Los nuevos centros escolares europeos. Las euro-redes de centros

El progreso y la competitividad de la nueva Europa unida se fundamenta en la educación de todos los ciudadanos de forma que nazca y se consolide una gran sociedad cognitiva; esta sociedad está impregnada de la acción de las tecnologías de la información y la comunicación. Razones de todo tipo justifican su introducción en los centros escolares. Una novedad son los intercambios de experiencias, informaciones, prácticas educativas, etc. entre centros europeos conectados en euro-redes; éstas ofrecen numerosas posibilidades de modernización de los mismos, y de asunción de la dimensión educativo-europea exigida a los estados miembros

Hospitalidad y asistencia en la provincia de León a finales del Antiguo Régimen (1728-1896)

El trabajo consta de dos partes. En la primera analizamos las peculiaridades de la red asistencial en la provincia de León a mediados del siglo XVIII, centrándonos en su distribución territorial, ámbito de actuación y tipo de administración. En la segunda, hemos analizado el mayor centro hospitalario de la provincia en ese momento: el hospital de San Antonio Abad. Nuestro objetivo en este caso ha sido conocer el perfil sociológico de los pacientes allí tratados, atendiendo al sexo, estado civil, edad y procedencia territorial

The effects on European importers' food safety controls in the time of COVID-19

[EN] COVID-19 has highlighted the fragility of the global economic system. In just a few months, the consequences of the pandemic have left their mark on the affected countries at all levels and without exception. This article analyses the profile of food safety notifications reported by European countries in the first five months of 2020. The aim was to detect possible changes in food safety regulations imposed by control authorities that could aggravate the economic impacts of the pandemic. While COVID-19 does not appear to be a foodborne disease, some outbreaks have been linked to imported food, which might have affected the food control behaviour of importing countries. In this study, contingency tables and clustering were used to assess differences between years and notification characteristics and to detect homogeneous groups to help identify how the reported notifications might have changed. In the period considered in this study, the volume of notifications on most imported foodstuffs decreased considerably. This decrease was a direct consequence of the fall in international trade, which might have increased countries' reliance on domestic sources. The COVID-19 crisis has not caused a substantial change in the profile of European countries¿ in terms of the characteristics of reported notifications (product category and risk decision). However, the worst affected countries have replaced border rejections with alerts, which may indicate greater reliance on intra-EU markets.This research was supported by grant RTI2018-093791-B-C22 funded by Ministry of Science (Spain) and European Regional Development FundMartí Selva, ML.; Puertas Medina, RM.; García Alvarez-Coque, JM. (2021). The effects on European importers' food safety controls in the time of COVID-19. Food Control. 125:1-11. https://doi.org/10.1016/j.foodcont.2021.107952S11112

Food Supply without Risk: Multicriteria Analysis of Institutional Conditions of Exporters

[EN] International trade in food knows no borders, hence the need for prevention systems to avoid the consumption of products that are harmful to health. This paper proposes the use of multicriteria risk prevention tools that consider the socioeconomic and institutional conditions of food exporters. We propose the use of three decision-making methods-Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), Elimination et Choix Traduisant la Realite (ELECTRE), and Cross-Efficiency (CE)-to establish a ranking of countries that export cereals to the European Union, based on structural criteria related to the detection of potential associated risks (notifications, food quality, corruption, environmental sustainability in agriculture, and logistics). In addition, the analysis examines whether the wealth and institutional capacity of supplier countries influence their position in the ranking. The research was carried out biannually over the period from 2012-2016, allowing an assessment to be made of the possible stability of the markets. The results reveal that suppliers' rankings based exclusively on aspects related to food risk differ from importers' actual choices determined by micro/macroeconomic features (price, production volume, and economic growth). The rankings obtained by the three proposed methods are not the same, but present certain similarities, with the ability to discern countries according to their level of food risk. The proposed methodology can be applied to support sourcing strategies. In the future, food safety considerations could have increased influence in importing decisions, which would involve further difficulties for low-income countries.Ministry of Science and Innovation (Spain) and European Commission-ERDF. Project "Strengthening innovation policy in the agri-food sector" (RTI2018-093791-B-C22).Puertas Medina, RM.; Martí Selva, ML.; García Alvarez-Coque, JM. (2020). Food Supply without Risk: Multicriteria Analysis of Institutional Conditions of Exporters. International Journal of Environmental research and Public Health. 17(10):1-21. https://doi.org/10.3390/ijerph17103432S1211710Walker, E., & Jones, N. (2002). An assessment of the value of documenting food safety in small and less developed catering businesses. Food Control, 13(4-5), 307-314. doi:10.1016/s0956-7135(02)00036-1Sun, Y.-M., & Ockerman, H. W. (2005). A review of the needs and current applications of hazard analysis and critical control point (HACCP) system in foodservice areas. Food Control, 16(4), 325-332. doi:10.1016/j.foodcont.2004.03.012Rohr, J. R., Barrett, C. B., Civitello, D. J., Craft, M. E., Delius, B., DeLeo, G. A., … Tilman, D. (2019). Emerging human infectious diseases and the links to global food production. Nature Sustainability, 2(6), 445-456. doi:10.1038/s41893-019-0293-3De Jonge, J., van Trijp, J. C. M., van der Lans, I. A., Renes, R. J., & Frewer, L. J. (2008). How trust in institutions and organizations builds general consumer confidence in the safety of food: A decomposition of effects. Appetite, 51(2), 311-317. doi:10.1016/j.appet.2008.03.008Neill, C. L., & Holcomb, R. B. (2019). Does a food safety label matter? Consumer heterogeneity and fresh produce risk perceptions under the Food Safety Modernization Act. Food Policy, 85, 7-14. doi:10.1016/j.foodpol.2019.04.001Wood, V. R., & Robertson, K. R. (2000). Evaluating international markets. International Marketing Review, 17(1), 34-55. doi:10.1108/02651330010314704Jouanjean, M.-A., Maur, J.-C., & Shepherd, B. (2015). Reputation matters: Spillover effects for developing countries in the enforcement of US food safety measures. Food Policy, 55, 81-91. doi:10.1016/j.foodpol.2015.06.001Van Ruth, S. M., Huisman, W., & Luning, P. A. (2017). Food fraud vulnerability and its key factors. Trends in Food Science & Technology, 67, 70-75. doi:10.1016/j.tifs.2017.06.017Baylis, K., Nogueira, L., & Pace, K. (2010). Food Import Refusals: Evidence from the European Union. American Journal of Agricultural Economics, 93(2), 566-572. doi:10.1093/ajae/aaq149Bouzembrak, Y., & Marvin, H. J. P. (2016). Prediction of food fraud type using data from Rapid Alert System for Food and Feed (RASFF) and Bayesian network modelling. Food Control, 61, 180-187. doi:10.1016/j.foodcont.2015.09.026Tudela-Marco, L., Garcia-Alvarez-Coque, J. M., & Martí-Selva, L. (2016). Do EU Member States Apply Food Standards Uniformly? A Look at Fruit and Vegetable Safety Notifications. JCMS: Journal of Common Market Studies, 55(2), 387-405. doi:10.1111/jcms.12503Verhaelen, K., Bauer, A., Günther, F., Müller, B., Nist, M., Ülker Celik, B., … Wallner, P. (2018). Anticipation of food safety and fraud issues: ISAR - A new screening tool to monitor food prices and commodity flows. Food Control, 94, 93-101. doi:10.1016/j.foodcont.2018.06.029Garcia‐Alvarez‐Coque, J., Taghouti, I., & Martinez‐Gomez, V. (2020). Changes in Aflatoxin Standards: Implications for EU Border Controls of Nut Imports. Applied Economic Perspectives and Policy, 42(3), 524-541. doi:10.1093/aepp/ppy036Fischer, A. R. H., de Jong, A. E. I., de Jonge, R., Frewer, L. J., & Nauta, M. J. (2005). Improving Food Safety in the Domestic Environment: The Need for a Transdisciplinary Approach. Risk Analysis, 25(3), 503-517. doi:10.1111/j.1539-6924.2005.00618.xHoughton, J. R., Rowe, G., Frewer, L. J., Van Kleef, E., Chryssochoidis, G., Kehagia, O., … Strada, A. (2008). The quality of food risk management in Europe: Perspectives and priorities. Food Policy, 33(1), 13-26. doi:10.1016/j.foodpol.2007.05.001Demortain, D. (2012). Enabling global principle-based regulation: The case of risk analysis in the Codex Alimentarius. Regulation & Governance, 6(2), 207-224. doi:10.1111/j.1748-5991.2012.01144.xFAZIL, A., RAJIC, A., SANCHEZ, J., & MCEWEN, S. (2008). Choices, Choices: The Application of Multi-Criteria Decision Analysis to a Food Safety Decision-Making Problem. Journal of Food Protection, 71(11), 2323-2333. doi:10.4315/0362-028x-71.11.2323Ruzante, J. M., Davidson, V. J., Caswell, J., Fazil, A., Cranfield, J. A. L., Henson, S. J., … Farber, J. M. (2010). A Multifactorial Risk Prioritization Framework for Foodborne Pathogens. Risk Analysis, 30(5), 724-742. doi:10.1111/j.1539-6924.2009.01278.xMazzocchi, M., Ragona, M., & Zanoli, A. (2013). A fuzzy multi-criteria approach for the ex-ante impact assessment of food safety policies. Food Policy, 38, 177-189. doi:10.1016/j.foodpol.2012.11.011Govindan, K., Kadziński, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129-145. doi:10.1016/j.omega.2016.10.004Segura, M., Maroto, C., & Segura, B. (2019). Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies. Sustainability, 11(21), 5875. doi:10.3390/su11215875Lau, H., Nakandala, D., & Shum, P. K. (2018). A business process decision model for fresh-food supplier evaluation. Business Process Management Journal, 24(3), 716-744. doi:10.1108/bpmj-01-2016-0015Garcia-Alvarez-Coque, J.-M., Abdullateef, O., Fenollosa, L., Ribal, J., Sanjuan, N., & Soriano, J. M. (2020). Integrating sustainability into the multi-criteria assessment of urban dietary patterns. Renewable Agriculture and Food Systems, 36(1), 69-76. doi:10.1017/s174217051900053xGrant, W. (2012). Economic patriotism in European agriculture. Journal of European Public Policy, 19(3), 420-434. doi:10.1080/13501763.2011.640797Maye, D., & Kirwan, J. (2013). Food security: A fractured consensus. Journal of Rural Studies, 29, 1-6. doi:10.1016/j.jrurstud.2012.12.001Anthony, R. (2011). Taming the Unruly Side of Ethics: Overcoming Challenges of a Bottom-Up Approach to Ethics in the Areas of Food Policy and Climate Change. Journal of Agricultural and Environmental Ethics, 25(6), 813-841. doi:10.1007/s10806-011-9358-7MacMillan, T., & Dowler, E. (2011). Just and Sustainable? Examining the Rhetoric and Potential Realities of UK Food Security. Journal of Agricultural and Environmental Ethics, 25(2), 181-204. doi:10.1007/s10806-011-9304-8Jaud, M., Cadot, O., & Suwa-Eisenmann, A. (2013). Do food scares explain supplier concentration? An analysis of EU agri-food imports. European Review of Agricultural Economics, 40(5), 873-890. doi:10.1093/erae/jbs038Spink, J., Fortin, N. D., Moyer, D. C., Miao, H., & Wu, Y. (2016). Food Fraud Prevention: Policy, Strategy, and Decision-Making – Implementation Steps for a Government Agency or Industry. CHIMIA International Journal for Chemistry, 70(5), 320-328. doi:10.2533/chimia.2016.320Van Ruth, S. M., Luning, P. A., Silvis, I. C. J., Yang, Y., & Huisman, W. (2018). Differences in fraud vulnerability in various food supply chains and their tiers. Food Control, 84, 375-381. doi:10.1016/j.foodcont.2017.08.020Xidonas, P., & Psarras, J. (2009). Equity portfolio management within the MCDM frame: a literature review. International Journal of Banking, Accounting and Finance, 1(3), 285. doi:10.1504/ijbaaf.2009.022717Melo, M. T., Nickel, S., & Saldanha-da-Gama, F. (2009). Facility location and supply chain management – A review. European Journal of Operational Research, 196(2), 401-412. doi:10.1016/j.ejor.2008.05.007Mandic, K., Delibasic, B., Knezevic, S., & Benkovic, S. (2014). Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods. Economic Modelling, 43, 30-37. doi:10.1016/j.econmod.2014.07.036Uygun, Ö., Kaçamak, H., & Kahraman, Ü. A. (2015). An integrated DEMATEL and Fuzzy ANP techniques for evaluation and selection of outsourcing provider for a telecommunication company. Computers & Industrial Engineering, 86, 137-146. doi:10.1016/j.cie.2014.09.014Wanke, P., Azad, M. D. A. K., & Barros, C. P. (2016). Predicting efficiency in Malaysian Islamic banks: A two-stage TOPSIS and neural networks approach. Research in International Business and Finance, 36, 485-498. doi:10.1016/j.ribaf.2015.10.002Stojčić, M., Zavadskas, E., Pamučar, D., Stević, Ž., & Mardani, A. (2019). Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008–2018. Symmetry, 11(3), 350. doi:10.3390/sym11030350Xu, L., Shah, S. A. A., Zameer, H., & Solangi, Y. A. (2019). Evaluating renewable energy sources for implementing the hydrogen economy in Pakistan: a two-stage fuzzy MCDM approach. Environmental Science and Pollution Research, 26(32), 33202-33215. doi:10.1007/s11356-019-06431-0Huang, I. B., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends. Science of The Total Environment, 409(19), 3578-3594. doi:10.1016/j.scitotenv.2011.06.022Pons, O., de la Fuente, A., & Aguado, A. (2016). The Use of MIVES as a Sustainability Assessment MCDM Method for Architecture and Civil Engineering Applications. Sustainability, 8(5), 460. doi:10.3390/su8050460Shishegaran, A., Shishegaran, A., Mazzulla, G., & Forciniti, C. (2020). A Novel Approach for a Sustainability Evaluation of Developing System Interchange: The Case Study of the Sheikhfazolah-Yadegar Interchange, Tehran, Iran. International Journal of Environmental Research and Public Health, 17(2), 435. doi:10.3390/ijerph17020435Wu, H.-Y., Chen, J.-K., Chen, I.-S., & Zhuo, H.-H. (2012). Ranking universities based on performance evaluation by a hybrid MCDM model. Measurement, 45(5), 856-880. doi:10.1016/j.measurement.2012.02.009Shakouri G., H., & Tavassoli N., Y. (2012). Implementation of a hybrid fuzzy system as a decision support process: A FAHP–FMCDM–FIS composition. Expert Systems with Applications, 39(3), 3682-3691. doi:10.1016/j.eswa.2011.09.063Mavi, R. K., Goh, M., & Mavi, N. K. (2016). Supplier Selection with Shannon Entropy and Fuzzy TOPSIS in the Context of Supply Chain Risk Management. Procedia - Social and Behavioral Sciences, 235, 216-225. doi:10.1016/j.sbspro.2016.11.017Montgomery, B., Dragićević, S., Dujmović, J., & Schmidt, M. (2016). A GIS-based Logic Scoring of Preference method for evaluation of land capability and suitability for agriculture. Computers and Electronics in Agriculture, 124, 340-353. doi:10.1016/j.compag.2016.04.013Debnath, A., Roy, J., Kar, S., Zavadskas, E., & Antucheviciene, J. (2017). A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products. Sustainability, 9(8), 1302. doi:10.3390/su9081302Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., Ghorbani, M. A., & Shahbazi, F. (2018). Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops. Geoderma, 310, 178-190. doi:10.1016/j.geoderma.2017.09.012Rostamzadeh, R., Ghorabaee, M. K., Govindan, K., Esmaeili, A., & Nobar, H. B. K. (2018). Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach. Journal of Cleaner Production, 175, 651-669. doi:10.1016/j.jclepro.2017.12.071Raut, R. D., Gardas, B. B., Kharat, M., & Narkhede, B. (2018). Modeling the drivers of post-harvest losses – MCDM approach. Computers and Electronics in Agriculture, 154, 426-433. doi:10.1016/j.compag.2018.09.035Qureshi, M. R. N., Singh, R. K., & Hasan, M. A. (2017). Decision support model to select crop pattern for sustainable agricultural practices using fuzzy MCDM. Environment, Development and Sustainability, 20(2), 641-659. doi:10.1007/s10668-016-9903-7Srinivasa Rao, C., Kareemulla, K., Krishnan, P., Murthy, G. R. K., Ramesh, P., Ananthan, P. S., & Joshi, P. K. (2019). Agro-ecosystem based sustainability indicators for climate resilient agriculture in India: A conceptual framework. Ecological Indicators, 105, 621-633. doi:10.1016/j.ecolind.2018.06.038Paul, M., Negahban-Azar, M., Shirmohammadi, A., & Montas, H. (2020). Assessment of agricultural land suitability for irrigation with reclaimed water using geospatial multi-criteria decision analysis. Agricultural Water Management, 231, 105987. doi:10.1016/j.agwat.2019.105987Balezentis, T., Chen, X., Galnaityte, A., & Namiotko, V. (2020). Optimizing crop mix with respect to economic and environmental constraints: An integrated MCDM approach. Science of The Total Environment, 705, 135896. doi:10.1016/j.scitotenv.2019.135896Jahan, A., & Edwards, K. L. (2013). VIKOR method for material selection problems with interval numbers and target-based criteria. Materials & Design, 47, 759-765. doi:10.1016/j.matdes.2012.12.072Pourhejazy, P., Kwon, O., Chang, Y.-T., & Park, H. (2017). Evaluating Resiliency of Supply Chain Network: A Data Envelopment Analysis Approach. Sustainability, 9(2), 255. doi:10.3390/su9020255Stewart, T. J. (1996). Relationships between Data Envelopment Analysis and Multicriteria Decision Analysis. Journal of the Operational Research Society, 47(5), 654-665. doi:10.1057/jors.1996.77Li, X.-B., & Reeves, G. R. (1999). A multiple criteria approach to data envelopment analysis. European Journal of Operational Research, 115(3), 507-517. doi:10.1016/s0377-2217(98)00130-1Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). STATE OF ART SURVEYS OF OVERVIEWS ON MCDM/MADM METHODS. Technological and Economic Development of Economy, 20(1), 165-179. doi:10.3846/20294913.2014.892037Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2017). A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Materials & Design, 121, 237-253. doi:10.1016/j.matdes.2017.02.041Bouyssou, D. (1999). Using DEA as a tool for MCDM: some remarks. Journal of the Operational Research Society, 50(9), 974-978. doi:10.1057/palgrave.jors.2600800Özcan, T., Çelebi, N., & Esnaf, Ş. (2011). Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem. Expert Systems with Applications, 38(8), 9773-9779. doi:10.1016/j.eswa.2011.02.022LOKEN, E. (2007). Use of multicriteria decision analysis methods for energy planning problems. Renewable and Sustainable Energy Reviews, 11(7), 1584-1595. doi:10.1016/j.rser.2005.11.005Darji, V. P., & Rao, R. V. (2014). Intelligent Multi Criteria Decision Making Methods for Material Selection in Sugar Industry. Procedia Materials Science, 5, 2585-2594. doi:10.1016/j.mspro.2014.07.519Ceballos, B., Lamata, M. T., & Pelta, D. A. (2016). A comparative analysis of multi-criteria decision-making methods. Progress in Artificial Intelligence, 5(4), 315-322. doi:10.1007/s13748-016-0093-1Sen, B., Bhattacharjee, P., & Mandal, U. K. (2016). A comparative study of some prominent multi criteria decision making methods for connecting rod material selection. Perspectives in Science, 8, 547-549. doi:10.1016/j.pisc.2016.06.016Wu, D. (2006). A note on DEA efficiency assessment using ideal point: An improvement of Wang and Luo’s model. Applied Mathematics and Computation, 183(2), 819-830. doi:10.1016/j.amc.2006.06.030Kou, G., Peng, Y., & Wang, G. (2014). Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Information Sciences, 275, 1-12. doi:10.1016/j.ins.2014.02.137Roy, B. (1991). The outranking approach and the foundations of electre methods. Theory and Decision, 31(1), 49-73. doi:10.1007/bf00134132YOON, K., & HWANG, C.-L. (1985). Manufacturing plant location analysis by multiple attribute decision making: part I—single-plant strategy. International Journal of Production Research, 23(2), 345-359. doi:10.1080/00207548508904712Doyle, J., & Green, R. (1994). Efficiency and Cross-efficiency in DEA: Derivations, Meanings and Uses. Journal of the Operational Research Society, 45(5), 567-578. doi:10.1057/jors.1994.84Martí, L., Martín, J. C., & Puertas, R. (2017). A Dea-Logistics Performance Index. Journal of Applied Economics, 20(1), 169-192. doi:10.1016/s1514-0326(17)30008-9Canadá y la UE: Si Quierohttps://www.Euroganadería.euKARABIYIK, C., & KUTLU KARABIYIK, B. (2018). Benchmarking International Trade Performance of OECD Countries: TOPSIS and AHP Approaches. Gaziantep University Journal of Social Sciences. doi:10.21547/jss.267381Lin, M.-C., Wang, C.-C., Chen, M.-S., & Chang, C. A. (2008). Using AHP and TOPSIS approaches in customer-driven product design process. Computers in Industry, 59(1), 17-31. doi:10.1016/j.compind.2007.05.013Lourenzutti, R., & Krohling, R. A. (2016). A generalized TOPSIS method for group decision making with heterogeneous information in a dynamic environment. Information Sciences, 330, 1-18. doi:10.1016/j.ins.2015.10.005Roy, B. (1968). Classement et choix en présence de points de vue multiples. Revue française d’informatique et de recherche opérationnelle, 2(8), 57-75. doi:10.1051/ro/196802v100571Jaini, N., & Utyuzhnikov, S. (2016). Trade-off ranking method for multi-criteria decision analysis. Journal of Multi-Criteria Decision Analysis, 24(3-4), e1600. doi:10.1002/mcda.1600Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253. doi:10.2307/2343100Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. doi:10.1016/0377-2217(78)90138-8Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078-1092. doi:10.1287/mnsc.30.9.1078Angulo-Meza, L., & Lins, M. P. E. (2002). Annals of Operations Research, 116(1/4), 225-242. doi:10.1023/a:1021340616758Falagario, M., Sciancalepore, F., Costantino, N., & Pietroforte, R. (2012). Using a DEA-cross efficiency approach in public procurement tenders. European Journal of Operational Research, 218(2), 523-529. doi:10.1016/j.ejor.2011.10.031Puertas, R., & Marti, L. (2019). Sustainability in Universities: DEA-GreenMetric. Sustainability, 11(14), 3766. doi:10.3390/su1114376

Innovation and sectoral linkages in the agri-food system in the Valencian Community

This paper aims to analyze the innovative effort of the agri-food system (AFS) in the Valencian Autonomous Community (VC), Spain, estimating the intensity of innovation in each subsector of the AFS. The analysis distinguishes between the direct and indirect (or induced) innovation intensities incorporated by the acquisition of inputs from other subsectors produced in the VC or in the rest of Spain. The methodology employed is based on the input-output framework combined with data of technological innovation in enterprises. This methodology provides the novelty of been applied to a region the VC and not to a country as it is usually done. The results show that the weight of intersectoral flows in the total innovation effort of the AFS is significant with marked differences between primary and food industry. In most activities, embodied knowledge in inputs purchased from Spain is greater than embodied knowledge of inputs produced inside the region.Authors would like to thank the Ministry of Science and innovation for its support for this paper (Project AGRINNOVA; reference: AGL2009-13303-C02-02).García Alvarez-Coque, JM.; Alba ., MF.; López-García Usach, T. (2012). Innovation and sectoral linkages in the agri-food system in the Valencian Community. SPANISH JOURNAL OF AGRICULTURAL RESEARCH. REVISTA DE INVESTIGACION AGRARIA. 10(1):18-28. https://doi.org/10.5424/sjar/2012101-207-11S1828101McKENZIE, D., & O’NIONS, R. K. (1991). Partial Melt Distributions from Inversion of Rare Earth Element Concentrations. Journal of Petrology, 32(5), 1021-1091. doi:10.1093/petrology/32.5.102

Envy and habits : panel data estimates of interdependent preferences

We estimate the importance of preference interdependence from consumption choices. Our strategy follows the literature that tests the constraints imposed by optimality in the evolution of individual consumption. We derive a Euler equation from a preference specifi cation that allows for non-separabilities across households and across time. The introduction of habits and envy places additional restrictions on the evolution of the optimal consumption path. We use a unique data set that follows a sample of 3,200 households for up to eight consecutive quarters to test these restrictions. Our estimates suggest that, if one defi nes utility over consumption services, a large fraction of these services is relative, with one-quarter of the weight placed in the consumption of the reference group and more than one-third of the weight placed in the agent’s past consumptionEste trabajo analiza el efecto de los hábitos y la envidia en las decisiones de consumo del hogar, con la fi nalidad de contrastar la importancia de los supuestos de separabilidad intertemporal y entre hogares admitidos tradicionalmente en la literatura de consumo. Para ello, derivamos una ecuación de Euler bajo una estructura de preferencias que no incorpora el supuesto de separabilidad intertemporal y entre familias. Los resultados, obtenidos a partir de los datos de panel de la Encuesta Continua de Presupuestos Familiares, muestran que una cuarta parte de la utilidad del consumo se obtiene como resultado de comparar el consumo presente con el del grupo de referencia y más de un tercio de dicha utilidad se deriva de la relación con el consumo del periodo anterio

Fingolimod phosphate protection against mitochondrial damage in neuronal cells

Background: Major role of oxidative stress in the pathogenesis of neurodegenerative diseases have been suggested, being mitochondria one of the main sources of ROS. Aim: In the present work, we have studied the antioxidant effect of fingolimod phosphate (FP) on neuronal mitochondrial function and morphology using a model of mitochondrial oxidative damage induced by menadione (Vitk3). Methods: SN4741 neuronal cells were grown (70-80% confluence) and used as control (non-treated cells) or treated cells with Vitk3 15 µM alone or in presence of FP 50 nM during 4 hours. Mitochondrial membrane potential (MMP), cytochrome c oxidase (COX) activity, mitochondrial oxygen consumption rate (OCR), mitochondrial distribution (MTG) and morphology (EM) were analysed. Statistical differences were determined using one-way ANOVA. Results: Vitk3 incubation produces a dramatical decrease in MMP compared to control (43.7 %); this can be almost totally reverted by the co-incubation of Vitk3 in presence of FP (p<0.05). A 20.7 % decrease in COX activity has been found after Vitk3 incubation, again this effect was counteracted when Vitk3 and FP are combined, restoring COX activity to control levels (p<0.05). Vitk3 incubation triggers initially an increase in OCR, decreasing dramatically (61%) after 4 hours. In experiments co-incubating Vitk3 in presence of FP, the OCR decrease found was reduced to only 17% (p<0.05). In experiments with MitoTracker™ Green, we found a change in the network pattern distribution after Vitk3 administration that partially disappears when co-incubated in presence of FP. Almost all the mitochondria treated with Vitk3 show ultrastructural alterations at the electron microscopy level while normal mitochondria can be found when Vitk3 and FP are combined. Conclusion: FP protects against the mitochondrial damage induced by Vitk3, as seen by the results obtained in mitochondrial functional markers, distribution and morphology.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. PS13/14: Study of the non-immunological mechanisms of action of Gilenya (Fingolimod) as therapeutic tool in Multiple Sclerosis and/or other neurodegenerative diseases. Novartis Farmacéutica S.A

Measuring Technology Platforms impact with search data and web scraping

Resumen de la comunicación[EN] In recent years, European research policies and priorities in the agricultural sector have been developed through industry-based partnerships sponsored by the European Commission (EC). In 2004, the EC regulated a form of partnership called European Technology Platform (ETP) with the aim to define research agendas that would attract private investment. Monitoring the impact and performance of public policies, such as the implementation of ETPs, is basic for policy-makers. However, assessing the performance of ETPs frequently result into costly efforts given the current lack of indicators to monitor their variety of activities. In addition, since most ETPs have been set up recently it is difficult to assess their results, which are typically revealed after some time and take a considerable amount of time to be captured and processed with traditional methods such as surveys. In this study, we propose to assess the dynamics of ETPs through measures based on online information, given that it is fresh, available in real-time and is a publicly reflect of the activities of organizations. We firstly consider an ETP as an innovation intermediary and define its functions according to innovation literature. Then, we enumerate the particular activities within each function in which the ETP may be involved. To monitor such functions and activities, some indicators based on online data are proposed. This conceptual basis has been put into practice with a particular case study based on the agri-food technology platform “TP Organics”. Preliminary results show that the online-based indicators are able to measure the level of activity of the platform, if its scope is expanding or reducing, and how the importance of the different functions has evolved over time.Blazquez, D.; Domenech, J.; García Alvarez-Coque, JM. (2018). Measuring Technology Platforms impact with search data and web scraping. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat Politècnica de València. 259-259. https://doi.org/10.4995/CARMA2018.2018.8363OCS25925

Ethical certification in the Spanish agrifood industry: An alternative paradigm?

[EN] The agrifood sector belongs to traditional industries often supported by the national governments. The quality of the output is directly related to human health and, therefore, several initiatives within the EU have been introduced. These initiatives support the consciousness of the broad public, including the individual agrifood businesses. Besides the marketing standards, geographical indications and organic farming, there are also national and private certification schemes. All these tendencies aim to promote the socio-ethical principles of the business to support the non-monetary issues related to the agrifood sector. This paper provides a closer exploration of the socio-ethical aspects of companies in the Spanish agrifood sector. Any awareness of these principles in the daily business routine can be considered as a potential competitive advantage for an individual company. The objective of the paper is to examine whether there are significant differences among individual sub-industries within the Spanish agrifood sector in terms of social and ethical aspects. A sample of 66,047 different agrifood companies in the year 2012 was examined. Results of empirical tests prove that there are significant differences between the agricultural producers, manufacturers, wholesalers, and retailers.Nováková, K.; Compes López, R.; García Alvarez-Coque, JM. (2016). Ethical certification in the Spanish agrifood industry: An alternative paradigm?. Society and Economy (Online). 38(3):399-411. doi:10.1556/204.2016.38.3.839941138