Measure Of Interdependence Research Articles

Mutual information between Polish subindexes – the use of copula entropy around the time of the COVID-19 pandemic

In this paper, the copula theory is used to describe the dependence structure between variables, while the information theory provides the tools necessary to measure the uncertainty associated with these variables. What both theories have in common is copula entropy, which is strictly related to mutual information. The findings of this study, focusing on the dependence of the (sub)indexes of the Polish stock market during the pandemic period, may prove useful not only to investors from Poland, but also from other countries, especially Central European, in making investment decisions. The results of calculating the interdependencies between WIG, sectoral indexes and among sectoral indexes of the Polish economy using copula entropy and Pearson’s correlation are quite different. The source of the basic difference between copula entropy and Pearson’s correlation is that the former enables the measurement of nonlinear interdependencies, while the latter not. The interrelations on the stock markets are nonlinear and returns are not normally distributed in general. The use of copulas is also superior in terms of ranking correlation, as it is more general and allows the examination of the structure of dependencies between extreme values.

Technologische Souveränität: Begriff und Voraussetzungen im transatlantischen Kontext

Abstract In uncertain geopolitical times, demand is high for political concepts to grasp the unfolding change and give direction. To Europeans and Germans, the presidency of Donald Trump, the Covid-19 pandemic and the Russian war of aggression in Ukraine have all demonstrated how dependent they are from other states and regions in the world. This is particularly true for technology in sectors such as health, energy, defense and digital. In order to reduce these dependencies,”technological sovereignty“ has become a key concept - some say a buzz word - in the political debate in Europe. In this article, we analyse prominent views of technological sovereignty particularly in Germany, and suggest a definition and three-pronged analysis framework to understand the key political challenges in implementing the concept. In today‘s highly connected world order, there is no sovereignty without a measure of interdependence. For Germany and Europe, this translates into a “transatlantic sovereignty“ in close alignment with the USA as a principal partner.

Involvement of Local Authorities in the Protection of Residents’ Health in the Light of the Smart City Concept on the Example of Polish Cities

According to the modern guidelines of the Smart City (SC) concept, smart cities are not only cities that are above average in terms of technology, but first and foremost are focused on the needs of their residents. A key need for quality of life is taking care of health, including education, prevention, and access to medical infrastructure. In the context of the given circumstances, this article seeks to answer the following research question: What is the level of involvement of local authorities in protecting the health of residents in Polish cities in the context of the Smart City concept? The involvement of local authorities in healthcare is considered in five aspects: (1) monitoring of residents’ health needs; (2) health education; (3) preventive healthcare; (4) healthcare infrastructure; and (5) environment and recreation. To obtain answers to the above research problem, surveys were conducted at the local government level in 399 Polish cities. The research utilized statistical measures of central tendency, indices of variation, and measures of interdependence. The results allow formulating the following key conclusions: (1) most of the surveyed cities do not monitor the health needs of their residents, contrary to the recommendations of the SC concept; (2) cities take measures to protect the health of their residents, but these are focused on sports and recreation; (3) the most neglected health areas are health education and environmental and climate protection. The level of involvement of the city authorities in protecting the health of residents is therefore quite low and is mainly image-related. The lack of monitoring of the expectations of the local community has a negative impact on the effectiveness of healthcare activities and the real improvement in the quality of urban life. Meanwhile, according to research results, cooperation with residents and care for meeting their needs is an important determinant of the effectiveness of healthcare. Given the above conditions, it is difficult to be effective both in terms of improving the quality of life of residents and developing fully sustainable smart cities. The research also shows that the involvement of the city authorities in holistic pro-health activities increases with the size of the city, which means that larger entities are more aware of cooperation with stakeholders and the importance of health for quality of life. Therefore, they are better prepared to implement the assumptions of the Smart City concept. The originality and scientific value of the conducted analysis will help fill the research gap in identifying the health determinants of Smart City development and assessing the involvement of city authorities in protecting the health of residents in a multifaceted perspective.

Associations between teamwork and implementation outcomes in multidisciplinary cross-sector teams implementing a mental health screening and referral protocol

PurposeTeams play a central role in the implementation of new practices in settings providing team-based care. However, the implementation science literature has paid little attention to potentially important team-level constructs. Aspects of teamwork, including team interdependence, team functioning, and team performance, may affect implementation processes and outcomes. This cross-sectional study tests associations between teamwork and implementation antecedents and outcomes in a statewide initiative to implement a standardized mental health screening/referral protocol in Child Advocacy Centers (CACs).MethodsMultidisciplinary team members (N = 433) from 21 CACs completed measures of team interdependence; affective, behavioral, and cognitive team functioning; and team performance. Team members also rated the acceptability, appropriateness, and feasibility of the screening/referral protocol and implementation climate. The implementation outcomes of days to adoption and reach were independently assessed with administrative data. Associations between team constructs and implementation antecedents and outcomes were tested with linear mixed models and regression analyses.ResultsTeam task interdependence was positively associated with implementation climate and reach, and outcome interdependence was negatively correlated with days to adoption. Task and outcome interdependence were not associated with acceptability, appropriateness, or feasibility of the screening/referral protocol. Affective team functioning (i.e., greater liking, trust, and respect) was associated with greater acceptability, appropriateness, and feasibility. Behavioral and cognitive team functioning were not associated with any implementation outcomes in multivariable models. Team performance was positively associated with acceptability, appropriateness, feasibility, and implementation climate; performance was not associated with days to adoption or reach.ConclusionsWe found associations of team interdependence, functioning, and performance with both individual- and center-level implementation outcomes. Implementation strategies targeting teamwork, especially task interdependence, affective functioning, and performance, may contribute to improving implementation outcomes in team-based service settings.

РИНОК РЕКРУТИНГОВИХ ПОСЛУГ В УКРАЇНІ: СУЧАСНІ ТЕНДЕНЦІЇ ТА ПЕРСПЕКТИВИ РОЗВИТКУ

The article examines current trends, outlines prospects, and identifies prerequisites for the development of the recruiting services market in Ukraine. A detailed study of the essence of the «recruiting» category was conducted. It is noted that recruiting should be understood as a purposeful, coordinated process, which involves the implementation of a complex of interdependent measures of an organizational, economic, managerial and other nature, aimed at filling a vacant position (positions) by recruiting, selecting and attracting the candidate (candidates) that best fits (correspond) to pre-determined criteria based on the set of necessary professional qualifications and personal characteristics. The content of the main recruiting services was studied and the specific features of their provision were determined. It has been established that recruiting is an important element of the labor market infrastructure, the task of which is to promote employment, strengthen professional orientation, training and retraining of personnel, due to its resistance to socio-economic changes and the existing powerful potential for development both in times of economic growth and in periods of crisis. It was noted that there is still no consensus among specialists regarding the expediency of using external recruiting. Certain representatives of the scientific community believe that the activity of recruiting agencies leads to an increase in unemployment, negatively affects the level of competence of employees and contributes to the deterioration of the interaction between the employee and the employer. Others hold the point of view that recruiting agencies contribute to the establishment of a civilized relationship between the manager and the employee, noting that thanks to recruiting employees get better prospects in finding high-paying work and building a successful career. The basic factors influencing the functioning of the recruiting services market have been identified. A comparison of the advantages and disadvantages of the main types of recruiting was made. Modern trends are established and prerequisites for the development of the recruiting services market in Ukraine are outlined. Prospective directions were identified and reserves for improving the efficiency of recruiting activities were identified. It has been proven that the relevance and demand of recruiting for the modern world will continue to grow, since the successful development of the entire organization directly depends on well-chosen employees.

When is caring sharing? Primary care provider interdependence and continuity of care.

Efforts to improve access to high-quality, efficient primary care have highlighted the need for team-based care. Most primary care teams are designed to maintain continuity of care between patients and primary care providers (PCPs), because continuity of care can improve some patient outcomes. However, PCPs are interdependent because they care for, or share, patients. PCP interdependence, and its association with continuity of care, is not well described. This study describes a measure of PCP interdependence. We also evaluate the association between patient and panel characteristics, including PCP interdependence. Our results found that the extent of interdependence between PCPs in the same clinic varies widely. A range of patient and panel characteristics affect continuity of care, including patient complexity and PCP interdependence. These results suggest that continuity of care for complex patients is sensitive to panel characteristics, including PCP interdependence and panel size. This information can be used by primary care organizations for evidence-based team design.

Analysis of microarray data by genetic algorithm

Microarray gene expression data is used to understand the actions of thousands of genes. Just a few genes out of thousands have a significant impact in any cancer process. Finding these defective genes using experimental data is impractical. To locate the relevant genes, computational techniques are required. A method to identifying cancer candidate genes from microarray data is created. Clustering of similar genes is necessary to find co-expressed genes in different biological conditions. It is important to develop methods to find the few candidate genes for cancer. An optimization process is used for such purpose. A genetic algorithm employs the principles of evolution: selection, recombination, and mutation to solve an optimization problem. Mutual information is used to find the dependency between genes. The two genes are similar if their expression levels are comparable. The similarity as well as positive and negative correlations between genes is considered while clustering them. Interdependence measure tells how the genes are correlated. The genes responsible for a sick state have higher interdependence measures. These genes are defective genes having cancer diagnostic information. Here microarray gene expression datasets from gastric cancer and colon cancer from the public domain are considered.

Spatial interdependence and spillovers of fiscal grants in Benin: Static and dynamic diffusions

This paper investigates the spatial diffusion of an intergovernmental grant in Benin. Using static and dynamic spatial models, we estimate the spillover effects of the Fonds d’Appui au Développement des Communes (FADeC) on per capita local government expenditure in the 77 municipalities from 2008 to 2015. Neighborliness – a measure of interdependence – is captured through geographic and distance-based spatial weighting schemes. In addition, we constructed a measurement of ethnic affinity as an alternative spatial weighting scheme to test for the existence of an ethno-spatial interdependence in local public finance in Benin. The empirical results suggest that a statistically significant share of the total effects of the FADeC stems from indirect elasticities or the diffusion process of grants received by neighboring jurisdictions, regardless of how we measure neighborliness. The results also confirm the existence of a robust ethno-spatial interdependence and complementarity in local government expenditure in Benin. The spillovers across ethnic neighbors are estimated to be 13.9% of the total effects in the short-run and 15.5% in the long-run. Put differently, the effects of the FADeC in a given municipality are influenced by the transfers received by its ethnic (and linguistic) neighbors. The findings point to the appeal of inter-governmental transfers for the decentralized financing of public services, especially in low-income countries where local bureaucratic capacity in raising own-source revenues might be limited. Supporting local governments with well-structured grants can not only be a channel to foster local public provision but also contribute to pushing geographic or ethnic neighboring localities to increase their own spending and generate positive spillovers that are crucial for wholistic regional development.

Survival analysis of pathway activity as a prognostic determinant in breast cancer.

High throughput biology enables the measurements of relative concentrations of thousands of biomolecules from e.g. tissue samples. The process leaves the investigator with the problem of how to best interpret the potentially large number of differences between samples. Many activities in a cell depend on ordered reactions involving multiple biomolecules, often referred to as pathways. It hence makes sense to study differences between samples in terms of altered pathway activity, using so-called pathway analysis. Traditional pathway analysis gives significance to differences in the pathway components' concentrations between sample groups, however, less frequently used methods for estimating individual samples' pathway activities have been suggested. Here we demonstrate that such a method can be used for pathway-based survival analysis. Specifically, we investigate the pathway activities' association with patients' survival time based on the transcription profiles of the METABRIC dataset. Our implementation shows that pathway activities are better prognostic markers for survival time in METABRIC than the individual transcripts. We also demonstrate that we can regress out the effect of individual pathways on other pathways, which allows us to estimate the other pathways' residual pathway activity on survival. Furthermore, we illustrate how one can visualize the often interdependent measures over hierarchical pathway databases using sunburst plots.

Identification of Key Sectors in Nigeria – Evidence of Backward and Forward Linkages from Input-Output Analysis

The input-output table provides summary information on the industrial structure of an economy in a specific period. This table contains information on the flow of goods and services between industries and economic sectors. The backward and forward links are descriptive measures of the economic interdependence of sectors in terms of the volume of transactions. Sectors with strong backwards and forward linkages are vital sectors and play an essential role in a country’s development strategy. This paper aims to construct a symmetric input-output table for Nigeria and examine the Nigerian economy’s production structure by using the results applying traditional backward and forward linkage methods developed by Chenery-Watanabe and Rasmussen. Our study identifies the key sectors with backward and forward linkages as Crop and Animal production, Manufacture of Food products, Textiles, Refined petroleum products, Chemicals, Motor vehicles, Furniture, Machinery and equipment, Wholesale/retail trade, Land transport and Telecommunication. In addition, through the constructed symmetric input-output table, sector development can be further done in line with the relationship matrix, as it serves as a conduit for investment strategy, local linkage matrix and policy development. So, for the development strategy it is very important to determine which industries possess high backward and forward linkages, then stimulating final demand or primary inputs namely of these industries could positively influence the economic activity of the country. The results from this work may be used by policy makers in terms of which sectors of the economy stimulate (for example, by means of creating extra final demand, decreasing taxes, or with the help of subsiding) in order to gain better results in the sphere of economic development of Nigeria.

Methodological and Practical Issues of the Organization of the Personnel of the Enterprise and the Implementation of Changes to its Structure

The article is devoted to the study of methodological features and substantiation of practical measures in the organization of the enterprise personnel system and the introduction of changes in its structure. It is proved that personnel management is a system of interdependent, organizational, economic and social measures aimed at implementing the conditions of normal functioning, development and effective use of labour potential at the enterprise level. Emphasis is placed on the fact that the active development of the labour market and related processes of economic relations have given rise to new theoretical ideas about the organization of personnel management, a critical understanding of this problem requires adequate approaches to solving the problems of labour management. The main goal of personnel management is highlighted, which is to effectively combine staff training, training and motivation to perform work with a more complex level. The authors, on the basis of general approaches, have developed a methodology for improving the structure of personnel in order to increase the efficiency of the enterprise. It is established that the personnel management system at the enterprise should provide the optimal balance of the processes of arrival and dismissal of employees, i.e. updating the number of staff; development of high-quality staff in accordance with the needs of the enterprise. It is revealed that the practical implementation of personnel strategy at the enterprise is carried out by the systematic use of means of implementation, and the means in turn involve ways and methods of action. As a result of elaboration of ways and means to achieve the strategic goal, the formation of personnel strategy is possible under the conditions of assessment of opportunities and threats of the external environment. Enterprises should create such a system of protection so that in the face of risk factors, it can improve its competitive position in relation to other enterprises that do not have such a system.

A nonparametric algorithm for estimating mutual information between digital signals

Recently it has been mathematically proved that any digital signal can be expressed as a string 13 3-point motifs and information in the signal is encoded in terms of those motifs. This result has several important applications in statistical signal processing, such as entropy estimation, transfer entropy, data mining, etc. In the current work we have shown an application in estimation of mutual information (MI) across any number of signals. MI is an important measure of interdependence among the signals with wide applications. However, estimating the MI between two signals as random variables, whose probability distributions are not known, is quite challenging. Here we propose a nonparametric, real time method to estimate MI between two signals and then generalize it to any number of signals. This has been done in terms of motifs. On simulated data, in which MI can be controlled, it performed at par with k nearest neighbor (kNN) based method and the permutation motif based method, but much faster and memory efficient. On real data with added noise and varying signal to noise ratio (SNR) the proposed method worked at par with the other two methods. A novel hypothesis testing method has also been introduced for comparing performances.

Holding Up a Mirror to the World Trade Organization: Lessons from the COVID-19 Pandemic

Holding Up a Mirror to the World Trade Organization: Lessons from the COVID-19 Pandemic

A scoping review of approaches for measuring 'interdependent' collaborative performances.

Individual assessment disregards the team aspect of clinical work. Team assessment collapses the individual into the group. Neither is sufficient for medical education, where measures need to attend to the individual while also accounting for interactions with others. Valid and reliable measures of interdependence are critical within medical education given the collaborative manner in which patient care is provided. Medical education currently lacks a consistent approach to measuring the performance between individuals working together as part of larger healthcare team. This review's objective was to identify existing approaches to measuring this interdependence. Following Arksey & O'Malley's methodology, we conducted a scoping review in 2018 and updated it to 2020. A search strategy involving five databases located >12000 citations. At least two reviewers independently screened titles and abstracts, screened full texts (n=161) and performed data extraction on twenty-seven included articles. Interviews were also conducted with key informants to check if any literature was missing and assess that our interpretations made sense. Eighteen of the twenty-seven articles were empirical; nine conceptual with an empirical illustration. Eighteen were quantitative; nine used mixed methods. The articles spanned five disciplines and various application contexts, from online learning to sports performance. Only two of the included articles were from the field of Medical Education. The articles conceptualised interdependence of a group, using theoretical constructs such as collaboration synergy; of a network, using constructs such as degree centrality; and of a dyad, using constructs such as synchrony. Both descriptive (eg social network analysis) and inferential (eg multi-level modelling) approaches were described. Efforts to measure interdependence are scarce and scattered across disciplines. Multiple theoretical concepts and inconsistent terminology may be limiting programmatic work. This review motivates the need for further study of measurement techniques, particularly those combining multiple approaches, to capture interdependence in medical education.

Measuring Dynamical Interdependence in Small-Group Collaborations

This paper addresses dynamical interdependence among the actions of group members. I assume that the actions of each member can be represented as nodes of a dynamical network and then collect the nodes into disjoint subsets (components) representing the individual group members. Interdependence among group members’ actions can then be defined with reference to a K-partite network, in which the partitions correspond to the group member components. Independence among group members’ actions can be defined with reference to a network in which the group member components are disconnected from one another. The degree to which the interactions of actual groups correspond to either of these theoretical network structures can be characterized using modified versions of existing network statistics. Taking this approach, I propose a number of network-based measures of dynamical interdependence, discuss the interpretation of the proposed measures, and consider how to assess their reliability and validity. These ideas are illustrated using an example in which dyads collaborated via online chat to complete a grade 12 level mathematics assessment.

Evaluating demand forecasting models using multi-criteria decision-making approach

PurposeDemand forecasting models in companies are often a mix of quantitative models and qualitative methods. As there are so many existing forecasting approaches, many forecasters have difficulty in deciding on which model to select as they may perform “best” in a specific error measure, and not in another. Currently, there is no approach that evaluates different model classes and several interdependent error measures simultaneously, making forecasting model selection particularly difficult when error measures yield conflicting results.Design/methodology/approachThis paper proposes a novel procedure of multi-criteria evaluation of demand forecasting models, simultaneously considering several error measures and their interdependencies based on a two-stage multi-criteria decision-making approach. Analytical Network Process combined with the Technique for Order of Preference by Similarity to Ideal Solution (ANP-TOPSIS) is developed, evaluated and validated through an implementation case of a plastic bag manufacturer.FindingsThe results show that the approach identifies the best forecasting model when considering many error measures, even in the presence of conflicting error measures. Furthermore, considering the interdependence between error measures is essential to determine their relative importance for the final ranking calculation.Originality/valueThe paper's contribution is a novel multi-criteria approach to evaluate multiclass demand forecasting models and select the best model, considering several interdependent error measures simultaneously, which is lacking in the literature. The work helps structuring decision making in forecasting and avoiding the selection of inappropriate or “worse” forecasting model.

Scale-Free Coupled Dynamics in Brain Networks Captured by Bivariate Focus-Based Multifractal Analysis.

While most connectivity studies investigate functional connectivity (FC) in a scale-dependent manner, coupled neural processes may also exhibit broadband dynamics, manifesting as power-law scaling of their measures of interdependence. Here we introduce the bivariate focus-based multifractal (BFMF) analysis as a robust tool for capturing such scale-free relations and use resting-state electroencephalography (EEG) recordings of 12 subjects to demonstrate its performance in reconstructing physiological networks. BFMF was employed to characterize broadband FC between 62 cortical regions in a pairwise manner, with all investigated connections being tested for true bivariate multifractality. EEG channels were also grouped to represent the activity of six resting-state networks (RSNs) in the brain, thus allowing for the analysis of within- and between- RSNs connectivity, separately. Most connections featured true bivariate multifractality, which could be attributed to the genuine scale-free coupling of neural dynamics. Bivariate multifractality showed a characteristic topology over the cortex that was highly concordant among subjects. Long-term autocorrelation was higher in within-RSNs, while the degree of multifractality was generally found stronger in between-RSNs connections. These results offer statistical evidence of the bivariate multifractal nature of functional coupling in the brain and validate BFMF as a robust method to capture such scale-independent coupled dynamics.

Analysis of Resilience Under Repair Strategy in Interdependent Mechatronic System

Existing works on the interdependent system have come to fruition based on the percolation theory and revealed that it possesses the great vulnerability due to the essential interdependency. However, how to effectively recover the performance of the interdependent system after cascading failures is still under research. In this article, we define an interdependent mechatronic system as an interdependent machine-electricity-communication network. By considering the behavior of the real-world system, we put forward an extended cascading failure model in which the non-giant component is also functional when its size proportion is not smaller than the proportion threshold $\delta $ and it has the interdependent links from the other two subnetworks. Then, according to the measures of a node (i.e., single measures), the interdependent measures are proposed and the repair strategies are obtained by these measures to determine the order of repaired nodes. In order to accurately reflect the resilience in the interdependent mechatronic system, we adopt three metrics to quantify it, i.e., the change of the robustness, the recovery ability, and the critical number of repaired nodes. Finally, we study the relationship between $\delta $ and the robustness, and apply different repair strategies to the analysis of the resilience in a real mechatronic system. The experiments show that the non-giant component plays a key role in the robustness and the resilience is affected by $\delta $ when a few nodes fail to work. In addition, we obtain the optimal repair strategy from different aspects of the resilience. A striking finding is that in most instances, the repair strategies concerning the interdependent measures lead to the higher resilience compared with the ones concerning the single measures. Our work may provide insights to make a plan for repairing equipment so as to enhance the resilience of the interdependent mechatronic system.

Partial Information Decomposition and the Information Delta: A Geometric Unification Disentangling Non-Pairwise Information.

Information theory provides robust measures of multivariable interdependence, but classically does little to characterize the multivariable relationships it detects. The Partial Information Decomposition (PID) characterizes the mutual information between variables by decomposing it into unique, redundant, and synergistic components. This has been usefully applied, particularly in neuroscience, but there is currently no generally accepted method for its computation. Independently, the Information Delta framework characterizes non-pairwise dependencies in genetic datasets. This framework has developed an intuitive geometric interpretation for how discrete functions encode information, but lacks some important generalizations. This paper shows that the PID and Delta frameworks are largely equivalent. We equate their key expressions, allowing for results in one framework to apply towards open questions in the other. For example, we find that the approach of Bertschinger et al. is useful for the open Information Delta question of how to deal with linkage disequilibrium. We also show how PID solutions can be mapped onto the space of delta measures. Using Bertschinger et al. as an example solution, we identify a specific plane in delta-space on which this approach’s optimization is constrained, and compute it for all possible three-variable discrete functions of a three-letter alphabet. This yields a clear geometric picture of how a given solution decomposes information.

Measuring financial interdependence in asset markets with an application to eurozone equities

A general measure of asset market interdependence based on higher order comoments is developed and applied to studying weekly U.S. and eurozone equity returns from 1990 to 2017. A new test of independence is also developed. The empirical results show that interdependence peaks during the global financial crisis with the covariance and covolatility comoments being the dominant factors. Conditioning the interdependence measure on volatility does not change the overall qualitative results. Implications of the results for constructing diversified portfolios reveal economic benefits from portfolios based on higher order comoments than the usual assumption of bivariate normality, especially during the GFC. The empirical results also provide evidence that European Union membership led to higher interdependence than did the adoption of the common currency.