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Abstract Background Public awareness is crucial for successful deployment of tidal energy, a renewable energy source that can provide clean electricity to remote islands. However, considering public attitudes on tidal energy are not well known, especially in developing countries, a barrier exists in implementing public engagement strategies. This study aims to contribute by identifying strategies for information provision—the initial step in public engagement—and estimate how these can be engaged to enhance support for tidal energy among the local public in a remote area of a developing country, in this case, Flores Timur Regency, Indonesia, considering their socio-cultural background. Methods In this paper, we employ statistical analyses using multinomial probit modelling to identify the key variables that shape information flow. The aptness of the variables is then verified using post-estimation techniques for their use as input parameters for the simulation of the information flow in the field study area. Agent-based simulation (ABS) is employed to replicate the actual conditions in Flores Timur Regency, Indonesia, and simulate the flow of information through the local community. Results According to the multinomial probit estimations, the people belonging to the top hierarchical group show a higher probability to support tidal energy compared to the members belonging to the lower groups. Understandably, around twice as many information flow cycles are needed to disseminate information to the members of the lowest hierarchical group, compared to the members of the top hierarchical group. The results also show that increasing the amount of available information has a positive impact on information dissemination. Conclusions This study demonstrated that information provision is highly effective with propagation of information that specifically highlights the individual benefits, rather than the community benefits of tidal energy. Additionally, savings in terms of costs, time, and efforts can be realized if the most influential members of the local community are targeted initially before including all other stakeholders. The study also indicated that locals absorb more information and increase their support for tidal energy when additional data is made available. Finally, as long-term strategy, information provision becomes most effective when the local population gains higher educational capabilities.

In the literature, researchers present construction projects as temporary self-organising coalition networks, composed of specialist entities that work towards set goals. The number of parties involved in the various processes during construction causes communications relations to be exceedingly complex and to change. The environment of a construction project is dynamic and complex, and self-organising communication networks are sensitive to institutional and social change. It becomes necessary to identify situations rooted in both insufficient communication during the carrying out of a project and its excess, which generates unnecessary cost. Effective control of information flow within self-organising communication networks through its planning and monitoring by project management can contribute to achieving project goals. This paper presents a proposal of an optimisation approach (in terms of minimising communication costs) to information flow planning that accounts for various constraints, on the example of a real-world case of building a housing complex in Poland.

Abstract Background The key challenge to constructing functional corticomuscular coupling (FCMC) is to accurately identify the direction and strength of the information flow between scalp electroencephalography (EEG) and surface electromyography (SEMG). Traditional TE and TDMI methods have difficulty in identifying the information interaction for short time series as they tend to rely on long and stable data, so we propose a time-delayed maximal information coefficient (TDMIC) method. With this method, we aim to investigate the directional specificity of bidirectional total and nonlinear information flow on FCMC, and to explore the neural mechanisms underlying motor dysfunction in stroke patients. Methods We introduced a time-delayed parameter in the maximal information coefficient to capture the direction of information interaction between two time series. We employed the linear and non-linear system model based on short data to verify the validity of our algorithm. We then used the TDMIC method to study the characteristics of total and nonlinear information flow in FCMC during a dorsiflexion task for healthy controls and stroke patients. Results The simulation results showed that the TDMIC method can better detect the direction of information interaction compared with TE and TDMI methods. For healthy controls, the beta band (14–30 Hz) had higher information flow in FCMC than the gamma band (31–45 Hz). Furthermore, the beta-band total and nonlinear information flow in the descending direction (EEG to EMG) was significantly higher than that in the ascending direction (EMG to EEG), whereas in the gamma band the ascending direction had significantly higher information flow than the descending direction. Additionally, we found that the strong bidirectional information flow mainly acted on Cz, C3, CP3, P3 and CPz. Compared to controls, both the beta-and gamma-band bidirectional total and nonlinear information flows of the stroke group were significantly weaker. There is no significant difference in the direction of beta- and gamma-band information flow in stroke group. Conclusions The proposed method could effectively identify the information interaction between short time series. According to our experiment, the beta band mainly passes downward motor control information while the gamma band features upward sensory feedback information delivery. Our observation demonstrate that the center and contralateral sensorimotor cortex play a major role in lower limb motor control. The study further demonstrates that brain damage caused by stroke disrupts the bidirectional information interaction between cortex and effector muscles in the sensorimotor system, leading to motor dysfunction.

Over the past decade, unmanned aerial vehicles (UAVs) have received increasing attention and are being used in the areas of harvesting, videotaping, and the military industry. In this article, the consideration is focused on areas where video recording is required for ground inspections. This paper describes modern communication technologies and systems that enable interaction and data exchange between UAVs and a ground control station (GCS). This article focuses on different architectures of communication systems, establishing the characteristics of each to identify the preferred architecture that does not require a significant consumption of resources and whose data transmission is reliable. A coherent architecture that includes multiple UAVs, wireless sensor networks, cellular networks, GCSs, and satellite network to duplicate communications for enhanced system security has been offered. Some reliability problems have been discussed, the solution of which was suggested to be a backup connection via satellite, i.e., a second connection. This study focused not only on the communication channels but also on the data exchanged between system components, indicating the purpose of their application. Some of the communication problems and shortcomings of various systems, as well as further focus areas and improvement recommendations were discussed.

The aim of this research is to test the volatility spillover between the stock values of the major liner shipping companies in the world and the freight indices measuring the freight revenues in the container market. The dataset in the study consists of 9 stock values of the top 10 biggest liner companies in 2018 and 3 container freight indices on weekly basis covering the period between 05.11.2010 and 06.07.2018. Volatility spillovers have been determined to some companies' stock values from some container freight indices, and the most influential freight index has been determined as New ConTex. Moreover, some volatility spillovers from some companies' stock values to freight indices have been also determined. These results suggest that some stock investors position their portfolios in the market according to the flow of information from freight indices while some investors position by following macro variables.

This paper revisits the empirical relationship between interest rates and money demand from a novel perspective, i.e., information theory. Particularly, we utilize the model-free transfer entropy to quantify the flow of information from interest rates to monetary aggregates and present three findings. First, we document a hump-shaped informational link between interest rate and M1 monetary aggregate, with a rounded high point in the late 1980s and early 1990s. Second, we identify three structural shifts in the information transmission from interest rate to M1. The first two breakpoints occurred in the early 1980s and mid-1990s, likely as a response to the removal of Regulation Q and the introduction of sweep technology, respectively. The third shift took place during the relatively less-explored period of the early 2000s. Finally, we unravel a previously unreported pivotal distinction between the first two changepoints despite the apparent similarity in inducing money demand instability: the 1980s financial deregulations facilitate the transmission of information, whereas the 1990s financial reforms acted as an impediment to the information flow. Our results are robust to alternative entropy measures. [ABSTRACT FROM AUTHOR]

With the increasingly close coupling between the cyber system and the physical system, cyber attacks have a significant impact on the physical system by attacking the cyber system. As a cyber–physical system with multiple energy sources, integrated energy cyber–physical system (IECPS) is facing the risk of cyber attacks. However, the research on IECPS is still in the direction of operation optimization at the physical level, which cannot meet the requirements of system security and stability analysis under cyber cooperative attacks. Firstly, this paper analyzes the interaction mechanism between the energy network composed of electricity, heat and gas and the cyber network in IECPS, and put forward a layered modeling method of IECPS to analyze the influence of abnormal information flow caused by cyber attacks on energy flow. Secondly, based on the energy circuit method (ECM), a hybrid calculation method of IECPS energy-information flow is proposed to solve the model. Then, the load shedding state of IECPS and the tampering process of system control commands after the fake data injection attack are analyzed by using the proposed calculation method. Finally, the simulation analysis is carried out in an integrated energy system composed of IEEE 39-node power grid, 6-node heating network and 7-node gas network. The results show that, compared with the traditional Newton–Raphson method, the proposed IECPS hybrid calculation method can better obtain the change results of energy flow in the steady-state scenario and the cyber cooperative attack scenario, and identify the high-risk branches in the system, which is of great significance to the safe and stable operation of the energy system. [Display omitted] • This article divides IECPS into energy layer, transmission layer and information layer, and the layered fusion model of IECPS is established based on the energy circuit method and information channel model. • The hybrid energy-information flow calculation method of IECPS is proposed to realize the hybrid solution of energy flow and information flow in the fusion model of IECPS, and be compared with the traditional Newton–Raphson method to verify the superiority of the method. • The cyber–physical collaborative attack scenario is established to analyze the process of system control instruction tampering under FDI attack and the result of IECPS energy flow changes, and identify the high-risk branches of the system based on the proposed calculation method. [ABSTRACT FROM AUTHOR]

Information flow within urban networks profoundly affects production modes and the structure of urban agglomeration economic systems. Drawing on the panel smooth transition regression (PSTR) model and the mediating effect model, this study examined the effects of information flow on agglomeration externalities, with considerations on non-linear effects, proximity mechanisms, and industrial heterogeneity. The resulting findings revealed that the ability to control information at the city node level exhibited a significant non-linear relationship with the agglomeration externalities of the manufacturing, producer, and consumer services industries. Furthermore, the ability to exchange information promoted the agglomeration externalities of producer and public services, albeit only under specific intensity conditions. The proximity mechanisms demonstrated significant mediating effects at the city connection level. This study highlights the infrastructure-like nature of information flow networks and underscores the unique role of network externalities in reshaping agglomeration externalities. These findings offer insights for governments to improve regional planning and leverage virtual urban networks effectively. • Information flow has reshaped the agglomeration economic system of cities. • Information management is an effective tool for regulating non-geographical proximity. • Coordinating urban information resources and industrial development from an urban network perspective is preferable. • Recommendations are provided for managing information resources to enhance beneficial agglomeration externalities. [ABSTRACT FROM AUTHOR]

This study aims to prepare for the development of an asset information model to increase traceability in offshore wind projects. The goal of the information modelling framework is to increase information flow between projects as well as the quality of the project delivery. Literature review describes traceability in a wide variety of cases and industries, and points to both challenges and benefits with the definition and implementation of traceability practices. However, a successfully maintained asset information model can help engineers make quick and well‐designed development decisions and solutions. The development of an asset information model shall contribute to an accelerated design process with higher accuracy and less deviations. Being able to create a product that answers the relevant stakeholders' expectations in a more accurate and efficient way can give the company a valuable advantage in a competitive market. Furthermore, a research design has been defined to form the basis for further research in the spring 2022 semester. [ABSTRACT FROM AUTHOR]

With the rise of the fifth-generation communication technology and the advent of the smart media era, the main front for international communication has shifted from traditional media to the Internet. Statistics show that China has the largest number of Internet users in the world, but the amount of information traffic on the Internet in Chinese is relatively small, and the gap with the amount of information traffic in English is particularly wide. The history of the development of the Internet in China is reviewed and divided into four eras, namely the Internet information traffic 1.0 era (1987-2001), the Internet information traffic 2.0 era (2001-2008), the Internet information traffic 3.0 era (2008-2017), and the new era of Internet information traffic (2017-present). The reasons for the lack of Chinese information flow in different eras include the pivotal position of English in the global language network, the Matthew effect formed by Internet giants, the high threshold and cost for individuals to build independent websites, and the decline of traditional websites in the era of mobile Internet, etc. It is thus recommended to soundly build an international communication system for all media, increase support for Internet enterprises going abroad, focus on the young generation abroad, cultivate key opinion leaders, and vigorously strengthen international Chinese education. [ABSTRACT FROM AUTHOR]

In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their group. Ant colonies display high levels of organizational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g. physiology), or at the group level (e.g. the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published data set (Mersch et al., 2013, Science, 340 (6136), 1090–1093) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individual's task – foraging, cleaning or nursing – and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of 'effective information'. Our results show that interaction history is tied to task allocation: ants that switched to a task were more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we found that colony cohesion was stable even as ant level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows. • We analysed the interaction networks of six C. fellah colonies. • We tested how centrality and information flow are tied to task switching. • Node metrics and effective information explained functional group differences. • Interactions were correlated with task switching. • The strength of this correlation, however, differed across functional groups. [ABSTRACT FROM AUTHOR]

Employees are critical stakeholders for an organization because they directly deal with the end-users and represent the entire firm. To recognize the strategic importance of the employees, organizations create communication programs to keep employees apprised of organizational issues. In this regard, this study examined the role of communication strategies (i.e., information flow, information adequacy, and information feedback) on organizational commitment. The study also investigated the mediating effect of faculty engagement between communication strategies and organizational commitment. Self-administered survey aided in acquiring data from276 English language teachers in China. The analysis of the data was conducted using SmartPLS through the Structured Equation Modeling technique. The outcome of the study demonstrated that information flow and information feedback significantly impact organizational commitment and faculty engagement. The analysis also revealed that information adequacy significantly impacts organizational commitment but has no relationship with faculty engagement. The mediation analysis demonstrated that faculty engagement mediated the relationship between information flow and organizational commitment and between information feedback and organization commitment. However, faculty engagement did not mediate the relationship between information adequacy and organizational commitment among English language teachers in China. In theoretical terms, the study contributed in terms of incorporating different communication strategies and examining their effect on organizational commitment and faculty engagement. In practical terms, this study would be beneficial for the management of the educational institutes to develop different ways of enhancing communication strategies within the institute. This study also provided directions for the future, for example, conducting the study on other subject teachers, increasing the sample, carrying out the research in a different context, and adding different mediators and moderators in the existing model. [ABSTRACT FROM AUTHOR]

Social networks are critical to the success of behavioral interventions in conservation because network processes such as information flows and social influence can enable behavior change to spread beyond a targeted group. We investigated these mechanisms in the context of a social marketing campaign to promote a wildlife poisoning hotline in Cambodia. With questionnaire surveys we measured a social network and knowledge and constructs from the theory of planned behavior at 3 points over 6 months. The intervention initially targeted ∼11% (of 365) of the village, but after 6 months ∼40% of the population was knowledgeable about the campaign. The likelihood of being knowledgeable nearly doubled with each additional knowledgeable household member. In the short term, there was also a modest, but widespread improvement in proconservation behavioral intentions, but this did not persist after 6 months. Estimates from stochastic actor‐oriented models suggested that the influences of social peers, rather than knowledge, were driving changes in intention and contributed to the failure to change behavioral intention in the long term, despite lasting changes in attitudes and perceived norms. Our results point to the importance of accounting for the interaction between networks and behavior when designing conservation interventions. [ABSTRACT FROM AUTHOR]

Plants and microorganisms sense and respond to biotic and abiotic signals in the environment to competitively optimize their fitness. These specific adjustments which are pertinent to prevailing environmental conditions bring about distinct signal-induced behavioural responses that appear intelligent. A suite of cellular and molecular networks underlie the generation of such attributes in plants and microorganisms. Recent advances in systems biology have gained insights from these biomolecular networks in fabricating biomimetic signaling circuits. Detailed interpretations, however, reveal the behavioural responses to be a conditioned alertness as a result of prudent signal perception. The review, therefore, examines the concept of 'intelligence' in the plant and microbial world and tries to ascertain whether their interactive responses are an outcome of pure intelligence or sheer response. [ABSTRACT FROM AUTHOR]

This paper presents the generalized information system theory, which is enlarged into pure quantum systems using wave probability functions. The novelty of this approach is based on analogies with electrical circuits and quantum physics. Information power was chosen as the relevant parameter, which guarantees the balance of both components—information flow and information content. Next, the principles of quantum resonance between individual information components, which can lead to emergent behavior, are analyzed. For such a system, adding more and more probabilistic information elements can lead to better convergence of the whole to the resulting trajectory due to phase parameters. The paper also offers an original interpretation of information "source–recipient" or "resource–demand" models, including not yet implemented "unused resources" and "unmet demands". Finally, possible applications of these principles are shown in several examples from the quantum gyrator to the hypothetical possibility of explaining some properties of the consciousness. [ABSTRACT FROM AUTHOR]

INCOM Egypt has undergone automation in some processes where critical aspects of its operations are transformed and automated. This paper presents an overview of INCOM Egypt processes using Ould Riva and analyses the process of 'handling a product'. It aims to demonstrate effective automation of the production of wires and cables process accompanied to Industry 4.0 while considering environmental and economic sustainability goals that were inhibited by COVID-19 restrictions. Ould's Riva method is used to analyse the production process of wires and cables to propose improvements for automating the process. Business process modelling is utilised to study the processes for clearer understating. The flow of information within the process is also analysed to integrate the production process with other processes and supply chains, which helps to identify which production activities can be automated and mainstreamed into the information flow to achieve environmental and economic sustainability. The context of INCOM Egypt, as a case study, is presented along with the Riva model of its operations. The paper identifies the before, i.e., As-Is process, and after, i.e., To-Be Process, automation of the 'handle a product' process using the Role Activity Diagram (RAD). The process involved redesigning and improving different activities to increase resource-use efficiency to participate in achieving the goals of sustainability. The focus of this paper is to investigate the negative impact of COVID-19 on sustainability and to examine the accomplishments of process automation of wire production towards environmental and economic sustainability. The results of the research reveal a relationship between business process modelling and sustainability. Moreover, automation of processes (Industry 4.0) is found to reduce the negative effect of COVID-19 on production. A triangulation between process modelling, process automation (Industry 4.0), and sustainability was determined. Each one is reinforcing and impacting one another. The RAD model demonstrates that automation of the activities in the process reduces waste, time, cost, and redundant processes as factors of sustainability, which may also help to lessen the unfavorable effects of the pandemic. The results proved generalisation on other organisations in the same line of business. [ABSTRACT FROM AUTHOR]

Institutional linkages and information flow between agricultural organizations play a critical role in addressing sustainability issues and promoting agrarian innovation. The aim of this study was to evaluate institutional relations and information between the various actors within the agricultural knowledge and information system (AKIS). The study focused on eight actors within the AKIS in Dakahlia governorate of Egypt, namely policy, extension, research, agricultural cooperatives, higher education, secondary education, credit, and the private sector. Thus, the survey sample included 11 representatives of each actor with 88 respondents. Data were collected by a standardized questionnaire distributed online. The graph theoretical technique was used for the quantitative assessment of information flow and institutional linkages established among actors. The findings indicated that agricultural extension ranked first about their real cause and effect on the rest of the system, having a value of 7.95. Two critical information pathways within the AKIS sustained innovation outcomes: (1) higher education–extension–agricultural cooperatives, (2) research–extension–agricultural cooperatives. The results also revealed that agricultural cooperatives ranked second after the extension component on the extent of supplying information to other members in the AKIS, with a value of 4.8. In contrast, the highest component received information from other components (7.6). By analyzing institutional linkages and information flow, this article gives insights to policymakers on the mechanisms that still need to be strengthened and the information gaps between actors to address the challenges of sustainable rural development. [ABSTRACT FROM AUTHOR]

Maritime supply chain (MarSC) stakeholders interact with third parties (e.g. freight forwarders, 3PLs, financial institutes, custom authorities) to facilitate the cargo flow and exchange of information, documents, or financials. Hence, MarSC stakeholders are increasingly interested in innovative technological solutions that vouch for the authenticity and/or the ownership of digital assets without the control of a central third party. Extended research is carried out to prove how applications based on the distributed ledger technology or blockchain address these requirements, yet limited research investigates their purchasing process and economic implications. This paper uses the phytosanitary certificate in an international supply chain flow as a case study where interaction between multiple stakeholders is fundamental and analyses the purchase scenarios of a blockchain-based tool. To do so, it uses a theoretical model that identifies and quantifies the costs and benefits incurred by MarSC stakeholders, formulates gain-sharing scenarios and presents the results of a sensitivity analysis to show the dependence between the data-use and the potential economic gains it generates. The results show that freight forwarders could share economic benefits with shippers or consignees to anticipate purchasing a blockchain-based tool. [ABSTRACT FROM AUTHOR]

Analysis of causality and information flow between time series in different fields is an important research topic in the literature and different causality tests have been proposed. The most widely used of these are the Granger, Toda-Yamamoto, and Hatemi-J causality tests. Although these tests reveal whether there is causality between time series and the direction of this causality, they do not measure the degree of causality. Transfer entropy is a new information theory-based method and a non-parametric method that can be used to measure causality and information flow between time series, and it can detect asymmetric and nonlinear information flow between two time series. In this study, the causality and information flow between the BIST100 index and the exchange rate of dollar were analyzed using transfer entropy, and the sliding window method was used to reveal how the information flow changed over time. In order to demonstrate the robustness of the results, the results obtained from three different sized time windows are presented. [ABSTRACT FROM AUTHOR]

Neural activity emerges and propagates swiftly between brain areas. Investigation of these transient large-scale flows requires sophisticated statistical models. We present a method for assessing the statistical confidence of event-related neural propagation. Furthermore, we propose a criterion for statistical model selection, based on both goodness of fit and width of confidence intervals. We show that event-related causality (ERC) with two-dimensional (2D) moving average, is an efficient estimator of task-related neural propagation and that it can be used to determine how different cognitive task demands affect the strength and directionality of neural propagation across human cortical networks. Using electrodes surgically implanted on the surface of the brain for clinical testing prior to epilepsy surgery, we recorded electrocorticographic (ECoG) signals as subjects performed three naming tasks: naming of ambiguous and unambiguous visual objects, and as a contrast, naming to auditory description. ERC revealed robust and statistically significant patterns of high gamma activity propagation, consistent with models of visually and auditorily cued word production. Interestingly, ambiguous visual stimuli elicited more robust propagation from visual to auditory cortices relative to unambiguous stimuli, whereas naming to auditory description elicited propagation in the opposite direction, consistent with recruitment of modalities other than those of the stimulus during object recognition and naming. The new method introduced here is uniquely suitable to both research and clinical applications and can be used to estimate the statistical significance of neural propagation for both cognitive neuroscientific studies and functional brain mapping prior to resective surgery for epilepsy and brain tumors. • 2D moving average provides an efficient smoothing estimator for statistical testing. • The technique has broad applicability to 2D planes of large dimensions. • New criterion for statistical model selection is proposed. • Event-related causality reveals brain interactions consistent with speech models. • The method is uniquely suitable to research and clinical applications. [ABSTRACT FROM AUTHOR]

The increasing prevalence of large-scale data collection in modern society represents a potential threat to individual privacy. Addressing this threat, for example through privacy-enhancing technologies (PETs), requires a rigorous definition of what exactly is being protected, that is, of privacy itself. In this work, we formulate an axiomatic definition of privacy based on quantifiable and irreducible information flows. Our definition synthesizes prior work from the domain of social science with a contemporary understanding of PETs such as differential privacy (DP). Our work highlights the fact that the inevitable difficulties of protecting privacy in practice are fundamentally information-theoretic. Moreover, it enables quantitative reasoning about PETs based on what they are protecting, thus fostering objective policy discourse about their societal implementation. [ABSTRACT FROM AUTHOR]

Panel data, which consist of observations on many individual units over two or more instances of time, have gradually become an important type of scientific data. Subsequently causal inference for panel data has attracted enormous interest from many fields as well as statistics. In this study, the rigorously formulated information flow analysis for time series, which is very concise in form and has been successfully applied in different disciplines, is generalized to identify the causality from homogeneous and independent identically distributed panel data. The resulting formula bears the same form as that for the former, though the meanings of the symbols differ. An algorithm is then proposed for panel data causality analysis, which has been validated with both linear and nonlinear problems. It has also been put to application to examine the causal relations among economic growth, energy consumption, trade openness, and energy price based on 15 Asian countries. Clearly identified are a strong bidirectional causality between economic growth and energy consumption, and a strong causality from import and export trade to economic growth. Energy price has no direct impact on energy consumption; it, instead, exerts a weak effect on the latter through influencing economic growth.