Queries for Generation of Pun Candidates

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    Pawel Dybala

    2011-01-01

    Full Text Available Humor processing is still a less studied issue, both in NLP and AI. In this paper we contribute to this field. In our previous research we showed that adding a simple pun generator to a chatterbot can significantly improve its performance. The pun generator we used generated only puns based on words (not phrases. In this paper we introduce the next stage of the system's development—an algorithm allowing generation of phrasal pun candidates. We show that by using only the Internet (without any hand-made humor-oriented lexicons, it is possible to generate puns based on complex phrases. As the output list is often excessively long, we also propose a method for reducing the number of candidates by comparing two web-query-based rankings. The evaluation experiment showed that the system achieved an accuracy of 72.5% for finding proper candidates in general, and the reduction method allowed us to significantly shorten the candidates list. The parameters of the reduction algorithm are variable, so that the balance between the number of candidates and the quality of output can be manipulated according to needs.

  5. Variable ranking based on the estimated degree of separation for two distributions of data by the length of the receiver operating characteristic curve.

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    Maswadeh, Waleed M; Snyder, A Peter

    2015-05-30

    Variable responses are fundamental for all experiments, and they can consist of information-rich, redundant, and low signal intensities. A dataset can consist of a collection of variable responses over multiple classes or groups. Usually some of the variables are removed in a dataset that contain very little information. Sometimes all the variables are used in the data analysis phase. It is common practice to discriminate between two distributions of data; however, there is no formal algorithm to arrive at a degree of separation (DS) between two distributions of data. The DS is defined herein as the average of the sum of the areas from the probability density functions (PDFs) of A and B that contain a≥percentage of A and/or B. Thus, DS90 is the average of the sum of the PDF areas of A and B that contain ≥90% of A and/or B. To arrive at a DS value, two synthesized PDFs or very large experimental datasets are required. Experimentally it is common practice to generate relatively small datasets. Therefore, the challenge was to find a statistical parameter that can be used on small datasets to estimate and highly correlate with the DS90 parameter. Established statistical methods include the overlap area of the two data distribution profiles, Welch's t-test, Kolmogorov-Smirnov (K-S) test, Mann-Whitney-Wilcoxon test, and the area under the receiver operating characteristics (ROC) curve (AUC). The area between the ROC curve and diagonal (ACD) and the length of the ROC curve (LROC) are introduced. The established, ACD, and LROC methods were correlated to the DS90 when applied on many pairs of synthesized PDFs. The LROC method provided the best linear correlation with, and estimation of, the DS90. The estimated DS90 from the LROC (DS90-LROC) is applied to a database, as an example, of three Italian wines consisting of thirteen variable responses for variable ranking consideration. An important highlight of the DS90-LROC method is utilizing the LROC curve methodology to

  6. An In Silico Identification of Common Putative Vaccine Candidates against Treponema pallidum: A Reverse Vaccinology and Subtractive Genomics Based Approach.

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    Kumar Jaiswal, Arun; Tiwari, Sandeep; Jamal, Syed Babar; Barh, Debmalya; Azevedo, Vasco; Soares, Siomar C

    2017-02-14

    Sexually transmitted infections (STIs) are caused by a wide variety of bacteria, viruses, and parasites that are transmitted from one person to another primarily by vaginal, anal, or oral sexual contact. Syphilis is a serious disease caused by a sexually transmitted infection. Syphilis is caused by the bacterium Treponema pallidum subspecies pallidum. Treponema pallidum (T. pallidum) is a motile, gram-negative spirochete, which can be transmitted both sexually and from mother to child, and can invade virtually any organ or structure in the human body. The current worldwide prevalence of syphilis emphasizes the need for continued preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine targets and putative drugs against syphilis disease using reverse vaccinology and subtractive genomics. We compared 13 strains of T. pallidum using T. pallidum Nichols as the reference genome. Using an in silicoapproach, four pathogenic islands were detected in the genome of T. pallidum Nichols. We identified 15 putative antigenic proteins and sixdrug targets through reverse vaccinology and subtractive genomics, respectively, which can be used as candidate therapeutic targets in the future.

  7. GC-MS Based Plasma Metabolomics for Identification of Candidate Biomarkers for Hepatocellular Carcinoma in Egyptian Cohort

    Science.gov (United States)

    Nezami Ranjbar, Mohammad R.; Luo, Yue; Di Poto, Cristina; Varghese, Rency S.; Ferrarini, Alessia; Zhang, Chi; Sarhan, Naglaa I.; Soliman, Hanan; Tadesse, Mahlet G.; Ziada, Dina H.; Roy, Rabindra; Ressom, Habtom W.

    2015-01-01

    This study evaluates changes in metabolite levels in hepatocellular carcinoma (HCC) cases vs. patients with liver cirrhosis by analysis of human blood plasma using gas chromatography coupled with mass spectrometry (GC-MS). Untargeted metabolomic analysis of plasma samples from participants recruited in Egypt was performed using two GC-MS platforms: a GC coupled to single quadruple mass spectrometer (GC-qMS) and a GC coupled to a time-of-flight mass spectrometer (GC-TOFMS). Analytes that showed statistically significant changes in ion intensities were selected using ANOVA models. These analytes and other candidates selected from related studies were further evaluated by targeted analysis in plasma samples from the same participants as in the untargeted metabolomic analysis. The targeted analysis was performed using the GC-qMS in selected ion monitoring (SIM) mode. The method confirmed significant changes in the levels of glutamic acid, citric acid, lactic acid, valine, isoleucine, leucine, alpha tocopherol, cholesterol, and sorbose in HCC cases vs. patients with liver cirrhosis. Specifically, our findings indicate up-regulation of metabolites involved in branched-chain amino acid (BCAA) metabolism. Although BCAAs are increasingly used as a treatment for cancer cachexia, others have shown that BCAA supplementation caused significant enhancement of tumor growth via activation of mTOR/AKT pathway, which is consistent with our results that BCAAs are up-regulated in HCC. PMID:26030804

  8. Designing defect-based qubit candidates in wide-gap binary semiconductors for solid-state quantum technologies

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    Seo, Hosung; Ma, He; Govoni, Marco; Galli, Giulia

    2017-12-01

    The development of novel quantum bits is key to extending the scope of solid-state quantum-information science and technology. Using first-principles calculations, we propose that large metal ion-vacancy pairs are promising qubit candidates in two binary crystals: 4 H -SiC and w -AlN. In particular, we found that the formation of neutral Hf- and Zr-vacancy pairs is energetically favorable in both solids; these defects have spin-triplet ground states, with electronic structures similar to those of the diamond nitrogen-vacancy center and the SiC divacancy. Interestingly, they exhibit different spin-strain coupling characteristics, and the nature of heavy metal ions may allow for easy defect implantation in desired lattice locations and ensure stability against defect diffusion. To support future experimental identification of the proposed defects, we report predictions of their optical zero-phonon line, zero-field splitting, and hyperfine parameters. The defect design concept identified here may be generalized to other binary semiconductors to facilitate the exploration of new solid-state qubits.

  9. GC-MS Based Plasma Metabolomics for Identification of Candidate Biomarkers for Hepatocellular Carcinoma in Egyptian Cohort.

    Directory of Open Access Journals (Sweden)

    Mohammad R Nezami Ranjbar

    Full Text Available This study evaluates changes in metabolite levels in hepatocellular carcinoma (HCC cases vs. patients with liver cirrhosis by analysis of human blood plasma using gas chromatography coupled with mass spectrometry (GC-MS. Untargeted metabolomic analysis of plasma samples from participants recruited in Egypt was performed using two GC-MS platforms: a GC coupled to single quadruple mass spectrometer (GC-qMS and a GC coupled to a time-of-flight mass spectrometer (GC-TOFMS. Analytes that showed statistically significant changes in ion intensities were selected using ANOVA models. These analytes and other candidates selected from related studies were further evaluated by targeted analysis in plasma samples from the same participants as in the untargeted metabolomic analysis. The targeted analysis was performed using the GC-qMS in selected ion monitoring (SIM mode. The method confirmed significant changes in the levels of glutamic acid, citric acid, lactic acid, valine, isoleucine, leucine, alpha tocopherol, cholesterol, and sorbose in HCC cases vs. patients with liver cirrhosis. Specifically, our findings indicate up-regulation of metabolites involved in branched-chain amino acid (BCAA metabolism. Although BCAAs are increasingly used as a treatment for cancer cachexia, others have shown that BCAA supplementation caused significant enhancement of tumor growth via activation of mTOR/AKT pathway, which is consistent with our results that BCAAs are up-regulated in HCC.

  10. Systematic exploration of a class of hydrophobic unnatural base pairs yields multiple new candidates for the expansion of the genetic alphabet.

    Science.gov (United States)

    Dhami, Kirandeep; Malyshev, Denis A; Ordoukhanian, Phillip; Kubelka, Tomáš; Hocek, Michal; Romesberg, Floyd E

    2014-01-01

    We have developed a family of unnatural base pairs (UBPs), which rely on hydrophobic and packing interactions for pairing and which are well replicated and transcribed. While the pair formed between d5SICS and dNaM (d5SICS-dNaM) has received the most attention, and has been used to expand the genetic alphabet of a living organism, recent efforts have identified dTPT3-dNaM, which is replicated with even higher fidelity. These efforts also resulted in more UBPs than could be independently analyzed, and thus we now report a PCR-based screen to identify the most promising. While we found that dTPT3-dNaM is generally the most promising UBP, we identified several others that are replicated nearly as well and significantly better than d5SICS-dNaM, and are thus viable candidates for the expansion of the genetic alphabet of a living organism. Moreover, the results suggest that continued optimization should be possible, and that the putatively essential hydrogen-bond acceptor at the position ortho to the glycosidic linkage may not be required. These results clearly demonstrate the generality of hydrophobic forces for the control of base pairing within DNA, provide a wealth of new structure-activity relationship data and importantly identify multiple new candidates for in vivo evaluation and further optimization. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Next-generation DNA sequencing-based assay for measuring allelic expression imbalance (AEI of candidate neuropsychiatric disorder genes in human brain

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    Xu Xiang

    2011-10-01

    Full Text Available Abstract Background Common genetic variants that regulate gene expression are widely suspected to contribute to the etiology and phenotypic variability of complex diseases. Although high-throughput, microarray-based assays have been developed to measure differences in mRNA expression among independent samples, these assays often lack the sensitivity to detect rare mRNAs and the reproducibility to quantify small changes in mRNA expression. By contrast, PCR-based allelic expression imbalance (AEI assays, which use a "marker" single nucleotide polymorphism (mSNP in the mRNA to distinguish expression from pairs of genetic alleles in individual samples, have high sensitivity and accuracy, allowing differences in mRNA expression greater than 1.2-fold to be quantified with high reproducibility. In this paper, we describe the use of an efficient PCR/next-generation DNA sequencing-based assay to analyze allele-specific differences in mRNA expression for candidate neuropsychiatric disorder genes in human brain. Results Using our assay, we successfully analyzed AEI for 70 candidate neuropsychiatric disorder genes in 52 independent human brain samples. Among these genes, 62/70 (89% showed AEI ratios greater than 1 ± 0.2 in at least one sample and 8/70 (11% showed no AEI. Arranging log2AEI ratios in increasing order from negative-to-positive values revealed highly reproducible distributions of log2AEI ratios that are distinct for each gene/marker SNP combination. Mathematical modeling suggests that these log2AEI distributions can provide important clues concerning the number, location and contributions of cis-acting regulatory variants to mRNA expression. Conclusions We have developed a highly sensitive and reproducible method for quantifying AEI of mRNA expressed in human brain. Importantly, this assay allowed quantification of differential mRNA expression for many candidate disease genes entirely missed in previously published microarray-based studies of

  12. Validating rankings in soccer championships

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    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.

  13. A QSAR/QSTR study on the human health impact of the rocket fuel 1,1-dimethyl hydrazine and its transformation products Multicriteria hazard ranking based on partial order methodologies.

    Science.gov (United States)

    Carlsen, Lars; Kenessov, Bulat N; Batyrbekova, Svetlana Ye

    2009-05-01

    The possible impact of the rocket fuel 1,1-dimethyl hydrazine (heptyl) (1) and its transformation products on human health has been studied using (Quantitative) Structure Activity/Toxicity ((Q)SAR/(Q)STR) modelling, including both ADME models and models for acute toxicity, organ specific adverse haematological effects, the cardiovascular and gastrointestinal systems, the kidneys, the liver and the lungs, as well as a model predicting the biological activity of the compounds. It was predicted that all compounds studied are readily bioavailable through oral intake and that significant amounts of the compounds will be freely available in the systemic circulation. In general, the compounds are not predicted to be acutely toxic apart from hydrogen cyanide, whereas several compounds are predicted to cause adverse organ specific human health effects. Further, several compounds are predicted to exhibit high probabilities for potential carcinogenicity, mutagenicity, teratogenicity and/or embryotoxicity. The compounds were ranked based on their predicted human health impact using partial order ranking methodologies that highlight which compounds on a cumulative basis should receive the major attention, i.e., N-nitroso dimethyl amine, 1,1,4,4-tetramethyl tetrazene, trimethyl, trimethyl hydrazine, acetaldehyde dimethyl hydrazone, 1, 1-formyl 2,2-dimethyl hydrazine and formaldehyde dimethyl hydrazone, respectively. Copyright © 2009 Elsevier B.V. All rights reserved.

  14. Identification and prioritization of candidate genes for symptom variability in breast cancer survivors based on disease characteristics at the cellular level.

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    Koleck, Theresa A; Conley, Yvette P

    2016-01-01

    Research is beginning to suggest that the presence and/or severity of symptoms reported by breast cancer survivors may be associated with disease-related factors of cancer. In this article, we present a novel approach to the identification and prioritization of biologically plausible candidate genes to investigate relationships between genomic variation and symptom variability in breast cancer survivors. Cognitive dysfunction is utilized as a representative breast cancer survivor symptom to elucidate the conceptualization of and justification for our cellular, disease-based approach to address symptom variability in cancer survivors. Initial candidate gene identification was based on genes evaluated as part of multigene expression profiles for breast cancer, which are commonly used in the clinical setting to characterize the biology of cancer cells for the purpose of describing overall tumor aggressiveness, prognostication, and individualization of therapy. A list of genes evaluated within five multigene expression profiles for breast cancer was compiled. In order to prioritize candidate genes for investigation, genes used in each profile were compared for duplication. Twenty-one genes (BAG1, BCL2, BIRC5, CCNB1, CENPA, CMC2, DIAPH3, ERBB2, ESR1, GRB7, MELK, MKI67, MMP11, MYBL2, NDC80, ORC6, PGR, RACGAP1, RFC4, RRM2, and SCUBE2) are utilized in two or more profiles, including five genes (CCNB1, CENPA, MELK, MYBL2, and ORC6) used in three profiles. To ensure that the parsimonious 21 gene set is representative of the more global biological hallmarks of cancer, an Ingenuity Pathway Analysis was conducted. Evaluation of genes known to impact pathways involved with cancer development and progression provide a means to evaluate the overlap between the biological underpinnings of cancer and symptom development within the context of cancer.

  15. Candidate pathway-based genome-wide association studies identify novel associations of genomic variants in the complement system associated with coronary artery disease.

    Science.gov (United States)

    Xu, Chengqi; Yang, Qin; Xiong, Hongbo; Wang, Longfei; Cai, Jianping; Wang, Fan; Li, Sisi; Chen, Jing; Wang, Chuchu; Wang, Dan; Xiong, Xin; Wang, Pengyun; Zhao, Yuanyuan; Wang, Xiaojing; Huang, Yufeng; Chen, Shanshan; Yin, Dan; Li, Xiuchun; Liu, Ying; Liu, Jinqiu; Wang, Jingjing; Li, Hui; Ke, Tie; Ren, Xiang; Wu, Yanxia; Wu, Gang; Wan, Jing; Zhang, Rongfeng; Wu, Tangchun; Wang, Junhan; Xia, Yunlong; Yang, Yanzong; Cheng, Xiang; Liao, Yuhua; Chen, Qiuyun; Zhou, Yanhong; He, Qing; Tu, Xin; Wang, Qing K

    2014-12-01

    Genomic variants identified by genome-wide association studies (GWAS) explain associated with CAD, we developed a candidate pathway-based GWAS by integrating expression quantitative loci analysis and mining of GWAS data with variants in a candidate pathway. Mining of GWAS data was performed to analyze variants in 32 complement system genes for positive association with CAD. Functional variants in genes showing positive association were then identified by searching existing expression quantitative loci databases and validated by real-time reverse transcription polymerase chain reaction. A follow-up case-control design was then used to determine whether the functional variants are associated with CAD in 2 independent GeneID Chinese populations. Candidate pathway-based GWAS identified positive association between variants in C3AR1 and C6 and CAD. Two functional variants, rs7842 in C3AR1 and rs4400166 in C6, were found to be associated with expression levels of C3AR1 and C6, respectively. Significant association was identified between rs7842 and CAD (P=3.99×10(-6); odds ratio, 1.47) and between rs4400166 and CAD (P=9.30×10(-3); odds ratio, 1.24) in the validation cohort. The significant findings were confirmed in the replication cohort (P=1.53×10(-5); odds ratio, 1.37 for rs7842; P=8.41×10(-3); odds ratio, 1.21 for rs4400166). Integration of GWAS with biological pathways and expression quantitative loci is effective in identifying new risk variants for CAD. Functional variants increasing C3AR1 and C6 expression were shown to confer significant risk of CAD for the first time. © 2014 American Heart Association, Inc.

  16. Combined Reduced-Rank Transform

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    Anatoli Torokhti

    2006-04-01

    Full Text Available We propose and justify a new approach to constructing optimal nonlinear transforms of random vectors. We show that the proposed transform improves such characteristics of {rank-reduced} transforms as compression ratio, accuracy of decompression and reduces required computational work. The proposed transform ${mathcal T}_p$ is presented in the form of a sum with $p$ terms where each term is interpreted as a particular rank-reduced transform. Moreover, terms in ${mathcal T}_p$ are represented as a combination of three operations ${mathcal F}_k$, ${mathcal Q}_k$ and ${oldsymbol{varphi}}_k$ with $k=1,ldots,p$. The prime idea is to determine ${mathcal F}_k$ separately, for each $k=1,ldots,p$, from an associated rank-constrained minimization problem similar to that used in the Karhunen--Lo`{e}ve transform. The operations ${mathcal Q}_k$ and ${oldsymbol{varphi}}_k$ are auxiliary for f/inding ${mathcal F}_k$. The contribution of each term in ${mathcal T}_p$ improves the entire transform performance. A corresponding unconstrained nonlinear optimal transform is also considered. Such a transform is important in its own right because it is treated as an optimal filter without signal compression. A rigorous analysis of errors associated with the proposed transforms is given.

  17. Functional Multiplex PageRank

    Science.gov (United States)

    Iacovacci, Jacopo; Rahmede, Christoph; Arenas, Alex; Bianconi, Ginestra

    2016-10-01

    Recently it has been recognized that many complex social, technological and biological networks have a multilayer nature and can be described by multiplex networks. Multiplex networks are formed by a set of nodes connected by links having different connotations forming the different layers of the multiplex. Characterizing the centrality of the nodes in a multiplex network is a challenging task since the centrality of the node naturally depends on the importance associated to links of a certain type. Here we propose to assign to each node of a multiplex network a centrality called Functional Multiplex PageRank that is a function of the weights given to every different pattern of connections (multilinks) existent in the multiplex network between any two nodes. Since multilinks distinguish all the possible ways in which the links in different layers can overlap, the Functional Multiplex PageRank can describe important non-linear effects when large relevance or small relevance is assigned to multilinks with overlap. Here we apply the Functional Page Rank to the multiplex airport networks, to the neuronal network of the nematode C. elegans, and to social collaboration and citation networks between scientists. This analysis reveals important differences existing between the most central nodes of these networks, and the correlations between their so-called pattern to success.

  18. Immunogenicity of a polyvalent HIV-1 candidate vaccine based on fourteen wild type gp120 proteins in golden hamsters

    Science.gov (United States)

    Azizi, Ali; Anderson, David E; Ghorbani, Masoud; Gee, Katrina; Diaz-Mitoma, Francisco

    2006-01-01

    Background One of the major obstacles in the design of an effective vaccine against HIV-1 is the hypervariability of the HIV-1 envelope glycoprotein. Most HIV-1 vaccine candidates have utilized envelope glycoprotein from a single virus isolate, but to date, none of them elicited broadly reactive humoral immunity. Herein, we hypothesised that a cocktail of HIV-1 gp120 proteins containing multiple epitopes may increase the breadth of immune responses against HIV-1. We compared and evaluated the immunogenicity of HIV-1 vaccines containing either gp120 protein alone or in combinations of four or fourteen gp120s from different primary HIV-1 isolates in immunized hamsters. Results We amplified and characterized 14 different gp120s from primary subtype B isolates with both syncytium and non-syncytium inducing properties, and expressed the proteins in Chinese Hamster Ovary (CHO) cell lines. Purified proteins were used either alone or in combinations of four or fourteen different gp120s to vaccinate golden hamsters. The polyvalent vaccine showed higher antibody titers to HIV-1 subtype B isolates MN and SF162 compared to the groups that received one or four gp120 proteins. However, the polyvalent vaccine was not able to show higher neutralizing antibody responses against HIV-1 primary isolates. Interestingly, the polyvalent vaccine group had the highest proliferative immune responses and showed a substantial proportion of cross-subtype CD4 reactivity to HIV-1 subtypes B, C, and A/E Conclusion Although the polyvalent approach achieved only a modest increase in the breadth of humoral and cellular immunity, the qualitative change in the vaccine (14 vs. 1 gp120) resulted in a quantitative improvement in vaccine-induced immunity. PMID:17076905

  19. Immunogenicity of a polyvalent HIV-1 candidate vaccine based on fourteen wild type gp120 proteins in golden hamsters

    Directory of Open Access Journals (Sweden)

    Ghorbani Masoud

    2006-10-01

    Full Text Available Abstract Background One of the major obstacles in the design of an effective vaccine against HIV-1 is the hypervariability of the HIV-1 envelope glycoprotein. Most HIV-1 vaccine candidates have utilized envelope glycoprotein from a single virus isolate, but to date, none of them elicited broadly reactive humoral immunity. Herein, we hypothesised that a cocktail of HIV-1 gp120 proteins containing multiple epitopes may increase the breadth of immune responses against HIV-1. We compared and evaluated the immunogenicity of HIV-1 vaccines containing either gp120 protein alone or in combinations of four or fourteen gp120s from different primary HIV-1 isolates in immunized hamsters. Results We amplified and characterized 14 different gp120s from primary subtype B isolates with both syncytium and non-syncytium inducing properties, and expressed the proteins in Chinese Hamster Ovary (CHO cell lines. Purified proteins were used either alone or in combinations of four or fourteen different gp120s to vaccinate golden hamsters. The polyvalent vaccine showed higher antibody titers to HIV-1 subtype B isolates MN and SF162 compared to the groups that received one or four gp120 proteins. However, the polyvalent vaccine was not able to show higher neutralizing antibody responses against HIV-1 primary isolates. Interestingly, the polyvalent vaccine group had the highest proliferative immune responses and showed a substantial proportion of cross-subtype CD4 reactivity to HIV-1 subtypes B, C, and A/E Conclusion Although the polyvalent approach achieved only a modest increase in the breadth of humoral and cellular immunity, the qualitative change in the vaccine (14 vs. 1 gp120 resulted in a quantitative improvement in vaccine-induced immunity.

  20. Candidate Gene Identification with SNP Marker-Based Fine Mapping of Anthracnose Resistance Gene Co-4 in Common Bean

    Science.gov (United States)

    Burt, Andrew J.; William, H. Manilal; Perry, Gregory; Khanal, Raja; Pauls, K. Peter; Kelly, James D.; Navabi, Alireza

    2015-01-01

    Anthracnose, caused by Colletotrichum lindemuthianum, is an important fungal disease of common bean (Phaseolus vulgaris). Alleles at the Co–4 locus confer resistance to a number of races of C. lindemuthianum. A population of 94 F4:5 recombinant inbred lines of a cross between resistant black bean genotype B09197 and susceptible navy bean cultivar Nautica was used to identify markers associated with resistance in bean chromosome 8 (Pv08) where Co–4 is localized. Three SCAR markers with known linkage to Co–4 and a panel of single nucleotide markers were used for genotyping. A refined physical region on Pv08 with significant association with anthracnose resistance identified by markers was used in BLAST searches with the genomic sequence of common bean accession G19833. Thirty two unique annotated candidate genes were identified that spanned a physical region of 936.46 kb. A majority of the annotated genes identified had functional similarity to leucine rich repeats/receptor like kinase domains. Three annotated genes had similarity to 1, 3-β-glucanase domains. There were sequence similarities between some of the annotated genes found in the study and the genes associated with phosphoinositide-specific phosphilipases C associated with Co-x and the COK–4 loci found in previous studies. It is possible that the Co–4 locus is structured as a group of genes with functional domains dominated by protein tyrosine kinase along with leucine rich repeats/nucleotide binding site, phosphilipases C as well as β-glucanases. PMID:26431031