scholarly journals Visibility network analysis of large-scale intermittency in convective surface layer turbulence

2021 ◽  
Vol 925 ◽  
Author(s):  
Subharthi Chowdhuri ◽  
Giovanni Iacobello ◽  
Tirtha Banerjee
Keyword(s):  
Surface Layer ◽  
Network Analysis ◽  
Large Scale ◽  
Temporal Structure ◽  
Nonlinear Effects ◽  
Surrogate Data ◽  
Statistical Characteristics ◽  
Layer Flow ◽  
Non Gaussian ◽  
New Research

Large-scale intermittency is a widely observed phenomenon in convective surface layer turbulence that induces non-Gaussian temperature statistics, while such a signature is not observed for velocity signals. Although approaches based on probability density functions have been used so far, those are not able to explain to what extent the signals’ temporal structure impacts the statistical characteristics of the velocity and temperature fluctuations. To tackle this issue, a visibility network analysis is carried out on a field-experimental dataset from a convective atmospheric surface layer flow. Through surrogate data and network-based measures, we demonstrate that the temperature intermittency is related to strong nonlinear dependencies in the temperature signals. Conversely, a competition between linear and nonlinear effects tends to inhibit the temperature-like intermittency behaviour in streamwise and vertical velocities. Based on present findings, new research avenues are likely to be opened up in studying large-scale intermittency in convective turbulence.

scholarly journals Network analysis to evaluate the impact of research funding on research community consolidation

2019 ◽  
Author(s):  
Daniel J. Hicks ◽  
David Coil ◽  
Carl G. Stahmer ◽  
Jonathan A. Eisen
Keyword(s):  
Network Analysis ◽  
Research Funding ◽  
Large Scale ◽  
Research Community ◽  
Collaboration Networks ◽  
Sloan Foundation ◽  
Funding Programs ◽  
Community Of Researchers ◽  
New Research ◽  
The Impact

AbstractIn 2004, the Alfred P. Sloan Foundation launched a new program focused on incubating a new field, “Microbiology of the Built Environment” (MoBE). By the end of 2017, the program had supported the publication of hundreds of scholarly works, but it was unclear to what extent it had stimulated the development of a new research community. We identified 307 works funded by the MoBE program, as well as a comparison set of 698 authors who published in the same journals during the same period of time but were not part of the Sloan Foundation-funded collaboration. Our analysis of collaboration networks for both groups of authors suggests that the Sloan Foundation’s program resulted in a more consolidated community of researchers, specifically in terms of number of components, diameter, density, and transitivity of the coauthor networks. In addition to highlighting the success of this particular program, our method could be applied to other fields to examine the impact of funding programs and other large-scale initiatives on the formation of research communities.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network

Bullying, School Violence, and Climate in Evolving Contexts

2018 ◽  
Author(s):  
Ron Avi Astor ◽  
Rami Benbenisthty
Keyword(s):  
School Violence ◽  
School Safety ◽  
Media Coverage ◽  
Large Scale ◽  
Ecological Model ◽  
Empirical Studies ◽  
Practical Applications ◽  
Teacher Student ◽  
Area Of Interest ◽  
New Research

Since 2005, the bullying, school violence, and school safety literatures have expanded dramatically in content, disciplines, and empirical studies. However, with this massive expansion of research, there is also a surprising lack of theoretical and empirical direction to guide efforts on how to advance our basic science and practical applications of this growing scientific area of interest. Parallel to this surge in interest, cultural norms, media coverage, and policies to address school safety and bullying have evolved at a remarkably quick pace over the past 13 years. For example, behaviors and populations that just a decade ago were not included in the school violence, bullying, and school safety discourse are now accepted areas of inquiry. These include, for instance, cyberbullying, sexting, social media shaming, teacher–student and student–teacher bullying, sexual harassment and assault, homicide, and suicide. Populations in schools not previously explored, such as lesbian, gay, bisexual, transgender, and queer students and educators and military- and veteran-connected students, become the foci of new research, policies, and programs. As a result, all US states and most industrialized countries now have a complex quilt of new school safety and bullying legislation and policies. Large-scale research and intervention funding programs are often linked to these policies. This book suggests an empirically driven unifying model that brings together these previously distinct literatures. This book presents an ecological model of school violence, bullying, and safety in evolving contexts that integrates all we have learned in the 13 years, and suggests ways to move forward.

scholarly journals A cosmic microscope for the preheating era

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
JiJi Fan ◽  
Zhong-Zhi Xianyu
Keyword(s):  
Scalar Field ◽  
Nonlinear Effect ◽  
Large Scale ◽  
Nonlinear Effects ◽  
Light Fields ◽  
Unique Probe ◽  
Light Scalar ◽  
Spatially Varying ◽  
Near Future ◽  
Scalar Perturbations

Abstract Light fields with spatially varying backgrounds can modulate cosmic preheating, and imprint the nonlinear effects of preheating dynamics at tiny scales on large scale fluctuations. This provides us a unique probe into the preheating era which we dub the “cosmic microscope”. We identify a distinctive effect of preheating on scalar perturbations that turns the Gaussian primordial fluctuations of a light scalar field into square waves, like a diode. The effect manifests itself as local non-Gaussianity. We present a model, “modulated partial preheating”, where this nonlinear effect is consistent with current observations and can be reached by near future cosmic probes.

scholarly journals Risk Assessment of Large-Scale Infrastructure Projects—Assumptions and Context

2020 ◽  
Vol 11 (1) ◽  
pp. 109
Author(s):  
Jana Korytárová ◽  
Vít Hromádka
Keyword(s):  
Risk Assessment ◽  
Economic Efficiency ◽  
Large Scale ◽  
Cash Flows ◽  
Statistical Characteristics ◽  
Individual Risk ◽  
Dependent Variables ◽  
Research Findings ◽  
Input Variables ◽  
Individual Risk Factors

This article deals with the partial outputs of large-scale infrastructure project risk assessment, specifically in the field of road and motorway construction. The Department of Transport spends a large amount of funds on project preparation and implementation, which however, must be allocated effectively, and with knowledge of the risks that may accompany them. Therefore, documentation for decision-making on project financing also includes their analysis. This article monitors the frequency of occurrence of individual risk factors within the qualitative risk analysis, with the support of the national risk register, and identifies dependent variables that represent part of the economic cash flows for determining project economic efficiency. At the same time, it compares these dependent variables identified by sensitivity analysis with critical variables, followed by testing the interaction of the critical variables’ effect on the project efficiency using the Monte Carlo method. A partial section of the research was focused on the analysis of the probability distribution of input variables, especially “the investment costs” and “time savings of infrastructure users” variables. The research findings conclude that it is necessary to pay attention to the setting of statistical characteristics of variables entering the economic efficiency indicator calculations, as the decision of whether or not to accept projects for funding is based on them.

Curvature Variability Study for Small- and Large-Scale Linear Fresnel Solar Fields: A Step Toward Optimization

2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Sara Benyakhlef ◽  
Ahmed Al Mers ◽  
Ossama Merroun ◽  
Abdelfattah Bouatem ◽  
Hamid Ajdad ◽  
...  
Keyword(s):  
Cost Reduction ◽  
Large Scale ◽  
Small Scale ◽  
Optimization Approach ◽  
Market Penetration ◽  
Concentrated Solar Power ◽  
Sustainable Technologies ◽  
Low Efficiency ◽  
New Research ◽  
Variability Study

Reducing levelized electricity costs of concentrated solar power (CSP) plants can be of great potential in accelerating the market penetration of these sustainable technologies. Linear Fresnel reflectors (LFRs) are one of these CSP technologies that may potentially contribute to such cost reduction. However, due to very little previous research, LFRs are considered as a low efficiency technology. In this type of solar collectors, there is a variety of design approaches when it comes to optimizing such systems. The present paper aims to tackle a new research axis based on variability study of heliostat curvature as an approach for optimizing small and large-scale LFRs. Numerical investigations based on a ray tracing model have demonstrated that LFR constructors should adopt a uniform curvature for small-scale LFRs and a variable curvature per row for large-scale LFRs. Better optical performances were obtained for LFRs regarding these adopted curvature types. An optimization approach based on the use of uniform heliostat curvature for small-scale LFRs has led to a system cost reduction by means of reducing its receiver surface and height.

scholarly journals Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions

PLoS ONE ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. e0146220 ◽  
Author(s):  
Aleksandra do Socorro da Silva ◽  
Silvana Rossy de Brito ◽  
Nandamudi Lankalapalli Vijaykumar ◽  
Cláudio Alex Jorge da Rocha ◽  
Maurílio de Abreu Monteiro ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Large Scale ◽  
Information And Communication

Modeling and Implementation of Inter-Campuses Equipment Optimized Management Based on WebGIS

2013 ◽  
Vol 680 ◽  
pp. 534-539
Author(s):  
Wei Feng Ma
Keyword(s):  
Information Management ◽  
Spatial Data ◽  
Large Scale ◽  
New Technology ◽  
Rapid Expansion ◽  
Mathematics Model ◽  
Data Mapping ◽  
Geographically Dispersed ◽  
New Research ◽  
Research Challenge

With the rapid expansion of the campus scale and the increasing of the geographically dispersed campus, how to adopt new theory, new method and new technology to realize the equipment optimized assignment and the information management is a new research challenge. It is the key to safeguard the national fund to use reasonably, and to speed up the development of education healthily. Through analyzing the domestic and foreign related research works, the paper proposed that it can take use of the spatial data expression and analysis with Geographic Information System (GIS) to realize the large-scale and inter-campuses equipment optimized assignment and information management. It discussed the mathematics model and the system architecture. Moreover, the paper described the key implementation technology in great detail such as spatial data mapping with MapInfo professional 9 and the development of WebGIS functions with MapXtreme. The results show that the solution is feasible and effective.

scholarly journals Degree Adjusted Large-Scale Network Analysis Reveals Novel Putative Metabolic Disease Genes

Biology ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 107
Author(s):  
Apurva Badkas ◽  
Thanh-Phuong Nguyen ◽  
Laura Caberlotto ◽  
Jochen G. Schneider ◽  
Sébastien De Landtsheer ◽  
...  
Keyword(s):  
Network Analysis ◽  
Network Topology ◽  
Large Scale ◽  
Metabolic Diseases ◽  
Critical Factor ◽  
Disease Genes ◽  
Alcoholic Fatty Liver ◽  
Large Scale Network ◽  
Depth Study ◽  
Public Datasets

A large percentage of the global population is currently afflicted by metabolic diseases (MD), and the incidence is likely to double in the next decades. MD associated co-morbidities such as non-alcoholic fatty liver disease (NAFLD) and cardiomyopathy contribute significantly to impaired health. MD are complex, polygenic, with many genes involved in its aetiology. A popular approach to investigate genetic contributions to disease aetiology is biological network analysis. However, data dependence introduces a bias (noise, false positives, over-publication) in the outcome. While several approaches have been proposed to overcome these biases, many of them have constraints, including data integration issues, dependence on arbitrary parameters, database dependent outcomes, and computational complexity. Network topology is also a critical factor affecting the outcomes. Here, we propose a simple, parameter-free method, that takes into account database dependence and network topology, to identify central genes in the MD network. Among them, we infer novel candidates that have not yet been annotated as MD genes and show their relevance by highlighting their differential expression in public datasets and carefully examining the literature. The method contributes to uncovering connections in the MD mechanisms and highlights several candidates for in-depth study of their contribution to MD and its co-morbidities.

Sign in / Sign up

Export Citation Format

Share Document