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Based on the work of Reid and DePalma (2005), a new type of location function on trees, called the weight balance function and denoted by W b , is introduced. We compare W b with the well known median function M e d and show that W b (π) ⊆ M e d (π) for any profile π such that | M e d (π) | ≥ 2. The special case of M e d (π) = { x } for some vertex x is also investigated. [ABSTRACT FROM AUTHOR]

In addition to considering the influence of a species on other species (centrality), the identification of keystone species should also consider whether it has a unique network position (uniqueness). Clarifying the correlation between species centrality and uniqueness, or whether central species exhibit positional redundancy in food webs, can enhance the understanding of mechanisms stabilizing food webs. However, the findings from analyses utilizing different measures of uniqueness are contentious. In this study, we constructed the food web of the eutrophic Zhangze Lake (northern China) using stable isotopes to estimate the contribution of food sources to consumers. We then calculated trophic field overlap index to assess the uniqueness of species using this quantified food web information. Additionally, we analyzed how the weak interaction and the threshold value under which interactions are considered as weak influence the relationship between species uniqueness and centrality. The findings revealed that, in contrast to the traditional trophic field overlap index, the improved index identified the basal species with the strongest trophic interactions with other species and the filter‐feeding fishes with the fewest interactors as the most unique species, while the basal species were considered the least unique under the traditional index. The ranking results of the traditional index and the centrality showed a significant negative correlation, whereas the improved index displayed a positive correlation, which was caused by the comprehensive consideration of threshold and weak interaction. In addition, based on the data analysis, the suggestion was given for the selection of indices used to identify unique species, and whether central species have positional redundancy was explored. The methodology used in study provides a practical solution for the identification of the most unique species, points out and solves the problems faced in the uniqueness analysis, and advances the understanding of the mechanisms underlying food web robustness. [ABSTRACT FROM AUTHOR]

We studied spatial variation in the effects of environment and network size on species positions and roles in multiple flea–mammal networks from four biogeographic realms. We asked whether species positions (measured as species strength [SS], the degree of interaction specialization [d′], and the eigenvector centrality [C]) or the roles of fleas and their hosts in the interaction networks: (a) are repeatable/conserved within a flea or a host species; (b) vary in dependence on environmental variables and/or network size; and (c) the effects of environment and network size on species positions or roles in the networks depend on species traits. The repeatability analysis of species position indices for 441 flea and 429 host species, occurring in at least two networks, demonstrated that the repeatability of SS, d′, and C within a species was significant, although not especially high, suggesting that the indices' values were affected by local factors. The majority of flea and host species in the majority of networks demonstrated a peripheral role. A value of at least one index of species position was significantly affected by environmental variables or network size in 41 and 36, respectively, of the 52 flea and 52 host species that occurred in multiple networks. In both fleas and hosts, the occurrence of the significant effect of environment or network size on at least one index of species position, but not on a species' role in a network, was associated with some species traits. [ABSTRACT FROM AUTHOR]

Water system connectivity is an important measure to optimize the balanced spatial allocation of water resources and water security patterns. Inland river basins in arid zones are generally insufficiently connected, so the scientific evaluation of the current status of water system connectivity and the centrality of its nodes in the water system network has practical significance for the scientific construction of regional water networks. Taking the Tarim River Basin in Xinjiang, China, as an object, this study conducted a comprehensive evaluation of basin water system connectivity by constructing a water system connectivity evaluation system with a total of 12 indicators for the three aspects of pattern connectivity, structural connectivity and functional connectivity. Subsequently, the TOPSIS model, with combined weights of the analytic hierarchy process and the entropy weight method, was used to comprehensively evaluate the connectivity of the watershed's water system. The research evaluated the node centrality of the water system network that was closely related to the basin water system connectivity by using complex network analyses. The study results indicated the following: (1) among the source streams in the Tarim River Basin, the connectivity of the Aksu Basin was the best and that of the Keriya Basin was the worst and (2) the distribution patterns of the eigenvector centrality and betweenness centrality of the basin hydrological network nodes were similar, with nodes of highest centrality concentrated in the vicinity of the mainstems and the source–mainstem intersections. This work provides a basis and reference for the construction of water system connectivity and the selection of key control sections for ecological flow in the Tarim River Basin. [ABSTRACT FROM AUTHOR]

This paper establishes a symmetric matrix based on the coopetition relationships among global automobile enterprises, and uses Ucinet software to obtain the visualization chart of the coopetition network of global automobile enterprises. Then, the multiple moderating effect method and two-stage least squares method are adopt to reveal the interaction between structural hole and centrality on enterprise market performance, and how the ego-network characteristics affect this interaction. The results show that structural hole and centrality have a positive interaction on market performance. Compared with high ego-network stability, the positive interaction between structural hole and centrality on enterprise market performance is stronger under the condition of low ego-network stability. And compared with low ego-network density, the positive interaction between structural hole and centrality on market performance is stronger under the condition of high ego-network density. These new findings further strengthen the connection between the overall network and ego-network. [ABSTRACT FROM AUTHOR]

The main aim of this study was to validate and adapt the Centrality of Religiosity Scale to the Portuguese population. A total of 1018 subjects participated in this study. The metric qualities demonstrated in the analyses suggested that the factor structure was based on five dimensions identical to those proposed by its authors. After analysing its psychometric qualities, we concluded that this instrument can be applied to the Portuguese population and is a valuable tool in studies related to the psychology of religion and spirituality. [ABSTRACT FROM AUTHOR]

This paper investigates publication strategies of the most distinguished local government researchers in eight European countries. Drawing upon dependency theory, accumulative advantage theory and 'utility maximizing' theory, we compare publication strategies of scholars from countries that vary in terms of the distance from the core of academic knowledge production, also taking into consideration their career length (academic age). The two publication strategies compared are international visibility and domestic visibility. The analysis confirmed the hypothesis that younger scholars are more prone to adopt internationalization strategy which has been institutionally incentivized by NPM reforms. However, the difference among core, catching‐up and peripheral countries is not as sizeable as expected. [ABSTRACT FROM AUTHOR]

Queer Aesthetics will be a new section for GLQ, and this essay explains its focus and rationale as it replaces the Moving Image Review. This essay outlines the need for queer aesthetics as an analytic as it relates to changes in liberal governance and media representation, subjectless critique, and academic discourse. In addition, it outlines a genealogy of queer aesthetics and form and questions the centrality of representation as a discourse for queer theory and studies. [ABSTRACT FROM AUTHOR]

The Katz centrality of a node in a complex network is a measure of the node's importance as far as the flow of information across the network is concerned. For ensembles of locally tree-like undirected random graphs, this observable is a random variable. Its full probability distribution is of interest but difficult to handle analytically because of its "global" character and its definition in terms of a matrix inverse. Leveraging a fast Gaussian Belief Propagation-Cavity algorithm to solve linear systems on tree-like structures, we show that i) the Katz centrality of a single instance can be computed recursively in a very fast way, and ii) the probability P(K) that a random node in the ensemble of undirected random graphs has centrality K satisfies a set of recursive distributional equations, which can be analytically characterized and efficiently solved using a population dynamics algorithm. We test our solution on ensembles of Erdős-Rényi and Scale Free networks in the locally tree-like regime, with excellent agreement. The analytical distribution of centrality for the configuration model conditioned on the degree of each node can be employed as a benchmark to identify nodes of empirical networks with over- and underexpressed centrality relative to a null baseline. We also provide an approximate formula based on a rank-1 projection that works well if the network is not too sparse, and we argue that an extension of our method could be efficiently extended to tackle analytical distributions of other centrality measures such as PageRank for directed networks in a transparent and user-friendly way. [ABSTRACT FROM AUTHOR]

The construction and operation of collaborative production networks based on multi-subject collaboration is an important path and means for enterprises to adapt to personalized, diversified, and differentiated market demand. It is of great practical significance to identify the key collaborative subjects in the collaborative network and protect and maintain them to ensure its normal operation. To identify the key collaborative subjects in the collaborative network of traditional manufacturing enterprises, this paper proposes a method for identifying and evaluating the importance of nodes in traditional manufacturing enterprise collaborative networks. Firstly, the method uses four parameters, degree centrality, betweenness centrality, closeness centrality, and subgraph centrality, as node importance evaluation indexes, based on complex network theory. Secondly, the coefficient of variation method (CVM) is used to calculate the weights of evaluation indexes. The Multiple Attribute Decision Making (MADM) based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is then used to comprehensively evaluate node importance and identify key nodes (key collaborative subjects) in the network. Finally, the proposed method's effectiveness, rationality, and scientific nature are verified by using the measurement index of network connectivity in combination with specific enterprise cases. The results show that the failure of key nodes has a more significant impact on network connectivity. Therefore, the node importance evaluation method based on Multiple Attribute Decision Making has better performance. It helps traditional manufacturing enterprises to focus on the protection and maintenance of the key collaborative subjects when coping with the competitive environment of the external market and provides a valuable reference for the normal operation of collaborative network organizations. [ABSTRACT FROM AUTHOR]

Setting the population, intervention, comparison, and outcome (PICO) elements during a search strategy development stage for a systematic review (SR) defines a research question specifically. In contrast to traditional methods that rely on researcher discretion, we propose a text network analysis (TNA) method using the R language to set the correct basis for the PICO. First, we collected 80 related papers from the PubMed database using 'Health Impact Assessment of arsenic exposure' as an example topic. Next, we recorded the keywords of each paper into a dataframe and converted the dataframe into an edge list format to create a network. Finally, we confirmed the connectivity and frequency of each keyword through network visualization and the importance of keywords according to three metrics through centrality analysis. As a result, arsenic could be expected to have detrimental effects on the occurrence of heart- and blood-related diseases or on mothers. By setting important keywords as the PICO elements known through a TNA, the reliability of SRs is improved, and this methodology can be equally applied to various topics. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between cross-shareholding networks and internal controls quality using a sample of all listed A-share firms in China during 2007–2020. We find that the higher the centrality of cross-shareholding networks, the lower the quality of internal control. This finding passes a series of robustness regressions. Moreover, we further test the influence channel of cross-shareholding on the internal control quality and find that the agency cost is the corresponding intermediary. That is, the cross-shareholding network increases the agency cost of the firm and thus reduces the quality of internal control. [ABSTRACT FROM AUTHOR]

Among the properties describing the behavior of centrality measures with respect to network modifications, score monotonicity means that adding an arc increases the centrality score of the target of the arc; rank monotonicity means that adding an arc improves the importance of the target with respect to the remaining nodes. It is known (Boldi and Vigna Intern Math 10:222–262, 2014, Boldi et al. Netw Sci 5(4):529–550, 2017) that score and rank monotonicity hold in directed graphs for almost all the classical centrality measures. In undirected graphs one expects that the corresponding properties hold when adding a new edge—in this case, both endpoints of the new edge should enjoy the increase in score/rank. However, recent results (Boldi et al. in Netw Sci 11(3):1–23, 2023) have shown that this is not true: for many centrality measures, it is possible to find situations in which adding an edge reduces the rank of one of its two endpoints. In this paper we introduce a weaker property for undirected networks, semi-monotonicity, in which just one of the two endpoints of a new edge is required to enjoy score or rank monotonicity. We show that this property is satisfied by closeness centrality, by a large class of distance-based centralities, and (somehow surprisingly) by betweenness centrality. In the last two cases, we prove in fact a stronger property, basin dominance, which is of independent interest. [ABSTRACT FROM AUTHOR]

It is of great significance to lead Chengdu-Chongqing economic circle to stride forward to world-class urban agglomeration, promote regional economic integrated development, and boost domestic circulation with regional circulation for accelerating the formation of a new development pattern with domestic circulation as the main body and the domestic and international dual circulation promoting each other. Based on the perspective of urban network structure, the urban network structure characteristics and differences of Chengdu-Chongqing Economic Circle are described by using the social network analysis method and the visualization function of ArcGIS spatial analysis tool on the basis of constructing the urban spatial connection network of transportation, economy, population and information by using the data of railway and highway passenger transport frequency, regional outward function influence quantity, population migration quantity and Baidu index. Finally, the optimization strategies and suggestions of the network structure of Chengdu-Chongqing economic circle are put forward from different perspectives. The results show that: (1) The urban network shows a dual-core circle radial spatial structure dominated by "Chengdu and Chongqing", and the overall network connection presents an "unbalanced" pattern. (2) The embryonic form of urban system is emerging, the network structure is not stable, and the resilience needs to be further improved. The overall index calculation shows that the tightness of the urban network is population> information> economy> transportation. (3) The "core-periphery" effect is significant, the "collapse" phenomenon is obvious, and there is no strong secondary central city. (4) The distribution of cohesive subgroups is highly different, and the spatial distribution of the cities in the agglomerated subgroups is basically in line with the geographical proximity. [ABSTRACT FROM AUTHOR]

Does position in the friendship network affect social status in early adolescence? Previous research shows that friendship relations are not equivalent to popularity hierarchies, but favorable positions in the friendship network should allow students to gain status. We use four waves of longitudinal network data and dynamic panel models with fixed effects to estimate the impact of network position on social status. Degree centrality and brokerage opportunity both exert large impacts on status, even compared against the effect of prior status. The results suggest future research on friendship across social identities, as well as network structure and hierarchy in adolescent social systems. [ABSTRACT FROM AUTHOR]

Project‐based interorganizational networks are temporary and dynamic, and significantly different from stable networks for mass production. However, empirical studies on project‐based interorganizational networks are scant. Drawing upon the network literature and distinguishing between production and distribution networks, we investigate how the centrality of a project in industry networks and tie strength of the project's member firms affect project performance in terms of product quality and sales. Using data of 821 Chinese movie projects during 2015–2018, we find empirical evidence that a project's centrality in the production network enhances product quality and that in the distribution network elevates product sales. Interestingly, weak ties in the production team contribute to product quality while strong ties in the distribution team improve product sales. This study advances the literature on project‐based industries and interorganizational networks. It highlights the distinction between production and distribution networks in project‐based industries and sheds light on the differential roles of a project's centrality and tie strength in both networks. These findings also offer novel insights to managers in project‐based industries. Highlights: In project‐based industries such as the movie industry, the industry network comprises various companies and can be categorized into production and distribution networks.When a movie is produced by companies at the center of the production network, it tends to have better quality; and when it is distributed by companies central in the distribution network, it is more likely to achieve box office success.When production companies collaborate too frequently in the past, it could actually be detrimental to product quality; but when distribution companies have strong connections, it usually helps boost box office sales. [ABSTRACT FROM AUTHOR]

Background/Objectives: Engaging in physical activity (PA) is crucial for children's physical and mental health, with PA in childhood influencing lifelong activity levels. However, PA during childhood tends to decrease with age. Childhood friendship networks influence various health behaviors, including physical activity. Centralities are objective measures of an individual's position and role in friendship networks. The relationship between centrality and PA is inconsistent. This study aimed to determine how centrality affects changes in PA in late childhood longitudinally and to investigate the distribution of centrality in the network. Methods: This prospective cohort study recruited fourth- and fifth-grade children (9–11 years old). A total of 143 children participated. We calculated three centralities—in-degree, closeness, and betweenness—based on social network analysis (SNA). PA was assessed using the physical activity questionnaire for older children (PAQ-C). To explore the relationship between centralities and the percentage change in PA, a multivariate logistic regression analysis was performed. Results: Children with higher closeness had a significantly higher rate of decrease in PA after adjusting for confounding factors. There was no significant association between betweenness and percentage change in PA (p = 0.66) or in-degree and percentage change in PA (p = 0.21). Conclusions: This study highlights the importance of considering social network dynamics in PA interventions, particularly for children with high social closeness. Future research should incorporate objective PA measures and explore broader social networks to enhance intervention strategies, especially for Generation Z and Alpha, who experience unique opportunities and motivations for PA due to pervasive digital environments. [ABSTRACT FROM AUTHOR]

Spectral analysis of networks states that many structural properties of graphs, such as the centrality of their nodes, are given in terms of their adjacency matrices. The natural extension of such spectral analysis to higher-order networks is strongly limited by the fact that a given hypergraph could have several different adjacency hypermatrices, and hence the results obtained so far are mainly restricted to the class of uniform hypergraphs, which leaves many real systems unattended. A new method for analyzing non-linear eigenvector-like centrality measures of non-uniform hypergraphs was presented in this paper that could be useful for studying properties of $ \mathcal{H} $-eigenvectors and $ \mathcal{Z} $-eigenvectors in the non-uniform case. In order to do so, a new operation——the uplift——was introduced, incorporating auxiliary nodes in the hypergraph to allow for a uniform-like analysis. We later argued why this was a mathematically sound operation, and we furthermore used it to classify a whole family of hypergraphs with unique Perron-like $ \mathcal{Z} $-eigenvectors. We supplemented the theoretical analysis with several examples and numerical simulations on synthetic and real datasets: On the latter, we find a clear improvement over the existing methods, specially in cases where there is a huge disparity between the structure at each order, and on the former, we find that regardless of the chosen uniformization scheme, the nodes were similarly ranked.

Abstract This paper establishes a symmetric matrix based on the coopetition relationships among global automobile enterprises, and uses Ucinet software to obtain the visualization chart of the coopetition network of global automobile enterprises. Then, the multiple moderating effect method and two-stage least squares method are adopt to reveal the interaction between structural hole and centrality on enterprise market performance, and how the ego-network characteristics affect this interaction. The results show that structural hole and centrality have a positive interaction on market performance. Compared with high ego-network stability, the positive interaction between structural hole and centrality on enterprise market performance is stronger under the condition of low ego-network stability. And compared with low ego-network density, the positive interaction between structural hole and centrality on market performance is stronger under the condition of high ego-network density. These new findings further strengthen the connection between the overall network and ego-network.

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Henri Grivois has posited that psychosis involves the subjective experience of oneself as the center or focal point of the world. In this experience, the world that is typically unrelated to oneself becomes incomprehensible, and in its place is the sense that all life events are directly related to oneself or that one is perpetually at the center of all noteworthy activity. We suggest that this experience of centrality can be understood through the lens of the integrated model of metacognition. Specifically, we explore the idea that the metacognitive domain of decentration, or the ability to form ideas about the larger community one is a part of, can be used to operationalize and measure centrality. We propose a three-phase approach to addressing centrality within an integrative psychotherapy focused on subjective and experiential aspects of recovery. These phases focus on the patient's experience of centrality and include (1) inviting the therapist to join one's centrality, (2) acknowledging others as different from oneself, and (3) recognizing alternative perspectives in the world. We provide case examples and explore the metacognitive tasks and potential barriers associated with each phase. [ABSTRACT FROM AUTHOR]

Data collection technologies or data sources are critical for highway network management. However, due to the limitations on available management resources, determining the importance of these data sources is necessary to allocate these resources reasonably. This study proposes a complex network based method for evaluating the importance of multiple data sources in highway networks. This method includes mainly three steps. First, the business-data source relation will be identified and formulated for the highway network. Second, a business data source complex network is built from the previously identified business-data relationship. Third, an entropy weight method is used to compute and rank the importance of data source nodes by combining three indexes of degree centrality (DC), closeness centrality (CC) and structural holes (SC) computed based on the complex network. The proposed method is applied and illustrated using the highway network of Xuzhou City, Jiangsu Province, China. The results show that among the data sources, the most important data source is the continuous traffic survey station, followed by an automatic gantry-based station and vehicle detectors-based system. Discussions on the limitations, applications and future studies are provided for the proposed approach.

Tourism destinations represent a vital element and the primary motivator for tourists in determining their travel and visitation patterns. Consequently, it is essential to implement effective planning strategies that align with the diverse motivations of tourists. One of the scientific discussions in tourism planning or development is through network analysis. With network analysis, it can explain the relationship or relationship between tourist attractions so that in the future it can be further developed how the attraction cluster in a tourist destination can be developed and directed. This research sees that the priority in terms of centrality should be given to the many attractions in West Kalimantan. This study aims to identify relationships or relationships between tourist attractions in West Kalimantan to be able to see the trend of networking (centrality), can be in the form of centralization, connectedness, clusters, and others. This research uses a network analysis approach which in principle is divided into several methods such as centrality calculations carried out with analytical techniques/tools such as degree, closeness, betweenness, and eigenvector. From the results obtained, the cluster of tourist attractions spread evenly in each region. The tourist attraction cluster with the most interaction is located in Bengkayang Regency, Pontianak City, North Kayong Regency, Ketapang Regency, and Kapuas Hulu Regency. For tourist attraction clusters with easy access, they are in the Sambas Regency and Singkawang City areas. Clusters of tourist attractions that become hubs are located in Sanggau Regency and Ketapang Regency. Then the cluster of tourist attractions with the most central point is located in Singkawang City. The road network (access) in the configuration is very influential in the connectivity between regions in reaching tourist attractions

Problems in dairy cattle agribusiness require attention not only from the farmers themselves but also from farmer organizations. To understand the communication patterns among group members in the agribusiness sector, including the exchange of information related to cattle production, animal health, and wholesale prices, it is essential to analyze the communication network of the dairy cattle farmer group. This network is significant because it serves as the hub of organizational communication, both internally and externally. This research seeks to analyze the communication structure of the dairy cattle farmer group and investigate the relationship between the respondent characteristics and the communication networks within the Tegal Mandiri farmer group in Bogor Regency. The Social Network Analysis (SNA) method and a quantitative approach were used to conduct the research, with the Tegal Mandiri farmer group members in Bogor Regency as the unit of analysis. The group communication structure was analyzed using degree and closeness centrality, and the relationship between respondent characteristics and the communication network was analyzed using Spearman rank correlation. IBM SPSS Statistics 26 and UCINET 6 were the tools used for analysis. The study revealed that 1) the average degree centrality of the group was between 1.00 and 2.20, and the average closeness centrality was between 400.00 and 558.10. 2) The respondents' characteristics of farmers were significantly related to the communication networks within the group. The study found that the communication structure of the Tegal Mandiri farmer group exhibited low connectivity and an ineffective coordination forum

Abstract Breast cancer is a prominent global health concern, as the data from the International Agency for Research on Cancer (IARC) shows that breast cancer is the leading cancer type with new cases in 2020 and among the Top 5 cancer types with the most deaths. To help improve the current breast cancer comorbidity identification by medical personnel and ultimately, lower the number of death cases from breast cancer comorbidity, this research aims to discover the breast cancer comorbidity community, do modularity and similarity-based evaluation, suggest the best semantic similarity measurement and threshold value, and validate the data of breast cancer comorbidities with several data from research papers. The Wang algorithm, with a threshold value of 0.5, is chosen to build the network. Leiden, Louvain, RBER Pots, RB Pots, and Walktrap are the best five community detection algorithms. Similarity measurements with the best three fitness functions (edges inside, scaled density, and size) suggest that the Leiden–Louvain algorithm and RBER Pots-RB Pots algorithm are two pairs of algorithms with similar results. Other similarity measurements with the V-measure heatmap suggest that Louvain–Leiden (0.99), RB Pots–Leiden (0.97), and RB Pots–RBER Pots (0.96) results are similar. Comorbidity is then evaluated using the best five community detection algorithms and four centrality algorithms. As a result, fourteen diseases are agreed upon by the best five community detection algorithms, five diseases are agreed by four algorithms, two diseases are agreed by three algorithms, a disease is agreed by two algorithms, and ten diseases are agreed by an algorithm.

AbstractProtein-protein interaction (PPI) network analysis holds significant promise for cancer diagnosis and drug target identification. This paper introduces a novel random walk-based method called essential cancer protein identification using graph-based random walk with restart (EPI-GBRWR) to address this gap. This proposed method incorporates local and global topological features of proteins, enhancing the accuracy of essential protein identification in PPI networks. Starting with meticulous preprocessing of cancer gene datasets from NCBI, including breast, lung, colorectal, and ovarian cancers, and identifying a core set of common genes. The proposed method constructs PPI networks to capture complex protein interactions from these common cancer genes. Topological analysis, including a centrality measures matrix, is generated to perform the analysis to identify essential nodes. The study revealed that 40 essential proteins among breast, colorectal, lung and ovarian cancer showcase the potency of integrative methodologies in unravelling cancer complexity, signalling a transformative era in cancer research and treatment. The strength of the findings from the study has direct clinical relevance in cancer diseases. It contributes to the field of precision medicine to guide personalized treatment strategies. [ABSTRACT FROM AUTHOR]

In response to the phenomenon of global warming, the transportation sector aims to mitigate carbon emissions by promoting the use of public transportation. This study employs social network analysis to propose effective improvements to the public transportation system, focusing on bus stop locations and route networks in Hwaseong City, South Korea. Two networks were constructed based on existing public transportation routes and usage data at each bus stop. The findings and implications are as follows: Analyzing the public transportation network from a network perspective can effectively contribute to improving the public transportation network route system. By evaluating centrality and brokerage for the existing routes, it is possible to identify inefficient routes and develop efficient route modification plans. Based on actual usage patterns, excessive bus supply and unnecessary bus stop locations can be identified, allowing for the establishment of appropriate operational plans. This can lead to improved operational efficiency and cost savings. Rational route design and operational planning can enhance public transportation services and promote increased use of public transportation. Ultimately, this contributes to sustainable development through carbon reduction in the transportation sector. [ABSTRACT FROM AUTHOR]

Identification of central elements in networks is an ill-defined problem. Hence, a large number of centrality measures have been proposed in the literature. We present a survey of existing axioms, which characterize certain properties of centralities. We also perform a perturbation analysis of centrality measures in real and artificial networks. [ABSTRACT FROM AUTHOR]

Knowledge regarding the influence of individual traits on interaction patterns in nature can help understand the topological role of individuals within a network of intrapopulation interactions. We tested hypotheses on the relationships between individuals' positions within networks (specialization and centrality) of 4 populations of the mouse opossum Gracilinanus agilis and their traits (i.e. body length, body condition, tail length relative to body length, sex, reproductive condition, and botfly parasitism) and also seasonal effects in the Brazilian savanna. Individuals with lower body length, better body condition, and relatively shorter tail were more specialized (i.e. less connected within the network). Individuals were also more specialized and less connected during the warm-wet season. The relationship between individuals' position in the network and body traits, however, was independent of season. We propose that specialization may arise not only as a result of preferred feeding strategies by more capable individuals (i.e. those with better body condition and potentially prone to defend and access high-quality food resources) but also because of morphological constraints. Smaller/younger individuals (consequently with less experience in foraging) and short-tailed individuals (less skilled to explore the vertical strata of the vegetation) would feed only on a subset of the available food resources and consequently become more specialized. Moreover, individuals are more specialized during the warm-wet season because of high competition (population-dense period) and higher ecological opportunities (resource-rich period). Therefore, our study reveals the relevance of individual traits in shaping interaction patterns and specialization in populations. [ABSTRACT FROM AUTHOR]

With the advance of the COVID-19 pandemic, the emergence of new variants of the virus and peaks of the disease that occur seasonally until today, the study of disease proliferation becomes important. Thus, this study simulates the transmission of the virus in a network of undergraduate students from a Brazilian public university, which implemented the return to face-to-face classes at the beginning of 2022, using the concept of centrality in graphs. Several scenarios were considered, taking different groups as the first infected and analyzing the propagation effect of the disease in the network. The individuals who would represent the highest possible risk of inducing the disease, if infected, were detected through measures of centrality in networks. In addition, we also observed the peak of the disease, noting the highest number of infected people and the time to reach this peak, depending on the definition of the first infected. The identification of those first infected considering their importance in the network, via centrality measures, determines the disease cycle. [ABSTRACT FROM AUTHOR]

Traditional network interdiction problems focus on removing vertices or edges from a network so as to disconnect or lengthen paths in the network; network diversion problems seek to remove vertices or edges to reroute flow through a designated critical vertex or edge. We introduce the all-pairs vitality maximization problem (VIMAX), in which vertex deletion attempts to maximize the amount of flow passing through a critical vertex, measured as the all-pairs vitality of the vertex. The assumption in this problem is that in a network for which the structure is known but the physical locations of vertices may not be known (e.g., a social network), locating a person or asset of interest might require the ability to detect a sufficient amount of flow (e.g., communications or financial transactions) passing through the corresponding vertex in the network. We formulate VIMAX as a mixed integer program, and show that it is NP-Hard. We compare the performance of the MIP and a simulated annealing heuristic on both real and simulated data sets and highlight the potential increase in vitality of key vertices that can be attained by subset removal. We also present graph theoretic results that can be used to narrow the set of vertices to consider for removal. [ABSTRACT FROM AUTHOR]

AbstractBi+ individuals are at increased risk for mood and anxiety disorders compared to heterosexual and lesbian/gay individuals in part due to unique experiences of discrimination. Minority stress theory posits that associations between discrimination and adverse mental health outcomes may be stronger for those with higher identity centrality and lower identity affirmation, but few studies have tested these hypotheses. Therefore, the current study examined whether identity centrality and affirmation moderated the associations between discrimination and depression and anxiety symptoms among 715 bi+ adults. In bivariate analyses, discrimination was positively associated with depression and anxiety symptoms, whereas identity centrality and affirmation were not significantly associated with either. However, in multivariate analyses, identity centrality and affirmation were negatively associated with depression and anxiety symptoms, respectively. Neither identity centrality nor affirmation moderated any associations. These findings raise the question whether identity characteristics moderate associations between discrimination and mental health, but replication is needed. [ABSTRACT FROM AUTHOR]

An abundance of centrality indices has been proposed which capture the importance of nodes in a network based on different structural features. While there remains a persistent belief that similarities in outcomes of indices is contingent on their technical definitions, a growing body of research shows that structural features affect observed similarities more than technicalities. We conduct a series of experiments on artificial networks to trace the influence of specific structural features on the similarity of indices which confirm previous results in the literature. Our analysis on 1163 real-world networks, however, shows that little of the observations on synthetic networks convincingly carry over to empirical settings. Our findings suggest that although it seems clear that (dis)similarities among centralities depend on structural properties of the network, using correlation type analyses do not seem to be a promising approach to uncover such connections. • The association of network topology with dissimilarities of indices is assessed. • Using synthetic networks to link structure to rank dissimilarities. • A process to generate networks with high discordance among indices is presented. • Entropy is used to measure the impact of structural features on 1163 real networks. • No feature could explain dissimilarities among indices in experimental settings. [ABSTRACT FROM AUTHOR]

This paper aims to take a closer critical look at the multiple and multi-layered nature of urban centrality. Centrality is conceptualized here as a kind of prominence, perceived, planned and represented quality within the urban timespace. We employ three distinct ontological categories of the urban centre (centre-as-event, centre-as-thing and centre-as-structure) to take a deeper insight into the symbolism, ideological narratives and planning practices behind the genesis of the prominent urban places and times. With this approach, we expose even the seemingly subtle phenomena that (co-)shape multiple urban centralities. We are empirically focusing on the case of the city of Brno (Czech Republic). Attention is paid in particular to the period of socialism, more specifically to the influence of socialist ideology on the reorganization of urban central places and times. We are trying to overcome the traditional view of centralized and all-encompassing socialist transformation. Instead, the socialist Brno provides the case study to demonstrate a subtle fabric of overlapping, competing or simply coexisting socialist and pre-socialist centralities. We argue that the physical re-centralization of the city was in the end less significant than the efforts to symbolically recode the urban environment. [ABSTRACT FROM AUTHOR]

This study utilized Neutrosophic Cognitive Maps (NCMs) integrated with the D-OWA operator to analyze the nutritional rights of pregnant women in Ecuador, with a focus on the crucial role of nutrition education. The innovative application of the D-OWA operator enabled the computation of a composite centrality measure by merging key centrality indicators--degree, closeness, and betweenness--each appropriately weighted according to its relevance to the analysis. This methodology provided a sophisticated evaluation of the factors impacting maternal nutrition, demonstrating how combining various centrality measures offers a deeper and more comprehensive insight into the dynamics of complex systems. The calculated composite centrality measures revealed the system's intricate structure, pinpointing critical nodes and pathways that could be targeted most effectively through interventions. The findings underscore the significant benefits of using composite centrality measures to enhance decision-making in public health and other sectors characterized by complexity and uncertainty. The potential for refining and expanding this approach in future research suggests that it could be further supported by technological advancements, enabling more efficient analysis and scalability across diverse complex systems. [ABSTRACT FROM AUTHOR]

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Community ecology and sociobiology share a number of problems (e.g. understanding part-to-whole relationships), so sharing methods may be beneficial. In this paper, we re-analyze a large social network database for Camponotus fellah ants, from the perspective of keystone individuals, based on methods developed in community ecology. We study different network types for six colonies, over a time series of 10 days. These include the total network of weighted interactions, the subnetworks for the castes and the subnetworks for Queen-linked and Queen-independent individuals. We perform time-independent (i.e. average values) and temporal (i.e. trends) analyses. The most commonly used global network metrics showed high variability in time but no clear trends. Yet, the variability of a network centrality index (topological importance, TI), developed earlier in community ecology, shows clear increase in each colony over time, suggesting the emergence of keystone individuals as a general tendency in all studied ant colonies. [ABSTRACT FROM AUTHOR]

Using an app for smartphones, we run an experiment among high-school students to study the pattern of aggregation of sparsely distributed information. Agents are randomly arranged in small networks and can share only non-verifiable pieces of information. Results show that while information exchange is high, the level and the distribution of centralities among network members are important to shape the overall level of information aggregation. A reduction in the asymmetry among agents' network centralities is associated with an improvement in the performance of the group in terms of aggregation of information. [ABSTRACT FROM AUTHOR]

This study employs urban mapping techniques to explore the intricate relationship between the built environment and urban processes amidst rapid urbanization. The study area is located in Pontianak city, a city with integrating historical, geographical, and cultural perspectives in Borneo Island, Indonesia. This study unravels Pontianak's urban morphology, aiming to decipher the correlations between accessibility, built form, and cultural identity. Utilizing quantitative methodologies and the Spacematrix method, this research unveils the evolving relationship between accessibility and building density. Analyzing centrality through Space Syntax, it investigates the city's morphological development and cultural identity. The findings highlight Pontianak's adaptability to transportation shifts, emphasizing the impact on its urban evolution. Economic activities strongly shape building density, influencing architectural landscapes across zones. Nuanced correlations between integration, building attributes, and gross floor area underscore historical, cultural, and economic influences. Infrastructure development, notably roads and bridges, significantly enhances connectivity and catalyzes urban growth. This research illuminates the intricate tapestry of Pontianak's urban life, emphasizing its resilience and dynamic evolution amidst changing influences. [ABSTRACT FROM AUTHOR]

Copyright of Journal of International Business Studies is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Port connectivity and trading community structure are two fundamental network characteristics that complement one another in explaining the evolution of maritime transport networks. Although port connectivity has been widely studied in the literature, the investigations on trading community structures are rather limited. To better fill this gap, this paper aims to provide a more complete picture of the Global Container Shipping Network (GCSN)'s evolution, based on our earlier works in MEL. In doing so, the GCSN, representing a snapshot of trade at the end of each quarter, from Q3/2011 to Q3/2017, is first constructed. The connectivity of ports and their respective trading communities are then extracted by the Container Port Connectivity Index and the Louvain algorithm, respectively. With our proposed framework, related players would be able to understand the growth of GCSN, as well as the impacts of maritime occurrences on the network of container shipping. Our computational results indicate that port connectivity and trading community structure gradually evolve according to the economic conditions that change over time and the evolution of GCSN could be well explained by these two explanatory variables. In this regard, ports in East Asia consistently dominate others in terms of both inbound and outbound connectivity, led by Shanghai and other major ports of mainland China. Furthermore, the formation of trading communities largely depends on trading patterns—rather than geographical locations—which is evident from the insolvency and mergers of communities in the North American region right after the expansion of the Panama Canal in 2016. [ABSTRACT FROM AUTHOR]

Agricultural landscape expansion and land development have disrupted wildlife habitats and movement pathways, limiting species’ access to critical resources. Identifying multispecies corridors across human-dominated landscapes is crucial to facilitate safe and unobstructed movement while minimizing negative interactions between humans and wildlife. We conducted a spatial distribution analysis to delineate potential high conflict areas and assess connectivity for the movement of focal species across Peninsular Malaysia. Using conflict data for the Asian elephant (Elephas maximus), Malayan sun bear (Helarctos malayanus), and Malayan tiger (Panthera tigris) spanning an eight-year period (2013–2020), we predicted conflict risk distribution with MaxEnt. We then overlaid the resulting risk maps onto a unified resistance surface and predicted least-cost corridors between high conservation value (HCV) patches. We ranked these corridors by their ecological importance in a plantation landscape. We identified pinch point areas (bottlenecks) to denote locations most critical to species movement along the corridors. Our results suggested that potential high conflict areas were primarily located in eastern and southern Peninsular Malaysia. We identified 89 HCV core patches that were interconnected by 126 linkages. The mean length of the least-cost corridors was 13.41 km. Among the top 10 linkages ranked by centrality value, three crossed commercial plantations for

Yielding of the particulate network in colloidal gels under applied deformation is accompanied by various microstructural changes, including rearrangement, bond rupture, anisotropy, and reformation of secondary structures. While much work has been done to understand the physical underpinnings of yielding in colloidal gels, its topological origins remain poorly understood. Here, employing a series of tools from network science, we characterize the bonds using their orientation and network centrality. We find that bonds with higher centralities in the network are ruptured the most at all applied deformation rates. This suggests that a network analysis of the particulate structure can be used to predict the failure points in colloidal gels a priori. [ABSTRACT FROM AUTHOR]

Little is known about how farms and markets are connected. Identifying critical gaps and central hubs in food systems is of importance in addressing a variety of concerns, such as navigating rapid shifts in marketing practices as seen during the COVID-19 pandemic and related food shortages. The constellation of growers and markets can also reinforce opportunities to shift growing and eating policies and practices with attention to addressing racial and income inequities in food system ownership and access. With this research, we compare network methods for measuring centrality and sociospatial orientations in food systems using two of America's most high-producing agricultural counties. Though the counties are adjacent, we demonstrate that their community food systems have little overlap in contributing farms and markets. Our findings show that the community food system for Yolo County is tightly interwoven with Bay Area restaurants and farmers' markets. The adjacent county, Sacramento, branded itself as America's Farm-to-Fork capital in 2012 and possesses network hubs focused more on grocery stores and restaurants. In both counties, the most central actors differ and have been involved with the community food system for decades. Such findings have implications beyond the case studies, and we conclude with considerations for how our methods could be standardized in the national agricultural census.