Food market analysis: a case study of the Glocal methodology in the Dominican Republic

The present paper provides an insight into the food value chain of three specific sectors (fruit and vegetables, poultry and rice) in the Dominican Republic. The Glocal methodology used for the study combines a global view with local conditions and thus it can be applied to food markets. Each of these food chains is analyzed by following traditional industrial organization theory, based on structure, conduct and performance. Regarding the specific case of the Dominican Republic, different sources of information are used to analyze the weaknesses of the studied chains, including direct interviews. The food value chains of fruit and vegetables, poultry and rice in the Dominican Republic show a lack of structure and they are undergoing changes; however, they also have great opportunities to improve efficiency by making some changes.

A methodology to estimate uncertainty for emission projections through sensitivity analysis

Air pollution abatement policies must be based on quantitative information on current and future emissions of pollutants. As emission projections uncertainties are inevitable and traditional statistical treatments of uncertainty are highly time/resources consuming, a simplified methodology for nonstatistical uncertainty estimation based on sensitivity analysis is presented in this work. The methodology was applied to the “with measures” scenario for Spain, concretely over the 12 highest emitting sectors regarding greenhouse gas and air pollutants emissions. Examples of methodology application for two important sectors (power plants, and agriculture and livestock) are shown and explained in depth. Uncertainty bands were obtained up to 2020 by modifying the driving factors of the 12 selected sectors and the methodology was tested against a recomputed emission trend in a low economic-growth perspective and official figures for 2010, showing a very good performance. Implications: A solid understanding and quantification of uncertainties related to atmospheric emission inventories and projections provide useful information for policy negotiations. However, as many of those uncertainties are irreducible, there is an interest on how they could be managed in order to derive robust policy conclusions. Taking this into account, a method developed to use sensitivity analysis as a source of information to derive nonstatistical uncertainty bands for emission projections is presented and applied to Spain. This method simplifies uncertainty assessment and allows other countries to take advantage of their sensitivity analyses.

Quality of experience of adaptive video streaming: investigation in service parameters and subjective quality assessment methodology

The usage of HTTP adaptive streaming (HAS) has become widely spread in multimedia services. Because it allows the service providers to improve the network resource utilization and user׳s Quality of Experience (QoE). Using this technology, the video playback interruption is reduced since the network and server status in addition to capability of user device, all are taken into account by HAS client to adapt the quality to the current condition. Adaptation can be done using different strategies. In order to provide optimal QoE, the perceptual impact of adaptation strategies from point of view of the user should be studied. However, the time-varying video quality due to the adaptation which usually takes place in a long interval introduces a new type of impairment making the subjective evaluation of adaptive streaming system challenging. The contribution of this paper is two-fold: first, it investigates the testing methodology to evaluate HAS QoE by comparing the subjective experimental outcomes obtained from ACR standardized method and a semi-continuous method developed to evaluate the long sequences. In addition, influence of using audiovisual stimuli to evaluate the video-related impairment is inquired. Second, impact of some of the adaptation technical factors including the quality switching amplitude and chunk size in combination with high range of commercial content type is investigated. The results of this study provide a good insight toward achieving appropriate testing method to evaluate HAS QoE, in addition to designing switching strategies with optimal visual quality.

Location of bioelectricity plants in the Madrid Community based on triticale crop: a multicriteria methodology

This paper presents a work whose objective is, first, to quantify the potential of the triticale biomass existing in each of the agricultural regions in the Madrid Community through a crop simulation model based on regression techniques and multiple correlation. Second, a methodology for defining which area has the best conditions for the installation of electricity plants from biomass has been described and applied. The study used a methodology based on compromise programming in a discrete multicriteria decision method (MDM) context. To make a ranking, the following criteria were taken into account: biomass potential, electric power infrastructure, road networks, protected spaces, and urban nuclei surfaces. The results indicate that, in the case of the Madrid Community, the Campiña region is the most suitable for setting up plants powered by biomass. A minimum of 17,339.9 tons of triticale will be needed to satisfy the requirements of a 2.2 MW power plant. The minimum range of action for obtaining the biomass necessary in Campiña region would be 6.6 km around the municipality of Algete, based on Geographic Information Systems. The total biomass which could be made available in considering this range in this region would be 18,430.68 t.

Methodology for instantaneous average exhaust gas mass flow rate measurement

This paper presents a new methodology for measurement of the instantaneous average exhaust mass flow rate in reciprocating internal combustion engines to be used to determinate real driving emissions on light duty vehicles, as part of a Portable Emission Measurement System (PEMS). Firstly a flow meter, named MIVECO flow meter, was designed based on a Pitot tube adapted to exhaust gases which are characterized by moisture and particle content, rapid changes in flow rate and chemical composition, pulsating and reverse flow at very low engine speed. Then, an off-line methodology was developed to calculate the instantaneous average flow, considering the ?square root error? phenomenon. The paper includes the theoretical fundamentals, the developed flow meter specifications, the calibration tests, the description of the proposed off-line methodology and the results of the validation test carried out in a chassis dynamometer, where the validity of the mass flow meter and the methodology developed are demonstrated.

Protein quantification from complex protein mixtures using a proteomics methodology with single-cell resolution

We have developed an extremely sensitive technique, termed immuno-detection amplified by T7 RNA polymerase (IDAT) that is capable of monitoring proteins, lipids, and metabolites and their modifications at the single-cell level. A double-stranded oligonucleotide containing the T7 promoter is conjugated to an antibody (Ab), and then T7 RNA polymerase is used to amplify RNA from the double-stranded oligonucleotides coupled to the Ab in the Ab-antigen complex. By using this technique, we are able to detect the p185her2/neu receptor from the crude lysate of T6–17 cells at 10−13 dilution, which is 109-fold more sensitive than the conventional ELISA method. Single-chain Fv fragments or complementarity determining region peptides of the Ab also can be substituted for the Ab in IDAT. In a modified protocol, the oligonucleotide has been coupled to an Ab against a common epitope to create a universal detector species. With the linear amplification ability of T7 RNA polymerase, IDAT represents a significant improvement over immuno-PCR in terms of sensitivity and has the potential to provide a robotic platform for proteomics.

A methodology for improving computed individual regressions predictions.

This research proposes a methodology to improve computed individual prediction values provided by an existing regression model without having to change either its parameters or its architecture. In other words, we are interested in achieving more accurate results by adjusting the calculated regression prediction values, without modifying or rebuilding the original regression model. Our proposition is to adjust the regression prediction values using individual reliability estimates that indicate if a single regression prediction is likely to produce an error considered critical by the user of the regression. The proposed method was tested in three sets of experiments using three different types of data. The first set of experiments worked with synthetically produced data, the second with cross sectional data from the public data source UCI Machine Learning Repository and the third with time series data from ISO-NE (Independent System Operator in New England). The experiments with synthetic data were performed to verify how the method behaves in controlled situations. In this case, the outcomes of the experiments produced superior results with respect to predictions improvement for artificially produced cleaner datasets with progressive worsening with the addition of increased random elements. The experiments with real data extracted from UCI and ISO-NE were done to investigate the applicability of the methodology in the real world. The proposed method was able to improve regression prediction values by about 95% of the experiments with real data.

Hayek and complexity: coordination, evolution and methodology in social adaptive systems

The affinity between the work of the Austrian economist Friedrich A. Hayek and the approach of Complexity Economics is widely recognized by the literature. In spite of this, there still is a lack of studies that seek to analyze in depth the relationship between Hayek and complexity. This dissertation is a contribution to the filling of this large gap in the literature. In the first part of the work, we analyze the various periods in the development of Hayek\'s vision of complexity, showing that this vision is strongly present in his works on knowledge, competition, methodology, evolution, and spontaneous order. In the second part, we explore how Hayek was influenced by two of the main precursors of modern complexity theory - cybernetics and general system theory - from the time he was working on his book on theoretical psychology, The Sensory Order (1952), until the end of his intellectual career.

Manager Training and Development Strategy: A Methodology to Link Strategic Initiatives at Washington and Lee University

Washington and Lee University has developed and implemented a strategic plan and performance development initiative for 2007-2017. In concert with the strategic plan and performance development initiative, supportive manager core competencies have been identified. The deliverable for this capstone project is a documented methodology that supports the strategy for the design and implementation of a manager training and development program that ensures needed competencies are available. The author uses survey data to determine training needs and priorities and, through a review of literature, investigates effective strategies to arrive at a successful implementation methodology. The author presents findings and conclusions regarding design implementation methodology for manager training and development.

A methodology for applying Taxonomic Sufficiency and benthic biotic indices in two Mediterranean areas

Biotic indices have been developed to summarise information provided by benthic macroinvertebrates, but their use can require specialized taxonomic expertise as well as a time-consuming operation. Using high taxonomic level in biotic indices reduces sampling processing time but should be considered with caution, since assigning tolerance level to high taxonomic levels may cause uncertainty. A methodology for family level tolerance categorization based on the affinity of each family with disturbed or undisturbed conditions was employed. This family tolerance classification approach was tested in two different areas from Mediterranean Sea affected by sewage discharges. Biotic indices employed at family level responded correctly to sewage presence. However, in areas with different communities among stations and high diversity of species within each family, assigning the same tolerance level to a whole family could imply mistakes. Thus, use of high taxonomic level in biotic indices should be only restricted to areas where homogeneous community is presented and families across sites have similar species composition.

Knowledge spirals, situational leadership and informal learning applied on b-learning methodology

The methodology “b-learning” is a new teaching scenario and it requires the creation, adaptation and application of new learning tools searching the assimilation of new collaborative competences. In this context, it is well known the knowledge spirals, the situational leadership and the informal learning. The knowledge spirals is a basic concept of the knowledge procedure and they are based on that the knowledge increases when a cycle of 4 phases is repeated successively.1) The knowledge is created (for instance, to have an idea); 2) The knowledge is decoded into a format to be easily transmitted; 3) The knowledge is modified to be easily comprehensive and it is used; 4) New knowledge is created. This new knowledge improves the previous one (step 1). Each cycle shows a step of a spiral staircase: by going up the staircase, more knowledge is created. On the other hand, the situational leadership is based on that each person has a maturity degree to develop a specific task and this maturity increases with the experience. Therefore, the teacher (leader) has to adapt the teaching style to the student (subordinate) requirements and in this way, the professional and personal development of the student will increase quickly by improving the results and satisfaction. This educational strategy, finally combined with the informal learning, and in particular the zone of proximal development, and using a learning content management system own in our University, gets a successful and well-evaluated learning activity in Master subjects focused on the collaborative activity of preparation and oral exhibition of short and specific topics affine to these subjects. Therefore, the teacher has a relevant and consultant role of the selected topic and his function is to guide and supervise the work, incorporating many times the previous works done in other courses, as a research tutor or more experienced student. Then, in this work, we show the academic results, grade of interactivity developed in these collaborative tasks, statistics and the satisfaction grade shown by our post-graduate students.

Combined simulation-optimization methodology for the design of environmental conscious absorption systems

This work addresses the optimization of ammonia–water absorption cycles for cooling and refrigeration applications with economic and environmental concerns. Our approach combines the capabilities of process simulation, multi-objective optimization (MOO), cost analysis and life cycle assessment (LCA). The optimization task is posed in mathematical terms as a multi-objective mixed-integer nonlinear program (moMINLP) that seeks to minimize the total annualized cost and environmental impact of the cycle. This moMINLP is solved by an outer-approximation strategy that iterates between primal nonlinear programming (NLP) subproblems with fixed binaries and a tailored mixed-integer linear programming (MILP) model. The capabilities of our approach are illustrated through its application to an ammonia–water absorption cycle used in cooling and refrigeration applications.