Prior Ranking Research Articles

Hierarchies and entrepreneurship

We establish a correlation between the hierarchical structure of a firm and the likelihood of business creation among its former employees, using a sample of 16 million observations of Swedish workers and a novel proxy for hierarchies based on occupation data. Conditional on firm size and many other variables, employees in firms with more layers are less likely to enter entrepreneurship, to become self-employed, and to switch to another employer. The effects of layers are much stronger for business creation than for job-switching and they are stronger for entrepreneurship than for self-employment. We discuss two potential explanations for the distinctive hierarchy effect we find. Part of the effect could be to be due to preference sorting by employees, and part due to employees in firms with fewer layers having a broader range of skills. One test showing that the probability of entrepreneurship increases with their prior rank in an organization is consistent with ability sorting and inconsistent with preference sorting.

SU‐G‐IeP1‐13: Sub‐Nyquist Dynamic MRI Via Prior Rank, Intensity and Sparsity Model (PRISM)

Purpose:Accelerated dynamic MRI is important for MRI guided radiotherapy. Inspired by compressive sensing (CS), sub‐Nyquist dynamic MRI has been an active research area, i.e., sparse sampling in k‐t space for accelerated dynamic MRI. This work is to investigate sub‐Nyquist dynamic MRI via a previously developed CS model, namely Prior Rank, Intensity and Sparsity Model (PRISM).Methods:The proposed method utilizes PRISM with rank minimization and incoherent sampling patterns for sub‐Nyquist reconstruction. In PRISM, the low‐rank background image, which is automatically calculated by rank minimization, is excluded from the L1 minimization step of the CS reconstruction to further sparsify the residual image, thus allowing for higher acceleration rates. Furthermore, the sampling pattern in k‐t space is made more incoherent by sampling a different set of k‐space points at different temporal frames.Results:Reconstruction results from L1‐sparsity method and PRISM method with 30% undersampled data and 15% undersampled data are compared to demonstrate the power of PRISM for dynamic MRI.Conclusion:A sub‐ Nyquist MRI reconstruction method based on PRISM is developed with improved image quality from the L1‐sparsity method.

Top of the Class: The Importance of Ordinal Rank

Abstract This article establishes a new fact about educational production: ordinal academic rank during primary school has lasting impacts on secondary school achievement that are independent of underlying ability. Using data on the universe of English school students, we exploit naturally occurring differences in achievement distributions across primary school classes to estimate the impact of class rank. We find large effects on test scores, confidence, and subject choice during secondary school, even though these students have a new set of peers and teachers who are unaware of the students’ prior ranking in primary school. The effects are especially pronounced for boys, contributing to an observed gender gap in the number of Maths courses chosen at the end of secondary school. Using a basic model of student effort allocation across subjects, we distinguish between learning and non-cognitive skills mechanisms, finding support for the latter.

Ability to Return to Play After Arthroscopic Shoulder Surgery in Professional Female Tennis Players

Ability to Return to Play After Arthroscopic Shoulder Surgery in Professional Female Tennis Players

A novel machine learning approach to rank web forum posts

Since the user generated contents in Web forums are rich but vary in quality, ranging from excellent detailed opinions to simple repetition of the content of previous, or even spams, it is difficult to find high quality information in the process of post browsing, retrieval and other Web forum applications. In this paper, we propose a novel machine learning approach named LGPRank to evaluate the web forum posts, where a genetic programming architecture is used to rank Web forum posts according to the qualities of their contents. In order to address the shortcomings of current studies, we take both the semantic-free and semantic-specific information of a post into account. We propose a set of new features named Latent Dirichlet Allocation (LDA) semantic features which are computed in LDA topic space. The proposed features as well as content surface features and forum specific features are used in the learning process. Experiments are conducted on three web forum datasets in comparison with methods used in prior ranking research. LGPRank outperforms all the other methods in terms of P@N, NDCG@N and MAP measures. Furthermore, the experimental results also indicate that the proposed LDA semantic features have a positive effect in improving the ranking performance.

Grading severity of carpal tunnel syndrome in electrodiagnostic reports: Why grading is recommended

Carpal tunnel syndrome (CTS) is not difficult to confirm by electrodiagnosis (EDx), but the challenge lies in whether to grade the severity and the method for doing so. The arguments about grading are discussed, with an emphasis in favor, using a method that relies on the EDx data, but qualifies that it is the median neuropathy being graded and not the syndrome of CTS. Although use of latencies can be arbitrary and misleading, it is possible to apply other criteria, such as low amplitudes or conduction block and denervation, to develop a grading scale that could be applied widely. Several previously published grading schemes are reviewed, and a new method is described that combines the prior ranking criteria into 3 basic categories. Application of a grading system identifies the degree of nerve injury and thus allows the referring physician to utilize optimally the EDx report to manage the patient.

Knowledge of and Training in Research Ethics in an African Health Research Community

Background: This study aimed at assessing knowledge of research ethics in a Nigerian health research community based on criteria for ethical research in the national code. It also sought to test the hypothesis that prior research ethics training, higher academic rank, and self-judged adequate knowledge of research ethics were not associated with knowledge of research ethics. Methods: As part of a descriptive, cross-sectional study, lecturers in university medical schools in two Nigerian states completed a structured questionnaire. Results: Of 133 study participants, 100 (75.2%) were trained in research ethics, mostly through workshops (72%). Fifty (37.6%) correctly identified all 10 criteria for ethical research listed. Prior research ethics training, rank, and self-judged adequate knowledge of research ethics were not associated with aggregate scores of research ethics knowledge. Conclusions: The majority of the respondents were trained in research ethics, but knowledge gaps were identified. Health researchers in this setting need to be trained more effectively in research ethics.

A New Speech Enhancement Approach Based on A Prior Rank and Sparsity Model

A New Speech Enhancement Approach Based on A Prior Rank and Sparsity Model

Personalized ranking in web databases: establishing and utilizing an appropriate workload

The emergence of the deep Web has given a new connotation to the concept of ranking database query results. Earlier approaches for ranking either resorted to analyzing frequencies of database values and query logs or establishing user profiles. In contrast, an integrated approach, based on the notion of a similarity model, for holistically supporting user- and query-dependent ranking has been recently proposed (Telang et al. in IEEE Transactions on Knowledge and Data Engineering (TKDE), 2011). An important component of this framework is a workload consisting of ranking functions, wherein each function represents an individual user's preferences towards the results of a specific query. At the time of answering a query for which no prior ranking function exists, the similarity model is employed, and is expected to ensure a good quality of ranking as long as a ranking function for a very similar user-query pair exists in this workload. In this paper, we address the problem of determining an appropriate set of user-query pairs to form a workload of ranking functions to support user- and query-dependent ranking for Web databases. We propose a novel metric, termed workload goodness, that quantifies the notion of a "good" workload into an absolute value. The process of finding such a workload of optimal goodness is a combinatorially explosive problem; therefore, we propose a heuristic solution, and advance three approaches for determining an acceptable workload, in a static as well as a dynamic environment. We discuss the effectiveness of our proposal analytically as well as experimentally over two Web databases.

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

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

Why Are Firms Admired?

In this paper, we explore why certain firms are admired while others are not. We examine a broad range of organizational, governance and financial variables to glean significant factors that impact a firm's status as ‘Most Admired’. On the basis of our analysis of 1,842 firms, 285 of which were featured in Fortune's Most Admired companies list, we found that factors important to corporate reputation did not necessarily play a definitive role in companies being ranked on the most admired list. The major finding, robust in all cases, is that a larger size, prior ranking on the ‘Most Admired Companies’ list and a high market-to-book value of shares have a positive significant effect on a firm's likelihood of being classified as ‘Most Admired’. Consistent with prior literature, we also find that increases in executive entrenchment, via curtailment of shareholder rights, are viewed negatively by the stakeholders. From a strategic perspective, if a firm wishes to be admired, it would do well with a reasonably sized work force, a better market performance and a more democratic form of corporate governance.

Ordinal prior knowledge-based ranking SVM

Ordinal prior knowledge-based ranking SVM

Variance heterogeneity analysis for detection of potentially interacting genetic loci: method and its limitations

BackgroundPresence of interaction between a genotype and certain factor in determination of a trait's value, it is expected that the trait's variance is increased in the group of subjects having this genotype. Thus, test of heterogeneity of variances can be used as a test to screen for potentially interacting single-nucleotide polymorphisms (SNPs). In this work, we evaluated statistical properties of variance heterogeneity analysis in respect to the detection of potentially interacting SNPs in a case when an interaction variable is unknown.ResultsThrough simulations, we investigated type I error for Bartlett's test, Bartlett's test with prior rank transformation of a trait to normality, and Levene's test for different genetic models. Additionally, we derived an analytical expression for power estimation. We showed that Bartlett's test has acceptable type I error in the case of trait following a normal distribution, whereas Levene's test kept nominal Type I error under all scenarios investigated. For the power of variance homogeneity test, we showed (as opposed to the power of direct test which uses information about known interacting factor) that, given the same interaction effect, the power can vary widely depending on the non-estimable direct effect of the unobserved interacting variable. Thus, for a given interaction effect, only very wide limits of power of the variance homogeneity test can be estimated. Also we applied Levene's approach to test genome-wide homogeneity of variances of the C-reactive protein in the Rotterdam Study population (n = 5959). In this analysis, we replicate previous results of Pare and colleagues (2010) for the SNP rs12753193 (n = 21, 799).ConclusionsScreening for differences in variances among genotypes of a SNP is a promising approach as a number of biologically interesting models may lead to the heterogeneity of variances. However, it should be kept in mind that the absence of variance heterogeneity for a SNP can not be interpreted as the absence of involvement of the SNP in the interaction network.

Composition dependence of ternary Pt–Ni–Cr catalyst activity for the methanol electro-oxidation reaction

Abstract Various compositions of binary and ternary Pt–Ni–Cr alloys were investigated as catalysts for the methanol electro-oxidation reaction (MOR). Among the binary (Pt 28 Ni 72 /C and Pt 28 Cr 72 /C) and ternary Pt–Ni–Cr catalysts (Pt 28 Ni 36 Cr 36 /C, Pt 22 Ni 39 Cr 39 /C, Pt 33 Ni 31 Cr 36 /C, and Pt 33 Ni 36 Cr 31 /C) examined, the Pt 28 Ni 36 Cr 36 /C composition exhibited the highest MOR mass activity (4.42 A g cat. −1 ) in the as-prepared version, which was higher than the 3.58 A g cat. −1 value of the PtRu/C catalyst after 60 min of chronoamperometry testing. The order of mass activity for the MOR was Pt 28 Ni 36 Cr 36 /C > Pt 33 Ni 36 Cr 31 /C > Pt 22 Ni 39 Cr 39 /C > Pt 33 Ni 31 Cr 36 /C > Pt 28 Cr 72 /C > Pt 28 Ni 72 /C, which was slightly changed to Pt 28 Ni 36 Cr 36 /C > Pt 22 Ni 39 Cr 39 /C > Pt 33 Ni 36 Cr 31 /C > Pt 33 Ni 31 Cr 36 /C > Pt 28 Cr 72 /C > Pt 28 Ni 72 /C after a conditioning process. The effect of anodic conditioning was also studied. A combination of X-ray diffraction, cyclic voltammetry, and chronoamperometry experiments revealed that the conditioning process caused dissolution and an oxidation state change of metallic Ni and Cr 2 O 3 in the binary catalysts. The higher MOR mass activities of the ternary catalysts compared to the binary ones is attributed to co-alloying of Ni and Cr, leading to exposure of more Pt on the catalyst surface without reducing specific activities of the catalysts. The results of this study also correlate well with a prior ranking of catalytic activity of the same compositions in the form of thin film catalysts that we processed and evaluated by a high-throughput combinatorial approach [J.S. Cooper, M.K. Jeon, P.J. McGinn, Electrochem. Commun. 10 (2008) 1545–1547].

WORLDWIDE ECONOMETRICS RANKINGS: 1989–2005

This paper updates Baltagi’s ~2003, Econometric Theory 19, 165–224! rankings of academic institutions by publication activity in econometrics over the period 1989–1999 to the period 1989–2005+ This ranking is based on 16 leading international journals that publish econometrics articles+ It is compared with the prior rankings by Hall ~1987, Econometric Theory 3, 171–194; 1990, Econometric Theory 6, 1–16! for the period 1980–1988+ In addition, a list of the top 150 individual producers of econometrics in these 16 journals over this 17-year period is provided+ This is done for theoretical econometrics and also for all contributions in econometrics+ Sensitivity analysis is provided using ~i! alternative weighting factors given to the 16 journals taking into account impact citations, excluding self-citations, size and age of the journal, ~ii! alternative time intervals, namely, 2000–2005, 1995–2005, and 1989–2005, ~iii! alternative ranking using the number of articles published in these journals, ~iv! separate rankings for both institutions and individuals by journal, ~v! rankings for institutions and individuals based on publications in three core econometrics journals+ What is certain is that econometrics now occupies a position in teaching programs that puts it on an equal footing with microeconomic and macroeconomic theory; and in research there seems to be no area of economics untouched by econometric method. To keep abreast of these changes, we intend to provide regular updates of the rankings of research activity presented in this issue of Econometric Theory+ —Peter C+B+ Phillips ~1987, Econometric Theory 3, 169!

Worldwide Econometrics Rankings: 1989-2005

This paper updates Baltagi’s (2003, Econometric Theory 19, 165-224) rankings of academic institutions by publication activity in econometrics from 1989-1999 to 1989-2005. This ranking is based on 16 leading international journals that publish econometrics articles. It is compared with the prior rankings by Hall (1980, 1987) for the period 1980-1988. In addition, a list of the top 150 individual producers of econometrics in these 16 journals over this 17-year period is provided. This is done for theoretical econometrics as well as all contributions in econometrics. Sensitivity analysis is provided using (i) alternative weighting factors given to the 16 journals taking into account impact citations, excluding self-citations, size and age of the journal, (ii) alternative time intervals, namely, (2000-2005), (1995-2005), and (1989-2005), (iii) alternative ranking using the number of articles published in these journals, (iii) separate rankings for both institutions and individuals by journal, (iv) rankings for institutions and individuals based on publications in three core econometrics journals.

Reputation Among Peer Academic Institutions: An Investigation of the US News and World Report's Rankings

The purpose of this study was to determine what leads to a higher reputation among peer academic institutions as reported in the US News and World Report's 2005 annual survey of ‘America's Best Colleges’. It was found that the level of student attention and selectivity are determinants of peer assessment for private universities. A university's research emphasis and prior ranking influence peer assessment for both private and public universities. An emphasis on research, however, has a greater impact on the peer assessment of public versus private universities. Student size and sports team performance appear to influence the peer assessment of private and public universities, respectively. Thus, peer assessors are able to make clear distinctions between private and public universities with a potential bias towards more visible universities in general.

Network Level을 고려한 교량의 우선순위 산정 알고리즘에 관한 연구

Bridge structures are properly designed in accordance with the design specifications with required safety margin. However, due to the heavy vehicle traffic and environmental attacks, bridge often requires repairs and the deteriorated one should be replaced or rehabilitated. In this paper, a prior ranking algorithm is proposed to assist a decision making process in bridge management at network level. Based on the literature survey for the existing studuies, two important factors which affect the decision making procedure for bridge management at network level are identified. These factors are implemented into the algorithm as a load carrying capacity function and traffic function, respectively.

Bioassay-directed Fractionation of Organic Extracts of Marine Surface Sediments from the North and Baltic Sea - Part II: Results of the biotest battery and development of a biotest index (8 pp)

Part I: Determination and identification of organic pollutants Part II: Results of the biotest battery and development of a biotest index Preamble. This series of two papers presents the results of an interdisciplinary research project (ISIS) dealing with bioassay-directed fractionation of marine sediment extracts. Part I presents the extraction and fractionation procedure as well as the results of chemical analysis, including non-target analysis of sediments. Part II describes the results of the biotest battery in relation to chemicals possibly causing parts of the observed effects. A biotest index is used to compare the toxicities of the samples. AUTHORS / AFFILIATIONS Ninja Reineke (3), Werner Wosniok (4), Dirk Danischewski (1), Heinrich Huhnerfuss (3), Angelika Kinder (5), Arne Sierts-Herrmann (5), Norbert Theobald (2), Hans-Heinrich Vahl (6), Michael Vobach (1), Johannes Westendorf (6) and Hans Steinhart (5). (1) Federal Research Centre for Fisheries, Institute for Fishery Ecology, Palmaille 9, 22767 Hamburg, Germany (2) Federal Maritime and Hydrographic Agency, Bernhard-Nochtstr. 78, 20359 Hamburg, Germany (3) University of Hamburg, Institute for Organic Chemistry, Martin-Luther-King-Platz 6, 20146 Hamburg, Germany (4) University of Bremen, Institute of Statistics, Bibliothekstr. 1, 28334 Bremen, Germany (5) University of Hamburg, Institute for Food Chemistry, Grindelallee 117, 20146 Hamburg, Germany (6) University of Hamburg, University Hospital Hamburg-Eppendorf, Department for Toxicology, Vogt-Kolln-Str. 30, 22527 Hamburg, Germany (7) Eurofins Wiertz-Eggert-Jorissen, Stenzelring 14b, 21107 Hamburg, Germany The ecological relevance of contaminants in mixtures is difficult to assess, because of possible interactions and due to lacking toxicity data for many substances present in environmental samples. Marine sediment extracts, which contain a mixture of environmental contaminants in low concentrations, were the object of this study. The extracts were investigated with a set of different biotests in order to identify the compound or the substance class responsible for the toxicity. For this goal, a combination of biotests, biotest-directed fractionation and chemical analysis has been applied. Further on, a strategy for the development of a biotest index to describe the toxicity of the fractions without a prior ranking of the test results is proposed. This article (Part II) focuses on the biological results of the approach. The toxicological potential of organic extracts of sediments from the North Sea and the Baltic Sea was analyzed in a bioassay-directed fractionation procedure with a set of biotests: luciferase reporter gene assays on hormone receptor and Ah receptor, arabinose resistance test, fish embryo test (Danio rerio), comet assay, acetylcholinesterase inhibition test, heat-shock protein 70 induction, oxidative stress and luminescence inhibition test (Vibrio fischeri). The test results provided the basis for the calculation of a biotest index by factor analysis to compare the toxicity of the samples and fractions. Results of 11 biotests on different fractionation levels of the samples were described and discussed with regard to the occurrence of contaminants and their toxic potentials. Polychlorinated biphenyls, polycyclic aromatic hydrocarbons, quinones, brominated indoles and brominated phenols were in the focus of interest. A biotest index was constructed to compare the toxic responses in the samples and to group the biotest results. The procedure presented in this study is well suited for bioassay-directed fractionation of marine sediment extracts. However, in relatively low contaminated samples, high enrichment factors and sufficient fractionation is necessary to allow identification of low concentrations of contaminants which is required to link effects and possible causes. In the present case, the relation between substances and effects was difficult to uncover due to relatively low concentrations of pollutants compared to the biogenic matrix and to the remaining complexity of the fractions. The results, with respect to the brominated phenols and indoles in the samples, highlight the successful use of bioassay directed fractionation in the case of high concentrations and high toxicity. In general, it has been shown that a marine risk assessment requires focusing on the input of diffuse sources and taking into account the fact of mixture toxicity. Effects resulting from biogenic substances will make the assessment of the influence of anthropogenic substances even more difficult.

Response: Different Purposes, Different Measures

This essay commends Chapple, Markusen, Schrock, Yamamoto, and Yu, whose article appears in this issue, for creating an index of metropolitan development potential that captures advantages related to city size and diversification over industries. Their critique of prior ranking studies, however, is unnecessarily harsh. In particular, studies that explore New Economy attributes or the presence of foundational technologies like computers and biotechnology may be valid when judged on their own terms. The authors imply that other analysts’ criteria for selecting high-technology regions are narrower than their own—typically ignoring the human capital dimension—but that is simply not the case. Index and ranking studies of metropolitan areas can provide useful insights provided that their purposes, conceptual frameworks, and methodologies are clearly understood.