Efecte de la pastura amb equí i cabrum sobre la reducció del fitovolum en un matollar mediterrani

El treball que es presenta postula recuperar i utilitzar els ramats en la gestió forestal encaminada a la prevenció d'incendis en hàbitats mediterranis. L'objectiu d'aquest estudi ha estat determinar les variacions estructurals de la vegetació d'una brolla mediterrània sotmesa a pastura de cavalls i cabres, i comparar l'efecte de cada espècie animal sobre la vegetació per a disminuir el risc d'incendi. La càrrega ramadera va ser de 70 UR/ha, elevada i intensa, de quatre dies de durada. Els resultats obtinguts indiquen que tant les cabres com els cavalls són eficients en la disminució del fitovolum combustible. Les espècies més pasturades van ser la foixarda (Globularia alypum) i el bruc d'hivern (Erica multiflora). L'efecte dels cavalls va ser significativament superior sobre la mortalitat de les plantes (21 %) respecte de les cabres (10 %). Les dues espècies animals redueixen significativament l'alçària dels matolls però no es van trobar diferències entre elles. En canvi, la pastura amb cabres va mostrar una reducció més gran de superfície de capçada i del fitovolum (38 % enfront del 36 %)

Preference by Donkeys and Goats among Five Mediterranean Forest Species : Implications for Reducing Fire Hazard

During the second half of the 20th century, European countries experienced an increase in their forest area due to the global change. Consequently, there has been an increase in large forest fires, mainly in the Mediterranean basin, and this has forced the development of several types of prevention programs. One of them is the control of the understory by livestock. In this sense, browsing with a combination of donkeys and goats could be a good option, as both animals usually feed on forest species. However, little is known about their preferences for the key species of the Mediterranean forest. Using a cafeteria test, the preferences and consumption of both animals have been determined for five typical species of the Mediterranean forest, such as Quercus ilex, Pinus halepensis, Phillyrea latifolia, Rubus ulmifolius, and Brachypodium retusum. Results showed that donkeys and goats could act complementarily in the reduction of the fuel biomass of forests. Donkeys appear to act more on fine fuel, such as B. retusum, and goats on the more pyrophyte species, in this case P. halepensis. In addition, given that donkeys are at severe risk of extinction in Europe, this role of providing ecosystem services could contribute to their conservation. Despite this study only showing that goats and donkeys would consume all five presented plant species and that there are some differences in consumption during a short-term test, it constitutes a useful first step for conservation and fire prevention in the Mediterranean forests

Cardiovascular magnetic resonance (CMR) and positron emission tomography (PET) imaging in the diagnosis and follow-up of patients with acute myocarditis and chronic inflammatory cardiomyopathy : A review paper with practical recommendations on behalf of the European Society of Cardiovascular Radiology (ESCR).

Advanced cardiac imaging techniques such as cardiovascular magnetic resonance (CMR) and positron emission tomography (PET) are widely used in clinical practice in patients with acute myocarditis and chronic inflammatory cardiomyopathies (I-CMP). We aimed to provide a review article with practical recommendations from the European Society of Cardiovascular Radiology (ESCR), in order to guide physicians in the use and interpretation of CMR and PET in clinical practice both for acute myocarditis and follow-up in chronic forms of I-CMP

Probabilistic Combination of Non-Linear Eigenprojections For Ensemble Classification

The emergence of new technologies has changed the way clinicians perform diagnosis. Medical imaging play a crucial role in this process, given the amount of information that they usually provide as non-invasive techniques. Despite the high quality offered by these images and the expertise of clinicians, the diagnostic process is not a straightforward task since different pathologies can have similar signs and symptoms. For this reason, it is extremely useful to assist this process with the inclusion of an automatic tool that reduces the bias when analyzing this kind of images. In this work, we propose an ensemble classifier based on probabilistic Support Vector Machine (SVM) in order to identify relevant patterns while providing information about the reliability of the classification. Specifically, each image is divided into patches and features contained in each one of them are extracted by applying kernel principal component analysis (PCA). The use of base classifiers within an ensemble allows our system to identify the informative patterns regardless of their size or location. Decisions of each individual patch are then combined according to the reliability of each individual classification: the lower the uncertainty, the higher the contribution. Performance is evaluated in a real scenario where distinguishing between pneumonia patients and controls from chest Computed Tomography (CCT) images, yielding an accuracy of 97.86%. The large performance obtained and the simplicity of the system (use of deep learning in CCT images would highly increase the computational cost) evidence the applicability of our proposal in a real-world environment.Projects PGC2018-098813-B-C32 and RTI2018-098913-B100 (Spanish “Ministerio de Ciencia, Innovación y Universidades”)UMA20-FEDERJA-086, A-TIC-080-UGR18 and P20 00525 (Consejer´ıa de econom´ıa y conocimiento, Junta de Andaluc´ıa)European Regional Development Funds (ERDF)Spanish ”Ministerio de Universidades” through Margarita-Salas gran

Efecto de la simulación de ramoneo en parámetros estructurales de tres especies de matorral mallorquín

La herviboría por la cabra salvaje mallorquina y la cabra doméstica asilvestrada puede ser uno de los factores que determinen la regresión en que se encuentran las poblaciones de tres especies anteriormente abundantes y actualmente raras del matorral mallorquín: boj balear (Buxus balearica), canadillo (Ephedra fragilis) y enebro rojo (Juniperus oxycedrus). Para determinar esta afectación analizamos la respuesta de estas especies en condiciones de invernadero, a las que se les realizó una simulación de ramoneo cortando el 80% de sus brotes terminales y se les midió la variación en los parámetros estructurales de crecimiento y capacidad de generar brotes nuevos. La simulación de ramoneo produjo respuestas morfológicas diferentes en las tres especies estudiadas. Mientras en las tres especies aumenta la producción de brotes, el crecimiento en diámetro no aumenta de manera significativa en B. balerica ni en E. fragilis, y en J. oxycedrus se ve afectado negativamente. Por lo que respecta al crecimiento en altura, el ramoneo tiene un efecto positivo en B. balearica y J. oxycedrus y es indiferente en E. fragilis. El hecho de que B .balearica sea actualmente una especie poco ramoneada contribuiría a explicar su regresión

Probabilistic combination of eigenlungs-based classifiers for COVID-19 diagnosis in chest CT images

The outbreak of the COVID-19 (Coronavirus disease 2019) pandemic has changed the world. According to the World Health Organization (WHO), there have been more than 100 million confirmed cases of COVID-19, including more than 2.4 million deaths. It is extremely important the early detection of the disease, and the use of medical imaging such as chest X-ray (CXR) and chest Computed Tomography (CCT) have proved to be an excellent solution. However, this process requires clinicians to do it within a manual and time-consuming task, which is not ideal when trying to speed up the diagnosis. In this work, we propose an ensemble classifier based on probabilistic Support Vector Machine (SVM) in order to identify pneumonia patterns while providing information about the reliability of the classification. Specifically, each CCT scan is divided into cubic patches and features contained in each one of them are extracted by applying kernel PCA. The use of base classifiers within an ensemble allows our system to identify the pneumonia patterns regardless of their size or location. Decisions of each individual patch are then combined into a global one according to the reliability of each individual classification: the lower the uncertainty, the higher the contribution. Performance is evaluated in a real scenario, yielding an accuracy of 97.86%. The large performance obtained and the simplicity of the system (use of deep learning in CCT images would result in a huge computational cost) evidence the applicability of our proposal in a real-world environment.Comment: 15 pages, 9 figure

Clinical translation of three-dimensional scar, diffusion tensor imaging, four-dimensional flow, and quantitative perfusion in cardiac MRI: a comprehensive review

Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy—both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease

Validation of time-resolved, automated peak trans-mitral velocity tracking: Two center four-dimensional flow cardiovascular magnetic resonance study

Objective: We aim to validate four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) peak velocity tracking methods for measuring the peak velocity of mitral inflow against Doppler echocardiography.  Method: Fifty patients were recruited who had 4D flow CMR and Doppler Echocardiography. After transvalvular flow segmentation using established valve tracking methods, peak velocity was automatically derived using three-dimensional streamlines of transvalvular flow. In addition, a static planar method was used at the tip of mitral valve to mimic Doppler technique.  Results: Peak E-wave mitral inflow velocity was comparable between TTE and the novel 4D flow automated dynamic method (1.02±0.41 m/s vs 1.02±0.36 m/s; P=0.77) however there was a statistically significant difference when compared with the static planar method (0.93±0.37 m/s; P=0.04). Mean A-wave peak velocity was also comparable across TTE and the automated dynamic streamline (0.87±0.39 m/s vs 0.87±0.36 m/s; P=0.99). A significant difference was seen with the static planar method (0.78±0.36 m/s; P=0.04). E/A ratio was comparable between TTE and both the automated dynamic and static planar method (1.22±0.52 vs 1.20±0.34; p=0.76 and 1.36±0.81; p=0.25 respectively). Both novel 4D flow methods showed good correlation with TTE for E-wave (dynamic method; r=0.70; P<0.001 and static planar method; r=0.67; P<0.001) and A-wave velocity measurements (dynamic method; r=0.83; P<0.001 and static method; r=0.71; P<0.001). The automated dynamic method demonstrated excellent intra/inter-observer reproducibility for all parameters.  Conclusion: Automated dynamic peak velocity tracing method using 4D flow CMR is comparable to Doppler echocardiography for mitral inflow assessment and has excellent reproducibility for clinical use