Topological Metrics Research Articles

Parasites alter food-web topology of a subarctic lake food web and its pelagic and benthic compartments

We compared three sets of highly resolved food webs with and without parasites for a subarctic lake system corresponding to its pelagic and benthic compartments and the whole-lake food web. Key topological food-web metrics were calculated for each set of compartments to explore the role parasites play in food-web topology in these highly contrasting webs. After controlling for effects from differences in web size, we observed similar responses to the addition of parasites in both the pelagic and benthic compartments demonstrated by increases in trophic levels, linkage density, connectance, generality, and vulnerability despite the contrasting composition of free-living and parasitic species between the two compartments. Similar effects on food-web topology can be expected with the inclusion of parasites, regardless of the physical characteristics and taxonomic community compositions of contrasting environments. Additionally, similar increases in key topological metrics were found in the whole-lake food web that combines the pelagic and benthic webs, effects that are comparable to parasite food-web analyses from other systems. These changes in topological metrics are a result of the unique properties of parasites as infectious agents and the links they participate in. Trematodes were key contributors to these results, as these parasites have distinct characteristics in aquatic systems that introduce new link types and increase the food web’s generality and vulnerability disproportionate to other parasites. Our analysis highlights the importance of incorporating parasites, especially trophically transmitted parasites, into food webs as they significantly alter key topological metrics and are thus essential for understanding an ecosystem’s structure and functioning.

Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task-based fMRI connectome study.

Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. Depressed and/or anxious youth (n = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls (n = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. High-risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency (Elocal, p = .022) and clustering coefficient (Cp, p = .029) and nodal metrics of the right superior frontal gyrus (SFG) (Elocal: p < .001; Cp: p = .001) in the high-risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p = .004; betweenness: p = .005; age-by-group interaction, p = .038) and right hippocampus (degree: p = .003; betweenness: p = .003). The case-control classifier achieved a cross-validation accuracy of 78.4%. Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at-risk youth.

The architecture of functional brain network modulated by driving under train running noise exposure.

A noisy environment can considerably impact drivers' attention and fatigue, endangering driving safety. Consequently, this study designed a simulated driving experimental scenario to analyse the effects of noise generated during urban rail transit train operation on drivers' functional brain networks. The experiment recruited 16 participants, and the simulated driving scenario was conducted at noise levels of 50, 60, 70, and 80 dB. Functional connectivity between all electrode pairs across various frequency bands was evaluated using the weighted phase lag index (WPLI), and a brain network based on this was constructed. Graph theoretic analysis employed network global efficiency, degree, and clustering coefficient as metrics. Significant increases in the WPLI values of theta and alpha frequency bands were observed in high noise environments (70 dB, 80 dB), as well as enhanced brain synchronisation. Furthermore, concerning the topological metrics of brain networks, it was observed that the global efficiency of brain networks in theta and alpha frequency ranges, as well as the node degree and clustering coefficients, experienced substantial growth in high noise environments (70 dB, 80 dB) as opposed to 50 dB and 60 dB. This finding indicates that high-noise environments impact the reorganisation of functional brain networks, leading to a preference for network structures with improved global efficiency. Such findings may improve our understanding of the neural mechanisms of driving under noise exposure, and thus potentially reduce road accidents to some extent.

Network Robustness Based Transient Stability Optimisation via Scheduling and Switching

Security and transient stability (TS) constrained OPFs do not include network switching and often require excessive computation time due to discretization of the TS model. This paper proposes a non-simulation methodology to optimize active power dispatching and network switching to ensure TS and system security in the preventive control mode. Network switching is introduced in the security constrained OPF and classical TS models, giving a general <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dynamic</i> security and TS constrained OPF. To ensure TS constraints are manageable in the optimization framework, TS is assessed by using proposed non-simulation based proxy measures. To this end, the key factors impacting TS are investigated and new composite robustness metrics for TS assessment are proposed; they consist of two terms, the nodal and network topology metrics. The former models generator features just before a fault, whilst the second considers impact of a fault on units. The general problem is then decomposed into two stages, the first being economic dispatching and the second optimization of network topology for TS via developed network robustness metrics. The minimum cost topology solutions are ranked by the TS performance. The proposed approach is tested on the IEEE68 Bus test system and compared with time-domain TS results.

A network model of social contacts with small-world and scale-free features, tunable connectivity, and geographic restrictions.

Small-world networks and scale-free networks are well-known theoretical models within the realm of complex graphs. These models exhibit "low" average shortest-path length; however, key distinctions are observed in their degree distributions and average clustering coefficients: in small-world networks, the degree distribution is bell-shaped and the clustering is "high"; in scale-free networks, the degree distribution follows a power law and the clustering is "low". Here, a model for generating scale-free graphs with "high" clustering is numerically explored, since these features are concurrently identified in networks representing social interactions. In this model, the values of average degree and exponent of the power-law degree distribution are both adjustable, and spatial limitations in the creation of links are taken into account. Several topological metrics are calculated and compared for computer-generated graphs. Unexpectedly, the numerical experiments show that, by varying the model parameters, a transition from a power-law to a bell-shaped degree distribution can occur. Also, in these graphs, the degree distribution is most accurately characterized by a pure power-law for values of the exponent typically found in real-world networks.

Cognition and motion dysfunction-associated brain functional network disruption in diabetic peripheral neuropathy.

Neuroimaging studies have demonstrated extensive brain functional alterations in cognitive and motor functional areas in Type 2 diabetes mellitus (T2DM) with diabetic peripheral neuropathy (DPN), suggesting potential alterations in large-scale brain networks related to DPN and associated cognition and motor dysfunction. In this study, using resting-state functional connectivity (FC) and graph theory computational approaches, we investigated the topological disruptions of brain functional networks in 28 DPN, 43 T2DM without DPN (NDPN), and 32 healthy controls (HCs) and examined the correlations between altered network topological metrics and cognitive/motor function parameters in T2DM. For global topology, NDPN exhibited a significantly decreased shortest path length compared with HCs, suggesting increased efficient global integration. For regional topology, DPN and NDPN had separated topological reorganization of functional hubs compared with HCs. In addition, DPN showed significantly decreased nodal efficiency (Enodal ), mainly in the bilateral superior occipital gyrus (SOG), right cuneus, middle temporal gyrus (MTG), and left inferior parietal gyrus (IPL), compared with NDPN, whereas NDPN showed significantly increased Enodal compared with HCs. Intriguingly, in T2DM patients, the Enodal of the right SOG was significantly negatively correlated with Toronto Clinical Scoring System scores, while the Enodal of the right postcentral gyrus (PoCG) and MTG were significantly positively correlated with Montreal Cognitive Assessment scores. Conclusively, DPN and NDPN patients had segregated disruptions in the brain functional network, which were related to cognition and motion dysfunctions. Our findings provide a theoretical basis for understanding the neurophysiological mechanism of DPN and its effective prevention and treatment in T2DM.

A longitudinal study of the brain structure network changes in HIV patients with ANI: combined VBM with SCN.

Despite the widespread adoption of combination antiretroviral therapy (cART) in managing HIV, the virus's impact on the brain structure of patients remains significant. This study aims to longitudinally explore the persistent effects of HIV on brain structure, focusing on changes in gray matter volume (GMV) and structural covariance network (SCN) among patients at the Asymptomatic Neurocognitive Impairment (ANI) stage. This research involved 45 HIV patients diagnosed with ANI and 45 demographically matched healthy controls (HCs). The participants were observed over a 1.5-year period. Differences in GMV between groups were analyzed using voxel-based morphometry (VBM), while the graph theory model facilitated the establishment of topological metrics for assessing network indices. These differences were evaluated using two-sample t-tests and paired-sample t-tests, applying the network-based statistics method. Additionally, the study examined correlations between GMV and cognitive performance, as well as clinical variables. Compared with HCs, HIV patients demonstrated reduced GMV in the right middle temporal gyrus and left middle frontal gyrus (FWE, p < 0.05), along with decreased betweenness centrality (BC) in the left anterior cingulate and paracingulate cortex. Conversely, an increase in the clustering coefficient (Cp) was observed (FDR, p < 0.05). During the follow-up period, a decline in GMV in the right fusiform gyrus (FWE, p < 0.05) and a reduction in node efficiency (Ne) in the triangular part of the inferior frontal gyrus were noted compared with baseline measurements (FDR, p < 0.05). The SCN of HIV patients exhibited small-world properties across most sparsity levels (Sigma >1), and area under the curve (AUC) analysis revealed no significant statistical differences between groups. The findings suggest that despite the administration of combination antiretroviral therapy (cART), HIV continues to exert slow and sustained damage on brain structures. However, when compared to HCs, the small-world properties of the patients' SCNs did not significantly differ, and the clustering coefficient, indicative of the overall information-processing capacity of the brain network, was slightly elevated in HIV patients. This elevation may relate to compensatory effects of brain area functions, the impact of cART, functional reorganization, or inflammatory responses.

Influence of generalist stingless bees on the structure of mutualistic flower–pollinator networks in the tropics: Temporal variation

Abstract Stingless bees (Meliponini) are expected to play a central role in structuring mutualistic networks in the Neotropics, as they are generalist and often abundant pollinators. Living in populous social colonies with a perennial life cycle, they require continuous large amounts of resources and often forage on abundant flowerings such as mass‐flowering throughout the year. In this field research, we seek to understand how temporal variations on foraging activity of stingless bees and abundance of mass‐flowering partner plants affect the topology of the plant–pollinator mutualistic networks. The networks were compared between spring and summer, periods of high and low abundances of flowerings and mass‐flowering, respectively. Bees were sampled on flowers, in replicates of floodplain fields in Atlantic Forest of southern Brazil. Interactions with partner plants were considered effective only when bees had pollen on their bodies (potential pollinators). Through analysis of pollen grains attached to their bodies, several topological metrics of networks and functional categories were obtained. The robustness or networks resistance to secondary species loss due to simulated focal species extinction was also measured. The networks maintained similar general structure throughout the year (high nestedness, moderate modularity and connectance, low community‐level specialisation and negative dependency asymmetry). Particularly, nestedness and dependency asymmetry did not change between the two seasons. Community‐level specialisation was higher in summer, contrary to expectations, when there was a collapse in the supply of floral resources and also a reduction in the abundance and foraging pressure of stingless bees. As there was also a greater number of specialist pollinators in summer, the hypothesis of temporal displacement due to foraging pressure from generalists was proposed. At the same time, stingless bees oscillated between network hubs in spring and connectors in summer, reflecting the variation in their abundance between these two seasons. In spring, the greater concentration of foraging by these generalists in the abundant mass‐flowering probably attenuated their diffuse competitive pressure on all other pollinators, even though the foraging overlap was higher in this period. In this period of high abundance of floral resources, specialist pollinators capable of expanding the realised niche are active. Based on recent theoretical conclusions of dynamic model of mutualistic networks structure that incorporated effects of inter‐specific competition and adaptive foraging, we argue that the adaptive foraging of generalist and abundant stingless bees contributes in an important way to the high nestedness and robustness of networks, which ultimately favour the coexistence of species in the long term. Particularly, taking the high intra‐annual turnover of bee and plant species between the two seasons, and the similar floral constancy of both generalist stingless bees and specialist pollinators, we also infer that stingless bees act as generalised pollinators in the networks rewiring throughout the year.

Disrupted topological organization of the default mode network in mild cognitive impairment with subsyndromal depression: A graph theoretical analysis.

Subsyndromal depression (SSD) is common in mild cognitive impairment (MCI). However, the neural mechanisms underlying MCI with SSD (MCID) are unclear. The default mode network (DMN) is associated with cognitive processes and depressive symptoms. Therefore, we aimed to explore the topological organization of the DMN in patients with MCID. Forty-two MCID patients, 34 MCI patients without SSD (MCIND), and 36 matched healthy controls (HCs) were enrolled. The resting-state functional connectivity of the DMN of the participants was analyzed using a graph theoretical approach. Correlation analyses of network topological metrics, depressive symptoms, and cognitive function were conducted. Moreover, support vector machine (SVM) models were constructed based on topological metrics to distinguish MCID from MCIND. Finally, we used 10 repeats of 5-fold cross-validation for performance verification. We found that the global efficiency and nodal efficiency of the left anterior medial prefrontal cortex (aMPFC) of the MCID group were significantly lower than the MCIND group. Moreover, small-worldness and global efficiency were negatively correlated with depressive symptoms in MCID, and the nodal efficiency of the left lateral temporal cortex and left aMPFC was positively correlated with cognitive function in MCID. In cross-validation, the SVM model had an accuracy of 0.83 [95% CI 0.79-0.87], a sensitivity of 0.88 [95% CI 0.86-0.90], a specificity of 0.75 [95% CI 0.72-0.78] and an area under the curve of 0.88 [95% CI 0.85-0.91]. The coexistence of MCI and SSD was associated with the greatest disrupted topological organization of the DMN. The network topological metrics could identify MCID and serve as biomarkers of different clinical phenotypic presentations of MCI.

Grothendieck lines in 3d N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 2 SQCD and the quantum K-theory of the Grassmannian

We revisit the 3d GLSM computation of the equivariant quantum K-theory ring of the complex Grassmannian from the perspective of line defects. The 3d GLSM onto X = Gr(Nc, nf) is a circle compactification of the 3d N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 2 supersymmetric gauge theory with gauge group UNck,k+lNc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{U}{\\left({N}_c\\right)}_{k,k+l{N}_c} $$\\end{document} and nf fundamental chiral multiplets, for any choice of the Chern-Simons levels (k, l) in the ‘geometric window’. For k=Nc−nf2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ k={N}_c-\\frac{n_f}{2} $$\\end{document} and l = −1, the twisted chiral ring generated by the half-BPS lines wrapping the circle has been previously identified with the quantum K-theory ring QKT(X). We identify new half-BPS line defects in the UV gauge theory, dubbed Grothendieck lines, which flow to the structure sheaves of the (equivariant) Schubert varieties of X. They are defined by coupling N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 2 supersymmetric gauged quantum mechanics of quiver type to the 3d GLSM. We explicitly show that the 1d Witten index of the defect worldline reproduces the Chern characters for the Schubert classes, which are written in terms of double Grothendieck polynomials. This gives us a physical realisation of the Schubert-class basis for QKT(X). We then use 3d A-model techniques to explicitly compute QKT(X) as well as other K-theoretic enumerative invariants such as the topological metric. We also consider the 2d/0d limit of our 3d/1d construction, which gives us local defects in the 2d GLSM, the Schubert defects, that realise equivariant quantum cohomology classes.

Comparison of topological functionality-based resilience metrics using link criticality

Resilient road networks ensure that transportation systems can withstand and return to normal performance fast after disruptions. Ensuring a better network structure for the system promises better resilience, irrespective of demand variations. Comparison between the ability of different topological functionality-based metrics in literature to measure resilience is an unexplored area. This study will bridge the gap by evaluating four such metrics. The distinguishing feature of the study is that link criticality approach and traffic functionality measures are used for comparing the metrics. The links are removed according to the order of their criticality ranking, and network performance is measured using Global Importance Index. The advantages of the proposed methodology are twofold. First, the position of critical links provides insight into the network characteristics measured by the metric. Second, the usage of traffic functionality-based performance measure for comparison ensures that the metric captures traffic perspective also. The position of critical links obtained using the four metrics for the networks considered in the study provides interesting observations about the network property that influences them. Also, the networks degrade the maximum when links are removed according to number of independent paths ranking when the network is not already majorly disrupted. Hence, it is more effective at measuring resilience in such networks. For networks that are already disrupted, removing links based on Global efficiency affected the network more.

Cleaning symbiosis in coral reefs of Jardines de la Reina National Park

Background Cleaning symbiotic interactions are an important component of coral reef biodiversity and the study of the characteristics of these interacting species networks allows to assess the health of communities. The coral reefs of Jardines de la Reina National Park (JRNP) are subject to a protection gradient and there is a lack of knowledge about the effect of different levels of protection on the cleaning mutualistic networks in the area. The present study aims to characterize the mutualistic cleaning networks in the reefs of JRNP and to assess the potential effect of the protection gradient on their characteristics. Methods We visited 26 reef sites distributed along the National Park and performed 96 band transects (50 m × 4 m). Low, medium and highly protected regions were compared according to the number of cleaning stations and the abundance and number of species of clients and cleaners associated with them. Additionally, we built interaction networks for the three regions and the entire archipelago based on a total of 150 minutes’ video records of active cleaning stations. We assessed ecological networks characteristics (specialization, nestedness) using network topological metrics. Results We found a high diversity and complex cleaning interaction network with 6 cleaner species and 39 client species, among them, the threatened grouper Epinephelus striatus was one of the most common clients. No clear effect of the protection level on the density, abundance or diversity of cleaners and clients was detected during this study. However, we found that the network structure varied among regions, with the highly protected region being more specialized and less nested than the other regions. Our research reveals some patterns that suggest the effect of fishing pressure on cleaning symbiosis, as fishing may reduce the abundance and composition of client species, especially those that are targeted by fishers. However, fishing pressure may not be the main factor influencing cleaning symbiosis inside of the National Park, as other factors, such as habitat quality or environmental conditions may have stronger effects on the demand for cleaning services and the interactions between cleaners and clients. Our research provides insights into the factors that influence cleaning symbiosis and its implications for coral reef conservation and management.

Benchmark Analysis for Robustness of Multi-Scale Urban Road Networks Under Global Disruptions

To date immunity to disruptions of multi-scale urban road networks (URNs) has not been effectively quantified. This study uses robustness as a meaningful - if partial - representation of immunity. We propose a novel Relative Area Index (RAI) based on traffic assignment theory to quantitatively measure the robustness of URNs under global capacity degradation due to three different types of disruptions, which takes into account many realistic characteristics. We also compare the RAI with weighted betweenness centrality, a traditional topological metric of robustness. We employ six realistic URNs as case studies for this comparison. Our analysis shows that RAI is a more effective measure of the robustness of URNs when multi-scale URNs suffer from global disruptions. This improved effectiveness is achieved because of RAI's ability to capture the effects of realistic network characteristics such as network topology, flow patterns, link capacity, and travel demand. Also, the results highlight the importance of central management when URNs suffer from disruptions. Our novel method may provide a benchmark tool for comparing robustness of multi-scale URNs, which facilitates the understanding and improvement of network robustness for the planning and management of URNs.

Depression- and anxiety-associated disrupted brain structural networks revealed by probabilistic tractography in thyroid associated ophthalmopathy

BackgroundPatients with thyroid-associated opthalmopathy (TAO) have widespread white matter (WM) abnormalities in the emotional and cognitive functional regions. However, the topological representation of these WM abnormalities and the network-level structural aberrations underlying TAO and concomitant affective disorders are still unclear. MethodsWe used probabilistic diffusion tractography and graph theory to investigate brain network topology in 37 active, 35 inactive TAO patients and 23 healthy controls. Then, we evaluated the partial correlations between network topological metrics and clinical parameters. ResultsFor global topology, only active TAO patients exhibited significantly decreased global (Eglob) and local (Eloc) efficiency compared with controls, while no significant difference was observed between active and inactive TAO patients. For regional topology, we found a significantly decreased nodal efficiency in the left orbital superior frontal gyrus (ORBsup), medial orbital superior frontal gyrus (ORBsupmed), hippocampus and amygdala in active TAO patients compared with inactive ones. Intriguingly, Eglob, Eloc, and nodal efficiency of left ORBsup, ORBsupmed, olfactory cortex, gyrus rectus, hippocampus, right parahippocampal gyrus and amygdala had significantly positive correlations with anxiety/depression scores, bilateral exophthalmos and intraocular pressure in active TAO patients, while no significant correlation was observed in inactive TAO patients. LimitationsNo longitudinal follow-up. ConclusionsWM networks of TAO are characterized by decreased local specialization and global integration in the active phase, and decreased nodal efficiency highly related to anxiety and depression in the emotional and cognitive regions. Our findings provide new insight regarding the neurobiological mechanisms of TAO and contribute to the treatment of concomitant affective disorders.

Factors of Accessibility Metrics and Research Progress

Accessibility studies are an important concept in urban transport systems and play an important role in human geography and regional economic studies. Due to the abstract nature of the concept of accessibility, it is easy to have a one-sided understanding and ambiguous knowledge of accessibility. In order to understand accessibility accurately, this paper summarize the concept of accessibility and its influencing factors. In addition, as accessibility research deepens, accessibility measurement methods and application areas are expanding, and this paper classifies different measurement methods and discusses their advantages, disadvantages and applications. The following conclusions are drawn: firstly, according to the needs of the research object and the characteristics of the facilities, the factors influencing accessibility are divided into four types of factors: transport system factors, land resource use, time description and individual characteristics; secondly, according to the purpose and conditions of the research, the broad categories of accessibility research methods can be divided into three types: metrics based on mathematical statistics, metrics based on geometric networks and metrics based on topological networks; thirdly, different Thirdly, different accessibility research methods have different scope of application, and each has its own advantages and disadvantages. In the future, accessibility research can be improved in four directions: spatial-temporal research, adoption of appropriate accessibility methods to avoid model shortcomings, research on topological metrics and construction of a perfect accessibility metric system. In this paper, the concept of spatial accessibility and the accessibility metrics of public service facilities in existing research are reviewed, and the different methods used are compared and analyzed, in the hope of providing assistances in the knowledge and selection of relevant research methods.

Altered single-subject gray matter structural networks in first-episode drug-naïve adolescent major depressive disorder

Although previous studies have demonstrated regional gray matter (GM) structural abnormalities in adolescents with major depressive disorder (MDD), how the topological organization of GM networks is affected in these patients is still unclear. Structural magnetic resonance imaging data were acquired from 100 first-episode drug-naïve adolescent MDD patients and 80 healthy controls (HCs). Whole-brain GM structural network was constructed for each subject, and a graph theory analysis was used to calculate the topological metrics of GM networks. Adolescent MDD patients showed significantly lower cluster coefficient and local efficiency compared to HCs. Compared to controls, adolescent MDD patients showed higher nodal centralities in the bilateral cuneus, left lingual gyrus, and right middle occipital gyrus and lower nodal centralities in the bilateral dorsolateral superior frontal gyrus, bilateral middle frontal gyrus, right anterior cingulate and paracingulate gyri, bilateral hippocampus, bilateral amygdala, bilateral caudate nucleus, and bilateral thalamus. Nodal centralities of the hippocampus were negatively associated with symptom severity and illness duration. Our findings suggest disrupted topological organization of GM structural networks in adolescent MDD patients. Impaired local segregation and abnormal nodal centralities in the prefrontal-subcortical-limbic areas and visual cortex regions may play important roles in the neurobiology of adolescent-onset MDD.

Recovering Power Grids Using Strategies Based on Network Metrics and Greedy Algorithms.

For this study, we investigated efficient strategies for the recovery of individual links in power grids governed by the direct current (DC) power flow model, under random link failures. Our primary objective was to explore the efficacy of recovering failed links based solely on topological network metrics. In total, we considered 13 recovery strategies, which encompassed 2 strategies based on link centrality values (link betweenness and link flow betweenness), 8 strategies based on the products of node centrality values at link endpoints (degree, eigenvector, weighted eigenvector, closeness, electrical closeness, weighted electrical closeness, zeta vector, and weighted zeta vector), and 2 heuristic strategies (greedy recovery and two-step greedy recovery), in addition to the random recovery strategy. To evaluate the performance of these proposed strategies, we conducted simulations on three distinct power systems: the IEEE 30, IEEE 39, and IEEE 118 systems. Our findings revealed several key insights: Firstly, there were notable variations in the performance of the recovery strategies based on topological network metrics across different power systems. Secondly, all such strategies exhibited inferior performance when compared to the heuristic recovery strategies. Thirdly, the two-step greedy recovery strategy consistently outperformed the others, with the greedy recovery strategy ranking second. Based on our results, we conclude that relying solely on a single metric for the development of a recovery strategy is insufficient when restoring power grids following link failures. By comparison, recovery strategies employing greedy algorithms prove to be more effective choices.

Towards identifying influential nodes in complex networks using semi-local centrality metrics

The influence of the node refers to the ability of the node to disseminate information. The faster and wider the node spreads, the greater its influence. There are many classical topological metrics that can be used to evaluate the influencing ability of nodes. Degree centrality, betweenness centrality, closeness centrality and local centrality are among the most common metrics for identifying influential nodes in complex networks. Degree centrality is very simple but not very effective. Global metrics such as betweenness centrality and closeness centrality can better identify influential nodes, but they are not compatible on large-scale networks due to their high complexity. In order to design a ranking method of influential nodes, in this paper a new semi-local centrality metric is proposed based on the relative change in the average shortest path of the entire network. Meanwhile, our metric provides a quantitative global importance model to measure the overall influence of each node. To evaluate the performance of the proposed centrality metric, we use the Susceptible-Infected-Recovered (SIR) epidemic model. Experimental results on several real-world networks show that the proposed metric has competitive performance in identifying influential nodes with existing equivalent centrality metrics and has high efficiency in dealing with large-scale networks. The effectiveness of the proposed metric has been proven with numerical examples and Kendall's coefficient.

Analysis of the impact of Suez Canal blockage on the global shipping network

This study aims to quantitatively analyze the impact of the Suez Canal blockage on global maritime transportation networks. The Suez Canal, a critical global maritime transport route, experienced a significant disruption due to a ship grounding accident in March 2021, exposing the fragility of global logistics supply chains. We constructed a comprehensive shipping network, integrating real trajectory data from automatic identification system (AIS) devices on ships collected in 2018. The network comprises 2713 nodes and 137,830 links, with defined targeted (Suez Canal blockage) and random attack modes. Our analysis, based on multiple network topology metrics, reveals that the blockage had a considerable effect on the global shipping network, significantly more than random disruptions of comparable scale. The incident led to a decrease in network accessibility and connectivity, conforming to the law of distance attenuation. The effects varied across continents; Africa experienced the most significant impact, while Asia and Europe were less affected. Europe's developed transport system effectively mitigated the impact. Data on different ship types passing through the Suez Canal showed that container ships and petrochemical tankers were the most affected. This research underlines the Suez Canal's significance to global shipping and the necessity of robust supply chain management strategies to limit the fallout from similar future incidents.

ENRN: A System for Evaluating Network Resilience against Natural Disasters

The frequency and severity of natural disasters is surging, posing an urgent need for robust communication network infrastructure that is capable of withstanding these events. In this paper, we present a groundbreaking graph-theoretic system designed to evaluate and enhance network resilience in the face of natural disasters. Our solution harnesses the power of topological robustness metrics, integrating real-time weather data, geographic information, detailed network topology data, advanced resilience algorithms, and continuous network monitoring. The proposed scheme considers four major real-world U.S.-based network providers and evaluates their physical topologies against two major hurricanes. Our novel framework quantifies the important characteristics of network infrastructure; for instance, AT&amp;T is identified to have fared better against Hurricane Ivan (57.98 points) than Hurricane Katrina (39.17 points). We not only provide current insights into network infrastructure resilience, but also uncover valuable findings that shed light on the performance of backbone U.S. networks during hurricanes. Furthermore, our findings provide actionable insights to enrich the overall survivability and functionality of communication networks, mitigating the adverse impacts of natural disasters on communication systems and critical services in terms of improving network resiliency via adding additional nodes and link or rewiring.