Central Difference Research Articles

Diagnostice breast elastography estimation from doppler imaging using central difference (CD) and least-squares (LS) algorithms

Breast elastography ultrasound has advantages as a fast, non-invasive, low-cost technology. It gives more details about tissue stiffness compared to conventional imaging techniques, which makes it more preferable. This study aims to evaluate the velocity-based strain estimation principle on in vivo public breast dataset. The proposed elastography algorithm has investigated using velocity-based strain estimation and one radio-frequency (RF) dataset of elasticity phantom, which was available online. The mean strain ratio of benign fibroadenoma was 0.5871, and the mean strain ratio of malignant invasive ductal carcinoma (IDC) was 2.6929, which matches with the literature. However, the elastography using velocity-based strain estimation still needs to be improved to obtain better results in the future. In conclusion, this technique can reduce unnecessary biopsies for patients and dramatically improve the diagnosis ratio.

The stability of social prominence and influence in a dynamic sow herd: A social network analysis approach

Social network analysis has developed as a valid technique in animal behaviour; despite an increase in the number of social network research in this field, comparatively few studies have focused on commercial animals. This study investigated a dry breeding sow herd (average = 69) as a model species for identifying socially prominent sows, individuals engaging in significantly higher levels of direct interactions than their conspecifics and socially influential sows, individuals with significantly higher levels of indirect interactions than their conspecifics. Animals were frequently added and removed from the herd during the study, creating a dynamic unstable social environment. In total, 63 h of video observations were obtained over three production cycles. Each production cycle covered 21 days, and behavioural observations occurred on days 1, 2, 3, 7, 14, 20, 21. The social network metrics of degree centrality (number of interactions), betweenness centrality (number of times an individual falls along the shortest path between two individuals) and centralisation (the extent to which a single individual dominates a network) were analysed to assess the stability of aggressive behaviour and preferential associations between production cycles. Preferential associations refer to lying behaviour <1 m from selected partners. Agonistic interactions included biting, thrusting, chasing and displacement behaviour. The results identified subgroup formations within the herd, based upon connectedness. Socially prominent and influential sows were identified within the subgroups, a result unaffected by low centralisation in the preferential association networks and substantial centralisation variance between the aggression networks. Sows quantified as socially prominent in the preferential association and aggression networks did not generally hold this position between production cycles, showing significant changes in degree centrality. Sows also demonstrated inconsistency in social influence in the preferential association networks, again with significant differences in betweenness centrality between production cycles. However, in the aggression networks, betweenness centrality was found to be a stable individual social network metric, with no significant changes in behaviour. Knowledge of the stability of social influence in the aggression networks could improve levels of agonistic interactions as it becomes possible to make predictions of future response to aid and inform intervention or management strategies. These findings highlight betweenness centrality as a powerful alternative tool that extends beyond the traditional methods of analysing dyadic interactions to identify critical animals.

Coexistence of Distinct Performance Models in High-Level Women's Volleyball.

In performance analysis, and most notably in match analysis, generalizing game patterns in a sport or competition may result in formulating generic models and neglecting relevant variability in benefit of average or central values. Here, we aimed to understand how different game models can coexist at the same competitive level using social network analysis with degree centrality to obtain systemic mappings for six volleyball matches, one for each of the six national teams playing in the 2014 World Grand Prix Finals, guaranteeing a homogeneous game level and balanced matches. Although the sample was not recent, this was not relevant for our purposes, since we aimed to merely expose a proof of concept. A total of 56 sets and 7,176 ball possessions were analysed through Gephi Software, considering game actions as nodes and the interaction between them as edges. Results supported the coexistence of different performance models at the highest levels of practice, with each of the six teams presenting a very distinct game model. For example, important differences in eigenvector centrality in attack zones (ranging from 0 to 34) and tempos (20 to 38) were found between the six teams, as well as in defensive lines (20 to 39) and block opposition (22 to 37). This further suggests that there may be multiple pathways towards expert performance within any given sport, inviting a re-conceptualization of monolithic talent identification, detection and selection models. Future studies could benefit from standardizing the metrics in function of the number of ball possessions.

Spatial familial networks to infer demographic structure of wild populations.

In social species, reproductive success and rates of dispersal vary among individuals resulting in spatially structured populations. Network analyses of familial relationships may provide insights on how these parameters influence population‐level demographic patterns. These methods, however, have rarely been applied to genetically derived pedigree data from wild populations.Here, we use parent–offspring relationships to construct familial networks from polygamous boreal woodland caribou (Rangifer tarandus caribou) in Saskatchewan, Canada, to inform recovery efforts. We collected samples from 933 individuals at 15 variable microsatellite loci along with caribou‐specific primers for sex identification. Using network measures, we assess the contribution of individual caribou to the population with several centrality measures and then determine which measures are best suited to inform on the population demographic structure. We investigate the centrality of individuals from eighteen different local areas, along with the entire population.We found substantial differences in centrality of individuals in different local areas, that in turn contributed differently to the full network, highlighting the importance of analyzing networks at different scales. The full network revealed that boreal caribou in Saskatchewan form a complex, interconnected familial network, as the removal of edges with high betweenness did not result in distinct subgroups. Alpha, betweenness, and eccentricity centrality were the most informative measures to characterize the population demographic structure and for spatially identifying areas of highest fitness levels and family cohesion across the range. We found varied levels of dispersal, fitness, and cohesion in family groups. Synthesis and applications: Our results demonstrate the value of different network measures in assessing genetically derived familial networks. The spatial application of the familial networks identified individuals presenting different fitness levels, short‐ and long‐distance dispersing ability across the range in support of population monitoring and recovery efforts.

Altered brain intrinsic functional hubs and connectivity associated with relapse risk in heroin dependents undergoing methadone maintenance treatment: A resting-state fMRI study

BackgroundThe neural substrates underlying the relapse behavior of heroin dependents (HD) who received long-term methadone maintenance treatment (MMT) have yet to be thoroughly expounded. This study investigated the relapse-related intrinsic functional hubs of HD and their functional integration feature at whole brain network level. Methods57 male HD receiving MMT and 49 matched healthy controls (HC) were enrolled. All of the subjects received resting-state functional magnetic resonance imaging scan. And the 57 patients were assigned a 26-month follow-up for collecting illegal drug use information. Of them, 11 were non-relapsers and 46 relapsers. We analyzed the voxel-based degree centrality (DC) to reveal the differences in nodule centrality between HD and HC, conducted Pearson partial-correlation analysis to confirm the relationship between relapse frequency and DC value of the nodes with significant intergroup differences, and finally compared the functional connectivity (FC) of the relapse-related hubs between non-relapsers and relapsers. ResultsWe found the DC values of right insula and left nucleus accumbens (NAc) were negatively correlated with relapse frequency. Compared with the non-relapsers, the relapsers had a significant decreased FC between left NAc and inhibitory control circuitry, including left dorsolateral prefrontal cortex, left inferior frontal gyrus and motor regions. ConclusionsThese findings suggest that the neural substrates of relapse vulnerability in HD undergoing MMT are the intrinsic functional hubs of introceptive and reward systems and the latter modulates relapse behavior via interaction with inhibitory control circuit.

Graph theory analysis reveals premature ejaculation is a brain disorder with altered structural connectivity and depressive symptom: A DTI-based connectome study.

Recent research has shown that premature ejaculation (PE) is associated with negative psychological effects (e.g., depression) and the decline of control over ejaculation is accompanied by structural and functional abnormalities in specific brain areas and connections. However, little is known about the alterations of topological organization in the brain network of patients with PE and its relationship with depressive symptom. We acquired diffusion tensor images, sexual function and depression assessment in 16 lifelong PE patients with depressive symptom, 16 lifelong PE patients without depression and 32 age- and education-matched healthy controls (HC). The differences in nodal centrality and different hub regions among the three groups were compared. Correlation analyses were conducted between the nodal centrality of brain regions displaying significant group differences and the clinical parameters of PE patients. PE patients with depression had increased nodal degree in the right middle frontal gyrus (orbital part) (ORBmid.R) (survived FDR-correction) compared with HC and PE without depression. PE patients with depression also had increased nodal degree in the left and right posterior cingulate gyrus (PCG.L; PCG.R) compared with HC. In addition, PE with depression had increased nodal betweenness in ORBmid.R compared with HC and PE without depression. Moreover PE with depression had decreased nodal participation in the right rolandic operculum (ROL.R), postcentral gyrus (PoCG.R) and supramarginal gyrus (SMG.R) compared with HC, and had decreased nodal participation in ROL.R and the right inferior parietal gyrus (IPL.R) compared with PE without depression, while PE without depression had increased nodal participation in the left precuneus (PCUN.L) compared with HC. The degree and betweenness of ORBmid.R were positively correlated with the total scores of Beck depression inventory (BDI) while the participation of IPL.R had a negative association with the total scores of BDI. Different hubs were found among PE patients with and without depression and HC based on nodal degree, betweenness and participation; however, no significant group differences were found in the frequency distribution of high-degree hubs, high-betweenness hubs, provincial hubs and connector hubs. These findings demonstrated that PE was a brain disorder with altered structural connectivity pattern of brain network and depressive symptom, which suggested that altered structural connectivities of the fronto-cingulate-parietal control network were core neurobiological features associated with PE and depression. Together, these alterations could prove helpful for understanding the pathophysiological mechanisms of PE in depression.

Social Network Analysis of a Chimpanzee (Pan troglodytes) Group in Captivity Following the Integration of a New Adult Member

Management of primates in captivity often presents the challenge of introducing new individuals into a group, and research investigating the stability of the social network in the medium term after the introduction can help inform management decisions. We investigated the behavior of a group of chimpanzees (Pan troglodytes) housed at Chester Zoo, UK over 12 months (divided into three periods of 4 months) following the introduction of a new adult female. We recorded grooming, proximity, other affiliative behaviors, and agonistic behaviors and used social network analysis to investigate the stability, reciprocity, and structure of the group, to examine the effect of rearing history on grooming network position and the role of sex in agonistic behavior. Both the grooming and agonistic networks correlated across all three periods, while affiliative networks correlated only between periods 2 and 3. Males had significantly higher out-degree centrality in agonistic behaviors than females, indicating that they carried out agonistic behaviors more often than females. There was no significant difference in centrality between hand-reared and mother-reared chimpanzees. Overall, the group structure was stable and cohesive during the first year after the introduction of the new female, suggesting that this change did not destabilize the group. Our findings highlight the utility of social network analysis in the study of primate sociality in captivity, and how it can be used to better understand primate behavior following the integration of new individuals.

Electrophysiological network alterations in adults with copy number variants associated with high neurodevelopmental risk

Rare copy number variants associated with increased risk for neurodevelopmental and psychiatric disorders (referred to as ND-CNVs) are characterized by heterogeneous phenotypes thought to share a considerable degree of overlap. Altered neural integration has often been linked to psychopathology and is a candidate marker for potential convergent mechanisms through which ND-CNVs modify risk; however, the rarity of ND-CNVs means that few studies have assessed their neural correlates. Here, we used magnetoencephalography (MEG) to investigate resting-state oscillatory connectivity in a cohort of 42 adults with ND-CNVs, including deletions or duplications at 22q11.2, 15q11.2, 15q13.3, 16p11.2, 17q12, 1q21.1, 3q29, and 2p16.3, and 42 controls. We observed decreased connectivity between occipital, temporal, and parietal areas in participants with ND-CNVs. This pattern was common across genotypes and not exclusively characteristic of 22q11.2 deletions, which were present in a third of our cohort. Furthermore, a data-driven graph theory framework enabled us to successfully distinguish participants with ND-CNVs from unaffected controls using differences in node centrality and network segregation. Together, our results point to alterations in electrophysiological connectivity as a putative common mechanism through which genetic factors confer increased risk for neurodevelopmental and psychiatric disorders.

Pixel asymmetry predicts between-object differences in the object-based compatibility effect.

When participants make left/right responses to unimanually graspable objects, response times (RTs) are faster when the responding hand is aligned with the viewed object's handle. This object-based compatibility effect (CE) is often attributed to motor activation elicited by the object's afforded grasp. However, some evidence suggests that the object-based CE is an example of spatial CEs, or Simon effects, elicited by the protruding nature of objects' handles. Moreover, recent work shows that the way in which objects are centred on-screen might attenuate or reverse CEs, perhaps due to differences in pixel asymmetry (the proportion of pixels either side of fixation) between centralities. In this study, we tested whether pixel asymmetry also contributes to between-object variation in object-based CEs. In experiment 1 (N = 34), we found that between-object differences in asymmetry predicted object-based CEs, such that objects with a greater proportion of pixels to the handle-congruent side of fixation produced larger CEs. In experiment 2 (N = 35), we presented participants with mug (low asymmetry) and frying pan (high asymmetry) images and found that between-object and within-object (due to stimulus centrality) differences in pixel asymmetry interact to moderate CEs. Base-centred stimuli (centred according to the width of the object's base) produced conventional CEs, whereas object-centred (centred according to the object's total width) stimuli produced negative CEs (NCEs). Furthermore, the effect of centrality was smaller for mugs than pans, indicating an interaction between within-object and between-object differences in pixel asymmetry.

SARS-CoV and SARS-CoV-2 main protease residue interaction networks change when bound to inhibitor N3

COVID-19 is a respiratory disease caused by the coronavirus SARS-CoV-2. SARS-CoV-2 has many similarities with SARS-CoV. Both viruses rely on a protease called the main protease, or Mpro, for replication. Therefore, inhibiting Mpro may be a successful strategy for treating COVID-19. Structures of the main proteases of SARS-CoV and SARS-CoV-2 with and without inhibitor N3 are available in the Protein Data Bank. Comparing these structures revealed residue interaction network changes associated with N3 inhibition. Comparing network clustering with and without inhibitor N3 identified the formation of a cluster of residues 17, 18, 30–33, 70, 95, 98, 103, 117, 122, and 177 as a network change in both viral proteases when bound to inhibitor N3. Betweenness and stress centrality differences as well as differences in bond energies and relative B-factors when comparing free Mpro to inhibitor-bound Mpro identified residues 131, 175, 182, and 185 as possibly conformationally relevant when bound to the inhibitor N3. Taken together, these results provide insight into conformational changes of betacoronavirus Mpros when bound to an inhibitor.

Exploring the Relationship Between Interaction and the Structure of Questions in Online Discussions Using Learning Analytics

Abstract While research has established the importance of questions as a key strategy used to facilitate student interaction in online discussions, there is a need to explore how the structure of questions influence students’ interactions. Using learning analytics, we explored the relationship between student-student interaction and the structure of initial questions with and without the Practical Inquiry Model (PIM). Degree centrality was used as the method to analyse the number of responses each student sent (out-degree centrality) and the number of responses each student received (in-degree centrality). Findings showed that the number of responses each student sent and received was higher in the discussions initiated by the PIM-question prompts. In addition, analysis revealed a positive relationship between students’ interaction and the discussions structured with PIM and non-PIM questions. Finally, there was a significant difference in out-degree centrality but no significant difference in in-degree centrality between discussions structured with the PIM and non-PIM questions. We conclude that initial questions can be structured using PIM as a guiding framework to facilitate student-student interaction in online discussions.

Functional Magnetic Resonance Imaging Connectivity Accurately Distinguishes Cases With Psychotic Disorders From Healthy Controls, Based on Cortical Features Associated With Brain Network Development

BackgroundMachine learning (ML) can distinguish cases with psychotic disorder from healthy controls based on magnetic resonance imaging (MRI) data, but it is not yet clear which MRI metrics are the most informative for case-control ML, or how ML algorithms relate to the underlying biology. MethodsWe analyzed multimodal MRI data from 2 independent case-control studies of psychotic disorders (cases, n = 65, 28; controls, n = 59, 80) and compared ML accuracy across 5 selected MRI metrics from 3 modalities. Cortical thickness, mean diffusivity, and fractional anisotropy were estimated at each of 308 cortical regions, as well as functional and structural connectivity between each pair of regions. Functional connectivity data were also used to classify nonpsychotic siblings of cases (n = 64) and to distinguish cases from controls in a third independent study (cases, n = 67; controls, n = 81). ResultsIn both principal studies, the most informative metric was functional MRI connectivity: The areas under the receiver operating characteristic curve were 88% and 76%, respectively. The cortical map of diagnostic connectivity features (ML weights) was replicable between studies (r = 0.27, p < .001); correlated with replicable case-control differences in functional MRI degree centrality and with a prior cortical map of adolescent development of functional connectivity; predicted intermediate probabilities of psychosis in siblings; and was replicated in the third case-control study. ConclusionsML most accurately distinguished cases from controls by a replicable pattern of functional MRI connectivity features, highlighting abnormal hubness of cortical nodes in an anatomical pattern consistent with the concept of psychosis as a disorder of network development.

Numerical study of blood flow and heat transfer through stretching cylinder in the presence of a magnetic dipole

AbstractIn the present paper we study numerically the Biomagnetic Fluid Flow (BFD) (blood) and heat transfer through a stretching cylinder. The physical problem is formulated by a BFD model which incorporates both principles of FerroHydroDynamics (FHD) and MagnetoHydroDynamics (MHD). Thus, blood is considered to be an electrically conducting fluid which simultaneously exhibits polarization. The governing equations are non‐dimensionalized using suitable similarity transformations and the resulting coupled non linear system of ordinary differential equations are solved using an efficient numerical technique which is based on a common finite differences method with central differencing, a tridiagonal matrix manipulation and an iterative procedure. Comparisons of our results with existed studies are made for some limiting case of the present study and found to be in a good agreement. The results are presented graphically for different values of the parameters with emphasis to the examination of FHD and MHD effect on the flow field as well as other physical quantities of interest, like skin friction coefficient and heat transfer on the wall.

Biomathematical model for gyrotactic free-forced bioconvection with oxygen diffusion in near-wall transport within a porous medium fuel cell

Bioconvection has shown significant promise for environmentally friendly, sustainable “green” fuel cell technologies. The improved design of such systems requires continuous refinements in biomathematical modeling in conjunction with laboratory and field testing. Motivated by exploring deeper the near-wall transport phenomena involved in bio-inspired fuel cells, in the present paper, we examine analytically and numerically the combined free-forced convective steady boundary layer flow from a solid vertical flat plate embedded in a Darcian porous medium containing gyrotactic microorganisms. Gyrotaxis is one of the many taxes exhibited in biological microscale transport, and other examples include magneto-taxis, photo-taxis, chemotaxis and geo-taxis (reflecting the response of microorganisms to magnetic field, light, chemical concentration or gravity, respectively). The bioconvection fuel cell also contains diffusing oxygen species which mimics the cathodic behavior in a proton exchange membrane (PEM) system. The vertical wall is maintained at iso-solutal (constant oxygen volume fraction and motile microorganism density) and iso-thermal conditions. Wall values of these quantities are sustained at higher values than the ambient temperature and concentration of oxygen and biological microorganism species. Similarity transformations are applied to render the governing partial differential equations for mass, momentum, energy, oxygen species and microorganism species density into a system of ordinary differential equations. The emerging eight order nonlinear coupled, ordinary differential boundary value problem features several important dimensionless control parameters, namely Lewis number (Le), buoyancy ratio parameter i.e. ratio of oxygen species buoyancy force to thermal buoyancy force (Nr), bioconvection Rayleigh number (Rb), bioconvection Lewis number (Lb), bioconvection Péclet number (Pe) and the mixed convection parameter ([Formula: see text] spanning the entire range of free and forced convection. The transformed nonlinear system of equations with boundary conditions is solved numerically by a finite difference method with central differencing, tridiagonal matrix manipulation and an iterative procedure. Computations are validated with the symbolic Maple 14.0 software. The influence of buoyancy and bioconvection parameters on the dimensionless temperature, velocity, oxygen concentration and motile microorganism density distribution, Nusselt, Sherwood and gradient of motile microorganism density are studied. The work clearly shows the benefit of utilizing biological organisms in fuel cell design and presents a logical biomathematical modeling framework for simulating such systems. In particular, the deployment of gyrotactic microorganisms is shown to stimulate improved transport characteristics in heat and momentum at the fuel cell wall.

Fast 3-D Inhomogeneous Radiative Transfer Model Using a Planar-Stratified Forward Algorithm and Horizontal Perturbation Series

A horizontally inhomogeneous unified microwave radiative transfer (HI-UMRT) model is presented to study the 3-D effects of the horizontal inhomogeneous clouds on the computed microwave radiances and facilitate satellite radiance assimilation over the horizontally inhomogeneous all-weather conditions. HI-UMRT provides a coupled two-Stokes parameter numerical radiance solution of the 3-D radiative transfer (RT) equation by embedding the existing 1-D UMRT algorithm into an iterative perturbation scheme. The horizontal derivatives in the radiances of the lower perturbation order are treated as the source functions of the azimuthal harmonic perturbation RT equations that are readily solved using the planar-stratified 1-D UMRT algorithm. The horizontal radiance derivative is estimated by central differencing. A perturbation source-function analysis shows that the increase in computing time for the 3-D HI-UMRT model relative to the 1-D UMRT model is moderate, since: 1) the computationally efficient UMRT engine is applied only to the perturbation equations with nontrivial solutions and 2) the layer parameters for the 1-D solution are reused for all higher perturbation orders. Numerical simulations using HI-UMRT based on 3-D cloud profiles simulated by the Weather Research and Forecasting numerical weather model illustrate the convergence of the iterative perturbation series. An intercomparison of the top-of-atmosphere brightness temperature images for HI-UMRT versus the change planar-stratifiedslant path UMRT model illustrates the considerable impact of cloud horizontal inhomogeneities on the computed upwelling microwave radiances.

Analysis of new visualization techniques of left heated lid‐driven square cavity

AbstractIn the present study, an attempt is made to explore the flow visualization techniques inside the left‐heated lid‐driven square cavity. The governing equations along with boundary conditions are solved numerically. The simulated results (100 ≤ Re ≤ 1000 and 0.001 ≤ Ri ≤ 10) are validated with previous results in the literature. The convection differencing schemes, namely, UPWIND, QUICK, SUPERBEE, and self‐filtered central differencing are discussed and are used to simulate the flow using MPI code. It is observed that the computational cost for all the differencing schemes get reduced tremendously when the MPI code is implemented. Plots demonstrating the influences of Re and Ri in terms of the contours of the fluid streamlines, isotherms, energy streamlines, and field synergy principle are presented.

Differences in network centrality between high and low myopia: a voxel-level degree centrality study.

Previous studies have linked high myopia (HM) to brain activity, and the difference between HM and low myopia (LM) can be assessed. To study the differences in functional networks of brain activity between HM and LM by the voxel-level degree centrality (DC) method. Twenty-eight patients with HM (10 men, 18 women), 18 patients with LM (4 men, 14 women), and 59 healthy controls (27 men, 32 women) were enrolled in this study. The voxel-level DC method was used to assess spontaneous brain activity. Correlation analysis was used to explore the change of average DC value in different brain regions, in order to analyze differences in brain activity between HM and LM. DC values of the right cerebellum anterior lobe/brainstem, right parahippocampal gyrus, and left caudate in HM patients were significantly higher than those in LM patients (P < 0.05). In contrast, DC values of the left medial frontal gyrus, right inferior frontal gyrus, left middle frontal gyrus, and left inferior parietal lobule were significantly lower in patients with HM (P < 0.05). However, there was no correlation between behavior and average DC values in different brain regions (P < 0.05). Different changes in brain regions between HM and LM may indicate differences in neural mechanisms between HM and LM. DC values could be useful as biomarkers for differences in brain activity between patients with HM and LM. This study provides a new method to assess differences in functional networks of brain activity between patients with HM and LM.

Topology of International Supply Chain Networks: A Case Study Using Factset Revere Datasets

International supply chain networks play a prominent role in shaping the economic outlook of the world. It has been a recent trend to analyse the topology of supply chain networks in order to gain a wholistic understanding about the interdependencies of firms in this regard. In this work, we undertake an extensive structural and topological analysis of the supply chain networks constructed from the Factset Revere dataset. The dataset is provided by FactSet Research Systems Inc. that captures global supply chain relationships between companies. The dataset consists of 154, 862 companies from 216 countries, with 1,571, 949 supply relationships among them. In addition to considering the global network, we also analysed country-specific networks of ten countries, which are the most significant nations represented in the dataset. The analysis revealed that all supply chain networks studied were relatively sparse scale-free networks, with scale-free exponents ranging from 1.0 to 2.0. In terms of centrality analysis, quite predictably, large multi-national corporates dominated. Comparing the centrality values of firms in terms of the global vs the country-specific networks, two classes of firms were found where the difference in centrality was significant. The first group was small firms with locally-centered business operations, such as Volunteers of America, New York State Teachers Retirement System, CarePlus Health Plan etc, where the country-based centrality scores and the rankings based on them were significantly more prominent than the global equivalent. The second group was firms with specific countries of origin which register themselves in other countries, such as China Shengda Packaging Group Inc (registered in US), Chinacast Education Corps (registered in the US), and China Biologic Products Inc (registered in the US). These firms all had significantly higher global centrality scores compared to country-based centrality scores. Overall, however, it was found that there was strong correlation between global centrality-based ranking and country-specific centrality ranking of firms. This indicated that in general, firms which are important to the global supply chain network are also important to the supply chain networks of individual countries. Studying the community structure of the supply chain networks, we identified twelve dominant communities, many of which had significant correlations with particular industries or countries. Some of these communities were made of firms primarily from a pair of countries, or had other interesting features. Therefore, the topological analysis of the supply chain networks created from this large dataset gives interesting insights about how the international supply chain networks are structured, and how they operate.

The network architecture of rat intrinsic interbrain (diencephalic) macroconnections

The endbrain and interbrain form 2 great vertebrate forebrain divisions, and the interbrain is subdivided into the hypothalamus ventrally and thalamus dorsally. General organizing principles of intrainterbrain axonal circuitry were examined here at the level of gray matter regions using network analysis tools in a mammal with the most complete available dataset-before examining interbrain input-output relationships with other nervous system parts. The dataset was curated expertly from the neuroanatomical literature using experimental axonal pathway-tracing methods, and evidence from 74,242 connection reports indicates the existence of 10,836 macroconnections of the possible 49,062 macroconnections between the 222 gray matter regions forming the right and left halves of the interbrain. Two identical sets of 6 putative hubs were identified in the intrainterbrain network and form a continuous tissue mass in a part of the right and left medial hypothalamus associated functionally with physiological mechanisms controlling bodily functions. The intrainterbrain network shows only weak evidence of small-world attributes, rich club organization is absent, and multiresolution consensus cluster analysis indicates a solution with only 3 top-level subsystems or modules. In contrast, a previous analysis employing the same methodology to the significantly denser 244-node intraendbrain network revealed 2 identical sets of 13 hubs, small-world and rich club attributes, and 4 top-level subsystems. These differences in intrinsic network architecture across subdivisions suggest that intrinsic connections shape regional functional specialization to a varying extent, in part driven by differences in density and centrality, with extrinsic input-output connectivity playing a greater role in subdivisions that are sparser and less centralized.

Application of network analysis to investigate sex differences in interactive systems of eating-disorder psychopathology.

Although men comprise 25% of persons with eating disorders (EDs), most research has focused on understanding EDs in women. The theoretical framework underlying common ED treatment has not been rigorously tested in men. The purpose of this study was to compare the interconnectivity among ED symptoms in men versus women. Participants (N = 1,348; 50% men) were individuals with anorexia nervosa, bulimia nervosa, binge-eating disorder, or other specified feeding or eating disorder who were users of Recovery Record, a smartphone app for monitoring ED symptoms. Participants were matched on age and duration of illness. Network analysis was used to create networks of symptoms for both sexes. Strength centrality, network stability, and bootstrapped centrality differences were tested. The network comparison test (NCT) was used to identify sex differences between networks. Key players analysis was used to compare fragmentation of each network. For both sexes, items related to binge eating and restricting emerged as highest in strength centrality. The NCT identified significant differences global strength (p = .03) but not network invariance (p = .06) suggesting that although the structure of the networks was not statistically different, the strength of the connections within the network was greater for women. Key players analysis indicated that both networks were similarly disrupted when important nodes within the network were removed. Findings suggested that there are more similarities than differences in networks of EDs in men and women. Results have important clinical implications by supporting theoretical underpinnings of cognitive-behavioral models of EDs in both men and women.