Rank Variation Research Articles

Happiness as a sustainability factor. The world happiness index: a posetic-based data analysis

The World Happiness Index is calculated by a simple arithmetic addition of 7 sub-indicators. Such an aggregation is subject to possible compensation effects and may thus hide important information and consequently give a false impression. A posetic-based data analysis allows an evaluation of the data without any presumptions or aggregations leading to a different happiness ranking. The relative importance of the seven sub-indicators is disclosed. The most important sub-indicator appears to be the ‘Dystopia’ indicator, which reflects the countries own perception of doing better or worse than the hypothetical country Dystopia. Further, it was shown that, e.g., the gross domestic product per capita in terms of purchasing power parity plays only an inferior role. The study further elucidated so-called ‘peculiar’ countries, i.e., countries where one or more sub-indicators are either extremely high or low compared to the general trend of this indicator(s). Thus, a contradiction for Switzerland with regard to generosity compared to the CAF World Giving Index is disclosed. The effect of introducing weight regimes leading to a significantly reduced uncertainty in the average happiness ranking is discussed as is the correlations between the original happiness index ranking and the average rankings. In a final section some variations in the average ranking when changing to the data to the 2017 index are discussed.

Group Differences in Student Performance in the Selection to Higher Education: Tests vs Grades

Student selection in the Swedish admission to higher education system is based on two fundamentally different performance measures: their criterion-referenced upper secondary grade point average (GPA) or their score on a norm-referenced and multiple-choice admissions test (SweSAT). Several student characteristics are known to affect rankings in such assessments. The objectives of this study are to assess main and interactive effects of several variables that influence rankings obtained from these measures in greater detail than previously attempted, and assess the findings from a fairness perspective. The data consist of test scores, upper secondary grades and background information for SweSAT participants, aged 19 to 25 years, who took the test in the autumn of 2011 (N=23,214) or spring of 2012 (N= 27,075). The data were analysed through correlation and regression analysis. The results support previous findings that gender, parents’ education, and immigration status are all influential. Males obtain better SweSAT scores than females while females obtain better GPAs, in accordance with previous findings regarding gender-related variations in rankings provided by similar instruments. Moreover, we found the same pattern in scores for specific components of the test and grades in specific subjects, suggesting that the test and GPA measure different, gender-related, things. In addition, students with an immigrant background seem to be more highly ranked by grades than by the SweSAT, largely due to differences in assessments of their verbal skills. □

Comparative evaluation of topographical data of dental implant surfaces applying optical interferometry and scanning electron microscopy

ObjectiveComparability of topographical data of implant surfaces in literature is low and their clinical relevance often equivocal. The aim of this study was to investigate the ability of scanning electron microscopy and optical interferometry to assess statistically similar 3-dimensional roughness parameter results and to evaluate these data based on predefined criteria regarded relevant for a favorable biological response. MethodsFour different commercial dental screw-type implants (NanoTite Certain Prevail, TiUnite Brånemark Mk III, XiVE S Plus and SLA Standard Plus) were analyzed by stereo scanning electron microscopy and white light interferometry. Surface height, spatial and hybrid roughness parameters (Sa, Sz, Ssk, Sku, Sal, Str, Sdr) were assessed from raw and filtered data (Gaussian 50μm and 5μm cut-off-filters), respectively. Data were statistically compared by one-way ANOVA and Tukey–Kramer post-hoc test. For a clinically relevant interpretation, a categorizing evaluation approach was used based on predefined threshold criteria for each roughness parameter. ResultsThe two methods exhibited predominantly statistical differences. Dependent on roughness parameters and filter settings, both methods showed variations in rankings of the implant surfaces and differed in their ability to discriminate the different topographies. Overall, the analyses revealed scale-dependent roughness data. Compared to the pure statistical approach, the categorizing evaluation resulted in much more similarities between the two methods. SignificanceThis study suggests to reconsider current approaches for the topographical evaluation of implant surfaces and to further seek after proper experimental settings. Furthermore, the specific role of different roughness parameters for the bioresponse has to be studied in detail in order to better define clinically relevant, scale-dependent and parameter-specific thresholds and ranges.

Personality traits and ego-network dynamics.

Strong and supportive social relationships are fundamental to our well-being. However, there are costs to their maintenance, resulting in a trade-off between quality and quantity, a typical strategy being to put a lot of effort on a few high-intensity relationships while maintaining larger numbers of less close relationships. It has also been shown that there are persistent individual differences in this pattern; some individuals allocate their efforts more uniformly across their networks, while others strongly focus on their closest relationships. Furthermore, some individuals maintain more stable networks than others. Here, we focus on how personality traits of individuals affect this picture, using mobile phone calls records and survey data from the Mobile Territorial Lab (MTL) study. In particular, we look at the relationship between personality traits and the (i) persistence of social signatures, namely the similarity of the social signature shape of an individual measured in different time intervals; (ii) the turnover in egocentric networks, that is, differences in the set of alters present at two consecutive temporal intervals; and (iii) the rank dynamics defined as the variation of alter rankings in egocentric networks in consecutive intervals. We observe that some traits have effects on the stability of the social signatures as well as network turnover and rank dynamics. As an example, individuals who score highly in the Openness to Experience trait tend to have higher levels of network turnover and larger alter rank variations. On broader terms, our study shows that personality traits clearly affect the ways in which individuals maintain their personal networks.

Analysis of Volatile Organic Pyrolysis Products of Bituminous and Anthracite Coals with Single-Photon Ionization Time-of-Flight Mass Spectrometry and Gas Chromatography/Mass Spectrometry

The volatile organic compound (VOC) emissions from the pyrolysis of anthracite and bituminous coals are studied using both online single-photon ionization time-of-flight mass spectrometry (SPI-TOFMS) and offline gas chromatography/mass spectrometry (GC/MS) techniques. It is found that the combination of the online and offline techniques is effective in the VOC analysis. It reveals that the dominant pyrolysis products of both anthracite and bituminous coals are comprised of a mixture of non-aromatic hydrocarbons, mainly alkanes and light alkenes, aromatic compounds, and their corresponding isomers. Rank variation of coal samples has important impacts on the release of pyrolysis products. High-volatile bituminous coal releases more VOCs than low-volatile anthracite coal under the same temperature. The relative contents of the pyrolysis products of the two coals also differ. SH coal releases more short-chain aliphatic and oxygen-containing compounds, while XT coal releases more aromatic and sulfur-containing...

Method for selection of optimal road safety composite index with examples from DEA and TOPSIS method

Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine “real best performers”. Need for composite road safety index is becoming dominant since road safety presents a complex system where more and more indicators are constantly being developed to describe it. Among wide variety of models and developed composite indexes, a decision maker can come to even bigger dilemma than choosing one adequate risk measure. As DEA and TOPSIS are well-known mathematical models and have recently been increasingly used for risk evaluation in road safety, we used efficiencies (composite indexes) obtained by different models, based on DEA and TOPSIS, to present PROMETHEE-RS model for selection of optimal method for composite index. Method for selection of optimal composite index is based on three parameters (average correlation, average rank variation and average cluster variation) inserted into a PROMETHEE MCDM method in order to choose the optimal one. The model is tested by comparing 27 police departments in Serbia.

Environmental life cycle assessments of producing maize, grass-clover, ryegrass and winter wheat straw for biorefinery

The aim of this study is to assess the potential environmental impacts of producing maize, grass-clover, ryegrass, and straw from winter wheat as biomass feedstocks for biorefinery. The Life Cycle Assessment (LCA) method included the following impact categories: Global Warming Potential (GWP100), Eutrophication Potential (EP), Non-Renewable Energy use (NRE), Potential Fresh Water Ecotoxicity (PFWTox) and Potential Biodiversity Damages (PBD). The results showed that GWP100 (in kg CO2 eq, including contribution from soil carbon change) for producing 1 ton of dry matter (t DM) was highest for ryegrass, grass-clover and maize, and lowest for straw. The carbon footprints of ryegrass, grass-clover and maize were affected by including the contribution from soil organic carbon (SOC) changes. Nitrous oxide emissions and emissions related to the production of agro-chemicals (including N-fertilizer) were other hotspots in the carbon footprint. The EP calculated per t DM was highest for grass-clover, ryegrass and maize, and was lowest for straw. NRE use (MJ eq/t DM) was highest for ryegrass, grass-clover and maize and lowest for straw. Major hotspots were diesel use for field operations and agro-chemicals production. The PBD, expressed as Potentially Disappeared Fraction (PDF) showed the highest adverse impact to biodiversity in maize, followed by straw, whereas the results showed relatively lower impact for ryegrass and grass-clover. The PFWTox (CTUe/t DM), at farm level was highest for straw, followed by maize, whereas the values were significantly lower for grass-clover and ryegrass. These variations in ranking of the different biomasses productions using different impact categories for environmental performance showed that it is important to consider a wider range of impact categories for assessing environmental sustainability.

Self-organizing maps for analysing pest profiles: Sensitivity analysis of weights and ranks

Self organizing maps for pest profile analysis (SOM PPA) is a quantitative filtering tool aimed to assist pest risk analysis. The main SOM PPA outputs used by risk analysts are species weights and species ranks. We investigated the sensitivity of SOM PPA to changes in input data. Variations in SOM PPA species weights and ranks were examined by creating datasets of different sizes and running numerous SOM PPA analyses. The results showed that species ranks are much less influenced by variations in dataset size than species weights. The results showed SOM PPA should be suitable for studying small datasets restricted to only a few species. Also, the results indicated that minor data pre-processing is needed before analyses, which has the dual benefits of reducing analysis time and modeller-induced bias.

Drug repurposing for glioblastoma based on molecular subtypes

A recent multi-platform analysis by The Cancer Genome Atlas identified four distinct molecular subtypes for glioblastoma (GBM) and demonstrated that the subtypes correlate with clinical phenotypes and treatment responses. In this study, we developed a computational drug repurposing approach to predict GBM drugs based on the molecular subtypes. Our approach leverages the genomic signature for each GBM subtype, and integrates the human cancer genomics with mouse phenotype data to identify the opportunity of reusing the FDA-approved agents to treat specific GBM subtypes. Specifically, we first constructed the phenotype profile for each GBM subtype using their genomic signatures. For each approved drug, we also constructed a phenotype profile using the drug target genes. Then we developed an algorithm to match and prioritize drugs based on their phenotypic similarities to the GBM subtypes. Our approach is highly generalizable for other disorders if provided with a list of disorder-specific genes. We first evaluated the approach in predicting drugs for the whole GBM. For a combined set of approved, potential and off-label GBM drugs, we achieved a median rank of 9.3%, which is significantly higher (p<e-7) than 45.7% for a recent approach that also uses the mouse phenotype data. Then we applied the approach on GBM subtypes. Analysis result shows the variations of enriched pathways, associated phenotypes and prioritized drugs across different subtypes. We ranked the first-line chemotherapy for GBM in different positions for each subtypes, and the rank variation was consistent with the previous finding on different drug responses among subtypes. In summary, this study makes an effort towards translating the molecular stratification into better survival for GBM.

A Novel Survey Tool to Quantify the Degree and Duration of STEMI Regionalization Across California.

California has been a global leader in regionalization efforts for time-critical medical conditions. A total of 33 local emergency medical service agencies (LEMSAs) exist, providing an organized EMS framework across the state for almost 40 years. We sought to develop a survey tool to quantify the degree and duration of ST-elevation myocardial infarction (STEMI) regionalization over the last decade in California. The project started with the development of an 8-question survey tool via a multi-disciplinary expert consensus process. Next, the survey tool was distributed at the annual meeting of administrators and medical directors of California LEMSAs to get responses valid through December, 2014. The first scoring approach was the Total Regionalization Score (TRS) and used answers from all 8 questions. The second approach was called the Core Score, and it focused on only 4 survey questions by assuming that the designation of STEMI Receiving Centers must have occurred at the beginning of any LEMSA's regionalization effort. Scores were ranked and grouped into tertiles. All 33 LEMSAs in California participated in this survey. The TRS ranged from 15 to 162. The Core Score range was much narrower, from 2 to 30. In comparing TRS and Core Score rankings, the top-tertiles were quite similar. More rank variation occurred between mid- and low-tertiles. This study evaluated the degree and duration of STEMI network regionalization from 2004 to 2014 in California, and ranked 33 LEMSAs into tertiles based upon their TRS and their Core Score. Successful application of the 8-item survey and ranking strategies across California suggests that this approach can be used to assess regionalization in other states or countries around the world.

Comparative efficacy of disease-modifying therapies for patients with relapsing remitting multiple sclerosis: Systematic review and network meta-analysis

IntroductionRandomised studies have demonstrated efficacy of disease-modifying therapies in relapsing remitting multiple sclerosis (RRMS). However it is unclear how the magnitude of treatment efficacy varies across all currently available therapies. ObjectiveTo perform a systematic review and network meta-analysis to evaluate the comparative efficacy of available therapies in reducing relapses and disability progression in RRMS. MethodsA systematic review identified 28 randomised, placebo-controlled and direct comparative trials. A network meta-analysis was conducted within a Bayesian framework to estimate comparative annualised relapse rates (ARR) and risks of disability progression (defined by both a 3-month, and 6-month confirmation interval). Potential sources of treatment-effect modification from study-level covariates and baseline risk were evaluated through meta-regression methods. The Surface Under the Cumulative RAnking curve (SUCRA) method was used to provide a ranking of treatments for each outcome. ResultsThe magnitude of ARR reduction varied between 15–36% for all interferon-beta products, glatiramer acetate and teriflunomide, and from 50 to 69% for alemtuzumab, dimethyl fumarate, fingolimod and natalizumab. The risk of disability progression (3-month) was reduced by 19–28% with interferon-beta products, glatiramer acetate, fingolimod and teriflunomide, by 38–45% for pegylated interferon-beta, dimethyl fumarate and natalizumab and by 68% with alemtuzumab. Broadly similar estimates for the risk of disability progression (6-month), with the exception of interferon-beta-1b 250mcg which was much more efficacious based on this definition. Alemtuzumab and natalizumab had the highest SUCRA scores (97% and 95% respectively) for ARR, while ranking for disability progression varied depending on the definition of the outcome. Interferon-beta-1b 250mcg ranked among the most efficacious treatments for disability progression confirmed after six months (92%) and among the least efficacious when the outcome was confirmed after three months (30%). No significant modification of relative treatment effects was identified from study-level covariates or baseline risk. ConclusionCompared with placebo, clear reductions in ARR with disease-modifying therapies were accompanied by more uncertain changes in disability progression. The magnitude of the reduction and the uncertainty associated with treatment effects varied between DMTs. While natalizumab and alemtuzumab demonstrated consistently high ranking across outcomes, with older interferon-beta and glatiramer acetate products ranking lowest, variation in disability progression definitions lead to variation in the relative ranking of treatments. Rigorously conducted comparative studies are required to fully evaluate the comparative treatment effects of disease modifying therapies for RRMS.

Teaching across the continuum: variations in rankings and valued teaching components between surgery residents and medical students

BackgroundSurgical faculty teach medical students and residents within the same environment; however, each group may require different teaching methods. The aim of this study was to identify teaching components valued by these sets of learners. MethodsTeaching evaluations for 43 surgical faculty members who received yearly evaluations from students and residents were analyzed. Highest and lowest ranked educators in medical student evaluations were traced to corresponding rankings in resident evaluations. Thematic analysis was conducted on written comments. ResultsEducators rated the highest in the medical student group were spread out among the residents' rankings, with several educators being rated the lowest. Similar patterns were observed in reverse for faculty rated highly by residents. ConclusionsResidents and medical students value faculty teaching using different criteria, with residents more focused on operative autonomy and medical students focused on approachability. Using one group to define best teaching methods is insufficient as learners value different optimal attributes.

Identifying and Explaining Organizational Cultures in the Public Sector: A Study of the Australian Public Service Using the Interaction Ritual Theory of Randall Collins

This article identifies and explains different cultures within the Australian Public Service (APS) using the interaction ritual (IR) theory of Randall Collins. It argues that such cultures vary along two dimensions: power and status. On the power dimension, we may distinguish three cultures: that of the order givers, that of the order takers, and that of those who both give and take orders. On the status dimension, we may distinguish localistic and cosmopolitan cultures. Cultural differences on these two dimensions are associated with variations in organizational rank, educational levels, agency tasks, relationships with clients, and central versus regional office location.

Dyson’s ranks and Appell–Lerch sums

Denote by $p(n)$ the number of partitions of $n$ and by $N(a,M;n)$ the number of partitions of $n$ with rank congruent to $a$ modulo $M$. We find and prove a general formula for Dyson's ranks by considering the deviation of the ranks from the average: \begin{equation*} D(a,M) := \sum_{n= 0}^{\infty}\left(N(a,M;n) - \frac{p(n)}{M}\right) q^n. \end{equation*} Using Appell--Lerch sum properties we decompose $D(a,M)$ into modular and mock modular parts so that the mock modular component is supported on certain arithmetic progressions, whose modulus we can control. Using our decomposition, we show how our formula gives as a straightforward consequence Atkin and Swinnerton-Dyer's results on ranks as well as Bringmann, Ono, and Rhoades's results on Maass forms. We also apply our techniques to a variation of Dyson's ranks due to Berkovitch and Garvan.

Comparing the traditional and Multiple Mini Interviews in the selection of post-graduate medical trainees

The traditional, panel style interview and the multiple mini interview (MMI) are two options to use in the selection of medical trainees with each interview format having inherent advantages and disadvantages. Our aim was to compare the traditional and MMI on the same cohort of postgraduate applicants to the Department of Otolaryngology - Head & Neck Surgery at the University of Toronto. Twenty-seven applicants from the 2010 Canadian Residency Matching Service selected for interview at the University of Toronto, Department of Otolaryngology - Head & Neck Surgery were included in the study. Each applicant participated in both a traditional interview and MMI. Traditional interviews marked out of a total maximum score of 570. On the traditional interview, scores ranged from 397-543.5 (69.6 - 95.3%), the mean was 460.2. The MMI maximum score was out of 180. MMI scores ranged from 93 - 146 (51.7 - 81.1%) with a mean of 114.8. Traditional interview total scores were plotted against MMI total scores. Scores correlated reasonably well, Pearson Correlation = 0.315 and is statistically significant at p = 0.001. Inter-interview reliability for the two interview methods was 0.038, with poor overall agreement 0.07%. MMI and traditional interview scores are correlated but do not reliably lead to the same rank order. We have demonstrated that these two interview formats measure different characteristics. One format may also be less reliable leading to greater variation in final rank. Further validation research is certainly required.

Selmer ranks of twists of hyperelliptic curves and superelliptic curves

We study the variation of Selmer ranks of Jacobians of twists of hyperelliptic curves and superelliptic curves. We find sufficient conditions for such curves to have infinitely many twists whose Jacobians have Selmer ranks equal to r, for any given nonnegative integer r. This generalizes earlier results of Mazur–Rubin on elliptic curves.

On the stability of citation-based journal rankings

Abstract The article presents a large-scale comparison of journal rankings based on seven impact measures: Impact Factor (2- and 5-year), SJR, IPP, SNIP, H index, and Article Influence Score. Three aspects of ranking stability in the 2007–2014 period were analyzed: temporal, cross-discipline, and cross-indicator. Impact measures based on five-year citation windows enable more stable journal rankings over time. Journal rankings based on the source-normalized indicator (SNIP) have the largest cross-discipline stability. Journals in the fields of social sciences and humanities have lower temporal and cross-discipline ranking stability compared to those in “hard” sciences. Although correlation coefficients indicate relatively high agreement among the rankings based on different indicators, variations in quartile and percentile ranks suggest different conclusions. WoS journals almost linearly improve their ranking positions in Scopus lists, while many high-impact journals covered by Scopus are not available in WoS. An important element of the ranking stability is the discriminability of impact measures. Beyond the segregation between the top and bottom ranked journals, our assessment of “quality” relies in most cases on a rather arguable assumption that a couple of citations more or less is making a big difference.

Impact of Self-Citations on Impact Factor: A Study Across Disciplines, Countries and Continents

Purpose. The present study is an attempt to find out the impact of self-citations on Impact Factor (IF) across disciplines. The study examines the number of research articles published across 27 major subject fields covered by SCImago, encompassing as many as 310 sub-disciplines. The study evaluates aspects like percentage of self-citations across each discipline, leading self-citing countries and continents, and the impact of self-citation on their IF. Scope. The study is global in nature, as it evaluates the trend of self-citation and its impact on IF of all the major subject disciplines of the world, along with countries and continents. IF has been calculated for the year 2012 by analyzing the articles published during the years 2010 and 2011. Methodology/Approach. The study is empirical in nature; as such, statistical and mathematical tools and techniques have been employed to work out the distribution across disciplines. The evaluation has been purely under-taken on the secondary data, retrieved from SCImago Journal and Country Ranking. Findings. Self-citations play a very significant part in inflating IF. All the subject fields under study are influenced by the practice of self-citation, ranging from 33.14% to 52.38%. Compared to the social sciences and the humanities, subject fields falling under the purview of pure and applied sciences have a higher number of self-citations, but a far lesser percentage than the social sciences and humanities. Upon excluding self-citations, a substantial amount of change was observed in the IF of subject fields under study, as 18 (66.66%) out of 27 subjects fields faced shuffle in their rankings. Variation in rankings based on IF with and without self-citation was observed at subject level, country level, and continental level.

Rank diversity of languages: generic behavior in computational linguistics.

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.

Mobility of Top Incomes inGermany

I analyzeGerman top income mobility using micro‐level panel data of personal income tax returns which are highly representative for top income taxpayers for the years 2001–06. Top income mobility is assessed in three dimensions: (i) persistence in top income fractiles and its stability over time, (ii) measures of individual mobility that are not dependent on the fractile size: the degree of mobility between equally sized groups and mobility in ranks, and (iii) mobility's impact on top income shares. Persistence in top income fractiles is comparatively high and fairly stable across the analyzed period. Top income recipients are less prone to downward mobility and see less variation in annual ranks than less rich tax units. Mobility's impact on income concentration is moderate. The top percentile's share is reduced by roughly 5 percent over six years.