scholarly journals General patterns of sexual dimorphism in graylings (Thymallus), with a comparison to other salmonid species

2021 ◽  
Author(s):  
Gernot K. Englmaier ◽  
Alexander Antonov ◽  
Steven J. Weiss
Keyword(s):  
Sexual Dimorphism ◽  
Large Scale ◽  
Phylogenetic Signal ◽  
Morphological Variability ◽  
Data Set ◽  
Research Attention ◽  
Morphometric Characters ◽  
Phenotypic Characters ◽  
Salmonid Species ◽  
Iteroparous Species

AbstractAmong fishes, salmonids (family Salmonidae) have attracted a great deal of research attention focused on sexual dimorphism and associated selective forces. Most of this research has been directed toward anadromous and mostly semelparous salmon and trout (Oncorhynchus, Salmo), and comparatively little is known about intersexual variability in strictly iteroparous freshwater salmonids. We examined a comprehensive data set of 28 linear morphometric characters in 11 of 15 currently recognised species of grayling (Thymallinae, Thymallus), a genus consisting of iteroparous species only, to identify general patterns of intersexual morphological variability. Overall, we found that all grayling species show common sex-specific traits particularly relating to size dimensions of the dorsal, anal, pelvic and pectoral fins. Although the magnitude of sexual dimorphism differed among species, there was no significant phylogenetic signal associated with these differences across the genus. These results are discussed in terms of the assumed selection pressures driving sexual dimorphism in graylings and are compared to existing knowledge in Salmonidae as a whole where similarities and differences with both Salmoninae and Coregoninae exist. The present study provides the first detailed genus-wide comparison of sexually dimorphic phenotypic characters in graylings, and highlights the need for more large-scale comparative studies in multiple salmonid species to better understand general macroevolutionary trends among this important group of freshwater fishes.

scholarly journals A Total-Evidence Dated Phylogeny of Echinoidea Combining Phylogenomic and Paleontological Data

2020 ◽  
Author(s):  
Nicolás Mongiardino Koch ◽  
Jeffrey R Thompson
Keyword(s):  
Large Scale ◽  
Sea Urchins ◽  
Phylogenetic Signal ◽  
Total Evidence ◽  
Morphological Data ◽  
Data Sets ◽  
Crown Group ◽  
Data Set ◽  
Paleontological Data ◽  
Time Calibration

Abstract Phylogenomic and paleontological data constitute complementary resources for unraveling the phylogenetic relationships and divergence times of lineages, yet few studies have attempted to fully integrate them. Several unique properties of echinoids (sea urchins) make them especially useful for such synthesizing approaches, including a remarkable fossil record that can be incorporated into explicit phylogenetic hypotheses. We revisit the phylogeny of crown group Echinoidea using a total-evidence dating approach that combines the largest phylogenomic data set for the clade, a large-scale morphological matrix with a dense fossil sampling, and a novel compendium of tip and node age constraints. To this end, we develop a novel method for subsampling phylogenomic data sets that selects loci with high phylogenetic signal, low systematic biases, and enhanced clock-like behavior. Our results demonstrate that combining different data sources increases topological accuracy and helps resolve conflicts between molecular and morphological data. Notably, we present a new hypothesis for the origin of sand dollars, and restructure the relationships between stem and crown echinoids in a way that implies a long stretch of undiscovered evolutionary history of the crown group in the late Paleozoic. Our efforts help bridge the gap between phylogenomics and phylogenetic paleontology, providing a model example of the benefits of combining the two. [Echinoidea; fossils; paleontology; phylogenomics; time calibration; total evidence.]

Data Challenges in Development of a Regional Assignment: Simulation Model to Evaluate Transit Signal Priority in Chicago

2003 ◽  
Vol 1841 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Elaine Chang ◽  
Athanasios Ziliaskopoulos
Keyword(s):  
Real World ◽  
Large Scale ◽  
Dynamic Traffic Assignment ◽  
Simulation Models ◽  
Data Sets ◽  
Transit Signal Priority ◽  
Data Set ◽  
Research Attention ◽  
Large Scale Simulation ◽  
Regional Assignment

Recent years have seen major advances in the field of simulation-based dynamic traffic assignment (DTA), resulting in the development of DTA software packages capable of simulating real-world networks. However, simulation of such networks requires not only sophisticated algorithms and software, but also large and detailed data sets. Although algorithmic and software-related issues in large-scale DTA development have received considerable research attention, there is little reported experience with the data-related challenges in real-world applications of large-scale simulation models. There were challenges in using a large-scale simulation-assignment model for evaluation of transit signal priority (TSP) in the Chicago, Illinois, region. Relevant impacts of TSP are described, to provide a framework for comparing simulation approaches and data sets. The practice of using microsimulation models to evaluate TSP impacts on short corridors is compared with that of using regional assignment-simulation approaches, with an emphasis on TSP impacts that can be captured and observed with each one of the approaches. The data sets used for the regional Chicago TSP study are then described, along with assumptions made to adapt each data set to the task of regional time-dependent simulation.

ProGen:Provenance database generator for large-scale data set

2009 ◽  
Vol 28 (11) ◽  
pp. 2737-2740
Author(s):  
Xiao ZHANG ◽  
Shan WANG ◽  
Na LIAN
Keyword(s):  
Large Scale ◽  
Data Set ◽  
Large Scale Data ◽  
Scale Data

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

scholarly journals Relationship between large-scale ionospheric field-aligned currents and electron/ion precipitations: DMSP observations

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Chao Xiong ◽  
Claudia Stolle ◽  
Patrick Alken ◽  
Jan Rauberg
Keyword(s):  
Time Distribution ◽  
Large Scale ◽  
Particle Flux ◽  
Particle Energy ◽  
Lower Latitude ◽  
Particle Precipitation ◽  
Data Set ◽  
The Mean ◽  
Two Parameters ◽  
Meteorological Satellite

Abstract In this study, we have derived field-aligned currents (FACs) from magnetometers onboard the Defense Meteorological Satellite Project (DMSP) satellites. The magnetic latitude versus local time distribution of FACs from DMSP shows comparable dependences with previous findings on the intensity and orientation of interplanetary magnetic field (IMF) By and Bz components, which confirms the reliability of DMSP FAC data set. With simultaneous measurements of precipitating particles from DMSP, we further investigate the relation between large-scale FACs and precipitating particles. Our result shows that precipitation electron and ion fluxes both increase in magnitude and extend to lower latitude for enhanced southward IMF Bz, which is similar to the behavior of FACs. Under weak northward and southward Bz conditions, the locations of the R2 current maxima, at both dusk and dawn sides and in both hemispheres, are found to be close to the maxima of the particle energy fluxes; while for the same IMF conditions, R1 currents are displaced further to the respective particle flux peaks. Largest displacement (about 3.5°) is found between the downward R1 current and ion flux peak at the dawn side. Our results suggest that there exists systematic differences in locations of electron/ion precipitation and large-scale upward/downward FACs. As outlined by the statistical mean of these two parameters, the FAC peaks enclose the particle energy flux peaks in an auroral band at both dusk and dawn sides. Our comparisons also found that particle precipitation at dawn and dusk and in both hemispheres maximizes near the mean R2 current peaks. The particle precipitation flux maxima closer to the R1 current peaks are lower in magnitude. This is opposite to the known feature that R1 currents are on average stronger than R2 currents.

scholarly journals Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

2020 ◽  
Vol 37 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Large Scale ◽  
Spiral Galaxies ◽  
Hubble Space Telescope ◽  
Gravitational Interaction ◽  
Large Data ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Dipole Axis ◽  
Data Set ◽  
The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

scholarly journals Is the Genotype-Phenotype Map Modular?: A Statistical Approach Using Mouse Quantitative Trait Loci Data

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 305-311 ◽  
Author(s):  
Jason G Mezey ◽  
James M Cheverud ◽  
Günter P Wagner
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Statistical Approach ◽  
Genetic Effects ◽  
Statistical Distribution ◽  
Data Set ◽  
Alveolar Region ◽  
Phenotypic Characters ◽  
Statistical Support ◽  
Complex Characters

Abstract Various theories about the evolution of complex characters make predictions about the statistical distribution of genetic effects on phenotypic characters, also called the genotype-phenotype map. With the advent of QTL technology, data about these distributions are becoming available. In this article, we propose simple tests for the prediction that functionally integrated characters have a modular genotype-phenotype map. The test is applied to QTL data on the mouse mandible. The results provide statistical support for the notion that the ascending ramus region of the mandible is modularized. A data set comprising the effects of QTL on a more extensive portion of the phenotype is required to determine if the alveolar region of the mandible is also modularized.

scholarly journals COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis

2021 ◽  
pp. 1-13
Author(s):  
Usman Naseem ◽  
Imran Razzak ◽  
Matloob Khushi ◽  
Peter W. Eklund ◽  
Jinman Kim
Keyword(s):  
Sentiment Analysis ◽  
Large Scale ◽  
Data Set ◽  
Twitter Data

Distributed learning with indefinite kernels

2019 ◽  
Vol 17 (06) ◽  
pp. 947-975 ◽  
Author(s):  
Lei Shi
Keyword(s):  
Large Scale ◽  
Substantial Reduction ◽  
Computation Time ◽  
Distributed Learning ◽  
Rates Of Convergence ◽  
Regression Problem ◽  
Data Set ◽  
Regularization Scheme ◽  
Original Algorithm ◽  
Indefinite Kernel

We investigate the distributed learning with coefficient-based regularization scheme under the framework of kernel regression methods. Compared with the classical kernel ridge regression (KRR), the algorithm under consideration does not require the kernel function to be positive semi-definite and hence provides a simple paradigm for designing indefinite kernel methods. The distributed learning approach partitions a massive data set into several disjoint data subsets, and then produces a global estimator by taking an average of the local estimator on each data subset. Easy exercisable partitions and performing algorithm on each subset in parallel lead to a substantial reduction in computation time versus the standard approach of performing the original algorithm on the entire samples. We establish the first mini-max optimal rates of convergence for distributed coefficient-based regularization scheme with indefinite kernels. We thus demonstrate that compared with distributed KRR, the concerned algorithm is more flexible and effective in regression problem for large-scale data sets.

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