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In group-living species, reproductive variation among individuals of the same sex is widespread. By identifying the mechanisms underlying this reproductive skew, we gain fundamental insights into the evolution and maintenance of sociality. A common mechanism, social control, is typically studied by quantifying dominance, which is one of many attributes of sociality that describes how individuals exert influence on others and is an incomprehensive measure of social control as it accounts only for direct relationships. Here, we use the global reaching centrality (GRC), which quantifies the degree of hierarchy in a social network by accounting for both direct and indirect social relationships. Using a wild, free-living population of adult female yellow-bellied marmots (Marmota flaviventris), we found a positive relationship between the reproductive skew index and GRC: more despotic social groups have higher reproductive skew. The GRC was stronger predictor for skew than traditional measures of social control (i.e. dominance). This allows deeper insights into the diverse ways individuals control other group members reproduction, a core component in the evolution of sociality. Future studies of skew across taxa may profit by using more comprehensive, network-based measures of social control.

OBJECTIVE: Infantile epileptic spasms (IS) are epileptic seizures that are associated with increased risk for developmental impairments, adult epilepsies, and mortality. Here, we investigated coherence-based network dynamics in scalp EEG of infants with IS to identify frequency-dependent networks associated with spasms. We hypothesized that there is a network of increased fast ripple connectivity during the electrographic onset of clinical spasms, which is distinct from controls. METHODS: We retrospectively analyzed peri-ictal and interictal EEG recordings of 14 IS patients. The data was compared with 9 age-matched controls. Wavelet phase coherence (WPC) was computed between 0.2 and 400 Hz. Frequency- and time-dependent brain networks were constructed using this coherence as the strength of connection between two EEG channels, based on graph theory principles. Connectivity was evaluated through global efficiency (GE) and channel-based closeness centrality (CC), over frequency and time. RESULTS: GE in the fast ripple band (251-400 Hz) was significantly greater following the onset of spasms in all patients (P  central > anterior, Kruskal-Wallis P

In this study, we utilize Protein Residue Networks (PRNs), constructed using Local Spatial Pattern (LSP) alignment, to explore the dynamic behavior of Catabolite Activator Protein (CAP) upon the sequential binding of cAMP. We employed the Degree Centrality of these PRNs to investigate protein dynamics on a sub-nanosecond time scale, hypothesizing that it would reflect changes in CAPs entropy related to its thermal motions. We show that the binding of the first cAMP led to an increase in stability in the Cyclic-Nucleotide Binding Domain A (CNBD-A) and destabilization in CNBD-B, agreeing with previous reports explaining the negative cooperativity of cAMP binding in terms of an entropy-driven allostery. LSP-based PRNs also allow for the study of Betweenness Centrality, another graph-theoretical characteristic of PRNs, providing insights into global residue connectivity within CAP. Using this approach, we were able to correctly identify amino acids that were shown to be critical in mediating allosteric interactions in CAP. The agreement between our studies and previous experimental reports validates our method, particularly with respect to the reliability of Degree Centrality as a proxy for entropy related to protein thermal dynamics. Because LSP-based PRNs can be easily extended to include dynamics of small organic molecules, polynucleotides, or other allosteric proteins, the methods presented here mark a significant advancement in the field, positioning them as vital tools for a fast, cost-effective, and accurate analysis of entropy-driven allostery and identification of allosteric hotspots.

Using computational Social Network Analysis (SNA), this longitudinal study investigates the development of the interaction network and its influence on the second language (L2) gains of a complete cohort of 41 U.S. sojourners enrolled in a 3‐month intensive study‐abroad Arabic program in Jordan. Unlike extant research, our study focuses on students' interactions with alma mater classmates, reconstructing their complete network, tracing the impact of individual students' positions in the social graph using centrality metrics, and incorporating a developmental perspective with three measurement points. Objective proficiency gains were influenced by predeparture proficiency (negatively), multilingualism, perceived integration of the peer learner group (negatively), and the number of fellow learners speaking to the student. Analyses reveal relatively stable same‐gender cliques, but with changes in the patterns and strength of interaction. We also discuss interesting divergent trajectories of centrality metrics, L2 use, and progress; predictors of self‐perceived progress across skills; and the interplay of context and gender. A one‐page Accessible Summary of this article in nontechnical language is freely available in the Supporting Information online and at https://oasis‐database.org [ABSTRACT FROM AUTHOR]

Aim: Changes in landscape configuration significantly impact ecosystems and the services they provide, including disease regulation for both humans and wildlife. Land use conversion usually favors disturbed‐adapted species, which are often known reservoirs of zoonotic parasites, thereby potentially escalating spillover events (i.e., the transmission of parasites to new hosts, including humans). Here we aimed to investigate how alterations in landscape use and configuration influence the distribution and co‐occurrence of potential hosts of zoonotic and epizootic parasites. Location: Brazilian Atlantic Forest. Time Period: Data collection spanned from 1997 to 2019. Major taxa studied small mammals. Methods: We integrated ecological network metrics and joint distribution models while accounting for phylogenetic relationships and functional traits to answer two main questions: (1) do small mammal species considered central hosts in the transmission of parasites exhibit a higher probability of occurrence in landscapes with reduced native vegetation areas? (2) Do small mammal hosts that share a higher number of parasites have higher co‐occurrence probabilities? Results: Our results demonstrated that species identified as significant hosts in our centrality network analysis displayed an increased probability of occurrence in landscapes that are both more fragmented and have a higher proportion of farming areas, hence fewer native vegetation areas. Regarding the relationship between species co‐occurrence and parasite sharing, our findings indicated that most strong co‐occurrences were prevalent within groups with higher parasite fauna similarity, but not all species sharing parasites had a higher probability of co‐occurring. Conclusions: Here we highlight the effects of landscape conversion on small mammal species, including how different configurations of land use can influence both central and non‐central host occurrences. Besides, our results also indicate that parasite transmission may be overestimated when the co‐occurrence probability of potential host species is not considered. We highly recommend incorporating co‐occurrence data to estimate zoonotic risk. [ABSTRACT FROM AUTHOR]

Background: The effects of panic disorder (PD) and pharmacotherapy on brain functional hubs in drug-free patients, and the utility of their degree centrality (DC) in diagnosing and predicting treatment response (TR) for PD, remained unclear. Aims: This study aimed to assess the effects of PD and paroxetine on brain functional hubs in drug-free patients and to identify neuroimaging biomarkers for diagnosing and predicting TR in patients with PD. Methods: Imaging data from 54 medication-free PD patients and 54 matched healthy controls (HCs) underwent DC and functional connectivity (FC) analyses before and after a 4-week paroxetine treatment. Diagnosis and prediction of TR models for PD were constructed using support vector machine (SVM) and support vector regression (SVR), with DC as features. Results: Patients with PD showed aberrant DC and FC in the anterior cingulum, temporal, and occipital areas compared with HCs at baseline. After treatment, DC of the patients increased in the calcarine cortex, lingual gyrus, and cerebellum IV/V, along with improved clinical symptoms. Utilizing voxel-wise DC values at baseline, the SVM effectively distinguished patients with PD from HCs with an accuracy of 83.33%. In SVR, the predicted TR significantly correlated with the observed TR (correlation coefficient (r) = 0.893, Mean Squared Error = 0.009). Conclusion: Patients with PD exhibited abnormal DC and FC, notably in the limbic network, temporal, and occipital regions. Paroxetine ameliorated patients' symptoms while altering their brain FC. SVM and SVR models, utilizing baseline DC, effectively distinguished the patients from HCs and accurately predicted TR. [ABSTRACT FROM AUTHOR]

Historically, Black women have been susceptible to the effects of race- and gender-related stress, such as the sexually promiscuous Jezebel or the motherly Mammy stereotypes. However, few studies have centered on the influence of the Sapphire stereotype--defined as being overbearing, emasculating, and aggressive--on Black women's health. Due to these stereotypes, Black women may utilize different coping strategies such as disengagement coping--limiting one's interpersonal interactions-- to manage these stressors. Yet, little research has specifically examined how Black women's gendered racial identity development relates to internalization of the Sapphire stereotype. The present study aimed to explore whether gendered racial identity centrality moderates the relationship between the Sapphire stereotype and disengagement coping among Black women. Two hundred ninetyeight Black/African American women between the ages of 18-52 completed an online survey via Qualtrics. Based on the Phenomenological Variant of Ecological Systems Theory, we hypothesized that gendered racial identity centrality will moderate the relationship between the Sapphire stereotype and disengagement coping. Consistent with the hypothesis, the results indicated that identity centrality significantly moderated the relationship between the Sapphire stereotype and the use of disengagement coping such that higher identity centrality decreased the association between the Sapphire stereotype and disengagement use (b = .51, SE = 0.09, t = 5.67, p < .001, 95% CI [.33, .69]). This research can be used to develop educational programs to promote healthy identity development among Black women. [ABSTRACT FROM AUTHOR]

Background and Purpose: To investigate the abnormal pattern of altered functional activity in the brain and the neuroimaging mechanisms underlying the cognitive impairment of patients with colorectal cancer (CRC) via resting-state functional magnetic resonance imaging (rs-fMRI). Materials and Methods: CRC patients (n = 56) and healthy controls (HCs) (n = 50) were studied. The participants underwent rs-fMRI scans and the Montreal Cognitive Assessment (MoCA). The amplitude of low-frequency fluctuations (ALFF), degree centrality (DC), regional homogeneity (ReHo), and MoCA scores, were calculated for participants. Results: The scores of executives, visuospatial, memory, language and attention were lower in CRC patients. ReHo and ALFF values in the left postcentral gyrus, ReHo values in the right postcentral gyrus, ALFF and DC values in the left middle occipital gyrus, ReHo and DC values in the right lingual gyrus, DC values in the right angular gyrus and precuneus, and ALFF values in the left middle temporal gyrus decreased conspicuously in the CRC patients. Conclusion: CRC patients have abnormal resting state function, mainly in the brain areas involved in cognitive function. The overlapping brain regions with abnormal functional indicators are in the middle occipital gyrus, postcentral gyrus, and lingual gyrus. This study reveals the potential biological pathways involved in brain impairment and neurocognitive decline in patients with CRC. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between transport networks and land use patterns in the Delhi Metropolitan Area by employing a weighted centrality assessment approach. Recognizing the limitations of traditional monocentric and accessibility-based urban models, this study introduces a multimodal perspective that integrates both road and rail systems. Land use patterns are scrutinized in terms of spatial distribution of Residential, commercial, Public semipublic (PSP)/institutional, industrial and other landuse. Weighted centrality measures are assessed in terms of closeness, betweenness, and straightness, applied within a weighted framework to reflect the multimodal transport characteristics. This study introduces a path evaluation function (PEF) that incorporates transport network capacity and travel time and is calibrated with a turning parameter (α). Through multinomial logistic regression, we explore the complex relationship between weighted centrality of transport network and land use patterns. Results reveal a significant relationship, underscoring that higher centrality tends to favor commercial and public-semi-public/institutional uses, whereas centrality at lower spectrum favors the development of residential areas. This research not only advances the theoretical understanding of urban planning but also offers practical insights for policymakers, emphasizing the importance of multimodal transport considerations in urban development. [ABSTRACT FROM AUTHOR]

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This paper deals with a problem which belongs to the general question: how to reconstruct a graph from limited amount of information. As given information, we use the closeness centrality, which assigns a non-negative number to each node of the graph in question: the reciprocal of the sum of the length of the shortest paths between the node and all other nodes in the graph. Here we consider the case when the original graph is a tree and it is also known which nodes are the leaves. Based on some theoretical results, three algorithms are proposed. The first one aims at finding a non-exact solution G P in short time; the second one is a metaheuristic with some variants, they are intended to give further improvement on G P ; and the third one is designed for giving accurate results. Detailed explanations of these algorithms are given, together with numerical experiments to demonstrate their efficiency. [ABSTRACT FROM AUTHOR]

Centrality metrics have become a popular concept in network science and optimization. Over the years, centrality has been used to assign importance and identify influential elements in various settings, including transportation, infrastructure, biological, and social networks, among others. That said, most of the literature has focused on nodal versions of centrality. Recently, group counterparts of centrality have started attracting scientific and practitioner interest. The identification of sets of nodes that are influential within a network is becoming increasingly more important. This is even more pronounced when these sets of nodes are required to induce a certain motif or structure. In this study, we review group centrality metrics from an operations research and optimization perspective for the first time. This is particularly interesting due to the rapid evolution and development of this area in the operations research community over the last decade. We first present a historical overview of how we have reached this point in the study of group centrality. We then discuss the different structures and motifs that appear prominently in the literature, alongside the techniques and methodologies that are popular. We finally present possible avenues and directions for future work, mainly in three areas: (i) probabilistic metrics to account for randomness along with stochastic optimization techniques; (ii) structures and relaxations that have not been yet studied; and (iii) new emerging applications that can take advantage of group centrality. Our survey offers a concise review of group centrality and its intersection with network analysis and optimization. [ABSTRACT FROM AUTHOR]

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]

Local and global functional connectivity densities (lFCD and gFCD, respectively), derived from functional magnetic resonance imaging (fMRI) data, represent the degree of functional centrality within local and global brain networks. While these methods are well-established for mapping brain connectivity, the molecular and synaptic foundations of these connectivity patterns remain unclear. Glutamate, the principal excitatory neurotransmitter in the brain, plays a key role in these processes. Among its receptors, the α -amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) is crucial for neurotransmission, particularly in cognitive functions such as learning and memory. This study aimed to examine the association of the AMPAR density and FCD metrics of intraregional and interregional functional centrality. Using [11C]K-2, a positron emission tomography (PET) tracer specific for AMPARs, we measured AMPAR density in the brains of 35 healthy participants. Our findings revealed a strong positive correlation between AMPAR density and both lFCD and gFCD-lFCD across the entire brain. This correlation was especially notable in key regions such as the anterior cingulate cortex, posterior cingulate cortex, pre-subgenual frontal cortex, Default Mode Network, and Visual Network. These results highlight that postsynaptic AMPARs significantly contribute to both local and global functional connectivity in the brain, particularly in network hub regions. This study provides valuable insights into the molecular and synaptic underpinnings of brain functional connectomes. [ABSTRACT FROM AUTHOR]

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]

This paper explores how analysts' forecasting behaviour is related to their centrality within a dynamic information network. In this network, analysts who issued coverage reports on the same listed firms in clusters are connected. The social learning hypothesis and social capital theory suggest that financial analysts could learn from other analyst forecasts and obtain information from analyst reports. Employing a dynamic complex network methodology, we focus on analysts' network centrality – degree, betweenness, and closeness – to represent their information access based on a sample of 819,539 analyst forecasts in the Chinese A-share market from 2018 to 2022. Our findings suggest that analysts with more central positions in the network produce more accurate earnings-per-share forecasts and have a longer persistent influence on other analysts. Our results support the perspective that the diffusion of information among analysts affects their forecasts and reporting behaviour. [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]

Background and Purpose Methods Results Conclusions Different types of physical training can lead to changes in brain activity and function, and these changes can vary depending on the type of training. However, it remains unclear whether there are commonalities in how different types of training affect brain activity and function. The purpose of this study is to compare the brain activity states of professional athletes with those of ordinary university students and to explore the relationship between training and differences in brain activity states.This study primarily utilizes resting‐state MRI and the degree centrality metric to investigate spontaneous brain activity in 86 high‐level athletes with extensive training and 74 age‐ and gender‐matched nonathletes. Additionally, a correlation analysis between brain activity in relevant regions and years of training was conducted.The analysis revealed that, compared to nonathletes, high‐level athletes exhibited reduced activity in the Calcarine (a visual area) and Middle Temporal Gyrus. Furthermore, changes in the activity of the Calcarine and Middle Temporal Gyrus were significantly correlated with the number of years of professional training.The study results indicate that long‐term physical training is associated with changes in brain activity in athletes, providing insights into the neural mechanisms underlying behavioral performance in professional athletes. [ABSTRACT FROM AUTHOR]

The advent of the Internet has led to the emergence of multi-source heterogeneous knowledge graphs, which have become a crucial means of storing and disseminating knowledge. Node importance estimation is a technique that is employed extensively in a number of fields, including recommender systems, intelligent search and resource allocation. This study introduces a Multi-perspective attention mechanism Fusion Algorithm for the mapping of multi-perspective features of knowledge graphs to Node Importance Estimation (MFA-NIE). First, structural embedding features, relational predicate features, and attribute features (both textual and quantitative) are established for the nodes. Subsequently, an enhanced attention mechanism is employed to extract, compress, and fuse these features. The fused hidden layer vector is employed in the design of a key-based attention mechanism, which enables the propagation of messages from neighboring nodes to the source node. This process results in the iterative updating of the source node's hidden features. Finally, TOPSIS centrality, based on the topology of the source node, is employed to dynamically adjust the mapping between the fused features and node importance. Experiments were conducted on real-world, large-scale, multi-source, heterogeneous knowledge graphs, comparing the MFA-NIE algorithm with traditional and advanced baseline algorithms, including PR, PPR, GENI, RGTN, CLINE, MCRL, and others. The results demonstrate that the MFA-NIE algorithm significantly improves effectiveness and accuracy, showcasing its superiority, versatility, and practical application value. [ABSTRACT FROM AUTHOR]

Background and Purpose: This study sought to explore dynamic degree centrality (DC) variability in particular regions of the brain in patients with poststroke Broca aphasia (BA) using a resting‐state functional magnetic resonance imaging (rs‐fMRI) approach, comparing differences between Uyghur and Chinese BA patients. Methods: This study investigated two factors, language and BA status, and divided patients into four groups: Uyghur aphasia patients (UA), Uyghur normal control subjects (UN), Chinese aphasia patients (CA), and Chinese normal subjects (CN) who underwent rs‐fMRI analysis. Two‐way analysis of variance (ANOVA) was used to calculate the comprehensive differences in dynamic DC among these four groups. Correlations between DC and language behavior were assessed with partial correlation analyses. Results: Two‐way ANOVA revealed comparable results for the results of pairwise comparisons of dynamic DC variability among the four groups in the right middle frontal gyrus/orbital part (ORBmid.R), right superior frontal gyrus/dorsolateral, and right precuneus (PCUN.R), with results as follows: UA < UN, CA > CN, UA < CA, and UN > CN (p <.05, with the exception of the p‐values for UA and UN in superior frontal gyrus/dorsolateral). In contrast, the opposite results were observed for the right calcarine fissure and surrounding cortex (CAL.R, p <.05). Conclusion: The observed enhancement of dynamic DC variability in ORBmid.R and PCUN.R among Chinese BA patients and in CAL.R in Uyghur BA patients may be attributable to language network restructuring. Overall, these results suggest that BA patients who use different language families may exhibit differences in the network mechanisms that characterize observed impairments of language function. [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]

In the last half-century, the 'centre–periphery' model has become insufficient to describe the increasingly fragmented and multicentric Latin American metropolises. Frontiers between central and peripheral areas are shifting, in part, due to the emergence of new corporate centralities, usually located outside historical city centres and heavily equipped with private 'security' agents and devices. By examining the evolving governing practices taking place in and around the dynamic frontier of a business centrality in São Paulo, Brazil, this article discusses the connections between the transformation in centre–periphery relations and the reworking of prior forms of socio-spatial control since the 'security' turn of the 1990s. More specifically, it explores the effects of the production of securitised corporate centralities on the racialised differential governance of urban space. For this purpose, the article draws from empirical work involving fieldwork, interviews with public and private 'security' agents, the observation of meetings of the local Public Security Community Council (CONSEG), and the analysis of police statistics. In sum, the argument presented here is that the evolution of segregation mechanisms and governing practices in Latin-American metropolises reproduces centre–periphery relations under new spatial configurations, and increases the capacity of private agents to subject urban space to their own rules and regulations. [ABSTRACT FROM AUTHOR]

Intensive mothering, a classed and gendered practice optimally performed by stay‐at‐home mothers, is a dominant parenting ideology, particularly in developed societies with wide disparities in wealth. Ironically, in these societies, women tend to be well educated and have good employment prospects that are expected to free them from domestic obligations. Facing competing expectations shaped by the institutions of work and the family, how do college‐educated mothers consider ending or limiting their participation in the workforce or holding jobs while resolving the moral dilemma of being both a worker and a mother? We compared 33 college‐educated Hong Kong mothers engaged in different professions and constructed typologies that describe how intersecting ideologies of mothering and work shape work‐family arrangements. We paid special attention to mothers with strong commitment to their work, but with different ideologies about mothering. Some espouse the ideology of intensive mothering. Their belief in gender essentialism proved exhausting for them, both at work and at home. While away from home, these mothers supervised domestic helpers from their workplaces. Other women value their professions as emblematic of their identity as the perfect mother—an integrated form of mothering, thus feeling no guilt for delegating childcare responsibilities. We argue that given the entrenched gender inequality in workplaces and men's slow progress in doing their share of domestic work, the emergence of integrated mothering both rhetorically and in practice reflects women's striving to bring the "unfinished revolution" closer to the finish line. [ABSTRACT FROM AUTHOR]

Game events, such as game conventions and esports tournaments, have gained tremendous appeal as thriving tourist attractions. Despite this, there has been limited investigation of this emerging phenomenon in the existing literature on event tourism and event management. This study proposes a structural model to explore the relationships between the identity and passion of video game players and their behavioral intention to participate in on-site game events. The model specifies identity centrality and harmonious passion as antecedents, with gaming social capital serving as a mediator. Our findings reveal that whereas the centrality of identity as a gamer did not directly and significantly influence players' event attendance intention, its indirect effect through gaming social capital was significantly positive. Harmonious passion, on the other hand, both directly and indirectly affected players' behavior at the significance level. In the analysis, gaming social capital functioned as a reliable mediator for bridging these relationships. [ABSTRACT FROM AUTHOR]

This study examines the internal migration patterns among Mexico's Indigenous population from 1990 to 2020. We begin by estimating the total interstate migration flows for Indigenous groups and employ an advanced interaction component model to identify migration flows that exceed expectations. This model allows us to detect significant deviations and patterns within the migration data. Additionally, we apply network analysis techniques to identify states that are central to these migration flows and categorize states into distinct communities based on their migration interactions. Our findings reveal that Indigenous migration exhibits higher‐than‐expected flows, particularly from the West Central and North regions of Mexico. By contrast, non‐Indigenous migration shows greater flows, predominantly in the southern and central states. Through network analysis, particularly the use of eigenvector centrality, we identify Nayarit and Durango as key hubs for Indigenous migration, whereas Estado de Mexico and Ciudad de Mexico emerge as central nodes in non‐Indigenous migration. Our study highlights the growing significance of Mexico's northern region, with Nuevo León playing a crucial role in Indigenous and non‐Indigenous migration flow networks. This study's findings contribute valuable insights regarding the spatial dynamics of internal migration and the evolving migration patterns of Indigenous populations in Mexico. [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 constructs an institutional investor network based on the heavy holdings of the same stock in China and conducts a social network analysis to investigate the influence of this network on stock price volatility from the perspectives of network structure (density) and location (centrality). The study demonstrates that institutional investor network density is negatively related to stock price volatility, while network centrality is positively related to it. Mechanism analyses further reveal that network density reduces stock price volatility by mitigating private information arbitrage behavior among institutional investors, whereas network centrality increases stock price volatility by creating private information arbitrage opportunities within the network. Additionally, the paper finds that information asymmetry enhances the positive effect of network centrality on stock price volatility. These findings are generally consistent across subsample analyses for different market states, reactions to good and bad news, and types of equity ownership, as well as in other robustness tests. The practical implications of these findings are significant for market stability regulation. [ABSTRACT FROM AUTHOR]

As universities evolve through mission expansion and grapple with the increasing need to bridge academic work with practical relevance, researchers are finding themselves in the complex terrain of simultaneously embracing their entrepreneurial and academic identities. This study investigates the factors enabling hybrid identity centrality—a conscious recognition of being both an academic and entrepreneurial individual—among university researchers. Drawing on a sample of 312 researchers from two multifaculty universities, the findings show that researchers' perception of a university's entrepreneurship strategy implementation and their society—industry orientation significantly influence the likelihood of hybrid identity centrality. Notably, the society-industry orientation moderates the relationship between entrepreneurship strategy implementation and the adoption of a hybrid identity. The study contributes to the research on the complementarity of academic and entrepreneurial identities and adds novel insights to the organizational research on academic entrepreneurship by suggesting that entrepreneurship strategy alone may not suffice in promoting hybrid identity. [ABSTRACT FROM AUTHOR]

This study examines the knowledge structures (KSs) of CEOs of firms that attempted turnaround from performance decline. We developed and tested a theoretical model that describes how two cognitive characteristics of CEOs, complexity and centrality, influence the likelihood of turnaround. It is found that CEO KS centrality directly increases the chance of turnaround. In addition, CEO KS complexity is found to increasingly improve the chance of turnaround as a firm in decline launches a greater extent of strategic change to their organization. Together, in theory, our research suggests that CEO cognitive competencies matter for managing successful turnaround attempts. Practically speaking, the findings of this article imply that to improve their chance of achieving successful turnaround, declining firms should look for CEOs who are cognitively focused or who are cognitively complex enough to engage in the degree of strategic changes launched to save the firm. JEL Classification: L20, M1 [ABSTRACT FROM AUTHOR]

Accurately portraying the spatially linked network characteristics of digital infrastructure and exploring its energy-saving effects are highly valuable for enhancing the synergy in digital infrastructure development and expanding its network spillover effects on energy conservation. This paper uses panel data at the city level in China and employs a modified gravity model to calculate the centrality of digital infrastructure spatial correlation network nodes. Based on this, an econometric model is constructed, incorporating variables such as digital infrastructure spatial correlation network node centrality and urban green total factor energy efficiency. The model is used to analyze the effects and transmission paths of digital infrastructure network node centrality on urban green total factor energy efficiency. The analysis yields the following conclusions: (1) Digital infrastructure spatial correlation network node centrality significantly improves urban green total factor energy efficiency, with considerable variability due to city geographic location, city scale, and city attributes. (2) Nonlinear testing results indicate that as digital infrastructure construction advances, its impact on urban green total factor energy efficiency shifts from inhibitory to promotional. (3) The impact mechanism shows that digital infrastructure node centrality enhances urban green total factor energy efficiency through green technology innovation. Additionally, it promotes advanced industrial structures and reduces capital mismatch, further influencing energy efficiency. (4) Digital infrastructure node centrality not only boosts urban green total factor energy efficiency but also facilitates regional convergence, increasing the convergence rate from 0.094 to 0.170%. The findings of the research offer policy guidance for the government on advancing digital transformation initiatives and enhancing energy efficiency. [ABSTRACT FROM AUTHOR]

Inflammatory bowel diseases (IBD) are a group of chronic, non-specific intestinal diseases that could comorbid with varieties of negative emotional constructs, including pain-related negative emotions and trait negative emotions; however, the link between brain functions and different dimensions of negative emotions remains largely unknown. Ninety-eight patients with IBD and forty-six healthy subjects were scanned using a 3.0-T functional magnetic resonance imaging scanner. The amplitudes of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) were used to assess resting-state brain activity. Partial least squares (PLS) correlation was employed to assess the relationship among abnormal brain activities, pain-related and trait negative emotions. Compared to controls, patients with IBD exhibited higher values of ALFF in the right anterior cingulate cortex (ACC), lower values of ALFF in the left postcentral gyrus, and higher values of DC in the bilateral ACC. Multivariate PLS correlation analysis revealed the brain scores of the ACC were correlated with pain-related negative emotions, the brain salience in the left postcentral gyrus was associated with the higher-order trait depression. These findings can enhance our comprehension of how pain-related negative emotion and trait negative emotion affect the brains of patients with IBD in distinct ways. [ABSTRACT FROM AUTHOR]

The graph theory is one of the fundamental structures in computer science used to model various scientific and engineering problems. Many problems within the graph theory are categorized as NP-hard and NP-complete. One such problem is the minimum dominating set (MDS) problem, which seeks to identify the minimum possible subsets in a graph such that every other node in the subset is directly connected to a node in this subset. Due to its inherent complexity, developing an efficient polynomial-time method to address the MDS problem remains a significant challenge in graph theory. This paper introduces a novel algorithm that utilizes a centrality measure known as the Malatya Centrality to effectively address the MDS problem. The proposed algorithm, called the Malatya Dominating Set Algorithm (MDSA), leverages centrality values to identify dominating sets within a graph. It extends the Malatya centrality by incorporating a second-level centrality measure, which enhances the identification of dominating nodes. Through a systematic and algorithmic approach, these centrality values are employed to pinpoint the elements of the dominating set. The MDSA uniquely integrates greedy and dynamic programming strategies. At each step, the algorithm selects the most optimal (or near-optimal) node based on the centrality values (greedy approach) while updating the neighboring nodes' criteria to influence subsequent decisions (dynamic programming). The proposed algorithm demonstrates efficient performance, particularly in large-scale graphs, with time and space requirements scaling proportionally with the size of the graph and its average degree. Experimental results indicate that our algorithm outperforms existing methods, especially in terms of time complexity when applied to large datasets, showcasing its effectiveness in addressing the MDS problem. [ABSTRACT FROM AUTHOR]

Based on self-regulation theory, this paper constructs two paths through which entrepreneurial fear of failure affects entrepreneurial exit intentions, and explores the moderating effect of the locus of control. We analyze a sample of 308 entrepreneurs from small and medium-sized private enterprises located in Southeast China. The results shown that entrepreneurial fear of failure not only stimulates entrepreneurial identity centrality in a self-regulated driving state but also leads to emotional exhaustion in a state of self-regulated depletion, with two effects on entrepreneurial exit intentions. The facilitating effect of entrepreneurial fear of failure on entrepreneurial identity centrality is stronger for internals than externals, whereas the facilitating effect of entrepreneurial fear of failure on emotional exhaustion is stronger for externals than internals. This research provides a theoretical basis and managerial insights for using entrepreneurial fear of failure to motivate its promoting effects and inhibit its hindering effects on sustainable entrepreneurship. [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]

AbstractThe rise in natural disasters and climate-induced events, such as wildfires, hurricanes, and flooding, has significantly affected urban life. These events can disrupt daily activity and flows of individuals and goods on road and transit networks. To enhance urban resilience against disasters, it’s crucial to study and understand road network vulnerability, utilizing data-driven insights to inform planning and preparedness efforts. The aim of this paper is to develop a data-driven exploratory approach to assess vulnerability in road networks in response to a disruption. To accomplish this, we compare the centrality of road segments before, during, and after disaster, considering the network topological structure and movement activity as it is observed through large tracking data of cellphone traces on the network. The novelty of our approach lies in inferring the impact from movement data, instead of manually removing links from the network. The results obtained from this study suggest that incorporating movement data into the assessment of network functionality provides a more realistic estimation of the road network vulnerability in response to a disruption, compared to solely using network topology. [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 combinatorial problem in this paper is motivated by a variant of the famous traveling salesman problem where the salesman must return to the starting point after each delivery. The total length of a delivery route is related to a metric known as closeness centrality. The closeness centrality of a vertex v in a graph G was defined in 1950 by Bavelas to be C C (v) = | V (G) | − 1 S D (v) , where S D (v) is the sum of the distances from v to each of the other vertices (which is one-half of the total distance in the delivery route). We provide a real-world example involving the Metro Atlanta Rapid Transit Authority rail network and identify stations whose S D values are nearly identical, meaning they have a similar proximity to other stations in the network. We then consider theoretical aspects involving asymmetric trees. For integer values of k, we considered the asymmetric tree with paths of lengths k , 2 k , ... , n k that are incident to a center vertex. We investigated trees with different values of k, and for k = 1 and k = 2 , we established necessary and sufficient conditions for the existence of two vertices with identical S D values, which has a surprising connection to the triangular numbers. Additionally, we investigated asymmetric trees with paths incident to two vertices and found a sufficient condition for vertices to have equal S D values. This leads to new combinatorial proofs of identities arising from Pascal's triangle. [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]

Katz centrality (and its limiting case, eigenvector centrality) is a frequently used tool to measure the importance of a node in a network, and to rank the nodes accordingly. One reason for its popularity is that Katz centrality can be computed very efficiently when the network is sparse, ie having only O (n) edges between its n nodes. While sparsity is common in practice, in some applications one faces the opposite situation of a very dense network, where only O (n) potential edges are missing with respect to a complete graph. We explain why and how, even for very dense networks, it is possible to efficiently compute the ranking stemming from Katz centrality for unweighted graphs, possibly directed and possibly with loops, by working on the complement graph. Our approach also provides an interpretation, regardless of sparsity, of 'Katz centrality with negative parameter' as usual Katz centrality on the complement graph. For weighted graphs, we provide instead an approximation method that is based on removing sufficiently many edges from the network (or from its complement), and we give sufficient conditions for this approximation to provide the correct ranking. We include numerical experiments to illustrate the advantages of the proposed approach. [ABSTRACT FROM AUTHOR]

As the importance of defending against cyber attacks has increased, various studies have been conducted to analyze and utilize the reachability between hosts. Although this approach effectively explains asset-based threat responses by security personnel, it is limited as a means of strategic judgment by top decision makers considering the tasks of an organization in a large-scale network environment. The purpose of this study is to develop a method for simplifying the characteristics of the attack paths of a large number of hosts by projecting them to a higher-level organization and aiding in visualizing the impacts of threats. To achieve this, a methodology is presented that supports both strategic judgment by top decision makers, considering the tasks of lower-level organizational units, and asset-based responses. This is accomplished by analyzing asset-based impacts through the generation of a Multi-Step Reachability Matrix (MRM2) and the multi-threat synthesis of low-level threat diffusion paths at the asset level, while gradually abstracting the transition information of the corresponding threats to the higher-level organization. In this paper, the diffusion process is modeled through the connectivity between hosts, and it is expected that this approach will contribute to the development of a decision support model that meets the needs of both upper- and lower-level decision makers. This is achieved by reflecting a variety of factors that influence attack and defense. These factors include the importance of the organization's mission or business to each asset, the criticality of the system function to which the asset belongs, the dependencies between assets, and the unique characteristics of the asset, including vulnerabilities, exploitation conditions, cyber resilience, and lifecycle costs. [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]