Lignocelluloses residues from the post-harvest crop are receiving great scientific attention nowadays. Generally, the composite materials based on lignocelluloses waste present low density and weight, and better insulation properties compared with those petroleum-based. This study presents the results of experimental investigations regarding soundproofing capabilities for a composite material based on expanded perlite (EP) and natural polymers matrix (starch) reinforced with rapeseed stalks waste. The preparation of light-weight samples of composites was performed at room temperature through a mechanical mixing process of EP with starch polymers and rapeseed residues until optimum moisture content composition was obtained. Rapeseed stalks long fibers were avoided through the preliminary dry grinding procedure, and the composite was air-dried at room temperature for 48 h. Four samples of composites with different ratio of EP and rapeseed waste were considered. The evaluation of sample sound insulation characteristics was performed using the transfer-matrix method based on a four-microphone acoustic impedance tube. The paper concludes that the proposed composite provides comparative sound insulation capabilities to actual materials, with few particular aspects presented within the paper. Thus, these new materials are promising as a viable alternative to the actual large-scale utilization solutions in soundproofing applications.

We are going through a period in which the concept of the smart village (SV) is a novelty for the management of a community, and the new smart economy of the village is based on the power of community support. Appropriately, the development of a SV is related to a family’s participation in the motivation and access to education, the increase in knowledge of information technology, information and communications technology (ICT) literacy, and also in the creation of facilities for research and development (R&D). The partnership between the public administration, the private sector, and the community heads will lead to a smart economy within the village. At the same time, the intervention of the food system to support climate change can be supported by intelligent agriculture. The SV has a strong social significance; research in the field can be multidisciplinary, including human nutrition, climate change, and community education. This paper aims to X-ray the research areas of the SV from a multidisciplinary sense, in support of the partnership with the community, and to identify the main directions of strategic development. In total, 368 pieces of research on SVs from the last ten years were analyzed through bibliometric analysis using VOSviewer software, doubled by the co-occurrence of keywords and the bibliometric combination of documents, followed by a systematic review of the literature. The research undertaken was intended to contribute to the development of research for SVs, with the analysis of identified clusters. The results obtained will have a special contribution at the SV level through strategic and research proposals and suggest that the most important strategic and research directions for SVs focus on community education, its satiety, as well as several environmental and social changes generated by SVs.

This paper presents a fuzzy quality certification of wheat. This analysis is based on the fuzzy analysis model of wheat. We developed a Matlab application with the help of which we modeled the perceptions in relation to the main quality physical and chemical characteristics of wheat obtaining a quality index of wheat lots. The algorithm presented in this article allows for obtaining and using the global quality index, generating applicability not only to the commercial sphere as a quality reference and price setting, but also a measure of appreciation of processing opportunities. Indices of fuzzy quality associated with wheat lots using a fuzzy model offer the opportunity to develop local markets through quality certification.

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In this paper, we present a system description for implementing a sentiment analysis agent capable of interpreting the state of an interlocutor engaged in short three message conversations. We present the results and observations of our work and which parts could be further improved in the future.