Setting competitiveness indicators using BSC and ANP

[EN] In this paper a new approach to assess companies' competitiveness performance in an efficient and reliable way is presented. It introduces a rigorous methodology, based on multi-criteria techniques, which seeks to assist managers of companies within a specific industrial sector in providing information about their relative position in order to define improvement action plans. The approach combines the use of the analytic network process (ANP) method with the balanced scorecard (BSC) to achieve competitiveness indicators. The ANP method allows the aggregation of experts judgments on each of the selected indicators used into one company competitiveness index (CCI). To demonstrate the goodness of the methodology, a case study of the plastic sector of Venezuela has been carried out. Three companies have been analysed using the CCI proposed. The participating experts agreed that the methodology is useful and an improvement from current competitiveness measurement techniques. They found the results obtained coherent and the use of resources significantly less than in other methods.Poveda Bautista, R.; Baptista, DC.; García Melón, M. (2012). Setting competitiveness indicators using BSC and ANP. International Journal of Production Research. 50(17):4738-4752. doi:10.1080/00207543.2012.657964S47384752501

Propuestas para una reforma laboral democrática

Este trabajo, presenta trece propuestas complementarias sobre los temas centrales de la reforma laboral: la contracción individual y colectiva, con si variable de "subcontratación"; la transparencia con la proposición concreta de creación del registro nacional de contratos y sindicatos; los salarios y la jornada laboral, temas clave en el proyecto de país de la izquierda democrátic

Revealing the last 13,500 years of environmental history from the multiproxy record of a mountain lake (Lago Enol, northern Iberian Peninsula)

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s10933-009-9387-7.We present the Holocene sequence from Lago Enol (43°16′N, 4°59′W, 1,070 m a.s.l.), Cantabrian Mountains, northern Spain. A multiproxy analysis provided comprehensive information about regional humidity and temperature changes. The analysis included sedimentological descriptions, physical properties, organic carbon and carbonate content, mineralogy and geochemical composition together with biological proxies including diatom and ostracod assemblages. A detailed pollen study enabled reconstruction of variations in vegetation cover, which were interpreted in the context of climate changes and human impact. Four distinct stages were recognized for the last 13,500 years: (1) a cold and dry episode that includes the Younger Dryas event (13,500–11,600 cal. year BP); (2) a humid and warmer period characterizing the onset of the Holocene (11,600–8,700 cal. year BP); (3) a tendency toward a drier climate during the middle Holocene (8,700–4,650 cal. year BP); and (4) a return to humid conditions following landscape modification by human activity (pastoral activities, deforestation) in the late Holocene (4,650–2,200 cal. year BP). Superimposed on relatively stable landscape conditions (e.g. maintenance of well established forests), the typical environmental variability of the southern European region is observed at this site.The Spanish Inter-Ministry Commission of Science and Technology (CICYT), the Spanish National Parks agency, the European Commission, the Spanish Ministry of Science, and the European Social Fund

Revealing the last 13,500 years of environmental history from the multiproxy record of a mountain lake (Lago Enol, northern Iberian Peninsula)

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s10933-009-9387-7.We present the Holocene sequence from Lago Enol (43°16′N, 4°59′W, 1,070 m a.s.l.), Cantabrian Mountains, northern Spain. A multiproxy analysis provided comprehensive information about regional humidity and temperature changes. The analysis included sedimentological descriptions, physical properties, organic carbon and carbonate content, mineralogy and geochemical composition together with biological proxies including diatom and ostracod assemblages. A detailed pollen study enabled reconstruction of variations in vegetation cover, which were interpreted in the context of climate changes and human impact. Four distinct stages were recognized for the last 13,500 years: (1) a cold and dry episode that includes the Younger Dryas event (13,500–11,600 cal. year BP); (2) a humid and warmer period characterizing the onset of the Holocene (11,600–8,700 cal. year BP); (3) a tendency toward a drier climate during the middle Holocene (8,700–4,650 cal. year BP); and (4) a return to humid conditions following landscape modification by human activity (pastoral activities, deforestation) in the late Holocene (4,650–2,200 cal. year BP). Superimposed on relatively stable landscape conditions (e.g. maintenance of well established forests), the typical environmental variability of the southern European region is observed at this site.The Spanish Inter-Ministry Commission of Science and Technology (CICYT), the Spanish National Parks agency, the European Commission, the Spanish Ministry of Science, and the European Social Fund

Effect of COMBinAtion therapy with remote ischemic conditioning and exenatide on the Myocardial Infarct size: a two-by-two factorial randomized trial (COMBAT-MI)

Remote ischemic conditioning (RIC) and the GLP-1 analog exenatide activate different cardioprotective pathways and may have additive effects on infarct size (IS). Here, we aimed to assess the efficacy of RIC as compared with sham procedure, and of exenatide, as compared with placebo, and the interaction between both, to reduce IS in humans. We designed a two-by-two factorial, randomized controlled, blinded, multicenter, clinical trial. Patients with ST-segment elevation myocardial infarction receiving primary percutaneous coronary intervention (PPCI) within 6 h of symptoms were randomized to RIC or sham procedure and exenatide or matching placebo. The primary outcome was IS measured by late gadolinium enhancement in cardiac magnetic resonance performed 3–7 days after PPCI. The secondary outcomes were myocardial salvage index, transmurality index, left ventricular ejection fraction and relative microvascular obstruction volume. A total of 378 patients were randomly allocated, and after applying exclusion criteria, 222 patients were available for analysis. There were no significant interactions between the two randomization factors on the primary or secondary outcomes. IS was similar between groups for the RIC (24 ± 11.8% in the RIC group vs 23.7 ± 10.9% in the sham group, P = 0.827) and the exenatide hypotheses (25.1 ± 11.5% in the exenatide group vs 22.5 ± 10.9% in the placebo group, P = 0.092). There were no effects with either RIC or exenatide on the secondary outcomes. Unexpected adverse events or side effects of RIC and exenatide were not observed. In conclusion, neither RIC nor exenatide, or its combination, were able to reduce IS in STEMI patients when administered as an adjunct to PPCI

A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

BackgroundThe clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal.Methodology/Principal FindingsNon-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification.Conclusions/SignificanceWe show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing

Efficacy and safety of a multifactor intervention to improve therapeutic adherence in patients with chronic obstructive pulmonary disease (COPD): protocol for the ICEPOC study

<p>Abstract</p> <p>Background</p> <p>Low therapeutic adherence to medication is very common. Clinical effectiveness is related to dose rate and route of administration and so poor therapeutic adherence can reduce the clinical benefit of treatment. The therapeutic adherence of patients with chronic obstructive pulmonary disease (COPD) is extremely poor according to most studies. The research about COPD adherence has mainly focussed on quantifying its effect, and few studies have researched factors that affect non-adherence. Our study will evaluate the effectiveness of a multifactor intervention to improve the therapeutic adherence of COPD patients.</p> <p>Methods/Design</p> <p>A randomized controlled clinical trial with 140 COPD diagnosed patients selected by a non-probabilistic method of sampling. Subjects will be randomly allocated into two groups, using the block randomization technique. Every patient in each group will be visited four times during the year of the study. Intervention: Motivational aspects related to adherence (beliefs and behaviour): group and individual interviews; cognitive aspects: information about illness; skills: inhaled technique training. Reinforcement of the cognitive-emotional aspects and inhaled technique training will be carried out in all visits of the intervention group.</p> <p>Discussion</p> <p>Adherence to a prescribed treatment involves a behavioural change. Cognitive, emotional and motivational aspects influence this change and so we consider the best intervention procedure to improve adherence would be a cognitive and emotional strategy which could be applied in daily clinical practice. Our hypothesis is that the application of a multifactor intervention (COPD information, dose reminders and reinforcing audiovisual material, motivational aspects and inhalation technique training) to COPD patients taking inhaled treatment will give a 25% increase in the number of patients showing therapeutic adherence in this group compared to the control group.</p> <p>We will evaluate the effectiveness of this multifactor intervention on patient adherence to inhaled drugs considering that it will be right and feasible to the clinical practice context.</p> <p>Trial registration</p> <p>Current Controlled Trials <a href="http://www.controlled-trials.com/ISCTN18841601">ISCTN18841601</a></p