Logistics global network connectivity and its determinants. A European City network analysis

The aim of this work is to explore the construct of autistic traits through the lens of network analysis with recently introduced Bayesian methods. A conditional dependence network structure was estimated from a data set composed of 649 university students that completed an autistic traits questionnaire. The connectedness of the network is also explored, as well as sex differences among female and male subjects in regard to network connectivity. The strongest connections in the network are found between items that measure similar autistic traits. Traits related to social skills are the most interconnected items in the network. Sex differences are found between female and male subjects. The Bayesian network analysis offers new insight on the connectivity of autistic traits as well as confirms several findings in the autism literature.

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The network boundary specification problem in the global and world city research: investigation of the reliability of empirical results from sampled networks

Journal of Geographical Systems ◽

10.1007/s10109-020-00340-4 ◽

2020 ◽

Author(s):

Vladimír Pažitka ◽

Dariusz Wójcik

Keyword(s):

Network Analysis ◽

Structural Parameters ◽

Empirical Studies ◽

World City ◽

Urban Networks ◽

Empirical Results ◽

Network Boundary ◽

City Network ◽

Network Centralities ◽

Modelling Approaches

AbstractDespite the well-known dependence of vertex and network structural parameters on network boundary specification employed by researchers, there has so far been effectively no discussion of this methodological caveat in the global and world city literature. Given the reliance of empirical studies of urban networks on the sampling of underlying actors that form these networks by their interactions, we consider it of key importance to examine the dependence of network centralities of cities on network boundary specification. We consider three distinctive modelling approaches based on: (a) office networks, (b) ownership ties and (c) inter-organisational projects. Our results indicate that city network centralities obtained from sampled networks are highly consistent with those obtained from whole network analysis for samples featuring as little as 4% (office networks), 10% (ownership ties) and 25% (inter-organisational projects) of the underlying actors.

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Neurological Soft Signs and Brain Network Abnormalities in Schizophrenia

Schizophrenia Bulletin ◽

10.1093/schbul/sbz118 ◽

2019 ◽

Vol 46 (3) ◽

pp. 562-571 ◽

Cited By ~ 3

Author(s):

Li Kong ◽

Christina J Herold ◽

Eric F C Cheung ◽

Raymond C K Chan ◽

Johannes Schröder

Keyword(s):

Network Analysis ◽

Frontal Cortex ◽

Temporal Cortex ◽

Brain Network ◽

Global Network ◽

Orbital Frontal Cortex ◽

Neural Basis ◽

Neurological Soft Signs ◽

Middle Temporal ◽

Significant Difference

Abstract Neurological soft signs (NSS) are often found in patients with schizophrenia. A wealth of neuroimaging studies have reported that NSS are related to disturbed cortical-subcortical-cerebellar circuitry in schizophrenia. However, the association between NSS and brain network abnormalities in patients with schizophrenia remains unclear. In this study, the graph theoretical approach was used to analyze brain network characteristics based on structural magnetic resonance imaging (MRI) data. NSS were assessed using the Heidelberg scale. We found that there was no significant difference in global network properties between individuals with high and low levels of NSS. Regional network analysis showed that NSS were associated with betweenness centrality involving the inferior orbital frontal cortex, the middle temporal cortex, the hippocampus, the supramarginal cortex, the amygdala, and the cerebellum. Global network analysis also demonstrated that NSS were associated with the distribution of network hubs involving the superior medial frontal cortex, the superior and middle temporal cortices, the postcentral cortex, the amygdala, and the cerebellum. Our findings suggest that NSS are associated with alterations in topological attributes of brain networks corresponding to the cortical-subcortical-cerebellum circuit in patients with schizophrenia, which may provide a new perspective for elucidating the neural basis of NSS in schizophrenia.

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Expanding Network Analysis Tools in Psychological Networks: Minimal Spanning Trees, Participation Coefficients, and Motif Analysis Applied to a Network of 26 Psychological Attributes

Complexity ◽

10.1155/2019/9424605 ◽

2019 ◽

Vol 2019 ◽

pp. 1-27 ◽

Cited By ~ 7

Author(s):

Srebrenka Letina ◽

Tessa F. Blanken ◽

Marie K. Deserno ◽

Denny Borsboom

Keyword(s):

Network Analysis ◽

Spanning Trees ◽

Main Idea ◽

Global Network ◽

Centrality Measures ◽

Future Research ◽

Motif Analysis ◽

Psychological Variables ◽

Hierarchical Arrangement ◽

Psychological Attributes

The analysis of psychological networks in previous research has been limited to the inspection of centrality measures and the quantification of specific global network features. The main idea of this paper is that a psychological network entails more potentially useful and interesting information that can be reaped by other methods widely used in network science. Specifically, we suggest methods that provide clearer picture about hierarchical arrangement of nodes in the network, address heterogeneity of nodes in the network, and look more closely at network’s local structure. We explore the potential value of minimum spanning trees, participation coefficients, and motif analyses and demonstrate the relevant analyses using a network of 26 psychological attributes. Using these techniques, we investigate how the network of different psychological concepts is organized, which attribute is most central, and what the role of intelligence in the network is relative to other psychological variables. Applying the three methods, we arrive at several tentative conclusions. Trait Empathy is the most “central” attribute in the network. Intelligence, although peripheral, is weakly but equally related to different kinds of attributes present in the network. Analysis of triadic configurations additionally shows that the network is characterized by relatively strong open triads and an unusually frequent occurrence of negative triangles. We discuss these and other findings in the light of possible theoretical explanations, methodological limitations, and future research.

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The association between insight and depressive symptoms in schizophrenia: Undirected and Bayesian network analyses

European Psychiatry ◽

10.1192/j.eurpsy.2020.45 ◽

2020 ◽

Vol 63 (1) ◽

Cited By ~ 1

Author(s):

Mario Amore ◽

Martino Belvederi Murri ◽

Pietro Calcagno ◽

Paola Rocca ◽

Alessandro Rossi ◽

...

Keyword(s):

Depressive Symptoms ◽

Network Analysis ◽

Bayesian Network ◽

Depression Scale ◽

Community Dwelling ◽

Global Network ◽

Network Analyses ◽

Causal Direction ◽

Service Engagement ◽

Symptom Level

Abstract Background. Greater levels of insight may be linked with depressive symptoms among patients with schizophrenia, however, it would be useful to characterize this association at symptom-level, in order to inform research on interventions. Methods. Data on depressive symptoms (Calgary Depression Scale for Schizophrenia) and insight (G12 item from the Positive and Negative Syndrome Scale) were obtained from 921 community-dwelling, clinically-stable individuals with a DSM-IV diagnosis of schizophrenia, recruited in a nationwide multicenter study. Network analysis was used to explore the most relevant connections between insight and depressive symptoms, including potential confounders in the model (neurocognitive and social-cognitive functioning, positive, negative and disorganization symptoms, extrapyramidal symptoms, hostility, internalized stigma, and perceived discrimination). Bayesian network analysis was used to estimate a directed acyclic graph (DAG) while investigating the most likely direction of the putative causal association between insight and depression. Results. After adjusting for confounders, better levels of insight were associated with greater self-depreciation, pathological guilt, morning depression and suicidal ideation. No difference in global network structure was detected for socioeconomic status, service engagement or illness severity. The DAG confirmed the presence of an association between greater insight and self-depreciation, suggesting the more probable causal direction was from insight to depressive symptoms. Conclusions. In schizophrenia, better levels of insight may cause self-depreciation and, possibly, other depressive symptoms. Person-centered and narrative psychotherapeutic approaches may be particularly fit to improve patient insight without dampening self-esteem.

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Bibliometric Analysis of Moxibustion Research Trends Over the Past 20 Years

Journal of Clinical Medicine ◽

10.3390/jcm9051254 ◽

2020 ◽

Vol 9 (5) ◽

pp. 1254 ◽

Cited By ~ 1

Author(s):

Hyejin Park ◽

In-Seon Lee ◽

Hyangsook Lee ◽

Younbyoung Chae

Keyword(s):

Network Analysis ◽

Bibliometric Analysis ◽

Collaborative Work ◽

Research Area ◽

Research Trends ◽

Global Network ◽

Journal Title ◽

Link Strength ◽

Number Of Publications ◽

Bibliometric Approach

Objectives: A bibliometric approach using network analysis was applied to identify the development and research trends for moxibustion. This study also examined the network hub of moxibustion research by investigating the collaborative work of organizations and authors. Methods: Academic articles on moxibustion research published from 2000 to 2019 were retrieved from the Web of Science database. Extracted records were analyzed according to publication year, research area, journal title, country, organization, and authors. The VOSviewer program was utilized to visualize the trends in moxibustion research and to explore the influential organizations and authors. Results: Analyses of 1146 original and review articles written in English demonstrated that the number of publications related to moxibustion research has increased consistently over the last 20 years. China issued the most articles in this field, and the most represented research area was integrative complementary medicine. A network analysis based on the co-occurrence and publication year of keywords identified the relevant characteristics and trends of moxibustion research. By assessing the total link strength of organizations and authors, influential organizations and authors who have contributed to moxibustion research were identified. Conclusions: The current study examined research on moxibustion using bibliometric analysis and identified a time-based development of moxibustion research and a global network hub of moxibustion research.

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Exploring the Impact of Dockless Bikeshare on Docked Bikeshare—A Case Study in London

Sustainability ◽

10.3390/su12156110 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6110

Author(s):

Dongdong Feng ◽

Lin Cheng ◽

Mingyang Du

Keyword(s):

Network Analysis ◽

Complex Network ◽

Interaction Strength ◽

Network Connectivity ◽

Temporal Analysis ◽

Complex Network Analysis ◽

Last Mile ◽

Considerable Impact ◽

The Impact ◽

Spatial Temporal Analysis

As a green and sustainable travel mode, the bikeshare plays an important role in solving the “last-mile” problem. The new dockless bikeshare system (DBS) is widely favored by travelers, and the traditional docked bikeshare system (BS) is affected to a certain extent, but the specific circumstances of this impact are not yet known. To fill the knowledge gap, the objective of this study is to measure the impacts of DBS on London cycle hire, which is a type of BS. In this study, the travel data of 707 docking stations in two periods, i.e., March 2018 and March 2017, are included. A spatial-temporal analysis is first conducted to investigate the mobility pattern changes. A complex network analysis is then developed to explore the impact of DBS on network connectivity. The results suggest a significant decrease of 64% in the average trip amounts, with both origins and destinations in the affected area, and the trips with short and medium duration and short and medium distances are mainly replaced by DBS. DBS also has a considerable impact on the structure and properties of the mobility network. The connectivity and interaction strength between stations decrease after DBS appears. We also concluded that the observed changes are heterogeneously distributed in space, especially on weekends. The applied spatial-temporal analysis and complex network analysis provide a better understanding of the relationships between DBS and BS.

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