High Network Degree Research Articles

Exploring scale-free networks: Survey on autonomous system dynamics and connectivity analysis

The global Internet is continuously developing; however, it is becoming more complex with time owing to the introduction of new nodes and links among autonomous systems (ASes). The network links among ASes appear and disappear, especially when the shortest path is required or a low-cost upstream Internet service provider (ISP) is a prerequisite. Understanding the Internet dynamics is critical for improving Internet characteristic analysis. In this work, we reviewed the existing studies from the last two decades on AS network topology as well as relations and routing among ASes. Similarly, we measured the link value differences within Russia and Central Asian ASes using the Barabasi–Albert (BA) model. Our analysis results show that in the last two years, the number of newly added links among 5377 ASes is 65,782. Further, the results show that the ASes with a high network degree in terms of high connectivity or preferential attachment approach are those used by the largest telecom companies in Russia and Central Asian regions. This survey paper aimed to determine whether the Internet AS graphs in these regions adhere to scale-free network properties, and we further examined the growth patterns of node connectivity within these regions.

Contemporary Britain in the Works of Russian Scholars

The article is dedicated to major findings of Russian scholars on a broad range of topics in the field of British studies. The works selected are mainly focused on the analysis of political, security and socio-economic models of development and trends in the UK from 1991 to 2021. The topics, which were most elaborated in the 1990s, related to the phenomena of Thatcherism, Third Way, the party-political system, social and economic model, British monarchy. Later the problems of devolution and constitutional reforms, identity politics, Euroscepticism, Brexit and migration, the concept of Global Britain shifted to the centre of attention. The study shows that Russian specialists tend to rely not only on empirical studies and approaches but have accumulated a rich experience in profound theoretical and conceptual understanding of the processes under scrutiny and demonstrate a high degree of critical reflection on the research implemented by foreign experts on British studies. Russian scholars pay interest both to structural and institutional processes and to concrete personalities and subjective factor in history. The undertaken research demonstrates a high degree of net working in cooperation among Russian specialists on British Studies, who represent different academic, educational centres and scientific schools.

Identifying Boys With Autism Spectrum Disorder Based on Whole-Brain Resting-State Interregional Functional Connections Using a Boruta-Based Support Vector Machine Approach.

An increasing number of resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used functional connections as discriminative features for machine learning to identify patients with brain diseases. However, it remains unclear which functional connections could serve as highly discriminative features to realize the classification of autism spectrum disorder (ASD). The aim of this study was to find ASD-related functional connectivity patterns and examine whether these patterns had the potential to provide neuroimaging-based information to clinically assist with the diagnosis of ASD by means of machine learning. We investigated the whole-brain interregional functional connections derived from R-fMRI. Data were acquired from 48 boys with ASD and 50 typically developing age-matched controls at NYU Langone Medical Center from the publicly available Autism Brain Imaging Data Exchange I (ABIDE I) dataset; the ASD-related functional connections identified by the Boruta algorithm were used as the features of support vector machine (SVM) to distinguish patients with ASD from typically developing controls (TDC); a permutation test was performed to assess the classification performance. Approximately, 92.9% of participants were correctly classified by a combined SVM and leave-one-out cross-validation (LOOCV) approach, wherein 95.8% of patients with ASD were correctly identified. The default mode network (DMN) exhibited a relatively high network degree and discriminative power. Eight important brain regions showed a high discriminative power, including the posterior cingulate cortex (PCC) and the ventrolateral prefrontal cortex (vlPFC). Significant correlations were found between the classification scores of several functional connections and ASD symptoms (p < 0.05). This study highlights the important role of DMN in ASD identification. Interregional functional connections might provide useful information for the clinical diagnosis of ASD.

Synergy and discount of punishment in the public goods game

Punishment has been verified as an important mechanism for promoting cooperation. Ethnographic evidence shows that punishment is coordinated within the group. Thus, we take into account the nonlinear group interaction and propose the synergetic and discounted punishment depicting how fines imposed on defectors nonlinearly accumulate within the group. We further model the replicator dynamics on regular networks and investigate the equilibria of evolutionary dynamics in structured populations. Our results show that cooperation can not be the unique stable equilibrium in well-mixed populations. However, for structured populations, the results indicate that cooperation can be the only stable equilibrium. The interior equilibrium is always an unstable equilibrium in well-mixed and structured populations, which means that cooperation and defection cannot coexist. For low values of β, the high network degree k is favorable to promoting cooperation. On the contrary, the low network degree k becomes beneficial to promoting cooperation with β increases.

Cell-specific gene association network construction from single-cell RNA sequence

ABSTRACT The recent development of a high throughput single-cell RNA sequence devises the opportunity to study entire transcriptomes in the smallest detail. It also leads to the characterization of molecules and subtypes of a cell. Cancer epigenetics induced not only from individual molecules but also from the dysfunction of the system and the coupling effect of genes. While rapid advances are being made in the development of tools for single-cell RNA-seq data analysis, few slants are noticed in the potential advantages of single-cell network construction. Here, we used network perturbation theory with significant analysis to develop a cell-specific network that provides an insight into gene–gene association based on molecular expressions in a single-cell resolution. Besides, using this method, we can characterize each cell by inspecting how genes are connected and can identify the hub genes using network degree theory. Pathway & Gene enrichment analysis of the identified cell-specific high network degree genes supported the effectiveness of this method. This method could be beneficial for personalized drug design and even therapeutics.

Egocentric sexual networks of men who have sex with men in the United States: Results from the ARTnet study

In this paper, we present an overview and descriptive results from one of the first egocentric network studies of men who have sex with men (MSM) from across the United States: the ARTnet study. ARTnet was designed to support prevention research for human immunodeficiency virus (HIV) and other sexually transmitted infections (STIs) that are transmitted across partnership networks. ARTnet implemented a population-based egocentric network study design that sampled egos from the target population and asked them to report on the number, attributes, and timing of their sexual partnerships. Such data provide the foundation needed for parameterizing stochastic network models that are used for disease projection and intervention planning. ARTnet collected data online from 2017 to 2019, with a final sample of 4904 participants who reported on 16198 sexual partnerships. The aims of this paper were to characterize the joint distribution of three network parameters needed for modeling: degree distributions, assortative mixing, and partnership age, with heterogeneity by partnership type (main, casual and one-time), demography, and geography. Participants had an average of 1.19 currently active partnerships (“mean degree”), which was higher for casual partnerships (0.74) than main partnerships (0.45). The mean rate of one-time partnership acquisition was 0.16 per week (8.5 partners per year). Main partnerships lasted 272.5 weeks on average, while casual partnerships lasted 133.0 weeks. There was strong but heterogenous assortative mixing by race/ethnicity for all groups. The mean absolute age difference for all partnership types was 9.5 years, with main partners differing by 6.3 years compared to 10.8 years for casual partners. Our analysis suggests that MSM may be at sustained risk for HIV/STI acquisition and transmission through high network degree of sexual partnerships. The ARTnet network study provides a robust and reproducible foundation for understanding the dynamics of HIV/STI epidemiology among U.S. MSM and supporting the implementation science that seeks to address persistent challenges in HIV/STI prevention.

Gene expression profiling by mRNA sequencing reveals dysregulation of core genes in Rictor deficient T-ALL mouse model

T-cell acute lymphoblastic leukemia (T-ALL) is a neoplastic disorder with peak incidence in children and young adults. The mTOR complex is an important component of the PI3K/Akt/mTOR signaling cascade and holds great promise for the treatment of hematopoietic malignancies. Previous studies have shown that the depression of Rictor, one of the components of the mTOR complex, prevents myeloproliferative disorders and leukemia However, knowledge of the progression of mTOR has not greatly improved the prognosis of T-ALL. To identify potential prognostic biomarkers for T-ALL, a whole-genome expression profile of Rictior deficient T-ALL mice was performed. As a result, 1475 differentially expressed genes (DEGs) were identified. Network analysis revealed 46 genes with a high network degree and fold-change value. Kaplan-Meier analysis identified ten crucial genes which significantly associated with survival in Rictor deficient T-ALL mice. These findings provide potential therapeutic targets in leukemia and bear immediate relevance to patients with leukemia.

Comprehensive analysis of aberrantly expressed profiles of messenger RNA in alcoholic liver disease.

Alcoholic liver disease (ALD) is one of the major cause of morbidity and mortality of clinical liver disease worldwide. Until today, although many general therapies are carried out and several molecular targets have been proposed to act as the potential therapeutic targets, more accurate molecular targets and more effective therapeutic methods remain needed. In the study, we analyze the differential expression genes (DEGs) between the patients with ALD and healthy controls. Gene Ontology enrichment and KEGG signaling pathway analysis are performed to identify the function of DEGs. Some significant molecules are proposed to act as the potential therapeutic targets for ALD. RNA data of 15 ALD tissues and 7 normal tissues for RNA expression analysis were obtained. DEGs in ALD samples compared with normal tissues identified through the limma R package and subjected to network analysis. As a result, we obtained a total of 274 DEGs that mainly involved in biological processes related to the angiogenesis, stress reaction, synthesis, and metabolism of organic acids. Network analysis obtained several genes with high network degree and fold change. Some significant molecules are proposed to act as the potential therapeutic targets for ALD. Our research identified some new progression-related genes of alcohol liver diseases, which could be regarded as the new targets for the early diagnosis and therapeutic management in ALD.

Comprehensive analysis of multi Ewing sarcoma microarray datasets identifies several prognosis biomarkers.

Ewing sarcoma (ES) is a common primary malignancy in children and adolescents. Progression of treatment methods hasn't contributed a lot to the imrovement of prognosis. To identify potential prognostic biomarkers, a meta-analysis pipeline of multi-gene expression datasets for ES from the Gene Expression Omnibus (GEO) was performed. Three datasets were screened and differential expression genes (DEGs) in ES samples compared with normal tissues were identified through limma package and subjected to network analysis. As a result, 1,470 DEGs were obtained which were mainly involved in biological processes associated with immune response and transcription regulation. Network analysis obtained 22 core genes with high network degree and fold change. Kaplan-Meier analysis based on ES datasets from The Cancer Genome Atlas identified five genes, including glycogen phosphorylase, muscle-associated, myocyte-specific enhancer factor 2C, tripartite motif containing 63, budding uninhibited by benzimidazoses1 and Ras GTPase-activating protein 1, whose altered expression profiles are significantly associated with survival. Changes of their expression values were further confirmed through RT-qPCR in ES cell and normal cell lines. Those genes may be considered as potential prognostic biomarkers of ES and should be helpful for its early diagnosis and treatment.

The Liquidity of Credit Default Index Swap Networks

Recent regulatory reforms like the mandatory clearing of standardized swap contracts and mandatory trading on centralized execution platforms have significantly changed the derivatives landscape. These reforms have, in certain cases, led the market to increasingly trade on multilateral platforms, potentially affecting the average cost of execution. Prior research has examined the effects of centralized trading on execution costs and has generally found reduced costs, especially for entities with higher transaction volumes or greater execution flexibility. We use detailed information on the trading of credit index swaps, the most actively traded credit derivatives instrument, between May 2014 and Sep 2016. We find that the customers who trade with a higher number of dealers (high network degree) and those who trade with the most active dealers (high network centrality) incur lower trading costs; for at least the less liquid indices, this cost improvement increases as trade size increases. We also identify a few liquidity trends: measures like average daily volumes, average price impact, and price dispersion have remained steady or have improved. However, during the same period, trade sizes for certain indices may have declined slightly.

Open source project success: Resource access, flow, and integration

Open source software projects share key resources including knowledge and developer attention. Developers who participate on multiple projects create ties among projects and facilitate access to those projects’ resources. However, projects also compete for developer attention, and they vary in their ability to integrate knowledge. This paper explores how factors that facilitate knowledge integration (low software coupling and high interactive discussion) impact project success and how developers’ attention to external projects may dampen a focal project’s success. Further, we explore how these factors may moderate the positive impact of a project’s network degree centrality to develop a more nuanced model of their influences on project success. Using data from 175 OSS projects we find that software coupling, interactive discussion and externally focused developer attention directly impact completed code commits. Interactive discussion also amplifies the benefit of high network degree centrality, while developers’ external attention weakens the positive impact of high network degree centrality. Results add to theory by providing a more nuanced view of how key strategic resources (knowledge and attention) drive OSS success. In particular it describes how knowledge integration ability, developer attention, and network degree centrality interact to influence project outcomes.

Development of Small and Medium Enterprises through Clusters and Networking: A Comparative Study of India, Pakistan and Sri Lanka

Clusters have several advantages. These include a high degree of networking which stimulates productivity, ability to diversify and to acquire the capacity to new products when the demand for existing products falls. The policy makers are searching ways to create new clusters. With an even more globalized world and increased competition the appeal of clusters has become stronger and more urgent. Yet, the formation and the sustenance of the clusters has somehow remained a mystery. There has been a limited research carried out in this direction. No doubt it is a complex area and no figurative results can be highlighted to show as to how the development of industrial clusters has taken place. The authors go about seeking answers to these questions by examining the experience of some of the prominent and successful clusters, their formation and sustenance in the three countries. The study further investigates various initiatives, the role and the results thereof in development of clusters.

Development of SMEs through clusters: a comparative study of India, Pakistan and Sri Lanka

Clusters evolve as a mechanism to gain competitive advantage, when industrial units come together to share knowledge and supplement each other in enhancing strengths. The phenomenon of clustering is known to have created a high degree of networking, a market focus, an ambiance of high productivity, excellence, development of skills and creativity. These in turn can lead a firm to technological innovation and its applications. Large customers prefer to source from clusters which have developed networking to meet the challenges of high demand. A high rate of success of SMEs in India, Pakistan and Sri Lanka can be traced in part to clusters. Some of these clusters are quite large responsible for a substantial share of production. The paper takes up several perspectives discussing the evolution and the growth of the clusters, their spread in the three countries and how these have helped in the development of SMEs.

System architecture of the predictive safety systems

The great number of individual functions supported by Bosch in the field of the environment-sensor based safety systems results in a very high degree of networking in the vehicle. The requirement to connect these individual functions to an overall system with coherent system behavior, to be able to flexibly react to customers’ wishes regarding the system behavior and at the same time to make distributed system development possible, can only be fulfilled by means of a resilient system architecture. In this, Bosch orients itself on hierarchically functional approaches from robotics and partitions the system into different hierarchical levels dependent on the length of term and level of detail of the task.

Green light emitting oxygen deficient ZnO forks, brooms and spheres

ZnO forks, brooms and spheres possessing self assembled nanowalls and nanocones of ZnO were synthesized, for the first time, via direct thermal evaporation of metallic Zn flakes. The samples exhibit visible green emission on UV excitation. EDX point towards oxygen deficient sample. Photoluminescence studies confirm the presence of defect related emission. The sharp nanocone tips and high degree of networking of nanowalls make them a potential candidate for field emission, gas sensing and catalytic applications.

Quality management in the electrics/electronics process chain

Willibert Schleuter, Georg Sterler and Magnus Schöffel If high-level quality targets are to be met under severe time pressure alongside increasing complexity and functional variety in vehicles, this can only be achieved by optimising the entire process chain. Audi consistently implements this ethos in every department involved in the development of electrical/electronic systems. The Electronics R&D Centre, into which Audi moved in 2003, is also a reflection of the required high degree of networking and communication density. The clear increase in E/E quality demonstrates that the overall concept is working successfully.

Three-dimensional interconnected nanowire networks of ZnO

In this Letter, three-dimensional (3D) interconnected networks of ZnO nanowires and nanorods are synthesized by a high temperature solid–vapor deposition process. The nanorods and nanowires have diameters of 20–100 nm and they grow along the c-axis. Due to the diverse orientation of the nanowires grown from a polycrystalline substrate, the networks are formed by a sintering process of the crossed nanowires during growth. The thickness of the multilayer nano-network could be as thick as ∼30 μm. The sharp nanowire tips, the high degree of networking, and high surface area of these unique nanonetworks make them a potential candidate for field emission, ultra-sensitive gas sensing, catalysts and filtering.