Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad RTI2018-098062-A-I00European Union’s Horizon 2020 No. 754489Science Foundation Ireland grant 13/RC/209

Anthropometric measures as predictive indicators of metabolic risk in a population of “holy week costaleros”

Preventive measures are a priority in those groups that perform intense physical efforts without physical preparation and that can also be overweight or obese. One of the groups that reflect these characteristics is the costaleros of the Holy Week of Andalusia, Spain. This paper aims to describe the effect of obesity on blood pressure. A descriptive cross-sectional study was conducted on 101 costaleros. The anthropometric measures were determined through segmental impedance. Cardiac recovery and anaerobic power were measured through the Ruffier–Dickson test and the Abalakov test, respectively. Blood pressure was measured when the individuals were at rest. The Kruskal–Wallis test was applied for of continuous parameters and the X2 test for dichotomous measures. Binary logistic regression models were used for the subsequent analysis with R-square and Receiver Operating Characteristic (ROC) curves. The average population was 28 years of age, 173.7 cm tall, and 82.59 Kg weigh. The excess of body fat was 11.27 Kg and Body Mass Index was 27.33 Kg/m2. 72.3% showed abnormal blood pressure and 68.2% were overweight. 32.7% had a waist-hip ratio higher than 0.94. The probability of presenting abnormal blood pressure was higher among the subjects whose fat content was higher and muscle content was lower

Risk analysis of Spanish companies

Producción CientíficaThis paper aims to investigate the determinants of different types of market riskfaced by Spanish firms from 2012 to 2019. Using Fama and French's (Journalof Financial Economics, 1993, 33, 3) three-factor model, we estimate total risk,diversifiable risk, and systematic or non-diversifiable risk in the three dimen-sions proposed by these authors: market risk, size risk, and valuation risk. Riskdeterminants are derived from a series of economic and financial variables ob-tained from the information contained in financial statements. This informationis summarised using a factor analysis that aims to resolve the correlation issuesbetween the proposed measures. The study demonstrates that the systematicrisk factors proposed by Fama and French in their 1993 three-factor model in-corporate dimensions of systematic risk that are relevant to investors and thatthe set of economic and financial variables proposed can explain these risks.Among these variables, profitability and the market to book ratio have the great-est impact in explaining company risk, while factors such as operating and fi-nancial leverage, growth, or company insolvency have a much smaller effect asexplanatory factors for risk.Research funding from the Spanish Ministry of Scienceand Innovation (grant PID2020-114797GB-I00

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

Driver drowsiness detection based on respiratory signal analysis

Drowsy driving is a prevalent and serious public health issue that deserves attention. Recent studies estimate around 20% of car crashes have been caused by drowsy drivers. Nowadays, one of the main goals in the development of new advanced driver assistance systems is the trustworthy drowsiness detection. In this paper, a drowsiness detection method based on changes in the respiratory signal is proposed. The respiratory signal, which has been obtained using an inductive plethysmography belt, has been processed in real-time in order to classify the driver’s state of alertness as drowsy or awake. The proposed algorithm is based on the analysis of the respiratory rate variability (RRV) in order to detect the fight against to fall asleep. Moreover, a method to provide a quality level of the respiratory signal is also proposed. Both methods have been combined to reduce false alarms due to changes of measured RRV associated not to drowsiness but body movements. A driving simulator cabin has been used to perform the validation tests and external observers have rated the drivers’ state of alertness in order to evaluate the algorithm performance. It has been achieved a specificity of 96.6%, sensitivity of 90.3% and Cohen’s Kappa agreement score of 0.75 on average across all subjects through a leave-one-subject-out cross-validation. A novel algorithm for driver’s state of alertness monitoring through the identification of the fight against to fall asleep has been validated. The proposed algorithm may be a valuable vehicle safety system to alert drowsiness while drivingPeer ReviewedPostprint (published version

A new and fast index for the quantification of short range self-similarity in RR time series

We propose a new and very fast index (the frequency of sign changes of the mirrored differences or fscmd) with good correlation with the short range scaling exponent ( Ｒ) estimated among scales 4 to 16 of the DFA. fscmd computes the relative number of sign changes of the difference of the RR time series minus their corresponding reversed RR time series after a moving average detrending procedure is applied using a window of 30 samples. Linear regression results with simulated time series with Fractional Brownian Noise and with actual time series using the Fantasia (FT), Normal Sinus Rhythm RR time series (NSR) and Congestive Heart Failure RR interval (CHF) databases after artifact correction show good agreement between fscmd and Ｒ. Finally, Mann-Whitney Rank Sum tests applied to Ｒ and fscmd when comparing NSR and CHF databases show very significant differences (p<0.001) between groups for both indices.Postprint (published version

Estimation of the uncertainty in time domain indices of RR time series

A method for estimating the uncertainty in time-domain indices of RR time series is described. The method relies on the central limit theorem that states that the distribution of a sample average of independent samples has an uncertainty that asymptotically approaches to the sample standard deviation divided by the square root of the number of samples. Because RR time series cannot be characterized by a set of independent samples, we propose to estimate the uncertainty of indices by computing them in blocks that satisfy that the obtained partial indices are independent. We propose a methodology to search sets of independent partial indices and apply this methodology to the estimation of the uncertainty in the mean RR, SDRR, and r-msDD indices. The results show that the uncertainty can be higher than the 10% of the index for the SDRR and even higher for the r-msDD. Moreover, a statistical test for the difference of two indices is proposed.Peer Reviewe

A generic natural language interface for task planning : application to a mobile robot

This paper presents a generic natural language interface that can be applied to the teleoperation of di!erent kinds of complex interactive systems. Through this interface the operators can ask for simple actions or more complex tasks to be executed by the system. Complex tasks will be decomposed into simpler actions generating a network of actions whose execution will result in the accomplishment of the required task. As a practical application, the system has been applied to the teleoperation of a real mobile robot, allowing the operator to move the robot in a partially structured environment through natural language sentences

SeniorFit : Una aplicación móvil para el seguimiento de la adherencia a estilos de vida saludable para gente mayor

El envejecimiento progresivo de la población en los países desarrollados exige la promoción de estilos de vida saludables para fomentar el envejecimiento activo. En este trabajo se presenta una aplicación denominada SeniorFit que pretende facilitar la autoevaluación de la adherencia al estilo de vida mediante una herramienta sencilla, cómoda y fiable. La aplicación está desarrollada para móviles y permite medir de forma no intrusiva la actividad física, el pulso cardíaco y evaluar el estado de ánimo utilizando únicamente el propio móvil. Esta aplicación ha sido utilizada por un grupo de gente mayor durante 3 semanas y en condiciones libres. Los usuarios han manifestado un alto grado de satisfacción y la facilidad de su uso.Postprint (published version

A New Refinement of Mediterranean Tropical-Like Cyclones Characteristics

Several warm-core cyclones in the Mediterranean, which were analyzed in the literature, are studied using ERA5 reanalysis, to identify the environment where they develop and distinguish tropical-like cyclones from non-tropical warm-core cyclones. Initially, the cyclone phase space is analyzed to distinguish the cyclones that have a symmetrical deep warm core. Subsequently, the temporal evolution of several parameters is considered, including the distance between the area of maximum tangential wind speed and the cyclone center. Some differences are observed between the cyclones analyzed: one category of cyclones develops in areas of moderate-low baroclinicity and intense convective processes, as occurs in tropical cyclones. Another group of cyclones develops in a strongly baroclinic environment with weak convective processes and intense vertical wind shear, as occurs in warm seclusions. Two cyclones, showing similarities with polar lows, are also identified.This work has been funded by the University of Castilla La-Mancha and the European Regional Development Fund, through Grants [2019/5964] and [2021/12543]. The present activity has been developed in the framework of the COST Action 19019 “MEDCYCLONES”