Inspección y análisis científico de las torres atalaya que defendieron el último reino islámico de la Península Ibérica

The Islamic Nasrid kingdom of Granada occupied the mountainous areas of the south-eastern area of the Iberian Peninsula. The Baetic mountain range worked as a natural frontier between the Nasrid kingdom and the Christian kingdom of Castile from 1232 to 1492. An extensive network of watchtowers was built by Nasrid to control this frontier stablishing visual communication between them and the Nasrid centre at the Alhambra citadel. Many of them are still standing, disperse through the provinces of Granada, Malaga, Almeria and the eastern parts of Jaen, Cordoba and Cadiz. Even being this military architecture protected by Spanish Heritage law, many of these medieval towers and their cultural landscapes are in severe risk. There are studies of individual towers, but any global comparative study has been developed. For this reason, within the framework of the R&D project called ‘Las atalayas que defendieron el reino nazarí de Granada. Análisis y documentación científica (Nazalaya)” (HAR2016-79689-P) financed by the Ministry of Economy, Industry and Competitiveness of Spain, the towers are being studied as individual exemplars as well as components of the same typological group. This generates a complete documentation constituted by a homogenous and exhaustively planimetry which supplements the existing information and enabling comparative analysis. Furthermore complete architectural surveys are being carried out using techniques as photogrammetry. In addition to the analysis of construction systems, the structural safety of these towers is evaluated formulating guidelines for its restoration.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Proyecto del Plan Nacional I+D+i (Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia) entitled ‘Las atalayas que defendieron el reino nazarí de Granada. Análisis y documentación científica (Nazalaya)’ (HAR2016-79689-P) Proyecto de Investigación Precompetitivo (mod. A) del Plan Propio de la Universidad de Málaga ‘La construcción de un paisaje: arquitectura de tapial en la Alta Andalucía en el siglo XIII. Estudio y análisis del sistema de torres andalusíes en el valle de Segura de la Sierra’ X Convocatoria de Proyectos de Investigación de la Fundación Pública Andaluza Centro de Estudios Andaluces en la modalidad de proyectos individuales, PRY/259/17 ‘Torres medievales y modernas conservadas en Andalucía. Documentación gráfica, análisis científico e interrelaciones

Automatic identification of physical activity intensity and modality from the fusion of accelerometry and heart rate data

Background: Physical activity (PA) is essential to prevent and to treat a variety of chronic diseases. The automated detection and quantification of PA over time empowers lifestyle interventions, facilitating reliable exercise tracking and data-driven counseling. Methods: We propose and compare various combinations of machine learning (ML) schemes for the automatic classification of PA from multi-modal data, simultaneously captured by a biaxial accelerometer and a heart rate (HR) monitor. Intensity levels (low/moderate/vigorous) were recognized, as well as for vigorous exercise, its modality (sustained aerobic/resistance/mixed). In total, 178.63 h of data about PA intensity (65.55% low/18.96% moderate/15.49% vigorous) and 17.00 h about modality were collected in two experiments: one in free-living conditions, another in a fitness center under controlled protocols. The structure used for automatic classification comprised: a) definition of 42 time-domain signal features, b) dimensionality reduction, c) data clustering, and d) temporal filtering to exploit time redundancy by means of a Hidden Markov Model (HMM). Four dimensionality reduction techniques and four clustering algorithms were studied. In order to cope with class imbalance in the dataset, a custom performance metric was defined to aggregate recognition accuracy, precision and recall. Results: The best scheme, which comprised a projection through Linear Discriminant Analysis (LDA) and k-means clustering, was evaluated in leave-one-subject-out cross-validation; notably outperforming the standard industry procedures for PA intensity classification: score 84.65%, versus up to 63.60%. Errors tended to be brief and to appear around transients. Conclusions: The application of ML techniques for pattern identification and temporal filtering allowed to merge accelerometry and HR data in a solid manner, and achieved markedly better recognition performances than the standard methods for PA intensity estimation

CAU: Contextos d'Aprenentatge U-a-u a la UOC. Informe executiu

[Informe executiu]. L'estudi que presentem té com a propòsit obtenir coneixement sobre les característiques, les problemàtiques i les experiències que incideixen en la definició i el funcionament dels Contextos d'Aprenentatge U-a-U a la UOC. Hem considerat tot aquest conjunt d'aspectes de forma sistèmica entenent que actuen des de múltiples dimensions més enllà de la funció estrictament pedagògica, com ara el tipus de relació entre els agents de la interacció, el model de comunicació seguit, els instruments utilitzats o els processos involucrats. Els resultats obtinguts constitueixen una base de coneixement que permet orientar propostes que contribueixin a definir la formalització dels Contextos d'Aprenentatge U-a-U a la UOC

CAU: Contextos d'Aprenentatge U-a-u a la UOC. Informe de resultats

L'estudi que presentem té com a propòsit obtenir coneixement sobre les característiques, les problemàtiques i les experiències que incideixen en la definició i el funcionament dels Contextos d'Aprenentatge U-a-U a la UOC. Hem considerat tot aquest conjunt d'aspectes de forma sistèmica entenent que actuen des de múltiples dimensions més enllà de la funció estrictament pedagògica, com ara el tipus de relació entre els agents de la interacció, el model de comunicació seguit, els instruments utilitzats o els processos involucrats. Els resultats obtinguts constitueixen una base de coneixement que permet orientar propostes que contribueixin a definir la formalització dels Contextos d'Aprenentatge U-a-U a la UOC

Flexible and low-cost binderless capacitors based on p- and n-containing fibrous activated carbons from denim cloth wastes

Activated carbon cloths have been prepared from denim cloth wastes (DCWs) through chemical activation with H3PO4. The effect of the H3PO4/DCWs impregnation ratio and the carbonization temperature on the porous texture, the chemical composition, the fibers morphology, and the electrochemical performance has been studied. Low H3PO4/DCWs impregnation ratios lead to flexible and microporous activated carbons cloths, whereas more fragile and rigid activated carbon cloths with higher external surface area are produced upon increasing the amount of H3PO4. The increase in the carbonization temperature allows for obtaining a more ordered and conductive carbon structure. The activated carbon prepared at 900 ºC with a H3PO4/DCWs impregnation ratio of 0.5 (w/w) exhibits the best performance as electric double layer capacitor. This electrode shows a specific surface area of 2016 m2 g-1 and the highest registered gravimetric capacitance (227 F g-1). Moreover, its flexibility minimizes the ohmic resistance of the electrode, thus increasing the feasibility of working at higher current densities than the other synthesized electrodes.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech; MINECO CTQ2015-68654-

Ambrosia artemisiifolia L., nueva especie para la flora alóctona invasora de Andalucía (España)

Ambrosia artemisiifolia, a new species for the aloctonous invasive flora of Andalusia (Spain)Palabras clave. Ambrosia artemisiifolia, planta invasora, Andalucía, España.Key words. Ambrosia artemisiifolia, invasive plant, Andalusia flora, Spain

A course-based undergraduate research experience to illustrate the early stages of the drug discovery process

We have implemented at the University of Málaga (Spain) a new course-based undergraduate research experience (CURE) to involve undergraduate students of Science in a real-world scientific problem. Within the topic “Let's find acetylcholinesterase inhibitors as new drug candidates for the treatment of Alzheimer's”, students have been engaged into the early stages of the drug discovery process. Working in groups of 4–5 persons, they have searched information in databases, proposed solutions to the driving question and designed protocols to carry them out in vitro and in silico. Overall, the implementation of this experience has been very satisfactory in terms of academic performance and students' perception. This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, “Teaching Science on Big Data”.This work was supported by the University of Málaga (Spain) funds granted to the educational innovation projects PIE19-086. Open access funded by Universidad de Málaga/CBUA