Data and visual displays in the Journal of Ecology 1996–2016

2020 ◽  
pp. 147387162098012
Author(s):  
Alon Friedman
Keyword(s):  
Best Practices ◽  
Pearson Correlation ◽  
Single Species ◽  
Data Type ◽  
Reliability Test ◽  
Visual Displays ◽  
Domain Type ◽  
Academic Publications ◽  
The Creation ◽  
The Impact

Scholars in scientific disciplines face unique challenges in the creation of visualizations, especially in publications that require insights derived from analyses to be visually displayed. The literature on visualizations describes different techniques and best practices for the creation of graphs. However, these techniques have not been used to evaluate the impact of visualizations in academic publications. In the field of ecology, as in other scientific fields, graphs are an essential part of journal articles. Little is known about the connections between the kind of data presented and domain in which the researchers conducted their study that together produces the visual graphics. This study focused on articles published in the Journal of Ecology between 1996 and 2016 to explore possible connections between data type, domain, and visualization type. Specifically, this study asked three questions: How many of the graphics published between 1996 and 2016 follow a particular set of recommendations for best practices? What can Pearson correlations reveal about the relationships between type of data, domain of study, and visual displays? Can the findings be examined through an inter-reliability test lens? Out of the 20,080 visualizations assessed, 54% included unnecessary graphical elements in the early part of the study (1996–2010). The most common type of data was univariate (35%) and it was often displayed using line graphs. Twenty-one percent of the articles in the period studied could be categorized under the domain type “single species.” Pearson correlation analysis showed that data type and domain type was positively correlated ( r = 0.08; p ≤ 0.05). Cohen’s kappa for the reliability test was 0.86, suggesting good agreement between the two categories. This study provides evidence that data type and domain types are equally important in determining the type of visualizations found in scientific journals.

scholarly journals The Impact of Extrinsic Motivation on Employees’ Performance: A Comparative Analysis of Food and Textile Industries in Sindh, Pakistan

2018 ◽  
Vol 11 (12) ◽  
pp. 61
Author(s):  
Sumra Haleem Shaikh ◽  
Saima Kamran Pathan ◽  
Imamuddin Khoso
Keyword(s):  
Extrinsic Motivation ◽  
Pearson Correlation ◽  
Reliability Test ◽  
Extrinsic Factors ◽  
Independent Variables ◽  
Regression Techniques ◽  
Pearson Correlation Analysis ◽  
Textile Industries ◽  
Amount Of Knowledge ◽  
The Impact

The purpose of present study is to examine the effects of external motivational factors on employees. Current study is employed Herzberg’s two-factor theory to investigate the effects of extrinsic factors on employees’ performance.in food and textile industries of Sindh, Pakistan. Seven point Likert scale is used for survey purpose. Reliability test is conducted for knowing the internal consistency of extrinsic factors as independent variables and employees’ performance as dependent variable. Pearson correlation, Analysis Of Variance (ANOVA), t test and multiple regression techniques are employed for data analysis.The results found that all extrinsic factors have positive and significant effects on employees. This study provides good amount of knowledge on the importance of extrinsic factors for improving the employees’ performance.

Trading faces: Complete AI face doubles avoid the uncanny valley

2020 ◽  
Author(s):  
Christopher Welker ◽  
David France ◽  
Alice Henty ◽  
Thalia Wheatley
Keyword(s):  
Artificial Intelligence ◽  
Sexual Orientation ◽  
Uncanny Valley ◽  
Torture Survivors ◽  
The Uncanny ◽  
The Creation ◽  
Full Face ◽  
The Impact

Advances in artificial intelligence (AI) enable the creation of videos in which a person appears to say or do things they did not. The impact of these so-called “deepfakes” hinges on their perceived realness. Here we tested different versions of deepfake faces for Welcome to Chechnya, a documentary that used face swaps to protect the privacy of Chechen torture survivors who were persecuted because of their sexual orientation. AI face swaps that replace an entire face with another were perceived as more human-like and less unsettling compared to partial face swaps that left the survivors’ original eyes unaltered. The full-face swap was deemed the least unsettling even in comparison to the original (unaltered) face. When rendered in full, AI face swaps can appear human and avoid aversive responses in the viewer associated with the uncanny valley.

Automated system for creating training programs for mass professional users

2020 ◽  
pp. 21-27
Author(s):  
V.K. Grigoriev ◽  
A.A. Biryukova ◽  
A. Yu. Volk ◽  
A.S. Ilyushechkin
Keyword(s):  
Experimental Verification ◽  
Training Programs ◽  
Automated System ◽  
Software Product ◽  
Learning Programs ◽  
E Learning ◽  
The Creation ◽  
The Impact

The article discusses the automation of the creation and use of e-learning programs. The impact of automating the learning of a large number of users on the effectiveness of the introduction of a new software product is analyzed. The methods and algorithms that increase the efficiency of creating electronic training programs on example of the author’s automated system “Tutor Builder” are described. The results of experimental verification of the automated system are provided.

Strategic Audit Inquiry: The Impact of Timing and the Promotion of Statutory Protections on Client Fraud Disclosures

2020 ◽  
Vol 34 (3) ◽  
pp. 153-167
Author(s):  
John R. Lauck ◽  
Stephen J. Perreault ◽  
Joseph R. Rakestraw ◽  
James S. Wainberg
Keyword(s):  
Best Practices ◽  
Audit Quality ◽  
Self Regulation ◽  
Data Availability ◽  
Audit Committees ◽  
External Auditors ◽  
Extant Literature ◽  
Psychological Theories ◽  
Inquiry Process ◽  
The Impact

SYNOPSIS Auditing standards require external auditors to inquire of client-employees regarding their knowledge of actual or suspected fraud (PCAOB 2010b; AICPA 2016). However, the extant literature provides little guidance on practical methods that auditors can employ to increase the likelihood of fraud disclosure and improve audit quality. Drawing upon best practices in the whistleblowing literature and psychological theories on self-regulation, we experimentally test the efficacy of two practical strategies that auditors can employ during the fraud inquiry process: actively promoting statutory whistleblower protections and strategically timing their fraud inquiries. Our results indicate that auditors are more likely to elicit client-employee fraud disclosures by actively promoting statutory whistleblower protections and strategically timing the fraud inquiry to take place in the afternoon, when client-employee self-regulation is more likely to be depleted. These two audit inquiry strategies should be of considerable interest to audit practitioners, audit committees, and those concerned with improving audit quality. Data Availability: From the authors by request.

scholarly journals Best practices on the differential expression analysis of multi-species RNA-seq

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Matthew Chung ◽  
Vincent M. Bruno ◽  
David A. Rasko ◽  
Christina A. Cuomo ◽  
José F. Muñoz ◽  
...  
Keyword(s):  
Best Practices ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Single Species ◽  
Rna Seq ◽  
Species Analysis ◽  
Differential Gene ◽  
Multiple Species ◽  
Downstream Analysis

AbstractAdvances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

scholarly journals Towards Including Dynamic Vegetation Parameters in the EUMETSAT H SAF ASCAT Soil Moisture Products

2021 ◽  
Vol 13 (8) ◽  
pp. 1463
Author(s):  
Susan C. Steele-Dunne ◽  
Sebastian Hahn ◽  
Wolfgang Wagner ◽  
Mariette Vreugdenhil
Keyword(s):  
Soil Moisture ◽  
Interannual Variability ◽  
Incidence Angle ◽  
Pearson Correlation ◽  
The United States ◽  
Research Network ◽  
Window Width ◽  
High Frequency Variability ◽  
Vegetation Parameters ◽  
The Impact

The TU Wien Soil Moisture Retrieval (TUW SMR) approach is used to produce several operational soil moisture products from the Advanced Scatterometer (ASCAT) on the Metop series of satellites as part of the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF). The incidence angle dependence of backscatter is described by a second-order Taylor polynomial, the coefficients of which are used to normalize ASCAT observations to the reference incidence angle of 40∘ and for correcting vegetation effects. Recently, a kernel smoother was developed to estimate the coefficients dynamically, in order to account for interannual variability. In this study, we used the kernel smoother for estimating these coefficients, where we distinguished for the first time between their two uses, meaning that we used a short and fixed window width for the backscatter normalisation while we tested different window widths for optimizing the vegetation correction. In particular, we investigated the impact of using the dynamic vegetation parameters on soil moisture retrieval. We compared soil moisture retrievals based on the dynamic vegetation parameters to those estimated using the current operational approach by examining their agreement, in terms of the Pearson correlation coefficient, unbiased RMSE and bias with respect to in situ soil moisture. Data from the United States Climate Research Network were used to study the influence of climate class and land cover type on performance. The sensitivity to the kernel smoother half-width was also investigated. Results show that estimating the vegetation parameters with the kernel smoother can yield an improvement when there is interannual variability in vegetation due to a trend or a change in the amplitude or timing of the seasonal cycle. However, using the kernel smoother introduces high-frequency variability in the dynamic vegetation parameters, particularly for shorter kernel half-widths.

scholarly journals Statistical Analysis and Machine Learning Prediction of Fog-Caused Low-Visibility Events at A-8 Motor-Road in Spain

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 679
Author(s):  
Sara Cornejo-Bueno ◽  
David Casillas-Pérez ◽  
Laura Cornejo-Bueno ◽  
Mihaela I. Chidean ◽  
Antonio J. Caamaño ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Probability Distributions ◽  
Pearson Correlation ◽  
Likelihood Method ◽  
Neural Network Approach ◽  
Event Duration ◽  
Full Characterization ◽  
Low Visibility ◽  
Learning Machine ◽  
The Impact

This work presents a full statistical analysis and accurate prediction of low-visibility events due to fog, at the A-8 motor-road in Mondoñedo (Galicia, Spain). The present analysis covers two years of study, considering visibility time series and exogenous variables collected in the zone affected the most by extreme low-visibility events. This paper has then a two-fold objective: first, we carry out a statistical analysis for estimating the fittest probability distributions to the fog event duration, using the Maximum Likelihood method and an alternative method known as the L-moments method. This statistical study allows association of the low-visibility depth with the event duration, showing a clear relationship, which can be modeled with distributions for extremes such as Generalized Extreme Value and Generalized Pareto distributions. Second, we apply a neural network approach, trained by means of the ELM (Extreme Learning Machine) algorithm, to predict the occurrence of low-visibility events due to fog, from atmospheric predictive variables. This study provides a full characterization of fog events at this motor-road, in which orographic fog is predominant, causing important traffic problems during all year. We also show how the ELM approach is able to obtain highly accurate low-visibility events predictions, with a Pearson correlation coefficient of 0.8, within a half-hour time horizon, enough to initialize some protocols aiming at reducing the impact of these extreme events in the traffic of the A-8 motor road.

scholarly journals An evaluation of the Victorian Salt Reduction Partnership’s advocacy strategy for policy change

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Emalie Rosewarne ◽  
Michael Moore ◽  
Wai-Kwan Chislett ◽  
Alexandra Jones ◽  
Kathy Trieu ◽  
...  
Keyword(s):  
Public Health ◽  
Policy Change ◽  
Action Plan ◽  
Evaluation Framework ◽  
Decision Makers ◽  
Health Advocacy ◽  
Salt Reduction ◽  
Public Health Advocacy ◽  
The Creation ◽  
The Impact

Abstract Background Public health advocacy strategies facilitate policy change by bringing key health issues to the forefront of public and political discourse, influencing decision-makers and public opinion, and increasing policy demand. The Victorian Salt Reduction Partnership (VSRP) was established in 2014 in response to inadequate government action to improve population diets in Australia. This study aimed to evaluate the success of the VSRP’s advocacy strategy in achieving policy change. Methods Documentation of VSRP activities and outputs were collected, and semi-structured interviews conducted as part of a comprehensive process evaluation. For this study, the Kotter Plus 10-step public health advocacy evaluation framework was used to guide data extraction, analysis, and synthesis. Results A sense of urgency for salt reduction was generated by producing evidence and outlining the potential impact of a state-based salt reduction programme. This enabled the creation of a coalition with diverse skills and expertise, which facilitated the development of an innovative and collaborative advocacy action plan. A clear change vision was established, but communication of the vision to decision-makers was lacking, which reduced the impact of the programme as decision-makers were not provided with a clear incentive for policy change. As a result, while programme outputs were achieved, these did not translate to achieving broader strategic goals during a limited-term intervention in a political climate unconcerned with salt. Conclusions The Kotter Plus 10-step framework was a useful tool for evaluating the success of the VSRP advocacy strategy. The framework enabled the identification of key strengths, including the creation of the guiding coalition, and areas where efforts could be improved in future similar strategies, such as effective communication within partnerships and to decision-makers, to better influence policy and improve public health impact.

scholarly journals The Impact of Sustainability Awareness and Moral Values on Environmental Laws

2021 ◽  
Vol 13 (11) ◽  
pp. 5882
Author(s):  
Rita Yi Man Li ◽  
Yi Lut Li ◽  
M. James C. Crabbe ◽  
Otilia Manta ◽  
Muhammad Shoaib
Keyword(s):  
Sustainable Development ◽  
Developing Countries ◽  
Environmental Law ◽  
Developed Countries ◽  
Moral Values ◽  
Web Pages ◽  
Environmental Legislation ◽  
Environmental Laws ◽  
Academic Publications ◽  
The Impact

We argue that environmental legislation and regulation of more developed countries reflects significantly their moral values, but in less developed countries it differs significantly from their moral values. We examined this topic by using the keywords “sustainability” and “sustainable development”, studying web pages and articles published between 1974 to 2018 in Web of Science, Scopus and Google. Australia, Zimbabwe, and Uganda were ranked as the top three countries in the number of Google searches for sustainability. The top five cities that appeared in sustainability searches through Google are all from Africa. In terms of academic publications, China, India, and Brazil record among the largest numbers of sustainability and sustainable development articles in Scopus. Six out of the ten top productive institutions publishing sustainable development articles indexed in Scopus were located in developing countries, indicating that developing countries are well aware of the issues surrounding sustainable development. Our results show that when environmental law reflects moral values for betterment, legal adoption is more likely to be successful, which usually happens in well-developed regions. In less-developed states, environmental law differs significantly from moral values, such that changes in moral values are necessary for successful legal implementation. Our study has important implications for the development of policies and cultures, together with the enforcement of environmental laws and regulations in all countries.

Best Practices for Modeling Egocentric Social Network Data and Health Outcomes

2021 ◽  
pp. 193758672110137
Author(s):  
Jacqueline M. Burgette ◽  
Jacquelin Rankine ◽  
Alison J. Culyba ◽  
Kar-Hai Chu ◽  
Kathleen M. Carley
Keyword(s):  
Social Network ◽  
Best Practices ◽  
Health Outcomes ◽  
Organizational Behavior ◽  
Network Data ◽  
Egocentric Networks ◽  
Covariate Selection ◽  
Social Network Modeling ◽  
Egocentric Network ◽  
The Impact

Objective/Aim: We describe best practices for modeling egocentric networks and health outcomes using a five-step guide. Background: Social network analysis (SNA) is common in social science fields and has more recently been used to study health-related topics including obesity, violence, substance use, health organizational behavior, and healthcare utilization. SNA, alone or in conjunction with spatial analysis, can be used to uniquely evaluate the impact of the physical or built environment on health. The environment can shape the presence, quality, and function of social relationships with spatial and network processes interacting to affect health outcomes. While there are some common measures frequently used in modeling the impact of social networks on health outcomes, there is no standard approach to social network modeling in health research, which impacts rigor and reproducibility. Methods: We provide an overview of social network concepts and terminology focused on egocentric network data. Egocentric, or personal networks, take the perspective of an individual who identifies their own connections (alters) and also the relationships between alters. Results: We describe best practices for modeling egocentric networks and health outcomes according to the following five-step guide: (1) model selection, (2) social network exposure variable and selection considerations, (3) covariate selection related to sociodemographic and health characteristics, (4) covariate selection related to social network characteristics, and (5) analytic considerations. We also present an example of SNA. Conclusions: SNA provides a powerful repertoire of techniques to examine how relationships impact attitudes, experiences, and behaviors—and subsequently health.

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