Variability in Quality and Management Practices in the Mango Supply Chain from Costa Rica

Produce quality is one of the features of any commodity that everyone has an opinion about, but quality is a complex concept. In one hand, quality is the consumer perception about a certain commodity an as well it is a relationship between all the intrinsic attributes of the commodity. It is argued that homogeneous management activities will increase the quality of the commodity. Reducing waste for example, but in a more generic way will reduce the variability of the commodity plus meeting the costumer needs and preferences. In this experimental article we try to disentangle the managerial activities that have an effect on the variability of the quality. For this purpose we have make use of the dispersion statistics such as standard deviation, standard error, deviation coefficient, meta-analysis and a regression analysis. We conducted a survey and collected 51 interviews of different actors in the supply chain of mango from Costa Rica, beside, we collected 10 mangos from each actor interview to analyze the intrinsic attribute of quality. We developed a proxy of quality as the ratio between the brix and the ph. We conclude that quality variability is affected positively related to technologic variations and socio-economic variations. In the case of the mango supply chain from Costa Rica the management differences among actors are dependent on the closeness to the consumer, therefore, actors closer to the consumer have higher variability in their indexes than those close to the production site.Variability, Supply Chain, Quality, Management, Agribusiness,

Input variable selection in time-critical knowledge integration applications: A review, analysis, and recommendation paper

This is the post-print version of the final paper published in Advanced Engineering Informatics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.The purpose of this research is twofold: first, to undertake a thorough appraisal of existing Input Variable Selection (IVS) methods within the context of time-critical and computation resource-limited dimensionality reduction problems; second, to demonstrate improvements to, and the application of, a recently proposed time-critical sensitivity analysis method called EventTracker to an environment science industrial use-case, i.e., sub-surface drilling. Producing time-critical accurate knowledge about the state of a system (effect) under computational and data acquisition (cause) constraints is a major challenge, especially if the knowledge required is critical to the system operation where the safety of operators or integrity of costly equipment is at stake. Understanding and interpreting, a chain of interrelated events, predicted or unpredicted, that may or may not result in a specific state of the system, is the core challenge of this research. The main objective is then to identify which set of input data signals has a significant impact on the set of system state information (i.e. output). Through a cause-effect analysis technique, the proposed technique supports the filtering of unsolicited data that can otherwise clog up the communication and computational capabilities of a standard supervisory control and data acquisition system. The paper analyzes the performance of input variable selection techniques from a series of perspectives. It then expands the categorization and assessment of sensitivity analysis methods in a structured framework that takes into account the relationship between inputs and outputs, the nature of their time series, and the computational effort required. The outcome of this analysis is that established methods have a limited suitability for use by time-critical variable selection applications. By way of a geological drilling monitoring scenario, the suitability of the proposed EventTracker Sensitivity Analysis method for use in high volume and time critical input variable selection problems is demonstrated.E

Computational approaches to shed light on molecular mechanisms in biological processes

Computational approaches based on Molecular Dynamics simulations, Quantum Mechanical methods and 3D Quantitative Structure-Activity Relationships were employed by computational chemistry groups at the University of Milano-Bicocca to study biological processes at the molecular level. The paper reports the methodologies adopted and the results obtained on Aryl hydrocarbon Receptor and homologous PAS proteins mechanisms, the properties of prion protein peptides, the reaction pathway of hydrogenase and peroxidase enzymes and the defibrillogenic activity of tetracyclines. © Springer-Verlag 2007

Weakly Supervised Domain-Specific Color Naming Based on Attention

The majority of existing color naming methods focuses on the eleven basic color terms of the English language. However, in many applications, different sets of color names are used for the accurate description of objects. Labeling data to learn these domain-specific color names is an expensive and laborious task. Therefore, in this article we aim to learn color names from weakly labeled data. For this purpose, we add an attention branch to the color naming network. The attention branch is used to modulate the pixel-wise color naming predictions of the network. In experiments, we illustrate that the attention branch correctly identifies the relevant regions. Furthermore, we show that our method obtains state-of-the-art results for pixel-wise and image-wise classification on the EBAY dataset and is able to learn color names for various domains.Comment: Accepted at ICPR201

Ecosystem properties and principles of living systems as foundation for sustainable agriculture – Critical reviews of environmental assessment tools, key findings and questions from a course process

With increasing demands on limited resources worldwide, there is a growing interest in sustainable patterns of utilisation and production. Ecological agriculture is a response to these concerns. To assess progress and compliance, standard and comprehensive measures of resource requirements, impacts and agro-ecological health are needed. Assessment tools should also be rapid, standardized, userfriendly, meaningful to public policy and applicable to management. Fully considering these requirements confounds the development of integrated methods. Currently, there are many methodologies for monitoring performance, each with its own foundations, assumptions, goals, and outcomes, dependent upon agency agenda or academic orientation. Clearly, a concept of sustainability must address biophysical, ecological, economic, and sociocultural foundations. Assessment indicators and criteria, however, are generally limited, lacking integration, and at times in conflict with one another. A result is that certification criteria, indicators, and assessment methods are not based on a consistent, underlying conceptual framework and often lack a management focus. Ecosystem properties and principles of living systems, including self-organisation, renewal, embeddedness, emergence and commensurate response provide foundation for sustainability assessments and may be appropriate focal points for critical thinking in an evaluation of current methods and standards. A systems framework may also help facilitate a comprehensive approach and promote a context for meaningful discourse. Without holistic accounts, sustainable progress remains an illdefined concept and an elusive goal. Our intent, in the work with this report, was to use systems ecology as a pedagogic basis for learning and discussion to: - Articulate general and common characteristics of living systems. - Identify principles, properties and patterns inherent in natural ecosystems. - Use these findings as foci in a dialogue about attributes of sustainability to: a. develop a model for communicating scientific rationale. b. critically evaluate environmental assessment tools for application in land-use. c. propose appropriate criteria for a comprehensive assessment and expanded definition of ecological land use