237 research outputs found

    Adaptation strategies to climate change in the tourist sector: The case of coastal tourism in Spain

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    Tourism activities, that are very important in the Spanish Mediterranean coast since 60s, have been described as highly vulnerable to climate change. Diversification of the tourism and tourist products are often presented as a possible strategy for adapting to the effects of climate change. The present study explores the initiatives in product diversification that are being put into practice in the Spanish Mediterranean coastal tourism sector. To this end, the study focuses on the analysis of the experiences of the rural tourism sector as an alternative to sun-and-sand tourism in the Alt Empordà (Costa Brava, North-eastern Spain). Methodology of this research is based in two aspects: a) desk research of relevant public documents aimed to promote the diversification of the tourist sector; b) regional survey of rural tourism establishments. The analysis reveals a process of diversification that is characterised by spontaneous developments that lack planning and shows an absence of product structuring in accordance with a segmentation of the market. Given these characteristics, the process of diversification that has taken place will not contribute to increasing adaptation\u27s capacity of tourism to climate change or, consequently, to reducing its level of vulnerability

    Reflexiones acerca de un grupo terapéutico con pacientes esquizofrénicos.

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    El artículo describe el uso en la esquizofrenia de la psicoterapia de grupo, coordinada con técnica analítico –operativa. Se concluye que es una herramienta de gran utilidad en esta enfermedad, y que su combinación con psicofármacos y sesiones grupales conjuntas de pacientes y familiares obtiene resultados favorables para su evolución

    Reflexiones acerca de un grupo terapéutico con pacientes esquizofrénicos.

    Get PDF
    El artículo describe el uso en la esquizofrenia de la psicoterapia de grupo, coordinada con técnica analítico –operativa. Se concluye que es una herramienta de gran utilidad en esta enfermedad, y que su combinación con psicofármacos y sesiones grupales conjuntas de pacientes y familiares obtiene resultados favorables para su evolución

    Contaminación Lumínica en España 2012: Light Pollution in Spain 2012

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    The evolution of electric power consumption on public lighting in Spain is obtained from DMSP-OLS satellite data and compared with official data. We provide trends for each Spanish province. Radiance calibrated images for the Iberian peninsula for 1996 and 2006 are shown. We are using pictures taken from the International Space Station (ISS) for Light Pollution studies

    Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies

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    The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of critical clinical information and/or the appearance of false information. To assess this, the focus was on the angular resolution of dMRI and a clinical trial was conducted on migraine, specifically between episodic and chronic migraine patients. The number of gradient directions had an impact on white matter analysis results, with statistically significant differences between groups being drastically reduced when using 21 gradient directions instead of the original 61. Fourteen teams from different institutions were tasked to use DL to enhance three diffusion metrics (FA, AD and MD) calculated from data acquired with 21 gradient directions and a b-value of 1000 s/mm2. The goal was to produce results that were comparable to those calculated from 61 gradient directions. The results were evaluated using both standard image quality metrics and Tract-Based Spatial Statistics (TBSS) to compare episodic and chronic migraine patients. The study results suggest that while most DL techniques improved the ability to detect statistical differences between groups, they also led to an increase in false positive. The results showed that there was a constant growth rate of false positives linearly proportional to the new true positives, which highlights the risk of generalization of AI-based tasks when assessing diverse clinical cohorts and training using data from a single group. The methods also showed divergent performance when replicating the original distribution of the data and some exhibited significant bias. In conclusion, extreme caution should be exercised when using AI methods for harmonization or synthesis in clinical studies when processing heterogeneous data in clinical studies, as important information may be altered, even when global metrics such as structural similarity or peak signal-to-noise ratio appear to suggest otherwise

    Risk factors for non-diabetic renal disease in diabetic patients

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    Background. Diabetic patients with kidney disease have a high prevalence of non-diabetic renal disease (NDRD). Renal and patient survival regarding the diagnosis of diabetic nephropathy (DN) or NDRD have not been widely studied. The aim of our study is to evaluate the prevalence of NDRD in patients with diabetes and to determine the capacity of clinical and analytical data in the prediction of NDRD. In addition, we will study renal and patient prognosis according to the renal biopsy findings in patients with diabetes. Methods. Retrospective multicentre observational study of renal biopsies performed in patients with diabetes from 2002 to 2014. Results. In total, 832 patients were included: 621 men (74.6%), mean age of 61.7 6 12.8 years, creatinine was 2.8 6 2.2 mg/dL and proteinuria 2.7 (interquartile range: 1.2–5.4) g/24 h. About 39.5% (n ¼ 329) of patients had DN, 49.6% (n ¼ 413) NDRD and 10.8% (n ¼ 90) mixed forms. The most frequent NDRD was nephroangiosclerosis (NAS) (n ¼ 87, 9.3%). In the multivariate logistic regression analysis, older age [odds ratio (OR) ¼ 1.03, 95% CI: 1.02–1.05, P < 0.001], microhaematuria (OR ¼ 1.51, 95% CI: 1.03–2.21, P ¼ 0.033) and absence of diabetic retinopathy (DR) (OR ¼ 0.28, 95% CI: 0.19–0.42, P < 0.001) were independently associated with NDRD. Kaplan–Meier analysis showed that patients with DN or mixed forms presented worse renal prognosis than NDRD (P < 0.001) and higher mortality (P ¼ 0.029). In multivariate Cox analyses, older age (P < 0.001), higher serum creatinine (P < 0.001), higher proteinuria (P < 0.001), DR (P ¼ 0.007) and DN (P < 0.001) were independent risk factors for renal replacement therapy. In addition, older age (P < 0.001), peripheral vascular disease (P ¼ 0.002), higher creatinine (P ¼ 0.01) and DN (P ¼ 0.015) were independent risk factors for mortality. Conclusions. The most frequent cause of NDRD is NAS. Elderly patients with microhaematuria and the absence of DR are the ones at risk for NDRD. Patients with DN presented worse renal prognosis and higher mortality than those with NDRD. These results suggest that in some patients with diabetes, kidney biopsy may be useful for an accurate renal diagnosis and subsequently treatment and prognosis

    Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

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    A measurement of the cosmic-ray spectrum for energies exceeding 4×10184{\times}10^{18} eV is presented, which is based on the analysis of showers with zenith angles greater than 6060^{\circ} detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above 5.3×10185.3{\times}10^{18} eV, the "ankle", the flux can be described by a power law EγE^{-\gamma} with index γ=2.70±0.02(stat)±0.1(sys)\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)} followed by a smooth suppression region. For the energy (EsE_\text{s}) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find Es=(5.12±0.25(stat)1.2+1.0(sys))×1019E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19} eV.Comment: Replaced with published version. Added journal reference and DO
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