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Culture is the system of knowledge, from whose meanings the human being screened and selected their understanding of Reality in the broad sense, and interprets and regulates the facts and data of social behavior. In this sense, culture is a program for social action and acting in humans during the process of socialization and social interaction. The meanings of each culture are the cumulative product of collective and individual thinking, in ecological economic, social and political specific situations, so are the expression of each particular cultural historical conjuncture. Moreover, the universal cognitive structure for the apprehension of cultural reality is the World Vision (WV). Due to its importance and significance as substratum of religious and political belief systems, we will gird our study to mythical cognitive mode or mythical WV.

Impure systems contain Objects and Subjects: Subjects are human beings. We can distinguish a person as an observer (subjectively outside the system) and that by definition is the Subject himself, and part of the system. In this case he acquires the category of object. Objects (relative beings) are significances, which are the consequence of perceptual beliefs on the part of the Subject about material or energetic objects (absolute beings) with certain characteristics.The IS (Impure System) approach is as follows: Objects are perceptual significances (relative beings) of material or energetic objects (absolute beings). The set of these objects will form an impure set of the first order. The existing relations between these relative objects will be of two classes: transactions of matter and/or energy and inferential relations. Transactions can have alethic modality: necessity, possibility, impossibility and contingency. Ontic existence of possibility entails that inferential relations have Deontic modality: obligation, permission, prohibition, faculty and analogy. We distinguished between theorems (natural laws) and norms (ethical, legislative and customary rules of conduct).

Ideology is a systemic property of cognition central to the transmission and actualization of beliefs. Ideologies take many forms including religious, philosophical, popular and scientific. They play a central role in both personal identity and in the way society holds itself together. Therefore, it is important to understand how to model identities. The article introduces ideologies as a function of cognition that have been described by political scientists and critical theorists. There follows a typology of ideologies that shows their increasing complexity as societies develop. These considerations lead to the identification of key elements and variables in an ideology that can be expressed mathematically together with some of their systemic relations. These variables may be used to estimate the validation of ideologies.

Many complex systems, such as the product life cycle (PLC), can be described in terms of networks, with elements interacting and based on terms of graph theory. In this article, we intend to analyze the PLC from the point of view of network theory and chaos. To do this we will use the Smarta software, developed by our research group (but not yet in a commercial phase), based on network analysis and that allows us to interpret the virtuous circles that the system possesses, and analyze the causalities by observing the plot of existing relationships between the system's attractors. Smarta allows us to manage the uncertainty of whether or not the product is ecological, and to be proactive, in the sense of designing strategies that anticipate it. A case study is the PLC of a smartphone, where Smarta will act as a filter since it will allow us to associate the concepts of ecological and attractor, so that if the product is recyclable an attractor will be found, and if it is not recyclable it will lack attractors. ; This work was supported in part by the Ministry of Economy and Business, Government of Spain under Grant RTI2018-094653-B-C22, in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) under Grant CloudDriver4Industry TIN2017-89266-R, and in part by the Regional Ministry of Education, Research, Culture, and Sports (Valencian Community) under Grant GV/ 2018//061.

When examining a sector of the economy, it can be sometimes difficult to identify the relationships between the underlying variables that compose it. Therefore, we developed a causal analysis technique, capable of converting large amounts of data into a directed graph of cause-effect relationships. The main objective of the technique is to locate the attractors associated with the system, that is, the sets of variables toward which the system tends dynamically. This methodology is based not only on General System Theory, but also on the Graph Theory and a discrete version of Chaos Theory. However, when systems have a large number of variables, applying the technique can be a tedious task. We thus implemented the Smarta application, a causal analysis simulator that allows automating this methodology. The software constitutes a reimplementation and continuation of the application already developed by our research group. We conducted a causal analysis of a system extracted from a database of structural statistics of Spanish industrial sector companies between 2008 to 2015 (the data were obtained from Spain's National Institute of Statistics). We focused on the yearly analysis of companies' structural and economic properties, based on 21 proxy variables. Based on the proposed analysis, we attempted to answer the following questions: how were the survey variables causally related? Were there any groups of independent variables within the system? And what trends did the system follow over the 2008–2015 period? The aim was to propose an alternative to classical statistical methods employed until now. ; This work was supported in part by the Valencian Government, under Project GV/2018/061.

The development of Internet technologies and their application to commerce environments has favored new business strategies for industries. These allow including in the design phase the experience of use that the clients have of the product. However, this new element has not been considered in formal terms. A fundamental problem in product design is that it has not been modeled in mathematical terms, which means that their characteristics do not appear in rigorous and short properties, but in long developments that from an economic point of view maintain their meaning but that from a mathematical point of view are not sufficiently manageable. Therefore, since these properties have not been axiomatically formalized, we cannot work with them mathematically. For this reason, we propose analyzing the design of products through a network and discrete chaos theory perspective, which will allow us to use important mathematical tools such as graph theory and concepts, such as coverage, invariability, orbits, attractors, and the structural function. This paper also draws attention to the importance of circular flow in the general systems theory and its application to the design phase of products. Finally, the Intel case study is analyzed, locating the current attractor and its relationship with the success of the company's products. ; This work was supported in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) through project CloudDriver4Industry under Grant TIN2017-89266-R, and in part by the Valencian Government under Grant GV/2018/061.

Complex Systems is a new field of science studying how parts of a system give rise to the collective behaviours of the system, and how the system interacts with its environment. Graph theory is a fundamental tool in the study of social systems and economic issues. The input-output tables are precisely one of the main examples of it. We use the interpretation of labour market through networks to get a better understanding on its overall functioning. One benefit of the network perspective is that a large body of mathematics exists to help analyse many forms of networks models. If an economic system has a suitable model, then it becomes possible to utilize relevant mathematical tools, such as general systems theory, graph theory and discrete chaos theory, to better understand the way the labour market works. In this article, we apply concepts including structural functions, coverage and invariant sets to a social system's modelling. ; This work was supported in part by the Ministry of Economic Affairs and Digital Transformation of the Spanish Government, through the Modelado del Comportamiento de Entidades Digitales Mediante Tecnologías del Lenguaje Humano Project, under Grant RTI2018-094653-B-C22, in part by the Spanish Research Agency (AEI), and in part by the European Regional Development Fund (ERDF), through the CloudDriver4Industry Project, under Grant TIN2017-89266-R.