Integration of B-to-B trade network models of structural evolution and monetary flows reproducing all major empirical laws.

We develop a single two-layered model framework that captures and replicates both the statistical properties of the network as well as those of the intrinsic quantities of the agents. Our model framework consists of two distinct yet connected elements that were previously only studied in isolation, namely methods related to temporal network structures and those associated with money transport flows. Within this context, the network structure emerges from the first layer and its topological structure is transferred to the second layer associated with the money transactions. In this manner, we can explain how the micro-level dynamics of the agents within the network lead to the exogenous manifestation of the aggregated system statistical data en-wrapping the very same agents within the system. This is done by capturing the essential dynamics of collective motion in complex networks that enable the simultaneous emergence of tent-shaped distributions in growth rates within the agents, together with the emergence of scaling properties within the network in the study. We can validate the model framework and dynamics by applying these to the context of the real-world inter-firm trading network of firms in Japan and comparing the results of the statistical distributions at both network and agent levels in a temporal manner. In particular, we compare our results to the fundamental quantities supporting the seven empirical laws observed in data: the degree distribution, the mean degree growth rate over time, the age distribution of the firms, the preferential attachment, the sales distribution in steady states, their growth rates, their scaling relations generated by the model. We find these results to be nearly identical to the real-world data. The framework has the potential to be transformed into a forecasting tool to support decision-makers on financial and prudential policies.

Economic Trading Susceptibility: Constructing Networks of Mutual Influence through the Fitness of Countries.

The emergence of economic blocks and the level of influence countries exert on each other are fundamental features of the 21st century globally interconnected economy. However, limited quantitative research exists measuring the level of influence among countries and quantitatively determining economic blocks. This research develops a method to quantify the mutual influence of countries by making use of relatively standard procedures for complex networks in order to assemble non-trivial networks of influences and to identify symbiotic relationships. The methods are of significant help to an enhanced understanding of the global politics of trading and associations. Moreover, we develop the Mutual Influence Robustness (MIR) metric to work together with the Economic Fitness metric to provide some level of predictive modeling for the trends and future paths of countries. Our key results show the existence of a mutually influencing network around East and Southeast Asia, developed North America, and the northern and Iberian countries. Moreover, we find that it is possible to do some level of path predictability for the fitness and mutual influence of countries.

Allometric Scaling of Mutual Information in Complex Networks: A Conceptual Framework and Empirical Approach.

Complexity and information theory are two very valuable but distinct fields of research, yet sharing the same roots. Here, we develop a complexity framework inspired by the allometric scaling laws of living biological systems in order to evaluate the structural features of networks. This is done by aligning the fundamental building blocks of information theory (entropy and mutual information) with the core concepts in network science such as the preferential attachment and degree correlations. In doing so, we are able to articulate the meaning and significance of mutual information as a comparative analysis tool for network activity. When adapting and applying the framework to the specific context of the business ecosystem of Japanese firms, we are able to highlight the key structural differences and efficiency levels of the economic activities within each prefecture in Japan. Moreover, we propose a method to quantify the distance of an economic system to its efficient free market configuration by distinguishing and quantifying two particular types of mutual information, total and structural.

Independência funcional entre comportamentos de falante e ouvinte relativos a paisagens desconhecidas / Functional independence between speaker-listener behaviors related to unknown landscapes / Independencia funcional entre comportamientos de hablante y oyente relacionados a paisajes desconocidos

Este estudo investigou o efeito de treinos sucessivos na emissão não treinada de comportamentos de ouvinte e falante após o treino do outro operante. Doze adultos universitários típicos foram divididos em dois grupos com base na ordem de exposição aos treinos e testes em três fases experimentais. Os participantes do Grupo Ouvinte-Falante passaram por treinos de ouvinte e testes de falante, e os demais foram submetidos a treinos e testes na ordem inversa. Os cinco estímulos utilizados por fase foram palavras inventadas e paisagens desconhecidas por eles. Os participantes do Grupo Falante-Ouvinte atingiram o critério de dependência funcional nas três fases experimentais. No outro grupo, apenas um integrante apresentou dependência funcional na primeira fase experimental, sendo observada melhora gradual no desempenho nos testes ao longo do experimento para os demais. Discutiu-se a eficácia dos treinos sucessivos na ocorrência de dependência funcional condicionalmente a aspectos do procedimento...(AU)

This study investigated the effect of successive training on the untrained emission of listener and speaker behaviors after the training of the other operant. Twelve typical undergraduates were divided into two groups based on order of training and testing in three experimental phases. The participants of the Listening-Speaker Group underwent listener training and speaker test; and the other participants were subjected to training and tests in the reverse order. The five stimuli used per phase were invented words and unknown landscapes. The participants of the Speaker-Listener Group reached the criterion of functional dependence in the three experimental phases. In the other group, only one participant presented functional dependence in the first experimental phase, with a gradual improvement in performance in the tests throughout the experiment for the remaining subjects. The efficacy of successive training in the occurrence of functional dependence associated to aspects of the procedure was discussed...(AU)

El presente estudio investigó el efecto de los entrenamientos sucesivos en la emisión no entrenada de las conductas del oyente y el hablante después del entrenamiento del otro operante. Se dividieron doce universitarios adultos típicos en dos grupos según el orden de entrenamiento y los test en tres fases experimentales. Los participantes del Grupo Oyente-Hablante pasaron por entrenamientos de oyentes y test de los hablantes; y los otros participantes se sometieron a entrenamientos y test en el orden inverso. Los cinco estímulos utilizados por fase fueron palabras inventadas y paisajes desconocidos por ellos. Los participantes del Grupo Hablante-Oyente alcanzaron el criterio de dependencia funcional en las tres fases. En el otro grupo, solo un participante presentó dependencia funcional en la primera fase, con una mejora gradual en el rendimiento en los test a lo largo del experimento para los demás. Se discutió la eficacia de los entrenamientos sucesivos en la aparición de dependencia funcional condicionalmente a aspectos del procedimiento...(AU)

Dynamics of essential interaction between firms on financial reports.

Companies tend to publish financial reports in order to articulate strategies, disclose key performance measurements as well as summarise the complex relationships with external stakeholders as a result of their business activities. Therefore, any major changes to business models or key relationships will be naturally reflected within these documents, albeit in an unstructured manner. In this research, we automatically scan through a large and rich database, containing over 400,000 reports of companies in Japan, in order to generate structured sets of data that capture the essential features, interactions and resulting relationships among these firms. In doing so, we generate a citation type network where we empirically observe that node creation, annihilation and link rewiring to be the dominant processes driving its structure and formation. These processes prompt the network to rapidly evolve, with over a quarter of the interactions between firms being altered within every single calendar year. In order to confirm our empirical observations and to highlight and replicate the essential dynamics of each of the three processes separately, we borrow inspiration from ecosystems and evolutionary theory. Specifically, we construct a network evolutionary model where we adapt and incorporate the concept of fitness within our numerical analysis to be a proxy real measure of a company's importance. By making use of parameters estimated from the real data, we find that our model reliably replicates degree distributions and motif formations of the citation network, and therefore reproducing both macro as well as micro, local level, structural features. This is done with the exception of the real frequency of bidirectional links, which are primarily formed as a result of an entirely separate and distinct process, namely the equity investments from one company into another.

Assembling real networks from synthetic and unstructured subsets: the corporate reporting case.

The analysis of interfirm business transaction networks provides invaluable insight into the trading dynamics and economic structure of countries. However, there is a general scarcity of data available recording real, accurate and extensive information for these types of networks. As a result, and in common with other types of network studies - such as protein interactions for instance - research tends to rely on partial and incomplete datasets, i.e. subsets, with less certain conclusions. Here, we make use of unstructured financial and corporate reporting data in Japan as the base source to construct a financial reporting network, which is then compared and contrasted to the wider real business transaction network. The comparative analysis between these two rich datasets - the proxy, partially derived network and the real, complete network at macro as well as local structural levels - provides an enhanced understanding of the non trivial relationships between partial sampled subsets and fully formed networks. Furthermore, we present an elemental agent based pruning algorithm that reconciles and preserves key structural differences between these two networks, which may serve as an embryonic generic framework of potentially wider use to network research, enabling enhanced extrapolation of conclusions from partial data or subsets.

Superiority of Interferon Gamma Assay Over Tuberculin Skin Test for Latent Tuberculosis in Inflammatory Bowel Disease Patients in Brazil.

BACKGROUND AND AIMS: To compare tuberculin skin test (TST) and interferon gamma release assay (IGRA) in the screening of LTBI among patients with inflammatory bowel disease (IBD) in an endemic area for tuberculosis, to evaluate the need for repeating tests during anti-TNFα, therapy, and to check whether the results may be affected by immunosuppression. METHODS: A cross-sectional study of 110 IBD patients and 64 controls was conducted in Rio de Janeiro, Brazil. The TST was administered after the Quantiferon(®)-TB Gold In-tube test was performed. RESULTS: TST and IGRA agreement was poor regarding diagnosis (kappa: control = 0.318; UC = 0.202; and CD = - 0.093), anti-TNFα therapy (kappa: with anti-TNFα = 0.150; w/o anti-TNFα = - 0.123), and immunosuppressive therapy (IST) (kappa: with IS = - 0.088; w/o IS = 0.146). Indeterminate IGRA was reported in four CD patients on IST. Follow-up tests after anti-TNFα identified conversion in 8.62% using TST and 20.0% using IGRA. Considering IGRA as a criterion standard, TST showed low sensitivity (19.05%) and positive predictive value (PPV) (21.05%). LTBI detection remarkably improved when IGRA was added to TST (sensitivity of 80.95% and PPV of 53.13%). Results were particularly relevant among CD patients where rates started from zero to reach sensitivity and PPV of more than 60%. CONCLUSION: IGRA alone was more effective to detect LTBI than TST alone and had an overall remarkable added value as an add-on sequential test, particularly in CD patients. While cost-effectiveness of these strategies remains to be evaluated, IGRA appears to be justified in CD prior to and during anti-TNFα therapy, where tuberculosis is endemic.

Appearance of Unstable Monopoly State Caused by Selective and Concentrative Mergers in Business Networks.

Recently, growth mechanism of firms in complex business networks became new targets of scientific study owing to increasing availability of high quality business firms' data. Here, we paid attention to comprehensive data of M&A events for 40 years and derived empirical laws by applying methods and concepts of aggregation dynamics of aerosol physics. It is found that the probability of merger between bigger firms is bigger than that between smaller ones, and such tendency is enhancing year by year. We introduced a numerical model simulating the whole ecosystem of firms and showed that the system is already in an unstable monopoly state in which growth of middle sized firms are suppressed.

The dynamics of mergers and acquisitions: ancestry as the seminal determinant.

Understanding the fundamental mechanisms behind the complex landscape of corporate mergers and acquisitions is of crucial importance to economies across the world. Adapting ideas from the fields of complexity and evolutionary dynamics to analyse business ecosystems, we show here that ancestry, i.e. the cumulative sum of historical mergers across all ancestors, is the key characteristic to company mergers and acquisitions. We verify this by comparing an agent-based model to an extensive range of business data, covering the period from the 1830s to the present day and a range of industries and geographies. This seemingly universal mechanism leads to imbalanced business ecosystems, with the emergence of a few very large, but sluggish 'too big to fail' entities, and very small, niche entities, thereby creating a paradigm where a configuration akin to effective oligopoly or monopoly is a likely outcome for free market systems.