Researches on thermoplastic composites using natural fiber as reinforcement are increasing, but studies of durability over time are scarce. In this sense the objective of this study is to evaluate changes in the properties of polypropylene/bamboo fiber (PP/BF) composite and the influence of the use of coupling agent (CA) in these composites after natural ageing. The PP/BF (70/30 wt) composites and 3% wt CA (citric acid from natural origin and maleic anhydride grafted polypropylene from petrochemical origin) were prepared by using an internal mixer chamber and then injection-molded. The samples were exposed to natural weathering for a total period of 12 months and characterized before and after exposure. All exposed composites experienced a decrease in their properties, however, the use of CA promoted more stability; in mechanical properties, the composites with CA showed lower loss about 23% in Young′s modulus, 18% in tensile stress at break, and 6% in impact strength. This behavior was similar in thermal and physical properties, the result for the CA of natural origin being similar to that of synthetic origin. These results indicate that the use of a CA may promote higher interaction between the fiber and the polymer. In addition, the CAs of organic origin and synthetic origin exhibited similar responses to natural ageing.

Currently, the interest in service-oriented architectures (SOA) has risen due to their structural flexibility, which allows to obtain features such as scalability, fault tolerance, low coupling, and easy integration, among others. In this context, this article presents the implementation of a SOA for tele-operated physical rehabilitation applications; this SOA ensures an effective orchestration of services, adding special functions, such as synchronous tele-operation of machines for physical rehabilitation, in such a way that it can be adapted and implemented by using information and communication technologies (ICT). The implementation of the architecture was validated by means of a test that allowed to analyze the behavior of the web services defined for the application.

In obtaining wood polymer composites (WPCs), a weak interfacial bonding can cause problems during the processing and affect the mechanical properties of the resulting composites. A coupling agent (CA) is commonly used to solving this limitation. To improve the interfacial bonding between bamboo fiber (BF) and a polypropylene matrix, the effect of three organic acids on the mechanical properties and interfacial morphology were investigated. The BF/PP composites were prepared in five families: the first without CA, the second using a maleic anhydride-grafted polypropylene coupling agent, and the third, fourth, and fifth families with the addition of organic acids (OA) tricarboxylic acid (TRIA), hexadecanoic acid (HEXA), and dodecanoic acid (DODA), respectively. The use of OA in BF/PP improved the interfacial adhesion with the PP matrix, and it results in better mechanical performance than composites without CA. Composites coupled with MAPP, TRIA, DODA, and HEXA showed an increase in Young’s modulus of about 26%, 23%, 15%, and 16% respectively compared to the composite without CA incorporation. In tensile strength, the increase in composites with CA was about 190%, while in the flexural modulus, the coupled composites showed higher values, and the increase was more in composites with TRIA: about 46%. The improvement caused by tricarboxylic acid was similar to that promoted by the addition of maleic anhydride-grafted polypropylene (MAPP).

This article presents an evaluation about the research related to the development of computational tools based on artificial intelligence techniques, which focus on the detection and diagnosis of faults in the different processes associated with a power generation plant such as: hydroelectric, thermoelectric and nuclear power plants. Initially, the main techniques of artificial intelligence that allow the construction of intelligent systems in the area of fault diagnosis is described in a general way, techniques such as: fuzzy logic, neural networks, knowledge-based systems and hybrid techniques Subsequently A summary of the research based on each of these techniques is presented. Subsequently, the different articles found for each of the techniques are presented in tables, illustrating the year of publication and the description of the research carried out. The result of this work is the comparison and evaluation of each technique focused on the diagnosis of failures in power plants. The novelty of this work is that it presents an extensive bibliography of the applications of the different intelligent techniques in solving the problem of detection and diagnosis of failure in power plants

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