José Sarsfield Cabral

Abstract
This paper aims to identify and analyze the factors that influence the decision of Mato Grosso’s farmers to produce soybean using the Analytic Hierarchy Process (AHP). We found evidence that decisionmaking of soybean production is related to rural production aspects such as climate, financing, cost of inputs, and soil quality rather than marketing and logistics. The novelty of this paper is the empirical analysis of the decision-making in agricultural production using AHP. The decision model was created and tested considering 21 farmers and 19 experts linked to the soybean production. Three different scenarios were considered: farmers’ view, experts’ view, and combined view. Our findings indicate that farmers and experts agree with rural aspects are predominant in the decision to plant soybean. Moreover, logistics have been used as an important flag of soybean competitiveness on international trade by soybean stakeholders in Brazil. However, our results show that logistics impact in the soybean decision-making process is low. Due to data limitation access, this study focuses only on Mato Grosso. However, this study has an exploratory character and presents empirical results that may help to understand soybean production over the country.

Abstract
The injection mold is a high precision tool responsible for the production of most plastic parts used everywhere. Its design is considered critically important for the quality of the product and efficient processing, as well as determinant for the economics of the entire injection molding process. However, typically, no formal engineering analysis is carried out during the mold design stage. In fact, traditionally, designers rely on their skills and intuition, following a set of general guidelines. This does not ensure that the final mold design is acceptable or the best option. At the same time, mold makers are now highly pressured to shorten both leading times and cost, as well as to accomplish higher levels of mold performance. For these reasons, it is imperative to adopt new methods and tools that allow for faster and higher integrated mold design. To that end, a new global approach, based on the integration of well-known quantitative techniques, such as Design for Six Sigma (DFSS), Structural Equation Modeling (SEM), Axiomatic Design (AD) and Multidisciplinary Design Optimization (MDO) is presented. Although some of these methods have been largely explored, individually or in combination with other methodologies, a quantitative integration of all aspects of design, in such a way that the whole process becomes logical and comprehensible, has not yet been considered. To that end, the DFSS methodology, through its IDOV roadmap, was adopted. It is based on the ICOV Yang and El-Haik proposal, establishing four stages for the design process: Identify, which aims to define customers’ requirements/expectations; Design, where the creation of a product concept, and its system-level design, is performed; Optimization, in which all the detailed design, through product optimization, is handled; and finally, Validation, where all product design decisions are validated, in order to verify if the new designed entity indeed meets customer and other requirements. As a result, this approach tackles the design of an injection mold in a global and quantitative approach, starting with a full understanding of customer requirements and converting them into optimal mold solutions. In order to validate it, an integrated platform was developed, where all different analysis modules were inserted and optimized through an overseeing code system. The results attained highlight the great potential of the proposed framework to achieve mold design improvements, with consequent reduction of rework and time savings for the entire mold design process. © 2011 by Nova Science Publishers, Inc.

Abstract
Soybean is one of the main sources of protein directly and indirectly in human nutrition, and it is highly dependent on logistics to connect country growers and international markets. Although recent studies deal with the impact of logistics on international trade, this impact in agricultural commodities is still an open research question. Moreover, these studies usually do not consider the influence of all components of the logistics on trade. This paper, therefore, aims at identifying the role of logistics performance in soybean exports among Argentina, Brazil, the US and their trading partners from 2012 to 2018. Using an extended gravity model, we examine whether the indicators of the World Bank Logistics Performance Index (LPI), adopted as a proxy of logistics efficiency, are an important determinant of bilateral soybean trade facilitation. The results lead to the conclusion that it is necessary to analyze the LPI throughout its indicators because they may affect trade differently. The novelty of this article is to provide an analysis of the impact of different logistics aspects on commodity trade, more specifically in the soybean case. Finally, regarding the model results, logistics infrastructure has a positive and significant correlation with soybean trade as supposed in most of the literature.

Abstract
In the last decades, the assurance of doctoral education's quality and their respective external quality assurance (QA) systems have been on the agenda of many European countries. Portugal is no exception, with doctoral education being envisaged by the national study programmes' accreditation system. This study aims to discuss both the forms assumed by the QA of doctoral education within the scope of a tightly regulated system, such as the Portuguese one, as well as the effects or impact of such a system in this education level. In trying to explore this impact, particular attention is given to the accreditation results (full accreditation, conditional accreditation and non-accreditation) of the doctoral programmes according to their scientific area and higher education sector (public and private). Overall it is possible to conclude that the Portuguese QA system has been contributing to the reorganisation of doctoral education, both by excluding programmes that do not meet a set of minimum quality criteria and by promoting the enhancement of the remaining programmes, through the enforcement of improvement measures. This reorganisation seems to differently affect doctoral programmes from distinct scientific areas as well as from private and public institutions.

Abstract
The Douro Valley of Portugal is a well-known wine region producing Port wine since the end of the 18th century, with quality table wines becoming increasingly important over the last 20 years. Port wine production is the most important economic sector of the region and Vintage Port is the top quality Port wine type, produced only from the best vintages. The purpose of this research was to examine how the variability of annual weather influences the quality of Vintage Port. A weather and climate data set for the period 1980-2009 and a consensus ranking that combined a collection of vintage chart scores into a ranking were used to characterize both the weather and the vintage quality. In order to more precisely model the weather influences on the quality of the vintages it was necessary to partition the growing season into smaller growth intervals in which several heat and precipitation variables were evaluated. The heat-related variables were defined according to the phenology of grapevines, using a partition of the growing season based on accumulated temperature, rather than on calendar dates. Precipitation variables were calculated using broad periods corresponding to the dormant, vegetative and maturation stages of the grapevines. A logistic regression model was used as a tool to identify the weather variables that help to explain the relationships between yearly weather characteristics and vintage quality. The results show that several weather characteristics are strongly associated with better quality vintages: growing season mean temperatures above the region's average, warm winters, cool July through veraison and cool temperatures during ripening. In summary, although the weather is not solely responsible for determining a vintage quality, it plays an important role on it; therefore, its understanding can provide invaluable management insights to growers and producers.