From Cocoa Producers to Chocolatiers? Developing an Entrepreneurial Model for Small‐scale Producers in Honduras

Purpose ‐ The cocoa value chain exemplifies the imbalances often seen in the global trade of commodities. The purpose of this paper is to evaluate the likeliness of cocoa growers to become entrepreneurs and chocolatiers and to reflex about the impact this would have in their socioeconomic context.Design/Methodology/Approach – This research studies the possibility of entrepreneurial endeavors using the concepts of the Theory of Planned Behavior (TPB) developed by Ajzen (1991). This way, a quantitative model based on the findings from Liñán and Chen (2009) was created, in which the Personal Attitude (PA), Subjective Norm (SN), and Perceived Behavioral Control (PBC) along with other personal and social variables ‐in this case the Readiness to be an Entrepreneur (RE)‐ affect directly the Entrepreneurial Intention (EI).Findings – Findings suggest that 75% of the farmers showed Entrepreneurial Intention and other entrepreneurial characteristics such as knowledge of the market, technology and regulatory framework. The existence of an organization of social capital in the same village, run by the wives of the farmers, alsoadds to the entrepreneurial intention of the village, since the main goal is to add value and produce chocolate.Originality/Value – This research provides insight of the mindset shared by Honduran cocoa growers about performing in the chocolate industry. At the same time provides a raw image of the living conditions these individuals face and how their view of the chocolate industry is affected by their need to escape poverty

HTself2: Combining p-values to Improve Classification of Differential Gene Expression in HTself

HTself is a web-based bioinformatics tool designed to deal with the classification of differential gene expression for low replication microarray studies. It is based on a statistical test that uses self-self experiments to derive intensity-dependent cutoffs. The method was previously described in Vêncio et al, (DNA Res. 12: 211- e 214, 2005). In this work we consider an extension of HTself by calculating p-values instead of using a fixed credibility level α. As before, the statistic used to compute single spots p-values is obtained from the gaussian Kernel Density Estimator method applied to self-self data. Different spots corresponding to the same biological gene (replicas) give rise to a set of independent p-values which can be combined by well known statistical methods. The combined p-value can be used to decide whether a gene can be considered differentially expressed or not. HTself2 is a new version of HTself that uses the idea of p-values combination. It was implemented as a user-friendly desktop application to help laboratories without a bioinformatics infrastructure

Using data mining to study the impact of topology characteristics on the performance of wireless mesh networks

This paper quantifies the impact of topological characteristics on the performance of single radio multichannel IEEE802.11 mesh networks. Topological characteristics are the number of nodes per subnetwork, the hop count, the neighbor node density, the hidden nodes, the number of nodes in the neighborhood of the gateway, and the hidden nodes in the neighborhood of the gateway. Network performance metrics are throughput, fairness and delay. The data mining Support Vector Machine (SVM) model was used to extract the relationships between the network topology metrics and the network per- formance metrics based on data results obtained through ns- 2 simulation of random networks. The results obtained can be used as a basis to design channel assignment algorithms or to aid the deployment and management of single radio wireless mesh networks.Fundação para a Ciência e a Tecnologia (FCT) - SitMe project from QREN–ON.2 program and FCT SFRH/BD/13444/2003