scholarly journals Preferred Interpersonal Distances: A Global Comparison

2017 ◽  
Vol 48 (4) ◽  
pp. 577-592 ◽  
Author(s):  
Agnieszka Sorokowska ◽  
Piotr Sorokowski ◽  
Peter Hilpert ◽  
Katarzyna Cantarero ◽  
Tomasz Frackowiak ◽  
...  
Keyword(s):  
Reference Data ◽  
Large Data ◽  
Individual Characteristics ◽  
Spatial Behavior ◽  
Data Set ◽  
Future Studies ◽  
Gender Influence ◽  
Global Comparison ◽  
Extensive Analysis ◽  
And Gender

Human spatial behavior has been the focus of hundreds of previous research studies. However, the conclusions and generalizability of previous studies on interpersonal distance preferences were limited by some important methodological and sampling issues. The objective of the present study was to compare preferred interpersonal distances across the world and to overcome the problems observed in previous studies. We present an extensive analysis of interpersonal distances over a large data set ( N = 8,943 participants from 42 countries). We attempted to relate the preferred social, personal, and intimate distances observed in each country to a set of individual characteristics of the participants, and some attributes of their cultures. Our study indicates that individual characteristics (age and gender) influence interpersonal space preferences and that some variation in results can be explained by temperature in a given region. We also present objective values of preferred interpersonal distances in different regions, which might be used as a reference data point in future studies.

The Intersectional Effects of Diverse Elections on Validated Turnout in the 2018 Midterm Elections

2020 ◽  
Vol 73 (4) ◽  
pp. 988-1003 ◽  
Author(s):  
Vladimir E. Medenica ◽  
Matthew Fowler
Keyword(s):  
Voter Turnout ◽  
Racial Diversity ◽  
The United States ◽  
Demographic Information ◽  
Racially Diverse ◽  
Data Set ◽  
Race And Gender ◽  
Gender Influence ◽  
Midterm Elections ◽  
And Gender

The 2018 midterm elections in the United States were unprecedented in their gender and racial diversity. Voters across the country, especially younger voters, elected the most diverse U.S. Congress in history. Despite increased electoral diversity along lines of gender, race, and the intersections of both, extant literature has remained siloed, focusing on the effect of either gender or race on turnout but rarely examining both in relation to one another. Using a novel data set of racially diverse young adults that includes demographic information for congressional candidates and vote-validated data, this study investigates how the intersection of race and gender influence voter turnout across diverse electoral contexts. Our study provides important insights for both unpacking the 2018 elections and more generally understanding how race and gender interact to influence youth voter turnout as candidate profiles and electoral contexts continue to diversify.

scholarly journals Analysis of Changes in Parathyroid Hormone and 25 (OH) Vitamin D Levels with Respect to Age, Gender and Season: A Data Mining Study

2017 ◽  
Vol 36 (1) ◽  
pp. 73-83 ◽  
Author(s):  
Muhittin A. Serdar ◽  
Başar Batu Can ◽  
Meltem Kilercik ◽  
Zeynep A. Durer ◽  
Fehime Benli Aksungar ◽  
...  
Keyword(s):  
Vitamin D ◽  
Parathyroid Hormone ◽  
Vitamin D Deficiency ◽  
Large Data ◽  
Seasonal Effects ◽  
Data Set ◽  
Vitamin D Levels ◽  
25 Oh Vitamin D ◽  
And Gender ◽  
Opposite Response

SummaryBackground:25 (OH) vitamin D3 (25(OH)D) and parathyroid hormone (PTH) are important regulators of calcium homeostasis. The aim of this study was to retrospectively determine the cut–off for sufficient 25(OH)D in a four-season region and the influence of age, seasons, and gender on serum 25(OH)D and PTH levels.Methods:Laboratory results of 9890 female and 2723 male individuals aged 38.8±22.1 years who had simultaneous measurements of 25(OH)D and PTH were retrospectively analyzed by statistical softwares. Serum 25(OH)D and PTH levels were measured by a mass spectrometry method and by an electrochemiluminescence immunoassay, respectively.Results:Mean serum 25(OH)D levels showed a sinusoidal fluctuation throughout the year and were significantly (p<0.01) higher in summer and autumn. On the other hand, PTH levels were significantly higher (p<0.01) in women and showed an opposite response to seasonal effects relative to 25(OH)D. Lowest levels of 25(OH)D were detected in people aged between 20 and 40 years whereas PTH hormone levels were gradually increasing in response to aging. The significant exponential inverse relationship that was found between PTH and 25(OH)D (PTH=exp(4.12–0.064*sqrt(25(OH)D)) (r=−0.325, R–squared=0.105, p<0.001)) suggested that the cut–off for sufficient 25(OH)D should be 75 nmol/L.Conclusions:Our retrospective study based on large data set supports the suitability of the currently accepted clinical cut–off of 75 nmol/L for sufficient 25(OH)D. However, the issue of assessing Vitamin D deficiency remains difficult due to seasonal variations in serum 25(OH)D. Therefore, PTH measurements should complement 25(OH)D results for diagnosing Vitamin D deficiency. It is imperative that seasonally different criteria should be considered in future.

scholarly journals #METOO AND INTERSECTIONALISM: "RADICAL COMMUNITY HEALING" OR "VOYEURISTIC TRAUMA PORN?"

2019 ◽  
Vol 2019 ◽  
Author(s):  
Verity Trott
Keyword(s):  
Sexual Abuse ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
White Women ◽  
Large Data ◽  
Data Set ◽  
Mainstream Media ◽  
And Gender ◽  
The Many

In October 2017, millions of people reflected on their experiences of sexual abuse and harassment, publicly sharing their testimonials in an expression of global vulnerability using the hashtag #MeToo. Many of the tweets portrayed the angst and distress individuals experienced in their decision to participate, indicating the psychological costs of engaging with #MeToo. Further, some tweets expressed frustration at the re-appropriated nature of the campaign and the collective feeling of an “intersectional betrayal” by white women and feminists who dominated the mainstream media reporting of the movement. This research foregrounds the intersectional concerns that result from the scale and reach of the millions of testimonials suspended online that constitute the #MeToo movement. It highlights how the many stories that have circulated the online sphere obscure the absence and recognition of marginalised women and those who are already more vulnerable in regards to experiencing sexual assault. The paper adopts an intersectional framework, as conceptualised by Crenshaw (1991), to further an understanding of how race, class, and gender collide and how subordination can be reproduced within feminist protests. Drawing on a large data set of tweets, this research combines content, discourse and social network analysis to examine the narratives related to participation. The paper highlights the experiences and reflections of users who self-identified as queer, disabled, or a person of colour within their tweets. A social network analysis is also used to visualise a snapshot of the affective publics that arose at the beginning and to illustrate how systems of oppression converge.

Prevalence Estimates of Adult Chronic Idiopathic Thrombocytopenic Purpura (ITP) in the United States.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3202-3202 ◽  
Author(s):  
Maurilee A. Feudjo-Tepie ◽  
Noah J. Robinson ◽  
Dimitri Bennett
Keyword(s):  
Large Data ◽  
The United States ◽  
Published Data ◽  
Age Group ◽  
Data Set ◽  
Age And Gender ◽  
Chronic Itp ◽  
Prevalence Estimates ◽  
The Us ◽  
And Gender

Abstract ITP is a disease caused by inadequate platelet production as well as increased platelet destruction. Literature on the epidemiology of ITP is currently sparse and the disease remains poorly described. Based on previous reviews, the overall incidence of ITP among adults ranges from 1.6 to 3.0 per 100,000 person years of observation (PYO); prevalence estimates range from 2.1 to approximately 36.4 per 100,000 persons (Neylon AJ et al., Br J Haematol. 2003; Satia J et al., Eur Hematol Assoc. [poster presentation] 2006; Deitz AC et al., Blood. 2006). In this study, the objective was to estimate the prevalence of adult chronic ITP (in 2005) stratified by age and gender using a large US claims database (Integrated Healthcare Information Services, IHCIS). IHCIS comprises over 70 million patients from 45 health plans. Adult chronic ITP cases were defined as patients with at least two diagnoses (ICD-9 code 287.3) for primary thrombocytopenia separated by at least 6 months between 2002 and 2006, and age 18 or older in 2004. Although ICD-9 code 287.3 is not exclusive to ITP, its sensitivity and specificity are likely to be high (Segal et al., Am J Hem. 2004). A patient’s first identified 287.3 ICD-9 code over the period 2002–2006 had to be in 2004 or earlier and the last one in 2004 or later. Patients had to have continuous enrollment throughout the year 2004. We estimated the 2004 prevalence as the total number of identified chronic ITP cases divided by the total population in the database in 2004 stratified by age group and gender. Estimates of adult cases for the US population were obtained by multiplying the 2004 prevalence estimates by the 2005 adult US census population estimates. The estimated adult prevalence was 23.6 [95% CI 23.4 – 23.8] per 100,000 persons, translating to approximately 52,700 (95% CI 52,200 – 53,100) adult chronic ITP cases in the US. Females had higher prevalence than males (28.1 vs 18.8 per 100,000). In addition, prevalence increased with age (from 17.0 in the age group 18–49 to 36.2 in the age group 65 and older). These results are broadly similar to previously published data and help to better understand the epidemiology of chronic ITP. While the tight CIs predominantly reflect the large data set rather than the precision of the estimates, we believe these data are among the most robust estimates of ITP prevalence and are the first to specifically estimate adult chronic ITP prevalence by age and gender in the US.

Religiosity, Denomination, and Mental Health among Young Men and Women

1993 ◽  
Vol 72 (3_suppl) ◽  
pp. 1157-1158 ◽  
Author(s):  
Larry C. Jensen ◽  
Janet Jensen ◽  
Terrie Wiederhold
Keyword(s):  
Mental Health ◽  
Large Data ◽  
Self Esteem ◽  
Religious Groups ◽  
Data Set ◽  
Emotional Maturity ◽  
Health Measures ◽  
Mormon Women ◽  
And Gender ◽  
Main Effects

The relations among religiosity, denomination, and mental health were studied. Comparisons of groups high, medium, and low in religiosity were made possible by extracting data from a large data set for three denominational groups and gender in a three-way analysis of variance design. There were significant main effects, with higher scores on three mental health measures for high religious groups, Mormons, and men. There were interactions resulting from highly religious Mormon women, but not highly religious Mormon men scoring higher. The three scores were self-esteem, emotional maturity, and nondepression.

Some statistical and CI models to predict chaotic high-frequency financial data

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Methodological Approach ◽  
Back Propagation ◽  
Large Data ◽  
Series Data ◽  
Data Set ◽  
Training Time ◽  
Optimal Population ◽  
Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

To The Problem Of Researching Individual Concepts In Author’s Texts

2020 ◽  
Vol 6 (1) ◽  
pp. 6-19
Author(s):  
Nadezhda V. Razumkova
Keyword(s):  
Intercultural Communication ◽  
Semantic Space ◽  
Individual Characteristics ◽  
Literary Translation ◽  
Anthropological Linguistics ◽  
Individual Concepts ◽  
And Gender ◽  
Further Development ◽  
Aesthetic Values ◽  
Individual Style

This article reviews the text concept studies on the material of a Russian poem and its translation into Chinese within the framework of the anthropological linguistics. The study of individual concepts, embodying the ethical and aesthetic values of a creative person, is relevant and promising for the further development of establishing their role in the implementation of a writer’s individual style in translation. The author analyzes the lexical-semantic space, which implements a fragment of the content of the universal concept of HOME, presented in the original and translated texts. The author presents a linguistic experiment carried out among Chinese students. Its purpose was to consider the cognitive (indicative, figurative, and situational) basis of the content of the translation and the degree of its compliance with the author’s intention. The tasks include the description of translation transformations as well as interpretation of the mental reactions of Chinese respondents. The results obtained indicate that the author’s representation of the HOME concept is achieved through the use of cognitive structures, associated with Russian traditional views. The representation of the discursive concept by interpreters is accompanied by cognitive refraction in terms of the associative development of thoughts. Literary translation is seen as an indirect act of intercultural communication, the subjects of which — the author, translator, and reader — have a set of individual characteristics, lining up on the principle of following an ethnic cultural standard to individual-emotional and gender marked manifestations.

In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning

2019 ◽  
Vol 21 (9) ◽  
pp. 662-669 ◽  
Author(s):  
Junnan Zhao ◽  
Lu Zhu ◽  
Weineng Zhou ◽  
Lingfeng Yin ◽  
Yuchen Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Regression Tree ◽  
Large Data ◽  
Thrombin Inhibitors ◽  
Coagulation Cascade ◽  
Gradient Boosting ◽  
Support Vector ◽  
Data Set ◽  
Descriptor Selection

Background: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors. Method: This study was carried out to predict Ki values of thrombin inhibitors based on a large data set by using machine learning methods. Taking advantage of finding non-intuitive regularities on high-dimensional datasets, machine learning can be used to build effective predictive models. A total of 6554 descriptors for each compound were collected and an efficient descriptor selection method was chosen to find the appropriate descriptors. Four different methods including multiple linear regression (MLR), K Nearest Neighbors (KNN), Gradient Boosting Regression Tree (GBRT) and Support Vector Machine (SVM) were implemented to build prediction models with these selected descriptors. Results: The SVM model was the best one among these methods with R2=0.84, MSE=0.55 for the training set and R2=0.83, MSE=0.56 for the test set. Several validation methods such as yrandomization test and applicability domain evaluation, were adopted to assess the robustness and generalization ability of the model. The final model shows excellent stability and predictive ability and can be employed for rapid estimation of the inhibitory constant, which is full of help for designing novel thrombin inhibitors.

scholarly journals Correlation between the structure and skin permeability of compounds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ruolan Zeng ◽  
Jiyong Deng ◽  
Limin Dang ◽  
Xinliang Yu
Keyword(s):  
Large Data ◽  
Qsar Model ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Skin Permeability ◽  
Data Set ◽  
Test Set ◽  
Svm Algorithm ◽  
Svm Model ◽  
Toxicity Relationship

AbstractA three-descriptor quantitative structure–activity/toxicity relationship (QSAR/QSTR) model was developed for the skin permeability of a sufficiently large data set consisting of 274 compounds, by applying support vector machine (SVM) together with genetic algorithm. The optimal SVM model possesses the coefficient of determination R2 of 0.946 and root mean square (rms) error of 0.253 for the training set of 139 compounds; and a R2 of 0.872 and rms of 0.302 for the test set of 135 compounds. Compared with other models reported in the literature, our SVM model shows better statistical performance in a model that deals with more samples in the test set. Therefore, applying a SVM algorithm to develop a nonlinear QSAR model for skin permeability was achieved.

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 $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

Sign in / Sign up

Export Citation Format

Share Document