Gestión conjunta de la calidad en grupos empresariales de la economía social

Due to the growth in markets, social economy enterprises are seeking a competitive advantage through economies of scale. In this regard, these enterprises should pursue the coordinated implementation of shared quality management strategies within groups. Accordingly, quality benchmarking through self-evaluation models is a key instrument in providing a balanced quality standard within the group and also in helping create synergies in the group. Likewise, coordinated managed of the quality records should be sought by the companies with a view to introducing a joint Quality Information System. Finally, joint quality circles should also be involved in shared quality management within social economy groups.Groups, quality management, benchmarking, quality information system, quality circles.

Detección de factores de riesgo en la conducción mediante técnicas de análisis de datos

Este estudio tiene como objetivo analizar los efectos de diferentes distracciones bien diferenciadas en el rendimiento de los conductores. Para ello se utilizan técnicas de análisis de datos utilizando el programa Rapidminer, para analizar diferentes conjuntos de datos que contienen desde información biométrica de los usuarios, sobre la conducción realizada y las distracciones ocurridas (todo ello sincronizando el tiempo), hasta la valoración subjetiva de los voluntarios sobre la dificultad para la realización de la conducción ante dichas distracciones. Durante el proyecto se toma especial consideración en mostrar las dificultades y los resultados de cada una de las etapas del tratamiento de los datos, hasta su posterior modelado y extracción de conclusiones. Dicho modelado se centra principalmente en técnicas de aprendizaje no supervisado. Entre las conclusiones finales se ha podido determinar que: -Los sujetos sometidos a distracciones, tienen cambios en sus medidas biométricas, más específicamente un aumento de las mismas, aunque no existe una diferencia entre las respuestas suficientemente diferenciada como para distinguir unas de otras a partir de los datos tomados. Asimismo la cantidad de veces que los sujetos a los que se les está aplicando una distracción (en la mayoría de los casos oral) pierden la vista de la carretera es significativamente mayor que la de los sujetos a los que no se les distrae. También se ha podido encontrar que las distracciones percibidas como más frustrantes y que más esfuerzo requieren son, las distracciones cognitivas, presumiblemente porque obligan a emplear parte de la capacidad de análisis que se utilizaría en la conducción en resolver otros problemas, las distracciones sensorio-motoras, porque obligan a perder la vista de la carretera momentáneamente, obligando a adaptarse más rápidamente a cualquier cambio y la distracción resultante de la combinación de varias distracciones, presumiblemente por desbordar la capacidad de atención de los sujetos. También se ha observado que cuando un sujeto cree que una prueba es difícil puntúa su rendimiento en dicha prueba de manera generosa, y cuando percibe una prueba como fácil puntúa su rendimiento de manera más baja. Esto es debido a la percepción de los sujetos de que realizan toda prueba correctamente y su percepción de sus propias capacidades es muy subjetiva. Por último cabe destacar que no se ha percibido ninguna diferenciación entre los resultados de las pruebas aplicadas a los sujetos por cuestiones de género, siendo los grupos obtenidos por las técnicas de agrupamiento muy equilibrados en el número de hombres y mujeres.Ingeniería en Tecnologías de Telecomunicació

LightDock: a new multi-scale approach to protein–protein docking

Computational prediction of protein–protein complex structure by docking can provide structural and mechanistic insights for protein interactions of biomedical interest. However, current methods struggle with difficult cases, such as those involving flexible proteins, low-affinity complexes or transient interactions. A major challenge is how to efficiently sample the structural and energetic landscape of the association at different resolution levels, given that each scoring function is often highly coupled to a specific type of search method. Thus, new methodologies capable of accommodating multi-scale conformational flexibility and scoring are strongly needed. We describe here a new multi-scale protein–protein docking methodology, LightDock, capable of accommodating conformational flexibility and a variety of scoring functions at different resolution levels. Implicit use of normal modes during the search and atomic/coarse-grained combined scoring functions yielded improved predictive results with respect to state-of-the-art rigid-body docking, especially in flexible cases.B.J-G was supported by a FPI fellowship from the Spanish Ministry of Economy and Competitiveness. This work was supported by I+D+I Research Project grants BIO2013-48213-R and BIO2016-79930-R from the Spanish Ministry of Economy and Competitiveness. This work is partially supported by the European Union H2020 program through HiPEAC (GA 687698), by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology (TIN2015-65316-P) and the Departament d’Innovació, Universitats i Empresa de la Generalitat de Catalunya, under project MPEXPAR: Models de Programaciói Entorns d’Execució Paral·lels (2014-SGR-1051).Peer ReviewedPostprint (author's final draft

The presence of toxic pollutants in buildings and construction materials increases the risk of cancer

To this day, construction materials that contain toxic and carcinogenic compounds are still used. These materials contribute to increase the levels of these compounds inside buildings, thus increasing the risk of cancer. It is necessary to avoid the use of these materials, carry out correct ventilation of buildings, improve energy efficiency, and design and build green buildings in order to reduce the risk of cancer and therefore to improve the health of the inhabitants

Learning on real robots from experience and simple user feedback

In this article we describe a novel algorithm that allows fast and continuous learning on a physical robot working in a real environment. The learning process is never stopped and new knowledge gained from robot-environment interactions can be incorporated into the controller at any time. Our algorithm lets a human observer control the reward given to the robot, hence avoiding the burden of defining a reward function. Despite the highly-non-deterministic reinforcement, through the experimental results described in this paper, we will see how the learning processes are never stopped and are able to achieve fast robot adaptation to the diversity of different situations the robot encounters while it is moving in several environments.This work was supported by the research grant TIN2009-07737 of the Spanish Ministerio de Economía y Competitividad, and María Barbeito program of the Xunta de Galicia

Feature Selection for Blood Glucose Level Prediction in Type 1 Diabetes Mellitus by Using the Sequential Input Selection Algorithm (SISAL)

Feature selection is a primary exercise to tackle any forecasting task. Machine learning algorithms used to predict any variable can improve their performance by lessening their computational effort with a proper dataset. Anticipating future glycemia in type 1 diabetes mellitus (DM1) patients provides a baseline in its management, and in this task, we need to carefully select data, especially now, when novel wearable devices offer more and more information. In this paper, a complete characterization of 25 diabetic people has been carried out, registering innovative variables like sleep, schedule, or heart rate in addition to other well-known ones like insulin, meal, and exercise. With this ground-breaking data compilation, we present a study of these features using the Sequential Input Selection Algorithm (SISAL), which is specially prepared for time series data. The results rank features according to their importance, regarding their relevance in blood glucose level prediction as well as indicating the most influential past values to be taken into account and distinguishing features with person-dependent behavior from others with a common performance in any patient. These ideas can be used as strategies to select data for predicting glycemia depending on the availability of computational power, required speed, or required accuracy. In conclusion, this paper tries to analyze if there exists symmetry among the different features that can affect blood glucose levels, that is, if their behavior is symmetric in terms of influence in glycemia.This work has been sponsored by the Spanish Ministry of Economy and Competitiveness through 387 the PERSEIDES (ref. TIN2017-86885-R) and CHIST-ERA (ref. PCIN-2016-010) projects; by MINECO grant BES-2015-071956 and by the European Commission through the H2020-ENTROPY-649849 EU Project. The authors would like to thank to the Endocrinology Department of the Morales Meseguer and Virgen de la Arrixaca hospitals of the city of Murcia (Spain)

Small and medium hotels cluster analysis in Huatulco, Mexico, as a tool to develop a cross sector network

En este estudio se realiza un diagnóstico sobre el sistema de calidad implantado en hoteles pequeños y medianos. A partir del mismo se realiza un análisis cluster para segmentar los mismos, como paso previo para desarrollar una estrategia común de calidad como primer escalón para desarrollar una red turística multiagente de destino. Bahías de Huatulco, México se presenta como estudio de caso.In order to develop a cross sector network hotels within the region must foster it due to their comparative size. This paper presents an investigation on the quality system implemented in small and medium hotels in the Bahias de Huatulco area. Segmentation is based on a cluster analysis. This is considered the first step in order to develop a cross sector network. Bahías de Huatulco, México, is a study case

Role of SODC protein in antineoplastic drug resistance

Cells need homeostasis to survive, therefore, they use the different pathways available to obtain it. The SODC protein overexpression, which is implicated in this process, suggests that could be implicated in the process of acquisition resistance during chemotherapy.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Metabolism is altered in the process of drug resistance acquisition

Cells need energy to survive, therefore, they increase the different pathways available to obtain it. This suggests that the cell, due to the cytotoxicity of bleomycin, increases the routes to obtain energy. For this reason, GPM1 could be a good candidate as bleomycin chemo-resistance biomarker. Knowing of the homologous gene in humans facilitates more studies of the expression of this protein in tumors.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Analysis of Immunotherapy in ovarian cancer

There are many Immunotherapy methods in ovarian cancer. Even the immune cells themselves can be part of the immunotherapy. But also at molecular level, the immunotherapy can be applied, like maintaining damage in DNA or inhibiting certain pathways. Nevertheless, there is still needed to understand the mechanism of immunotherapy.Campus de Excelencia Internacional Andalucía Tech