Multifuncionalidad y Sistemas Agroalimentarios locales: prioridades de investigación e innovación en medio ambiente, territorio y desarrollo rural en el sector español del aceite de oliva

Los sistemas agroalimentarios locales (SIAL) de aceite de oliva en España son un buen ejemplo del comportamiento multifuncional y de su contribución potencial a la gobernanza territorial. Se detectan cambios significativos en la geografía del olivar español, derivados, por una parte, de la expansión de nuevas superficies de olivar en regadío de cultivo intensivo y superintensivo y, por otra, de la creciente marginalización a la que se ve abocado el olivar español de media y alta pendiente. Por otra parte, el olivar español produce un fuerte grado de externalidades ambientales negativas, como la erosión o la contaminación difusa de suelos y acuíferos. El principal objetivo del trabajo es detectar las relaciones que se establecen entre la definición de los principales problemas que atañen a los SIAL de aceite de oliva en España y las prioridades de investigación e innovación en materia de territorio y medio ambiente, desde una óptica multidisciplinar que integre enfoques procedentes de las Ciencias Sociales y de las Ciencias Agronómicas y Ambientales. El marco teórico procede de las teorías sobre la multifuncionalidad de los espacios rurales y sobre los SIAL. La metodología utiliza información cualitativa y cuantitativa procedente de dos fuentes primarias: i) un grupo de discusión integrado en un panel presencial de expertos sobre innovación en olivicultura, sostenibilidad y aprovechamiento de residuos; ii) un análisis Delphi dirigido a un conjunto amplio de expertos sobre medio ambiente, territorio y desarrollo rural sostenible en el sector oleícola. En cuanto al análisis de resultados, el grupo de discusión ha tenido como misión categorizar las grandes tipologías de olivicultura en España y sintetizar sus respectivos problemas ambientales y territoriales. Estos resultados sirven como marco de referencia del análisis Delphi, que tiene un doble objetivo: por una parte, el análisis de los principales problemas ambientales y territoriales de los SIAL oleícolas en España; por otra, el estudio de las prioridades en materia de programas y de grupos de líneas de investigación sobre la materia, así como las relaciones entre dichas líneas de investigación y los problemas a los que se enfrentan los SIAL oleícolas.prioridades de investigación e innovación, medio ambiente y territorio, análisis Delphi., Agribusiness, Agricultural and Food Policy, Community/Rural/Urban Development, Food Consumption/Nutrition/Food Safety, Labor and Human Capital,

Diabetes Patients´ Care based on Mobile Monitoring

In this paper, we propose a new architecture for diabetes patients. These applications allow the monitoring, patient selfcontrol and communication between patient and doctor. Moreover, as an important study case, we present a mobile monitoring system which allows patients with diabetes to have a constant control of their glucose tendency as well as direct communication with their doctor. We present an application to solve this problem; we share some details of the current implementation, detailing the functionalities achieved so far.In this paper, we propose a new architecture for diabetes patients. These applications allow the monitoring, patient selfcontrol and communication between patient and doctor. Moreover, as an important study case, we present a mobile monitoring system which allows patients with diabetes to have a constant control of their glucose tendency as well as direct communication with their doctor. We present an application to solve this problem; we share some details of the current implementation, detailing the functionalities achieved so far

Diabetes Patients' Care based on Mobile Monitoring

In this paper, we propose a new architecture for diabetes patients. These applications allow the monitoring, patient selfcontrol and communication between patient and doctor. Moreover, as an important study case, we present a mobile monitoring system which allows patients with diabetes to have a constant control of their glucose tendency as well as direct communication with their doctor. We present an application to solve this problem; we share some details of the current implementation, detailing the functionalities achieved so far.In this paper, we propose a new architecture for diabetes patients. These applications allow the monitoring, patient selfcontrol and communication between patient and doctor. Moreover, as an important study case, we present a mobile monitoring system which allows patients with diabetes to have a constant control of their glucose tendency as well as direct communication with their doctor. We present an application to solve this problem; we share some details of the current implementation, detailing the functionalities achieved so far

Machine learning methods for binary and multiclass classification of melanoma thickness From dermoscopic images

Thickness of the melanoma is the most important factor associated with survival in patients with melanoma. It is most commonly reported as a measurement of depth given in millimeters (mm) and computed by means of pathological examination after a biopsy of the suspected lesion. In order to avoid the use of an invasive method in the estimation of the thickness of melanoma before surgery, we propose a computational image analysis system from dermoscopic images. The proposed feature extraction is based on the clinical findings that correlate certain characteristics present in dermoscopic images and tumor depth. Two supervised classification schemes are proposed: a binary classification in which melanomas are classified into thin or thick, and a three-class scheme (thin, intermediate, and thick). The performance of several nominal classification methods, including a recent interpretable method combining logistic regression with artificial neural networks (Logistic regression using Initial variables and Product Units, LIPU), is compared. For the three-class problem, a set of ordinal classification methods (considering ordering relation between the three classes) is included. For the binary case, LIPU outperforms all the other methods with an accuracy of 77.6%, while, for the second scheme, although LIPU reports the highest overall accuracy, the ordinal classification methods achieve a better balance between the performances of all classes

Diagnóstico y seguimiento de la fragilidad en ancianos mediante el uso de dispositivos móviles

Con la edad, la resistencia y las reservas fisiológicas de una persona adulta disminuyen, provocando un mayor riesgo de sufrir efectos adversos para la salud. Estos factores llevan al conocido estado de fragilidad. El término fragilidad es difícil de conceptualizar, aunque en la mayoría de los casos está relacionado con el envejecimiento, discapacidad o comorbilidad. En la actualidad, la detección de la fragilidad se realiza mediante la observación en la ejecución de las AVD e AIVD, pruebas de marcha y equilibrio, y evaluación de parámetros nutricionales y cognitivos. Sin embargo, su valoración depende del punto de vista del geriatra o facultativo, cuyo diagnóstico se realiza en función de la puntuación obtenida en distintas escalas (Índice de Barthel, Tinetti, Lawton, MMS,...) y a partir de su propia observación. En este trabajo se presenta un sistema de apoyo al personal sanitario de residencias y centros especializados, para la detección de la fragilidad en ancianos mediante el uso de dispositivos móviles con sensores acelerómetros, en combinación con el historial clínico del residente.Con la edad, la resistencia y las reservas fisiológicas de una persona adulta disminuyen, provocando un mayor riesgo de sufrir efectos adversos para la salud. Estos factores llevan al conocido estado de fragilidad. El término fragilidad es difícil de conceptualizar, aunque en la mayoría de los casos está relacionado con el envejecimiento, discapacidad o comorbilidad. En la actualidad, la detección de la fragilidad se realiza mediante la observación en la ejecución de las AVD e AIVD, pruebas de marcha y equilibrio, y evaluación de parámetros nutricionales y cognitivos. Sin embargo, su valoración depende del punto de vista del geriatra o facultativo, cuyo diagnóstico se realiza en función de la puntuación obtenida en distintas escalas (Índice de Barthel, Tinetti, Lawton, MMS,...) y a partir de su propia observación. En este trabajo se presenta un sistema de apoyo al personal sanitario de residencias y centros especializados, para la detección de la fragilidad en ancianos mediante el uso de dispositivos móviles con sensores acelerómetros, en combinación con el historial clínico del residente

Aplicabilidad de la tecnologia movil en residencias y centros especializados

Uno de los principales esfuerzos de nuestro trabajo radica en aprovechar las capacidades de dispositivos móviles universales como los teléfonos móviles y sensores autónomos integrados, permitiendo la obtención de servicios del entorno y la realización de tareas esenciales en el día a día de centros residenciales y sanitarios. Por tanto, se presentan distintos desarrollos de aplicabilidad de estos dispositivos en los entornos mencionados. La integración y adaptación de nuevas tecnologías en entornos residenciales, centros especializados y hospitales es hoy en día una realidad a la par que una necesidad inherente, aún más tratándose de entornos tan heterogéneos y dispersos como los citados anteriormente. Por ello, el concepto de movilidad desarrollado por las diferentes tecnologías móviles existentes se presenta como una de las principales alternativas y soluciones para dar soporte al profesional en sus tareas diarias, así como mejorar la calidad asistencial de los pacientes y residentes de estos centros. Sin embargo, esta adaptación tecnológica debe presentarse de forma natural, intuitiva y no intrusiva de cara al personal sanitario y a los propios pacientes.Uno de los principales esfuerzos de nuestro trabajo radica en aprovechar las capacidades de dispositivos móviles universales como los teléfonos móviles y sensores autónomos integrados, permitiendo la obtención de servicios del entorno y la realización de tareas esenciales en el día a día de centros residenciales y sanitarios. Por tanto, se presentan distintos desarrollos de aplicabilidad de estos dispositivos en los entornos mencionados. La integración y adaptación de nuevas tecnologías en entornos residenciales, centros especializados y hospitales es hoy en día una realidad a la par que una necesidad inherente, aún más tratándose de entornos tan heterogéneos y dispersos como los citados anteriormente. Por ello, el concepto de movilidad desarrollado por las diferentes tecnologías móviles existentes se presenta como una de las principales alternativas y soluciones para dar soporte al profesional en sus tareas diarias, así como mejorar la calidad asistencial de los pacientes y residentes de estos centros. Sin embargo, esta adaptación tecnológica debe presentarse de forma natural, intuitiva y no intrusiva de cara al personal sanitario y a los propios pacientes

Intermediation for technology diffusion and user innovation in a developing rural economy:a social learning perspective

Technology intermediaries are seen as potent vehicles for addressing perennial problems in transferring technology from university to industry in developed and developing countries. This paper examines what constitutes effective user-end intermediation in a low-technology, developing economy context, which is an under-researched topic. The social learning in technological innovation framework is extended using situated learning theory in a longitudinal instrumental case study of an exemplar technology intermediation programme. The paper documents the role that academic-related research and advisory centres can play as intermediaries in brokering, facilitating and configuring technology, against the backdrop of a group of small-scale pisciculture businesses in a rural area of Colombia. In doing so, it demonstrates how technology intermediation activities can be optimized in the domestication and innofusion of technology amongst end-users. The design components featured in this instrumental case of intermediation can inform policy making and practice relating to technology transfer from university to rural industry. Future research on this subject should consider the intermediation components put forward, as well as the impact of such interventions, in different countries and industrial sectors. Such research would allow for theoretical replication and help improve technology domestication and innofusion in different contexts, especially in less-developed countries

A study on multi-scale kernel optimisation via centered kernel-target alignment

Kernel mapping is one of the most widespread approaches to intrinsically deriving nonlinear classifiers. With the aim of better suiting a given dataset, different kernels have been proposed and different bounds and methodologies have been studied to optimise them. We focus on the optimisation of a multi-scale kernel, where a different width is chosen for each feature. This idea has been barely studied in the literature, although it has been shown to achieve better performance in the presence of heterogeneous attributes. The large number of parameters in multi-scale kernels makes it computationally unaffordable to optimise them by applying traditional cross-validation. Instead, an analytical measure known as centered kernel-target alignment (CKTA) can be used to align the kernel to the so-called ideal kernel matrix. This paper analyses and compares this and other alternatives, providing a review of the literature in kernel optimisation and some insights into the usefulness of multi-scale kernel optimisation via CKTA. When applied to the binary support vector machine paradigm (SVM), the results using 24 datasets show that CKTA with a multi-scale kernel leads to the construction of a well-defined feature space and simpler SVM models, provides an implicit filtering of non-informative features and achieves robust and comparable performance to other methods even when using random initialisations. Finally, we derive some considerations about when a multi-scale approach could be, in general, useful and propose a distance-based initialisation technique for the gradient-ascent method, which shows promising results

Partial order label decomposition approaches for melanoma diagnosis

Melanoma is a type of cancer that develops from the pigment-containing cells known as melanocytes. Usually occurring on the skin, early detection and diagnosis is strongly related to survival rates. Melanoma recognition is a challenging task that nowadays is performed by well trained dermatologists who may produce varying diagnosis due to the task complexity. This motivates the development of automated diagnosis tools, in spite of the inherent difficulties (intra-class variation, visual similarity between melanoma and non-melanoma lesions, among others). In the present work, we propose a system combining image analysis and machine learning to detect melanoma presence and severity. The severity is assessed in terms of melanoma thickness, which is measured by the Breslow index. Previous works mainly focus on the binary problem of detecting the presence of the melanoma. However, the system proposed in this paper goes a step further by also considering the stage of the lesion in the classification task. To do so, we extract 100 features that consider the shape, colour, pigment network and texture of the benign and malignant lesions. The problem is tackled as a five-class classification problem, where the first class represents benign lesions, and the remaining four classes represent the different stages of the melanoma (via the Breslow index). Based on the problem definition, we identify the learning setting as a partial order problem, in which the patterns belonging to the different melanoma stages present an order relationship, but where there is no order arrangement with respect to the benign lesions. Under this assumption about the class topology, we design several proposals to exploit this structure and improve data preprocessing. In this sense, we experimentally demonstrate that those proposals exploiting the partial order assumption achieve better performance than 12 baseline nominal and ordinal classifiers (including a deep learning model) which do not consider this partial order. To deal with class imbalance, we additionally propose specific over-sampling techniques that consider the structure of the problem for the creation of synthetic patterns. The experimental study is carried out with clinician-curated images from the Interactive Atlas of Dermoscopy, which eases reproducibility of experiments. Concerning the results obtained, in spite of having augmented the complexity of the classification problem with more classes, the performance of our proposals in the binary problem is similar to the one reported in the literature

Fisher score-based feature selection for ordinal classification: a social survey on subjective well-being

This paper approaches the problem of feature selection in the context of ordinal classification problems. To do so, an ordinal version of the Fisher score is proposed. We test this new strategy considering data from an European social survey concerning subjective well-being, in order to understand and identify the most important variables for a person’s happiness, which is represented using ordered categories. The input variables have been chosen according to previous research, and these have been categorised in the following groups: demographics, daily activities, social well-being, health and habits, community well-being and personality/opinion. The proposed strategy shows promising results and performs significantly better than its nominal counterpart, therefore validating the need of developing specific ordinal feature selection methods. Furthermore, the results of this paper can shed some light on the human psyche by analysing the most and less frequently selected variables