satellite technologies to support the sustainability of agricultural production

Precision farming is a form of multidisciplinary and technologically advanced agriculture, which recourses to machines equipped with "intelligent systems," able to dose the productive factors (fertilizers, pesticides, etc.) according to the real needs of the homogeneous areas constituent to the plot (Verhagen and Bouma, Modeling soil variability. In: Pierce FJ, Sadler EJ (eds) The state of site specific management for agriculture. ASA Publications, 1997)

Who leads research productivity growth? Guidelines for R&D policy-makers

[EN] This paper evaluates to what extent policy-makers have been able to promote the creation and consolidation of comprehensive research groups that contribute to the implementation of a successful innovation system. Malmquist productivity indices are applied in the case of the Spanish Food Technology Program, finding that a large size and a comprehensive multi-dimensional research output are the key features of the leading groups exhibiting high efficiency and productivity levels. While identifying these groups as benchmarks, we conclude that the financial grants allocated by the program, typically aimed at small-sized and partially oriented research groups, have not succeeded in reorienting them in time so as to overcome their limitations. We suggest that this methodology offers relevant conclusions to policy evaluation methods, helping policy-makers to readapt and reorient policies and their associated means, most notably resource allocation (financial schemes), to better respond to the actual needs of research groups in their search for excellence (micro-level perspective), and to adapt future policy design to the achievement of medium-long term policy objectives (meso and macro-level).Jiménez Saez, F.; Zabala Iturriagagoitia, JM.; Zofio, JL. (2013). Who leads research productivity growth? Guidelines for R&D policy-makers. Scientometrics. 94(1):273-303. doi:10.1007/s11192-012-0763-0S273303941Abbring, J. H., & Heckman, J. J. (2008). Dynamic policy analysis. In L. Mátyás & P. Sevestre (Eds.), The econometrics of panel data (3rd ed., pp. 795–863). Heidelberg: Springer.Acosta Ballesteros, J., & Modrego Rico, A. (2001). 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Regulation of immunity during visceral Leishmania infection

Unicellular eukaryotes of the genus Leishmania are collectively responsible for a heterogeneous group of diseases known as leishmaniasis. The visceral form of leishmaniasis, caused by L. donovani or L. infantum, is a devastating condition, claiming 20,000 to 40,000 lives annually, with particular incidence in some of the poorest regions of the world. Immunity to Leishmania depends on the development of protective type I immune responses capable of activating infected phagocytes to kill intracellular amastigotes. However, despite the induction of protective responses, disease progresses due to a multitude of factors that impede an optimal response. These include the action of suppressive cytokines, exhaustion of specific T cells, loss of lymphoid tissue architecture and a defective humoral response. We will review how these responses are orchestrated during the course of infection, including both early and chronic stages, focusing on the spleen and the liver, which are the main target organs of visceral Leishmania in the host. A comprehensive understanding of the immune events that occur during visceral Leishmania infection is crucial for the implementation of immunotherapeutic approaches that complement the current anti-Leishmania chemotherapy and the development of effective vaccines to prevent disease.The research leading to these results has received funding from the European Community’s Seventh Framework Programme under grant agreement No.602773 (Project KINDRED). VR is supported by a post-doctoral fellowship granted by the KINDReD consortium. RS thanks the Foundation for Science and Technology (FCT) for an Investigator Grant (IF/00021/2014). This work was supported by grants to JE from ANR (LEISH-APO, France), Partenariat Hubert Curien (PHC) (program Volubilis, MA/11/262). JE acknowledges the support of the Canada Research Chair Program

Estimation of banking technology under credit uncertainty

Credit risk is crucial to understanding banks’ production technology and should be explicitly accounted for when modeling the latter. The banking literature has largely accounted for risk usingex-post realizations of banks’ uncertain outputs and the variables intended to capture risk. This is equivalent to estimating an ex-post realization of bank’s production technology which, however, may not reflect optimality conditions that banks seek to satisfy under uncertainty. The ex-post estimates of technology are likely to be biased and inconsistent, and one thus may call into question the reliability of the results regarding banks’ technological characteristics broadly reported in the literature. However, the extent to which these concerns are relevant for policy analysis is an empirical question. In this paper, we offer an alternative methodology to estimate banks’ production technology based on the ex-ante cost function. We model credit uncertainty explicitly by recognizing that bank managers minimize costs subject to given expected outputs and credit risk. We estimate unobservable expected outputs and associated credit risk levels from banks’ supply functions via nonparametric kernel methods. We apply this framework to estimate production technology of U.S. commercial banks during the period from 2001 to 2010 and contrast the new estimates with those based on the ex-post models widely employed in the literature