Characteristics Of Information Flow Research Articles

Characteristics of Information Flow in Scientific Research

Characteristics of Information Flow in Scientific Research

The influence of recommendation algorithm's information flow on targeted advertising audience's coping behavior

Targeted advertising equipped with a recommendation algorithm can achieve accurate matching between users and recommended content, but overly precise recommendations may exacerbate negative audience reactions or behaviors. Improving the transparency of algorithm recommendation is one of the ways to address audience concerns or skepticism, and transparency guarantees the audience's right to know and thus brings more trust, which will reduce the audience's negative behavior. But increased transparency may also make the audience feel pressured or threatened, and requiring more cognitive and behavioral effort, which was called coping behavior. In order to clarify the relationship between the transparency of the algorithm recommendation and the audience's coping behavior, based on the persuasion theory, this study discusses the mechanism of the influence of the characteristics of the algorithm recommendation information flow on the audience's coping behavior of targeted advertising from the perspective of the flow mode and transmission principle of information. Based on the data of 120 online pretests and 297 formal tests, the results show that the perceived trust and perceived threat caused by the information flow characteristics of the algorithm recommendation jointly determine the possible coping behaviors of targeted advertising audiences. Additionally, users' self-efficacy regulates the relationship between mental process and coping behavior. Different from previous studies on audience coping behaviors of targeted ads, which mainly start from the perspective of participants and advertising content, this research tries to start from the perspective of information flow. The research results demystify the relationship between recommendation algorithm information flow and the audience's coping behavior, and enrich the algorithmic persuasion framework. The research results have reference value for the improvement of personalized recommendation effect, and provide a new way to further study the transparency of algorithm recommendation in the field of consumer behavior. Meanwhile, it also provides suggestions for the practices of platforms and advertisers in practice.

Developing the data management component of an academic discipline program for an educational management information system

Objectives . The need to apply methods and models to support the educational process at universities including the formation and management of academic discipline programs (ADPs) is determined by the growing need for the active implementation of various automation tools including integrated information systems, which arise in response to a number of regulatory and legal factors. Such social factors result in the significant increase in the volume and categories of information circulating within business processes of an educational organization, as well as the expansion of the requirements for ensuring the protection, storage, and transmission of information. In recent years, the Government of the Russian Federation has approved the national “Digital Economy” and “Education” projects (including the Federal Project “Digital Educational Environment”) emphasizing the growing role of informatization and digitalization processes in education. In this connection, an obvious discrepancy arises between the theoretical characteristics of information flows existing in educational organizations and the methods of its collection, processing, storage, analysis, and application used in practice. One of the most important conceptual components of the educational process in higher education institutions is the ADP, which organizes the relationship between various components of the educational process: curriculum, competencies, training areas, learning technologies, and methods for conducting the control check of students’ knowledge. The labor-intensive and variable nature of ADP development and implementation requires the introduction of information technologies. Thus, the aim of the present work is to analyze the volume and structure of institutional educational programs in order to identify the necessary software requirements. Methods . The classification of learning management systems according to various criteria, key requirements for academic disciplines, and ADP structure is considered. Results . An analysis of links between the ADP and key entities of the educational process is presented. The functionality of the self-developed ADP module for implementing at RTU MIREA is aimed at providing interconnection, transparency, and availability of links between academic discipline parameters and its sections. Conclusions . Introducing the ADP module allows reducing the time spent on developing the program by providing universal templates of academic disciplines, along with the possibility of autofilling the academic discipline parameters and tracking the current status of ADPs, as well as increasing the level of awareness of participants in the educational process.

Distributed Supervision Model for Enterprise Data Asset Trading Based on Blockchain Multi-Channel in Industry Alliance.

Compared with traditional physical commodities, data are intangible and easy to leak, and the related trading process has problems, such as complex participating roles, lengthy information flow, poor supervisory coverage and difficult information traceability. To handle these problems, we construct a distributed supervision model for data trading based on blockchain, and conduct multi-party hierarchical and multi-dimensional supervision of the whole process of data trading through collaborative supervision before the event, at present and after the event. First, the characteristics of information flow in the data trading process are analyzed, and the main subject and key supervision information in the data trading process are sorted out and refined. Secondly, combined with the actual business process of data trading supervision, a multi-channel structure of distributed supervision is proposed by adopting an access–verification–traceability strategy. Finally, under the logical framework of the supervision model, the on-chain hierarchical structure and the data hybrid storage method of “on-chain + off-chain” are designed, and multi-supervisor-oriented hierarchical supervision and post-event traceability are realized through smart contracts. The results show that the constructed blockchain-based distributed supervision model of data trading can effectively isolate and protect sensitive and private information between data trading, so as to realize the whole process, multi-subject and differentiated supervision of key information of data trading, and provide an effective and feasible method for the controllable and safe supervision of data trading.

A Refined Supervision Model of Rice Supply Chain Based on Multi-Blockchain.

With the development of Agriculture 4.0, the requirements for sustainable agriculture and precision agriculture continue to grow. As one of the three major staple foods globally, the quality and safety of rice affect human health as well as social development. To ensure the quality and safety of rice and reduce the flow of problematic rice, a multi-layer blockchain-based rice supply chain refinement supervision model MBRRSM (Multi-blockchain Rice Refined Supervision Model) is proposed from the information level. First, the characteristics of information flow in the rice supply chain are analyzed, and a classification table of key information is constructed. Second, the MBRRSM framework is designed. Based on a multi-party hybrid encryption algorithm, secure multi-party computing algorithm, multi-mode storage mechanism, and SPOP (Supervision Proof of Peers) consensus algorithm, a set of mechanisms is designed for the transmission, use, storage, and consensus of rice data in MBRRSM. Subsequently, the security and performance capabilities of MBRRSM are analyzed. Meanwhile, the SPOP consensus algorithm is analyzed. Finally, a prototype system is built based on MBRRSM and verified through exemplary scenarios in different usage situations. The results show that research on the refined supervision of the rice supply chain based on multi-blockchain can finely supervise all types of data in the rice supply chain, and provide a guarantee for enterprise users to safely transmit and use data with different privacy levels. This study presents a unique research paradigm that introduces the theories and methods of the new information field generation into the field of agricultural research, and thus assists in the strategy implementation of “holding grain in the land and storing grain in technology”.

Location and Language Independent Fake Rumor Detection Through Epidemiological and Structural Graph Analysis of Social Connections.

Detection and identification of misinformation and fake news is a complex problem that intersects several disciplines, ranging from sociology to computer science and mathematics. In this work, we focus on social media analyzing characteristics that are independent of the text language (language-independent) and social context (location-independent) and common to most social media, not only Twitter as mostly analyzed in the literature. Specifically, we analyze temporal and structural characteristics of information flow in the social networks and we evaluate the importance and effect of two different types of features in the detection process of fake rumors. Specifically, we extract epidemiological features exploiting epidemiological models for spreading false rumors; furthermore, we extract graph-based features from the graph structure of the information cascade of the social graph. Using these features, we evaluate them for fake rumor detection with 3 configurations: (i) using only epidemiological features, (ii) using only graph-based features, and (iii) using the combination of epidemiological and graph-based features. Evaluation is performed with a Gradient Boosting classifier on two benchmark fake rumor detection datasets. Our results demonstrate that epidemiological models fit rumor propagation well, while graph-based features lead to more effective classification of rumors; the combination of epidemiological and graph-based features leads to improved performance.

Digital Technology-and-Services-Driven Sustainable Transformation of Agriculture: Cases of China and the EU

China’s sustainable development goals and carbon neutrality targets cannot be achieved without revolutionary transitions of the agricultural sector. The rapid development of digital technologies is believed to play a huge role in this revolution. The ongoing prevention and control of COVID-19 has greatly boosted the penetration of digital technology services in all areas of society, and sustainable transformation driven by digital technologies and services is rapidly becoming an area of innovation and research. Studies have shown that the rapid advancement of digitalization is also accompanied by a series of new governance challenges and problems: (1) unclear strategic orientation and inadequate policy and regulatory responses; (2) various stakeholders have not formed a sustainable community of interest; (3) information explosion is accompanied by information fragmentation and digital divide between countries and populations within countries. Meanwhile, current research has focused more on the role of digital services in urban governance and industrial development and lacks systematic research on its role in sustainable agricultural and rural development. To address the realities faced by different stakeholders in the process of digital transformation of agriculture, this paper aims to propose an inclusive analytical framework based on the meta-governance theory to identify and analyze the demand, supply, actor networks, and incentives in the digital technology-and-services-driven sustainable agricultural transformation, starting from the goals and connotations of sustainable agricultural and rural transformation and the interactions among different stakeholders in governing information flows. This analytical framework is further applied to analyze the cases of China and the EU. Although China and the EU represent different development phases and policy contexts, the framework is valid for capturing the characteristics of information flows and actor networks along the flows. It is concluded that a common information platform based on the stakeholder network would benefit all stakeholders, help reach common framing of issues, and maintain a dynamic exchange of information. Depending on the country context, different types of stakeholders may play different roles in creating, supervising, and maintaining such platforms. Digital infrastructures/products as hardware and farmers digital capacity as ‘software’ are the two wings for digital sustainable transformation. Innovative incentives from different countries may inspire each other. In any case, farmers’ actual farming behavior changes should be an important criterion for evaluating the effects and effectiveness of digital transition governance.

Multiresolution directed transfer function approach for segment-wise seizure classification of epileptic EEG signal.

Currently, with the bloom in artificial intelligence (AI) algorithms, various human-centered smart systems can be utilized, especially in cognitive computing, for the detection of various chronic brain diseases such as epileptic seizure. The primary goal of this research article is to propose a novel human-centered cognitive computing (HCCC) method for segment-wise seizure classification by employing multiresolution extracted data with directed transfer function (DTF) features, termed as the multiresolution directed transfer function (MDTF) approach. Initially, the multiresolution information of the epileptic seizure signal is extracted using a multiresolution adaptive filtering (MRAF) method. These seizure details are passed to the DTF where the information flow of high frequency bands is computed. Thereafter, different measures of complexity such as approximate entropy (AEN) and sample entropy (SAEN) are computed from the extracted high frequency bands. Lastly, a k-nearest neighbor (k-NN) and support vector machine (SVM) are used for classifying the EEG signal into non-seizure and seizure data depending on the multiresolution based information flow characteristics. The MDTF approach is tested on a standard dataset and validated using a dataset from a local hospital. The proposed technique has obtained an average sensitivity of 98.31%, specificity of 96.13% and accuracy of 98.89% using SVM classifier. The average detection rate of the MDTF approach is 97.72% which is greater than the existing approaches. The proposed MDTF method will help neuro-specialists to locate seizure information drift which occurs within the consecutive segments and between two channels. The main advantage of the MDTF approach is its capability to locate the seizure activity contained by the EEG signal with accuracy. This will assist the neurologists with the precise localization of the epileptic seizure automatically and hence will reduce the burden of time-consuming epileptic seizure analysis.

Performance Improvement in Manufacturing Shop Floor Operations of Developing Countries Based on Three Characteristics of Information Flow

The management of information flow for production improvement has always been a target in the research. In this paper, the focus is on the analysis model of the characteristics of information flow in shop floor operations based on the influence that dimension (support or medium), direction and the quality information flow have on the value of information flow using machine learning classification algorithms. The obtained results of classification algorithms used to analyze the value of information flow are Decision Trees (DT) and Random Forest (RF) with a score of 0.99% and the mean absolute error of 0.005. The results also show that the management of information flow using DT or RF shows that, the dimension of information such as digital information has the greatest value of information flow in shop floor operations when the shop floor is totally digitalized. Direction of information flow does not have any great influence on shop floor operations processes when the operations processes are digitalized or done by operators as machines.

CLASSIFICATION OF INFORMATION FLOWS IN THE TOURISM BUSINESS

Purpose. The aim of the article is formulation of the main classification features of information flows in the tourism business. Methodology of research. Realization of the established goal of the research involves the use of a certain methodology. To highlight the main approaches, signs and types of information flows, the deduction method was used, which involved the selection of individual structural components based on an in-depth analysis of the characteristics of the phenomenon under study. The classification of signs was carried out on the basis of the method of data systematization. The assessment of the conformity of the positions of the authors with the content of a certain scientific approach was carried out on the basis of the application of a comparative analysis of the content of the provisions of their research. Findings. The main approaches and corresponding classification features of information flows in the tourism sphere are singled out, which made it possible to formulate a typology of the latter. The presented classification of signs and types of information flows was developed taking into account the modern characteristics and specifics of the development of the tourist business, which functions taking into account social transformations, social and economic, information and communication changes. It has been proven that the reference to the given classification signs (multi-branch signs, advertising subject-object sign, marketing-market subject-object sign, sign of synthesized influence) will enable tourism enterprises to make important management decisions in various areas, to carry out analysis and forecasting of future development prospects. It is noted that it cannot be claimed that the presented list of classification features and types of information flows in the tourism sphere is unchanged or is distinguished by stable characteristics for the long term, since the dynamism of the environment can provide transformations in its development. Originality. The classification of signs of information flows in the tourism business has gained further development, in particular, the author put forward and substantiated the sign of synthesized influence, and the main types of information flows in tourism characteristic of it have also been highlighted. Practical value. The given classification of information flows can be used to assess the actual and forecast types and characteristics of information flows in the tourism business. Key words: information flows, tourism business, synthesized impact, multi-industry features, advertising subject-object feature, marketing-market subject-object feature, advantages, negative impact.

ОЦІНКА ІНФОРМАЦІЙНОЇ ПОВ’ЯЗАНОСТІ ПРОЦЕСІВ ПРИ ФУНКЦІОНАЛЬНОМУ МОДЕЛЮВАННІ СИСТЕМИ ВИПРОБУВАНЬ

The national security and defense capability of the state is largely determined by the level of equipping the armed forces with modern weapons and military equipment. An important point in the rearmament of the army is the high-quality and timely testing of the latest military models, which, to a large extent, is ensured by successful and systematic planning and management of test activities. The automated test support information system is aimed at solving such problems. During the IDEF0 notation, functional modeling of the armaments and military equipment testing system was designed, which allowed to determine the system-wide characteristics of information flows, but did not allow obtaining models performance evaluation. Existing methods for estimating distributed structures, as a rule, are reduced to estimating the connectivity of graph models and do not take into account the features of the interface of the IDEF0 notation functions.The article considers the issue of evaluation of functional models at the pre-design stage. A method for estimating the functional connectivity of processes in the functional modeling of complex systems using graph-ical notation IDEF0 and using automated design tools is proposed. The estimation has clear logical limits and is sensitive to changes in the parameters of the evaluated model. Due to the different importance of connections provided by the graphical notation interface IDEF0, it is proposed to use a scale of importance of the type of connection, which reflects the assessment of the connectedness of functions of strong or weak types of connections, and, accordingly, the success and rationality of functional configuration models. Estimates of the functional model of the weapons and military equipment test system are obtained.The use of the proposed evaluation method will allow to compare the structures of functional models of complex systems at the stage of pre-design studies

Predictive analysis of the value of information flow on the shop floor of developing countries using artificial neural network based deep learning

To facilitate the continuous improvement of performance and the management of information flow (MIF) for production and manufacturing purposes on the shop floor of developing countries, there is a need to characterize information flow that will be shared during the process. MIF provides a key performance shop floor metric called the value of information flow (VIF). Previous methods have been used to analyze VIF in developed countries. However, these methods are sometimes limited when applied to developing countries where the shop floor is disorganized. It then renders the MIF with the imported software inefficient because of the gap between the user environments. Taking Cameroon as a case study, this study proposes a new method of modeling and analyzing the information flow and its value based on the characteristics of information flow (CIF) for developing countries. In addition, a predictive analysis of the VIF based on CIF using an artificial neural network (ANN) on one hand and optimized ANN with particle swarm optimizer (PSO) and genetic algorithms (GA) on the other is performed. The ANN model of regression developed has the following performance: coefficient of determination: 0.99 and mean squared error (MSE): 0.00043. For the PSO-ANN, the MSE decreased to 0.00011, and this model result was similar to that of the deep learning model used for regression. The GA-ANN model results were not as satisfactory as those of the PSO-ANN model. A predictive system to analyze VIF is proposed for managers of companies in developing countries.

Системний аналіз та побудова моделі інформаційних потоків тепличного комплексу

The analysis of existing methods and systems of management of the greenhouse complex is carried out. It has been determined that the most expedient is the development of new methods and control systems that would take into account the mutual influence of microclimate parameters, predicted changes in external natural disturbances and determine the most energy efficient modes of functioning of the greenhouse economy. A systematic analysis of the greenhouse complex at the stages of structural, functional, informational and parametric analysis was carried out. A system of goals and a tree of goals for the energy efficient functioning of the greenhouse complex has been built using the decomposition of goals and objectives and synthesis with the definition of the components of the greenhouse economy. The quantitative and qualitative characteristics of information flows between subsystems have been determined and a model of information flows has been built. For the purpose of carrying out functional analysis and synthesis, the method of mathematical description is used - the theory of graphs. The quantitative and qualitative characteristics of information flows between subsystems have been determined using the construction of a model of information flows. A parametric analysis and synthesis were carried out to determine the main controlled and regulated parameters of the greenhouse complex in order to ensure the maximum efficiency of the control system. Structural analysis and synthesis were carried out with the definition of the components of the greenhouse economy, the interrelationships of the subsystems of the greenhouse complex were analyzed and it was proved that the object under study is a complex system. The directions of further research have been formed for the processes of self-organization and management of information flows of the greenhouse complex, which provide for a plurality of scenarios for further development. Key words: greenhouse complex, system analysis, information flows, goal tree, energy efficient management

Spatial Characteristics of the Tourism Flows in China: A Study Based on the Baidu Index

The characteristics of information flow, as represented by the Baidu index, reflect the pattern of tourism flows between different cities. This paper is based on the Baidu index and applies the seasonal concentration index and social network analysis (SNA) methods to study the spatial structure characteristics of tourism flows in China. The results reveal that: (1) both the search volume of the Baidu index in different cities and the online attention to different scenic areas exhibit obvious spatial heterogeneity and seasonal differences; (2) regions with strong tourism flow connections mainly occur in the areas between metropolises or among the inner cities of urban agglomerations, which are largely distributed on the southeast side of the Heihe–Tengchong Line; (3) the development of the whole tourism flow network in China is low, with an unbalanced development between tourism supply and demand, indicating that tourism resources are concentrated in a few cities and that most of the information interaction among cities occurs in core areas, while a weak interaction is observed in peripheral areas; (4) cities like Beijing and Wuhan attain obvious advantages in regard to their tourism resources, whereas other cities, including Beijing, Shanghai, Shenzhen and Guangzhou, exhibit a high demand for tourism. Moreover, tourism information flow networks are concentrated in several cities with an important role in the Chinese urban system, such as Beijing, Wuhan, and Chengdu, because they contain abundant tourism resources, well-developed transportation systems and advanced economic and societal development levels. (5) Cities such as Beijing, Lhasa, Wuhan, and Zhengzhou possess numerous advantages due to structural holes, and they thus occur at an advantageous position in the tourism flow network.

Analysis of Information Flow Characteristics in Shop Floor: State-of-the-Art and Future Research Directions for Developing Countries

The information flow in a company is a whole set of static or dynamic data obtained from communication used for the conception and realization of products; facing competition, every company aims at improving its performance to meet customer needs. The focus on information flow to improve the performances of companies has always been a major preoccupation in the research domain, which always contributes to the evolution of the analysis of information flow for companies to be more efficient. This article presents the state of the art on the analysis of information flow model based on information characteristics in shop floor manufacturing companies (known as advanced in technology) to ameliorate their performance and future research directions for small- and medium-sized manufacturing companies for developing countries to be more competitive and efficient.

THEORETICAL - APPLIED PRINCIPLES OF FORMATION OF INFORMATION AND ANALYTICAL SUPPORT OF PROTECTION OF THE MARINE ENVIRONMENT FROM VESSEL POLLUTION

Topicality. The relevance of the study is due to the fact that the growing dynamics of marine pollution and power and uneven information flows that accompany the pollution process. This requires the creation of an information-analytical system to support decision-making on effective pollution prevention and elimination. And the creation of such a system, in turn, requires research on the theoretical and applied principles of its formation. Aim and tasks. The main purpose of the study is the development of theoretical and applied provisions on the peculiarities of the formation of information and analytical support of the marine environment from pollution and development of system approaches and mathematical apparatus for designing information transmission channels and ensuring efficient Traffic Engineering. Research results. Theoretical and applied bases of formation of information-analytical maintenance of protection of the marine environment from pollution by ships are investigated. Peculiarities of formation, first of all, connected with the existing branched normative-legal base of protection of water area from pollution are revealed. The mechanisms of pollution and their inherent characteristics of information flows are identified, which requires the use of methods Traffic Engineering. Mathematical formalization is proposed for efficient design of information transmission channels and ensuring efficient Traffic Engineering. An approach to assessing the effectiveness of the information transfer process and as the main criterion in Traffic Engineering for ISMP - resource utilization factor. The algorithm before the design check of the bandwidth of the information system routes under the dynamic variant of information processing is formalized. Conclusion. The presented article investigates the theoretical and applied aspects of the formation of a single information and analytical support for the protection of the marine environment, in particular, those features that are due to the existing regulatory framework and existing pollution mechanisms. A mathematical apparatus for designing information transmission channels and ensuring efficient Traffic Engineering. An approach to assessing the effectiveness of the information transfer process and as the main criterion in the method is proposed Traffic Engineering for ISMP - resource utilization factor. The algorithm before the design check of the bandwidth of the information system routes under the dynamic variant of information processing is formalized. All this allows creating the necessary conditions for the formation of a single information and analytical support for the protection of the marine environment.

Abnormal information flow in postpartum depression: A resting-state functional magnetic resonance imaging study

Background: Postpartum depression (PPD) is a common mental disorder among women. However, the brain information flow alteration in patients with PPD remains unclear. This study investigated the brain information flow characteristics of patients with PPD and their value for clinical evaluation by using support vector regression (SVR). Methods: Structural and resting-state functional magnetic resonance imaging data were acquired from 21 patients with PPD and 23 age-, educational level-, body mass index-, and menstruation-matched healthy controls. The preferred information flow direction between local brain regions and the preferred information flow direction index within local brain regions based on non-parametric multiplicative regression granger causality analysis were calculated to determine the global and local brain functional characteristics of the patients with PPD. Pearson's correlation analyses were performed to evaluate the relationship of the information flow characteristics with clinical scales. A predictive model for the mental state of the patients with PPD was established using SVR based on information flow characteristics. Results: The information flow patterns in the amygdala, cingulum gyrus, insula, hippocampus, frontal lobe, parietal lobe, and occipital lobe changed significantly in the patients with PPD. The preferred information flow direction between the amygdala and the temporal and frontal lobes significantly correlated with clinical scales. Prediction analysis shows that the information flow patterns can be used to assess depression in patients with PPD. Limitation: This exploratory study has a small sample size with no longitudinal research. Conclusion: The change in information flow pattern in the amygdala may play an important role in the neuropathological mechanism of PPD and may provide promising markers for clinical evaluation.

Інформаційна модель оперативно-розшукової діяльності оперативних підрозділів Державної прикордонної служби України

In the scientific article the definition and information model of the operational-search activity of the operational units of the State Border Guard Service of Ukraine are defined and developed. It is noted that such a model is a set of information describing the structure and directions of information flows of information-analytical interaction, which systematically circulate in the information space to ensure the fulfillment of tasks defined by the laws ofUkraine. The information model and its structure is described and analyzed. The levels of the State Border Guard's Service of Ukraine operational and search units and the internal and external objects of information are presented. The procedure of forming the internal and external information space of the information model is briefly explained.It is noted that in the process of the activity the operational-search units of the State Border Guard Service of Ukraine are united by different flows of information, the list of which is provided. In addition, it is noted that the information flows of the internal and external information space of the developed model have certain properties, which are characterized by the content, methods of receiving, the form of sending and the intensity of information exchange between the operational and search units and the objects of its receipt. Parameters and indicators of quantitative and qualitative characteristics of information flows are determined. An example of estimating the content of information in the information flow by the indicator of reliability using the method "4x4" and an approach to its improvement is given. The criteria for the information model of the operative-search activity of the operational-search units of the State Border Guard Service of Ukraine should meet is suggested. It is stated that the creation of an information model is a necessary stage for further research of the information-analytical activity of the operational-search units of the State Border Guard Service of Ukraine.

Маркeтинг, збут та логістика сільськогосподарської продукції в систeмі управління розвитком аграрного підприємства

У статті обґрунтовано значимість впровадження і використання у процeсі маркетингової діяльності підприємства інформаційних систeм і технологій, окреслено основні проблеми, що виникають у даній сфері. Наведено принципи та фактори, відповідно до яких повинне формуватися ефективне інформаційне забезпечення маркетингу аграрних підприємств. Встановлено важливість ролі інформаційних потоків у ефективній організації маркетингової діяльності аграрних підприємств, відзначено, що ключовим елементом у структурі організаційно-економічного механізму функціонування системи маркетингової інформації є зворотній зв'язок.

Intracortical Causal Information Flow of Oscillatory Activity (Effective Connectivity) at the Sleep Onset Transition.

We investigated the sleep onset transition in humans from an effective connectivity perspective in a baseline condition (approx. 16 h of wakefulness) and after sleep deprivation (40 h of sustained wakefulness). Using EEG recordings (27 derivations), source localization (LORETA) allowed us to reconstruct the underlying patterns of neuronal activity in various brain regions, e.g., the default mode network (DMN), dorsolateral prefrontal cortex and hippocampus, which were defined as regions of interest (ROI). We applied isolated effective coherence (iCOH) to assess effective connectivity patterns at the sleep onset transition [2 min prior to and 10 min after sleep onset (first occurrence of stage 2)]. ICOH reveals directionality aspects and resolves the spectral characteristics of information flow in a given network of ROIs. We observed an anterior-posterior decoupling of the DMN, and moreover, a prominent role of the posterior cingulate cortex guiding the process of the sleep onset transition, particularly, by transmitting information in the low frequency range (delta and theta bands) to other nodes of DMN (including the hippocampus). In addition, the midcingulate cortex appeared as a major cortical relay station for spindle synchronization (originating from the thalamus; sigma activity). The inclusion of hippocampus indicated that this region might be functionally involved in sigma synchronization observed in the cortex after sleep onset. Furthermore, under conditions of increased homeostatic pressure, we hypothesize that an anterior-posterior decoupling of the DMN occurred at a faster rate compared to baseline overall indicating weakened connectivity strength within the DMN. Finally, we also demonstrated that cortico-cortical spindle synchronization was less effective after sleep deprivation than in baseline, thus, reflecting the reduction of spindles under increased sleep pressure.