Changes In Network Structure Research Articles

Influence and Modeling of Loading Frequency on Dynamic Mechanical Properties of Thermally-Aging HTPB Coating

For the sake of studying the influence of loading frequency on the hydroxyl-terminated polybutadiene (HTPB) coating’s dynamic mechanical properties during aging, the one month’s thermal accelerated aging test was carried out at 70°C. The dynamic mechanical properties of the aged HTPB coatings were tested through dynamic mechanical analysis (DMA) Q800 with the loading frequency range of 0~100Hz, the dynamic strain amplitude of 0.1% and the test temperature of 25°C. The change models of the dynamic modulus with the loading frequency were established. The results showed that with the extension of the aging time, the storage modulus and the loss modulus both rose, which were related with the change of the crosslinking network structure. The storage modulus increased exponentially with the loading frequency, and the correlation coefficients fitted by the exponential models were all greater than 0.96. The loss modulus changed in sections. When the loading frequency was less than 70 Hz, the loss modulus showed a cubic function growth relationship with the loading frequency, and the correlation coefficients were larger than 0.98; when the loading frequency was between 70 Hz and 100 Hz, the loss modulus showed a quadratic function relationship with the loading frequency that first decreased and then increased, and the correlation coefficients were all larger than 0.97.

Analysis of extracellular matrix network dynamics in cancer using the MatriNet database

The extracellular matrix (ECM) is a three-dimensional network of proteins of diverse nature, whose interactions are essential to provide tissues with the correct mechanical and biochemical cues they need for proper development and homeostasis. Changes in the quantity of extracellular matrix (ECM) components and their balance within the tumor microenvironment (TME) accompany and fuel all steps of tumor development, growth and metastasis, and a deeper and more systematic understanding of these processes is fundamental for the development of future therapeutic approaches. The wealth of “big data” from numerous sources has enabled gigantic steps forward in the comprehension of the oncogenic process, also impacting on our understanding of ECM changes in the TME. Most of the available studies, however, have not considered the network nature of ECM and the possibility that changes in the quantity of components might be regulated (co-occur) in cancer and significantly “rebound” on the whole network through its connections, fundamentally altering the matrix interactome. To facilitate the exploration of these network-scale effects we have implemented MatriNet (www.matrinet.org), a database enabling the study of structural changes in ECM network architectures as a function of their protein-protein interaction strengths across 20 different tumor types. The use of MatriNet is intuitive and offers new insights into tumor-specific as well as pan-cancer features of ECM networks, facilitating the identification of similarities and differences between cancers as well as the visualization of single-tumor events and the prioritization of ECM targets for further experimental investigations.

Six-year changes of posttraumatic stress symptoms and depressive symptoms among Chinese earthquake survivors: A network analysis

BackgroundThe risk factors of Posttraumatic Stress Symptoms (PTSS) and depressive symptoms have been well-established, but whether the network structure of their symptoms changes over time remains unclear. This study aims to examine the six-year changes of network structure of PTSS and depressive symptoms among Wenchuan earthquake adult survivors in China. MethodsIn this pooled cross-sectional study, respondents were sampled from the same population at each of the five waves (N = 1343, 1205, 1177, 1376, and 1339). The network structure of them was investigated using network analyses. ResultsThe study shows network connections stable across waves were the positive connections between hyperarousal and intrusions, hyperarousal and somatic symptoms, and two dimensions of positive effects. Stable negative connections were those between depressed affects and positive effects, avoidance and depressed affects, avoidance with interpersonal symptoms and avoidance with somatic symptoms. Across waves, fearful emotion consistently was the strongest bridge symptom connecting with PTSS symptoms. However, for PTSS the strongest bridge symptom varied across time as it was avoidance in wave 1 but were hyperarousal in other four waves. LimitationsThis study was based on a pooled cross-sectional survey, which inhibits conclusions regarding causal influences between symptoms at the individual patient level. ConclusionsThe network structure of PTSS and depressive symptoms was partly stable, yet also varied across survey waves. Core symptom clusters for PTSS and depressive symptoms were avoidance and depressed affect, respectively. The central role of these clusters in PTSS and depressive symptoms has important implications to future psychiatric programs.

Evaluation of macular and choroidal thickness in healthy residents living at high altitude.

Purpose:Assessment of long-term effects of high altitude on choroidal thickness.Methods:This prospective cross-sectional study included 88 and 79 age- and sex-matched healthy individuals who were living at sea-level (SL group) and high-altitude (HA group), respectively. Participants were required to have resided in the same place for at least 10 years. Spectral-domain optical coherence tomography (SD-OCT) scans were conducted in two different and were performed within the same time (08:00 am to 10:00 am). Central macular thickness (CMT) and choroidal thickness were measured at five different points (i.e., at the central fovea and 1 mm and 2 mm temporal and nasal of the fovea). Blood hemoglobin (Hb), red blood cell (RBC), hematocrit (Htc) levels, blood oxygen saturation, heart rate, and body mass index (BMI) were compared between groups statistically.Results:The HA group had a mean age of 47.5 ± 13.3 years, whereas the SL group was 48.7 ± 13.4 years (P = 0.57). There was no significant difference between the groups in terms of CMT. Subfoveal choroidal thickness (SCFT) was 282.73 ± 87.82 mm in the HA group and 310.49 ± 74.73 in the SL group (P = 0.02). The choroid was found to be thinner at all the measured locations in the HA group except the 2 mm nasal point of the fovea. However, only the difference at an SFCT was statistically significant. Furthermore compared with the SL group statistically significant higher Hb, RBC, Htc levels were determined in the HA group. In the multiple linear regression model analysis, age was found an only effective confounder factor for SCFT (P = 0.001, 95% CI 4.132–2.476).Conclusion:The systemic adaptive changes due to chronic high altitude exposure may cause structural changes in the choroidal vascular network. The current study results revealed significant thinning only at SFCT. Large-scale longitudinal studies are needed to obtain more definitive data on this subject.

Inequality and cooperation in social networks

Social networks are fundamental to the broad scale cooperation observed in human populations. But by structuring the flow of benefits from cooperation, networks also create and sustain macro-level inequalities. Here we ask how two aspects of inequality shape the evolution of cooperation in dynamic social networks. Results from a crowdsourced experiment (N = 1080) show that inequality alters the distribution of cooperation within networks such that participants engage in more costly cooperation with their wealthier partners in order to maintain more valuable connections to them. Inequality also influences network dynamics, increasing the tendency for participants to seek wealthier partners, resulting in structural network change. These processes aggregate to alter network structures and produce greater system-level inequality. The findings thus shed critical light on how networks serve as both boon and barrier to macro-level human flourishing.

Can Cognitive training Reignite Compensatory Mechanisms in Advanced Multiple Sclerosis Patients? An Explorative Morphological Network Approach

Multiple Sclerosis (MS) has been shown to significantly impair brain connectivity, as alterations in functional and structural networks have been identified and associated with clinical status, particularly cognitive deficits. We aimed to identify structural connectivity changes in grey matter networks following cognitive rehabilitation (CR) in persons with MS (PwMS). Fifteen long-standing PwMS underwent a 5-week CR-program and five healthy controls (HC) were also investigated. T1-weighted MRI scans and neuropsychological tests were obtained before and after CR. T1-weighted scans were used to examine grey matter networks with graph analytic parameters [betweenness centrality (BC), degree (D), clustering (Cl), path length (PL) and small world properties: connectedness, gamma and lambda values]. Results were analysed at the whole brain level and for each brain lobe. Before CR, PwMS displayed lower values for D in the left parietal lobe (p = 0.009) compared to HC. After CR, significant increases in Cl located in frontal (p = 0.024) and temporal (p = 0.026) regions in PwMS were accompanied by significant decreases in PL located in the right parietal lobe (p = 0.025) and BC globally (p = 0.010). Overall, CR may prevent a network worsening in long-standing PwMS by increasing local efficiency of the brain and therefore facilitating compensation mechanisms.

Upregulating positive affect through compassion: Psychological and physiological evidence

Positive emotion regulation, that is, upregulating, maintaining, and savoring positive emotions, also bears the potential to counteract and thus mitigate negative affect. In this narrative review, we report on the social emotion of compassion as a particularly efficient form of positive emotion regulation. Compassion emerges as an affiliative response to the suffering of others. It is characterized by feelings of warmth and kindness and an initiation of prosocial caring behavior towards others. The inherent positivity of compassion is also in line with its related neural correlates. Compassion is associated with activity in the ventral striatum, the (subgenual) anterior cingulate cortex, and the orbitofrontal cortex, brain regions related to strong positive emotions, such as romantic and maternal love. In addition to its long tradition in Eastern philosophy, the practice of compassion has in recent years found its way into interventions in Western psychology, for example, within compassion-focused therapy. Recent findings confirm that affect-related mental training promoting compassion is also linked to functional and structural changes in neural networks associated with positive emotions and emotion regulation. This compassion-related plasticity in the neural systems of positive emotion regulation suggests that incorporating compassion into psychological interventions could prove to be a particularly effective way to support positive emotion regulation.

Viewing the network parameters and H‐factors from the perspective of geometry

Recent studies have shown that there is a profound connection between the existence of H -factors under attack circumstances and the parameters to measure the vulnerability of the network. The disadvantage of the previous theoretical conclusions is that the connectivity is often regarded as fixed, and the relationship between other network parameters and the H -factor is explored. However, in a real situation, as the network structure changes, connectivity becomes a dynamically variational parameter, and its changing will affect other parameters to make corresponding changes. In this study, we treat all parameters as a complex system that restricts each other, consider their mutual constraints from a geometric point of view, and apply high-dimensional surfaces to characterize their relationships. Seven network parameters including toughness and binding number are considered, and the concrete expression form of the surfaces in several specific settings are obtained. Furthermore, the local version for these seven network parameters are introduced.

Detecting changes in dynamical structures in synchronous neural oscillations using probabilistic inference

Recent neuroscience studies have suggested that cognitive functions and learning capacity are reflected in the time-evolving dynamics of brain networks. However, an efficient method to detect changes in dynamical brain structures using neural data has yet to be established. To address this issue, we developed a new model-based approach to detect change points in dynamical network structures by combining the model-based network estimation with a phase-coupled oscillator model and sequential Bayesian inference. By giving the model parameter as the prior distribution, applying Bayesian inference allows the extent of temporal changes in dynamic brain networks to be quantified by comparing the prior distribution with the posterior distribution using information theoretical criteria. For this, we used the Kullback-Leibler divergence as an index of such changes. To validate our method, we applied it to numerical data and electroencephalography data. As a result, we confirmed that the Kullback-Leibler divergence only increased when changes in dynamical network structures occurred. Our proposed method successfully estimated both directed network couplings and change points of dynamical structures in the numerical and electroencephalography data. These results suggest that our proposed method can reveal the neural basis of dynamic brain networks.

Changes of network structure and water distribution in sludge with the stratified extraction of extracellular polymeric substances.

The water in sludge is trapped within the extracellular polymeric substance (EPS) with gelatinous structure, greatly challenging the sludge deep dewatering. In this paper, the effect of the EPS viscoelasticity and the structural characteristics of sludge flocs on water distribution was revealed to provide a highly efficient approach in research on sludge dewatering. After biological, and physical method conditioning, the change of viscoelasticity and sludge network structure before/after EPS extraction was comprehensively explored, together with the sludge dewaterability and water distribution. The results suggested the proportion of capillary water and adsorption water carried in soluble EPS (S-EPS) was 59.17% and 40.83%, and that in tightly bound EPS (TB-EPS) was 54.77% and 45.23%, respectively. By contrast, the capillary water in loosely bound EPS (LB-EPS) accounted for as high as 99.99%. In comparison with raw sludge, adsorption water proportion in TB-EPS and S-EPS was reduced after lysozyme (LZM) or freezing-thaw conditioning, which was ascribed to reduction of EPS viscosity and the weakness of water adsorption capacity. Additionally, the sludge yield stress (τy) value first reduced and then increased with the extraction of EPS. Meanwhile, the consistency coefficient (k) also decreased from 4.23Pa·sn to 0.006Pa·sn and then slightly increased after LZM conditioning. This observation indicated the sludge system became sensitive to shearing, and its network structural strength as well as colloid elasticity first weakened and then slightly strengthened. In addition, after LZM or freezing-thaw conditioning, the sludge particle size significantly increased after TB-EPS extraction, while the sludge particle more easily absorbed water molecules, thereby increasing adsorption water and capillary water within the sludge flocs. This phenomenon also resulted in an increasing trend of capillary suction time (CST) after TB-EPS extraction, indicating the deterioration of sludge filtration performance.

Flattened Structural Network Changes and Association of Hyperconnectivity With Symptom Severity in 2-7-Year-Old Children With Autism.

Understanding the brain differences present at the earliest possible diagnostic age for autism spectrum disorder (ASD) is crucial for delineating the underlying neuropathology of the disorder. However, knowledge of brain structural network changes in the early important developmental period between 2 and 7 years of age is limited in children with ASD. In this study, we aimed to fill the knowledge gap by characterizing age-related brain structural network changes in ASD from 2 to 7 years of age, and identify sensitive network-based imaging biomarkers that are significantly correlated with the symptom severity. Diffusion MRI was acquired in 30 children with ASD and 21 typically developmental (TD) children. With diffusion MRI and quantified clinical assessment, we conducted network-based analysis and correlation between graph-theory-based measurements and symptom severity. Significant age-by-group interaction was found in global network measures and nodal efficiencies during the developmental period of 2–7 years old. Compared with significant age-related growth of the structural network in TD, relatively flattened maturational trends were observed in ASD. Hyper-connectivity in the structural network with higher global efficiency, global network strength, and nodal efficiency were observed in children with ASD. Network edge strength in ASD also demonstrated hyper-connectivity in widespread anatomical connections, including those in default-mode, frontoparietal, and sensorimotor networks. Importantly, identified higher nodal efficiencies and higher network edge strengths were significantly correlated with symptom severity in ASD. Collectively, structural networks in ASD during this early developmental period of 2–7 years of age are characterized by hyper-connectivity and slower maturation, with aberrant hyper-connectivity significantly correlated with symptom severity. These aberrant network measures may serve as imaging biomarkers for ASD from 2 to 7 years of age.

Large-scale structural network change correlates with clinical response to rTMS in depression.

Response to repetitive transcranial magnetic stimulation (rTMS) among individuals with major depressive disorder (MDD) varies widely. The neural mechanisms underlying rTMS are thought to involve changes in large-scale networks. Whether structural network integrity and plasticity are associated with response to rTMS therapy is unclear. Structural MRIs were acquired from a series of 70 adult healthy controls and 268 persons with MDD who participated in two arms of a large randomized, non-inferiority trial, THREE-D, comparing intermittent theta-burst stimulation to high-frequency rTMS of the left dorsolateral prefrontal cortex (DLPFC). Patients were grouped according to percentage improvement on the 17-item Hamilton Depression Rating Score at treatment completion. For the entire sample and then for each treatment arm, multivariate analyses were used to characterize structural covariance networks (SCN) from cortical gray matter thickness, volume, and surface area maps from T1-weighted MRI. The association between SCNs and clinical improvement was assessed. For both study arms, cortical thickness and volume SCNs distinguished healthy controls from MDD (p = 0.005); however, post-hoc analyses did not reveal a significant association between pre-treatment SCN expression and clinical improvement. We also isolated an anticorrelated SCN between the left DLPFC rTMS target site and the subgenual anterior cingulate cortex across cortical measures (p = 0.0004). Post-treatment change in cortical thickness SCN architecture was associated with clinical improvement in treatment responders (p = 0.001), but not in non-responders. Structural network changes may underpin clinical response to rTMS, and SCNs are useful for understanding the pathophysiology of depression and neural mechanisms of plasticity and response to circuit-based treatments.

Social Network Evolution: The Case of UK Companies Before and After Brexit

The Brexit referendum has impacted both the UK and the EU economies in several ways. The uncertainty around Brexit highlighted the importance of a relationships network between directors of companies to access information and resources that are necessary for optimal decision making. It is difficult to develop informed business and economy policies without a deep understanding of the magnitude of Brexit on business-to-business relationships with EU-based firms. This study aims to analyze the impact of the passage of the Brexit referendum on the evolution of board interlock networks. The study uses network analysis to measure the evolution of UK-EU directors’ relationships over the Brexit period, predominantly between the 2010 and 2020 period. The study models the structural changes in dynamic networks by converting this evolving network into static graphs on yearly basis. The analysis indicates that links formation in the UK is affected negatively by the Brexit referendum. It also has a negative impact on forming a new link with potential companies’ directors in the EU, but it shows a rising tendency for shared affiliation bias analysis. Interestingly, the contradicted trend in 2007, the number of directors’ connection in consumer service and food & drug sectors was decreasing in the UK while rocketing in the EU. Doi: 10.28991/ESJ-2022-06-01-01 Full Text: PDF

Optimizing the energy storage and charge-discharge performance of borate glass-ceramics by adjusting the glass structure

In this work, the niobate-based borate glass-ceramic system K 2 O–Na 2 O–Nb 2 O 5 –B 2 O 3 was proposed for the first time, in which the presence of alkali metal oxides not only tends to form ferroelectric crystalline phase to obtain high permittivity, but also optimizes the borate glass network structure to enhance the breakdown strength. The change of borate glass network structure and the influence on conductivity and carriers migrate is systematically discussed. The results show that the high breakdown performance is attributed to the transformation from [B∅ 2 O − ] triangle to [B∅ 4 ] - tetrahedron realizes the high extent of glass network polymerization, which effectively impedes carriers migration and reduces the conductivity. The high permittivity and low dielectric loss are obtained in the range of room temperature to 200 °C. Compared to other niobate-based glass-ceramics, the potassium sodium niobate borate glass-ceramic simultaneously achieve high discharge energy density, high power density and rapid discharge rate (∼14 ns).

Imaging Clinical Subtypes and Associated Brain Networks in Alzheimer's Disease.

Alzheimer’s disease (AD) does not present uniform symptoms or a uniform rate of progression in all cases. The classification of subtypes can be based on clinical symptoms or patterns of pathological brain alterations. Imaging techniques may allow for the identification of AD subtypes and their differentiation from other neurodegenerative diseases already at an early stage. In this review, the strengths and weaknesses of current clinical imaging methods are described. These include positron emission tomography (PET) to image cerebral glucose metabolism and pathological amyloid or tau deposits. Magnetic resonance imaging (MRI) is more widely available than PET. It provides information on structural or functional changes in brain networks and their relation to AD subtypes. Amyloid PET provides a very early marker of AD but does not distinguish between AD subtypes. Regional patterns of pathology related to AD subtypes are observed with tau and glucose PET, and eventually as atrophy patterns on MRI. Structural and functional network changes occur early in AD but have not yet provided diagnostic specificity.

Airport pricing versus (grandfathered) slots: A generalization

Many passengers can choose among various destinations for their flight trips (for instance, a leisure trip from Asia to Europe or the US). This study tests the sensitivity of the outcomes of equilibrium congestion policies with respect to changes in airport network and demand structures. A major feature is to incorporate substitute destination choices for origin–destination passengers into the analysis of equilibrium airport congestion policies involving slot or pricing policies. The analysis shows that the presence of substitute destination choices is a necessary condition for equilibrium slot quantities to reach the first-best outcome that maximizes the welfare of all airport regions whereas equilibrium pricing levels will always be too high relative to the first-best prices independent of the presence or absence of substitute destination choices. Examples based on specific functional forms and numerical simulations are used to illustrate the main results.

Cognitive Implications of Correlated Structural Network Changes in Schizophrenia

BackgroundSchizophrenia is a brain disorder characterized by diffuse, diverse, and wide-spread changes in gray matter volume (GM) and white matter structure (fractional anisotropy, FA), as well as cognitive impairments that greatly impact an individual’s quality of life. While the relationship of each of these image modalities and their links to schizophrenia status and cognitive impairment has been investigated separately, a multimodal fusion via parallel independent component analysis (pICA) affords the opportunity to explore the relationships between the changes in GM and FA, and the implications these network changes have on cognitive performance.MethodsImages from 73 subjects with schizophrenia (SZ) and 82 healthy controls (HC) were drawn from an existing dataset. We investigated 12 components from each feature (FA and GM). Loading coefficients from the images were used to identify pairs of features that were significantly correlated and showed significant group differences between HC and SZ. MANCOVA analysis uncovered the relationships the identified spatial maps had with age, gender, and a global cognitive performance score.ResultsThree component pairs showed significant group differences (HC > SZ) in both gray and white matter measurements. Two of the component pairs identified networks of gray matter that drove significant relationships with cognition (HC > SZ) after accounting for age and gender. The gray and white matter structural networks identified in these three component pairs pull broadly from many regions, including the right and left thalamus, lateral occipital cortex, multiple regions of the middle temporal gyrus, precuneus cortex, postcentral gyrus, cingulate gyrus/cingulum, lingual gyrus, and brain stem.ConclusionThe results of this multimodal analysis adds to our understanding of how the relationship between GM, FA, and cognition differs between HC and SZ by highlighting the correlated intermodal covariance of these structural networks and their differential relationships with cognitive performance. Previous unimodal research has found similar areas of GM and FA differences between these groups, and the cognitive deficits associated with SZ have been well documented. This study allowed us to evaluate the intercorrelated covariance of these structural networks and how these networks are involved the differences in cognitive performance between HC and SZ.

Inducing banana Fusarium wilt disease suppression through soil microbiome reshaping by pineapple–banana rotation combined with biofertilizer application

Abstract. Crop rotation and biofertilizer application have historically been employed as efficient management strategies for soil-borne disease suppression through soil microbiome manipulation. However, how this occurs and to what extent the combination of methods affects the microbiota reconstruction of diseased soil is unknown. In this study, pineapple–banana rotation combined with biofertilizer application was used to suppress banana Fusarium wilt disease, and the effects on both bacterial and fungal communities were investigated using the MiSeq Illumina sequencing platform. Our results showed that pineapple–banana rotation significantly reduced Fusarium wilt disease incidence and the application of biofertilizer caused additional suppression. Bacterial and fungal communities thrived using rotation combined with biofertilizer application: taxonomic and phylogenetic α diversity of both bacteria and fungi increased along with disease suppression. Between the two strategies, biofertilizer application predominantly affected both bacterial and fungal community composition compared to rotation. Burkholderia genus may have been attributed to the general wilt suppression for its change in network structure and high relative importance in linear models. Our results indicated that pineapple–banana rotation combined with biofertilizer application has strong potential for the sustainable management of banana Fusarium wilt disease.

Aerobic Exercise Alters Brain Function and Structure in Parkinson's Disease: A Randomized Controlled Trial.

ObjectiveRandomized clinical trials have shown that aerobic exercise attenuates motor symptom progression in Parkinson's disease, but the underlying neural mechanisms are unclear. Here, we investigated how aerobic exercise influences disease‐related functional and structural changes in the corticostriatal sensorimotor network, which is involved in the emergence of motor deficits in Parkinson's disease. Additionally, we explored effects of aerobic exercise on tissue integrity of the substantia nigra, and on behavioral and cerebral indices of cognitive control.MethodsThe Park‐in‐Shape trial is a single‐center, double‐blind randomized controlled trial in 130 Parkinson's disease patients who were randomly assigned (1:1 ratio) to aerobic exercise (stationary home trainer) or stretching (active control) interventions (duration = 6 months). An unselected subset from this trial (exercise, n = 25; stretching, n = 31) underwent resting‐state functional and structural magnetic resonance imaging (MRI), and an oculomotor cognitive control task (pro‐ and antisaccades), at baseline and at 6‐month follow‐up.ResultsAerobic exercise, but not stretching, led to increased functional connectivity of the anterior putamen with the sensorimotor cortex relative to the posterior putamen. Behaviorally, aerobic exercise also improved cognitive control. Furthermore, aerobic exercise increased functional connectivity in the right frontoparietal network, proportionally to fitness improvements, and it reduced global brain atrophy.InterpretationMRI, clinical, and behavioral results converge toward the conclusion that aerobic exercise stabilizes disease progression in the corticostriatal sensorimotor network and enhances cognitive performance. ANN NEUROL 2022;91:203–216

Simulated poaching affects global connectivity and efficiency in social networks of African savanna elephants-An exemplar of how human disturbance impacts group-living species.

Selective harvest, such as poaching, impacts group-living animals directly through mortality of individuals with desirable traits, and indirectly by altering the structure of their social networks. Understanding the relationship between disturbance-induced, structural network changes and group performance in wild animals remains an outstanding problem. To address this problem, we evaluated the immediate effect of disturbance on group sociality in African savanna elephants-an example, group-living species threatened by poaching. Drawing on static association data from ten free-ranging groups, we constructed one empirically based, population-wide network and 100 virtual networks; performed a series of experiments 'poaching' the oldest, socially central or random individuals; and quantified the immediate change in the theoretical indices of network connectivity and efficiency of social diffusion. Although the social networks never broke down, targeted elimination of the socially central conspecifics, regardless of age, decreased network connectivity and efficiency. These findings hint at the need to further study resilience by modeling network reorganization and interaction-mediated socioecological learning, empirical data permitting. The main contribution of our work is in quantifying connectivity together with global efficiency in multiple social networks that feature the sociodemographic diversity likely found in wild elephant populations. The basic design of our simulation makes it adaptable for hypothesis testing about the consequences of anthropogenic disturbance or lethal management on social interactions in a variety of group-living species with limited, real-world data.