Network Interaction Model Research Articles

Optimization of resource use in the formation of a network interaction model

The article is based on the research materials of the network interaction of universities in the context of physical culture and sports activity. The research is based on the methodology of network theory and the resource approach in the strategic management of organizations. The results of the study show that the formation of a network model can significantly increase the coverage of the population with projects of physical culture and sports activity using already existing resources. The results obtained indicate the effectiveness of strategies for networking organizations.

The level model of network interaction primary school students in classroom activities

The article considers the problem of organization and methodological support of the process of formation of skills of network joint activities in primary school students. The relevance of this research problem is due to the following contradictions:between the need for a practice-oriented and controlled focus on the process of forming in young schoolchildren the skills of safe and ethical interaction in the network, as a requirement of a modern digital society and the lack of pedagogical conditions for its implementation in educational institutions;between the high potential of network interaction in the formation of digital literacy elements of elementary schoolchildren and insufficient practical and theoretical research in this area;between the didactic opportunities of joint network activities in the process of training and education in elementary school and the insufficient development of pedagogical conditions for its implementation.The purpose of the study: the development and experimental testing of the level model of network interaction of primary school children in a distributed information and educational environment. This model is based on the principle of a phased increase in the degree of activity, independence and responsibility of subjects of joint network activities, which is implemented through specially designed educational and methodological support. The problem is highlighted due to the lack of research and the lack of specialized methodological support in the field of networking in elementary school.Materials and methods. The theoretical basis of the study is the analysis of research works in the field of Internet security for schoolchildren and the psychology of primary school children, a generalization of pedagogical experience in the use of distance and network technologies in classroom activities, an analysis of the regulatory documents of primary general education.Results. The approbation of the level model of network interaction of primary schoolchildren was carried out during the 2016–2017, 2017– 2018, 2018–2019 academic years on the basis of MAOU Gymnasium No. 9 of Krasnoyarsk and secondary school No. 11 of Abakan. The study covered 105 primary school students. A complete set of educational and methodological support for the network interaction of elementary schoolchildren in computer science lessons in a distributed information and educational environment has been developed and fully tested.Conclusion. The level model of network interaction of elementary schoolchildren described in the article can be used both in the classroom and in extracurricular activities in various subject areas in elementary school. This model includes four levels of network interaction formation: interaction independently from each other without feedback, interaction independently from each other with the need for mutual control, consistent interaction with observance of the order and correctness of the task, non-linear interaction. In accordance with the developed model of network interaction, a distributed informational and educational environment of elementary school was formed and filled up on the example of the subject field “informatics”, which ensures the implementation of various types of elementary school students network interaction in classroom activities. Research materials can be replicated in general education organizations at the initial stage, and also used to improve the skills of primary school teachers and computer scientists.

Networking Cooperation in Forming Soft Skills of a New Type of Teacher

The primary aim of this research is to develop an effective network interaction model in developing a new teacher’s soft skills. The authors carried out an analysis of a new teacher’s necessary soft skills and the existing models of partnerships. They outlined their views on the development of a networking model that is aimed at the systematic formation of a teacher’s soft skills. The empirical part is executed based on the Elabuga Institute of the Kazan Federal University. The created model can be used for the organisation of training system of a new type of teacher. It might as well be used as a model of the school-university partnership for revealing pedagogically gifted children or as an integrated model for the formation of basic teachers’ soft skills in the university.

Impaired interactions among white-matter functional networks in antipsychotic-naive first-episode schizophrenia.

Schizophrenia has been conceptualized as a disorder arising from structurally pathological alterations to white‐matter fibers in the brain. However, few studies have focused on white‐matter functional changes in schizophrenia. Considering that converging evidence suggests that white‐matter resting state functional MRI (rsfMRI) signals can effectively depict neuronal activity and psychopathological status, this study examined white‐matter network‐level interactions in antipsychotic‐naive first‐episode schizophrenia (FES) to facilitate the interpretation of the psychiatric pathological mechanisms in schizophrenia. We recruited 42 FES patients (FESs) and 38 healthy controls (HCs), all of whom underwent rsfMRI. We identified 11 white‐matter functional networks, which could be further classified into deep, middle, and superficial layers of networks. We then examined network‐level interactions among these 11 white‐matter functional networks using coefficient Granger causality analysis. We employed group comparisons on the influences among 11 networks using network‐based statistic. Excitatory influences from the middle superior corona radiate network to the superficial orbitofrontal and deep networks were disrupted in FESs compared with HCs. Additionally, an extra failure of suppression within superficial networks (including the frontoparietal network, temporofrontal network, and the orbitofrontal network) was observed in FESs. We additionally recruited an independent cohort (13 FESs and 13 HCs) from another center to examine the replicability of our findings across centers. Similar replication results further verified the white‐matter functional network interaction model of schizophrenia. The novel findings of impaired interactions among white‐matter functional networks in schizophrenia indicate that the pathophysiology of schizophrenia may also lie in white‐matter functional abnormalities.

Project activities of bachelor students of a pedagogical university as a condition for preparing schoolchildren’s research activities

The paper discusses current issues of training a professional teacher, a successful organizer of schoolchildrens research activities. The material is presented in terms of new standards. The author discusses innovative forms of educational process organization at university and school the creation of a single educational space based on the principles of science and education integration. The main condition for schoolchildrens research potential development and successful teachers development is the project activity of students and schoolchildren in the framework of cooperation. A structural model of network interaction between the Minin Nizhny Novgorod State Pedagogical University, schools № 151, 129, 173 of Nizhny Novgorod, the Immanuel Kant Baltic Federal University (Kaliningrad) and the A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences (Moscow) has been developed. This model is a key factor contributing to the solution of the problem of high-quality training of a prospective teacher majoring in Biology who will be able to organize students research activities and develop their creative activity. The experience of the development and testing of various joint scientific, social and creative projects is shown. The data of the experiment are presented, which speak about the success of the events held as part of the implementation of the project technology.

Global air transport complex network: multi-scale analysis

Almost half of the world’s population is carried by airlines each year, and understanding this mode of transport is important from economic and scientific perspectives. In recent years, the increasing availability of data has led to complex network and agent interaction models which attempt to gain better understanding of the air transport network and develop forecasts. In this case study paper, we review existing research on two key approaches, namely: (1) a top-down multi-scale network science approach, and (2) a bottom-up entropy-maximization interaction network approach. Using simple socioeconomic indicators, we were able to construct a very accurate interaction model that can predict traffic volume, and the model can forward estimate the impact of population growth or fuel cost. Using network science approaches, we were able to identify community structures and relate them to economic outputs. We also saw how hubs evolved over time to become more influential. Looking into the future, using random graph theory, it seems that reduced flight cost will lead to increased hub influence. The disseminated knowledge in this case study paper will provide both academics and industry practitioners with steps forward to co-explore the interesting research landscape.

AUE youth organization as an integrated phenomenon of the Russian postmodernity

The article is devoted to the analysis of the AUE phenomenon (Convict's Codex is Unified) using a Siberian Federal District case study. The author bases the analysis primarily on neo-institutional and post-structuralist approaches. The paper considers non-formal aspects of the AUE institution functioning related to the relationships between the nodes forming various forms and models of network interactions. The purpose of the study is the need for scientific analysis and interpretation as well as the importance to design ways to prevent and detect this phenomenon. The research problem is the contradiction between today’s approaches towards interpretation of the AUE phenomenon and inability to create effective youth policies to prevent it.
 The study is founded on empirical material gathered by the author in Siberian Federal District in cooperation with the “Siberian Politics” Foundation in 2017 - early 2018. The empirical part includes 9 focus groups, a survey of high school students (920 respondents), a focused interview and an expert survey.
 The author argues that the AUE structure includes three partly overlapping phenomena: criminal youth subculture, rhizomatous youth movement, and criminal youth organization. However, the author proves that the AUE phenomenon cannot be fully identified with any of them.

МОДЕЛЬ СЕТЕВОГО ВЗАИМОДЕЙСТВИЯ ОБРАЗОВАТЕЛЬНОЙ ОРГАНИЗАЦИИ И ПРЕДПРИЯТИЯ В ФОРМЕ КОРПОРАТИВНОГО ПРОЕКТНОГО ОФИСА (на примере МАОУ «Татановская СОШ» – школа агробизнеса – Тамбов)

МОДЕЛЬ СЕТЕВОГО ВЗАИМОДЕЙСТВИЯ ОБРАЗОВАТЕЛЬНОЙ ОРГАНИЗАЦИИ И ПРЕДПРИЯТИЯ В ФОРМЕ КОРПОРАТИВНОГО ПРОЕКТНОГО ОФИСА (на примере МАОУ «Татановская СОШ» – школа агробизнеса – Тамбов)

Automated Formal Reasoning to Uncover Molecular Programs of Self-Renewal.

The Reasoning Engine for Interaction Networks (RE:IN) is a tool that was developed initially for the study of pluripotency in mouse embryonic stem cells. A set of critical factors that regulate the pluripotent state had been identified experimentally, but it was not known how these genes interacted to stabilize self-renewal or commit the cell to differentiation. The methodology encapsulated in RE:IN enabled the exploration of a space of possible network interaction models, allowing for uncertainty in whether individual interactions exist between the pluripotency factors. This concept of an "abstract" network was combined with automated reasoning that allows the user to eliminate models that are inconsistent with experimental observations. The tool generalizes beyond the study of stem cell decision-making, allowing for the study of interaction networks more broadly across biology.

Organisation of work on the pedagogic support of the formation of personality in the networked form of the implementation of educational programmes

This article proposes the organisation of work on the basis of a network form of interaction; creating conditions for the formation of a single social and educational medium that ensures the development and socialisation of students is described as well as implementation of joint educational and socio-pedagogic projects that ensure the inclusion of students in various types of social practices; organising and conducting joint research aimed at finding and solving topical problems of education and upbringing; strengthening the human resource capacity of network partner organisations; expanding the material and technical base to improve the efficiency of interaction; improving the scientific and methodological work of pedagogues. Mechanisms of network interaction are described, as well as its logic and steps that correspond to the stages of the professional development of the personality of students on a particular course, while solving specific educational tasks. The model "institute – resource centre" was the leading model of network interaction. This model represents the integration of several educational organisations around one of them, which has the greatest material and personnel potential, which will play the role of a resource centre for other educational organisations.

Impaired Interactions Among White-Matter Functional Networks in Antipsychotic-Naive First-Episode Schizophrenia

Background: Schizophrenia has been conceptualized as a disorder arising from structurally pathological alterations to white-matter fibers in the brain. However, few studies have focused on white-matter functional changes in schizophrenia. Considering that converging evidence suggests that white-matter resting state functional MRI (rsfMRI) signals can effectively depict neuronal activity and psychopathological status, this study examined white-matter network-level interactions in antipsychotic-naive first-episode schizophrenia (FES) to facilitate the interpretation of the psychiatric pathological mechanisms in schizophrenia. Methods: We recruited a total of 106 participants from two independent cohorts including 55 FES patients (FESs) and 51 healthy controls (HCs), all of whom underwent rsfMRI. We identified 11 white-matter functional networks, which could be further classified into deep, middle, and superficial layers of networks. We then examined network-level interactions among these 11 white-matter functional networks using Granger causality analysis. We employed group comparisons on the influences among 11 networks using network-based statistic. Outcomes: In the primary cohort, excitatory influences from the middle superior corona radiate network to the superficial orbitofrontal and deep networks were disrupted in FESs compared with HCs. Additionally, an extra failure of suppression within superficial networks (including the pre/post-central network, temporofrontal network, and the orbitofrontal network) was observed in FESs. Similar replication results of an independent sample further verified the middle network disengagement in the white-matter network interaction model of FES. Interpretations: The novel findings of impaired interactions among white-matter functional networks in schizophrenia indicate that the pathophysiology of schizophrenia may also lie in white-matter functional abnormalities. Funding Statement: This work was supported by the National Natural Science Foundation of China (61533006, 81471653, 81771919, 61673089 and U1808204), China Postdoctoral Science Foundation (2013M532229), Sichuan Science and Technology Program (2018TJPT0016), and the “111” project (B12027). Declaration of Interests: The authors declare that they have no conflict of interest. Ethics Approval Statement: This study was approved by the Ethics Committee of the Second Affiliated Hospital of Xinxiang Medical University, China.

“Neighbors in values”: A new dataset of cultural distances between countries based on individuals’ values, and its application to the study of global trade

The paper proposes a method for evaluating the cultural distance between countries by analyzing the differences in values of individuals residing in these countries. These differences are assessed with an innovative approach based on MELNN ensemble of five metrics (Mahalanobis distance, Euclidean distance, L-distance, as well as normalized versions of Euclidean and L-distances), compiled through factor analysis. For each individual we find “neighbors in values”, i.e. other individuals with possibly closest MELNN scores. We proceed to build a network interaction model on the basis of MELNN scores. Analyzing the closeness to each individual from country A of the whole multitude of individuals residing in country B eventually allows to define the cultural distance between these countries. We use the thus obtained cultural distances in a gravity model, where they prove to be a significant factor influencing bilateral trade.

СЕТЕВАЯ ФОРМА РЕАЛИЗАЦИИ ОБРАЗОВАТЕЛЬНЫХ ПРОГРАММ ПРИ ПОДГОТОВКЕ БАКАЛАВРОВ ПРОФЕССИОНАЛЬНОГО ОБУЧЕНИЯ: ПРОБЛЕМЫ И ПЕРСПЕКТИВЫ

<p>The article provides an overview of research relating to various aspects of networking, especially network interaction models, used in educational practice institutions. Here are considered some of the existing concept of networking. The article offers a detailed considering of networking in higher education, which is characterized by several basic processes, namely the development of distance education, academic mobility of teachers, distribution of student exchange programs, the development of research activities, including the international level. As an example, we consider the networking of vocational training in the preparation of bachelors in the branch FSAEI HE (Federal State Autonomous Educational Institution of Higher Education) "Russian State Vocational Pedagogical University" in Kemerovo. The purpose of training teachers of SVE (secondary vocational education) in accordance with the professional standards of the teacher and the federal state educational standards is to design the network of educational programs and the participation of educational institutions in networking. The author offers criteria of efficiency networking IBD (Integrated base department) (VTE) (vocational teacher education) and base organizations.</p>

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The study is relevant in the context of global projects supported by the government and initiated by the President of the Russian Federation: the federal
 state educational standards, the complex project of modernization of education, national educational initiative �Our new school�, �Concept of the
 spiritual and moral development and education of a citizen of Russia.� In the context of extracurricular activities in the design development of the FSES
 becoming especially popular networking projects that brings together institutions of diff erent levels (schools, supplementary education for children, psychological
 urban centers, higher education institutions). The interaction of educational institutions is becoming a modern highly innovative technology
 that allows them to develop dynamically.
 The article describes a model of network interaction of educational-governmental organizations of the city of Kaluga in the framework of the extracurricular
 activity of younger schoolboys in the terms of realization of the FSES of primary education.
 Model networking educational institutions of the city of Kaluga in the framework of the extracurricular activity of younger schoolboys in the development
 of the FSES of primary education has been successfully tested on the basis of four elementary schools in the city of Kaluga, the study involved 177 students
 and 7 primary school teachers. Social partners of educational networking were: Children and Youth Space Education Center �Galaxy� of the city of Kaluga
 and Kaluga State University named after K.E. Tsiolkovsky. The basis of networking cooperation were programs of extracurricular activities of I.V. Ivanova.
 The main results of testing of the model is the development of individual students in the development of programs that increase the level of professional
 competence of primary school teachers in the organization of extracurricular activities of the FSES of the primary general education.
 The study contributes to a system of total innovative design, Further and Higher Education; It shows the possibility of the contents and forms of social and
 pedagogical partnership in the system of education in the introduction of the FSES of primary education. The practical signifi cance of the study consists
 in the possibility of using the developed model in educational practice. The study will allow to make science-based contribution to the practical implementation
 of the regional. Prospects for the development of research consist in the development of new models of a network of educational cooperation,
 attraction of new bases for cooperation.
 This publication was prepared within the framework of a research project supported by the Russian Foundation for Humanities �14-16-40007.

Rainwater Harvesting and Social Networks: Visualising Interactions for Niche Governance, Resilience and Sustainability

Visualising interactions across urban water systems to explore transition and change processes requires the development of methods and models at different scales. This paper contributes a model representing the network interactions of rainwater harvesting (RWH) infrastructure innovators and other organisations in the UK RWH niche to identify how resilience and sustainability feature within niche governance in practice. The RWH network interaction model was constructed using a modified participatory social network analysis (SNA). The SNA was further analysed through the application of a two-part analytical framework based on niche management and the safe, resilient and sustainable (‘Safe and SuRe’) framework. Weak interactions between some RWH infrastructure innovators and other organisations highlighted reliance on a limited number of persuaders to influence the regime and landscape, which were underrepresented. Features from niche creation and management were exhibited by the RWH network interaction model, though some observed characteristics were not represented. Additional Safe and SuRe features were identified covering diverse innovation, responsivity, no protection, unconverged expectations, primary influencers, polycentric or adaptive governance and multiple learning-types. These features enable RWH infrastructure innovators and other organisations to reflect on improving resilience and sustainability, though further research in other sectors would be useful to verify and validate observation of the seven features.

Point-process models of social network interactions: Parameter estimation and missing data recovery

Electronic communications, as well as other categories of interactions within social networks, exhibit bursts of activity localised in time. We adopt a self-exciting Hawkes process model for this behaviour. First we investigate parameter estimation of such processes and find that, in the parameter regime we encounter, the choice of triggering function is not as important as getting the correct parameters once a choice is made. Then we present a relaxed maximum likelihood method for filling in missing data in records of communications in social networks. Our optimisation algorithm adapts a recent curvilinear search method to handle inequality constraints and a non-vanishing derivative. Finally we demonstrate the method using a data set composed of email records from a social network based at the United States Military Academy. The method performs differently on this data and data from simulations, but the performance degrades only slightly as more information is removed. The ability to fill in large blocks of missing social network data has implications for security, surveillance, and privacy.

Regulatory Networks Controlling Nitrogen Sensing and Uptake in Candida albicans

Nitrogen is one of the key nutrients for microbial growth. During infection, pathogenic fungi like C. albicans need to acquire nitrogen from a broad range of different and changing sources inside the host. Detecting the available nitrogen sources and adjusting the expression of genes for their uptake and degradation is therefore crucial for survival and growth as well as for establishing an infection. Here, we analyzed the transcriptional response of C. albicans to nitrogen starvation and feeding with the infection-relevant nitrogen sources arginine and bovine serum albumin (BSA), representing amino acids and proteins, respectively. The response to nitrogen starvation was marked by an immediate repression of protein synthesis and an up-regulation of general amino acid permeases, as well as an up-regulation of autophagal processes in its later stages. Feeding with arginine led to a fast reduction in expression of general permeases for amino acids and to resumption of protein synthesis. The response to BSA feeding was generally slower, and was additionally characterized by an up-regulation of oligopeptide transporter genes. From time-series data, we inferred network interaction models for genes relevant in nitrogen detection and uptake. Each individual network was found to be largely specific for the experimental condition (starvation or feeding with arginine or BSA). In addition, we detected several novel connections between regulator and effector genes, with putative roles in nitrogen uptake. We conclude that C. albicans adopts a particular nitrogen response network, defined by sets of specific gene-gene connections for each environmental condition. All together, they form a grid of possible gene regulatory networks, increasing the transcriptional flexibility of C. albicans.

Probabilistic analysis of communities and inner roles in networks: Bayesian generative models and approximate inference

Two fundamental tasks in network analysis are community discovery and role assignment. Hitherto, these have been conducted separately. We argue that their integration provides a deeper understanding of connectivity patterns and present unsupervised learning approaches to the exploratory analysis of communities and inner roles of nodes across their interactions in directed networks. In particular, we propose two Bayesian probabilistic models of network interactions that seamlessly integrate community discovery and role assignment. One is the model of a generative process, in which pairs of nodes in a network are associated with communities and roles in the context of their communities; before that an interaction is possibly established between them. According to the generative semantics of such a model, nodes are represented as probability distributions over communities, while communities are viewed as probability distributions over roles. The other model specifies a generative process based on link partitioning, that associates pairs of nodes with respective roles and then assigns their possible interaction to one link community. This is accomplished by representing nodes as probability distributions over roles and, additionally, by explicitly modeling how roles interact with each other. The foresaid distributions are unknown parameters of the proposed models that are estimated from the observed network interactions through suitable Markov Chain Monte Carlo algorithms for approximated posterior inference and parameter estimation. One model overcomes state-of-the-art competitors in link-prediction over real-world networks. The other exhibits a competitive predictive power. Both models overcome an established probabilistic competitor at identifying relatively recognizable structure in synthetic networks.

Research on Micro-Macro Process of Industrial Aggregation Based on Social Network Interaction Model

It is necessary to detect the aggregation dynamics and aggregation process of industry cluster for there are still some problems in the development of industrial cluster. The existing theories are less attention to the impacts of the social network of enterprises and their interactions on the industrial aggregation. We proposed a social network interaction model and research on the industrial aggregation process from the aspect of economic sociology. The impacts of signal effect, network effect and crowding effect on the dynamic micro-macro process of industrial aggregation are discussed and two possible phase transition and its causes in industrial aggregation process are explored. The simulation outcomes are good explanations for industrial aggregation process and made some useful implications for policy-making.

Transfer entropy in magnetoencephalographic data: Quantifying information flow in cortical and cerebellar networks

The analysis of cortical and subcortical networks requires the identification of their nodes, and of the topology and dynamics of their interactions. Exploratory tools for the identification of nodes are available, e.g. magnetoencephalography (MEG) in combination with beamformer source analysis. Competing network topologies and interaction models can be investigated using dynamic causal modelling. However, we lack a method for the exploratory investigation of network topologies to choose from the very large number of possible network graphs. Ideally, this method should not require a pre-specified model of the interaction. Transfer entropy – an information theoretic implementation of Wiener-type causality – is a method for the investigation of causal interactions (or information flow) that is independent of a pre-specified interaction model. We analysed MEG data from an auditory short-term memory experiment to assess whether the reconfiguration of networks implied in this task can be detected using transfer entropy. Transfer entropy analysis of MEG source-level signals detected changes in the network between the different task types. These changes prominently involved the left temporal pole and cerebellum – structures that have previously been implied in auditory short-term or working memory. Thus, the analysis of information flow with transfer entropy at the source-level may be used to derive hypotheses for further model-based testing.