Regional Kendall test for trend

USGS Publications Warehouse

Helsel, D.R.; Frans, L.M.

2006-01-01

Trends in environmental variables are often investigated within a study region at more than one site. At each site, a trend analysis determines whether a trend has occurred. Yet often also of interest is whether a consistent trend is evident throughout the entire region. This paper adapts the Seasonal Kendall trend test to determine whether a consistent regional trend occurs in environmental variables.

Computer program for the Kendall family of trend tests

USGS Publications Warehouse

Helsel, Dennis R.; Mueller, David K.; Slack, James R.

2006-01-01

The Seasonal Kendall (SK) test for trend was developed by the U.S. Geological Survey and has become the most frequently used test for trend in the environmental sciences. Recently the test was modified to form the Regional Kendall (RK) test for trend. In this form, trends at numerous locations within a region are tested to determine whether the direction of trend is consistent across the entire region. Computer code developed at the USGS in the 1980s to perform the SK test is no longer widely available. Other versions written by other scientists may or may not be easily available, and may require commercial software in order to be run. These other versions do not explicitly compute the RK test. Therefore, the original code for computing the SK test has been repackaged into a program that runs under the Windows operating system. This program may be used to verify that other implementations of the test give the same results as the original. The program also provides a means for computing the RK test and the simpler Mann-Kendall test for trend.

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

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

PubMed

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

2015-07-01

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

Surface-Water and Ground-Water Resources of Kendall County, Illinois

USGS Publications Warehouse

Kay, Robert T.; Mills, Patrick C.; Hogan, Jennifer L.; Arnold, Terri L.

2005-01-01

Water-supply needs in Kendall County, in northern Illinois, are met exclusively from ground water derived from glacial drift aquifers and bedrock aquifers open to Silurian, Ordovician, and Cambrian System units. As a result of population growth in Kendall County and the surrounding area, water use has increased from about 1.2 million gallons per day in 1957 to more than 5 million gallons per day in 2000. The purpose of this report is to characterize the surface-water and ground-water resources of Kendall County. The report presents a compilation of available information on geology, surface-water and ground-water hydrology, water quality, and water use. The Fox River is the primary surface-water body in Kendall County and is used for both wastewater disposal and as a drinking-water supply upstream of the county. Water from the Fox River requires pretreatment for use as drinking water, but the river is a potentially viable additional source of water for the county. Glacial drift aquifers capable of yielding sufficient water for municipal supply are expected to be present in northern Kendall County, along the Fox River, and in the Newark Valley and its tributaries. Glacial drift aquifers capable of yielding sufficient water for residential supply are present in most of the county, with the exception of the southeastern portion. Volatile organic compounds and select trace metals and pesticides have been detected at low concentrations in glacial drift aquifers near waste-disposal sites. Agricultural-related constituents have been detected infrequently in glacial drift aquifers near agricultural areas. However, on the basis of the available data, widespread, consistent problems with water quality are not apparent in these aquifers. These aquifers are a viable source for additional water supply, but would require further characterization prior to full development. The shallow bedrock aquifer is composed of the sandstone units of the Ancell Group, the Prairie du Chien

Assessing the Priority Area of Mountainous Tourism Using Geospatial Approach in Kendal Regency, Central Java

NASA Astrophysics Data System (ADS)

Riwayatiningsih; Purnaweni, Hartuti

2018-02-01

Kendal is one of 35 regencies in Central Java which has diverse topographies, from low land, hilly, to mountainous areas. Mountainous area of Kendal with numerous unique and distinct natural environments, supported by various unique and distinct culture of its community can be used for tourism activities. Kendal has natural and sociocultural resources for developing tourism that must be considered by the local government. Therefore, nature based tourism resources assessment is important in order to determine the appropriate area in the planning of sustainable tourism destination. The objectives of this study are to assess and prioritize the potential area of mountainous tourism object in Kendal using geospatial approach based on criteria attractiveness, accessibility and amenity of the tourism object. Those criteria are modification of ADO-ODTWA guidelines and condition of the study location. There are 16 locations of tourism object that will be assessed. The result will be processed using ArcMap 10.3. The result will show the most potential tourism object that could become priority for mountainous tourism development in Kendal.

Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes.

PubMed

Huang, Zirui; Davis, Henry Hap; Wolff, Annemarie; Northoff, Georg

2017-01-01

Brain plasticity studies have shown functional reorganization in participants with outstanding motor expertise. Little is known about neural plasticity associated with exceptionally long motor training or of its predictive value for motor performance excellence. The present study utilised resting-state functional magnetic resonance imaging (rs-fMRI) in a unique sample of world-class athletes: Olympic, elite, and internationally ranked swimmers ( n = 30). Their world ranking ranged from 1st to 250th: each had prepared for participation in the Olympic Games. Combining rs-fMRI graph-theoretical and seed-based functional connectivity analyses, it was discovered that the thalamus has its strongest connections with the sensorimotor network in elite swimmers with the highest world rankings (career best rank: 1-35). Strikingly, thalamo-sensorimotor functional connections were highly correlated with the swimmers' motor performance excellence, that is, accounting for 41% of the individual variance in best world ranking. Our findings shed light on neural correlates of long-term athletic performance involving thalamo-sensorimotor functional circuits.

Frequency-Rank Distributions

ERIC Educational Resources Information Center

Brookes, Bertram C.; Griffiths, Jose M.

1978-01-01

Frequency, rank, and frequency rank distributions are defined. Extensive discussion on several aspects of frequency rank distributions includes the Poisson process as a means of exploring the stability of ranks; the correlation of frequency rank distributions; and the transfer coefficient, a new measure in frequency rank distribution. (MBR)

75 FR 61479 - Kendall Head Tidal Energy Project; Notice of Preliminary Permit Application Accepted for Filing...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-05

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Project No. 13801-000] Kendall Head Tidal Energy Project; Notice of Preliminary Permit Application Accepted for Filing and Soliciting... Federal Power Act, proposing to study the feasibility of the Kendall Head Tidal Energy Project, located in...

The Problems of Applying Student Centered Syllabus of English in Vocational High Schools in Kendal Regency

ERIC Educational Resources Information Center

Faridi, Abdurrachman; Bahri, Seful; Nurmasitah, Sita

2016-01-01

This study was descriptive qualitative study aimed to investigate the problems of applying student centered syllabus in vocational high schools in Kendal regency, Central Java, Indonesia. The subjects of the study were twenty English teacher in vocational high schools in Kendal. The data were collected through observations, questionnaires, and…

Kendall Demonstration Elementary School: Mathematics Curriculum Guide. Second Edition.

ERIC Educational Resources Information Center

Mason, Virgyl

This mathematics curriculum guide is one of a series developed by the Kendall Demonstration Elementary School (KDES), which serves hearing-impaired students in grades 1-8, to provide a clear representation of the school's programs in various subject areas. Essential classroom practices in the areas of planning, instruction, and evaluation are…

Do Quantitative Measures of Research Productivity Correlate with Academic Rank in Oral and Maxillofacial Surgery?

PubMed

Susarla, Srinivas M; Dodson, Thomas B; Lopez, Joseph; Swanson, Edward W; Calotta, Nicholas; Peacock, Zachary S

2015-08-01

Academic promotion is linked to research productivity. The purpose of this study was to assess the correlation between quantitative measures of academic productivity and academic rank among academic oral and maxillofacial surgeons. This was a cross-sectional study of full-time academic oral and maxillofacial surgeons in the United States. The predictor variables were categorized as demographic (gender, medical degree, research doctorate, other advanced degree) and quantitative measures of academic productivity (total number of publications, total number of citations, maximum number of citations for a single article, I-10 index [number of publications with ≥ 10 citations], and h-index [number of publications h with ≥ h citations each]). The outcome variable was current academic rank (instructor, assistant professor, associate professor, professor, or endowed professor). Descriptive, bivariate, and multiple regression statistics were computed to evaluate associations between the predictors and academic rank. Receiver-operator characteristic curves were computed to identify thresholds for academic promotion. The sample consisted of 324 academic oral and maxillofacial surgeons, of whom 11.7% were female, 40% had medical degrees, and 8% had research doctorates. The h-index was the most strongly correlated with academic rank (ρ = 0.62, p < 0.001). H-indexes of ≥ 4, ≥ 8, and ≥ 13 were identified as thresholds for promotion to associate professor, professor, and endowed professor, respectively (p < 0.001). This study found that the h-index was strongly correlated with academic rank among oral and maxillofacial surgery faculty members and thus suggests that promotions committees should consider using the h-index as an additional method to assess research activity.

AmeriFlux US-Wkg Walnut Gulch Kendall Grasslands

DOE Data Explorer

Scott, Russell [United States Department of Agriculture

2016-01-01

This is the AmeriFlux version of the carbon flux data for the site US-Wkg Walnut Gulch Kendall Grasslands. Site Description - This site is located in a small, intensively-studied, experimental watershed within USDA-ARS's Walnut Gulch Experimental Watershed. Eddy covariance measurements of energy, water and CO2 fluxes began in the spring of 2004, though meteorological (including Bowen ratio) and hydrological measurements are available much further back.

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations.

PubMed

Cheng, Wei; Zhang, Kai; Chen, Haifeng; Jiang, Guofei; Chen, Zhengzhang; Wang, Wei

2016-08-01

Modern world has witnessed a dramatic increase in our ability to collect, transmit and distribute real-time monitoring and surveillance data from large-scale information systems and cyber-physical systems. Detecting system anomalies thus attracts significant amount of interest in many fields such as security, fault management, and industrial optimization. Recently, invariant network has shown to be a powerful way in characterizing complex system behaviours. In the invariant network, a node represents a system component and an edge indicates a stable, significant interaction between two components. Structures and evolutions of the invariance network, in particular the vanishing correlations, can shed important light on locating causal anomalies and performing diagnosis. However, existing approaches to detect causal anomalies with the invariant network often use the percentage of vanishing correlations to rank possible casual components, which have several limitations: 1) fault propagation in the network is ignored; 2) the root casual anomalies may not always be the nodes with a high-percentage of vanishing correlations; 3) temporal patterns of vanishing correlations are not exploited for robust detection. To address these limitations, in this paper we propose a network diffusion based framework to identify significant causal anomalies and rank them. Our approach can effectively model fault propagation over the entire invariant network, and can perform joint inference on both the structural, and the time-evolving broken invariance patterns. As a result, it can locate high-confidence anomalies that are truly responsible for the vanishing correlations, and can compensate for unstructured measurement noise in the system. Extensive experiments on synthetic datasets, bank information system datasets, and coal plant cyber-physical system datasets demonstrate the effectiveness of our approach.

The rank correlated SLW model of gas radiation in non-uniform media

NASA Astrophysics Data System (ADS)

Solovjov, Vladimir P.; Andre, Frederic; Lemonnier, Denis; Webb, Brent W.

2017-08-01

A comprehensive theoretical development of possible reference approaches in modelling of radiation transfer in non-uniform gaseous media is developed within the framework of the Generalized SLW Model. The notion of absorption spectrum ;correlation; adopted currently for global methods in gas radiation is critically revisited and replaced by a less restrictive concept of rank correlated spectrum. Within this framework it is shown that eight different reference approaches are possible, of which only three have been reported in the literature. Among the approaches presented is a novel Rank Correlated SLW Model, which is distinguished by the fact that i) it does not require the specification of a reference gas thermodynamic state, and ii) it preserves the emission term in the spectrally integrated Radiative Transfer Equation. Construction of this reference model requires only two absorption line blackbody distribution functions, and subdivision into gray gases can be performed using standard quadratures. Consequently, this new reference approach appears to have significant advantages over all other methods, and is, in general, a significant improvement in the global modelling of gas radiation. All reference approaches are summarized in the present work, and their use in radiative transfer prediction is demonstrated for simple example cases. Further, a detailed rigorous theoretical development of the improved methods is provided.

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

PubMed

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.

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

PubMed Central

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

2017-01-01

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. PMID:29035341

Chromatographic and computational assessment of lipophilicity using sum of ranking differences and generalized pair-correlation.

PubMed

Andrić, Filip; Héberger, Károly

2015-02-06

Lipophilicity (logP) represents one of the most studied and most frequently used fundamental physicochemical properties. At present there are several possibilities for its quantitative expression and many of them stems from chromatographic experiments. Numerous attempts have been made to compare different computational methods, chromatographic methods vs. computational approaches, as well as chromatographic methods and direct shake-flask procedure without definite results or these findings are not accepted generally. In the present work numerous chromatographically derived lipophilicity measures in combination with diverse computational methods were ranked and clustered using the novel variable discrimination and ranking approaches based on the sum of ranking differences and the generalized pair correlation method. Available literature logP data measured on HILIC, and classical reversed-phase combining different classes of compounds have been compared with most frequently used multivariate data analysis techniques (principal component and hierarchical cluster analysis) as well as with the conclusions in the original sources. Chromatographic lipophilicity measures obtained under typical reversed-phase conditions outperform the majority of computationally estimated logPs. Oppositely, in the case of HILIC none of the many proposed chromatographic indices overcomes any of the computationally assessed logPs. Only two of them (logkmin and kmin) may be selected as recommended chromatographic lipophilicity measures. Both ranking approaches, sum of ranking differences and generalized pair correlation method, although based on different backgrounds, provides highly similar variable ordering and grouping leading to the same conclusions. Copyright © 2015. Published by Elsevier B.V.

Introduction to Psychology and Leadership. Rank-Biserial Correlation as an Item Discrimination.

ERIC Educational Resources Information Center

Westinghouse Learning Corp., Annapolis, MD.

Written as a technical report for the leadership course of the United States Naval Academy (see the final reports which summarize the course development project, EM 010 418, EM 010 419, and EM 010 484), this paper examines the use and interpretation of the rank-biserial correlation as an index of item discrimination. The advantages and…

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures

PubMed Central

Someswara Rao, Chinta; Viswanadha Raju, S.

2016-01-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc. PMID:26981409

Similarity analysis between chromosomes of Homo sapiens and monkeys with correlation coefficient, rank correlation coefficient and cosine similarity measures.

PubMed

Someswara Rao, Chinta; Viswanadha Raju, S

2016-03-01

In this paper, we consider correlation coefficient, rank correlation coefficient and cosine similarity measures for evaluating similarity between Homo sapiens and monkeys. We used DNA chromosomes of genome wide genes to determine the correlation between the chromosomal content and evolutionary relationship. The similarity among the H. sapiens and monkeys is measured for a total of 210 chromosomes related to 10 species. The similarity measures of these different species show the relationship between the H. sapiens and monkey. This similarity will be helpful at theft identification, maternity identification, disease identification, etc.

Analysis of Correlation Tendency between Wind and Solar from Various Spatio-temporal Perspectives

NASA Astrophysics Data System (ADS)

Wang, X.; Weihua, X.; Mei, Y.

2017-12-01

Analysis of correlation between wind resources and solar resources could explore their complementary features, enhance the utilization efficiency of renewable energy and further alleviate the carbon emission issues caused by the fossil energy. In this paper, we discuss the correlation between wind and solar from various spatio-temporal perspectives (from east to west, in terms of plain, plateau, hill, and mountain, from hourly to daily, ten days and monthly) with observed data and modeled data from NOAA (National Oceanic and Atmospheric Administration) and NERL (National Renewable Energy Laboratory). With investigation of wind speed time series and solar radiation time series (period: 10 years, resolution: 1h) of 72 stations located in various landform and distributed dispersedly in USA, the results show that the correlation coefficient, Kendall's rank correlation coefficient, changes negative to positive value from east coast to west coast of USA, and this phenomena become more obvious when the time scale of resolution increases from daily to ten days and monthly. Furthermore, considering the differences of landforms which influence the local meteorology the Kendall coefficients of diverse topographies are compared and it is found that the coefficients descend from mountain to hill, plateau and plain. However, no such evident tendencies could be found in daily scale. According to this research, it is proposed that the complementary feature of wind resources and solar resources in the east or in the mountain area of USA is conspicuous. Subsequent study would try to further verify this analysis by investigating the operation status of wind power station and solar power station.

Testing independence of bivariate interval-censored data using modified Kendall's tau statistic.

PubMed

Kim, Yuneung; Lim, Johan; Park, DoHwan

2015-11-01

In this paper, we study a nonparametric procedure to test independence of bivariate interval censored data; for both current status data (case 1 interval-censored data) and case 2 interval-censored data. To do it, we propose a score-based modification of the Kendall's tau statistic for bivariate interval-censored data. Our modification defines the Kendall's tau statistic with expected numbers of concordant and disconcordant pairs of data. The performance of the modified approach is illustrated by simulation studies and application to the AIDS study. We compare our method to alternative approaches such as the two-stage estimation method by Sun et al. (Scandinavian Journal of Statistics, 2006) and the multiple imputation method by Betensky and Finkelstein (Statistics in Medicine, 1999b). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Are Quantitative Measures of Academic Productivity Correlated with Academic Rank in Plastic Surgery? A National Study.

PubMed

Susarla, Srinivas M; Lopez, Joseph; Swanson, Edward W; Miller, Devin; O'Brien-Coon, Devin; Zins, James E; Serletti, Joseph M; Yaremchuk, Michael J; Manson, Paul N; Gordon, Chad R

2015-09-01

The purpose of this study was to investigate the correlation between quantitative measures of academic productivity and academic rank among full-time academic plastic surgeons. Bibliometric indices were computed for all full-time academic plastic surgeons in the United States. The primary study variable was academic rank. Bibliometric predictors included the Hirsch index, I-10 index, number of publications, number of citations, and highest number of citations for a single publication. Descriptive, bivariate, and correlation analyses were computed. Multiple comparisons testing was used to calculate adjusted associations for subgroups. For all analyses, a value of p < 0.05 was considered significant. The cohort consisted of 607 plastic surgeons across 91 Accreditation Council for Graduate Medical Education-approved programs. Of them, 4.1 percent were instructors/lecturers, 43.7 percent were assistant professors, 22.1 percent were associate professors, 25.7 percent were professors, and 4.4 percent were endowed professors. Mean values were as follows: Hirsch index, 10.2 ± 9.0; I-10 index, 17.2 ± 10.2; total number of publications, 45.5 ± 69.4; total number of citations, 725.0 ± 1448.8; and highest number of citations for a single work, 117.8 ± 262.4. Correlation analyses revealed strong associations of the Hirsch index, I-10 index, number of publications, and number of citations with academic rank (rs = 0.62 to 0.64; p < 0.001). Academic rank in plastic surgery is strongly correlated with several quantitative metrics of research productivity. Although academic promotion is the result of success in multiple different areas, bibliometric measures may be useful adjuncts for assessment of research productivity.

Do Standard Bibliometric Measures Correlate with Academic Rank of Full-Time Pediatric Dentistry Faculty Members?

PubMed

Susarla, Harlyn K; Dhar, Vineet; Karimbux, Nadeem Y; Tinanoff, Norman

2017-04-01

The aim of this cross-sectional study was to assess the relationship between quantitative measures of research productivity and academic rank for full-time pediatric dentistry faculty members in accredited U.S. and Canadian residency programs. For each pediatric dentist in the study group, academic rank and bibliometric factors derived from publicly available databases were recorded. Academic ranks were lecturer/instructor, assistant professor, associate professor, and professor. Bibliometric factors were mean total number of publications, mean total number of citations, maximum number of citations for a single work, and h-index (a measure of the impact of publications, determined by total number of publications h that had at least h citations each). The study sample was comprised of 267 pediatric dentists: 4% were lecturers/instructors, 44% were assistant professors, 30% were associate professors, and 22% were professors. The mean number of publications for the sample was 15.4±27.8. The mean number of citations was 218.4±482.0. The mean h-index was 4.9±6.6. The h-index was strongly correlated with academic rank (r=0.60, p=0.001). For this sample, an h-index of ≥3 was identified as a threshold for promotion to associate professor, and an h-index of ≥6 was identified as a threshold for promotion to professor. The h-index was strongly correlated with the academic rank of these pediatric dental faculty members, suggesting that this index may be considered a measure for promotion, along with a faculty member's quality and quantity of research, teaching, service, and clinical activities.

PageRank as a method to rank biomedical literature by importance.

PubMed

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 < 0.01) and we thus validate the former as a surrogate of literature importance. Furthermore, the algorithm can be run in trivial time on cheap, commodity cluster hardware, lowering the barrier of entry for resource-limited open access organisations. 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.

Development of reliable predictive heat transfer correlations for low-rank coal-fired fluid bed combustors. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grewal, N.S.

(1) The proposed correlation of Equation (5) is recommended to predict the maximum value of heat transfer coefficient between a horzontal tube and a gas-solid fluidized bed of small particles under the conditions given. For high temperature applications (T/sub B/ > 600/sup 0/C), the radiative component is important and was estimated following Baskakov et al. (2) The proposed correlation of Equation (8) was found reliable to predict the existing data on the maximum value of heat transfer coefficient between a horizontal tube bundle and a gas-solid fluidized bed of small particles under the conditions given. At high temperatures, the radiativemore » component was estimated from the experimental data of Baskakov et al. (3) The correlation of Equation (8) predicted the GFETC data taken during the combustion of low-rank coal very well, when the contribution due to radiation was estimated following Baskakov et al. (4) The correlations proposed by Grewal and Bansal et al. were found to predict the data taken during low-rank coal combustion within +-25%, when the contribution due to radiation was included and estimated following Baskakov et al. (5) Finally, the correlations for large particles (anti d/sub p/ > 1mm) as proposed by Glicksman and Decker, Catipovic et al., Xavier and Davidson, and Zabrodsky et al. also predicted the data for low-rank coal fluidized bed combustor quite well, when the radiative component was estimated from the data of Baskakov et al. 64 references, 19 figures, 10 tables.« less

Flexibility of internal and external glenohumeral rotation of junior female tennis players and its correlation with performance ranking.

PubMed

Chiang, Ching-Cheng; Hsu, Chih-Chia; Chiang, Jinn-Yen; Chang, Weng-Cheng; Tsai, Jong-Chang

2016-12-01

[Purpose] The purpose of this study was to compare the internal and external rotation of the dominant and nondominant shoulders of adolescent female tennis players. The correlation between the shoulder rotation range of motion and the player's ranking was also analyzed. [Subjects and Methods] Twenty-one female junior tennis players who were 13 to 18 years old participated in this study. A standard goniometer was used to measure the internal and external rotation of both glenohumeral joints. The difference in internal and external rotation was calculated as the glenohumeral rotation deficit. The year-end ranking of each player was obtained from the Chinese Taipei Tennis Association. [Results] The internal rotation of the dominant shoulder was significantly smaller than that of the nondominant shoulder. Moreover, player ranking was significantly and negatively correlated with the internal rotation range of motion of both shoulders. On the other hand, the correlations of the internal and external rotation ranges of motion with the age, height, and weight were not significant. [Conclusion] The flexibility of the glenohumeral internal rotation is smaller in the dominant shoulder than of the nondominant shoulder in these junior female tennis players. Flexibility of the glenohumeral internal rotation may be a factor affecting performance in junior female tennis players.

Relationships between genotype x environment interactions and rank orders for a set of genotypes tested in different environments.

PubMed

Hühn, M; Lotito, S; Piepho, H P

1993-09-01

Multilocation trials in plant breeding lead to cross-classified data sets with rows=genotypes and columns=environments, where the breeder is particularly interested in the rank orders of the genotypes in the different environments. Non-identical rank orders are the result of genotype x environment interactions. Not every interaction, however, causes rank changes among the genotypes (rank-interaction). From a breeder's point of view, interaction is tolerable only as long as it does not affect the rank orders. Therefore, the question arises of under which circumstances does interaction become rank-interaction. This paper contributes to our understanding of this topic. In our study we emphasized the detection of relationships between the similarity of the rank orders (measured by Kendall's coefficient of concordance W) and the functions of the diverse variance components (genotypes, environments, interaction, error). On the basis of extensive data sets on different agricultural crops (faba bean, fodder beet, sugar beet, oats, winter rape) obtained from registration trials (1985-1989) carried out in the Federal Republic of Germany, we obtained the following as main result: W ≅ σ 2 (g) /(σ 2 (g) + σ 2 (v) ) where σ 2 (g) =genotypic variance and σ 2 (v) = σ 2 (ge) + σ 2 (o) /L with σ 2 (ge) =interaction variance, σ 2 (o) =error variance and L=number of replications.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

A Ranking Approach to Genomic Selection.

PubMed

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

2015-01-01

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

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

PubMed

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

2016-01-01

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

Modeling Area-Level Health Rankings.

PubMed

Courtemanche, Charles; Soneji, Samir; Tchernis, Rusty

2015-10-01

Rank county health using a Bayesian factor analysis model. Secondary county data from the National Center for Health Statistics (through 2007) and Behavioral Risk Factor Surveillance System (through 2009). Our model builds on the existing county health rankings (CHRs) by using data-derived weights to compute ranks from mortality and morbidity variables, and by quantifying uncertainty based on population, spatial correlation, and missing data. We apply our model to Wisconsin, which has comprehensive data, and Texas, which has substantial missing information. The data were downloaded from www.countyhealthrankings.org. Our estimated rankings are more similar to the CHRs for Wisconsin than Texas, as the data-derived factor weights are closer to the assigned weights for Wisconsin. The correlations between the CHRs and our ranks are 0.89 for Wisconsin and 0.65 for Texas. Uncertainty is especially severe for Texas given the state's substantial missing data. The reliability of comprehensive CHRs varies from state to state. We advise focusing on the counties that remain among the least healthy after incorporating alternate weighting methods and accounting for uncertainty. Our results also highlight the need for broader geographic coverage in health data. © Health Research and Educational Trust.

Content, Structure, and Sequence of the Detailing Discipline at Kendall College of Art and Design.

ERIC Educational Resources Information Center

Mulder, Bruce E.

A study identified the appropriate general content, structure, and sequence for a detailing discipline that promoted student achievement to professional levels. Its focus was the detailing discipline, a sequence of studio courses within the furniture design program at Kendall College of Art and Design, Grand Rapids, Michigan. (Detailing, an…

Comparison of Measures of Predictive Power.

ERIC Educational Resources Information Center

Tarling, Roger

1982-01-01

The Mean Cost Rating, P(A) from Signal Detection Theory, Kendall's rank correlation coefficient tau, and Goodman and Kruskal's gamma measures of predictive power are compared and shown to be different transformations of the statistic S. Gamma is generally preferred for hypothesis testing. Measures of association for ordered contingency tables are…

77 FR 76065 - Endangered and Threatened Wildlife and Plants; Draft Revised Recovery Plan for Kendall Warm...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-26

..., exotic species, grazing, hydrologic changes, invasive plants, pollution, and energy resource exploration... revised recovery plan for the Kendall Warm Springs dace (Rhinichthys osculus thermalis). This species is federally listed as endangered under the Endangered Species Act of 1973, as amended (ESA). The Service...

Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman's rho tests and ARIMA model

NASA Astrophysics Data System (ADS)

Rahman, Mohammad Atiqur; Yunsheng, Lou; Sultana, Nahid

2017-08-01

In this study, 60-year monthly rainfall data of Bangladesh were analysed to detect trends. Modified Mann-Kendall, Spearman's rho tests and Sen's slope estimators were applied to find the long-term annual, dry season and monthly trends. Sequential Mann-Kendall analysis was applied to detect the potential trend turning points. Spatial variations of the trends were examined using inverse distance weighting (IDW) interpolation. AutoRegressive integrated moving average (ARIMA) model was used for the country mean rainfall and for other two stations data which depicted the highest and the lowest trend in the Mann-Kendall and Spearman's rho tests. Results showed that there is no significant trend in annual rainfall pattern except increasing trends for Cox's Bazar, Khulna, Satkhira and decreasing trend for Srimagal areas. For the dry season, only Bogra area represented significant decreasing trend. Long-term monthly trends demonstrated a mixed pattern; both negative and positive changes were found from February to September. Comilla area showed a significant decreasing trend for consecutive 3 months while Rangpur and Khulna stations confirmed the significant rising trends for three different months in month-wise trends analysis. Rangpur station data gave a maximum increasing trend in April whereas a maximum decreasing trend was found in August for Comilla station. ARIMA models predict +3.26, +8.6 and -2.30 mm rainfall per year for the country, Cox's Bazar and Srimangal areas, respectively. However, all the test results and predictions revealed a good agreement among them in the study.

How to Rank Journals

PubMed Central

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. PMID:26930052

How to Rank Journals.

PubMed

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.

Assessing the Readability of Medical Documents: A Ranking Approach.

PubMed

Zheng, Jiaping; Yu, Hong

2018-03-23

The use of electronic health record (EHR) systems with patient engagement capabilities, including viewing, downloading, and transmitting health information, has recently grown tremendously. However, using these resources to engage patients in managing their own health remains challenging due to the complex and technical nature of the EHR narratives. Our objective was to develop a machine learning-based system to assess readability levels of complex documents such as EHR notes. We collected difficulty ratings of EHR notes and Wikipedia articles using crowdsourcing from 90 readers. We built a supervised model to assess readability based on relative orders of text difficulty using both surface text features and word embeddings. We evaluated system performance using the Kendall coefficient of concordance against human ratings. Our system achieved significantly higher concordance (.734) with human annotators than did a baseline using the Flesch-Kincaid Grade Level, a widely adopted readability formula (.531). The improvement was also consistent across different disease topics. This method's concordance with an individual human user's ratings was also higher than the concordance between different human annotators (.658). We explored methods to automatically assess the readability levels of clinical narratives. Our ranking-based system using simple textual features and easy-to-learn word embeddings outperformed a widely used readability formula. Our ranking-based method can predict relative difficulties of medical documents. It is not constrained to a predefined set of readability levels, a common design in many machine learning-based systems. Furthermore, the feature set does not rely on complex processing of the documents. One potential application of our readability ranking is personalization, allowing patients to better accommodate their own background knowledge. ©Jiaping Zheng, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.03.2018.

Diversity rankings among bacterial lineages in soil.

PubMed

Youssef, Noha H; Elshahed, Mostafa S

2009-03-01

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

The design and content of orthodontic practise websites in the UK is suboptimal and does not correlate with search ranking.

PubMed

Patel, Annika; Cobourne, Martyn T

2015-08-01

This study investigated standards of ethical advertising; design and content; and information quality associated with UK dental practice websites offering orthodontic treatment. The World Wide Web was searched from a UK-based computer using the Google search engine combined with the term 'orthodontic braces'. The first 100 UK-based dental practice websites were pooled and saved following duplicate removal. Websites were evaluated for compliance with current General Dental Council ethical advertising guidelines; accessibility, usability, and reliability using the LIDA instrument (a validated outcome tool for healthcare website design and content evaluation); and quality of information using the DISCERN toolkit (a validated method of quality assessment for online written patient information). Nine per cent of websites demonstrated full compliance with current guidelines on ethical advertising. Mean total LIDA score was 110/144 (76%) [range: 51-135; 35-94%]. Eleven websites reached a gold standard of 90% or more for total LIDA score. Mean total DISCERN score was 48/75 (64%) [range: 19-73; 25-97%]. Five websites achieved a total DISCERN score above 90%. Spearman's rank correlation coefficients demonstrated no significant correlations between LIDA (0.1669; P = 0.4252, confidence interval [CI]: -0.2560 to 0.5362) or DISCERN (0.3572; P = 0.0796, CI: -0.0565 to 0.663) score and ranking amongst the 25 highest ranked websites. Most UK websites offering orthodontic services are not fully compliant with national guidelines relating to ethical advertising. Validated measures of website design (LIDA) and information quality (DISCERN) showed wide variation amongst sites. No correlation existed between ranking amongst the highest 25 sites and either of these measures. This investigation was limited to a subsample of UK-only websites; and whilst not representative of European-wide sites, it does suggest that in the UK at least website quality can be improved. © The Author 2014

Rank Order Entropy: why one metric is not enough

PubMed Central

McLellan, Margaret R.; Ryan, M. Dominic; Breneman, Curt M.

2011-01-01

The use of Quantitative Structure-Activity Relationship models to address problems in drug discovery has a mixed history, generally resulting from the mis-application of QSAR models that were either poorly constructed or used outside of their domains of applicability. This situation has motivated the development of a variety of model performance metrics (r2, PRESS r2, F-tests, etc) designed to increase user confidence in the validity of QSAR predictions. In a typical workflow scenario, QSAR models are created and validated on training sets of molecules using metrics such as Leave-One-Out or many-fold cross-validation methods that attempt to assess their internal consistency. However, few current validation methods are designed to directly address the stability of QSAR predictions in response to changes in the information content of the training set. Since the main purpose of QSAR is to quickly and accurately estimate a property of interest for an untested set of molecules, it makes sense to have a means at hand to correctly set user expectations of model performance. In fact, the numerical value of a molecular prediction is often less important to the end user than knowing the rank order of that set of molecules according to their predicted endpoint values. Consequently, a means for characterizing the stability of predicted rank order is an important component of predictive QSAR. Unfortunately, none of the many validation metrics currently available directly measure the stability of rank order prediction, making the development of an additional metric that can quantify model stability a high priority. To address this need, this work examines the stabilities of QSAR rank order models created from representative data sets, descriptor sets, and modeling methods that were then assessed using Kendall Tau as a rank order metric, upon which the Shannon Entropy was evaluated as a means of quantifying rank-order stability. Random removal of data from the training set, also

Global network centrality of university rankings

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Relative abundance and lengths of Kendall Warm Springs dace captured from different habitats in a specially designed trap

USGS Publications Warehouse

Gryska, A.D.; Hubert, W.A.; Gerow, K.G.

1998-01-01

A trap was designed to capture endangered Kendall Warm Springs dace Rhinichthys osculus thermalis (a subspecies of speckled dace Rhinichthys osculus) without being destructive to the habitat of the fish in Kendall Warm Springs Creek, Wyoming. Four experiments were conducted to determine differences in catch per unit effort (CPUE) and length frequencies of fish among differing habitat types. The CPUE was highest in channel habitats with current, and one experiment indicated that it was particularly high at vertical interfaces with vegetation. Longer fish were captured in channel habitats away from vegetation than in vegetated areas. The CPUE was significantly greater during the day than at night during one experiment, but no significant differences were observed among the other three experiments. The traps were easy and inexpensive to construct, could be used in a variety of stream habitats, and may have applications in other small streams for sampling small, benthic fishes.

The existence of High Conservation Value Forest (HCVF) in Perum Perhutani KPH Kendal to support Implementation of FSC Certification

NASA Astrophysics Data System (ADS)

Sulistyowati, Sri; Hadi, Sudharto P.

2018-02-01

High Conservation Value Forest (HCVF) is the identification of High Conservation Values that are important and need to be protected. Under FSC certification mechanism, HCVF becomes one of Principles and Criteria to attain certification. In this study, we identify the existence of HCVF in Perum Perhutani KPH Kendal to support implementation process of FSC certification. Qualitative method was conducted through observation and secondary data from Perum Perhutani KPH Kendal. Data analysis showed through ecolabel certification, Perum Perhutani KPH Kendal has been identified HCVF area covering 2,715.5 hectares consists of HCV 1 until 6. Secondary Natural Forest (HAS) Subah and Kaliwungu for Ulolanang and Pagerwunung Nature Reserve buffer zone include as HCV 1.1, conservation area of leopard (Panthera pardus melas) and Pangolin (Manis javanica).for HCV 1.2, conservation area of lutung (Trachypiyhecus auratus) as endemic species for CITES App I and Critically Endangered species include as HCV 1.3, Goa kiskendo for bats species habitat include as HCV 1.4, regions of interest species for Deer (Cervus timorensis) and Kepodang (Oriolus chinensis) as HCV 2.3, Germplasm Protection Region/ KPPN area with high biodiversity include as HCV 3, river border area and water springs for HCV 4. While, utilization of firewood, grass for cattle fodder include as HCV 5 and 14 cultural sites include as HCV 6. From monitoring and evaluation of HCVF data, showed that in 2011-2015 the level of diversity for flora and fauna were increased.

Visualizing Rank Time Series of Wikipedia Top-Viewed Pages.

PubMed

Xia, Jing; Hou, Yumeng; Chen, Yingjie Victor; Qian, Zhenyu Cheryl; Ebert, David S; Chen, Wei

2017-01-01

Visual clutter is a common challenge when visualizing large rank time series data. WikiTopReader, a reader of Wikipedia page rank, lets users explore connections among top-viewed pages by connecting page-rank behaviors with page-link relations. Such a combination enhances the unweighted Wikipedia page-link network and focuses attention on the page of interest. A set of user evaluations shows that the system effectively represents evolving ranking patterns and page-wise correlation.

Partial Roc Reveals Superiority of Mutual Rank of Pearson's Correlation Coefficient as a Coexpression Measure to Elucidate Functional Association of Genes

NASA Astrophysics Data System (ADS)

Obayashi, Takeshi; Kinoshita, Kengo

2013-01-01

Gene coexpression analysis is a powerful approach to elucidate gene function. We have established and developed this approach using vast amount of publicly available gene expression data measured by microarray techniques. The coexpressed genes are used to estimate gene function of the guide gene or to construct gene coexpression networks. In the case to construct gene networks, researchers should introduce an arbitrary threshold of gene coexpression, because gene coexpression value is continuous value. In the viewpoint to introduce common threshold of gene coexpression, we previously reported rank of Pearson's correlation coefficient (PCC) is more useful than the original PCC value. In this manuscript, we re-assessed the measure of gene coexpression to construct gene coexpression network, and found that mutual rank (MR) of PCC showed better performance than rank of PCC and the original PCC in low false positive rate.

Global network centrality of university rankings

PubMed Central

Del Vecchio, Marco; Pogrebna, Ganna

2017-01-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport’s aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity. PMID:29134105

An Array-Based Analysis of MicroRNA Expression Comparing Matched Frozen and Formalin-Fixed Paraffin-Embedded Human Tissue Samples

PubMed Central

Zhang, Xiao; Chen, Jiamin; Radcliffe, Tom; LeBrun, Dave P.; Tron, Victor A.; Feilotter, Harriet

2008-01-01

MicroRNAs (miRNAs) are small, noncoding RNAs that suppress gene expression at the posttranscriptional level via an antisense RNA-RNA interaction. miRNAs used for array-based profiling are generally purified from either snap-frozen or fresh samples. Because tissues found in most pathology departments are available only in formalin-fixed and paraffin-embedded (FFPE) states, we sought to evaluate miRNA derived from FFPE samples for microarray analysis. In this study, miRNAs extracted from matched snap-frozen and FFPE samples were profiled using the Agilent miRNA array platform (Agilent, Santa Clara, CA). Each miRNA sample was hybridized to arrays containing probes interrogating 470 human miRNAs. Seven cases were compared in either duplicate or triplicate. Intrachip and interchip analyses demonstrated that the processes of miRNA extraction, labeling, and hybridization from both frozen and FFPE samples are highly reproducible and add little variation to the results; technical replicates showed high correlations with one another (Kendall tau, 0.722 to 0.853; Spearman rank correlation coefficient, 0.891 to 0.954). Our results showed consistent high correlations between matched frozen and FFPE samples (Kendall tau, 0.669 to 0.815; Spearman rank correlation coefficient, 0.847 to 0.948), supporting the use of FFPE-derived miRNAs for array-based, gene expression profiling. PMID:18832457

Personality correlates (BAS-BIS), self-perception of social ranking, and cortical (alpha frequency band) modulation in peer-group comparison.

PubMed

Balconi, Michela; Pagani, Silvia

2014-06-22

The perception and interpretation of social hierarchies are a key part of our social life. In the present research we considered the activation of cortical areas, mainly the prefrontal cortex, related to social ranking perception in conjunction with some personality components (BAS - Behavioral Activation System - and BIS - Behavioral Inhibition System). In two experiments we manipulated the perceived superior/inferior status during a competitive cognitive task. Indeed, we created an explicit and strongly reinforced social hierarchy based on incidental rating in an attentional task. Specifically, a peer group comparison was undertaken and improved (Experiment 1) or decreased (Experiment 2) performance was artificially manipulated by the experimenter. For each experiment two groups were compared, based on a BAS and BIS dichotomy. Alpha band modulation in prefrontal cortex, behavioral measures (performance: error rate, ER; response times, RTs), and self-perceived ranking were considered. Repeated measures ANOVAs and regression analyses showed in Experiment 1 a significant improved cognitive performance (decreased ER and RTs) and higher self-perceived ranking in high-BAS participants. Moreover, their prefrontal activity was increased within the left side (alpha band decreasing). Conversely, in Experiment 2 a significant decreased cognitive performance (increased ER and RTs) and lower self-perceived ranking was observed in higher-BIS participants. Their prefrontal right activity was increased in comparison with higher BAS. The regression analyses confirmed the significant predictive role of alpha band modulation with respect of subjects' performance and self-perception of social ranking, differently for BAS/BIS components. The present results suggest that social status perception is directly modulated by cortical activity and personality correlates. Copyright © 2014 Elsevier Inc. All rights reserved.

Support vector regression scoring of receptor-ligand complexes for rank-ordering and virtual screening of chemical libraries.

PubMed

Li, Liwei; Wang, Bo; Meroueh, Samy O

2011-09-26

The community structure-activity resource (CSAR) data sets are used to develop and test a support vector machine-based scoring function in regression mode (SVR). Two scoring functions (SVR-KB and SVR-EP) are derived with the objective of reproducing the trend of the experimental binding affinities provided within the two CSAR data sets. The features used to train SVR-KB are knowledge-based pairwise potentials, while SVR-EP is based on physicochemical properties. SVR-KB and SVR-EP were compared to seven other widely used scoring functions, including Glide, X-score, GoldScore, ChemScore, Vina, Dock, and PMF. Results showed that SVR-KB trained with features obtained from three-dimensional complexes of the PDBbind data set outperformed all other scoring functions, including best performing X-score, by nearly 0.1 using three correlation coefficients, namely Pearson, Spearman, and Kendall. It was interesting that higher performance in rank ordering did not translate into greater enrichment in virtual screening assessed using the 40 targets of the Directory of Useful Decoys (DUD). To remedy this situation, a variant of SVR-KB (SVR-KBD) was developed by following a target-specific tailoring strategy that we had previously employed to derive SVM-SP. SVR-KBD showed a much higher enrichment, outperforming all other scoring functions tested, and was comparable in performance to our previously derived scoring function SVM-SP.

Linking of EEM spectra with FTICRMS data via van Krevelen diagrams and rank correlation

NASA Astrophysics Data System (ADS)

Herzsprung, Peter; von Tümpling, Wolf; Hertkorn, Norbert; Harir, Mourad; Bravidor, Jenny; Büttner, Olaf; Friese, Kurt; Schmitt-Kopplin, Philippe

2014-05-01

DOM plays an important role in both natural and engineered water systems. Due to its sensitivity and non-destruction of samples EEM is widespread used for comprehension of CDOM. EEM provides sensitive bulk optical parameters with low structural resolution concerning DOM quality even when spectra are modelled by PARAFAC or EEM is coupled to chromatography. Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) is a high-resolution analytical tool to determine the elemental compositions of thousands of DOM components directly out of mixtures. Lacking the ability for identification of distinct chemical substances (isomers), the elemental compositions can nevertheless be allocated to biogeochemical pools by means of van Krevelen diagrams. The spearman rank correlation was applied to link the EEM intensities (humic like fluorescence) with exact molecular formulas and their corresponding relative mass peak abundances. The initiative for this study to find out what is humic like fluorescence was the environmental problem of increasing levels of organic carbon in fresh waters as a great challenge for processing and commercial supply of drinking water. In the southern Saxony region, Germany, raw drinking water is mainly received from reservoirs situated in the ore mountains (Erzgebirge). Most of these reservoirs are affected by high concentrations of humic substances detected by the drinking water administration via measurement of the dissolved organic carbon (DOC) and the spectral absorption coefficient at 254 nm (SAC254). To get a better insight into the DOM composition, the seasonal variability of DOM quality was determined using EEM and FTICRMS and coupling these two methods in the catchment area of the reservoir Muldenberg. Thereby, humic-like fluorescence could be allocated to the pool of oxygen-rich and relatively unsaturated components with stoichiometries similar to those of tannic acids [1]. [1] Herzsprung, P., von Tümpling, W., Hertkorn, N., Harir

Understanding Kendal aquifer system: a baseline analysis for sustainable water management proposal

NASA Astrophysics Data System (ADS)

Lukman, A.; Aryanto, M. D.; Pramudito, A.; Andhika, A.; Irawan, D. E.

2017-07-01

North coast of Java has been grown as the center of economic activities and major connectivity hub for Sumatra and Bali. Sustainable water management must support such role. One of the basis is to understand the baseline of groundwater occurrences and potential. However the complex alluvium aquiver system has not been well-understood. A geoelectric measurements were performed to determine which rock layer has a good potential as groundwater aquifers in the northern coast of Kaliwungu Regency, Kendal District, Central Java province. Total of 10 vertical electrical sounding (VES) points has been performed, using a Schlumberger configuration with the current electrode spacing (AB/2) varies between 200 - 300 m and the potential difference electrode spacing (MN/2) varies between 0.5 to 20 m with depths target ranging between 150 - 200 m. Geoelectrical data processing is done using Ip2win software which generates resistivity value, thickness and depth of subsurface rock layers. Based on the correlation between resistivity value with regional geology, hydrogeology and local well data, we identify three aquifer layers. The first layer is silty clay with resistivity values vary between 0 - 10 ohm.m, then the second layer is tuffaceous claystone with resistivity value between 10 - 60 ohm.m. Both layers serve as impermeable layer. The third layer is sandy tuff with resistivity value between 60 - 100 ohm.m which serves as a confined aquifer layer located at 70 - 100 m below surface. Its thickness is vary between 70 to 110 m. The aquifer layer is a mixing of volcanic and alluvium sediment, which is a member of Damar Formation. The stratification of the aquifer system may change in short distance and depth. This natural setting prevent us to make a long continuous correlation between layers. Aquifer discharge is estimated between 5 - 71 L/s with the potential deep well locations lies in the west and southeast part of the study area. These hydrogeological settings should be used

Business Students' Ranking of Reasons for Assessment: Gender Differences.

ERIC Educational Resources Information Center

Adams, Carl; Thomas, Richard; King, Karen

2000-01-01

Describes an explorative study to investigate the purposes of assessment as seen from the student perspective. Results showed strong correlation in the ranked reasons for assessment across gender and between the two institutions involved. Some significant differences in gender were observed in the top ranked reasons. Discusses possible extensions…

Trachomatous Scar Ranking: A Novel Outcome for Trachoma Studies.

PubMed

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

2017-06-01

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

[Relativity among starch quantity, polysaccharides content and total alkaloid content of Dendrobium loddigesii].

PubMed

Zhu, Hua; Teng, Jianbei; Cai, Yi; Liang, Jie; Zhu, Yilin; Wei, Tao

2011-12-01

To find out the relativity among starch quantity, polysaccharides content and total alkaloid content of Dendrobium loddigesii. Microscopy-counting process was applied to starch quantity statistics, sulfuric acid-anthrone colorimetry was used to assay polysaccharides content and bromocresol green colorimetry was used to assay alkaloid content. Pearson product moment correlation analysis, Kendall's rank correlation analysis and Spearman's concordance coefficient analysis were applied to study their relativity. Extremely significant positive correlation was found between starch quantity and polysaccharides content, and significant negative correlation between alkaloid content and starch quantity was discovered, as well was between alkaloid content and polysaccharides content.

Comparison and ranking of superelasticity of different austenite active nickel-titanium orthodontic archwires using mechanical tensile testing and correlating with its electrical resistivity

PubMed Central

Nagarajan, D.; Baskaranarayanan, Balashanmugam; Usha, K.; Jayanthi, M. S.; Vijjaykanth, M.

2016-01-01

Introduction: The application of light and continuous forces for optimum physiological response and the least damage to the tooth supporting structures should be the primary aim of an orthodontist. Nickel-titanium (NiTi) alloys with their desirable properties are one of the natural choices of the clinicians. Aim: This study was aimed to compare and rank them based on its tensile strength and electrical resistivity. Materials and Methods: The sample consisted of eight groups of 0.017 inch × 0.025 inch rectangular archwires from eight different manufacturers, and five samples from each group for tensile testing and nine samples for electrical resistivity tests were used. Data for stress at 10% strain and the initial slope were statistically analyzed with an analysis of variance and Scheffe tests with P < 0.05. The stress/strain plots of each product were ranked for superelastic behavior. The rankings of the wires tested were based primarily on the unloading curve's slope which is indicative of the magnitude of the deactivation force and secondarily on the length of the horizontal segment which is indicative of continuous forces during deactivation. For calculating the electric resistivity, the change in resistance after inducing strain in the wires was taken into account for the calculation of degree of martensite transformation and for ranking. Results: In tensile testing Ortho Organizers wires ranked first and GAC Lowland NiTi wires ranked last. For resistivity tests Ormco A wires were found superior and Morelli remained last. Conclusion: these rankings should be correlated clinically and need further studies. PMID:27829751

Suppression pheromone and cockroach rank formation

NASA Astrophysics Data System (ADS)

Kou, Rong; Chang, Huan-Wen; Chen, Shu-Chun; Ho, Hsiao-Yung

2009-06-01

Although agonistic behaviors in the male lobster cockroach ( Nauphoeta cinerea) are well known, the formation of an unstable hierarchy has long been a puzzle. In this study, we investigate how the unstable dominance hierarchy in N. cinerea is maintained via a pheromone signaling system. In agonistic interactions, aggressive posture (AP) is an important behavioral index of aggression. This study showed that, during the formation of a governing hierarchy, thousands of nanograms of 3-hydroxy-2-butanone (3H-2B) were released by the AP-adopting dominant in the first encounter fight, then during the early domination period and that this release of 3H-2B was related to rank maintenance, but not to rank establishment. For rank maintenance, 3H-2B functioned as a suppression pheromone, which suppressed the fighting capability of rivals and kept them in a submissive state. During the period of rank maintenance, as the dominant male gradually decreased his 3H-2B release, the fighting ability of the subordinate gradually developed, as shown by the increasing odds of a subordinate adopting an AP (OSAP). The OSAP was negatively correlated with the amount of 3H-2B released by the dominant and positively correlated with the number of domination days. The same OSAP could be achieved earlier by reducing the amount of 3H-2B released by the dominant indicates that whether the subordinate adopts an offensive strategy depends on what the dominant is doing.

Rank Dynamics

NASA Astrophysics Data System (ADS)

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

Urinary testosterone-metabolite levels and dominance rank in male and female bonobos (Pan paniscus).

PubMed

Sannen, Adinda; Van Elsacker, Linda; Heistermann, Michael; Eens, Marcel

2004-04-01

The correlation between testosterone (T) and dominance rank may vary among species, and is expected to become stronger as the importance of aggressive competition for rank increases. However, it may also vary among social situations within a species, showing a stronger correlation during socially unstable periods. Knowledge on this topic in great apes, especially in females, is scant. This study presents the first data on the relationship between T and dominance rank in both sexes of the bonobo ( Pan paniscus). For each period (four socially unstable and two stable ones), linear rank orders were determined and subsequently correlated with the accompanying mean urinary T-metabolite concentrations (measured as immunoreactive 5alpha-androstan-17alpha-ol-3-one). No correlation between these two variables was found for either sex among individuals during socially unstable or stable periods. Also, within an individual over the six periods, no relationship of T with rank could be demonstrated. These results suggest that either the outcomes of aggressions have no influence on T levels, or such clear outcomes appear insufficiently frequent to affect T levels over longer periods. Even during the unstable periods, the rate of aggressions was not higher than during stable periods, suggesting that frequencies of aggression have little effect on rank. Further analyses indeed demonstrated no correlation between frequencies of overall aggressions or any type of aggressive behavior separately, or rank. Perhaps factors other than the frequency of displayed aggressions alone have a marked influence on a bonobo's rank, for example, coalition partners. Overall, in bonobos, T apparently does not form a physiological reflection of social status.

Social ranking effects on tooth-brushing behaviour.

PubMed

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

Characterizing Microseismicity at the Newberry Volcano Geothermal Site using PageRank

NASA Astrophysics Data System (ADS)

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

An Improved Rank Correlation Effect Size Statistic for Single-Case Designs: Baseline Corrected Tau.

PubMed

Tarlow, Kevin R

2017-07-01

Measuring treatment effects when an individual's pretreatment performance is improving poses a challenge for single-case experimental designs. It may be difficult to determine whether improvement is due to the treatment or due to the preexisting baseline trend. Tau- U is a popular single-case effect size statistic that purports to control for baseline trend. However, despite its strengths, Tau- U has substantial limitations: Its values are inflated and not bound between -1 and +1, it cannot be visually graphed, and its relatively weak method of trend control leads to unacceptable levels of Type I error wherein ineffective treatments appear effective. An improved effect size statistic based on rank correlation and robust regression, Baseline Corrected Tau, is proposed and field-tested with both published and simulated single-case time series. A web-based calculator for Baseline Corrected Tau is also introduced for use by single-case investigators.

Cross-modal learning to rank via latent joint representation.

PubMed

Wu, Fei; Jiang, Xinyang; Li, Xi; Tang, Siliang; Lu, Weiming; Zhang, Zhongfei; Zhuang, Yueting

2015-05-01

Cross-modal ranking is a research topic that is imperative to many applications involving multimodal data. Discovering a joint representation for multimodal data and learning a ranking function are essential in order to boost the cross-media retrieval (i.e., image-query-text or text-query-image). In this paper, we propose an approach to discover the latent joint representation of pairs of multimodal data (e.g., pairs of an image query and a text document) via a conditional random field and structural learning in a listwise ranking manner. We call this approach cross-modal learning to rank via latent joint representation (CML²R). In CML²R, the correlations between multimodal data are captured in terms of their sharing hidden variables (e.g., topics), and a hidden-topic-driven discriminative ranking function is learned in a listwise ranking manner. The experiments show that the proposed approach achieves a good performance in cross-media retrieval and meanwhile has the capability to learn the discriminative representation of multimodal data.

Processing of Antenna-Array Signals on the Basis of the Interference Model Including a Rank-Deficient Correlation Matrix

NASA Astrophysics Data System (ADS)

Rodionov, A. A.; Turchin, V. I.

2017-06-01

We propose a new method of signal processing in antenna arrays, which is called the Maximum-Likelihood Signal Classification. The proposed method is based on the model in which interference includes a component with a rank-deficient correlation matrix. Using numerical simulation, we show that the proposed method allows one to ensure variance of the estimated arrival angle of the plane wave, which is close to the Cramer-Rao lower boundary and more efficient than the best-known MUSIC method. It is also shown that the proposed technique can be efficiently used for estimating the time dependence of the useful signal.

0.1 Trend analysis of δ18O composition of precipitation in Germany: Combining Mann-Kendall trend test and ARIMA models to correct for higher order serial correlation

NASA Astrophysics Data System (ADS)

Klaus, Julian; Pan Chun, Kwok; Stumpp, Christine

2015-04-01

Spatio-temporal dynamics of stable oxygen (18O) and hydrogen (2H) isotopes in precipitation can be used as proxies for changing hydro-meteorological and regional and global climate patterns. While spatial patterns and distributions gained much attention in recent years the temporal trends in stable isotope time series are rarely investigated and our understanding of them is still limited. These might be a result of a lack of proper trend detection tools and effort for exploring trend processes. Here we make use of an extensive data set of stable isotope in German precipitation. In this study we investigate temporal trends of δ18O in precipitation at 17 observation station in Germany between 1978 and 2009. For that we test different approaches for proper trend detection, accounting for first and higher order serial correlation. We test if significant trends in the isotope time series based on different models can be observed. We apply the Mann-Kendall trend tests on the isotope series, using general multiplicative seasonal autoregressive integrate moving average (ARIMA) models which account for first and higher order serial correlations. With the approach we can also account for the effects of temperature, precipitation amount on the trend. Further we investigate the role of geographic parameters on isotope trends. To benchmark our proposed approach, the ARIMA results are compared to a trend-free prewhiting (TFPW) procedure, the state of the art method for removing the first order autocorrelation in environmental trend studies. Moreover, we explore whether higher order serial correlations in isotope series affects our trend results. The results show that three out of the 17 stations have significant changes when higher order autocorrelation are adjusted, and four stations show a significant trend when temperature and precipitation effects are considered. Significant trends in the isotope time series are generally observed at low elevation stations (≤315 m a

To Rank or to Be Ranked: The Impact of Global Rankings in Higher Education

ERIC Educational Resources Information Center

Marginson, Simon; van der Wende, Marijk

2007-01-01

Global university rankings have cemented the notion of a world university market arranged in a single "league table" for comparative purposes and have given a powerful impetus to intranational and international competitive pressures in the sector. Both the research rankings by Shanghai Jiao Tong University and the composite rankings by…

Ranking and averaging independent component analysis by reproducibility (RAICAR).

PubMed

Yang, Zhi; LaConte, Stephen; Weng, Xuchu; Hu, Xiaoping

2008-06-01

Independent component analysis (ICA) is a data-driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient-based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between-realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data. Copyright 2007 Wiley-Liss, Inc.

Impact of Doximity Residency Rankings on Emergency Medicine Applicant Rank Lists.

PubMed

Peterson, William J; Hopson, Laura R; Khandelwal, Sorabh; White, Melissa; Gallahue, Fiona E; Burkhardt, John; Rolston, Aimee M; Santen, Sally A

2016-05-01

This study investigates the impact of the Doximity rankings on the rank list choices made by residency applicants in emergency medicine (EM). We sent an 11-item survey by email to all students who applied to EM residency programs at four different institutions representing diverse geographical regions. Students were asked questions about their perception of Doximity rankings and how it may have impacted their rank list decisions. Response rate was 58% of 1,372 opened electronic surveys. This study found that a majority of medical students applying to residency in EM were aware of the Doximity rankings prior to submitting rank lists (67%). One-quarter of these applicants changed the number of programs and ranks of those programs when completing their rank list based on the Doximity rankings (26%). Though the absolute number of programs changed on the rank lists was small, the results demonstrate that the EM Doximity rankings impact applicant decision-making in ranking residency programs. While applicants do not find the Doximity rankings to be important compared to other factors in the application process, the Doximity rankings result in a small change in residency applicant ranking behavior. This unvalidated ranking, based principally on reputational data rather than objective outcome criteria, thus has the potential to be detrimental to students, programs, and the public. We feel it important for specialties to develop consensus around measurable training outcomes and provide freely accessible metrics for candidate education.

Role of RANK and Akt1 activation in human osteosarcoma progression: A clinicopathological study.

PubMed

Zhu, Jianxi; Liu, Yuwei; Zhu, Yong; Zeng, Min; Xie, Jie; Lei, Pengfei; Li, Kanghua; Hu, Yihe

2017-06-01

The receptor activator of nuclear factor κB (RANK) axis is the fundamental signaling pathway in bone formation as well as bone tumor pathophysiology. The aim of the present study was to evaluate the impact of the expression of RANK and its downstream signaling molecule Akt1 on tumor progression in patients with osteosarcoma. Expression of RANK and Akt1 was examined in 78 human osteosarcoma samples by immunohistochemistry using formalin-fixed samples. Following this, each graded immunohistochemistry result was correlated with clinicopathological parameters and patient survival. In total, 60 osteosarcomas (76.9%) expressed RANK and 58 cases (74.4%) showed expression of Akt1. In addition, expression of RANK was negatively correlated with disease-free survival by Kaplan-Meier analysis. A resistance was observed to chemotherapy in RANK-expressing cases, which was statistically significant (P<0.05). In addition, chemotherapy and staging of the tumor were found to independent factors that have an effect on patient survival (P<0.05). Thus, RANK was identified as a negative prognostic factor of osteosarcoma survival.

The influence of base rates on correlations: An evaluation of proposed alternative effect sizes with real-world data.

PubMed

Babchishin, Kelly M; Helmus, Leslie-Maaike

2016-09-01

Correlations are the simplest and most commonly understood effect size statistic in psychology. The purpose of the current paper was to use a large sample of real-world data (109 correlations with 60,415 participants) to illustrate the base rate dependence of correlations when applied to dichotomous or ordinal data. Specifically, we examined the influence of the base rate on different effect size metrics. Correlations decreased when the dichotomous variable did not have a 50 % base rate. The higher the deviation from a 50 % base rate, the smaller the observed Pearson's point-biserial and Kendall's tau correlation coefficients. In contrast, the relationship between base rate deviations and the more commonly proposed alternatives (i.e., polychoric correlation coefficients, AUCs, Pearson/Thorndike adjusted correlations, and Cohen's d) were less remarkable, with AUCs being most robust to attenuation due to base rates. In other words, the base rate makes a marked difference in the magnitude of the correlation. As such, when using dichotomous data, the correlation may be more sensitive to base rates than is optimal for the researcher's goals. Given the magnitude of the association between the base rate and point-biserial correlations (r = -.81) and Kendall's tau (r = -.80), we recommend that AUCs, Pearson/Thorndike adjusted correlations, Cohen's d, or polychoric correlations should be considered as alternate effect size statistics in many contexts.

Plus Disease in Retinopathy of Prematurity: Improving Diagnosis by Ranking Disease Severity and Using Quantitative Image Analysis.

PubMed

Kalpathy-Cramer, Jayashree; Campbell, J Peter; Erdogmus, Deniz; Tian, Peng; Kedarisetti, Dharanish; Moleta, Chace; Reynolds, James D; Hutcheson, Kelly; Shapiro, Michael J; Repka, Michael X; Ferrone, Philip; Drenser, Kimberly; Horowitz, Jason; Sonmez, Kemal; Swan, Ryan; Ostmo, Susan; Jonas, Karyn E; Chan, R V Paul; Chiang, Michael F

2016-11-01

To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06-0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74-0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95-0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). Experts

A Review on Climate Change in Weather Stations of Guilan Province Using Mann-Kendal Methodand GIS

NASA Astrophysics Data System (ADS)

Behzadi, Jalal

2016-07-01

Climate has always been changing during the life time of the earth, and has appeared in the form of ice age, hurricanes, severe and sudden temperature changes, precipitation and other climatic elements, and has dramatically influenced the environment, and in some cases has caused severe changes and even destructions. Some of the most important aspects of climate changes can be found in precipitation types of different regions in the world and especially Guilan, which is influenced by drastic land conversions and greenhouse gases. Also, agriculture division, industrial activities and unnecessary land conversions are thought to have a huge influence on climate change. Climate change is a result of abnormalcies of metorologyl parameters. Generally, the element of precipitation is somehow included in most theories about climate change. The present study aims to reveal precipitation abnormalcies in Guilan which lead to climate change, and possible deviations of precipitation parameter based on annual, seasonal and monthly series have been evaluated. The Mann-Kendal test has been used to reveal likely deviations leading to climate change. The trend of precipitation changes in long-term has been identifiedusing this method. Also, the beginning and end of these changes have been studied in five stations as representatives of all the thirteen weather stations. Then,the areas which have experienced climate change have been identified using the GIS software along with the severity of the changes with an emphasis on drought. These results can be used in planning and identifying the effects of these changes on the environment. Keywords: Climate Change, Guilan, Mann-Kendal, GIS

RANK Expression and Osteoclastogenesis in Human Monocytes in Peripheral Blood from Rheumatoid Arthritis Patients.

PubMed

Nanke, Yuki; Kobashigawa, Tsuyoshi; Yago, Toru; Kawamoto, Manabu; Yamanaka, Hisashi; Kotake, Shigeru

2016-01-01

Rheumatoid arthritis (RA) appears as inflammation of synovial tissue and joint destruction. Receptor activator of NF- κ B (RANK) is a member of the TNF receptor superfamily and a receptor for the RANK ligand (RANKL). In this study, we examined the expression of RANK high and CCR6 on CD14 + monocytes from patients with RA and healthy volunteers. Peripheral blood samples were obtained from both the RA patients and the healthy volunteers. Osteoclastogenesis from monocytes was induced by RANKL and M-CSF in vitro . To study the expression of RANK high and CCR6 on CD14 + monocytes, two-color flow cytometry was performed. Levels of expression of RANK on monocytes were significantly correlated with the level of osteoclastogenesis in the healthy volunteers. The expression of RANK high on CD14 + monocyte in RA patients without treatment was elevated and that in those receiving treatment was decreased. In addition, the high-level expression of RANK on CD14 + monocytes was correlated with the high-level expression of CCR6 in healthy volunteers. Monocytes expressing both RANK and CCR6 differentiate into osteoclasts. The expression of CD14 + RANK high in untreated RA patients was elevated. RANK and CCR6 expressed on monocytes may be novel targets for the regulation of bone resorption in RA and osteoporosis.

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

DTIC Science & Technology

2015-04-28

the players . In addition, we compare the algorithms on three real data sets: the outcome of soccer games in the English Premier League, a Microsoft...Premier League soccer games, a Halo 2 game tournament and NCAA College Basketball games), which show that our proposed method compares favorably to...information on the ground truth rank of a subset of players , and propose an algorithm based on SDP which is able to recover the ranking of the remaining

Microseismic Event Relocation and Focal Mechanism Estimation Based on PageRank Linkage

NASA Astrophysics Data System (ADS)

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

2017-12-01

Microseismicity associated with enhanced geothermal systems (EGS) is key in understanding how subsurface stimulation can modify stress, fracture rock, and increase permeability. Large numbers of microseismic events are commonly associated with hydroshearing an EGS, making data mining methods useful in their analysis. We focus on PageRank, originally developed as Google's search engine, and subsequently adapted for use in seismology to detect low-frequency earthquakes by linking events directly and indirectly through cross-correlation (Aguiar and Beroza, 2014). We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes from the Newberry Volcano EGS in Central Oregon, which has been stimulated two times using high-pressure fluid injection. We create PageRank signal families from both data sets and compare these to the spatial and temporal proximity of associated earthquakes. PageRank families are relocated using differential travel times measured by waveform cross-correlation (CC) and the Bayesloc approach (Myers et al., 2007). Prior to relocation events are loosely clustered with events at a distance from the cluster. After relocation, event families are found to be tightly clustered. Indirect linkage of signals using PageRank is a reliable way to increase the number of events confidently determined to be similar, suggesting an efficient and effective grouping of earthquakes with similar physical characteristics (ie. location, focal mechanism, stress drop). We further explore the possibility of using PageRank families to identify events with similar relative phase polarities and estimate focal mechanisms following Shelly et al. (2016) method, where CC measurements are used to determine individual polarities within event clusters. Given a positive result, PageRank might be a useful tool in adaptive approaches to enhance production at well-instrumented geothermal sites. Prepared by LLNL under Contract DE-AC52-07NA27344

Max-margin multiattribute learning with low-rank constraint.

PubMed

Zhang, Qiang; Chen, Lin; Li, Baoxin

2014-07-01

Attribute learning has attracted a lot of interests in recent years for its advantage of being able to model high-level concepts with a compact set of midlevel attributes. Real-world objects often demand multiple attributes for effective modeling. Most existing methods learn attributes independently without explicitly considering their intrinsic relatedness. In this paper, we propose max margin multiattribute learning with low-rank constraint, which learns a set of attributes simultaneously, using only relative ranking of the attributes for the data. By learning all the attributes simultaneously through low-rank constraint, the proposed method is able to capture their intrinsic correlation for improved learning; by requiring only relative ranking, the method avoids restrictive binary labels of attributes that are often assumed by many existing techniques. The proposed method is evaluated on both synthetic data and real visual data including a challenging video data set. Experimental results demonstrate the effectiveness of the proposed method.

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

NASA Astrophysics Data System (ADS)

Shams, Bita; Haratizadeh, Saman

2016-09-01

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

Quantum anonymous ranking

NASA Astrophysics Data System (ADS)

Huang, Wei; Wen, Qiao-Yan; Liu, Bin; Su, Qi; Qin, Su-Juan; Gao, Fei

2014-03-01

Anonymous ranking is a kind of privacy-preserving ranking whereby each of the involved participants can correctly and anonymously get the rankings of his data. It can be utilized to solve many practical problems, such as anonymously ranking the students' exam scores. We investigate the issue of how quantum mechanics can be of use in maintaining the anonymity of the participants in multiparty ranking and present a series of quantum anonymous multiparty, multidata ranking protocols. In each of these protocols, a participant can get the correct rankings of his data and nobody else can match the identity to his data. Furthermore, the security of these protocols with respect to different kinds of attacks is proved.

Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

NASA Astrophysics Data System (ADS)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

Rank-dependent deactivation in network evolution.

PubMed

Xu, Xin-Jian; Zhou, Ming-Chen

2009-12-01

A rank-dependent deactivation mechanism is introduced to network evolution. The growth dynamics of the network is based on a finite memory of individuals, which is implemented by deactivating one site at each time step. The model shows striking features of a wide range of real-world networks: power-law degree distribution, high clustering coefficient, and disassortative degree correlation.

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

PubMed

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

2012-12-01

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

Efficiency of including first-generation information in second-generation ranking and selection: results of computer simulation.

Treesearch

T.Z. Ye; K.J.S. Jayawickrama; G.R. Johnson

2006-01-01

Using computer simulation, we evaluated the impact of using first-generation information to increase selection efficiency in a second-generation breeding program. Selection efficiency was compared in terms of increase in rank correlation between estimated and true breeding values (i.e., ranking accuracy), reduction in coefficient of variation of correlation...

The Marketing of Canadian University Rankings: A Misadventure Now 24 Years Old

ERIC Educational Resources Information Center

Cramer, Kenneth M.; Page, Stewart; Burrows, Vanessa; Lamoureux, Chastine; Mackay, Sarah; Pedri, Victoria; Pschibul, Rebecca

2016-01-01

Based on analyses of Maclean's ranking data pertaining to Canadian universities published over the last 24 years, we present a summary of statistical findings of annual ranking exercises, as well as discussion about their current status and the effects upon student welfare. Some illustrative tables are also presented. Using correlational and…

Econophysics of a ranked demand and supply resource allocation problem

NASA Astrophysics Data System (ADS)

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.

TRENDS IN FLOODS AND LOW FLOWS IN THE UNITED STATES: IMPACT OF SPATIAL CORRELATION. (R824992,R826888)

EPA Science Inventory

Trends in flood and low flows in the US were evaluated using a regional average Kendall's S trend test at two spatial scales and over two timeframes. Field significance was assessed using a bootstrap methodology to account for the observed regional cross-correlation of streamflow...

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

ERIC Educational Resources Information Center

Tienken, Christopher H.

2008-01-01

Examining a popular political notion, this article presents results from a series of Spearman Rho calculations conducted to investigate relationships between countries' rankings on international tests of mathematics and science and future economic competitiveness as measured by the 2006 World Economic Forum's Growth Competitiveness Index (GCI).…

Exponential smoothing weighted correlations

NASA Astrophysics Data System (ADS)

Pozzi, F.; Di Matteo, T.; Aste, T.

2012-06-01

In many practical applications, correlation matrices might be affected by the "curse of dimensionality" and by an excessive sensitiveness to outliers and remote observations. These shortcomings can cause problems of statistical robustness especially accentuated when a system of dynamic correlations over a running window is concerned. These drawbacks can be partially mitigated by assigning a structure of weights to observational events. In this paper, we discuss Pearson's ρ and Kendall's τ correlation matrices, weighted with an exponential smoothing, computed on moving windows using a data-set of daily returns for 300 NYSE highly capitalized companies in the period between 2001 and 2003. Criteria for jointly determining optimal weights together with the optimal length of the running window are proposed. We find that the exponential smoothing can provide more robust and reliable dynamic measures and we discuss that a careful choice of the parameters can reduce the autocorrelation of dynamic correlations whilst keeping significance and robustness of the measure. Weighted correlations are found to be smoother and recovering faster from market turbulence than their unweighted counterparts, helping also to discriminate more effectively genuine from spurious correlations.

Extension of latin hypercube samples with correlated variables.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hora, Stephen Curtis; Helton, Jon Craig; Sallaberry, Cedric J. PhD.

2006-11-01

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number ofmore » model evaluations.« less

Citation Ranking versus Peer Evaluation of Senior Faculty Research Performance: A Case Study of Kurdish Scholarship.

ERIC Educational Resources Information Center

Meho, Lokman I.; Sonnenwald, Diane H.

2000-01-01

Analyzes the relationship between citation ranking and peer evaluation in assessing senior faculty research performance. Describes a study of faculty specializing in Kurdish studies that investigated to what degree citation ranking correlates with data from citation content analysis, book reviews, and peer ranking. (Contains 72 references.)…

Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

PubMed

García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

2018-01-01

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In

Rank order scaling of pictorial depth

PubMed Central

van Doorn, Andrea; Koenderink, Jan; Wagemans, Johan

2011-01-01

We address the topic of “pictorial depth” in cases of pictures that are unlike photographic renderings. The most basic measure of “depth” is no doubt that of depth order. We establish depth order through the pairwise depth-comparison method, involving all pairs from a set of 49 fiducial points. The pictorial space for this study was evoked by a capriccio (imaginary landscape) by Francesco Guardi (1712–1793). In such a drawing pictorial space is suggested by the artist through a small set of conventional depth cues. As a result typical Western observers tend to agree largely in their visual awareness when looking at such art. We rank depths for locations that are not on a single surface and far apart in pictorial space. We find that observers resolve about 40 distinct depth layers and agree largely in this. From a previous experiment we have metrical data for the same observers. The rank correlations between the results are high. Perhaps surprisingly, we find no correlation between the number of distinct depth layers and the total metrical depth range. Thus, the relation between subjective magnitude and discrimination threshold fails to hold for pictorial depth. PMID:23145256

. Facial attractiveness: ranking of end-of-treatment facial photographs by pairs of Chinese and US orthodontists.

PubMed

Xu, Tian-Min; Korn, Edward L; Liu, Yan; Oh, Hee Soo; Lee, Ki Heon; Boyd, Robert L; Baumrind, Sheldon

2008-07-01

In this study, we assessed agreement and disagreement among pairs of Chinese and US orthodontists in the ranking for "facial attractiveness" of end-of-treatment photographs of growing Chinese and white orthodontic patients. Two groups of orthodontist-judges participated: from the University of the Pacific, School of Dentistry, in California and from Peking University School and Hospital of Stomatology in China. Each judge independently ranked standard clinical sets of profile, frontal, and frontal-smiling photographs of 43 white patients and 48 Chinese patients. Pearson correlations were generated for a total of 1980 rankings by pairs of judges. The resulting correlations ranged from +0.004 to +0.96 with a median of +0.54. Of these, 18.7% were lower than 0.4; 41.0% were lower than 0.5; 68.8% were lower than 0.6; 91.6% were lower than 0.7; and only 8.4% were greater than 0.7. As had been anticipated, correlations between judges were higher when they ranked patients of their own ethnicity than when they ranked patients of different ethnicity, but the differences were smaller than had been expected. The rankings of no pair of judges correlated negatively. This is to say that no pair of judges, whether of the same or different ethnicity, ranked the patients so that those 1 judge tended to find attractive were consistently found unattractive by the other. The distribution of levels of agreement between pairs of orthodontists did not differ substantially whether the pairs included 2 US orthodontists, 2 Chinese orthodontists, or 1 US and 1 Chinese orthodontist. As might be expected, the pairs of Chinese orthodontists agreed with each other slightly better on average when ranking Chinese patients, and the pairs of US orthodontists agreed with each other slightly better on average when ranking white American patients, but the overall differences were small. These findings appear consistent with the inference that, on average, judgments of "facial attractiveness" by

Conservation threats and the phylogenetic utility of IUCN Red List rankings in Incilius toads.

PubMed

Schachat, Sandra R; Mulcahy, Daniel G; Mendelson, Joseph R

2016-02-01

Phylogenetic analysis of extinction threat is an emerging tool in the field of conservation. However, there are problems with the methods and data as commonly used. Phylogenetic sampling usually extends to the level of family or genus, but International Union for Conservation of Nature (IUCN) rankings are available only for individual species, and, although different species within a taxonomic group may have the same IUCN rank, the species may have been ranked as such for different reasons. Therefore, IUCN rank may not reflect evolutionary history and thus may not be appropriate for use in a phylogenetic context. To be used appropriately, threat-risk data should reflect the cause of extinction threat rather than the IUCN threat ranking. In a case study of the toad genus Incilius, with phylogenetic sampling at the species level (so that the resolution of the phylogeny matches character data from the IUCN Red List), we analyzed causes of decline and IUCN threat rankings by calculating metrics of phylogenetic signal (such as Fritz and Purvis' D). We also analyzed the extent to which cause of decline and threat ranking overlap by calculating phylogenetic correlation between these 2 types of character data. Incilius species varied greatly in both threat ranking and cause of decline; this variability would be lost at a coarser taxonomic resolution. We found far more phylogenetic signal, likely correlated with evolutionary history, for causes of decline than for IUCN threat ranking. Individual causes of decline and IUCN threat rankings were largely uncorrelated on the phylogeny. Our results demonstrate the importance of character selection and taxonomic resolution when extinction threat is analyzed in a phylogenetic context. © 2015 Society for Conservation Biology.

Michigan's Top-to-Bottom Ranking: A Measure of School Quality or Student Poverty?

ERIC Educational Resources Information Center

Spalding, Audrey

2013-01-01

This study examines the state's "Top-to-Bottom" ranking, which has been repeatedly criticized by educators for appearing to be correlated with school poverty rates. Mackinac Center research finds that schools that serve more lower-income students tend to receive lower scores on the TTB list. These results matters because TTB rankings are…

RANK Expression and Osteoclastogenesis in Human Monocytes in Peripheral Blood from Rheumatoid Arthritis Patients

PubMed Central

Kobashigawa, Tsuyoshi

2016-01-01

Rheumatoid arthritis (RA) appears as inflammation of synovial tissue and joint destruction. Receptor activator of NF-κB (RANK) is a member of the TNF receptor superfamily and a receptor for the RANK ligand (RANKL). In this study, we examined the expression of RANKhigh and CCR6 on CD14+ monocytes from patients with RA and healthy volunteers. Peripheral blood samples were obtained from both the RA patients and the healthy volunteers. Osteoclastogenesis from monocytes was induced by RANKL and M-CSF in vitro. To study the expression of RANKhigh and CCR6 on CD14+ monocytes, two-color flow cytometry was performed. Levels of expression of RANK on monocytes were significantly correlated with the level of osteoclastogenesis in the healthy volunteers. The expression of RANKhigh on CD14+ monocyte in RA patients without treatment was elevated and that in those receiving treatment was decreased. In addition, the high-level expression of RANK on CD14+ monocytes was correlated with the high-level expression of CCR6 in healthy volunteers. Monocytes expressing both RANK and CCR6 differentiate into osteoclasts. The expression of CD14+RANKhigh in untreated RA patients was elevated. RANK and CCR6 expressed on monocytes may be novel targets for the regulation of bone resorption in RA and osteoporosis. PMID:27822475

The Diversity of Vibrios Associated with Vibriosis in Pacific White Shrimp (Litopenaeus vannamei) from Extensive Shrimp Pond in Kendal District, Indonesia

NASA Astrophysics Data System (ADS)

Sarjito; Harjuno Condro Haditomo, Alfabetian; Desrina; Djunaedi, Ali; Budi Prayitno, Slamet

2018-02-01

Vibriosis out breaks frequently occur in extensive shrimps farming. The study were commenced to find out the clinical signs of white shrimp that was infected by the Vibrio and to identify the bacterial associated with vibriosis in the pacific white shrimp, Litopenaeus vannamei. Bacterial isolates were gained from hepatopancreas and telson of moribund shrimps that were collected from extensive shrimp ponds of Kendal District, Indonesia and cultured on Thiosulfate Citrate Bile Salts Sucrose Agar (TCBSA). Isolates were clustered and identified using repetitive sequence-based polymerase chain reaction (rep-PCR). Three representative isolates (SJV 03, SJV 05 and SJV 19) were amplified with PCR using primers for 16S rRNA, and sequence for further identification. The clinical signs of shrimps affected by vibrio were pale hepatopancreas, weak of telson, dark and reddish coloration of smouth, patches of red colour in part of the body on the carapace, periopods, pleuopods, and telson. A total of 19 isolates were obtained and belong to three groups of genus Vibrios. Result of the 16S DNA sequence analysis, the vibrio found in this study related to vibriosis in white shrimps from extensive shrimp ponds of Kendal were closely related to Vibrio harveyi (SJV 03); V. parahaemolyticus (SJV 05) and V. alginolyticus (SJV 19).

Applicant Characteristics Associated With Selection for Ranking at Independent Surgery Residency Programs.

PubMed

Dort, Jonathan M; Trickey, Amber W; Kallies, Kara J; Joshi, Amit R T; Sidwell, Richard A; Jarman, Benjamin T

2015-01-01

This study evaluated characteristics of applicants selected for interview and ranked by independent general surgery residency programs and assessed independent program application volumes, interview selection, rank list formation, and match success. Demographic and academic information was analyzed for 2014-2015 applicants. Applicant characteristics were compared by ranking status using univariate and multivariable statistical techniques. Characteristics independently associated with whether or not an applicant was ranked were identified using multivariable logistic regression modeling with backward stepwise variable selection and cluster-correlated robust variance estimates to account for correlations among individuals who applied to multiple programs. The Electronic Residency Application Service was used to obtain applicant data and program match outcomes at 33 independent surgery programs. All applicants selected to interview at 33 participating independent general surgery residency programs were included in the study. Applicants were 60% male with median age of 26 years. Birthplace was well distributed. Most applicants (73%) had ≥1 academic publication. Median United States Medical Licensing Exams (USMLE) Step 1 score was 228 (interquartile range: 218-240), and median USMLE Step 2 clinical knowledge score was 241 (interquartile range: 231-250). Residency programs in some regions more often ranked applicants who attended medical school within the same region. On multivariable analysis, significant predictors of ranking by an independent residency program were: USMLE scores, medical school region, and birth region. Independent programs received an average of 764 applications (range: 307-1704). On average, 12% interviews, and 81% of interviewed applicants were ranked. Most programs (84%) matched at least 1 applicant ranked in their top 10. Participating independent programs attract a large volume of applicants and have high standards in the selection process

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, Jan P.; Ochoa, Ellen; Sweeney, Donald W.

1990-01-01

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed.

A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

PubMed

Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

2014-10-01

Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

Academic Productivity of US Neurosurgery Residents as Measured by H-Index: Program Ranking with Correlation to Faculty Productivity.

PubMed

Sarkiss, Christopher A; Riley, Kyle J; Hernandez, Christopher M; Oermann, Eric K; Ladner, Travis R; Bederson, Joshua B; Shrivastava, Raj K

2017-06-01

Engagement in research and academic productivity are crucial components in the training of a neurosurgeon. This process typically begins in residency training. In this study, we analyzed individual resident productivity as it correlated to publications across all Accreditation Council for Graduate Medical Education (ACGME)-accredited neurosurgery training programs in an attempt to identify how programs have developed and fostered a research culture and environment. We obtained a list of current neurosurgery residents in ACGME-accredited programs from the American Association of Neurological Surgeons database. An expanded PubMed and Scopus search was conducted for each resident through the present time. We tabulated all articles attributed to each resident. We then categorized the publications based on each neurosurgical subspecialty while in residency. A spreadsheet-based statistical analysis was performed. This formulated the average number of resident articles, h-indices, and most common subspecialty categories by training program. We analyzed 1352 current neurosurgery residents in 105 programs. There were a total of 10 645 publications, of which 3985 were resident first-author publications during the period of study. The most common subspecialties among all resident publications were vascular (24.9%), spine (16.9%), oncology (16.1%), pediatric (5.6%), functional (4.9%), and trauma (3.8%). The average resident published 2.9 first-author papers with average of 38.0 first-author publications by total residents at each program (range 0-241). The average h-index per resident is 2.47 ± 3.25. When comparing previously published faculty h-index program rankings against our resident h-index rankings, there is a strong correlation between the 2 datasets with a clear delineation between Top-20 productivity and that of other programs (average h-index 4.2 vs 1.7, respectively, P < .001). Increasing program size leads to a clear increase in academic productivity on both the

Correlates of cognitive function scores in elderly outpatients.

PubMed

Mangione, C M; Seddon, J M; Cook, E F; Krug, J H; Sahagian, C R; Campion, E W; Glynn, R J

1993-05-01

To determine medical, ophthalmologic, and demographic predictors of cognitive function scores as measured by the Telephone Interview for Cognitive Status (TICS), an adaptation of the Folstein Mini-Mental Status Exam. A secondary objective was to perform an item-by-item analysis of the TICS scores to determine which items correlated most highly with the overall scores. Cross-sectional cohort study. The Glaucoma Consultation Service of the Massachusetts Eye and Ear Infirmary. 472 of 565 consecutive patients age 65 and older who were seen at the Glaucoma Consultation Service between November 1, 1987 and October 31, 1988. Each subject had a standard visual examination and review of medical history at entry, followed by a telephone interview that collected information on demographic characteristics, cognitive status, health status, accidents, falls, symptoms of depression, and alcohol intake. A multivariate linear regression model of correlates of TICS score found the strongest correlates to be education, age, occupation, and the presence of depressive symptoms. The only significant ocular condition that correlated with lower TICS score was the presence of surgical aphakia (model R2 = .46). Forty-six percent (216/472) of patients fell below the established definition of normal on the mental status scale. In a logistic regression analysis, the strongest correlates of an abnormal cognitive function score were age, diabetes, educational status, and occupational status. An item analysis using step-wise linear regression showed that 85 percent of the variance in the TICS score was explained by the ability to perform serial sevens and to repeat 10 items immediately after hearing them. Educational status correlated most highly with both of these items (Kendall Tau R = .43 and Kendall Tau R = .30, respectively). Education, occupation, depression, and age were the strongest correlates of the score on this new screening test for assessing cognitive status. These factors were

Online ranking by projecting.

PubMed

Crammer, Koby; Singer, Yoram

2005-01-01

We discuss the problem of ranking instances. In our framework, each instance is associated with a rank or a rating, which is an integer in 1 to k. Our goal is to find a rank-prediction rule that assigns each instance a rank that is as close as possible to the instance's true rank. We discuss a group of closely related online algorithms, analyze their performance in the mistake-bound model, and prove their correctness. We describe two sets of experiments, with synthetic data and with the EachMovie data set for collaborative filtering. In the experiments we performed, our algorithms outperform online algorithms for regression and classification applied to ranking.

The Publication Ranking Score for pediatric urology: quantifying thought leadership within the subspecialty.

PubMed

Lloyd, Jessica C; Madden-Fuentes, Ramiro J; Nelson, Caleb P; Kokorowski, Paul J; Wiener, John S; Ross, Sherry S; Kutikov, Alexander; Routh, Jonathan C

2013-12-01

Clinical care parameters are frequently assessed by national ranking systems. However, these rankings do little to comment on institutions' academic contributions. The Publication Ranking Score (PRS) was developed to allow for objective comparisons of scientific thought-leadership at various pediatric urology institutions. Faculty lists were compiled for each of the US News & World Report (USNWR) top-50 pediatric urology hospitals. A list of all faculty publications (2006-2011) was then compiled, after adjusting for journal impact factor, and summed to derive a Publication Ranking Score (PRS). PRS rankings were then compared to the USNWR pediatric urology top-50 hospital list. A total of 1811 publications were indexed. PRS rankings resulted in a mean change in rank of 12 positions, compared to USNWR ranks. Of the top-10 USNWR hospitals, only 4 were ranked in the top-10 by the PRS. There was little correlation between the USNWR and PRS ranks for either top-10 (r = 0.42, p = 0.23) or top-50 (r = 0.48, p = 0.0004) hospitals. PRS institutional ranking differs significantly from the USNWR top-50 hospital list in pediatric urology. While not a replacement, we believe the PRS to be a useful adjunct to the USNWR rankings of pediatric urology hospitals. Copyright © 2013 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-01-01

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

The Wilcoxon signed rank test for paired comparisons of clustered data.

PubMed

Rosner, Bernard; Glynn, Robert J; Lee, Mei-Ling T

2006-03-01

The Wilcoxon signed rank test is a frequently used nonparametric test for paired data (e.g., consisting of pre- and posttreatment measurements) based on independent units of analysis. This test cannot be used for paired comparisons arising from clustered data (e.g., if paired comparisons are available for each of two eyes of an individual). To incorporate clustering, a generalization of the randomization test formulation for the signed rank test is proposed, where the unit of randomization is at the cluster level (e.g., person), while the individual paired units of analysis are at the subunit within cluster level (e.g., eye within person). An adjusted variance estimate of the signed rank test statistic is then derived, which can be used for either balanced (same number of subunits per cluster) or unbalanced (different number of subunits per cluster) data, with an exchangeable correlation structure, with or without tied values. The resulting test statistic is shown to be asymptotically normal as the number of clusters becomes large, if the cluster size is bounded. Simulation studies are performed based on simulating correlated ranked data from a signed log-normal distribution. These studies indicate appropriate type I error for data sets with > or =20 clusters and a superior power profile compared with either the ordinary signed rank test based on the average cluster difference score or the multivariate signed rank test of Puri and Sen. Finally, the methods are illustrated with two data sets, (i) an ophthalmologic data set involving a comparison of electroretinogram (ERG) data in retinitis pigmentosa (RP) patients before and after undergoing an experimental surgical procedure, and (ii) a nutritional data set based on a randomized prospective study of nutritional supplements in RP patients where vitamin E intake outside of study capsules is compared before and after randomization to monitor compliance with nutritional protocols.

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, J.P.; Ochoa, E.; Sweeney, D.W.

1987-10-09

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed. 3 figs.

Alpha trimmed correlation for touchless finger image mosaicing

NASA Astrophysics Data System (ADS)

Rao, Shishir P.; Rajendran, Rahul; Agaian, Sos S.; Mulawka, Marzena Mary Ann

2016-05-01

In this paper, a novel technique to mosaic multiview contactless finger images is presented. This technique makes use of different correlation methods, such as, the Alpha-trimmed correlation, Pearson's correlation [1], Kendall's correlation [2], and Spearman's correlation [2], to combine multiple views of the finger. The key contributions of the algorithm are: 1) stitches images more accurately, 2) provides better image fusion effects, 3) has better visual effect on the overall image, and 4) is more reliable. The extensive computer simulations show that the proposed method produces better or comparable stitched images than several state-of-the-art methods, such as those presented by Feng Liu [3], K Choi [4], H Choi [5], and G Parziale [6]. In addition, we also compare various correlation techniques with the correlation method mentioned in [3] and analyze the output. In the future, this method can be extended to obtain a 3D model of the finger using multiple views of the finger, and help in generating scenic panoramic images and underwater 360-degree panoramas.

Pitch ranking, electrode discrimination, and physiological spread-of-excitation using Cochlear's dual-electrode mode.

PubMed

Goehring, Jenny L; Neff, Donna L; Baudhuin, Jacquelyn L; Hughes, Michelle L

2014-08-01

This study compared pitch ranking, electrode discrimination, and electrically evoked compound action potential (ECAP) spatial excitation patterns for adjacent physical electrodes (PEs) and the corresponding dual electrodes (DEs) for newer-generation Cochlear devices (Cochlear Ltd., Macquarie, New South Wales, Australia). The first goal was to determine whether pitch ranking and electrode discrimination yield similar outcomes for PEs and DEs. The second goal was to determine if the amount of spatial separation among ECAP excitation patterns (separation index, Σ) between adjacent PEs and the PE-DE pairs can predict performance on the psychophysical tasks. Using non-adaptive procedures, 13 subjects completed pitch ranking and electrode discrimination for adjacent PEs and the corresponding PE-DE pairs (DE versus each flanking PE) from the basal, middle, and apical electrode regions. Analysis of d' scores indicated that pitch-ranking and electrode-discrimination scores were not significantly different, but rather produced similar levels of performance. As expected, accuracy was significantly better for the PE-PE comparison than either PE-DE comparison. Correlations of the psychophysical versus ECAP Σ measures were positive; however, not all test/region correlations were significant across the array. Thus, the ECAP separation index is not sensitive enough to predict performance on behavioral tasks of pitch ranking or electrode discrimination for adjacent PEs or corresponding DEs.

Telehealth Stroke Dysphagia Evaluation Is Safe and Effective.

PubMed

Morrell, Kate; Hyers, Megan; Stuchiner, Tamela; Lucas, Lindsay; Schwartz, Karissa; Mako, Jenniffer; Spinelli, Kateri J; Yanase, Lisa

2017-01-01

Rapid evaluation of dysphagia poststroke significantly lowers rates of aspiration pneumonia. Logistical barriers often significantly delay in-person dysphagia evaluation by speech language pathologists (SLPs) in remote and rural hospitals. Clinical swallow evaluations delivered via telehealth have been validated in a number of clinical contexts, yet no one has specifically validated a teleswallow evaluation for in-hospital post-stroke dysphagia assessment. A team of 6 SLPs experienced in stroke care and a telestroke neurologist designed, implemented, and tested a teleswallow evaluation for acute stroke patients, in which 100 patients across 2 affiliated, urban certified stroke centers were sequentially evaluated by a bedside and telehealth SLP. Inter-rater reliability was analyzed using percent agreement, Cohen's kappa, Kendall's tau-b, and Wilcoxon matched-pairs signed rank tests. Logistic regression models accounting for age and gender were used to test the impact of stroke severity and stroke location on agreement. We found excellent agreement for both liquid (91% agreement; kappa = 0.808; Kendall's tau-b = 0.813, p < 0.001; Wilcoxon signed rank = -0.818, p = 0.417) and solid (87% agreement; kappa = 0.792; Kendall's tau-b = 0.844, p < 0.001; Wilcoxon signed rank = 0.243, p = 0.808) dietary textures. From regression modeling, there is suggestive but inconclusive evidence that higher National Institute of Health Stroke Scale (NIHSS) scores correlate with lower levels of agreement for liquid diet recommendations (OR [95% CI] 0.895 [0.793-1.01]; p = 0.07). There was no impact of NIHSS score for solid diet recommendations and no impact of stroke location on solid or liquid diet recommendations. Qualitatively, we identified professional, logistical, technical, and patient barriers to implementation, many of which resolved with experience over time. Dysphagia evaluation by a remote SLP via telehealth is safe and effective following stroke. We plan to implement

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

PubMed Central

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

2018-01-01

Background Odontogenic myxoma (OM) is a benign intraosseous neoplasm that exhibits local aggressiveness and high recurrence rates. Osteoclastogenesis is an important phenomenon in the tumor growth of maxillary neoplasms. RANK (Receptor Activator of Nuclear Factor κappa B) is the signaling receptor of RANK-L (Receptor activator of nuclear factor kappa-Β ligand) that activates the osteoclasts. OPG (osteoprotegerin) is a decoy receptor for RANK-L that inhibits pro-osteoclastogenesis. The RANK / RANKL / OPG system participates in the regulation of osteolytic activity under normal conditions, and its alteration has been associated with greater bone destruction, and also with tumor growth. Objectives To analyze the immunohistochemical expression of OPG, RANK and RANK-L proteins in odontogenic myxomas (OMs) and their relationship with the tumor size. Material and Methods Eighteen OMs, 4 small (<3 cm) and 14 large (> 3cm) and 18 dental follicles (DF) that were included as control were studied by means of standard immunohistochemical procedure with RANK, RANKL and OPG antibodies. For the evaluation, 5 fields (40x) of representative areas of OM and DF were selected where the expression of each antibody was determined. Descriptive and comparative statistical analyses were performed with the obtained data. Results There are significant differences in the expression of RANK in OM samples as compared to DF (p = 0.022) and among the OMSs and OMLs (p = 0.032). Also a strong association is recognized in the expression of RANK-L and OPG in OM samples. Conclusions Activation of the RANK / RANK-L / OPG triad seems to be involved in the mechanisms of bone balance and destruction, as well as associated with tumor growth in odontogenic myxomas. Key words:Odontogenic myxoma, dental follicle, RANK, RANK-L, OPG, osteoclastogenesis. PMID:29680857

Kriging for Simulation Metamodeling: Experimental Design, Reduced Rank Kriging, and Omni-Rank Kriging

NASA Astrophysics Data System (ADS)

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

Time evolution of Wikipedia network ranking

NASA Astrophysics Data System (ADS)

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.

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.

PubMed

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 (TCD 50 ) =36.5 Gy and γ 50 =0.72] and curative intent (TCD 50 =51.24 Gy and γ 50 =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

Multiple graph regularized protein domain ranking.

PubMed

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

2012-11-19

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

Course fees and academic ranking: insights from the IMI EMTRAIN on-course® database.

PubMed

Payton, Antony; Dallakian, Pavel; Fitton, Alexander; Payton, Anna; Hardman, Mike; Yuille, Martin

2014-07-01

The Innovative Medicines Initiative (IMI) funded project on-course® (http://www.on-course.eu/) lists postgraduate biomedical courses in Europe and is comprehensive for all taught and research master's courses. Using on-course®, new insights into education and training in Europe can be delivered; and here we investigate the relationship between master's course fees and university ranking. We hypothesise that higher master's course fees would be associated with higher university ranking. This was indeed the case for research master's courses and for taught master's courses for non-EU students. However, we observed no correlation between taught master's course fees for EU students and university ranking, meaning EU students are paying on average as much for courses at lower ranked universities as they are for courses at higher ranked universities. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Rank 4 Premodular Categories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruillard, Paul J.; Galindo, Cesar; Ng, Siu Hung

2016-09-01

We consider the classification problem for rank 4 premodular categories. We uncover a formula for the 2nd Frobenius-Schur indicator of a premodular category is determined and the classification of rank 4 premodular categories (up to Grothendieck equivalence) is completed. In the appendix we show rank finiteness for premodular categories.

Multiplex PageRank.

PubMed

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.

Pitch ranking, electrode discrimination, and physiological spread-of-excitation using Cochlear's dual-electrode mode

PubMed Central

Goehring, Jenny L.; Neff, Donna L.; Baudhuin, Jacquelyn L.; Hughes, Michelle L.

2014-01-01

This study compared pitch ranking, electrode discrimination, and electrically evoked compound action potential (ECAP) spatial excitation patterns for adjacent physical electrodes (PEs) and the corresponding dual electrodes (DEs) for newer-generation Cochlear devices (Cochlear Ltd., Macquarie, New South Wales, Australia). The first goal was to determine whether pitch ranking and electrode discrimination yield similar outcomes for PEs and DEs. The second goal was to determine if the amount of spatial separation among ECAP excitation patterns (separation index, Σ) between adjacent PEs and the PE-DE pairs can predict performance on the psychophysical tasks. Using non-adaptive procedures, 13 subjects completed pitch ranking and electrode discrimination for adjacent PEs and the corresponding PE-DE pairs (DE versus each flanking PE) from the basal, middle, and apical electrode regions. Analysis of d′ scores indicated that pitch-ranking and electrode-discrimination scores were not significantly different, but rather produced similar levels of performance. As expected, accuracy was significantly better for the PE-PE comparison than either PE-DE comparison. Correlations of the psychophysical versus ECAP Σ measures were positive; however, not all test/region correlations were significant across the array. Thus, the ECAP separation index is not sensitive enough to predict performance on behavioral tasks of pitch ranking or electrode discrimination for adjacent PEs or corresponding DEs. PMID:25096106

The Effectiveness of Building Permit Regulation for Green Open Space at Housing Estates: Case Study of Kendal Regency, Central Java, Indonesia

NASA Astrophysics Data System (ADS)

Yulianti, Wiwik; Hadi, Sudharto P.

2018-02-01

Increasing demand for settlements steamed by population growth declines the quality of the environment specifically at urban area. The existing spatial planning could not able to prevent the change of land use for settlement and other infrastructures. The Act no. 26 of 2007 on spatial planning stipulates that green open space must reach 30% of the total area, consisting of 20% public open space and 10% private open space. The existing condition of urban area at Kendal Regency reach 245,6 million m2 with 88.145,5 m2 green open space or 0,036% out of total area. An effort to increase green open space in urban areas taken by the Government of Kendal Regency is by promulgating a local regulation stipulating that each housing developer request a building permit is obliged to provide a green open space at least 10 percent of the total housing area. This paper reviews the effectiveness of building permit regulation, the problems encountered and the concept proposed to make the local regulation work. The area of sample taken is three urban districts out of five urban districts, the resource persons chosen are those from relevant offices (Dinas) involved at the implementation of the local regulation. The data collection techniques employed are the Analytical Hierarchy Process (AHP), Geographic Information System (GIS) technology, social observation and informal interview. The data gathered will be analyzed quantitatively and qualitatively.

The choice of statistical methods for comparisons of dosimetric data in radiotherapy.

PubMed

Chaikh, Abdulhamid; Giraud, Jean-Yves; Perrin, Emmanuel; Bresciani, Jean-Pierre; Balosso, Jacques

2014-09-18

Novel irradiation techniques are continuously introduced in radiotherapy to optimize the accuracy, the security and the clinical outcome of treatments. These changes could raise the question of discontinuity in dosimetric presentation and the subsequent need for practice adjustments in case of significant modifications. This study proposes a comprehensive approach to compare different techniques and tests whether their respective dose calculation algorithms give rise to statistically significant differences in the treatment doses for the patient. Statistical investigation principles are presented in the framework of a clinical example based on 62 fields of radiotherapy for lung cancer. The delivered doses in monitor units were calculated using three different dose calculation methods: the reference method accounts the dose without tissues density corrections using Pencil Beam Convolution (PBC) algorithm, whereas new methods calculate the dose with tissues density correction for 1D and 3D using Modified Batho (MB) method and Equivalent Tissue air ratio (ETAR) method, respectively. The normality of the data and the homogeneity of variance between groups were tested using Shapiro-Wilks and Levene test, respectively, then non-parametric statistical tests were performed. Specifically, the dose means estimated by the different calculation methods were compared using Friedman's test and Wilcoxon signed-rank test. In addition, the correlation between the doses calculated by the three methods was assessed using Spearman's rank and Kendall's rank tests. The Friedman's test showed a significant effect on the calculation method for the delivered dose of lung cancer patients (p <0.001). The density correction methods yielded to lower doses as compared to PBC by on average (-5 ± 4.4 SD) for MB and (-4.7 ± 5 SD) for ETAR. Post-hoc Wilcoxon signed-rank test of paired comparisons indicated that the delivered dose was significantly reduced using density-corrected methods

Large-scale linear rankSVM.

PubMed

Lee, Ching-Pei; Lin, Chih-Jen

2014-04-01

Linear rankSVM is one of the widely used methods for learning to rank. Although its performance may be inferior to nonlinear methods such as kernel rankSVM and gradient boosting decision trees, linear rankSVM is useful to quickly produce a baseline model. Furthermore, following its recent development for classification, linear rankSVM may give competitive performance for large and sparse data. A great deal of works have studied linear rankSVM. The focus is on the computational efficiency when the number of preference pairs is large. In this letter, we systematically study existing works, discuss their advantages and disadvantages, and propose an efficient algorithm. We discuss different implementation issues and extensions with detailed experiments. Finally, we develop a robust linear rankSVM tool for public use.

Multiple graph regularized protein domain ranking

PubMed Central

2012-01-01

Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. PMID:23157331

Neophilia Ranking of Scientific Journals.

PubMed

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.

Neophilia Ranking of Scientific Journals

PubMed Central

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

What's wrong with hazard-ranking systems? An expository note.

PubMed

Cox, Louis Anthony Tony

2009-07-01

Two commonly recommended principles for allocating risk management resources to remediate uncertain hazards are: (1) select a subset to maximize risk-reduction benefits (e.g., maximize the von Neumann-Morgenstern expected utility of the selected risk-reducing activities), and (2) assign priorities to risk-reducing opportunities and then select activities from the top of the priority list down until no more can be afforded. When different activities create uncertain but correlated risk reductions, as is often the case in practice, then these principles are inconsistent: priority scoring and ranking fails to maximize risk-reduction benefits. Real-world risk priority scoring systems used in homeland security and terrorism risk assessment, environmental risk management, information system vulnerability rating, business risk matrices, and many other important applications do not exploit correlations among risk-reducing opportunities or optimally diversify risk-reducing investments. As a result, they generally make suboptimal risk management recommendations. Applying portfolio optimization methods instead of risk prioritization ranking, rating, or scoring methods can achieve greater risk-reduction value for resources spent.

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

PubMed

Bigbee, Jeri L

2008-01-01

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

Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment.

PubMed

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

Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment

PubMed Central

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

Rank restriction for the variational calculation of two-electron reduced density matrices of many-electron atoms and molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Naftchi-Ardebili, Kasra; Hau, Nathania W.; Mazziotti, David A.

2011-11-15

Variational minimization of the ground-state energy as a function of the two-electron reduced density matrix (2-RDM), constrained by necessary N-representability conditions, provides a polynomial-scaling approach to studying strongly correlated molecules without computing the many-electron wave function. Here we introduce a route to enhancing necessary conditions for N representability through rank restriction of the 2-RDM. Rather than adding computationally more expensive N-representability conditions, we directly enhance the accuracy of two-particle (2-positivity) conditions through rank restriction, which removes degrees of freedom in the 2-RDM that are not sufficiently constrained. We select the rank of the particle-hole 2-RDM by deriving the ranks associatedmore » with model wave functions, including both mean-field and antisymmetrized geminal power (AGP) wave functions. Because the 2-positivity conditions are exact for quantum systems with AGP ground states, the rank of the particle-hole 2-RDM from the AGP ansatz provides a minimum for its value in variational 2-RDM calculations of general quantum systems. To implement the rank-restricted conditions, we extend a first-order algorithm for large-scale semidefinite programming. The rank-restricted conditions significantly improve the accuracy of the energies; for example, the percentages of correlation energies recovered for HF, CO, and N{sub 2} improve from 115.2%, 121.7%, and 121.5% without rank restriction to 97.8%, 101.1%, and 100.0% with rank restriction. Similar results are found at both equilibrium and nonequilibrium geometries. While more accurate, the rank-restricted N-representability conditions are less expensive computationally than the full-rank conditions.« less

Ultrasonic ranking of toughness of tungsten carbide

NASA Technical Reports Server (NTRS)

Vary, A.; Hull, D. R.

1983-01-01

The feasibility of using ultrasonic attenuation measurements to rank tungsten carbide alloys according to their fracture toughness was demonstrated. Six samples of cobalt-cemented tungsten carbide (WC-Co) were examined. These varied in cobalt content from approximately 2 to 16 weight percent. The toughness generally increased with increasing cobalt content. Toughness was first determined by the Palmqvist and short rod fracture toughness tests. Subsequently, ultrasonic attenuation measurements were correlated with both these mechanical test methods. It is shown that there is a strong increase in ultrasonic attenuation corresponding to increased toughness of the WC-Co alloys. A correlation between attenuation and toughness exists for a wide range of ultrasonic frequencies. However, the best correlation for the WC-Co alloys occurs when the attenuation coefficient measured in the vicinity of 100 megahertz is compared with toughness as determined by the Palmqvist technique.

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

PubMed Central

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

2017-01-01

Lung cancer is the leading cause of cancer deaths. Besides smoking, epidemiological studies have linked female sex hormones to lung cancer in women; however, the underlying mechanisms remain unclear. Here we report that the receptor activator of nuclear factor-kB (RANK), the key regulator of osteoclastogenesis, is frequently expressed in primary lung tumors, an active RANK pathway correlates with decreased survival, and pharmacologic RANK inhibition reduces tumor growth in patient-derived lung cancer xenografts. Clonal genetic inactivation of KRasG12D in mouse lung epithelial cells markedly impairs the progression of KRasG12D-driven lung cancer, resulting in a significant survival advantage. Mechanistically, RANK rewires energy homeostasis in human and murine lung cancer cells and promotes expansion of lung cancer stem-like cells, which is blocked by inhibiting mitochondrial respiration. Our data also indicate survival differences in KRasG12D-driven lung cancer between male and female mice, and we show that female sex hormones can promote lung cancer progression via the RANK pathway. These data uncover a direct role for RANK in lung cancer and may explain why female sex hormones accelerate lung cancer development. Inhibition of RANK using the approved drug denosumab may be a therapeutic drug candidate for primary lung cancer. PMID:29118048

Wikipedia ranking of world universities

NASA Astrophysics Data System (ADS)

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.

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

PubMed Central

Xue, Li C.; Jordan, Rafael A.; EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2015-01-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. Dock-Rank uses interface residues predicted by partner-specific sequence homology-based protein–protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. PMID:23873600

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

PubMed

Xue, Li C; Jordan, Rafael A; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-02-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. Copyright © 2013 Wiley Periodicals, Inc.

Does resident ranking during recruitment accurately predict subsequent performance as a surgical resident?

PubMed

Fryer, Jonathan P; Corcoran, Noreen; George, Brian; Wang, Ed; Darosa, Debra

2012-01-01

While the primary goal of ranking applicants for surgical residency training positions is to identify the candidates who will subsequently perform best as surgical residents, the effectiveness of the ranking process has not been adequately studied. We evaluated our general surgery resident recruitment process between 2001 and 2011 inclusive, to determine if our recruitment ranking parameters effectively predicted subsequent resident performance. We identified 3 candidate ranking parameters (United States Medical Licensing Examination [USMLE] Step 1 score, unadjusted ranking score [URS], and final adjusted ranking [FAR]), and 4 resident performance parameters (American Board of Surgery In-Training Examination [ABSITE] score, PGY1 resident evaluation grade [REG], overall REG, and independent faculty rating ranking [IFRR]), and assessed whether the former were predictive of the latter. Analyses utilized Spearman correlation coefficient. We found that the URS, which is based on objective and criterion based parameters, was a better predictor of subsequent performance than the FAR, which is a modification of the URS based on subsequent determinations of the resident selection committee. USMLE score was a reliable predictor of ABSITE scores only. However, when we compared our worst residence performances with the performances of the other residents in this evaluation, the data did not produce convincing evidence that poor resident performances could be reliably predicted by any of the recruitment ranking parameters. Finally, stratifying candidates based on their rank range did not effectively define a ranking cut-off beyond which resident performance would drop off. Based on these findings, we recommend surgery programs may be better served by utilizing a more structured resident ranking process and that subsequent adjustments to the rank list generated by this process should be undertaken with caution. Copyright © 2012 Association of Program Directors in Surgery

Removing Size as a Determinant of Quality: A Per Capita Approach to Ranking Doctoral Programs in Finance

ERIC Educational Resources Information Center

White, Roger McNeill; White, John Bryan; Barth, Michael M.

2011-01-01

Rankings of finance doctoral programs generally fall into two categories: a qualitative opinion survey or a quantitative analysis of research productivity. The consistency of these rankings suggests either the best programs have the most productive faculty, or that the university affiliations most often seen in publications are correlated with…

A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

PubMed

Nakarmi, Ukash; Wang, Yanhua; Lyu, Jingyuan; Liang, Dong; Ying, Leslie

2017-11-01

While many low rank and sparsity-based approaches have been developed for accelerated dynamic magnetic resonance imaging (dMRI), they all use low rankness or sparsity in input space, overlooking the intrinsic nonlinear correlation in most dMRI data. In this paper, we propose a kernel-based framework to allow nonlinear manifold models in reconstruction from sub-Nyquist data. Within this framework, many existing algorithms can be extended to kernel framework with nonlinear models. In particular, we have developed a novel algorithm with a kernel-based low-rank model generalizing the conventional low rank formulation. The algorithm consists of manifold learning using kernel, low rank enforcement in feature space, and preimaging with data consistency. Extensive simulation and experiment results show that the proposed method surpasses the conventional low-rank-modeled approaches for dMRI.

The Impact of Oral Hygiene Maintenance on the Association Between Periodontitis and Osteoporosis

PubMed Central

Huang, Yi-Fang; Chang, Chung-Ta; Liu, Shih-Ping; Muo, Chih-Hsin; Tsai, Chun-Hao; Hong, Hsiang-Hsi; Shen, Yu-Fu; Wu, Ching-Zong

2016-01-01

Abstract Both periodontitis and osteoporosis have similar sign of bone resorption in nature. However, the relationship of the severity between these 2 bone-loss diseases is still uncertain. The aim of this study was to investigate the association between the severity of osteoporosis and periodontitis regarding the impact of oral hygiene maintenance. In total, 35,127 osteoporosis patients and 50,498 comparisons were derived from the Longitudinal Health Insurance Database of Taiwan between 2000 and 2010. The population was subdivided into groups according to the different level oral hygiene maintenance and the severity of periodontitis and osteoporosis. The association between osteoporosis and periodontitis was estimated by multinomial logistic regression and rank correlation by Kendall rank correlation test, presented by odds ratio (OR), and 5% confidence intervals (CIs). After controlling the age, sex, and comorbidities, variables in the good oral hygiene maintenance population, we found that periodontitis raised 1.29-fold risk of osteoporosis (95% CI = 1.12–1.49); the risk of osteoporosis was increased with the elevated severity of periodontitis from 1.27 (95% CI = 1.08–1.48) to 1.38 (95% CI = 1.01–1.89). There is a positive correlation between the severity of periodontitis and osteoporosis occurrence in this population (OR = 1.27–1.46; Kendall rank correlation test P = 0.0003). In the poor oral hygiene maintenance population, periodontitis patients had 6.02-fold risk of osteoporosis than those who without periodontitis (95% CI = 4.65–7.81); the risk of osteoporosis was increased with periodontitis severity from 5.96 (95% CI = 4.48–7.92) to 6.37 (95% CI = 3.36–12.1). This result indicated the periodontitis and osteoporosis are conjunctive. The sudden periodontal breakdown of those who with good oral hygiene maintenance might be an indicator for the risk of osteoporosis; if those who were diagnosed as osteoporosis must pay

Memory Efficient Ranking.

ERIC Educational Resources Information Center

Moffat, Alistair; And Others

1994-01-01

Describes an approximate document ranking process that uses a compact array of in-memory, low-precision approximations for document length. Combined with another rule for reducing the memory required by partial similarity accumulators, the approximation heuristic allows the ranking of large document collections using less than one byte of memory…

Optimal affinity ranking for automated virtual screening validated in prospective D3R grand challenges

NASA Astrophysics Data System (ADS)

Wingert, Bentley M.; Oerlemans, Rick; Camacho, Carlos J.

2018-01-01

The goal of virtual screening is to generate a substantially reduced and enriched subset of compounds from a large virtual chemistry space. Critical in these efforts are methods to properly rank the binding affinity of compounds. Prospective evaluations of ranking strategies in the D3R grand challenges show that for targets with deep pockets the best correlations (Spearman ρ 0.5) were obtained by our submissions that docked compounds to the holo-receptors with the most chemically similar ligand. On the other hand, for targets with open pockets using multiple receptor structures is not a good strategy. Instead, docking to a single optimal receptor led to the best correlations (Spearman ρ 0.5), and overall performs better than any other method. Yet, choosing a suboptimal receptor for crossdocking can significantly undermine the affinity rankings. Our submissions that evaluated the free energy of congeneric compounds were also among the best in the community experiment. Error bars of around 1 kcal/mol are still too large to significantly improve the overall rankings. Collectively, our top of the line predictions show that automated virtual screening with rigid receptors perform better than flexible docking and other more complex methods.

24 CFR 599.401 - Ranking of applications.

Code of Federal Regulations, 2010 CFR

2010-04-01

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

An Automated Approach for Ranking Journals to Help in Clinician Decision Support

PubMed Central

Jonnalagadda, Siddhartha R.; Moosavinasab, Soheil; Nath, Chinmoy; Li, Dingcheng; Chute, Christopher G.; Liu, Hongfang

2014-01-01

Point of care access to knowledge from full text journal articles supports decision-making and decreases medical errors. However, it is an overwhelming task to search through full text journal articles and find quality information needed by clinicians. We developed a method to rate journals for a given clinical topic, Congestive Heart Failure (CHF). Our method enables filtering of journals and ranking of journal articles based on source journal in relation to CHF. We also obtained a journal priority score, which automatically rates any journal based on its importance to CHF. Comparing our ranking with data gathered by surveying 169 cardiologists, who publish on CHF, our best Multiple Linear Regression model showed a correlation of 0.880, based on five-fold cross validation. Our ranking system can be extended to other clinical topics. PMID:25954382

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

PubMed

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

2017-10-15

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

University Rankings: The Web Ranking

ERIC Educational Resources Information Center

Aguillo, Isidro F.

2012-01-01

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

Sex Differences in Academic Rank and Publication Rate at Top-Ranked US Neurology Programs.

PubMed

McDermott, Mollie; Gelb, Douglas J; Wilson, Kelsey; Pawloski, Megan; Burke, James F; Shelgikar, Anita V; London, Zachary N

2018-04-02

Women are underrepresented in academic neurology, and the reasons for the underrepresentation are unclear. To explore potential sex differences in top-ranked academic neurology programs by comparing the number of men and women at each academic faculty rank and how many articles each group has published. Twenty-nine top-ranked neurology programs were identified by combining the top 20 programs listed on either the 2016 or 2017 Doximity Residency Navigator tool with the top 20 programs listed in the US News and World Report ranking of Best Graduate Schools. An internet search of the departmental websites was performed between December 1, 2015, and April 30, 2016. For each faculty member on a program site, the following biographical information was obtained: first name, last name, academic institution, sex, academic faculty rank, educational leadership (clerkship, fellowship, or residency director/assistant director), and year of medical school graduation. To compare the distribution of men vs women and the number of publications for men vs women at each academic faculty rank. Secondary analyses included Scopus h-index, book authorship, educational leadership (clerkship, residency, or fellowship director/assistant director), and clinical activity as inferred through Medicare claims data in men vs women after controlling for years since medical school graduation. Of 1712 academic neurologists in our sample, 528 (30.8%) were women and 1184 (69.2%) were men (P < .001). Men outnumbered women at all academic faculty ranks, and the difference increased with advancing rank (instructor/lecturer, 59.4% vs 40.5%; assistant professor, 56.7% vs 43.3%; associate professor, 69.8% vs 30.2%; and professor, 86.2% vs 13.8%). After controlling for clustering and years since medical school graduation, men were twice as likely as women to be full professors (odds ratio [OR], 2.06; 95% CI, 1.40-3.01), whereas men and women had the same odds of being associate professors (OR, 1.04; 95

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

PubMed

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

2017-12-01

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

Ranking Specific Sets of Objects.

PubMed

Maly, Jan; Woltran, Stefan

2017-01-01

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

Ranking Support Vector Machine with Kernel Approximation

PubMed Central

Dou, Yong

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. PMID:28293256

Ranking Support Vector Machine with Kernel Approximation.

PubMed

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.

University Rankings and Social Science

ERIC Educational Resources Information Center

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…

Two-dimensional ranking of Wikipedia articles

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

PubMed

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

2017-09-01

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

Educational Background and Academic Rank of Faculty Members within US Schools of Pharmacy.

PubMed

Assemi, Mitra; Hudmon, Karen Suchanek; Sowinski, Kevin M; Corelli, Robin L

2016-05-25

Objective. To characterize the educational background and academic rank of faculty members in US schools of pharmacy, estimate the extent to which they are employed by institutions where they received previous training, and determine whether differences in degree origin and rank exist between faculty members in established (≤1995) vs newer programs. Methods. A cross-sectional study was conducted using the American Association of Colleges of Pharmacy (AACP) faculty database and demographic information from the public domain. Results. Among 5516 faculty members, 50.3% held two or more types of degrees. Established schools had a higher median number of faculty members and a higher mean faculty rank than did newer schools. Conclusion. The difference in mean faculty rank highlights the shortage of experienced faculty members in newer schools. Future research efforts should investigate educational attainment in correlation to other faculty and school characteristics and prospectively track and report trends related to pharmacy faculty members composition.

I did eat my vegetables. Agreement between parent and child food intake diaries.

PubMed

Rangelov, Natalie; Suggs, L Suzanne; Marques-Vidal, Pedro

2016-12-01

To assess the level of agreement between children and their parents when reporting a child's food consumption. Cross-sectional study in which children and parents independently completed 7 d food diaries describing the foods and drinks the child consumed at every meal and snack. The association between child and parent reporting was assessed for nineteen food groups using Kendall's tau-b non-parametric correlations, Spearman's rank correlations, kappa coefficients and Lin's concordance measure of agreement. Results were also stratified by gender of the child and his/her grade at school. Households in Ticino, Switzerland, April-June 2014. Two hundred and ninety-nine children aged 6-12 years and one of their parents participated, with 264 providing complete data (35 % completion rate). Results showed a high level of agreement between child and parent reporting. Spearman correlations ranged from 0·55 (sauces) and 0·57 (fatty meat) to 0·80 (fruit), 0·83 (starchy foods) and 0·84 (pastries). All nineteen Spearman correlations were significant at the 0·001 level. Kendall's tau-b correlations ranged from 0·44 (fat meat) to 0·81 (puff pastry). Kappa values showed low to high levels of agreement, ranging from 0·15 (sweets) to 0·77 (puff pastry). Lin's concordance correlation coefficients ranged from 0·39 (whole grains) to 0·86 (puff pastry). When assessing the eating behaviour of children using a 7 d food diary, children's reports might be as reliable as their parents'.

Systematic Differences in Signal Emitting and Receiving Revealed by PageRank Analysis of a Human Protein Interactome

PubMed Central

Li, Xiu-Qing

2012-01-01

Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell. PMID:23028653

Ranking Community Health Status to Stimulate Discussion of Local Public Health Issues: The Wisconsin County Health Rankings

PubMed Central

Peppard, Paul E.; Kindig, David A.; Dranger, Elizabeth; Jovaag, Amanda; Remington, Patrick L.

2008-01-01

United Health Foundation’s America’s Health Rankings, which ranks the states from “least healthy” to “healthiest,” receives wide press coverage and promotes discussion of public health issues. The University of Wisconsin Population Health Institute used the United Health Foundation’s model to develop the Wisconsin County Health Rankings (“Health Rankings”) from existing county-level data. The institute first released the rankings in 2004. A survey of the Wisconsin county health officers indicated that they intend to use the rankings for needs assessment, program planning, and discussion with county health boards. The institute implemented many of the health officers’ suggestions for improvement of the rankings in subsequent editions. The methods employed to create the rankings should be applicable in other states. PMID:18172156

Recurrent fuzzy ranking methods

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2016-02-02

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

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

PubMed

Brown, Ted; Gutman, Sharon A

2018-05-18

Journals are currently assessed and ranked using a number of different quantitative performance metrics. To compare and correlate the publication metrics of English-language occupational therapy journals published in 2015. Bibliometric data was sourced for 14 English-language occupational therapy journals including the Journal Citations Report (JCR) 2-year impact factor (IF), Eigenfactor Score (EFS), Article Influence Score (AIS), Scopus Source Normalized Impact per Paper (SNIP), Scopus Citescore, and SCImago Journal Rank (SJR) score. The JCR, Scopus, and SJR 2015 bibliometric data were correlated. The top six English-language occupational therapy journals in relation to JCR IF, EFS, AIS, SNIP, Citescore, SJR score, and SJR IIF were AJOT, AOTJ, POPT, CJOT, SJOT, and BJOT. JCR IF, EFS, JCR AIS, SNIP, Citescore, SJR score and SJR IIF were all significantly correlated with coefficients ranging from 0.751 to 0.961 (p < 0.05; p < 0.01). The calculated SJR IIF was on average 0.335 larger than the JCR IFs reported. The findings indicate that the range of available bibliometric measures should be used collectively to yield a more comprehensive assessment of journal and article rankings rather than the singular use of IF scores that currently and frequently occurs in many jurisdictions.

RRCRank: a fusion method using rank strategy for residue-residue contact prediction.

PubMed

Jing, Xiaoyang; Dong, Qiwen; Lu, Ruqian

2017-09-02

In structural biology area, protein residue-residue contacts play a crucial role in protein structure prediction. Some researchers have found that the predicted residue-residue contacts could effectively constrain the conformational search space, which is significant for de novo protein structure prediction. In the last few decades, related researchers have developed various methods to predict residue-residue contacts, especially, significant performance has been achieved by using fusion methods in recent years. In this work, a novel fusion method based on rank strategy has been proposed to predict contacts. Unlike the traditional regression or classification strategies, the contact prediction task is regarded as a ranking task. First, two kinds of features are extracted from correlated mutations methods and ensemble machine-learning classifiers, and then the proposed method uses the learning-to-rank algorithm to predict contact probability of each residue pair. First, we perform two benchmark tests for the proposed fusion method (RRCRank) on CASP11 dataset and CASP12 dataset respectively. The test results show that the RRCRank method outperforms other well-developed methods, especially for medium and short range contacts. Second, in order to verify the superiority of ranking strategy, we predict contacts by using the traditional regression and classification strategies based on the same features as ranking strategy. Compared with these two traditional strategies, the proposed ranking strategy shows better performance for three contact types, in particular for long range contacts. Third, the proposed RRCRank has been compared with several state-of-the-art methods in CASP11 and CASP12. The results show that the RRCRank could achieve comparable prediction precisions and is better than three methods in most assessment metrics. The learning-to-rank algorithm is introduced to develop a novel rank-based method for the residue-residue contact prediction of proteins, which

Characteristics of fundamental combustion and NOx emission using various rank coals.

PubMed

Kim, Sung Su; Kang, Youn Suk; Lee, Hyun Dong; Kim, Jae-Kwan; Hong, Sung Chang

2011-03-01

Eight types of coals of different rank were selected and their fundamental combustion characteristics were examined along with the conversion of volatile nitrogen (N) to nitrogen oxides (NOx)/fuel N to NOx. The activation energy, onset temperature, and burnout temperature were obtained from the differential thermogravimetry curve and Arrhenius plot, which were derived through thermo-gravimetric analysis. In addition, to derive the combustion of volatile N to NOx/fuel N to NOx, the coal sample, which was pretreated at various temperatures, was burned, and the results were compared with previously derived fundamental combustion characteristics. The authors' experimental results confirmed that coal rank was highly correlated with the combustion of volatile N to NOx/fuel N to NOx.

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

PubMed

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

2017-06-15

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

Assessing validity of a short food frequency questionnaire on present dietary intake of elderly Icelanders

PubMed Central

2012-01-01

Background Few studies exist on the validity of food frequency questionnaires (FFQs) administered to elderly people. The aim of this study was to assess the validity of a short FFQ on present dietary intake, developed specially for the AGES-Reykjavik Study, which includes 5,764 elderly individuals. Assessing the validity of FFQs is essential before they are used in studies on diet-related disease risk and health outcomes. Method 128 healthy elderly participants (74 y ± 5.7; 58.6% female) answered the AGES-FFQ, and subsequently filled out a 3-day weighed food record. Validity of the AGES-FFQ was assessed by comparing its answers to the dietary data obtained from the weighed food records, using Spearman's rank correlation, Chi-Square/Kendall's tau, and a Jonckheere-Terpstra test for trend. Result For men a correlation ≥ 0.4 was found for potatoes, fresh fruits, oatmeal/muesli, cakes/cookies, candy, dairy products, milk, pure fruit juice, cod liver oil, coffee, tea and sugar in coffee/tea (r = 0.40-0.71). A lower, but acceptable, correlation was also found for raw vegetables (r = 0.33). The highest correlation for women was found for consumption of rye bread, oatmeal/muesli, raw vegetables, candy, dairy products, milk, pure fruit juice, cod liver oil, coffee and tea (r = 0.40-0.61). An acceptable correlation was also found for fish topping/salad, fresh fruit, blood/liver sausage, whole-wheat bread, and sugar in coffee/tea (r = 0.28-0.37). Questions on meat/fish meals, cooked vegetables and soft drinks did not show a significant correlation to the reference method. Pearson Chi-Square and Kendall's tau showed similar results, as did the Jonckheere-Terpstra trend test. Conclusion A majority of the questions in the AGES-FFQ had an acceptable correlation and may be used to rank individuals according to their level of intake of several important foods/food groups. The AGES-FFQ on present diet may therefore be used to study the relationship between consumption of several

Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

PubMed

Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

2017-09-12

In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

Multicriteria decision analysis in ranking of analytical procedures for aldrin determination in water.

PubMed

Tobiszewski, Marek; Orłowski, Aleksander

2015-03-27

The study presents the possibility of multi-criteria decision analysis (MCDA) application when choosing analytical procedures with low environmental impact. A type of MCDA, Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), was chosen as versatile tool that meets all the analytical chemists--decision makers requirements. Twenty five analytical procedures for aldrin determination in water samples (as an example) were selected as input alternatives to MCDA analysis. Nine different criteria describing the alternatives were chosen from different groups--metrological, economical and the most importantly--environmental impact. The weights for each criterion were obtained from questionnaires that were sent to experts, giving three different scenarios for MCDA results. The results of analysis show that PROMETHEE is very promising tool to choose the analytical procedure with respect to its greenness. The rankings for all three scenarios placed solid phase microextraction and liquid phase microextraction--based procedures high, while liquid-liquid extraction, solid phase extraction and stir bar sorptive extraction--based procedures were placed low in the ranking. The results show that although some of the experts do not intentionally choose green analytical chemistry procedures, their MCDA choice is in accordance with green chemistry principles. The PROMETHEE ranking results were compared with more widely accepted green analytical chemistry tools--NEMI and Eco-Scale. As PROMETHEE involved more different factors than NEMI, the assessment results were only weakly correlated. Oppositely, the results of Eco-Scale assessment were well-correlated as both methodologies involved similar criteria of assessment. Copyright © 2015 Elsevier B.V. All rights reserved.

The structure of first-ranked cluster galaxies and the radius-magnitude relation

NASA Astrophysics Data System (ADS)

Lugger, P. M.

1984-11-01

To investigate theoretical predictions for the dynamical evolution of first-ranked galaxies, a quantitative study of their properties, as a function of cluster morphology, has been carried out using photographic plates obtained with the Palomar 48 inch (1.2 m) Schmidt telescope. Surface brightness profiles to radii of several hundred kpc for 35 first-ranked cluster galaxies have been analyzed. The dispersion in the metric magnitudes of first-ranked galaxies is quite small (about 0.4 mag), which is consistent with the results of Kristian, Sandage, and Westphal (1978) as well as those of Hoessel, Gunn, and Thuan (1980) and the recent work of Schneider, Gunn, and Hoessel (1983). For the cD (supergiant elliptical) galaxy sample, the mean metric magnitude is about 0.5 mag brighter than for the non-cD galaxies. The mean de Vaucouleurs effective radius for the cD galaxy sample is 80 percent larger than that of the non-cD sample. The relation between de Vaucouleurs effective radius and magnitude determined in the present study for first-ranked galaxies, log r(e) equal to about -0.26 M + constant is consistent with the relations found for fainter galaxies by Strom and Strom (1978) as well as Wirth (1982). The residuals in radius from the mean radius-magnitude relation for first-ranked galaxies do not correlate with the Bautz-Morgan (1970) type of the cluster.

Fracturing ranked surfaces

NASA Astrophysics Data System (ADS)

Schrenk, K. J.; Araújo, N. A. M.; Andrade, J. S., Jr.; Herrmann, H. J.

2012-04-01

Discretized landscapes can be mapped onto ranked surfaces, where every element (site or bond) has a unique rank associated with its corresponding relative height. By sequentially allocating these elements according to their ranks and systematically preventing the occupation of bridges, namely elements that, if occupied, would provide global connectivity, we disclose that bridges hide a new tricritical point at an occupation fraction p = pc, where pc is the percolation threshold of random percolation. For any value of p in the interval pc < p <= 1, our results show that the set of bridges has a fractal dimension dBB ~ 1.22 in two dimensions. In the limit p --> 1, a self-similar fracture is revealed as a singly connected line that divides the system in two domains. We then unveil how several seemingly unrelated physical models tumble into the same universality class and also present results for higher dimensions.

Adsorption isotherms and kinetics of activated carbons produced from coals of different ranks.

PubMed

Purevsuren, B; Lin, Chin-Jung; Davaajav, Y; Ariunaa, A; Batbileg, S; Avid, B; Jargalmaa, S; Huang, Yu; Liou, Sofia Ya-Hsuan

2015-01-01

Activated carbons (ACs) from six coals, ranging from low-rank lignite brown coal to high-rank stone coal, were utilized as adsorbents to remove basic methylene blue (MB) from an aqueous solution. The surface properties of the obtained ACs were characterized via thermal analysis, N2 isothermal sorption, scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and Boehm titration. As coal rank decreased, an increase in the heterogeneity of the pore structures and abundance of oxygen-containing functional groups increased MB coverage on its surface. The equilibrium data fitted well with the Langmuir model, and adsorption capacity of MB ranged from 51.8 to 344.8 mg g⁻¹. Good correlation coefficients were obtained using the intra-particle diffusion model, indicating that the adsorption of MB onto ACs is diffusion controlled. The values of the effective diffusion coefficient ranged from 0.61 × 10⁻¹⁰ to 7.1 × 10⁻¹⁰ m² s⁻¹, indicating that ACs from lower-rank coals have higher effective diffusivities. Among all the ACs obtained from selected coals, the AC from low-rank lignite brown coal was the most effective in removing MB from an aqueous solution.

Improved dynamic MRI reconstruction by exploiting sparsity and rank-deficiency.

PubMed

Majumdar, Angshul

2013-06-01

In this paper we address the problem of dynamic MRI reconstruction from partially sampled K-space data. Our work is motivated by previous studies in this area that proposed exploiting the spatiotemporal correlation of the dynamic MRI sequence by posing the reconstruction problem as a least squares minimization regularized by sparsity and low-rank penalties. Ideally the sparsity and low-rank penalties should be represented by the l(0)-norm and the rank of a matrix; however both are NP hard penalties. The previous studies used the convex l(1)-norm as a surrogate for the l(0)-norm and the non-convex Schatten-q norm (0rank of matrix. Following past research in sparse recovery, we know that non-convex l(p)-norm (0

rank penalty. There are no efficient algorithms to solve the said problems. In this paper, we derive efficient algorithms to solve them. The experiments have been carried out on Dynamic Contrast Enhanced (DCE) MRI datasets. Both quantitative and qualitative analysis indicates the superiority of our proposed improvement over the existing methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Hitting the Rankings Jackpot

ERIC Educational Resources Information Center

Chapman, David W.

2008-01-01

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

The feasibility of ranking material fracture toughness by ultrasonic attenuation measurements

NASA Technical Reports Server (NTRS)

Vary, A.

1975-01-01

A preliminary study was conducted to assess the feasibility of ultrasonically ranking material fracture toughness. Specimens of two grades of maraging steel for which fracture toughness values were measured were subjected to ultrasonic probing. The slope of the attenuation coefficient vs frequency curve was empirically correlated with the plane strain fracture toughness value for each grade of steel.

The feasibility of ranking material fracture toughness by ultrasonic attenuation measurements

NASA Technical Reports Server (NTRS)

Vary, A.

1975-01-01

A preliminary study was conducted to assess the feasibility of ultrasonically ranking material fracture toughness. Specimens of two grades of maraging steel for which fracture toughness values were measured were subjected to ultrasonic probing. The slope of the attenuation coefficient versus frequency curve was empirically correlated with the plane strain fracture toughness value for each grade of steel.

Male ruff colour as a rank signal in a monomorphic-horned mammal: behavioural correlates

NASA Astrophysics Data System (ADS)

Lovari, S.; Fattorini, N.; Boesi, R.; Bocci, A.

2015-08-01

Coexistence of individuals within a social group is possible through the establishment of a hierarchy. Social dominance is achieved through aggressive interactions, and, in wild sheep and goats, it is related mainly to age, body size and weapon size as rank signals. Adult male Himalayan tahr are much larger than females and subadult males. They have a prominent neck ruff, ranging in colour from yellow (5.5-9.5 years old, i.e. young adults, golden males) to brown (7.5-14.5 years old, i.e. older individuals, pale and dark brown males), with golden males being the most dominant. We investigated the social behaviour of male tahr and analysed the relationships between ruff colour, courtship and agonistic behaviour patterns during the rut. Colour classes varied in their use of several behaviour patterns (male dominance: approach, stare, horning vegetation; courtship: low stretch, naso- genital contact, rush). Golden-ruffed males used more threats than darker ones. Pale brown and dark brown males addressed threats significantly more often to males of lower or their own colour classes, respectively, whereas golden ones addressed threats to all colour classes, including their own. The courtship of dominant males was characterised by the assertive rush, whereas that of subordinates did not. Ruff colour of male Himalayan tahr may have evolved as a rank signal, homologous to horn size in wild sheep and goats.

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

PubMed

Wood, Lisa; Irons, Chris

2017-09-01

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

Understanding of social capital condition among red guava farmers in Tambahrejo Village, Pageruyung District, Kendal Regency

NASA Astrophysics Data System (ADS)

Gayatri, S.; Sumarjono, D.; Satmoko, S.

2018-01-01

The aim of the study was to explore the potential of social capital and growing income of red guava farmers in Tambahrejo Village, Pageruyung District, Kendal Regency. Interview and observation were used for data collection. Set of Questionnaire was developed to answer research’ goal. All member of farmer group I ACC (Kelompok Tani Makmur I ACC) were chosen as respondents in this research. Data were analyzed using multiple regressions. The result shows that there was significant relationship between social capital in community and the income of the red guava farmers. Farmer’ group was found as a media to improve farmers’ knowledge and networking. Farmers group facilitated farmers to market red guava product. Moreover, wife of the farmers established women group or KWT (Kelompok Wanita Tani). The result found that KWT contributed to improve family’s income. KWT also promote activities to help product’s diversification of red guava. Both farmer group and KWT provided activities such as saving and loans, it means there was trust among member of farmer group.

K2 and K2*: efficient alignment-free sequence similarity measurement based on Kendall statistics.

PubMed

Lin, Jie; Adjeroh, Donald A; Jiang, Bing-Hua; Jiang, Yue

2018-05-15

Alignment-free sequence comparison methods can compute the pairwise similarity between a huge number of sequences much faster than sequence-alignment based methods. We propose a new non-parametric alignment-free sequence comparison method, called K2, based on the Kendall statistics. Comparing to the other state-of-the-art alignment-free comparison methods, K2 demonstrates competitive performance in generating the phylogenetic tree, in evaluating functionally related regulatory sequences, and in computing the edit distance (similarity/dissimilarity) between sequences. Furthermore, the K2 approach is much faster than the other methods. An improved method, K2*, is also proposed, which is able to determine the appropriate algorithmic parameter (length) automatically, without first considering different values. Comparative analysis with the state-of-the-art alignment-free sequence similarity methods demonstrates the superiority of the proposed approaches, especially with increasing sequence length, or increasing dataset sizes. The K2 and K2* approaches are implemented in the R language as a package and is freely available for open access (http://community.wvu.edu/daadjeroh/projects/K2/K2_1.0.tar.gz). yueljiang@163.com. Supplementary data are available at Bioinformatics online.

The Globalization of College and University Rankings

ERIC Educational Resources Information Center

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…

Different actuarial risk measures produce different risk rankings for sexual offenders.

PubMed

Barbaree, Howard E; Langton, Calvin M; Peacock, Edward J

2006-10-01

Percentile ranks were computed for N=262 sex offenders using each of 5 actuarial risk instruments commonly used with adult sex offenders (RRASOR, Static-99, VRAG, SORAG, and MnSOST-R). Mean differences between percentile ranks obtained by different actuarial measures were found to vary inversely with the correlation between the actuarial scores. Following studies of factor analyses of actuarial items, we argue that the discrepancies among actuarial instruments can be substantially accounted for by the way in which the factor Antisocial Behavior and various factors reflecting sexual deviance are represented among the items contained in each instrument. In the discussion, we provide guidance to clinicians in resolving discrepancies between instruments and we discuss implications for future developments in sex offender risk assessment.

Statistical Optimality in Multipartite Ranking and Ordinal Regression.

PubMed

Uematsu, Kazuki; Lee, Yoonkyung

2015-05-01

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

Interval-Valued Rank in Finite Ordered Sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joslyn, Cliff; Pogel, Alex; Purvine, Emilie

We consider the concept of rank as a measure of the vertical levels and positions of elements of partially ordered sets (posets). We are motivated by the need for algorithmic measures on large, real-world hierarchically-structured data objects like the semantic hierarchies of ontolog- ical databases. These rarely satisfy the strong property of gradedness, which is required for traditional rank functions to exist. Representing such semantic hierarchies as finite, bounded posets, we recognize the duality of ordered structures to motivate rank functions which respect verticality both from the bottom and from the top. Our rank functions are thus interval-valued, and alwaysmore » exist, even for non-graded posets, providing order homomorphisms to an interval order on the interval-valued ranks. The concept of rank width arises naturally, allowing us to identify the poset region with point-valued width as its longest graded portion (which we call the “spindle”). A standard interval rank function is naturally motivated both in terms of its extremality and on pragmatic grounds. Its properties are examined, including the relation- ship to traditional grading and rank functions, and methods to assess comparisons of standard interval-valued ranks.« less

Class Rank Weighs Down True Learning

ERIC Educational Resources Information Center

Guskey, Thomas R.

2014-01-01

The process of determining class rank does not help students achieve more or reach higher levels of proficiency. Evidence indicates ranking students may diminish students' motivation. High school educators argue that they are compelled to rank-order graduating students because selective colleges and universities require information about…

Ranking in evolving complex networks

NASA Astrophysics Data System (ADS)

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.

IL-17A-mediated sRANK ligand elevation involved in postmenopausal osteoporosis.

PubMed

Molnár, I; Bohaty, I; Somogyiné-Vári, É

2014-02-01

The role of proinflammatory IL-17 cytokine was studied in postmenopausal bone loss between 31 osteopenic and 41 osteoporotic women. The effect of serum IL-17A, soluble receptor activator of NF-κB (sRANK) ligand, and osteoprotegerin (OPG) levels on lumbar bone mineral densities was measured. The results demonstrated an increased IL-17A-mediated sRANK ligand elevation in postmenopausal osteoporotic bone loss. IL-17 proinflammatory cytokine is a new inducer of bone loss. Postmenopausal osteoporosis represents a cross talk between estrogen deprivation and increased immune reactivity. The role of IL-17 was studied in the bone loss of postmenopausal osteoporosis. Serum IL-17A, sRANK ligand, and OPG levels were investigated on bone mineral densities (BMDs) in the total lumbar (L1-L4) region in 18 pre- and 72 postmenopausal women. IL-17A, sRANK ligand, OPG levels, and BMDs were measured with enzyme-linked immunosorbent assay (ELISA) and dual-energy X-ray absorptiometry (DXA). Increased serum IL-17A, sRANK ligand, and OPG levels were demonstrated in postmenopausal osteoporotic women compared to osteopenic women (3.65 ± 0.61 vs 3.31 ± 0.43 ng/ml for IL-17A, P < 0.007; 2.88 ± 0.84 vs 2.49 ± 0.61 ng/ml for sRANK ligand, P < 0.027; and 1.43 ± 0.07 vs 1.39 ± 0.07 ng/ml for OPG, P < 0.038). In postmenopausal women, IL-17A levels correlated inversely with total lumbar BMDs (P < 0.008, r = -0.279) and positively with sRANK ligand levels (P < 0.0001, r = 0.387) or the ratio of sRANK ligand and OPG (P < 0.013, r = 0.261), but did not with OPG levels alone. Increased IL-17A levels are involved in postmenopausal osteoporosis, playing a role in the bone-resorpting processes.

14 CFR 1214.1105 - Final ranking.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Final ranking. 1214.1105 Section 1214.1105 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION SPACE FLIGHT NASA Astronaut Candidate Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of...

What Contributes More to the Ranking of Higher Education Institutions? A Comparison of Three World University Rankings

ERIC Educational Resources Information Center

Hou, Ya-Wen; Jacob, W. James

2017-01-01

Recently, many universities have drawn attention to world university rankings, which reflect the international competition of universities and represent their relative statuses. This study does not radically contradict types of global university rankings but calls for an examination of the effects of their indicators on the final ranking of…

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

PubMed

Kianifar, Hamidreza; Sadeghi, Ramin; Zarifmahmoudi, Leili

2014-04-01

Impact Factor (IF) as a major journal quality indicator has a series of shortcomings including effect of self-citation, review articles, total number of articles, etc. In this study, we compared 4 journals quality indices ((IF), Eigenfactor Score (ES), Article Influence Score (AIS) and SCImago Journal Rank indicator (SJR)) in the specific Pediatric Neurology journals. All ISI and Scopus indexed specific Pediatric Neurology journals were compared regarding their 2011 IF, ES, AIS and SJR. Fourteen pediatric Neurology journals were identified, 3 of which were only Scopus indexed and the others were both ISI and Scopus indexed. High correlation was found between IF and AIS (0.850). Correlations between IF and other indices were not that high. Self-citation, total article number and review articles were related to the IF and other indices as well as their ranks. English language and citation to non citable item didn't have any effect on pediatric neurology journals ranks. Although all the above mentioned indicators can be used interchangeably, using all considered indices is a more appropriate way than using only IF for quality assessment of pediatric neurology journals.

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

PubMed Central

Kianifar, Hamidreza; Sadeghi, Ramin; Zarifmahmoudi, Leili

2014-01-01

Background: Impact Factor (IF) as a major journal quality indicator has a series of shortcomings including effect of self-citation, review articles, total number of articles, etc. In this study, we compared 4 journals quality indices ((IF), Eigenfactor Score (ES), Article Influence Score (AIS) and SCImago Journal Rank indicator (SJR)) in the specific Pediatric Neurology journals. Methods: All ISI and Scopus indexed specific Pediatric Neurology journals were compared regarding their 2011 IF, ES, AIS and SJR. Results: Fourteen pediatric Neurology journals were identified, 3 of which were only Scopus indexed and the others were both ISI and Scopus indexed. High correlation was found between IF and AIS (0.850). Correlations between IF and other indices were not that high. Self-citation, total article number and review articles were related to the IF and other indices as well as their ranks. English language and citation to non citable item didn’t have any effect on pediatric neurology journals ranks. Conclusion: Although all the above mentioned indicators can be used interchangeably, using all considered indices is a more appropriate way than using only IF for quality assessment of pediatric neurology journals. PMID:24825934

Dynamics of Ranking Processes in Complex Systems

NASA Astrophysics Data System (ADS)

Blumm, Nicholas; Ghoshal, Gourab; Forró, Zalán; Schich, Maximilian; Bianconi, Ginestra; Bouchaud, Jean-Philippe; Barabási, Albert-László

2012-09-01

The world is addicted to ranking: everything, from the reputation of scientists, journals, and universities to purchasing decisions is driven by measured or perceived differences between them. Here, we analyze empirical data capturing real time ranking in a number of systems, helping to identify the universal characteristics of ranking dynamics. We develop a continuum theory that not only predicts the stability of the ranking process, but shows that a noise-induced phase transition is at the heart of the observed differences in ranking regimes. The key parameters of the continuum theory can be explicitly measured from data, allowing us to predict and experimentally document the existence of three phases that govern ranking stability.

On Rank and Nullity

ERIC Educational Resources Information Center

Dobbs, David E.

2012-01-01

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

A Universal Rank-Size Law

PubMed Central

2016-01-01

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

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

PubMed

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.

Pacing Behavior and Tactical Positioning in 1500-m Short-Track Speed Skating.

PubMed

Konings, Marco J; Noorbergen, Olaf S; Parry, David; Hettinga, Florentina J

2016-01-01

To gain more insight in pacing behavior and tactical positioning in 1500-m short-track speed skating, a sport in which several athletes directly compete in the same race. Lap times and intermediate rankings of elite 1500-m short-track- skating competitors were collected over the season 2012-13 (N = 510, 85 races). Two statistical approaches were used to assess pacing behavior and tactical positioning. First, lap times were analyzed using a MANOVA, and for each lap differences between sex, race type, final rankings, and stage of competition were determined. Second, Kendall tau b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined. In 1500 m (13.5 laps of 111.12 m), correlations between intermediate and final ranking gradually increased throughout the race (eg, lap 1, r = .05; lap 7, r = .26; lap 13, r = .85). Moreover, the percentage of race winners skating in the leading position was over 50% during the last 3 laps. Top finishers were faster than bottom-place finishers only during the last 5 laps, with on average 0.1- to 1.5-s faster lap times of the race winners compared with the others during the last 5 laps. Although a fast start led to faster finishing times, top finishers were faster than bottom-placed finishers only during the last 5 laps. Moreover, tactical positioning at 1 of the foremost positions during the latter phase of the race appeared to be a strong determinant of finishing position.

Pacing Behavior and Tactical Positioning in 500- and 1000-m Short-Track Speed Skating.

PubMed

Noorbergen, Olaf S; Konings, Marco J; Micklewright, Dominic; Elferink-Gemser, Marije T; Hettinga, Florentina J

2016-09-01

To explore pacing behavior and tactical positioning during the shorter 500- and 1000-m short-track competitions. Lap times and intermediate rankings of elite 500- and 1000-m short-track-skating competitors were collected over the 2012-13 season. First, lap times were analyzed using a MANOVA, and for each lap, differences between sex, race type, final ranking, and stage of competition were determined. Second, Kendall tau-b correlations were used to assess relationships between intermediate and final rankings. In addition, intermediate rankings of the winner of each race were examined. Top-placed athletes appeared faster than bottom-placed athletes in every lap in the 500-m, while in the 1000-m no differences were found until the final 4 laps (P < .05). Correlations between intermediate and final rankings were already high at the beginning stages of the 50-m (lap 1: r = .59) but not for the 1000-m (lap 1: r = .21). Although 500- and 1000-m short-track races are both relatively short, fundamental differences in pacing behavior and tactical positioning were found. A fast-start strategy seems to be optimal for 500-m races, while the crucial segment in 1000-m races seems to be from the 6th lap to the finish line (ie, after ± 650 m). These findings provide evidence to suggest that athletes balance between choosing an energetically optimal profile and the tactical and positional benefits that play a role when riding against an opponent, as well as contributing to developing novel insights in exploring athletic behavior when racing against opponents.

Similarity preserving low-rank representation for enhanced data representation and effective subspace learning.

PubMed

Zhang, Zhao; Yan, Shuicheng; Zhao, Mingbo

2014-05-01

Latent Low-Rank Representation (LatLRR) delivers robust and promising results for subspace recovery and feature extraction through mining the so-called hidden effects, but the locality of both similar principal and salient features cannot be preserved in the optimizations. To solve this issue for achieving enhanced performance, a boosted version of LatLRR, referred to as Regularized Low-Rank Representation (rLRR), is proposed through explicitly including an appropriate Laplacian regularization that can maximally preserve the similarity among local features. Resembling LatLRR, rLRR decomposes given data matrix from two directions by seeking a pair of low-rank matrices. But the similarities of principal and salient features can be effectively preserved by rLRR. As a result, the correlated features are well grouped and the robustness of representations is also enhanced. Based on the outputted bi-directional low-rank codes by rLRR, an unsupervised subspace learning framework termed Low-rank Similarity Preserving Projections (LSPP) is also derived for feature learning. The supervised extension of LSPP is also discussed for discriminant subspace learning. The validity of rLRR is examined by robust representation and decomposition of real images. Results demonstrated the superiority of our rLRR and LSPP in comparison to other related state-of-the-art algorithms. Copyright © 2014 Elsevier Ltd. All rights reserved.

A framework for automatic information quality ranking of diabetes websites.

PubMed

Belen Sağlam, Rahime; Taskaya Temizel, Tugba

2015-01-01

Objective: When searching for particular medical information on the internet the challenge lies in distinguishing the websites that are relevant to the topic, and contain accurate information. In this article, we propose a framework that automatically identifies and ranks diabetes websites according to their relevance and information quality based on the website content. Design: The proposed framework ranks diabetes websites according to their content quality, relevance and evidence based medicine. The framework combines information retrieval techniques with a lexical resource based on Sentiwordnet making it possible to work with biased and untrusted websites while, at the same time, ensuring the content relevance. Measurement: The evaluation measurements used were Pearson-correlation, true positives, false positives and accuracy. We tested the framework with a benchmark data set consisting of 55 websites with varying degrees of information quality problems. Results: The proposed framework gives good results that are comparable with the non-automated information quality measuring approaches in the literature. The correlation between the results of the proposed automated framework and ground-truth is 0.68 on an average with p < 0.001 which is greater than the other proposed automated methods in the literature (r score in average is 0.33).

Rank-based decompositions of morphological templates.

PubMed

Sussner, P; Ritter, G X

2000-01-01

Methods for matrix decomposition have found numerous applications in image processing, in particular for the problem of template decomposition. Since existing matrix decomposition techniques are mainly concerned with the linear domain, we consider it timely to investigate matrix decomposition techniques in the nonlinear domain with applications in image processing. The mathematical basis for these investigations is the new theory of rank within minimax algebra. Thus far, only minimax decompositions of rank 1 and rank 2 matrices into outer product expansions are known to the image processing community. We derive a heuristic algorithm for the decomposition of matrices having arbitrary rank.

Judging in Rhythmic Gymnastics at Different Levels of Performance.

PubMed

Leandro, Catarina; Ávila-Carvalho, Lurdes; Sierra-Palmeiro, Elena; Bobo-Arce, Marta

2017-12-01

This study aimed to analyse the quality of difficulty judging in rhythmic gymnastics, at different levels of performance. The sample consisted of 1152 difficulty scores concerning 288 individual routines, performed in the World Championships in 2013. The data were analysed using the mean absolute judge deviation from the final difficulty score, a Cronbach's alpha coefficient and intra-class correlations, for consistency and reliability assessment. For validity assessment, mean deviations of judges' difficulty scores, the Kendall's coefficient of concordance W and ANOVA eta-squared values were calculated. Overall, the results in terms of consistency (Cronbach's alpha mostly above 0.90) and reliability (intra-class correlations for single and average measures above 0.70 and 0.90, respectively) were satisfactory, in the first and third parts of the ranking on all apparatus. The medium level gymnasts, those in the second part of the ranking, had inferior reliability indices and highest score dispersion. In this part, the minimum of corrected item-total correlation of individual judges was 0.55, with most values well below, and the matrix for between-judge correlations identified remarkable inferior correlations. These findings suggest that the quality of difficulty judging in rhythmic gymnastics may be compromised at certain levels of performance. In future, special attention should be paid to the judging analysis of the medium level gymnasts, as well as the Code of Points applicability at this level.

MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation

PubMed Central

Wang, Luman; Mo, Qiaochu; Wang, Jianxin

2015-01-01

Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches. PMID:26881263

MIrExpress: A Database for Gene Coexpression Correlation in Immune Cells Based on Mutual Information and Pearson Correlation.

PubMed

Wang, Luman; Mo, Qiaochu; Wang, Jianxin

2015-01-01

Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches.

Publication Productivity and Experience: Factors Associated with Academic Rank Among Orthopaedic Surgery Faculty in the United States.

PubMed

Ence, Andrew K; Cope, Seth R; Holliday, Emma B; Somerson, Jeremy S

2016-05-18

Many factors play a role in academic promotion among orthopaedic surgeons. This study specifically examined the importance of publication productivity metrics, career duration, and sex on academic rank in orthopaedic surgery programs in the United States. Faculty at 142 civilian academic orthopaedic surgery departments in 2014 were identified. Geographic region, department size, and 3 specific faculty characteristics (sex, career duration, and academic position) were recorded. The Hirsch index (h-index), defined as the number (h) of an investigator's publications that have been cited at least h times, was recorded for each surgeon. The m-index was also calculated by dividing the h-index by career duration in years. Thresholds for the h-index and the m-index were identified between junior and senior academic ranks. Multivariate analysis was used to determine whether the 3 physician factors correlated independently with academic rank. The analysis included 4,663 orthopaedic surgeons at 142 academic institutions (24.7% clinical faculty and 75.3% academic faculty). Among academic faculty, the median h-index was 5, the median career duration was 15 years, and the median m-index was 0.37. Thresholds between junior and senior faculty status were 12 for the h-index and 0.51 for the m-index. Female academic faculty had a lower median h-index (3 compared with 5; p < 0.001) and career duration (10 years compared with 16 years; p < 0.001) than male academic faculty, but had a similar median m-index (0.33 compared with 0.38; p = 0.103). A higher h-index and longer career duration correlated independently with an increased probability of senior academic rank (p < 0.001), but sex did not (p = 0.217). This analysis demonstrates that a higher h-index and m-index correlate with a higher academic orthopaedic faculty rank. Although female surgeons had a lower median h-index and a shorter median career duration than male surgeons, their m-index was not significantly different, and thus

Synchronous correlation matrices and Connes’ embedding conjecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dykema, Kenneth J., E-mail: kdykema@math.tamu.edu; Paulsen, Vern, E-mail: vern@math.uh.edu

In the work of Paulsen et al. [J. Funct. Anal. (in press); preprint arXiv:1407.6918], the concept of synchronous quantum correlation matrices was introduced and these were shown to correspond to traces on certain C*-algebras. In particular, synchronous correlation matrices arose in their study of various versions of quantum chromatic numbers of graphs and other quantum versions of graph theoretic parameters. In this paper, we develop these ideas further, focusing on the relations between synchronous correlation matrices and microstates. We prove that Connes’ embedding conjecture is equivalent to the equality of two families of synchronous quantum correlation matrices. We prove thatmore » if Connes’ embedding conjecture has a positive answer, then the tracial rank and projective rank are equal for every graph. We then apply these results to more general non-local games.« less

Error analysis of stochastic gradient descent ranking.

PubMed

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.

Variations of DOM quality in inflows of a drinking water reservoir: linking of van Krevelen diagrams with EEMF spectra by rank correlation.

PubMed

Herzsprung, Peter; von Tümpling, Wolf; Hertkorn, Norbert; Harir, Mourad; Büttner, Olaf; Bravidor, Jenny; Friese, Kurt; Schmitt-Kopplin, Philippe

2012-05-15

Elevated concentrations of dissolved organic matter (DOM) such as humic substances in raw water pose significant challenges during the processing of the commercial drinking water supplies. This is a relevant issue in Saxony, Central East Germany, and many other regions worldwide, where drinking water is produced from raw waters with noticeable presence of chromophoric DOM (CDOM), which is assumed to originate from forested watersheds in spring regions of the catchment area. For improved comprehension of DOM molecular composition, the seasonal and spatial variations of humic-like fluorescence and elemental formulas in the catchment area of the Muldenberg reservoir were recorded by excitation emission matrix fluorescence (EEMF) and ultrahigh-resolution mass spectrometry (FT-ICR-MS). The Spearman rank correlation was applied to link the EEMF intensities with exact molecular formulas and their corresponding relative mass peak abundances. Thereby, humic-like fluorescence could be allocated to the pool of oxygen-rich and relatively unsaturated components with stoichiometries similar to those of tannic acids, which are suspected to have a comparatively high disinfection byproduct formation potential associated with the chlorination of raw water. Analogous relationships were established for UV absorption at 254 nm (UV(254)) and dissolved organic carbon (DOC) and compared to the EEMF correlation.

Rank distributions: A panoramic macroscopic outlook

NASA Astrophysics Data System (ADS)

Eliazar, Iddo I.; Cohen, Morrel H.

2014-01-01

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

Rank distributions: a panoramic macroscopic outlook.

PubMed

Eliazar, Iddo I; Cohen, Morrel H

2014-01-01

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

Ranking Disciplinary Journals with the Google Scholar H-Index: A New Tool for Constructing Cases for Tenure, Promotion, and Other Professional Decisions

ERIC Educational Resources Information Center

Hodge, David R.; Lacasse, Jeffrey R.

2011-01-01

Given the importance of journal rankings to tenure, promotion, and other professional decisions, this study examines a new method for ranking social work journals. The Google Scholar h-index correlated highly with the current gold standard for measuring journal quality, Thomson Institute for Scientific Information (ISI) impact factors, but…

Diversifying customer review rankings.

PubMed

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.

Implication of correlations among some common stability statistics - a Monte Carlo simulations.

PubMed

Piepho, H P

1995-03-01

Stability analysis of multilocation trials is often based on a mixed two-way model. Two stability measures in frequent use are the environmental variance (S i (2) )and the ecovalence (W i). Under the two-way model the rank orders of the expected values of these two statistics are identical for a given set of genotypes. By contrast, empirical rank correlations among these measures are consistently low. This suggests that the two-way mixed model may not be appropriate for describing real data. To check this hypothesis, a Monte Carlo simulation was conducted. It revealed that the low empirical rank correlation amongS i (2) and W i is most likely due to sampling errors. It is concluded that the observed low rank correlation does not invalidate the two-way model. The paper also discusses tests for homogeneity of S i (2) as well as implications of the two-way model for the classification of stability statistics.

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

PubMed

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

2015-01-01

Health administration (HA) faculty members publish in a variety of journals, including journals focused on management, economics, policy, and information technology. HA faculty members are evaluated on the basis of the quality and quantity of their journal publications. However, it is unclear how perceptions of these journals vary by subdiscipline, department leadership role, or faculty rank. It is also not clear how perceptions of journals may have changed over the past decade since the last evaluation of journal rankings in the field was published. The purpose of the current study is to examine how respondents rank journals in the field of HA, as well as the variation in perception by academic rank, department leadership status, and area of expertise. Data were drawn from a survey of HA faculty members at U.S. universities, which was completed in 2012. Different journal ranking patterns were noted for faculty members of different subdisciplines. The health management-oriented journals (Health Care Management Review and Journal of Healthcare Management) were ranked higher than in previous research, suggesting that journal ranking perceptions may have changed over the intervening decade. Few differences in perceptions were noted by academic rank, but we found that department chairs were more likely than others to select Health Affairs in their top three most prestigious journals (β = 0.768; p < .01). Perceived journal prestige varied between a department chair and untenured faculty in different disciplines, and this perceived difference could have implications for promotion and tenure decisions.

Correlation Between Cephalometric Measures and End-of-Treatment Facial Attractiveness.

PubMed

Yu, Xiao-nan; Bai, Ding; Feng, Xue; Liu, Yue-hua; Chen, Wen-jing; Li, Song; Han, Guang-li; Jiang, Ruo-ping; Xu, Tian-min

2016-03-01

Sixty-nine experienced Chinese orthodontists evaluated 108 Chinese patients' facial attractiveness from set of photographs (frontal, lateral, and frontal smiling photos) taken at the end of orthodontic treatment. These 108 patients, which contained an equal number of patients with Class I, II, and III malocclusion, were randomly selected from 6 orthodontic treatment centers throughout China. Spearman rank-order correlation coefficients (rs) analyses were performed to examine agreement in ranking between all judge pairs. Pearson correlation and multivariate regression were performed to examine the correlation between cephalometric measures and end-of-treatment Photo Attractiveness Rank.96.68% judge pairs showed moderate correlated (+0.4 ≤ rs < +0.7) subjective rankings. Cephalometric measures significantly correlated with end-of-treatment Photo Attractiveness Rank included interincisal angle (r = 0.330, P < 0.05), L1/MP° (r = 0.386, P < 0.05), L1-NBmm (r = 0.451, P < 0.01), L1/NB° (r = 0.374, P < 0.05), and profile angle (r = 0.353, P < 0.05) in Class I patients with an explained variance of 32.8%, and ANB angle (r = 0.432, P < 0.01), angle of convexity (r = 0.448, P < 0.01), profile angle (r = 0.488, P < 0.01), Li to E-line (r = 0.374, P < 0.05), Li to B-line (r = 0.543, P < 0.01), and Z angle (r = 0.543, P < 0.01) in Class II patient with an explained variance of 43.3%.There was less association than expected between objective measurements on the lateral cephalograms and clinicians' rankings of facial attractiveness on clinical photography in Chinese patients. Straight-stand lower incisor was desired for facial attractiveness of Class I malocclusion; and sagittal relationship and lip prominence influence the esthetics of Class II malocclusion in Chinese population.

Chandrasekhar-Kendall modes and Taylor relaxation in an axisymmetric torus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, X.Z.; Boozer, A.H.; Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027

2005-10-01

The helicity-conserving Taylor relaxation of a plasma in a toroidal chamber to a force-free configuration, which means j=(j{sub parallel})/B)B with j{sub parallel}/B independent of position, can be generalized to include the external injection of magnetic helicity. When this is done, j{sub parallel}/B has resonant values, which can be understood using the eigenmodes of Taylor-relaxed plasmas enclosed by a perfectly conducting toroidal shell. These eigenmodes include a toroidal generalization of those found by Chandrasekhar and Kendall (CK) [Astrophys. J. 126, 457 (1957)] for a spherical chamber, which has no externally produced magnetic flux. It is shown that the CK modes inmore » an axisymmetric torus are of three types: (1) helical modes as well as axisymmetric modes that have (2) and have no (3) net toroidal flux. Yoshida and Giga (YG) [Math. Z. 204, 235 (1990)] published a fourth class of modes: axisymmetric modes that have no net toroidal flux in the chamber due to toroidal flux produced by a net poloidal current in the shell canceling the net toroidal flux from the plasma currents. Jensen and Chu [Phys. Fluids 27, 2881 (1984)], as well as Taylor [Rev. Mod. Phys. 58, 741 (1986)], considered modes in which the vector potential was zero on the axisymmetric toroidal chamber. It is shown that these Jensen-Chu-Taylor modes include only the CK helical modes and the CK axisymmetric modes without net toroidal flux. If the toroidal chamber is perfectly conducting except for a cut that prevents a net poloidal current from flowing, resonances in j{sub parallel}/B occur at the eigenvalues of the axisymmetric CK modes. Jensen and Chu studied this type of resonance. Without the cut, so a poloidal current flows to conserve the net toroidal flux, it is shown that j{sub parallel}/B resonances occur at the eigenvalues of the CK modes that have no net toroidal flux and at the eigenvalues of the YG modes, which are upshifted from the eigenvalues of the axisymmetric CK modes

Augmenting the Deliberative Method for Ranking Risks.

PubMed

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.

Validation of the CNS Penetration-Effectiveness Rank for Quantifying Antiretroviral Penetration Into the Central Nervous System

PubMed Central

Letendre, Scott; Marquie-Beck, Jennifer; Capparelli, Edmund; Best, Brookie; Clifford, David; Collier, Ann C.; Gelman, Benjamin B.; McArthur, Justin C.; McCutchan, J. Allen; Morgello, Susan; Simpson, David; Grant, Igor; Ellis, Ronald J.

2009-01-01

Objective To evaluate whether penetration of a combination regimen into the central nervous system (CNS), as estimated by the CNS Penetration-Effectiveness (CPE) rank, is associated with lower cerebrospinal fluid (CSF) viral load. Design Data were analyzed from 467 participants who were human immunodeficiency virus (HIV) seropositive and who reported antiretroviral (ARV) drug use. Individual ARV drugs were assigned a penetration rank of 0 (low), 0.5 (intermediate), or 1 (high) based on their chemical properties, concentrations in CSF, and/or effectiveness in the CNS in clinical studies. The CPE rank was calculated by summing the individual penetration ranks for each ARV in the regimen. Results The median CPE rank was 1.5 (interquartile range, 1–2). Lower CPE ranks correlated with higher CSF viral loads. Ranks less than 2 were associated with an 88% increase in the odds of detectable CSF viral load. In multivariate regression, lower CPE ranks were associated with detectable CSF viral loads even after adjusting for total number of ARV drugs, ARV drug adherence, plasma viral load, duration and type of the current regimen, and CD4 count. Conclusions Poorer penetration of ARV drugs into the CNS appears to allow continued HIV replication in the CNS as indicated by higher CSF HIV viral loads. Because inhibition of HIV replication in the CNS is probably critical in treating patients who have HIV-associated neurocognitive disorders, ARV treatment strategies that account for CNS penetration should be considered in consensus treatment guidelines and validated in clinical studies. PMID:18195140

A Gaussian-based rank approximation for subspace clustering

NASA Astrophysics Data System (ADS)

Xu, Fei; Peng, Chong; Hu, Yunhong; He, Guoping

2018-04-01

Low-rank representation (LRR) has been shown successful in seeking low-rank structures of data relationships in a union of subspaces. Generally, LRR and LRR-based variants need to solve the nuclear norm-based minimization problems. Beyond the success of such methods, it has been widely noted that the nuclear norm may not be a good rank approximation because it simply adds all singular values of a matrix together and thus large singular values may dominant the weight. This results in far from satisfactory rank approximation and may degrade the performance of lowrank models based on the nuclear norm. In this paper, we propose a novel nonconvex rank approximation based on the Gaussian distribution function, which has demanding properties to be a better rank approximation than the nuclear norm. Then a low-rank model is proposed based on the new rank approximation with application to motion segmentation. Experimental results have shown significant improvements and verified the effectiveness of our method.

Technical Pitfalls in University Rankings

ERIC Educational Resources Information Center

Bougnol, Marie-Laure; Dulá, Jose H.

2015-01-01

Academicians, experts, and other stakeholders have contributed extensively to the literature on university rankings also known as "league tables". Often the tone is critical usually focused on the subjective aspects of the process; e.g., the list of the universities' attributes used in the rankings, their respective weights, and the size…

Rankings matter: nurse graduates from higher-ranked institutions have higher productivity.

PubMed

Yakusheva, Olga; Weiss, Marianne

2017-02-13

Increasing demand for baccalaureate-prepared nurses has led to rapid growth in the number of baccalaureate-granting programs, and to concerns about educational quality and potential effects on productivity of the graduating nursing workforce. We examined the association of individual productivity of a baccalaureate-prepared nurse with the ranking of the degree-granting institution. For a sample of 691 nurses from general medical-surgical units at a large magnet urban hospital between 6/1/2011-12/31/2011, we conducted multivariate regression analysis of nurse productivity on the ranking of the degree-granting institution, adjusted for age, hospital tenure, gender, and unit-specific effects. Nurse productivity was coded as "top"/"average"/"bottom" based on a computation of individual nurse value-added to patient outcomes. Ranking of the baccalaureate-granting institution was derived from the US News and World Report Best Colleges Rankings' categorization of the nurse's institution as the "first tier" or the "second tier", with diploma or associate degree as the reference category. Relative to diploma or associate degree nurses, nurses who had attended first-tier universities had three-times the odds of being in the top productivity category (OR = 3.18, p < 0.001), while second-tier education had a non-significant association with productivity (OR = 1.73, p = 0.11). Being in the bottom productivity category was not associated with having a baccalaureate degree or the quality tier. The productivity boost from a nursing baccalaureate degree depends on the quality of the educational institution. Recognizing differences in educational outcomes, initiatives to build a baccalaureate-educated nursing workforce should be accompanied by improved access to high-quality educational institutions.

Ranking Information in Networks

NASA Astrophysics Data System (ADS)

Eliassi-Rad, Tina; Henderson, Keith

Given a network, we are interested in ranking sets of nodes that score highest on user-specified criteria. For instance in graphs from bibliographic data (e.g. PubMed), we would like to discover sets of authors with expertise in a wide range of disciplines. We present this ranking task as a Top-K problem; utilize fixed-memory heuristic search; and present performance of both the serial and distributed search algorithms on synthetic and real-world data sets.

Deans' Perceptions of Published Rankings of Business Programs

ERIC Educational Resources Information Center

Athavale, Manoj; Bott, Jennifer; Myring, Mark; Richardson, Lynne

2017-01-01

Using a survey of college of business deans, the authors investigate perceptions of published rankings of academic programs. Published rankings have become quite prominent, and anecdotal evidence suggests great efforts are being undertaken to be included in rankings or enhance rankings. The authors conducted a survey of business school deans to…

University Ranking as Social Exclusion

ERIC Educational Resources Information Center

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…

The Privilege of Ranking: Google Plays Ball.

ERIC Educational Resources Information Center

Wiggins, Richard

2003-01-01

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

14 CFR 1214.1105 - Final ranking.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of the selection board's initial evaluations and the results of the interview process. Veteran's...

Academic Quality Rankings of American Colleges and Universities.

ERIC Educational Resources Information Center

Webster, David S.

Past and current methods used in academic quality rankings of U.S. colleges and universities are discussed. In addition to a literature and historical review, modern quality rankings are compared with early (pre-1959) rankings, including past rankings of medical, dental, legal and black education. Also considered are the exemplary 1982 evaluation…

University Rankings in Critical Perspective

ERIC Educational Resources Information Center

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…

Ranking Theory and Conditional Reasoning.

PubMed

Skovgaard-Olsen, Niels

2016-05-01

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

Nominal versus Attained Weights in Universitas 21 Ranking

ERIC Educational Resources Information Center

Soh, Kaycheng

2014-01-01

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

Ethics: An Indispensable Dimension in the University Rankings.

PubMed

Khaki Sedigh, Ali

2017-02-01

University ranking systems attempt to provide an ordinal gauge to make an expert evaluation of the university's performance for a general audience. University rankings have always had their pros and cons in the higher education community. Some seriously question the usefulness, accuracy, and lack of consensus in ranking systems and therefore multidimensional ranking systems have been proposed to overcome some shortcomings of the earlier systems. Although the present ranking results may rather be rough, they are the only available sources that illustrate the complex university performance in a tangible format. Their relative accuracy has turned the ranking systems into an essential feature of the academic lifecycle within the foreseeable future. The main concern however, is that the present ranking systems totally neglect the ethical issues involved in university performances. Ethics should be a new dimension added into the university ranking systems, as it is an undisputable right of the public and all the parties involved in higher education to have an ethical evaluation of the university's achievements. In this paper, to initiate ethical assessment and rankings, the main factors involved in the university performances are reviewed from an ethical perspective. Finally, a basic benchmarking model for university ethical performance is presented.

A Comprehensive Analysis of Marketing Journal Rankings

ERIC Educational Resources Information Center

Steward, Michelle D.; Lewis, Bruce R.

2010-01-01

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

Obsession with Rankings Goes Global

ERIC Educational Resources Information Center

Labi, Aisha

2008-01-01

A Chinese list of the world's top universities would seem an unlikely concern for French politicians. But this year, France's legislature took aim at the annual rankings produced by Shanghai Jiao Tong University, which claims to list the 500 best universities in the world. The highest-ranked French entry, Universite Pierre et Marie Curie, comes in…

Diversity efforts, admissions, and national rankings: can we align priorities?

PubMed

Heller, Caren A; Rúa, Sandra Hurtado; Mazumdar, Madhu; Moon, Jennifer E; Bardes, Charles; Gotto, Antonio M

2014-01-01

Increasing student body diversity is a priority for national health education and professional organizations and for many medical schools. However, national rankings of medical schools, such as those published by U.S. News & World Report, place a heavy emphasis on grade point average (GPA) and Medical College Admissions Test (MCAT) scores, without considering student body diversity. These rankings affect organizational reputation and admissions outcomes, even though there is considerable controversy surrounding the predictive value of GPA and MCAT scores. Our aim in this article was to explore the relationship between standard admissions practices, which typically aim to attract students with the highest academic scores, and student body diversity. We examined how changes in GPA and MCAT scores over 5 years correlated with the percentage of enrolled students who are underrepresented in medicine. In a majority of medical schools in the United States from 2005 to 2009, average GPA and MCAT scores of applicants increased, whereas the percentage of enrolled students who are underrepresented in medicine decreased. Our findings suggest that efforts to increase the diversity of medical school student bodies may be complicated by a desire to maintain high average GPA and MCAT scores. We propose that U.S. News revise its ranking methodology by incorporating a new diversity score into its student selectivity score and by reducing the weight placed on GPA and MCAT scores.

46 CFR 282.11 - Ranking of flags.

Code of Federal Regulations, 2010 CFR

2010-10-01

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

Ranking Businesses and Municipal Locations by Spatiotemporal Cardiac Arrest Risk to Guide Public Defibrillator Placement.

PubMed

Sun, Christopher L F; Brooks, Steven C; Morrison, Laurie J; Chan, Timothy C Y

2017-03-21

Efforts to guide automated external defibrillator placement for out-of-hospital cardiac arrest (OHCA) treatment have focused on identifying broadly defined location categories without considering hours of operation. Broad location categories may be composed of many businesses with varying accessibility. Identifying specific locations for automated external defibrillator deployment incorporating operating hours and time of OHCA occurrence may improve automated external defibrillator accessibility. We aim to identify specific businesses and municipal locations that maximize OHCA coverage on the basis of spatiotemporal assessment of OHCA risk in the immediate vicinity of franchise locations. This study was a retrospective population-based cohort study using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public OHCAs occurring in Toronto, ON, Canada, from January 2007 through December 2015. We identified 41 unique businesses and municipal location types with ≥20 locations in Toronto from the YellowPages, Canadian Franchise Association, and the City of Toronto Open Data Portal. We obtained their geographic coordinates and hours of operation from Web sites, by phone, or in person. We determined the number of OHCAs that occurred within 100 m of each location when it was open (spatiotemporal coverage) for Toronto overall and downtown. The businesses and municipal locations were then ranked by spatiotemporal OHCA coverage. To evaluate temporal stability of the rankings, we calculated intraclass correlation of the annual coverage values. There were 2654 nontraumatic public OHCAs. Tim Hortons ranked first in Toronto, covering 286 OHCAs. Starbucks ranked first in downtown, covering 110 OHCAs. Coffee shops and bank machines from the 5 largest Canadian banks occupied 8 of the top 10 spots in both Toronto and downtown. The rankings exhibited high temporal stability with intraclass correlation values of 0.88 (95

MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis.

PubMed

Yang, Wanqi; Gao, Yang; Shi, Yinghuan; Cao, Longbing

2015-11-01

Learning about multiview data involves many applications, such as video understanding, image classification, and social media. However, when the data dimension increases dramatically, it is important but very challenging to remove redundant features in multiview feature selection. In this paper, we propose a novel feature selection algorithm, multiview rank minimization-based Lasso (MRM-Lasso), which jointly utilizes Lasso for sparse feature selection and rank minimization for learning relevant patterns across views. Instead of simply integrating multiple Lasso from view level, we focus on the performance of sample-level (sample significance) and introduce pattern-specific weights into MRM-Lasso. The weights are utilized to measure the contribution of each sample to the labels in the current view. In addition, the latent correlation across different views is successfully captured by learning a low-rank matrix consisting of pattern-specific weights. The alternating direction method of multipliers is applied to optimize the proposed MRM-Lasso. Experiments on four real-life data sets show that features selected by MRM-Lasso have better multiview classification performance than the baselines. Moreover, pattern-specific weights are demonstrated to be significant for learning about multiview data, compared with view-specific weights.

Evaluation of motion artifact metrics for coronary CT angiography.

PubMed

Ma, Hongfeng; Gros, Eric; Szabo, Aniko; Baginski, Scott G; Laste, Zachary R; Kulkarni, Naveen M; Okerlund, Darin; Schmidt, Taly G

2018-02-01

agreement. The FOR, LIRS, and transformed positivity (the fourth root of the positivity) were further evaluated in the study of clinical images. The Kendall's Tau coefficients of the selected metrics were 0.59 (FOR), 0.53 (LIRS), and 0.21 (Transformed positivity). In the study of clinical data, a Motion Artifact Score, defined as the product of FOR and LIRS metrics, further improved agreement with reader scores, with a Kendall's Tau coefficient of 0.65. The metrics of FOR, LIRS, and the product of the two metrics provided the highest agreement in motion artifact ranking when compared to the readers, and the highest linear correlation to the reader scores. The validated motion artifact metrics may be useful for developing and evaluating methods to reduce motion in Coronary Computed Tomography Angiography (CCTA) images. © 2017 American Association of Physicists in Medicine.

Low-ranking female Japanese macaques make efforts for social grooming

PubMed Central

Kurihara, Yosuke

2016-01-01

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

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

PubMed

Kurihara, Yosuke

2016-04-01

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

Selection for family medicine residency training in Canada: How consistently are the same students ranked by different programs?

PubMed

Wycliffe-Jones, Keith; Hecker, Kent G; Schipper, Shirley; Topps, Maureen; Robinson, Jeanine; Abedin, Tasnima

2018-02-01

To examine the consistency of the ranking of Canadian and US medical graduates who applied to Canadian family medicine (FM) residency programs between 2007 and 2013. Descriptive cross-sectional study. Family medicine residency programs in Canada. All 17 Canadian medical schools allowed access to their anonymized program rank-order lists of students applying to FM residency programs submitted to the first iteration of the Canadian Resident Matching Service match from 2007 to 2013. The rank position of medical students who applied to more than 1 FM residency program on the rank-order lists submitted by the programs. Anonymized ranking data submitted to the Canadian Resident Matching Service from 2007 to 2013 by all 17 FM residency programs were used. Ranking data of eligible Canadian and US medical graduates were analyzed to assess the within-student and between-student variability in rank score. These covariance parameters were then used to calculate the intraclass correlation coefficient (ICC) for all programs. Program descriptions and selection criteria were also reviewed to identify sites with similar profiles for subset ICC analysis. Between 2007 and 2013, the consistency of ranking by all programs was fair at best (ICC = 0.34 to 0.39). The consistency of ranking by larger urban-based sites was weak to fair (ICC = 0.23 to 0.36), and the consistency of ranking by sites focusing on training for rural practice was weak to moderate (ICC = 0.16 to 0.55). In most cases, there is a low level of consistency of ranking of students applying for FM training in Canada. This raises concerns regarding fairness, particularly in relation to expectations around equity and distributive justice in selection processes. Copyright© the College of Family Physicians of Canada.

Comparison of Mann-Kendall and innovative trend method for water quality parameters of the Kizilirmak River, Turkey

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Ay, Murat

2014-05-01

Low, medium and high values of a parameter are very important issues in climatological, meteorological and hydrological events. Moreover these values are used to decide various design parameters based on scientific aspects and real applications everywhere in the world. With this concept, a new trend method recently proposed by Şen was used for water parameters, pH, T, EC, Na+, K+, CO3-2, HCO3-, Cl-, SO4-2, B+3 and Q recorded at five different stations (station numbers and locations: 1535-Sogutluhan (Sivas), 1501-Yamula (Kayseri), 1546-Tuzkoy (Kayseri), 1503-Yahsihan (Kirsehir), and 1533-Inozu (Samsun)) selected from the Kizilirmak River in Turkey. Low, medium and high values of the parameters were graphically evaluated with this method. For comparison purposes, the Mann-Kendall trend test was also applied to the same data. Differences of the two trend tests were also emphasised. It was found that the Şen trend test compared with the MK trend test had several advantages. The results also revealed that the Şen trend test could be successfully used for trend analysis of water parameters especially in terms of evaluation of low, medium and high values of data.

Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques

NASA Astrophysics Data System (ADS)

Machiwal, Deepesh; Gupta, Ankit; Jha, Madan Kumar; Kamble, Trupti

2018-04-01

This study investigated trends in 35 years (1979-2013) temperature (maximum, Tmax and minimum, Tmin) and rainfall at annual and seasonal (pre-monsoon, monsoon, post-monsoon, and winter) scales for 31 grid points in a coastal arid region of India. Box-whisker plots of annual temperature and rainfall time series depict systematic spatial gradients. Trends were examined by applying eight tests, such as Kendall rank correlation (KRC), Spearman rank order correlation (SROC), Mann-Kendall (MK), four modified MK tests, and innovative trend analysis (ITA). Trend magnitudes were quantified by Sen's slope estimator, and a new method was adopted to assess the significance of linear trends in MK-test statistics. It was found that the significant serial correlation is prominent in the annual and post-monsoon Tmax and Tmin, and pre-monsoon Tmin. The KRC and MK tests yielded similar results in close resemblance with the SROC test. The performance of two modified MK tests considering variance-correction approaches was found superior to the KRC, MK, modified MK with pre-whitening, and ITA tests. The performance of original MK test is poor due to the presence of serial correlation, whereas the ITA method is over-sensitive in identifying trends. Significantly increasing trends are more prominent in Tmin than Tmax. Further, both the annual and monsoon rainfall time series have a significantly increasing trend of 9 mm year-1. The sequential significance of linear trend in MK test-statistics is very strong (R 2 ≥ 0.90) in the annual and pre-monsoon Tmin (90% grid points), and strong (R 2 ≥ 0.75) in monsoon Tmax (68% grid points), monsoon, post-monsoon, and winter Tmin (respectively 65, 55, and 48% grid points), as well as in the annual and monsoon rainfalls (respectively 68 and 61% grid points). Finally, this study recommends use of variance-corrected MK test for the precise identification of trends. It is emphasized that the rising Tmax may hamper crop growth due to enhanced

Fair ranking of researchers and research teams

PubMed Central

2018-01-01

The main drawback of ranking of researchers by the number of papers, citations or by the Hirsch index is ignoring the problem of distributing authorship among authors in multi-author publications. So far, the single-author or multi-author publications contribute to the publication record of a researcher equally. This full counting scheme is apparently unfair and causes unjust disproportions, in particular, if ranked researchers have distinctly different collaboration profiles. These disproportions are removed by less common fractional or authorship-weighted counting schemes, which can distribute the authorship credit more properly and suppress a tendency to unjustified inflation of co-authors. The urgent need of widely adopting a fair ranking scheme in practise is exemplified by analysing citation profiles of several highly-cited astronomers and astrophysicists. While the full counting scheme often leads to completely incorrect and misleading ranking, the fractional or authorship-weighted schemes are more accurate and applicable to ranking of researchers as well as research teams. In addition, they suppress differences in ranking among scientific disciplines. These more appropriate schemes should urgently be adopted by scientific publication databases as the Web of Science (Thomson Reuters) or the Scopus (Elsevier). PMID:29621316

Fair ranking of researchers and research teams.

PubMed

Vavryčuk, Václav

2018-01-01

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

Toxic chemical release weighted ranking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrocchi, A.J.

1989-07-19

The weighted ranking as used in this report is an attempt to combine total air release with recognized exposure limit for each toxic chemical to arrive at a single ranking factor called Release Exposure Index (REI) which takes both release amount and degree of hazard into consideration. The REIs can then be used in decision making to prioritize how these chemicals are addressed. 2 tabs.

The application of low-rank and sparse decomposition method in the field of climatology

NASA Astrophysics Data System (ADS)

Gupta, Nitika; Bhaskaran, Prasad K.

2018-04-01

The present study reports a low-rank and sparse decomposition method that separates the mean and the variability of a climate data field. Until now, the application of this technique was limited only in areas such as image processing, web data ranking, and bioinformatics data analysis. In climate science, this method exactly separates the original data into a set of low-rank and sparse components, wherein the low-rank components depict the linearly correlated dataset (expected or mean behavior), and the sparse component represents the variation or perturbation in the dataset from its mean behavior. The study attempts to verify the efficacy of this proposed technique in the field of climatology with two examples of real world. The first example attempts this technique on the maximum wind-speed (MWS) data for the Indian Ocean (IO) region. The study brings to light a decadal reversal pattern in the MWS for the North Indian Ocean (NIO) during the months of June, July, and August (JJA). The second example deals with the sea surface temperature (SST) data for the Bay of Bengal region that exhibits a distinct pattern in the sparse component. The study highlights the importance of the proposed technique used for interpretation and visualization of climate data.

Rank diversity of languages: generic behavior in computational linguistics.

PubMed

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.

Comparing the rankings obtained from two biodiversity indices: the Fair Proportion Index and the Shapley Value.

PubMed

Wicke, Kristina; Fischer, Mareike

2017-10-07

The Shapley Value and the Fair Proportion Index of phylogenetic trees have been frequently discussed as prioritization tools in conservation biology. Both indices rank species according to their contribution to total phylogenetic diversity, allowing for a simple conservation criterion. While both indices have their specific advantages and drawbacks, it has recently been shown that both values are closely related. However, as different authors use different definitions of the Shapley Value, the specific degree of relatedness depends on the specific version of the Shapley Value - it ranges from a high correlation index to equality of the indices. In this note, we first give an overview of the different indices. Then we turn our attention to the mere ranking order provided by either of the indices. We compare the rankings obtained from different versions of the Shapley Value for a phylogenetic tree of European amphibians and illustrate their differences. We then undertake further analyses on simulated data and show that even though the chance of two rankings being exactly identical (when obtained from different versions of the Shapley Value) decreases with an increasing number of taxa, the distance between the two rankings converges to zero, i.e., the rankings are becoming more and more alike. Moreover, we introduce our freely available software package FairShapley, which was implemented in Perl and with which all calculations have been performed. Copyright © 2017 Elsevier Ltd. All rights reserved.

5 CFR 451.302 - Ranks for senior career employees.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Ranks for senior career employees. 451... AWARDS Presidential Rank Awards § 451.302 Ranks for senior career employees. (a) The circumstances under which the President may award the rank of Distinguished Senior Professional and Meritorious Senior...

Node Ranking Tool - NoRT

DTIC Science & Technology

2018-03-23

Unclassified Unlimited Unclassified Unlimited Unclassified Unlimited 23 Ira S. Moskowitz (202) 404-7930 This paper gives a description of the Node Ranking Tool...Disease, Virus, Expectation, Pandemic, Close- ness, Graph, Degree, Spectrum. I. INTRODUCTION THis paper gives a description of the Node Ranking Tool...is very much dependent upon which centrality measure we use. Therefore, following [6] and [3], we use TOPSIS to evaluate our decisions about the

CNN-based ranking for biomedical entity normalization.

PubMed

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.

Composite multi-parameter ranking of real and virtual compounds for design of MC4R agonists: renaissance of the Free-Wilson methodology.

PubMed

Nilsson, Ingemar; Polla, Magnus O

2012-10-01

Drug design is a multi-parameter task present in the analysis of experimental data for synthesized compounds and in the prediction of new compounds with desired properties. This article describes the implementation of a binned scoring and composite ranking scheme for 11 experimental parameters that were identified as key drivers in the MC4R project. The composite ranking scheme was implemented in an AstraZeneca tool for analysis of project data, thereby providing an immediate re-ranking as new experimental data was added. The automated ranking also highlighted compounds overlooked by the project team. The successful implementation of a composite ranking on experimental data led to the development of an equivalent virtual score, which was based on Free-Wilson models of the parameters from the experimental ranking. The individual Free-Wilson models showed good to high predictive power with a correlation coefficient between 0.45 and 0.97 based on the external test set. The virtual ranking adds value to the selection of compounds for synthesis but error propagation must be controlled. The experimental ranking approach adds significant value, is parameter independent and can be tuned and applied to any drug discovery project.

Generalization Performance of Regularized Ranking With Multiscale Kernels.

PubMed

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

2016-05-01

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

Rank-based pooling for deep convolutional neural networks.

PubMed

Shi, Zenglin; Ye, Yangdong; Wu, Yunpeng

2016-11-01

Pooling is a key mechanism in deep convolutional neural networks (CNNs) which helps to achieve translation invariance. Numerous studies, both empirically and theoretically, show that pooling consistently boosts the performance of the CNNs. The conventional pooling methods are operated on activation values. In this work, we alternatively propose rank-based pooling. It is derived from the observations that ranking list is invariant under changes of activation values in a pooling region, and thus rank-based pooling operation may achieve more robust performance. In addition, the reasonable usage of rank can avoid the scale problems encountered by value-based methods. The novel pooling mechanism can be regarded as an instance of weighted pooling where a weighted sum of activations is used to generate the pooling output. This pooling mechanism can also be realized as rank-based average pooling (RAP), rank-based weighted pooling (RWP) and rank-based stochastic pooling (RSP) according to different weighting strategies. As another major contribution, we present a novel criterion to analyze the discriminant ability of various pooling methods, which is heavily under-researched in machine learning and computer vision community. Experimental results on several image benchmarks show that rank-based pooling outperforms the existing pooling methods in classification performance. We further demonstrate better performance on CIFAR datasets by integrating RSP into Network-in-Network. Copyright © 2016 Elsevier Ltd. All rights reserved.

Scalable Faceted Ranking in Tagging Systems

NASA Astrophysics Data System (ADS)

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

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

Rank Diversity of Languages: Generic Behavior in Computational Linguistics

PubMed Central

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

2015-01-01

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

Rehabbing the Rankings: Fool's Errand or the Lord's Work?

ERIC Educational Resources Information Center

Kuh, George D.

2011-01-01

For better or worse, rankings shape public conceptions of collegiate quality. This paper reviews the history of rankings, analyzes what they represent, explores recent efforts to employ indicators in addition to institutional resources and reputation on which the most popular rankings are based, and evaluates the extent to which rankings serve…

Receptor Activator of Nuclear Factor Kappa B (RANK) and Clinicopathological Variables in Endometrial Cancer: A Study at Protein and Gene Level.

PubMed

Gómez, Raúl; Castro, Ana; Martínez, Jessica; Rodríguez-García, Víctor; Burgués, Octavio; Tarín, Juan J; Cano, Antonio

2018-06-22

The system integrated by the receptor activator of nuclear factor kappa B (RANK) and its ligand, RANKL, modulates the role of hormones in the genesis and progression of breast tumors. We investigated whether the expression of RANK was related with clinicopathological features of primary endometrial tumors. Immunohistochemistry was used in an endometrial cancer tissue array containing samples from 36 tumors. The amount of RANK mRNA was examined in a tissue scan cDNA array containing cDNA from 40 tumors. Normal endometrium was examined for comparison. Immunohistochemical analyses showed that RANK expression was higher in malignant than in normal endometrium ( p < 0.05). RANK expression was related to histological grade (Pearson correlation index = 0.484, p < 0.001), but not to tumor stage or to age of the women. The gene expression was similar in malignant and normal endometrium. The study of RANK isoforms confirmed that the overall relative abundance of the three clearly identified transcripts was similar in normal and pathological endometrium. RANK protein expression increased from normal to malignant endometrium, and the expression level was related with tumor grade but not with stage or the age of subjects in endometrial cancer. In contrast, similar comparisons showed no change in RANK gene expression.

FSMRank: feature selection algorithm for learning to rank.

PubMed

Lai, Han-Jiang; Pan, Yan; Tang, Yong; Yu, Rong

2013-06-01

In recent years, there has been growing interest in learning to rank. The introduction of feature selection into different learning problems has been proven effective. These facts motivate us to investigate the problem of feature selection for learning to rank. We propose a joint convex optimization formulation which minimizes ranking errors while simultaneously conducting feature selection. This optimization formulation provides a flexible framework in which we can easily incorporate various importance measures and similarity measures of the features. To solve this optimization problem, we use the Nesterov's approach to derive an accelerated gradient algorithm with a fast convergence rate O(1/T(2)). We further develop a generalization bound for the proposed optimization problem using the Rademacher complexities. Extensive experimental evaluations are conducted on the public LETOR benchmark datasets. The results demonstrate that the proposed method shows: 1) significant ranking performance gain compared to several feature selection baselines for ranking, and 2) very competitive performance compared to several state-of-the-art learning-to-rank algorithms.

Social class rank, threat vigilance, and hostile reactivity.

PubMed

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

2011-10-01

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

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

PubMed

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

2018-01-01

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

Are university rankings useful to improve research? A systematic review

PubMed Central

Momani, Shaher

2018-01-01

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

[Correlation analysis of hearing level and soft palate movement after palatoplasty].

PubMed

Lou, Qun; Ma, Xiaoran; Ma, Lian; Luo, Yi; Zhu, Hongping; Zhou, Zhibo

2015-10-01

To explore the relationship between hearing level and soft palate movement after palatoplasty and to verify the importance of recovery of soft palate movement function for improving the middle ear function as well as reducing the hearing loss. A total of 64 non-syndromic cleft palate patients were selected and the lateral cephalometric radiographs were taken. The patients hearing level was evaluated by the pure tone hearing threshold examination. This study also analyzed the correlation between hearing threshold of the patients after palatoplasty and the soft palate elevation angle and velopharyngeal rate respectively. Kendall correlation analysis revealed that the correlation coefficient between hearing threshold and the soft palate elevation angle after palatoplasty was -0.339 (r = -0.339, P < 0.01).The correlation showed a negative correlation. The hearing threshold decreased as the soft palate elevation angle increased. After palatoplasty, the correlation coefficient between the hearing threshold and the rate of velopharyngeal closure was -0.277 (r = -0.277, P < 0.01). The correlation showed a negative correlation. While, The hearing threshold decreased with the increase of velopharyngeal closure rate. The hearing threshold was correlated with soft palate elevation angle and velpharyngeal closure rate. The movement of soft palate and velopharyngeal closure function after palatoplasty both have impact on patient hearing level. In terms of the influence level, the movement of soft palate has a higher level of impact on patient hearing level than velopharygeal closure function.

Multi-Target Regression via Robust Low-Rank Learning.

PubMed

Zhen, Xiantong; Yu, Mengyang; He, Xiaofei; Li, Shuo

2018-02-01

Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.

25 CFR 1001.3 - Priority ranking for negotiations.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 2 2010-04-01 2010-04-01 false Priority ranking for negotiations. 1001.3 Section 1001.3... PROGRAM § 1001.3 Priority ranking for negotiations. In addition to the eligibility criteria identified above, a tribe or consortium of tribes seeking priority ranking for negotiations must submit a...

25 CFR 1001.3 - Priority ranking for negotiations.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 25 Indians 2 2012-04-01 2012-04-01 false Priority ranking for negotiations. 1001.3 Section 1001.3... PROGRAM § 1001.3 Priority ranking for negotiations. In addition to the eligibility criteria identified above, a tribe or consortium of tribes seeking priority ranking for negotiations must submit a...

25 CFR 1001.3 - Priority ranking for negotiations.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 25 Indians 2 2013-04-01 2013-04-01 false Priority ranking for negotiations. 1001.3 Section 1001.3... PROGRAM § 1001.3 Priority ranking for negotiations. In addition to the eligibility criteria identified above, a tribe or consortium of tribes seeking priority ranking for negotiations must submit a...

25 CFR 1001.3 - Priority ranking for negotiations.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 2 2011-04-01 2011-04-01 false Priority ranking for negotiations. 1001.3 Section 1001.3... PROGRAM § 1001.3 Priority ranking for negotiations. In addition to the eligibility criteria identified above, a tribe or consortium of tribes seeking priority ranking for negotiations must submit a...

25 CFR 1001.3 - Priority ranking for negotiations.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 25 Indians 2 2014-04-01 2014-04-01 false Priority ranking for negotiations. 1001.3 Section 1001.3... PROGRAM § 1001.3 Priority ranking for negotiations. In addition to the eligibility criteria identified above, a tribe or consortium of tribes seeking priority ranking for negotiations must submit a...

Ranking Quality in Higher Education: Guiding or Misleading?

ERIC Educational Resources Information Center

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…

Ending the Reign of the Fraser Institute's School Rankings

ERIC Educational Resources Information Center

Raptis, Helen

2012-01-01

The Fraser Institute "Report Card" of school rankings has won the hearts of parents and the press. For over a decade, the rankings have been particularly burdensome for low-ranking (usually low socio-economic status, high-poverty) schools when parents of high-achieving children move them to higher-ranking schools. In February 2010, after…

An R package for analyzing and modeling ranking data

PubMed Central

2013-01-01

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

An R package for analyzing and modeling ranking data.

PubMed

Lee, Paul H; Yu, Philip L H

2013-05-14

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

Model diagnostics in reduced-rank estimation

PubMed Central

Chen, Kun

2016-01-01

Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches. PMID:28003860

Model diagnostics in reduced-rank estimation.

PubMed

Chen, Kun

2016-01-01

Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches.

Quantum probability ranking principle for ligand-based virtual screening.

PubMed

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.

Quantum probability ranking principle for ligand-based virtual screening

NASA Astrophysics Data System (ADS)

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.

Hydrologic, Hydraulic, and Flood Analyses of the Blackberry Creek Watershed, Kendall County, Illinois

USGS Publications Warehouse

Murphy, Elizabeth A.; Straub, Timothy D.; Soong, David T.; Hamblen, Christopher S.

2007-01-01

Results of the hydrologic model, flood-frequency, hydraulic model, and flood-hazard analysis of the Blackberry Creek watershed in Kendall County, Illinois, indicate that the 100-year and 500-year flood plains cover approximately 3,699 and 3,762 acres of land, respectively. On the basis of land-cover data for 2003, most of the land in the flood plains was cropland and residential land. Although many acres of residential land were included in the flood plain, this land was mostly lawns, with 25 homes within the 100-year flood plain, and 41 homes within the 500-year flood plain in the 2003 aerial photograph. This report describes the data collection activities to refine the hydrologic and hydraulic models used in an earlier study of the Kane County part of the Blackberry Creek watershed and to extend the flood-frequency analysis through water year 2003. The results of the flood-hazard analysis are presented in graphical and tabular form. The hydrologic model, Hydrological Simulation Program - FORTRAN (HSPF), was used to simulate continuous water movement through various land-use patterns in the watershed. Flood-frequency analysis was applied to an annual maximum series to determine flood quantiles in subbasins for flood-hazard analysis. The Hydrologic Engineering Center- River Analysis System (HEC-RAS) hydraulic model was used to determine the 100-year and 500-year flood elevations, and the 100-year floodway. The hydraulic model was calibrated and verified using observations during three storms at two crest-stage gages and the U.S. Geological Survey streamflowgaging station near Yorkville. Digital maps of the 100-year and 500-year flood plains and the 100-year floodway for each tributary and the main stem of Blackberry Creek were compiled.

A novel three-stage distance-based consensus ranking method

NASA Astrophysics Data System (ADS)

Aghayi, Nazila; Tavana, Madjid

2018-05-01

In this study, we propose a three-stage weighted sum method for identifying the group ranks of alternatives. In the first stage, a rank matrix, similar to the cross-efficiency matrix, is obtained by computing the individual rank position of each alternative based on importance weights. In the second stage, a secondary goal is defined to limit the vector of weights since the vector of weights obtained in the first stage is not unique. Finally, in the third stage, the group rank position of alternatives is obtained based on a distance of individual rank positions. The third stage determines a consensus solution for the group so that the ranks obtained have a minimum distance from the ranks acquired by each alternative in the previous stage. A numerical example is presented to demonstrate the applicability and exhibit the efficacy of the proposed method and algorithms.

Learning to rank figures within a biomedical article.

PubMed

Liu, Feifan; Yu, Hong

2014-01-01

Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1) First Author, (2) Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3) Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or out

[Rating and ranking of medical journals: a randomised controlled evaluation of impact factor and number of listed journals].

PubMed

Göbel, U; Niem, V

2012-01-01

The impact factor is a purely bibliometric parameter built on a number of publications and their citations that occur within clearly defined periods. Appropriate interpretation of the impact factor is important as it is also used worldwide for the evaluation of research performance. It is assumed that the number of medical journals reflects the extent of diseases and patient populations involved and that the number is correlated with the level of the impact factor. 174 category lists (Subject Categories) are included in the area Health Sciences of the ISI Web of Knowledge of Thomson Reuters, 71 of which belong to the field of medicine and 50 of which have a clinical and/or application-oriented focus. These alphabetically arranged 50 category lists were consecutively numbered, randomized by odd and even numbers, respectively, into 2 equal-sized groups and then grouped according to organ specialities, sub-specialities and cross-disciplinary fields. By tossing up a coin it was decided which group should be evaluated first. Only then the category lists were downloaded and the number of journals, as well as the impact factors of journals ranking number 1 and 2, as well as the impact factors of journals at the end of the first third and at the end of the first half of each category list were compared. The number of journals per category list varies considerably between 5 and 252. The lists of organ specialties and cross-disciplinary fields include more than three times as many journals as those of the sub-specialities; the highest numbers of journals are listed for the cross-disciplinary fields. The level of impact factor of journals that rank number 1 in the lists varies considerably and ranges from 3,058 to 94,333; a similar variability exists for the journals at rank 2. On the other hand, the impact factor of journals at the end of the first third of the lists varies from 1,214 and 3,953, and for those journals at the end of the first half of a respective category

Image Re-Ranking Based on Topic Diversity.

PubMed

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.

Social class rank, essentialism, and punitive judgment.

PubMed

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.

A Different Approach to University Rankings

ERIC Educational Resources Information Center

Tofallis, Chris

2012-01-01

Educationalists are well able to find fault with rankings on numerous grounds and may reject them outright. However, given that they are here to stay, we could also try to improve them wherever possible. All currently published university rankings combine various measures to produce an overall score using an additive approach. The individual…

Benchmarking Jiangsu University to Improve Its Academic Ranking

ERIC Educational Resources Information Center

Li, Xinchao; Thige, Joseph Muiruri

2017-01-01

This paper collates research on global ranking through U.S.News.com in relation to Jiangsu University's nonappearance in global ranking of higher education institutions. The author critiques the Academic set up of the University in comparison with universities Ranked as World Class. The author navigates the study largely through descriptive and…

Universality, correlations, and rankings in the Brazilian universities national admission examinations

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Lamb, Luis C.; Barbosa, Marcia C.

2016-09-01

We analyze the scores obtained by students who have taken the ENEM examination, The Brazilian High School National Examination which is used in the admission process at Brazilian universities. The average high schools scores from different disciplines are compared through the Pearson correlation coefficient. The results show a very large correlation between the performance in the different school subjects. Even though the students' scores in the ENEM form a Gaussian due to the standardization, we show that the high schools' scores form a bimodal distribution that cannot be used to evaluate and compare students performance over time. We also show that this high schools distribution reflects the correlation between school performance and the economic level (based on the average family income) of the students. The ENEM scores are compared with a Brazilian non standardized exam, the entrance examination from the Universidade Federal do Rio Grande do Sul. The analysis of the performance of the same individuals in both tests shows that the two tests not only select different abilities, but also lead to the admission of different sets of individuals. Our results indicate that standardized tests might be an interesting tool to compare performance of individuals over the years, but not of institutions.

Sign rank versus Vapnik-Chervonenkis dimension

NASA Astrophysics Data System (ADS)

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.

A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.

Rankings and the Global Reputation Race

ERIC Educational Resources Information Center

Hazelkorn, Ellen

2014-01-01

This chapter delves into the growing influence and impact of rankings on higher education, as a lens through which to view how the race for reputation and status is changing the higher education landscape, both globally and nationally. The author considers the extent to which rankings are driving policy choices and institutional decisions and the…

The Rankings Game: Who's Playing Whom?

ERIC Educational Resources Information Center

Burness, John F.

2008-01-01

This summer, Forbes magazine published its new rankings of "America's Best Colleges," implying that it had developed a methodology that would give the public the information that it needed to choose a college wisely. "U.S. News & World Report," which in 1983 published the first annual ranking, just announced its latest ratings last week--including…

College Rankings: History, Criticism and Reform

ERIC Educational Resources Information Center

Myers, Luke; Robe, Jonathan

2009-01-01

Today, college quality rankings in news magazines and guidebooks are a big business with tangible impacts on the operation of higher education institutions. The college rankings published annually by "U.S. News and World Report" ("U.S. News") are so influential that Don Hossler of Indiana University derisively claims that higher education is the…

Public Perception of Cancer Survival Rankings

ERIC Educational Resources Information Center

Jensen, Jakob D.; Scherr, Courtney L.; Brown, Natasha; Jones, Christina; Christy, Katheryn

2013-01-01

Past research has observed that certain subgroups (e.g., individuals who are overweight/obese) have inaccurate estimates of survival rates for particular cancers (e.g., colon cancer). However, no study has examined whether the lay public can accurately rank cancer survival rates in comparison with one another (i.e., rank cancers from most deadly…

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

PubMed

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

Comparison of Anthropometry and Lower Limb Power Qualities According to Different Levels and Ranking Position of Competitive Surfers.

PubMed

Fernandez-Gamboa, Iosu; Yanci, Javier; Granados, Cristina; Camara, Jesus

2017-08-01

Fernandez-Gamboa, I, Yanci, J, Granados, C, and Camara, J. Comparison of anthropometry and lower limb power qualities according to different levels and ranking position of competitive surfers. J Strength Cond Res 31(8): 2231-2237, 2017-The aim of this study was to compare competitive surfers' lower limb power output depending on their competitive level, and to evaluate the association between competition rankings. Twenty competitive surfers were divided according to the competitive level as follows: international (INT) or national (NAT), and competitive ranking (RANK1-50 or RANK51-100). Vertical jump and maximal peak power of the lower limbs were measured. No differences were found between INT and NAT surfers in the anthropometric variables, in the vertical jump, or in lower extremity power; although the NAT group had higher levels on the elasticity index, squat jumps (SJs), and counter movement jumps (CMJs) compared with the INT group. The RANK1-50 group had a lower biceps skinfold (p < 0.01), lower skinfolds in the legs (Front thigh: p ≤ 0.05; medial calf: p < 0.01), lower sum of skinfolds (p ≤ 0.05), higher SJ (p < 0.01), CMJ (p < 0.01), and 15 seconds vertical CMJ (p ≤ 0.05); also, maximal peak power of the right leg (MPPR) and left leg (MPPL) were higher in the RANK1-50 group. Moderate to large significant correlations were obtained between the surfers' ranking position and some skinfolds, the sum of skinfolds, and vertical jump. Results demonstrate that surfers' physical performance seems to be an accurate indicator of ranking positioning, also revealing that vertical jump capacity and anthropometric variables play an important role in their competitive performance, which may be important when considering their power training.

Objective measurements for grading the nasal esthetics on Basal view in individuals with secondary cleft nasal deformity.

PubMed

He, Xing; Li, Hua; Shao, Yan; Shi, Bing

2015-01-01

The purpose of this study is to ascertain objective nasal measurements from the basal view that are predictive of nasal esthetics in individuals with secondary cleft nasal deformity. Thirty-three patients who had undergone unilateral cleft lip repair were retrospectively reviewed in this study. The degree of nasal deformity was subjectively ranked by seven surgeons using standardized basal-view measurements. Nine physical objective parameters including angles and ratios were measured. Correlations and regressions between these objective and subjective measurements were then analyzed. There was high concordance in subjective measurements by different surgeons (Kendall's harmonious coefficient = W = .825, P = .006). The strongest predictive factors for nasal aesthetics were the ratio of length of nasal alar (r = .370, P = .034) and the degree of deviation of the columnar axis (r = .451, P = .008). The columellar angle had a more powerful effect in rating nasal esthetics. There was reliable concordance in subjective ranking of nasal esthetics by surgeons. Measurement of the columnar angle may serve as an independent, objective predictor of esthetics of the nose.

Learning to Rank the Severity of Unrepaired Cleft Lip Nasal Deformity on 3D Mesh Data.

PubMed

Wu, Jia; Tse, Raymond; Shapiro, Linda G

2014-08-01

Cleft lip is a birth defect that results in deformity of the upper lip and nose. Its severity is widely variable and the results of treatment are influenced by the initial deformity. Objective assessment of severity would help to guide prognosis and treatment. However, most assessments are subjective. The purpose of this study is to develop and test quantitative computer-based methods of measuring cleft lip severity. In this paper, a grid-patch based measurement of symmetry is introduced, with which a computer program learns to rank the severity of cleft lip on 3D meshes of human infant faces. Three computer-based methods to define the midfacial reference plane were compared to two manual methods. Four different symmetry features were calculated based upon these reference planes, and evaluated. The result shows that the rankings predicted by the proposed features were highly correlated with the ranking orders provided by experts that were used as the ground truth.

A Case-Based Reasoning Method with Rank Aggregation

NASA Astrophysics Data System (ADS)

Sun, Jinhua; Du, Jiao; Hu, Jian

2018-03-01

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

Rank-preserving regression: a more robust rank regression model against outliers.

PubMed

Chen, Tian; Kowalski, Jeanne; Chen, Rui; Wu, Pan; Zhang, Hui; Feng, Changyong; Tu, Xin M

2016-08-30

Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Aggregate Interview Method of ranking orthopedic applicants predicts future performance.

PubMed

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 (P<.05). Residents ranked 1-5 scored higher on the OITE compared with those ranked 6-14 during postgraduate years 2 and 3 (P⩽.5). Graduates who had been ranked 1-5 had a 100% pass rate on the ABOS part 1 examination on the first attempt. The most favorably ranked residents performed at or above the level of other residents in the program; they did not score inferiorly on any measure. These results support the authors' method of ranking residents. The rigorous Aggregate Interview Method for ranking applicants consistently identified orthopedic 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.

Learning to Rank Figures within a Biomedical Article

PubMed Central

Liu, Feifan; Yu, Hong

2014-01-01

Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the “bag of figures” assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as “figure ranking”. Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1) First Author, (2) Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3) Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or out

Correlations between cephalometric and photographic measurements of facial attractiveness in Chinese and US patients after orthodontic treatment.

PubMed

Oh, Hee Soo; Korn, Edward L; Zhang, Xiaoyun; Liu, Yan; Xu, Tianmin; Boyd, Robert; Baumrind, Sheldon

2009-12-01

Orthodontists rely on esthetic judgments from facial photographs. Concordance between estimates of facial attractiveness made from lateral cephalograms and those made from clinical photographs has not been determined. We conducted a preliminary examination to correlate clinicians' rankings of facial attractiveness from standardized end-of-treatment facial photographs (Photo Attractiveness Rank) with cephalometric measurements of facial attractiveness made for the same subjects at the same time. Forty-five Chinese and US orthodontic clinicians ranked end-of-treatment photographs of separate samples of 45 US and 48 Chinese adolescent patients for facial attractiveness. Separately for each sample, the photographic rankings were correlated with the values of 21 conventional hard- and soft-tissue measures from lateral cephalograms taken at the same visits as the photographs. Among US patients, higher rank for facial attractiveness on the photographs was strongly associated with higher values for profile angle, chin prominence, lower lip prominence, and Z-angle, and also with lower values for angle of convexity, H-angle, and ANB. Among Chinese patients, higher rank for facial attractiveness on the photographs was strongly associated with higher values for Z-angle and chin prominence, and also with lower values for angle of convexity, H-angle, B-line to upper lip, and mandibular plane angle. Chinese patients whose %lower face height values approximated the ethnic "ideal" (54%) tended to rank higher for facial attractiveness than patients with either higher or lower values for %lower face height. The absolute values of the correlations for the 7 US measures noted above ranged from 0.41 to 0.59; those of the 7 Chinese measures ranged from 0.39 to 0.49.The P value of the least statistically significant of these 14 correlations was 0.006, unadjusted for multiple comparisons. On the other hand, many cephalometric measures believed by clinicians to be indicators of facial

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

PubMed

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

2017-08-18

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

Implicating Receptor Activator of NF-κB (RANK)/RANK Ligand Signalling in Microglial Responses to Toll-Like Receptor Stimuli

PubMed Central

Kichev, Anton; Eede, Pascale; Gressens, Pierre; Thornton, Claire; Hagberg, Henrik

2017-01-01

Inflammation in the perinatal brain caused by maternal or intrauterine fetal infection is now well established as an important contributor to the development of perinatal brain injury. Exposure to inflammatory products can impair perinatal brain development and act as a risk factor for neurological dysfunction, cognitive disorders, cerebral palsy, or preterm birth. Pre-exposure to inflammation significantly exacerbates brain injury caused by hypoxic/ischaemic insult. Tumour necrosis factor (TNF) is a family of cytokines largely involved in inflammation signalling. In our previous study, we identified the importance of TNF-related apoptosis-inducing ligand (TRAIL) signalling in the development of perinatal brain injury. We observed a significant increase in the expression levels of a soluble decoy receptor for TRAIL, osteoprotegerin (OPG). Besides TRAIL, OPG is able to bind the receptor activator of the NF-κB (RANK) ligand (RANKL) and inhibit its signalling. The function of the RANK/RANKL/OPG system in the brain has not come under much scrutiny. The aim of this research study was to elucidate the role of RANK, RANKL, and OPG in microglial responses to the proinflammatory stimuli lipopolysaccharide (LPS) and polyinosinic-polycytidylic acid (Poly I:C). Here, we show that RANK signalling is important for regulating the activation of the BV2 microglial cell line. We found that LPS treatment causes a significant decrease in the expression of RANK in the BV2 cell line while significantly increasing the expression of OPG, Toll-like receptor (TLR)3, and the adaptor proteins MyD88 and TRIF. We found that pretreatment of BV2 cells with RANKL for 24 h before the LPS or Poly I:C exposure decreases the expression of inflammatory markers such as inducible nitric oxide synthase and cyclooxygenase. This is accompanied by a decreased expression of the TLR adaptor proteins MyD88 and TRIF, which we observed after RANKL treatment. Similar results were obtained in our experiments with

Implicating Receptor Activator of NF-κB (RANK)/RANK Ligand Signalling in Microglial Responses to Toll-Like Receptor Stimuli.

PubMed

Kichev, Anton; Eede, Pascale; Gressens, Pierre; Thornton, Claire; Hagberg, Henrik

2017-01-01

Inflammation in the perinatal brain caused by maternal or intrauterine fetal infection is now well established as an important contributor to the development of perinatal brain injury. Exposure to inflammatory products can impair perinatal brain development and act as a risk factor for neurological dysfunction, cognitive disorders, cerebral palsy, or preterm birth. Pre-exposure to inflammation significantly exacerbates brain injury caused by hypoxic/ischaemic insult. Tumour necrosis factor (TNF) is a family of cytokines largely involved in inflammation signalling. In our previous study, we identified the importance of TNF-related apoptosis-inducing ligand (TRAIL) signalling in the development of perinatal brain injury. We observed a significant increase in the expression levels of a soluble decoy receptor for TRAIL, osteoprotegerin (OPG). Besides TRAIL, OPG is able to bind the receptor activator of the NF-κB (RANK) ligand (RANKL) and inhibit its signalling. The function of the RANK/RANKL/OPG system in the brain has not come under much scrutiny. The aim of this research study was to elucidate the role of RANK, RANKL, and OPG in microglial responses to the proinflammatory stimuli lipopolysaccharide (LPS) and polyinosinic-polycytidylic acid (Poly I:C). Here, we show that RANK signalling is important for regulating the activation of the BV2 microglial cell line. We found that LPS treatment causes a significant decrease in the expression of RANK in the BV2 cell line while significantly increasing the expression of OPG, Toll-like receptor (TLR)3, and the adaptor proteins MyD88 and TRIF. We found that pretreatment of BV2 cells with RANKL for 24 h before the LPS or Poly I:C exposure decreases the expression of inflammatory markers such as inducible nitric oxide synthase and cyclooxygenase. This is accompanied by a decreased expression of the TLR adaptor proteins MyD88 and TRIF, which we observed after RANKL treatment. Similar results were obtained in our experiments with

Sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants.

PubMed

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.

English Language Use at the Internationalised Universities of Northern Europe: Is There a Correlation between Englishisation and World Rank?

ERIC Educational Resources Information Center

Hultgren, Anna Kristina

2014-01-01

European universities have, since the late 1990s, undergone dramatic changes centred on internationalisation, harmonisation and competition. This paper is concerned with two specific consequences of these changes and their interrelationship: rankings and Englishisation, the latter defined as an increase in the use of English at universities of…

Ranking fluctuating asymmetry in a dot figure and the significant impact of imagining a face.

PubMed

Neby, Magne; Ivar, Folstad

2013-01-01

Fluctuating asymmetry and averageness is correlated with our perception of beauty in human faces. Yet, whether deviations of centrality in the positioning of the eyes, the nose, and the mouth have different effects on our perception of asymmetry in a holistic human face, is still uncertain. In this study we aimed to test the relative effect of decentralising the horizontal position of three sets of paired dots representing eyes, nostrils, or mouth from the vertical midline of ambiguous dot figures, vaguely resembling a face. The figures were ranked according to perceived asymmetry by human observers. When associating the figures with non-facial objects (eg a butterfly), none of the figures' rank distribution differed from each other. However, when observers imagined the figures to represent a human face, the figure with the decentralised pair of dots representing the nostrils was significantly ranked as more asymmetric than the other figures. This result provides indications that the brain may deal with information about facial asymmetry and averageness heavily depending on the centrality of the nasal region.

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

PubMed

Chen, Liang-Hsuan; Tu, Chien-Cheng

2014-08-01

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

Trend analysis of hydro-climatic variables in the north of Iran

NASA Astrophysics Data System (ADS)

Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.

2018-04-01

Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z < -1.96) and an upward trend in annual maximum daily precipitation. Annual and monthly mean flows for most of the months in the Neka basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value < 0.05). Correlation coefficients for Kendall, Spearman's rank and linear regression are 0.43, 0.61, and 0.67, respectively. The spatial presentation of the detected precipitation and streamflow trends showed a downward trend for the mean annual precipitation observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

International ranking systems for universities and institutions: a critical appraisal

PubMed Central

Ioannidis, John PA; Patsopoulos, Nikolaos A; Kavvoura, Fotini K; Tatsioni, Athina; Evangelou, Evangelos; Kouri, Ioanna; Contopoulos-Ioannidis, Despina G; Liberopoulos, George

2007-01-01

Background Ranking of universities and institutions has attracted wide attention recently. Several systems have been proposed that attempt to rank academic institutions worldwide. Methods We review the two most publicly visible ranking systems, the Shanghai Jiao Tong University 'Academic Ranking of World Universities' and the Times Higher Education Supplement 'World University Rankings' and also briefly review other ranking systems that use different criteria. We assess the construct validity for educational and research excellence and the measurement validity of each of the proposed ranking criteria, and try to identify generic challenges in international ranking of universities and institutions. Results None of the reviewed criteria for international ranking seems to have very good construct validity for both educational and research excellence, and most don't have very good construct validity even for just one of these two aspects of excellence. Measurement error for many items is also considerable or is not possible to determine due to lack of publication of the relevant data and methodology details. The concordance between the 2006 rankings by Shanghai and Times is modest at best, with only 133 universities shared in their top 200 lists. The examination of the existing international ranking systems suggests that generic challenges include adjustment for institutional size, definition of institutions, implications of average measurements of excellence versus measurements of extremes, adjustments for scientific field, time frame of measurement and allocation of credit for excellence. Conclusion Naïve lists of international institutional rankings that do not address these fundamental challenges with transparent methods are misleading and should be abandoned. We make some suggestions on how focused and standardized evaluations of excellence could be improved and placed in proper context. PMID:17961208

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

PubMed

Kruczek, Małgorzata; Zatorska, Magdalena

2008-07-05

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

SIMULTANEOUS MULTISLICE MAGNETIC RESONANCE FINGERPRINTING WITH LOW-RANK AND SUBSPACE MODELING

PubMed Central

Zhao, Bo; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A.; Wald, Lawrence L.; Setsompop, Kawin

2018-01-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T1, T2, and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3x speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice. PMID:29060594

Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling.

PubMed

Bo Zhao; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A; Wald, Lawrence L; Setsompop, Kawin

2017-07-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T 1 , T 2 , and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3× speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.

Order-disorder transition in conflicting dynamics leading to rank-frequency generalized beta distributions

NASA Astrophysics Data System (ADS)

Alvarez-Martinez, R.; Martinez-Mekler, G.; Cocho, G.

2011-01-01

The behavior of rank-ordered distributions of phenomena present in a variety of fields such as biology, sociology, linguistics, finance and geophysics has been a matter of intense research. Often power laws have been encountered; however, their validity tends to hold mainly for an intermediate range of rank values. In a recent publication (Martínez-Mekler et al., 2009 [7]), a generalization of the functional form of the beta distribution has been shown to give excellent fits for many systems of very diverse nature, valid for the whole range of rank values, regardless of whether or not a power law behavior has been previously suggested. Here we give some insight on the significance of the two free parameters which appear as exponents in the functional form, by looking into discrete probabilistic branching processes with conflicting dynamics. We analyze a variety of realizations of these so-called expansion-modification models first introduced by Wentian Li (1989) [10]. We focus our attention on an order-disorder transition we encounter as we vary the modification probability p. We characterize this transition by means of the fitting parameters. Our numerical studies show that one of the fitting exponents is related to the presence of long-range correlations exhibited by power spectrum scale invariance, while the other registers the effect of disordering elements leading to a breakdown of these properties. In the absence of long-range correlations, this parameter is sensitive to the occurrence of unlikely events. We also introduce an approximate calculation scheme that relates this dynamics to multinomial multiplicative processes. A better understanding through these models of the meaning of the generalized beta-fitting exponents may contribute to their potential for identifying and characterizing universality classes.

Comparison between a new computer program and the reference software for gray-scale median analysis of atherosclerotic carotid plaques.

PubMed

Casella, Ivan Benaduce; Fukushima, Rodrigo Bono; Marques, Anita Battistini de Azevedo; Cury, Marcus Vinícius Martins; Presti, Calógero

2015-03-01

To compare a new dedicated software program and Adobe Photoshop for gray-scale median (GSM) analysis of B-mode images of carotid plaques. A series of 42 carotid plaques generating ≥50% diameter stenosis was evaluated by a single observer. The best segment for visualization of internal carotid artery plaque was identified on a single longitudinal view and images were recorded in JPEG format. Plaque analysis was performed by both programs. After normalization of image intensity (blood = 0, adventitial layer = 190), histograms were obtained after manual delineation of plaque. Results were compared with nonparametric Wilcoxon signed rank test and Kendall tau-b correlation analysis. GSM ranged from 00 to 100 with Adobe Photoshop and from 00 to 96 with IMTPC, with a high grade of similarity between image pairs, and a highly significant correlation (R = 0.94, p < .0001). IMTPC software appears suitable for the GSM analysis of carotid plaques. © 2014 Wiley Periodicals, Inc.

REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

NASA Astrophysics Data System (ADS)

Rock, N. M. S.; Duffy, T. R.

REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.

Methods for trend analysis: Examples with problem/failure data

NASA Technical Reports Server (NTRS)

Church, Curtis K.

1989-01-01

Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.

Data-driven reconstruction of directed networks

NASA Astrophysics Data System (ADS)

Hempel, Sabrina; Koseska, Aneta; Nikoloski, Zoran

2013-06-01

We investigate the properties of a recently introduced asymmetric association measure, called inner composition alignment (IOTA), aimed at inferring regulatory links (couplings). We show that the measure can be used to determine the direction of coupling, detect superfluous links, and to account for autoregulation. In addition, the measure can be extended to infer the type of regulation (positive or negative). The capabilities of IOTA to correctly infer couplings together with their directionality are compared against Kendall's rank correlation for time series of different lengths, particularly focussing on biological examples. We demonstrate that an extended version of the measure, bidirectional inner composition alignment (biIOTA), increases the accuracy of the network reconstruction for short time series. Finally, we discuss the applicability of the measure to infer couplings in chaotic systems.

Male dominance rank, mating and reproductive success in captive bonobos (Pan paniscus).

PubMed

Marvan, R; Stevens, J M G; Roeder, A D; Mazura, I; Bruford, M W; de Ruiter, J R

2006-01-01

In the recent past, application of DNA genotyping techniques has enabled researchers to more accurately test relationships between dominance rank (DR), mating success (MS) and reproductive success (RS). Paternity studies often reveal that reproductive outcome does not always correlate with male DR and/or MS and thus open room for discussion and interpretation of alternative reproductive tactics of both sexes. In this study, we analysed male DR, MS and RS in a group of bonobos at Twycross Zoo (UK). Genetic relationships were determined using 8 tetrameric microsatellite loci. Despite clear and asymmetric dominance relationships, analysed using normalised David's scores based on a dyadic index of dominance among the group's 3 mature males, we found that the most dominant male did not sire the most offspring. In fact, both infants conceived during the observation period were found to be sired by the lower-ranking males. Although the alpha male had almost exclusive mating access to one of the females during the time she was showing a maximal anogenital swelling, her infant was sired by the lowest-ranking male who mostly mated with her when outside the maximal swelling period. This result suggests that either sperm competition operates and/or ovulation is decoupled from the phase of maximal anogenital swelling which could allow greater female choice. Copyright 2006 S. Karger AG, Basel.

Learning to rank-based gene summary extraction.

PubMed

Shang, Yue; Hao, Huihui; Wu, Jiajin; Lin, Hongfei

2014-01-01

In recent years, the biomedical literature has been growing rapidly. These articles provide a large amount of information about proteins, genes and their interactions. Reading such a huge amount of literature is a tedious task for researchers to gain knowledge about a gene. As a result, it is significant for biomedical researchers to have a quick understanding of the query concept by integrating its relevant resources. In the task of gene summary generation, we regard automatic summary as a ranking problem and apply the method of learning to rank to automatically solve this problem. This paper uses three features as a basis for sentence selection: gene ontology relevance, topic relevance and TextRank. From there, we obtain the feature weight vector using the learning to rank algorithm and predict the scores of candidate summary sentences and obtain top sentences to generate the summary. ROUGE (a toolkit for summarization of automatic evaluation) was used to evaluate the summarization result and the experimental results showed that our method outperforms the baseline techniques. According to the experimental result, the combination of three features can improve the performance of summary. The application of learning to rank can facilitate the further expansion of features for measuring the significance of sentences.

World University Rankings: Take with a Large Pinch of Salt

ERIC Educational Resources Information Center

Cheng, Soh Kay

2011-01-01

Equating the unequal is misleading, and this happens consistently in comparing rankings from different university ranking systems, as the NUT saga shows. This article illustrates the problem by analyzing the 2011 rankings of the top 100 universities in the AWUR, QSWUR and THEWUR ranking results. It also discusses the reasons why the rankings…

On Classification of Modular Categories by Rank: Table A.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruillard, Paul; Ng, Siu-Hung; Rowell, Eric C.

2016-04-10

The feasibility of a classification-by-rank program for modular categories follows from the Rank-Finiteness Theorem. We develop arithmetic, representation theoretic and algebraic methods for classifying modular categories by rank. As an application, we determine all possible fusion rules for all rank=5 modular categories and describe the corresponding monoidal equivalence classes.

Low-rank structure learning via nonconvex heuristic recovery.

PubMed

Deng, Yue; Dai, Qionghai; Liu, Risheng; Zhang, Zengke; Hu, Sanqing

2013-03-01

In this paper, we propose a nonconvex framework to learn the essential low-rank structure from corrupted data. Different from traditional approaches, which directly utilizes convex norms to measure the sparseness, our method introduces more reasonable nonconvex measurements to enhance the sparsity in both the intrinsic low-rank structure and the sparse corruptions. We will, respectively, introduce how to combine the widely used ℓp norm (0 < p < 1) and log-sum term into the framework of low-rank structure learning. Although the proposed optimization is no longer convex, it still can be effectively solved by a majorization-minimization (MM)-type algorithm, with which the nonconvex objective function is iteratively replaced by its convex surrogate and the nonconvex problem finally falls into the general framework of reweighed approaches. We prove that the MM-type algorithm can converge to a stationary point after successive iterations. The proposed model is applied to solve two typical problems: robust principal component analysis and low-rank representation. Experimental results on low-rank structure learning demonstrate that our nonconvex heuristic methods, especially the log-sum heuristic recovery algorithm, generally perform much better than the convex-norm-based method (0 < p < 1) for both data with higher rank and with denser corruptions.

Low rank magnetic resonance fingerprinting.

PubMed

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

2016-08-01

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

The Rankings of Marketing Programs in China.

ERIC Educational Resources Information Center

Siu, Wai-sum

1996-01-01

Nineteen marketing faculty and administrators in China ranked 10 universities offering business administration education and indicated their criteria. Results of the rankings and evaluative criteria are presented, and implications for marketing education in China discussed. It was found that most respondents were more concerned about input…

Rankings in Institutional Strategies and Processes: Impact or Illusion?

ERIC Educational Resources Information Center

Hazelkorn, Ellen; Loukkola, Tia; Zhang, Thérèse

2014-01-01

The "Rankings in Institutional Strategies and Processes" (RISP) project is the first pan-European study of the impact and influence of rankings on European higher education institutions. The project has sought to build understanding of how rankings impact and influence the development of institutional strategies and processes and its…

Revisiting the Relationship between Institutional Rank and Student Engagement

ERIC Educational Resources Information Center

Zilvinskis, John; Louis Rocconi

2018-01-01

College rankings dominate the conversation regarding quality in postsecondary education. However, the criteria used to rank institutions often have nothing to do with the quality of education students receive. A decade ago, Pike (2004) demonstrated that institutional rank had little association with student involvement in educational activities.…

Bayesian Inference of Natural Rankings in Incomplete Competition Networks

NASA Astrophysics Data System (ADS)

Park, Juyong; Yook, Soon-Hyung

2014-08-01

Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest - essential in determining reward and penalty - is frequently an ambiguous task due to the incomplete (partially filled) nature of competition networks. Here we introduce the ``Natural Ranking,'' an unambiguous ranking method applicable to a round robin tournament, and formulate an analytical model based on the Bayesian formula for inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in resolving important issues of ranking by applying it to real-world competition networks.

Academic Ranking--From Its Genesis to Its International Expansion

ERIC Educational Resources Information Center

Vieira, Rosilene C.; Lima, Manolita C.

2015-01-01

Given the visibility and popularity of rankings that encompass the measurement of quality of post-graduate courses, for instance, the MBA (Master of Business Administration) or graduate studies program (MSc and PhD) as do global academic rankings--Academic Ranking of World Universities-ARWU, Times Higher/Thomson Reuters World University Ranking…

Academic Ranking of World Universities by Broad Subject Fields

ERIC Educational Resources Information Center

Cheng, Ying; Liu, Nian Cai

2007-01-01

Upon numerous requests to provide ranking of world universities by broad subject fields/schools/colleges and by subject fields/programs/departments, the authors present the ranking methodologies and problems that arose from the research by the Institute of Higher Education, Shanghai Jiao Tong University on the Academic Ranking of World…

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

PubMed Central

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

2017-01-01

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

Rank on emotional intelligence, unlearning and self-leadership.

PubMed

Kramer, Robert

2012-12-01

Propelled from the inner circle after publishing The Trauma of Birth (1924), Otto Rank jettisoned Freud's science of knowing because it denied the intelligence of the emotions. Transforming therapy from knowing to being-in-relationship, Rank invented modern object-relations theory, which advocates continual learning, unlearning and relearning: that is, cutting the chains that bind us to the past. Separating, no matter how anxiety-provoking, from outworn phases of life, including previously taken-for-granted ideologies and internalized others, is essential for self-leadership. In 1926, Rank coined the terms "here-and-now" and "pre-Oedipal." By 1926, Rank had formulated a model of "creative willing"-self-leadership infused with the intelligence of the emotions-as the optimal way of being-in-relationship with others.

Extreme learning machine for ranking: generalization analysis and applications.

PubMed

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.

World University Rankings: Ambiguous Signals. Go8 Backgrounder 30

ERIC Educational Resources Information Center

Group of Eight (NJ1), 2012

2012-01-01

The current main world university rankings broadly group the leading research universities of nations. Australia's Go8 universities are generally within the top 250 ranked universities, with several institutions in the top 50-100 on some measures. This recognition is commendable, however imperfect the individual rankings may be. Use is made of…

A Rational Method for Ranking Engineering Programs.

ERIC Educational Resources Information Center

Glower, Donald D.

1980-01-01

Compares two methods for ranking academic programs, the opinion poll v examination of career successes of the program's alumni. For the latter, "Who's Who in Engineering" and levels of research funding provided data. Tables display resulting data and compare rankings by the two methods for chemical engineering and civil engineering. (CS)

Mining Feedback in Ranking and Recommendation Systems

ERIC Educational Resources Information Center

Zhuang, Ziming

2009-01-01

The amount of online information has grown exponentially over the past few decades, and users become more and more dependent on ranking and recommendation systems to address their information seeking needs. The advance in information technologies has enabled users to provide feedback on the utilities of the underlying ranking and recommendation…

Comparative Case Studies on Indonesian Higher Education Rankings

NASA Astrophysics Data System (ADS)

Kurniasih, Nuning; Hasyim, C.; Wulandari, A.; Setiawan, M. I.; Ahmar, A. S.

2018-01-01

The quality of the higher education is the result of a continuous process. There are many indicators that can be used to assess the quality of a higher education. The existence of different indicators makes the different result of university rankings. This research aims to find variables that can connect ranking indicators that are used by Indonesian Ministry of Research, Technology, and Higher Education with indicators that are used by international rankings by taking two kind of ranking systems i.e. Webometrics and 4icu. This research uses qualitative research method with comparative case studies approach. The result of the research shows that to bridge the indicators that are used by Indonesian Ministry or Research, Technology, and Higher Education with web-based ranking system like Webometrics and 4icu so that the Indonesian higher education institutions need to open access towards either scientific or non-scientific that are publicly used into web-based environment. One of the strategies that can be used to improve the openness and access towards scientific work of a university is by involving in open science and collaboration.

Bayesian Inference of Natural Rankings in Incomplete Competition Networks

PubMed Central

Park, Juyong; Yook, Soon-Hyung

2014-01-01

Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest – essential in determining reward and penalty – is frequently an ambiguous task due to the incomplete (partially filled) nature of competition networks. Here we introduce the “Natural Ranking,” an unambiguous ranking method applicable to a round robin tournament, and formulate an analytical model based on the Bayesian formula for inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in resolving important issues of ranking by applying it to real-world competition networks. PMID:25163528

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

PubMed Central

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

2016-01-01

Motivation: 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. Methods: 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. Results: 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. Availability: http://datamining-iip.fudan.edu.cn/service/DrugE-Rank Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307615

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

PubMed

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.

Tutorial: Calculating Percentile Rank and Percentile Norms Using SPSS

ERIC Educational Resources Information Center

Baumgartner, Ted A.

2009-01-01

Practitioners can benefit from using norms, but they often have to develop their own percentile rank and percentile norms. This article is a tutorial on how to quickly and easily calculate percentile rank and percentile norms using SPSS, and this information is presented for a data set. Some issues in calculating percentile rank and percentile…

Money and happiness: rank of income, not income, affects life satisfaction.

PubMed

Boyce, Christopher J; Brown, Gordon D A; Moore, Simon C

2010-04-01

Does money buy happiness, or does happiness come indirectly from the higher rank in society that money brings? We tested a rank-income hypothesis, according to which people gain utility from the ranked position of their income within a comparison group. The rank hypothesis contrasts with traditional reference-income hypotheses, which suggest that utility from income depends on comparison to a social reference-group norm. We found that the ranked position of an individual's income predicts general life satisfaction, whereas absolute income and reference income have no effect. Furthermore, individuals weight upward comparisons more heavily than downward comparisons. According to the rank hypothesis, income and utility are not directly linked: Increasing an individual's income will increase his or her utility only if ranked position also increases and will necessarily reduce the utility of others who will lose rank.

Rank Determination of Mental Functions by 1D Wavelets and Partial Correlation.

PubMed

Karaca, Y; Aslan, Z; Cattani, C; Galletta, D; Zhang, Y

2017-01-01

The main aim of this paper is to classify mental functions by the Wechsler Adult Intelligence Scale-Revised tests with a mixed method based on wavelets and partial correlation. The Wechsler Adult Intelligence Scale-Revised is a widely used test designed and applied for the classification of the adults cognitive skills in a comprehensive manner. In this paper, many different intellectual profiles have been taken into consideration to measure the relationship between the mental functioning and psychological disorder. We propose a method based on wavelets and correlation analysis for classifying mental functioning, by the analysis of some selected parameters measured by the Wechsler Adult Intelligence Scale-Revised tests. In particular, 1-D Continuous Wavelet Analysis, 1-D Wavelet Coefficient Method and Partial Correlation Method have been analyzed on some Wechsler Adult Intelligence Scale-Revised parameters such as School Education, Gender, Age, Performance Information Verbal and Full Scale Intelligence Quotient. In particular, we will show that gender variable has a negative but a significant role on age and Performance Information Verbal factors. The age parameters also has a significant relation in its role on Performance Information Verbal and Full Scale Intelligence Quotient change.

Male urine signals social rank in the Mozambique tilapia (Oreochromis mossambicus)

PubMed Central

Barata, Eduardo N; Hubbard, Peter C; Almeida, Olinda G; Miranda, António; Canário, Adelino VM

2007-01-01

Background The urine of freshwater fish species investigated so far acts as a vehicle for reproductive pheromones affecting the behaviour and physiology of the opposite sex. However, the role of urinary pheromones in intra-sexual competition has received less attention. This is particularly relevant in lek-breeding species, such as the Mozambique tilapia (Oreochromis mossambicus), where males establish dominance hierarchies and there is the possibility for chemical communication in the modulation of aggression among males. To investigate whether males use urine during aggressive interactions, we measured urination frequency of dye-injected males during paired interactions between size-matched males. Furthermore, we assessed urinary volume stored in the bladder of males in a stable social hierarchy and the olfactory potency of their urine by recording of the electro-olfactogram. Results Males released urine in pulses of short duration (about one second) and markedly increased urination frequency during aggressive behaviour, but did not release urine whilst submissive. In the stable hierarchy, subordinate males stored less urine than males of higher social rank; the olfactory potency of the urine was positively correlated with the rank of the male donor. Conclusion Dominant males store urine and use it as a vehicle for odorants actively released during aggressive disputes. The olfactory potency of the urine is positively correlated with the social status of the male. We suggest that males actively advertise their dominant status through urinary odorants which may act as a 'dominance' pheromone to modulate aggression in rivals, thereby contributing to social stability within the lek. PMID:18076759

University Rankings 2.0: New Frontiers in Institutional Comparisons

ERIC Educational Resources Information Center

Usher, Alex

2009-01-01

The number of university rankings systems in use around the world has increased dramatically over the last decade. As they have spread, they have mutated; no longer are ranking systems simply clones of the original ranking systems such as "US News" and "World Report". A number of different types of "mutation" have occurred, so that there are now…

Gender Differences in Publication Productivity, Academic Rank, and Career Duration Among U.S. Academic Gastroenterology Faculty.

PubMed

Diamond, Sarah J; Thomas, Charles R; Desai, Sima; Holliday, Emma B; Jagsi, Reshma; Schmitt, Colleen; Enestvedt, Brintha K

2016-08-01

Female representation in academic medicine is increasing without proportional increases in female representation at senior ranks. The purpose of this study is to describe the gender representation in academic gastroenterology (GI) and compare publication productivity, academic rank, and career duration between male and female gastroenterologists. In 2014, the authors collected data including number of publications, career duration, h-index, and m-index for faculty members at 114 U.S. academic GI programs. Of 2,440 academic faculty, 1,859 (76%) were men and 581 (24%) were women. Half (50%) of men held senior faculty position compared with 29% of women (P < .001). Compared with female faculty, male faculty had significantly (P < .001) longer careers (20 vs. 11 years), more publications (median 24 [0-949] vs. 9 [0-438]), and higher h-indices (8 vs. 4). Higher h-index correlated with higher academic rank (P < .001). The authors detected no difference in the h-index between men and women at the same rank for professor, associate professor, and instructor, nor any difference in the m-index between men and women (0.5 vs. 0.46, respectively, P = .214). A gender gap exists in the number and proportion of women in academic GI; however, after correcting for career duration, productivity measures that consider quantity and impact are similar for male and female faculty. Women holding senior faculty positions are equally productive as their male counterparts. Early and continued career mentorship will likely lead to continued increases in the rise of women in academic rank.

Maximising information recovery from rank-order codes

NASA Astrophysics Data System (ADS)

Sen, B.; Furber, S.

2007-04-01

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

Embedded feature ranking for ensemble MLP classifiers.

PubMed

Windeatt, Terry; Duangsoithong, Rakkrit; Smith, Raymond

2011-06-01

A feature ranking scheme for multilayer perceptron (MLP) ensembles is proposed, along with a stopping criterion based upon the out-of-bootstrap estimate. To solve multi-class problems feature ranking is combined with modified error-correcting output coding. Experimental results on benchmark data demonstrate the versatility of the MLP base classifier in removing irrelevant features.

A Ranking Method for Evaluating Constructed Responses

ERIC Educational Resources Information Center

Attali, Yigal

2014-01-01

This article presents a comparative judgment approach for holistically scored constructed response tasks. In this approach, the grader rank orders (rather than rate) the quality of a small set of responses. A prior automated evaluation of responses guides both set formation and scaling of rankings. Sets are formed to have similar prior scores and…

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits.

PubMed

Fu, Liya; Wang, You-Gan

2011-02-15

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which clearly demonstrates the advantages of the rank regression models.

Adjoints and Low-rank Covariance Representation

NASA Technical Reports Server (NTRS)

Tippett, Michael K.; Cohn, Stephen E.

2000-01-01

Quantitative measures of the uncertainty of Earth System estimates can be as important as the estimates themselves. Second moments of estimation errors are described by the covariance matrix, whose direct calculation is impractical when the number of degrees of freedom of the system state is large. Ensemble and reduced-state approaches to prediction and data assimilation replace full estimation error covariance matrices by low-rank approximations. The appropriateness of such approximations depends on the spectrum of the full error covariance matrix, whose calculation is also often impractical. Here we examine the situation where the error covariance is a linear transformation of a forcing error covariance. We use operator norms and adjoints to relate the appropriateness of low-rank representations to the conditioning of this transformation. The analysis is used to investigate low-rank representations of the steady-state response to random forcing of an idealized discrete-time dynamical system.

Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

PubMed

Ma, Chuang; Wang, Xiangfeng

2012-09-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.

An epidermal equivalent assay for identification and ranking potency of contact sensitizers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gibbs, Susan, E-mail: S.Gibbs@VUMC.nl; Corsini, Emanuela; Spiekstra, Sander W.

2013-10-15

The purpose of this study was to explore the possibility of combining the epidermal equivalent (EE) potency assay with the assay which assesses release of interleukin-18 (IL-18) to provide a single test for identification and classification of skin sensitizing chemicals, including chemicals of low water solubility or stability. A protocol was developed using different 3D-epidermal models including in house VUMC model, epiCS® (previously EST1000™), MatTek EpiDerm™ and SkinEthic™ RHE and also the impact of different vehicles (acetone:olive oil 4:1, 1% DMSO, ethanol, water) was investigated. Following topical exposure for 24 h to 17 contact allergens and 13 non-sensitizers a robustmore » increase in IL-18 release was observed only after exposure to contact allergens. A putative prediction model is proposed from data obtained from two laboratories yielding 95% accuracy. Correlating the in vitro EE sensitizer potency data, which assesses the chemical concentration which results in 50% cytotoxicity (EE-EC{sub 50}) with human and animal data showed a superior correlation with human DSA{sub 05} (μg/cm{sup 2}) data (Spearman r = 0.8500; P value (two-tailed) = 0.0061) compared to LLNA data (Spearman r = 0.5968; P value (two-tailed) = 0.0542). DSA{sub 05} = induction dose per skin area that produces a positive response in 5% of the tested population Also a good correlation was observed for release of IL-18 (SI-2) into culture supernatants with human DSA{sub 05} data (Spearman r = 0.8333; P value (two-tailed) = 0.0154). This easily transferable human in vitro assay appears to be very promising, but additional testing of a larger chemical set with the different EE models is required to fully evaluate the utility of this assay and to establish a definitive prediction model. - Highlights: • A potential epidermal equivalent assay to label and classify sensitizers • Il-18 release distinguishes sensitizers from non sensitizers • IL-18 release can rank sensitizer

Reduction from cost-sensitive ordinal ranking to weighted binary classification.

PubMed

Lin, Hsuan-Tien; Li, Ling

2012-05-01

We present a reduction framework from ordinal ranking to binary classification. The framework consists of three steps: extracting extended examples from the original examples, learning a binary classifier on the extended examples with any binary classification algorithm, and constructing a ranker from the binary classifier. Based on the framework, we show that a weighted 0/1 loss of the binary classifier upper-bounds the mislabeling cost of the ranker, both error-wise and regret-wise. Our framework allows not only the design of good ordinal ranking algorithms based on well-tuned binary classification approaches, but also the derivation of new generalization bounds for ordinal ranking from known bounds for binary classification. In addition, our framework unifies many existing ordinal ranking algorithms, such as perceptron ranking and support vector ordinal regression. When compared empirically on benchmark data sets, some of our newly designed algorithms enjoy advantages in terms of both training speed and generalization performance over existing algorithms. In addition, the newly designed algorithms lead to better cost-sensitive ordinal ranking performance, as well as improved listwise ranking performance.

Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.

PubMed

Eom, Young-Ho; Shepelyansky, Dima L

2013-01-01

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

Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles

PubMed Central

Eom, Young-Ho; Shepelyansky, Dima L.

2013-01-01

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

Likelihoods for fixed rank nomination networks

PubMed Central

HOFF, PETER; FOSDICK, BAILEY; VOLFOVSKY, ALEX; STOVEL, KATHERINE

2014-01-01

Many studies that gather social network data use survey methods that lead to censored, missing, or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study participants to nominate and rank at most a small number of contacts or friends, leaving the existence of other relations uncertain. However, most statistical models are formulated in terms of completely observed binary networks. Statistical analyses of FRN data with such models ignore the censored and ranked nature of the data and could potentially result in misleading statistical inference. To investigate this possibility, we compare Bayesian parameter estimates obtained from a likelihood for complete binary networks with those obtained from likelihoods that are derived from the FRN scheme, and therefore accommodate the ranked and censored nature of the data. We show analytically and via simulation that the binary likelihood can provide misleading inference, particularly for certain model parameters that relate network ties to characteristics of individuals and pairs of individuals. We also compare these different likelihoods in a data analysis of several adolescent social networks. For some of these networks, the parameter estimates from the binary and FRN likelihoods lead to different conclusions, indicating the importance of analyzing FRN data with a method that accounts for the FRN survey design. PMID:25110586

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

PubMed

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

2018-01-01

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

Rank-frequency relation for Chinese characters

NASA Astrophysics Data System (ADS)

Deng, Weibing; Allahverdyan, Armen E.; Li, Bo; Wang, Qiuping A.

2014-02-01

We show that the Zipf's law for Chinese characters perfectly holds for sufficiently short texts (few thousand different characters). The scenario of its validity is similar to the Zipf's law for words in short English texts. For long Chinese texts (or for mixtures of short Chinese texts), rank-frequency relations for Chinese characters display a two-layer, hierarchic structure that combines a Zipfian power-law regime for frequent characters (first layer) with an exponential-like regime for less frequent characters (second layer). For these two layers we provide different (though related) theoretical descriptions that include the range of low-frequency characters (hapax legomena). We suggest that this hierarchic structure of the rank-frequency relation connects to semantic features of Chinese characters (number of different meanings and homographies). The comparative analysis of rank-frequency relations for Chinese characters versus English words illustrates the extent to which the characters play for Chinese writers the same role as the words for those writing within alphabetical systems.

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

PubMed

Reid, Machar; Morris, Craig

2013-01-01

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

Determining hospital performance based on rank ordering: is it appropriate?

PubMed

Anderson, Judy; Hackman, Mark; Burnich, Jeff; Gurgiolo, Thomas R

2007-01-01

An increasing number of "pay for performance" initiatives for hospitals and physicians ascribe performance by ranking hospitals or physicians on quality of care measures. Payment is subsequently based on where a hospital or physician ranks among peers. This study examines the variability of ranking hospitals on quality of care measures and its impact on comparing hospital performance. Variability in the ranks of 3 quality of care measures was examined: discharge instruction for congestive heart failure, use of beta-blockers at discharge for heart attack, and timing of initial antibiotic therapy within 4 hours of admission to the hospital for pneumonia. The data are available on the Centers for Medicare and Medicaid Services Web site as part of the Hospital Quality Alliance project. We found that considerable uncertainty exists in ranking of hospitals on these measures, which calls into question the use of rank ordering as a determinant of performance.

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

NASA Astrophysics Data System (ADS)

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

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

Comparison of two anaerobic water polo-specific tests with the Wingate test.

PubMed

Bampouras, Theodoros M; Marrin, Kelly

2009-01-01

The purpose of the current study was to compare 2 water polo-specific tests-the 14 x 25-m swims (SWIM) and the 30-second crossbar jumps (30CJ)-with a laboratory-based test of anaerobic power, the Wingate Anaerobic Test (WAnT). Thirteen elite women's water polo players (mean +/- SD: age 22.0 +/- 4.4 years, height 168.7 +/- 7.9 cm, body mass 65.9 +/- 6.1 kg, body fat 23.6 +/- 3.5 %, maximum oxygen uptake 51.4 +/- 4.5 mlxkgxmin) participated in the study. The SWIM involved 14 repeated "all-out" sprints every 30 seconds. Swimming time was recorded, and sprint velocity, mean velocity (Vmean), and the gradient of the linear regression equation (GRADIENT) were calculated. The 30CJ involved repeated in-water water polo jumps and touching the goal crossbar with both hands. The number of touches in 30 seconds was recorded. Additionally, the subjects completed a 30-second WAnT, and mean power (Mp) and fatigue index (FI) were calculated. Kendall tau (tau) rank correlation was used to examine for correlation between ranks. Significance level was set at p correlation was found between any of the measures of the WAnT and the 2 sport-specific tests. It was suggested that the WAnT may not be an appropriate evaluation tool for anaerobic power assessment of water polo players, stressing the importance of sport-specific tests.

United3D: a protein model quality assessment program that uses two consensus based methods.

PubMed

Terashi, Genki; Oosawa, Makoto; Nakamura, Yuuki; Kanou, Kazuhiko; Takeda-Shitaka, Mayuko

2012-01-01

In protein structure prediction, such as template-based modeling and free modeling (ab initio modeling), the step that assesses the quality of protein models is very important. We have developed a model quality assessment (QA) program United3D that uses an optimized clustering method and a simple Cα atom contact-based potential. United3D automatically estimates the quality scores (Qscore) of predicted protein models that are highly correlated with the actual quality (GDT_TS). The performance of United3D was tested in the ninth Critical Assessment of protein Structure Prediction (CASP9) experiment. In CASP9, United3D showed the lowest average loss of GDT_TS (5.3) among the QA methods participated in CASP9. This result indicates that the performance of United3D to identify the high quality models from the models predicted by CASP9 servers on 116 targets was best among the QA methods that were tested in CASP9. United3D also produced high average Pearson correlation coefficients (0.93) and acceptable Kendall rank correlation coefficients (0.68) between the Qscore and GDT_TS. This performance was competitive with the other top ranked QA methods that were tested in CASP9. These results indicate that United3D is a useful tool for selecting high quality models from many candidate model structures provided by various modeling methods. United3D will improve the accuracy of protein structure prediction.

Rank-frequency distributions of Romanian words

NASA Astrophysics Data System (ADS)

Cocioceanu, Adrian; Raportaru, Carina Mihaela; Nicolin, Alexandru I.; Jakimovski, Dragan

2017-12-01

The calibration of voice biometrics solutions requires detailed analyses of spoken texts and in this context we investigate by computational means the rank-frequency distributions of Romanian words and word series to determine the most common words and word series of the language. To this end, we have constructed a corpus of approximately 2.5 million words and then determined that the rank-frequency distributions of the Romanian words, as well as series of two, and three subsequent words, obey the celebrated Zipf law.

SRS: Site ranking system for hazardous chemical and radioactive waste

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

1988-05-01

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

RANKL/RANK/OPG cytokine receptor system: mRNA expression pattern in BPH, primary and metastatic prostate cancer disease.

PubMed

Christoph, Frank; König, Frank; Lebentrau, Steffen; Jandrig, Burkhard; Krause, Hans; Strenziok, Romy; Schostak, Martin

2018-02-01

The cytokine system RANKL (receptor activator of NF-κB ligand), its receptor RANK and the antagonist OPG (osteoprotegerin) play a critical role in bone turnover. Our investigation was conducted to describe the gene expression at primary tumour site in prostate cancer patients and correlate the results with Gleason Score and PSA level. Seventy-one samples were obtained from prostate cancer patients at the time of radical prostatectomy and palliative prostate resection (n = 71). Patients with benign prostate hyperplasia served as controls (n = 60). We performed real-time RT-PCR after microdissection of the samples. The mRNA expression of RANK was highest in tumour tissue from patients with bone metastases (p < 0.001) as compared to BPH or locally confined tumours, also shown in clinical subgroups distinguished by Gleason Score (< 7 or ≥ 7, p = 0.028) or PSA level (< 10 or ≥ 10 µg/l, p = 0.004). RANKL and OPG mRNA expression was higher in tumour tissue from patients with metastatic compared to local disease. The RANKL/OPG ratio was low in normal prostate tissue and high tumours with bone metastases (p < 0.05). Expression of all three cytokines was high in BPH tissue but did not exceed as much as in the tumour tissue. We demonstrated that RANK, RANKL and OPG are directly expressed by prostate cancer cells at the primary tumour site and showed a clear correlation with Gleason Score, serum PSA level and advanced disease. In BPH, mRNA expression is also detectable, but RANK expression does not exceed as much as compared to tumour tissue.

AGU journals continue to rank highly in Impact Factors

NASA Astrophysics Data System (ADS)

Sears, Jon; Warner, Mary

2012-07-01

AGU journals continue to rank highly in the 2011 Journal Citation Reports (JCR), which was released by Thomson Reuters on 28 June. The impact factor of several AGU journals increased significantly, continuing their trend over the previous 5 years, while others remained consistent with the previous year's ranking. Paleoceanography is an outstanding performer in both the Paleontology and Oceanography categories. Since 1995, Paleoceanography has been the top-ranked journal in the Paleontology category (of 49 titles in 2011), with an Impact Factor of 3.357. In the Oceanography group (59 journals total), Paleoceanography ranks third in Impact Factor. Reviews of Geophysics, with an Impact Factor of 12.364 (an increase of 2.826 from the prior year's score of 9.538), ranks second in Geochemistry and Geophysics out of a total of 77 journals in this cohort. Water Resources Research comes in at second place in the Limnology group, with 19 titles, and third place in the Water Resources group, which has a cohort of 78 titles.

Discriminative Multi-View Interactive Image Re-Ranking.

PubMed

Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

2017-07-01

Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

Improving the Incoherence of a Learned Dictionary via Rank Shrinkage.

PubMed

Ubaru, Shashanka; Seghouane, Abd-Krim; Saad, Yousef

2017-01-01

This letter considers the problem of dictionary learning for sparse signal representation whose atoms have low mutual coherence. To learn such dictionaries, at each step, we first update the dictionary using the method of optimal directions (MOD) and then apply a dictionary rank shrinkage step to decrease its mutual coherence. In the rank shrinkage step, we first compute a rank 1 decomposition of the column-normalized least squares estimate of the dictionary obtained from the MOD step. We then shrink the rank of this learned dictionary by transforming the problem of reducing the rank to a nonnegative garrotte estimation problem and solving it using a path-wise coordinate descent approach. We establish theoretical results that show that the rank shrinkage step included will reduce the coherence of the dictionary, which is further validated by experimental results. Numerical experiments illustrating the performance of the proposed algorithm in comparison to various other well-known dictionary learning algorithms are also presented.

Using Concept Relations to Improve Ranking in Information Retrieval

PubMed Central

Price, Susan L.; Delcambre, Lois M.

2005-01-01

Despite improved search engine technology, most searches return numerous documents not directly related to the query. This problem is mitigated if relevant documents appear high on a ranked list of search results. We propose that some queries and the underlying information needs can be modeled as relationships between concepts (relations), and we match relations in queries to relations in documents to try to improve ranking of search results. We investigate four techniques to identify two relationships important in medicine, causes and treats, to improve the ranking of medical text documents relevant to clinical questions about causation and treatment. Preliminary results suggest that identifying relation instances can improve the ranking of search results. PMID:16779114

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

PubMed

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

Connectivity ranking of heterogeneous random conductivity models

NASA Astrophysics Data System (ADS)

Rizzo, C. B.; de Barros, F.

2017-12-01

To overcome the challenges associated with hydrogeological data scarcity, the hydraulic conductivity (K) field is often represented by a spatial random process. The state-of-the-art provides several methods to generate 2D or 3D random K-fields, such as the classic multi-Gaussian fields or non-Gaussian fields, training image-based fields and object-based fields. We provide a systematic comparison of these models based on their connectivity. We use the minimum hydraulic resistance as a connectivity measure, which it has been found to be strictly correlated with early time arrival of dissolved contaminants. A computationally efficient graph-based algorithm is employed, allowing a stochastic treatment of the minimum hydraulic resistance through a Monte-Carlo approach and therefore enabling the computation of its uncertainty. The results show the impact of geostatistical parameters on the connectivity for each group of random fields, being able to rank the fields according to their minimum hydraulic resistance.

Social brains and divides: the interplay between social dominance orientation and the neural sensitivity to hierarchical ranks

PubMed Central

Ligneul, Romain; Girard, Romuald; Dreher, Jean-Claude

2017-01-01

Ubiquitous in the animal kingdom, dominance hierarchies emerge through social competition and underlie the control of resources. Confronting the disruptive influence of socioeconomic inequalities, human populations tend to split into groups who legitimize existing dominance hierarchies and groups who condemn them. Here, we hypothesized that variations in the neural sensitivity to dominance ranks partly underpins this ideological split, as measured by the social dominance orientation scale (SDO). Following a competitive task used to induce dominance representations about three opponents (superior, equal and inferior), subjects were passively presented the faces of these opponents while undergoing fMRI. Analyses demonstrated that two key brain regions, the superior temporal sulcus (STS) and anterior dorsolateral prefrontal cortex (aDLPFC) were sensitive to social ranks. Confirming our hypothesis, the sensitivity of the right aDLPFC to social ranks correlated positively with the SDO scale, which is known to predict behaviors and political attitudes associated with the legitimization of dominance hierarchies. This study opens new perspectives for the neurosciences of political orientation and social dominance. PMID:28378784

The Distribution of the Sum of Signed Ranks

ERIC Educational Resources Information Center

Albright, Brian

2012-01-01

We describe the calculation of the distribution of the sum of signed ranks and develop an exact recursive algorithm for the distribution as well as an approximation of the distribution using the normal. The results have applications to the non-parametric Wilcoxon signed-rank test.

A cautionary note on the rank product statistic.

PubMed

Koziol, James A

2016-06-01

The rank product method introduced by Breitling R et al. [2004, FEBS Letters 573, 83-92] has rapidly generated popularity in practical settings, in particular, detecting differential expression of genes in microarray experiments. The purpose of this note is to point out a particular property of the rank product method, namely, its differential sensitivity to over- and underexpression. It turns out that overexpression is less likely to be detected than underexpression with the rank product statistic. We have conducted both empirical and exact power studies that demonstrate this phenomenon, and summarize these findings in this note. © 2016 Federation of European Biochemical Societies.

Biomarkers of Fatigue: Ranking Mental Fatigue Susceptibility

DTIC Science & Technology

2010-12-10

expected declines in performance during the 36-hour, 15-minute period of sleep deprivation without caffeine. The simple change from baseline results...rankings for fatigue resistance were then determined via a percent- change rule similar to that used in Chaiken, Harville, Harrison, Fischer, Fisher...and Whitmore (2008). This rule ranks subjects on percent change of cognitive performance from a baseline performance (before fatigue) to a fatigue

Rank Dynamics of Word Usage at Multiple Scales

NASA Astrophysics Data System (ADS)

Morales, José A.; Colman, Ewan; Sánchez, Sergio; Sánchez-Puig, Fernanda; Pineda, Carlos; Iñiguez, Gerardo; Cocho, Germinal; Flores, Jorge; Gershenson, Carlos

2018-05-01

The recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books N-grams dataset to analyze the temporal evolution of word usage in several languages. We apply measures proposed recently to study rank dynamics, such as the diversity of N-grams in a given rank, the probability that an N-gram changes rank between successive time intervals, the rank entropy, and the rank complexity. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. We also propose a null model to explore the relevance of linguistic structure across multiple scales, concluding that N-gram statistics cannot be reduced to word statistics. We expect our results to be useful in improving text prediction algorithms, as well as in shedding light on the large-scale features of language use, beyond linguistic and cultural differences across human populations.

The relationship between start performance and race outcome in elite 500-m short-track speed skating.

PubMed

Haug, William B; Drinkwater, Eric J; Mitchell, Lachlan J; Chapman, Dale W

2015-10-01

Initial short-track speed-skating 14-m start performance has substantial influence on 500-m race outcome at the international level, yet the relationship has not been systematically quantified. The purpose of this investigation was to examine the relationship between rank position entering first corner (RPEFC) and race outcome and to understand how this relationship changes with competition round and absolute race intensity. Data were compiled from 2011-2014 World Cup seasons and 2010 and 2014 Olympic Winter Games. Association between RPEFC and race outcome was determined through Kendall tau-rank correlations. A visual comparison was made of how the relationship changes with relative competition level (race tau correlations were sorted by competition round) and with race intensity (race tau correlations were sorted by within-event winning time). A very large relationship between RPEFC and race outcome was observed (correlations for cohort, τ = .60; men, τ = .53; women, τ = .67). When examined by competition round (quarter- to A-finals), no substantial change in relationship was observed (men, τ = .57-.46; women, τ = .73-.53). However, when the start-performance relationship was considered by within-event winning time, the relationship strength increased with decreasing time (men, τ = .61 to .46; women, τ = .76 to .57; fastest to 7th- and 8th-fastest combined, respectively). These results establish and quantify RPEFC as an important aspect of elite short-track 500-m race outcome. RPEFC as an indicator of race outcome becomes increasingly important with absolute race intensity, suggesting that RPEFC capability is a discriminating factor for competitors of similar top speed and speed endurance.

Mining User Dwell Time for Personalized Web Search Re-Ranking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Songhua; Jiang, Hao; Lau, Francis

We propose a personalized re-ranking algorithm through mining user dwell times derived from a user's previously online reading or browsing activities. We acquire document level user dwell times via a customized web browser, from which we then infer conceptword level user dwell times in order to understand a user's personal interest. According to the estimated concept word level user dwell times, our algorithm can estimate a user's potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. We compare the rankings produced by our algorithm with rankings generated by popular commercial search enginesmore » and a recently proposed personalized ranking algorithm. The results clearly show the superiority of our method. In this paper, we propose a new personalized webpage ranking algorithmthrough mining dwell times of a user. We introduce a quantitative model to derive concept word level user dwell times from the observed document level user dwell times. Once we have inferred a user's interest over the set of concept words the user has encountered in previous readings, we can then predict the user's potential dwell time over a new document. Such predicted user dwell time allows us to carry out personalized webpage re-ranking. To explore the effectiveness of our algorithm, we measured the performance of our algorithm under two conditions - one with a relatively limited amount of user dwell time data and the other with a doubled amount. Both evaluation cases put our algorithm for generating personalized webpage rankings to satisfy a user's personal preference ahead of those by Google, Yahoo!, and Bing, as well as a recent personalized webpage ranking algorithm.« less

Social correlates of variation in urinary cortisol in wild male bonobos (Pan paniscus).

PubMed

Surbeck, Martin; Deschner, Tobias; Weltring, Anja; Hohmann, Gottfried

2012-06-01

Cortisol excretion in males of group living species is often associated with social rank and competition for oestrous females. Rank-related patterns of cortisol levels can be used to study mechanisms of rank maintenance and costs associated with mate competition. Bonobos (Pan paniscus) are interesting because males form a linear dominance hierarchy but are not dominant over females and therefore aggressive male-male competition over access to females alone is not considered to be a successful reproductive strategy. In this study on social correlates of urinary cortisol in wild male bonobos, we investigated the relationship between cortisol levels and several aspects of mate competition, including male rank, aggression rates, and association time with oestrous females. We found that cortisol levels correlated positively with dominance rank when oestrous females were present, but not when they were absent. This result is consistent with the idea that aggressive behaviour plays a minor role in maintenance of high rank. While aggression received from males and females explained within-individual variation in cortisol levels, it was the time spent in association with oestrous females that best explained between-individual variation in male cortisol levels. The observed increase in male cortisol may be associated with spatial proximity to oestrous females and could result from anticipated aggression from other group members, reduced feeding time in the males, or a combination of both. Copyright © 2012 Elsevier Inc. All rights reserved.

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection

PubMed Central

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-01-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices. PMID:25177107

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

PubMed

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-11-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

Kendall-Theil Robust Line (KTRLine--version 1.0)-A Visual Basic Program for Calculating and Graphing Robust Nonparametric Estimates of Linear-Regression Coefficients Between Two Continuous Variables

USGS Publications Warehouse

Granato, Gregory E.

2006-01-01

The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. The KTRLine software was developed by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, for use in stochastic data modeling with local, regional, and national hydrologic data sets to develop planning-level estimates of potential effects of highway runoff on the quality of receiving waters. The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. The slope of the line is calculated as the median of all possible pairwise slopes between points. The intercept is calculated so that the line will run through the median of input data. A single-line model or a multisegment model may be specified. The program was developed to provide regression equations with an error component for stochastic data generation because nonparametric multisegment regression tools are not available with the software that is commonly used to develop regression models. The Kendall-Theil robust line is a median line and, therefore, may underestimate total mass, volume, or loads unless the error component or a bias correction factor is incorporated into the estimate. Regression statistics such as the median error, the median absolute deviation, the prediction error sum of squares, the root mean square error, the confidence interval for the slope, and the bias correction factor for median estimates are calculated by use of nonparametric methods. These statistics, however, may be used to formulate estimates of mass, volume, or total loads. The program is used to read a two- or three-column tab-delimited input file with variable names in the first row and

Resolution of ranking hierarchies in directed networks.

PubMed

Letizia, Elisa; Barucca, Paolo; Lillo, Fabrizio

2018-01-01

Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit.

Resolution of ranking hierarchies in directed networks

PubMed Central

Barucca, Paolo; Lillo, Fabrizio

2018-01-01

Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit. PMID:29394278

Factors Impacting Faculty Research Productivity at a Highly-Ranked University

ERIC Educational Resources Information Center

Fung, Jin Lung Michael

2017-01-01

Universities around the world are facing increasing pressure to perform well in rankings, and rankings results have been shown to impact institutional reputation, ability to secure funding, and recruitment of students and faculty. Faculty research productivity is one of the main factors impacting rankings performance, and the aim of this project…

Ranking of healthcare programmes based on health outcome, health costs and safe delivery of care in hospital pharmacy practice.

PubMed

Brisseau, Lionel; Bussières, Jean-François; Bois, Denis; Vallée, Marc; Racine, Marie-Claude; Bonnici, André

2013-02-01

To establish a consensual and coherent ranking of healthcare programmes that involve the presence of ward-based and clinic-based clinical pharmacists, based on health outcome, health costs and safe delivery of care. This descriptive study was derived from a structured dialogue (Delphi technique) among directors of pharmacy department. We established a quantitative profile of healthcare programmes at five sites that involved the provision of ward-based and clinic-based pharmaceutical care. A summary table of evidence established a unique quality rating per inpatient (clinic-based) or outpatient (ward-based) healthcare programme. Each director rated the perceived impact of pharmaceutical care per inpatient or outpatient healthcare programme on three fields: health outcome, health costs and safe delivery of care. They agreed by consensus on the final ranking of healthcare programmes. A ranking was assigned for each of the 18 healthcare programmes for outpatient care and the 17 healthcare programmes for inpatient care involving the presence of pharmacists, based on health outcome, health costs and safe delivery of care. There was a good correlation between ranking based on data from a 2007-2008 Canadian report on hospital pharmacy practice and the ranking proposed by directors of pharmacy department. Given the often limited human and financial resources, managers should consider the best evidence available on a profession's impact to plan healthcare services within an organization. Data are few on ranking healthcare programmes in order to prioritize which healthcare programme would mostly benefit from the delivery of pharmaceutical care by ward-based and clinic-based pharmacists. © 2012 The Authors. IJPP © 2012 Royal Pharmaceutical Society.

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

An ensemble rank learning approach for gene prioritization.

PubMed

Lee, Po-Feng; Soo, Von-Wun

2013-01-01

Several different computational approaches have been developed to solve the gene prioritization problem. We intend to use the ensemble boosting learning techniques to combine variant computational approaches for gene prioritization in order to improve the overall performance. In particular we add a heuristic weighting function to the Rankboost algorithm according to: 1) the absolute ranks generated by the adopted methods for a certain gene, and 2) the ranking relationship between all gene-pairs from each prioritization result. We select 13 known prostate cancer genes in OMIM database as training set and protein coding gene data in HGNC database as test set. We adopt the leave-one-out strategy for the ensemble rank boosting learning. The experimental results show that our ensemble learning approach outperforms the four gene-prioritization methods in ToppGene suite in the ranking results of the 13 known genes in terms of mean average precision, ROC and AUC measures.

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

PubMed

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.

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

PubMed

Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

Correlation between dental and cervical vertebral maturation in Iranian females.

PubMed

Valizadeh, Solmaz; Eil, Nakissa; Ehsani, Sara; Bakhshandeh, Hooman

2012-12-01

Considerable variations in the development stage among patients of the same chronological age have led to introduce the concept of the developmental age based on the maturation of different organs such as cervical vertebrae or teeth. The purpose of this study was to investigate the correlation between the stages of tooth calcification and the cervical vertebral maturation in Iranian females. Four hundred females (age range, 8 to 14 years) participated in the study. To determine the dental maturational stage, calcification of the mandibular teeth except for third molars were rated according to the method suggested by Demirjian et al. To evaluate the stage of skeletal maturation, cervical vertebral morphologic changes were assessed on lateral cephalometric radiographs according to the method explained by Baccetti et al. Correlations between bone maturation and teeth calcification were showed by Spearman's correlation and Kendall's tau-b coefficients. The relevant associations were investigated by ordinal logistic regression models. Correlations between the two stages were observed in the first and second premolars, canine and central incisors. All these correlations were significant. The association between cervical vertebral maturation and tooth calcification was greatest in the lateral incisor (odds ratio (OR) = 11, 95% confidence interval (CI): 6.6-18.3). However, considering the 95% CI for OR, no significant difference was detected among the second molar, first molar and lateral incisor. The relationship between calcification of teeth and maturation of cervical bones was significant. Bone maturation can be predicted by using teeth calcification stages, especially in the second molar, first molar and lateral incisor.

5 CFR 451.301 - Ranks for the Senior Executive Service.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Ranks for the Senior Executive Service... REGULATIONS AWARDS Presidential Rank Awards § 451.301 Ranks for the Senior Executive Service. (a) The... to a Senior Executive Service (SES) career appointee are set forth in 5 U.S.C. 4507. (b) To be...

Multi-Task Learning with Low Rank Attribute Embedding for Multi-Camera Person Re-Identification.

PubMed

Su, Chi; Yang, Fan; Zhang, Shiliang; Tian, Qi; Davis, Larry Steven; Gao, Wen

2018-05-01

We propose Multi-Task Learning with Low Rank Attribute Embedding (MTL-LORAE) to address the problem of person re-identification on multi-cameras. Re-identifications on different cameras are considered as related tasks, which allows the shared information among different tasks to be explored to improve the re-identification accuracy. The MTL-LORAE framework integrates low-level features with mid-level attributes as the descriptions for persons. To improve the accuracy of such description, we introduce the low-rank attribute embedding, which maps original binary attributes into a continuous space utilizing the correlative relationship between each pair of attributes. In this way, inaccurate attributes are rectified and missing attributes are recovered. The resulting objective function is constructed with an attribute embedding error and a quadratic loss concerning class labels. It is solved by an alternating optimization strategy. The proposed MTL-LORAE is tested on four datasets and is validated to outperform the existing methods with significant margins.

Development of an index to rank dairy females on expected lifetime profit.

PubMed

Kelleher, M M; Amer, P R; Shalloo, L; Evans, R D; Byrne, T J; Buckley, F; Berry, D P

2015-06-01

The objective of this study was to develop an index to rank dairy females on expected profit for the remainder of their lifetime, taking cognizance of both additive and nonadditive genetic merit, permanent environmental effects, and current states of the animal including the most recent calving date and cow parity. The cow own worth (COW) index is intended to be used for culling the expected least profitable females in a herd, as well as inform purchase and pricing decisions for trading of females. The framework of the COW index consisted of the profit accruing from (1) the current lactation, (2) future lactations, and (3) net replacement cost differential. The COW index was generated from estimated performance values (sum of additive genetic merit, nonadditive genetic merit, and permanent environmental effects) of traits, their respective net margin values, and transition probability matrices for month of calving, survival, and somatic cell count; the transition matrices were to account for predicted change in a cow's state in the future. Transition matrices were generated from 3,156,109 lactation records from the Irish national database between the years 2010 and 2013. Phenotypic performance records for 162,981 cows in the year 2012 were used to validate the COW index. Genetic and permanent environmental effects (where applicable) were available for these cows from the 2011 national genetic evaluations and used to calculate the COW index and their national breeding index values (includes only additive genetic effects). Cows were stratified per quartile within herd, based on their COW index value and national breeding index value. The correlation between individual animal COW index value and national breeding index value was 0.65. Month of calving of the cow in her current lactation explained 18% of the variation in the COW index, with the parity of the cow explaining an additional 3 percentage units of the variance in the COW index. Females ranking higher on the

Universality in the tail of musical note rank distribution

NASA Astrophysics Data System (ADS)

Beltrán del Río, M.; Cocho, G.; Naumis, G. G.

2008-09-01

Although power laws have been used to fit rank distributions in many different contexts, they usually fail at the tails. Languages as sequences of symbols have been a popular subject for ranking distributions, and for this purpose, music can be treated as such. Here we show that more than 1800 musical compositions are very well fitted by the first kind two parameter beta distribution, which arises in the ranking of multiplicative stochastic processes. The parameters a and b are obtained for classical, jazz and rock music, revealing interesting features. Specially, we have obtained a clear trend in the values of the parameters for major and minor tonal modes. Finally, we discuss the distribution of notes for each octave and its connection with the ranking of the notes.

Time-Aware Service Ranking Prediction in the Internet of Things Environment

PubMed Central

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-01-01

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets. PMID:28448451

Time-Aware Service Ranking Prediction in the Internet of Things Environment.

PubMed

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-04-27

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

Ranking Regime and the Future of Vernacular Scholarship

ERIC Educational Resources Information Center

Ishikawa, Mayumi

2014-01-01

World university rankings and their global popularity present a number of far-reaching impacts for vernacular scholarship. This article employs a multidimensional approach to analyze the ranking regime's threat to local scholarship and knowledge construction through a study of Japanese research universities. First, local conditions that have led…

Expanding the landscape of $$ \\mathcal{N} $$ = 2 rank 1 SCFTs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Argyres, Philip C.; Lotito, Matteo; Lu, Yongchao

Here, we refine our previous proposal [1-3] for systematically classifying 4d rank-1 N = 2 SCFTs by constructing their possible Coulomb branch geometries. Four new recently discussed rank-1 theories [4, 5], including novel N = 3 SCFTs, sit beautifully in our refined classification framework. By arguing for the consistency of their RG flows we can make a strong case for the existence of at least four additional rank-1 SCFTs, nearly doubling the number of known rank-1 SCFTs. The refinement consists of relaxing the assumption that the flavor symmetries of the SCFTs have no discrete factors. This results in an enlargedmore » (but finite) set of possible rank-1 SCFTs. Their existence can be further constrained using consistency of their central charges and RG flows.« less

Expanding the landscape of $$ \\mathcal{N} $$ = 2 rank 1 SCFTs

DOE PAGES

Argyres, Philip C.; Lotito, Matteo; Lu, Yongchao; ...

2016-05-16

Here, we refine our previous proposal [1-3] for systematically classifying 4d rank-1 N = 2 SCFTs by constructing their possible Coulomb branch geometries. Four new recently discussed rank-1 theories [4, 5], including novel N = 3 SCFTs, sit beautifully in our refined classification framework. By arguing for the consistency of their RG flows we can make a strong case for the existence of at least four additional rank-1 SCFTs, nearly doubling the number of known rank-1 SCFTs. The refinement consists of relaxing the assumption that the flavor symmetries of the SCFTs have no discrete factors. This results in an enlargedmore » (but finite) set of possible rank-1 SCFTs. Their existence can be further constrained using consistency of their central charges and RG flows.« less

Rank-Order and Paired Comparisons as the Basis for Measurement.

ERIC Educational Resources Information Center

Linacre, John M.

Three case studies are presented demonstrating the application of straight-forward Rasch techniques to rank order data. Paired comparisons are the simplest form of rank ordering. A consumer preference test with 56 pairs of cups of coffee tasted by each of 26 consumers illustrates analysis of these rankings. When subjects are allowed the option of…

Learning to rank image tags with limited training examples.

PubMed

Songhe Feng; Zheyun Feng; Rong Jin

2015-04-01

With an increasing number of images that are available in social media, image annotation has emerged as an important research topic due to its application in image matching and retrieval. Most studies cast image annotation into a multilabel classification problem. The main shortcoming of this approach is that it requires a large number of training images with clean and complete annotations in order to learn a reliable model for tag prediction. We address this limitation by developing a novel approach that combines the strength of tag ranking with the power of matrix recovery. Instead of having to make a binary decision for each tag, our approach ranks tags in the descending order of their relevance to the given image, significantly simplifying the problem. In addition, the proposed method aggregates the prediction models for different tags into a matrix, and casts tag ranking into a matrix recovery problem. It introduces the matrix trace norm to explicitly control the model complexity, so that a reliable prediction model can be learned for tag ranking even when the tag space is large and the number of training images is limited. Experiments on multiple well-known image data sets demonstrate the effectiveness of the proposed framework for tag ranking compared with the state-of-the-art approaches for image annotation and tag ranking.

Higher Education Ranking and Leagues Tables: Lessons Learned from Benchmarking

ERIC Educational Resources Information Center

Proulx, Roland

2007-01-01

The paper intends to contribute to the debate on ranking and league tables by adopting a critical approach to ranking methodologies from the point of view of a university benchmarking exercise. The absence of a strict benchmarking exercise in the ranking process has been, in the opinion of the author, one of the major problems encountered in the…

Control by Numbers: New Managerialism and Ranking in Higher Education

ERIC Educational Resources Information Center

Lynch, Kathleen

2015-01-01

This paper analyses the role of rankings as an instrument of new managerialism. It shows how rankings are reconstituting the purpose of universities, the role of academics and the definition of what it is to be a student. The paper opens by examining the forces that have facilitated the emergence of the ranking industry and the ideologies…

Multimodal biometric system using rank-level fusion approach.

PubMed

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

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

Review assessment support in Open Journal System using TextRank

NASA Astrophysics Data System (ADS)

Manalu, S. R.; Willy; Sundjaja, A. M.; Noerlina

2017-01-01

In this paper, a review assessment support in Open Journal System (OJS) using TextRank is proposed. OJS is an open-source journal management platform that provides a streamlined journal publishing workflow. TextRank is an unsupervised, graph-based ranking model commonly used as extractive auto summarization of text documents. This study applies the TextRank algorithm to summarize 50 article reviews from an OJS-based international journal. The resulting summaries are formed using the most representative sentences extracted from the reviews. The summaries are then used to help OJS editors in assessing a review’s quality.

Correlation between dental maturity and cervical vertebral maturity.

PubMed

Chen, Jianwei; Hu, Haikun; Guo, Jing; Liu, Zeping; Liu, Renkai; Li, Fan; Zou, Shujuan

2010-12-01

The aim of this study was to investigate the association between dental and skeletal maturity. Digital panoramic radiographs and lateral skull cephalograms of 302 patients (134 boys and 168 girls, ranging from 8 to 16 years of age) were examined. Dental maturity was assessed by calcification stages of the mandibular canines, first and second premolars, and second molars, whereas skeletal maturity was estimated by the cervical vertebral maturation (CVM) stages. The Spearman rank-order correlation coefficient was used to measure the association between CVM stage and dental calcification stage of individual teeth. The mean chronologic age of girls was significantly lower than that of boys in each CVM stage. The Spearman rank-order correlation coefficients between dental maturity and cervical vertebral maturity ranged from 0.391 to 0.582 for girls and from 0.464 to 0.496 for boys (P < 0.05). In girls, the mandibular second molar had the highest and the canine the lowest correlation. In boys, the canine had the highest and the first premolar the lowest correlation. Tooth calcification stage was significantly correlated with cervical vertebral maturation stage. The development of the mandibular second molar in females and that of the mandibular canine in males had the strongest correlations with cervical vertebral maturity. Therefore, it is practical to consider the relationship between dental and skeletal maturity when planning orthodontic treatment. Copyright © 2010 Mosby, Inc. All rights reserved.

The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children

PubMed Central

Ameel, Eef; Storms, Gert

2016-01-01

An alternative method for deriving typicality judgments, applicable in young children that are not familiar with numerical values yet, is introduced, allowing researchers to study gradedness at younger ages in concept development. Contrary to the long tradition of using rating-based procedures to derive typicality judgments, we propose a method that is based on typicality ranking rather than rating, in which items are gradually sorted according to their typicality, and that requires a minimum of linguistic knowledge. The validity of the method is investigated and the method is compared to the traditional typicality rating measurement in a large empirical study with eight different semantic concepts. The results show that the typicality ranking task can be used to assess children’s category knowledge and to evaluate how this knowledge evolves over time. Contrary to earlier held assumptions in studies on typicality in young children, our results also show that preference is not so much a confounding variable to be avoided, but that both variables are often significantly correlated in older children and even in adults. PMID:27322371

Hyperspectral image denoising and anomaly detection based on low-rank and sparse representations

NASA Astrophysics Data System (ADS)

Zhuang, Lina; Gao, Lianru; Zhang, Bing; Bioucas-Dias, José M.

2017-10-01

The very high spectral resolution of Hyperspectral Images (HSIs) enables the identification of materials with subtle differences and the extraction subpixel information. However, the increasing of spectral resolution often implies an increasing in the noise linked with the image formation process. This degradation mechanism limits the quality of extracted information and its potential applications. Since HSIs represent natural scenes and their spectral channels are highly correlated, they are characterized by a high level of self-similarity and are well approximated by low-rank representations. These characteristic underlies the state-of-the-art in HSI denoising. However, in presence of rare pixels, the denoising performance of those methods is not optimal and, in addition, it may compromise the future detection of those pixels. To address these hurdles, we introduce RhyDe (Robust hyperspectral Denoising), a powerful HSI denoiser, which implements explicit low-rank representation, promotes self-similarity, and, by using a form of collaborative sparsity, preserves rare pixels. The denoising and detection effectiveness of the proposed robust HSI denoiser is illustrated using semi-real data.

The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children.

PubMed

Djalal, Farah Mutiasari; Ameel, Eef; Storms, Gert

2016-01-01

An alternative method for deriving typicality judgments, applicable in young children that are not familiar with numerical values yet, is introduced, allowing researchers to study gradedness at younger ages in concept development. Contrary to the long tradition of using rating-based procedures to derive typicality judgments, we propose a method that is based on typicality ranking rather than rating, in which items are gradually sorted according to their typicality, and that requires a minimum of linguistic knowledge. The validity of the method is investigated and the method is compared to the traditional typicality rating measurement in a large empirical study with eight different semantic concepts. The results show that the typicality ranking task can be used to assess children's category knowledge and to evaluate how this knowledge evolves over time. Contrary to earlier held assumptions in studies on typicality in young children, our results also show that preference is not so much a confounding variable to be avoided, but that both variables are often significantly correlated in older children and even in adults.

Beyond Zipf's Law: The Lavalette Rank Function and Its Properties.

PubMed

Fontanelli, Oscar; Miramontes, Pedro; Yang, Yaning; Cocho, Germinal; Li, Wentian

Although Zipf's law is widespread in natural and social data, one often encounters situations where one or both ends of the ranked data deviate from the power-law function. Previously we proposed the Beta rank function to improve the fitting of data which does not follow a perfect Zipf's law. Here we show that when the two parameters in the Beta rank function have the same value, the Lavalette rank function, the probability density function can be derived analytically. We also show both computationally and analytically that Lavalette distribution is approximately equal, though not identical, to the lognormal distribution. We illustrate the utility of Lavalette rank function in several datasets. We also address three analysis issues on the statistical testing of Lavalette fitting function, comparison between Zipf's law and lognormal distribution through Lavalette function, and comparison between lognormal distribution and Lavalette distribution.

Global University Rankings--Impacts and Unintended Side Effects

ERIC Educational Resources Information Center

Kehm, Barbara M.

2014-01-01

In this article, global and other university rankings are critically assessed with regard to their unintended side effects and their impacts on the European and national landscape of universities, as well as on individual institutions. An emphasis is put on the effects of ranking logics rather than on criticising their methodology. Nevertheless,…

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

PubMed Central

Salomon, Joshua A

2003-01-01

Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO) or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC) between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99). Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions Modeling health

SortNet: learning to rank by a neural preference function.

PubMed

Rigutini, Leonardo; Papini, Tiziano; Maggini, Marco; Scarselli, Franco

2011-09-01

Relevance ranking consists in sorting a set of objects with respect to a given criterion. However, in personalized retrieval systems, the relevance criteria may usually vary among different users and may not be predefined. In this case, ranking algorithms that adapt their behavior from users' feedbacks must be devised. Two main approaches are proposed in the literature for learning to rank: the use of a scoring function, learned by examples, that evaluates a feature-based representation of each object yielding an absolute relevance score, a pairwise approach, where a preference function is learned to determine the object that has to be ranked first in a given pair. In this paper, we present a preference learning method for learning to rank. A neural network, the comparative neural network (CmpNN), is trained from examples to approximate the comparison function for a pair of objects. The CmpNN adopts a particular architecture designed to implement the symmetries naturally present in a preference function. The learned preference function can be embedded as the comparator into a classical sorting algorithm to provide a global ranking of a set of objects. To improve the ranking performances, an active-learning procedure is devised, that aims at selecting the most informative patterns in the training set. The proposed algorithm is evaluated on the LETOR dataset showing promising performances in comparison with other state-of-the-art algorithms.

College Rankings. ERIC Digest.

ERIC Educational Resources Information Center

Holub, Tamara

The popularity of college ranking surveys published by "U.S. News and World Report" and other magazines is indisputable, but the methodologies used to measure the quality of higher education institutions have come under fire by scholars and college officials. Criticisms have focused on methodological flaws, such as failure to consider…

Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

PubMed Central

Ma, Chuang; Wang, Xiangfeng

2012-01-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655

Analysis of Duplicated Multiple-Samples Rank Data Using the Mack-Skillings Test.

PubMed

Carabante, Kennet Mariano; Alonso-Marenco, Jose Ramon; Chokumnoyporn, Napapan; Sriwattana, Sujinda; Prinyawiwatkul, Witoon

2016-07-01

Appropriate analysis for duplicated multiple-samples rank data is needed. This study compared analysis of duplicated rank preference data using the Friedman versus Mack-Skillings tests. Panelists (n = 125) ranked twice 2 orange juice sets: different-samples set (100%, 70%, vs. 40% juice) and similar-samples set (100%, 95%, vs. 90%). These 2 sample sets were designed to get contrasting differences in preference. For each sample set, rank sum data were obtained from (1) averaged rank data of each panelist from the 2 replications (n = 125), (2) rank data of all panelists from each of the 2 separate replications (n = 125 each), (3) jointed rank data of all panelists from the 2 replications (n = 125), and (4) rank data of all panelists pooled from the 2 replications (n = 250); rank data (1), (2), and (4) were separately analyzed by the Friedman test, although those from (3) by the Mack-Skillings test. The effect of sample sizes (n = 10 to 125) was evaluated. For the similar-samples set, higher variations in rank data from the 2 replications were observed; therefore, results of the main effects were more inconsistent among methods and sample sizes. Regardless of analysis methods, the larger the sample size, the higher the χ(2) value, the lower the P-value (testing H0 : all samples are not different). Analyzing rank data (2) separately by replication yielded inconsistent conclusions across sample sizes, hence this method is not recommended. The Mack-Skillings test was more sensitive than the Friedman test. Furthermore, it takes into account within-panelist variations and is more appropriate for analyzing duplicated rank data. © 2016 Institute of Food Technologists®

Charting taxonomic knowledge through ontologies and ranking algorithms

NASA Astrophysics Data System (ADS)

Huber, Robert; Klump, Jens

2009-04-01

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

A Global Comparison of Business Journal Ranking Systems

ERIC Educational Resources Information Center

Alexander, Jennifer K.; Scherer, Robert F.; Lecoutre, Marc

2007-01-01

The authors compared business journal ranking systems from 6 countries. Results revealed a low degree of agreement among the systems, and a low to moderate relationship between pairs of systems. In addition, the French and United Kingdom ranking systems were different from each other and from the systems in Australia, Germany, Hong Kong, and the…