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Bioenergy is a renewable energy obtained from biomass, and its main benefits are the reduction of greenhouse gases and waste disposal. One way to generate bioenergy is through anaerobic digesters. However, a common problem found in feasibility analyses is the appropriate location for these biodigesters, since the biomass is geographically and spatially dispersed. When the location is poorly chosen, it can interfere with the viability of the project. Therefore, the objective of this research is to determine the existence of areas that could still be explored by investigating studies that seek to identify suitable locations for deploying the biodigesters from the perspective of aspects (economic, environmental and social), localization problems (location/allocation and supply chain) and techniques. To this end, a systematic review of the literature was conducted from the Science Direct, Scopus and Web of Science databases. It was observed that the literature could be more explored to (a) consider the social aspect in biodigesters location models, (b) propose studies that specify and consolidate each aspects’ characteristics found in the literature applied in biodigesters location models, (c) integrate the economic–environmental–social aspects into supply chain project problems, and (d) explore the creation of clusters for energy production through strategic partnerships between small farms.
Rômulo Henrique Gomes de Jesus; Jovani Taveira de Souza; Fabio Neves Puglieri; Cassiano Moro Piekarski; Antonio Carlos de Francisco. Biodigester location problems, its economic–environmental–social aspects and techniques: Areas yet to be explored. Energy Reports 2021, 7, 3998 -4008.
AMA StyleRômulo Henrique Gomes de Jesus, Jovani Taveira de Souza, Fabio Neves Puglieri, Cassiano Moro Piekarski, Antonio Carlos de Francisco. Biodigester location problems, its economic–environmental–social aspects and techniques: Areas yet to be explored. Energy Reports. 2021; 7 ():3998-4008.
Chicago/Turabian StyleRômulo Henrique Gomes de Jesus; Jovani Taveira de Souza; Fabio Neves Puglieri; Cassiano Moro Piekarski; Antonio Carlos de Francisco. 2021. "Biodigester location problems, its economic–environmental–social aspects and techniques: Areas yet to be explored." Energy Reports 7, no. : 3998-4008.
The aim of this paper is twofold: (i) to build a model by combining an agglomerative hierarchical algorithm with multicriteria analysis and geographic information systems (GIS) in order to identify whether there are opportunities to create strategic partnerships based on geographic coordinates of raw material suppliers and the volume of raw material supply; and (ii) to apply the model in a case study in order to identify suitable locations for building a biodigester, thus establishing strategic partnerships and circular economy-based practices. The model involves four stages: (1) defining the study site, (2) building the set of cluster solutions, (3) defining the suitable locations for building a biodigester, and (4) conducting analyses of feasibility of strategic partnership and sensitivity. The model was applied in a small region and it was analyzed the possibility of creating two or three clusters. The use of the model allowed, from both quantitative and qualitative perspectives, to preliminarily identify the possibility of creating a strategic partnership, and also determine the location of a biodigester. The case study applied in southern Brazil took place in a region with high potential for generating biogas from agro-waste. A geographic map with roads, rivers, and constraints was built. Strategic partnerships, sensitivity analysis, and circular economy-based practices were discussed. The results of this work could provide useful information when using the model for other regions, and the model could easily incorporate further criteria and conditions, making it flexible and tailored to users' needs.
Rômulo Henrique Gomes de Jesus; Murillo Vetroni Barros; Rodrigo Salvador; Jovani Taveira de Souza; Cassiano Moro Piekarski; Antonio Carlos de Francisco. Forming clusters based on strategic partnerships and circular economy for biogas production: A GIS analysis for optimal location. Biomass and Bioenergy 2021, 150, 106097 .
AMA StyleRômulo Henrique Gomes de Jesus, Murillo Vetroni Barros, Rodrigo Salvador, Jovani Taveira de Souza, Cassiano Moro Piekarski, Antonio Carlos de Francisco. Forming clusters based on strategic partnerships and circular economy for biogas production: A GIS analysis for optimal location. Biomass and Bioenergy. 2021; 150 ():106097.
Chicago/Turabian StyleRômulo Henrique Gomes de Jesus; Murillo Vetroni Barros; Rodrigo Salvador; Jovani Taveira de Souza; Cassiano Moro Piekarski; Antonio Carlos de Francisco. 2021. "Forming clusters based on strategic partnerships and circular economy for biogas production: A GIS analysis for optimal location." Biomass and Bioenergy 150, no. : 106097.
The use of petroleum-based packaging and its disposal in the environment poses several environmental problems, driving research into the development of biopolymers as substitutes for conventional polymers. Therefore, this study used the by-product of potato industrialization as the main raw material, xanthan gum as a plasticizer, and natural oat fiber as reinforcement to develop a biodegradable foam through thermo-pressing. The morphology, mechanical properties, and biodegradability of the final product were investigated. The water absorption and solubility index were highest in the sample with 20% plasticizer and 20% fiber. The water activity was not affected by variations in additives. The samples with the highest concentration of additives had the highest mechanical tensile strength, but there was a limit to these levels for foam resistance. The most accentuated visual effect was the yellow color. It is believed that hydrolysis was the main foam degradation mechanism, which took between 14 and 20 days for total decomposition. The combination of a by-product from potato industrialization with xanthan gum and natural oat fiber made it possible to produce a promising substitute for synthetic polymers, providing an environmentally friendly solution for both the use of agro-industrial by-products and reducing the volume of petroleum-based packaging waste.
Nathalie Hamine Panzarini Rodrigues; Jovani Taveira De Souza; Reinaldo Luan Rodrigues; Maria Helene Giovanetti Canteri; Sandra Mara Kaminski Tramontin; Antonio Carlos De Francisco. Starch-Based Foam Packaging Developed from a By-Product of Potato Industrialization (Solanum tuberosum L.). Applied Sciences 2020, 10, 2235 .
AMA StyleNathalie Hamine Panzarini Rodrigues, Jovani Taveira De Souza, Reinaldo Luan Rodrigues, Maria Helene Giovanetti Canteri, Sandra Mara Kaminski Tramontin, Antonio Carlos De Francisco. Starch-Based Foam Packaging Developed from a By-Product of Potato Industrialization (Solanum tuberosum L.). Applied Sciences. 2020; 10 (7):2235.
Chicago/Turabian StyleNathalie Hamine Panzarini Rodrigues; Jovani Taveira De Souza; Reinaldo Luan Rodrigues; Maria Helene Giovanetti Canteri; Sandra Mara Kaminski Tramontin; Antonio Carlos De Francisco. 2020. "Starch-Based Foam Packaging Developed from a By-Product of Potato Industrialization (Solanum tuberosum L.)." Applied Sciences 10, no. 7: 2235.
The transport sector is seen as the main responsible for greenhouse gas emissions, accounting for approximately 33% of global emissions. Faced with this environmental concern, the automotive sector has sought to incorporate sustainability into the life cycle of vehicles, via for instance, eco-efficiency approaches. The aim of this paper was to demonstrate the environmental and economic effects of the change in the differential ratio in a heavy-duty vehicle. Thus, a detailed case study was carried out. From an environmental perspective, a Life Cycle Assessment was conducted to quantify the potential impacts considering the impact categories of (i) resource consumption, human health with (ii) carcinogenic and (iii) effects, and (iv) global warming potential. Life Cycle Assessment results indicated an average of 6.50% impact reduction for each category analyzed, due to the change in the differential ratio. Moreover, from an economic perspective, it was observed a reduction of 5,000 liters/year of diesel consumption for the studied truck, which was equivalent to BRL 15,000.
Mariane Bigarelli Ferreira; Rodrigo Salvador; Murillo Vetroni Barros; Jovani Taveira De Souza; Tulio Gustavo Lima Rabelo; Antonio Carlos De Francisco; Ricardo Coelho; Cassiano Moro Piekarski. Eco-efficiency of the differential ratio change in a heavy-duty vehicle and implications for the automotive industry. Sustainable Production and Consumption 2020, 21, 145 -155.
AMA StyleMariane Bigarelli Ferreira, Rodrigo Salvador, Murillo Vetroni Barros, Jovani Taveira De Souza, Tulio Gustavo Lima Rabelo, Antonio Carlos De Francisco, Ricardo Coelho, Cassiano Moro Piekarski. Eco-efficiency of the differential ratio change in a heavy-duty vehicle and implications for the automotive industry. Sustainable Production and Consumption. 2020; 21 ():145-155.
Chicago/Turabian StyleMariane Bigarelli Ferreira; Rodrigo Salvador; Murillo Vetroni Barros; Jovani Taveira De Souza; Tulio Gustavo Lima Rabelo; Antonio Carlos De Francisco; Ricardo Coelho; Cassiano Moro Piekarski. 2020. "Eco-efficiency of the differential ratio change in a heavy-duty vehicle and implications for the automotive industry." Sustainable Production and Consumption 21, no. : 145-155.
Guilherme Francisco Prado; Cassiano Moro Piekarski; Leila Mendes Luz; Jovani Taveira Souza; Rodrigo Salvador; Antonio Carlos Francisco. Sustainable development and economic performance: Gaps and trends for future research. Sustainable Development 2019, 28, 368 -384.
AMA StyleGuilherme Francisco Prado, Cassiano Moro Piekarski, Leila Mendes Luz, Jovani Taveira Souza, Rodrigo Salvador, Antonio Carlos Francisco. Sustainable development and economic performance: Gaps and trends for future research. Sustainable Development. 2019; 28 (1):368-384.
Chicago/Turabian StyleGuilherme Francisco Prado; Cassiano Moro Piekarski; Leila Mendes Luz; Jovani Taveira Souza; Rodrigo Salvador; Antonio Carlos Francisco. 2019. "Sustainable development and economic performance: Gaps and trends for future research." Sustainable Development 28, no. 1: 368-384.
Dimensionality reduction is used in microarray data analysis to enhance prediction quality, reduce computing time, and construct more robust models. In addition, the algorithm learning performance involves an expressive number of attributes (genes) relative to the classes (samples). Therefore, in this study, we conducted a detailed comparison of two reduction methods, Attribute Selection and Principal Component Analysis, to analyze gene expression data sets. Both reduction methods were employed in the pre-processing stage and then evaluated experimentally. Furthermore, we introduced a combination of consistency-based subset evaluation (CSE) and minimum redundancy maximum relevance (mRMR), which we referred to as CSE-mRMR, to improve classification efficiency. The results indicated significant increase in classifier hit rates with both methods, compared to using all attributes. Employing cross-validation, attribute selection outperformed PCA consistently across classifiers and datasets, and CSE-mRMR demonstrated good classification performance in the data sets. Taken together, the literature and current results suggest that attribute selection may be relevant in the analysis and future prediction of gene expression data sets.
Jovani Taveira De Souza; Antonio Carlos De Francisco; Dayana Carla De Macedo. Dimensionality Reduction in Gene Expression Data Sets. IEEE Access 2019, 7, 61136 -61144.
AMA StyleJovani Taveira De Souza, Antonio Carlos De Francisco, Dayana Carla De Macedo. Dimensionality Reduction in Gene Expression Data Sets. IEEE Access. 2019; 7 (99):61136-61144.
Chicago/Turabian StyleJovani Taveira De Souza; Antonio Carlos De Francisco; Dayana Carla De Macedo. 2019. "Dimensionality Reduction in Gene Expression Data Sets." IEEE Access 7, no. 99: 61136-61144.
Jovani Taveira De Souza; Antonio Carlos De Francisco; Cassiano Moro Piekarski; Guilherme Francisco Do Prado; Leandro Gasparello De Oliveira. Data mining and machine learning in the context of sustainable evaluation: a literature review. IEEE Latin America Transactions 2019, 17, 372 -382.
AMA StyleJovani Taveira De Souza, Antonio Carlos De Francisco, Cassiano Moro Piekarski, Guilherme Francisco Do Prado, Leandro Gasparello De Oliveira. Data mining and machine learning in the context of sustainable evaluation: a literature review. IEEE Latin America Transactions. 2019; 17 (03):372-382.
Chicago/Turabian StyleJovani Taveira De Souza; Antonio Carlos De Francisco; Cassiano Moro Piekarski; Guilherme Francisco Do Prado; Leandro Gasparello De Oliveira. 2019. "Data mining and machine learning in the context of sustainable evaluation: a literature review." IEEE Latin America Transactions 17, no. 03: 372-382.
Smart cities (SC) promote economic development, improve the welfare of their citizens, and help in the ability of people to use technologies to build sustainable services. However, computational methods are necessary to assist in the process of creating smart cities because they are fundamental to the decision-making process, assist in policy making, and offer improved services to citizens. As such, the aim of this research is to present a systematic review regarding data mining (DM) and machine learning (ML) approaches adopted in the promotion of smart cities. The Methodi Ordinatio was used to find relevant articles and the VOSviewer software was performed for a network analysis. Thirty-nine significant articles were identified for analysis from the Web of Science and Scopus databases, in which we analyzed the DM and ML techniques used, as well as the areas that are most engaged in promoting smart cities. Predictive analytics was the most common technique and the studies focused primarily on the areas of smart mobility and smart environment. This study seeks to encourage approaches that can be used by governmental agencies and companies to develop smart cities, being essential to assist in the Sustainable Development Goals.
Jovani Taveira De Souza; Antonio Carlos De Francisco; Cassiano Moro Piekarski; Guilherme Francisco Do Prado. Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018. Sustainability 2019, 11, 1077 .
AMA StyleJovani Taveira De Souza, Antonio Carlos De Francisco, Cassiano Moro Piekarski, Guilherme Francisco Do Prado. Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018. Sustainability. 2019; 11 (4):1077.
Chicago/Turabian StyleJovani Taveira De Souza; Antonio Carlos De Francisco; Cassiano Moro Piekarski; Guilherme Francisco Do Prado. 2019. "Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018." Sustainability 11, no. 4: 1077.
Waste disposal is a worldwide concern. In the case of the textile and clothing industries, consumption has increased steadily, especially in the clothing business, which generates large amounts of post-industrial waste. The objective of this article is to identify opportunities for improvement in the use of reverse logistics (RL) in clothing industries, as well as to list the existing strengths in the valuation of textile waste (TW) and minimize environmental impacts. To achieve this objective, a questionnaire was developed, validated and applied in a clothing cluster. The questionnaire assessed strengths and weaknesses in 8 dimensions using 32 assertions involving reverse logistics and management of textile waste. We identified in the research that: (i) there are no route facilitators between RL and TW in clothing industries; (ii) there are opportunities for the textile companies to increase the adoption of RL to combat TW; (iii) the main improvement opportunities for increasing cluster advancement in terms of RL and TW are: reuse of TW by the generating company and separating waste according to the composition of materials, which would facilitate the possibility of recycling and disclosing to consumers the importance of social and environmental practices. Conclusion remarks point that, despite the existence of strengths in the use of the RL for the TW valuing in the clothing industry, it is still required a readjustment of the destination of TW as a by-product to be used in a new cycle.
Eliane Pinheiro; Antonio Carlos de Francisco; Cassiano Moro Piekarski; Jovani Taveira de Souza. How to identify opportunities for improvement in the use of reverse logistics in clothing industries? A case study in a Brazilian cluster. Journal of Cleaner Production 2018, 210, 612 -619.
AMA StyleEliane Pinheiro, Antonio Carlos de Francisco, Cassiano Moro Piekarski, Jovani Taveira de Souza. How to identify opportunities for improvement in the use of reverse logistics in clothing industries? A case study in a Brazilian cluster. Journal of Cleaner Production. 2018; 210 ():612-619.
Chicago/Turabian StyleEliane Pinheiro; Antonio Carlos de Francisco; Cassiano Moro Piekarski; Jovani Taveira de Souza. 2018. "How to identify opportunities for improvement in the use of reverse logistics in clothing industries? A case study in a Brazilian cluster." Journal of Cleaner Production 210, no. : 612-619.