Stably stratified Taylor-Couette flows

Stably stratified Taylor–Couette flow has attracted much attention due to its relevance as a canonical example of the interplay among rotation, stable stratification, shear and container boundaries, as well as its potential applications in geophysics and astrophysics. In this article, we review the current knowledge on this topic, highlight unanswered questions and propose directions for future research. This article is part of the theme issue ‘Taylor–Couette and related flows on the centennial of Taylor’s seminal Philosophical Transactions paper (part 2)’.Postprint (author's final draft

Intelligent Detection and Recovery from Cyberattacks for Small and Medium-Sized Enterprises

Cyberattacks threaten continuously computer security in companies. These attacks evolve everyday, being more and more sophisticated and robust. In addition, they take advantage of security breaches in organizations and companies, both public and private. Small and Medium-sized Enterprises (SME), due to their structure and economic characteristics, are particularly damaged when a cyberattack takes place. Although organizations and companies put lots of efforts in implementing security solutions, they are not always effective. This is specially relevant for SMEs, which do not have enough economic resources to introduce such solutions. Thus, there is a need of providing SMEs with affordable, intelligent security systems with the ability of detecting and recovering from the most detrimental attacks. In this paper, we propose an intelligent cybersecurity platform, which has been designed with the objective of helping SMEs to make their systems and network more secure. The aim of this platform is to provide a solution optimizing detection and recovery from attacks. To do this, we propose the application of proactive security techniques in combination with both Machine Learning (ML) and blockchain. Our proposal is enclosed in the IASEC project, which allows providing security in each of the phases of an attack. Like this, we help SMEs in prevention, avoiding systems and network from being attacked; detection, identifying when there is something potentially harmful for the systems; containment, trying to stop the effects of an attack; and response, helping to recover the systems to a normal state

Unusual Tachycardia Association In A patient Without Structural Heart Disease

We report an unusual association of persistent atrial flutter and bundle branch re-entrant ventricular tachycardia in a young patient without structural heart disease. Atrial flutter masked the infra-Hisian conduction disease, was fundamentally dependent on a long PR interval, and could be a possible trigger of ventricular tachycardia

Driver Drowsiness Detection by Applying Deep Learning Techniques to Sequences of Images

This work presents the development of an ADAS (advanced driving assistance system) focused on driver drowsiness detection, whose objective is to alert drivers of their drowsy state to avoid road traffic accidents. In a driving environment, it is necessary that fatigue detection is performed in a non-intrusive way, and that the driver is not bothered with alarms when he or she is not drowsy. Our approach to this open problem uses sequences of images that are 60 s long and are recorded in such a way that the subject’s face is visible. To detect whether the driver shows symptoms of drowsiness or not, two alternative solutions are developed, focusing on the minimization of false positives. The first alternative uses a recurrent and convolutional neural network, while the second one uses deep learning techniques to extract numeric features from images, which are introduced into a fuzzy logic-based system afterwards. The accuracy obtained by both systems is similar: around 65% accuracy over training data, and 60% accuracy on test data. However, the fuzzy logic-based system stands out because it avoids raising false alarms and reaches a specificity (proportion of videos in which the driver is not drowsy that are correctly classified) of 93%. Although the obtained results do not achieve very satisfactory rates, the proposals presented in this work are promising and can be considered a solid baseline for future works.This work was supported by the Spanish Government under projects PID2019- 104793RB-C31, TRA2016-78886-C3-1-R, RTI2018-096036-B-C22, PEAVAUTO-CM-UC3M and by the Region of Madrid’s Excellence Program (EPUC3M17)

Predicción de volúmenes comerciales de Eucalyptus grandis a través de modelos de volumen total y de razón

Eight total volume and four volume-ratio models were evaluated for use in a system for predicting marketable volumes in Eucalyptusgrandis plantations. Data were collected from 101 trees in stands at harvest age, located in Salento, Quindio. Weighted regression was used to avoid problems of heteroscedasticity in the fit of total volume models. An autoregressive error structure was used to reduce autocorrelation of longitudinal data used in the fit of the volume-ratio models. After evaluation of goodness of fit and prediction, the models of Schumacher & Hall (1993) as total volume model and Cao etal. (1980) as volume-ratio model were selected. The bias and average error in the prediction of marketable volumes to variable-top diameter limits of 0, 5 and 10 cm were always below 4.4% and 11.5%, respectively. The functionality of the system to quantify marketable volumes during the construction of stand and stocks tables was demonstrated.Ocho ecuaciones de volumen total y cuatro modelos de volumen de razón fueron evaluados con el objetivo de seleccionar el mejor modelo de volumen total y de razón de volumen, a fin de ser utilizados en un sistema para la predicción de volúmenes comerciales en plantaciones de Eucalyptus grandis. Los datos usados en el estudio corresponden a 101 árboles colectados en rodales a la edad de cosecha, ubicados en el municipio de Salento, Quindío. Técnicas de regresión ponderada fue utilizada para evitar problemas de heterocedasticidad en el ajuste de modelos de volumen total. Una estructura autorregresiva del error se empleó para disminuir la autocorrelación, propia de los datos longitudinales utilizados en el ajuste de los modelos de volumen de razón. A partir de la evaluación de la bondad de ajuste y predicción fueron seleccionados los modelos de: Schumacher & Hall (1993), como modelo de volumen total, y Cao etal. (1980) como modelo de volumen de razón. El sesgo y el error promedio en la predicción de volúmenes comerciales hasta los índices de utilización 0, 5 y 10 cm estuvieron siempre por debajo de 4.4% y 11.5%, respectivamente. Finalmente, se demuestra la funcionalidad del sistema de cuantificación de volúmenes comerciales en la construcción de tablas de rodal y existencias

Reporting guidelines for health research: protocol for a cross-sectional analysis of the EQUATOR Network Library

INTRODUCTION: Transparency and completeness of health research is highly variable, with important deficiencies in the reporting of methods and results of studies. Reporting guidelines aim to improve transparency and quality of research reports, and are often developed by consortia of journal editors, peer reviewers, authors, consumers and other key stakeholders. The objective of this study will be to investigate the characteristics of scientific collaboration among developers and the citation metrics of reporting guidelines of health research. METHODS AND ANALYSIS: This is the study protocol for a cross-sectional analysis of completed reporting guidelines indexed in the Enhancing the QUAlity and Transparency Of health Research Network Library. We will search PubMed/MEDLINE and the Web of Science. Screening, selection and data abstraction will be conducted by one researcher and verified by a second researcher. Potential discrepancies will be resolved via discussion. We will include published papers of reporting guidelines written in English. Published papers will have to meet the definition of a reporting guideline related to health research (eg, a checklist, flow diagram or explicit text), with no restrictions by study design, medical specialty, disease or condition. Raw data from each included paper (including title, publication year, journal, subject category, keywords, citations, and the authors' names, author's affiliated institution and country) will be exported from the Web of Science. Descriptive analyses will be conducted (including the number of papers, citations, authors, countries, journals, keywords and main collaboration metrics). We will identify the most prolific authors, institutions, countries, journals and the most cited papers. Network analyses will be carried out to study the structure of collaborations. ETHICS AND DISSEMINATION: No ethical approval will be required. Findings from this study will be published in peer-reviewed journals. All data will be deposited in a cross-disciplinary public repository. It is anticipated the study findings could be relevant to a variety of audiences.Instituto de Salud Carlos III; Australian National Health and Medical Research Council; Canadian Institutes of Health Research; Universidad de Ottawa. FC-L and RT-S are supported by the Institute of Health Carlos III/CIBERSAM. MJP is supported by an Australian National Health and Medical Research Council Early Career Fellowship (1088535). BH is supported by a New Investigator Award from the Canadian Institutes of Health Research and the Drug Safety and Effectiveness Network. MR is supported by the Institute of Health Carlos III/Spanish Health Services Research on Chronic Patients Network (REDISSEC). DM is supported by a University Research Chair, University of Ottawa.S

Prevalence and comorbidity of attention deficit hyperactivity disorder in Spain: study protocol for extending a systematic review with updated meta-analysis of observational studies

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a childhood-onset disorder characterized by a persistent pattern of symptoms of developmentally inappropriate and impaired inattention and/or hyperactivity/impulsivity, with difficulties often continuing into adulthood. ADHD can come with other comorbid conditions. The aim of this study will be to quantify the prevalence and comorbidity of ADHD among children, adolescent, and adult population in Spain. METHODS/DESIGN: We designed and registered a study protocol for an update and expansion of a systematic review and meta-analysis of pooled prevalence data. We will include cross-sectional observational studies reporting prevalence of ADHD in Spain and conducted in the general population, outpatient, and/or school settings. The primary outcome will be the prevalence of ADHD. Secondary outcomes will be the prevalence of any physical or mental comorbidity in association with ADHD. No limitations will be imposed on publication status, study conduct period, and language of dissemination. Comprehensive literature searches will be conducted in multiple electronic databases, including PubMed/MEDLINE, EMBASE, Scopus, Web of Science, PsycINFO, IME - Spanish Medical Index, and IBECS - Spanish Bibliographic Index of Health Sciences. We will also search Google Scholar, dissertation databases, and conference abstracts. Two team members will independently screen all citations, full-text articles, and abstract data. Potential conflicts will be resolved through discussion. The methodological quality (or risk of bias) of individual studies will be appraised using an appropriate tool. If feasible, we will conduct random effects meta-analysis. Prevalence estimates will be stratified according to gender, age, and geographical location. Additional analyses will be conducted to explore the potential sources of heterogeneity (e.g., methodological quality, sample size, diagnostic criteria). DISCUSSION: This systematic review and meta-analysis of observational data will provide an updated synthesis of the prevalence and comorbidity of ADHD in Spain. This study will also examine factors that may explain potential variations in prevalence data. The findings of this study will be published in a peer-reviewed journal. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018106082 .FC-L and RT-S are funded by CIBERSAM/Institute of Health Carlos III. MR is partially funded by the Spanish Health Services Research on Chronic Patients Network (REDISSEC)/Institute of Health Carlos III. The funders were not involved in the design of the protocol or decision to submit the protocol for publication, nor will they be involved in any aspect of the conduct of the study.S

On the Optimal Identification of Tag Sets in Time-Constrained RFID Configurations

In Radio Frequency Identification facilities the identification delay of a set of tags is mainly caused by the random access nature of the reading protocol, yielding a random identification time of the set of tags. In this paper, the cumulative distribution function of the identification time is evaluated using a discrete time Markov chain for single-set time-constrained passive RFID systems, namely those ones where a single group of tags is assumed to be in the reading area and only for a bounded time (sojourn time) before leaving. In these scenarios some tags in a set may leave the reader coverage area unidentified. The probability of this event is obtained from the cumulative distribution function of the identification time as a function of the sojourn time. This result provides a suitable criterion to minimize the probability of losing tags. Besides, an identification strategy based on splitting the set of tags in smaller subsets is also considered. Results demonstrate that there are optimal splitting configurations that reduce the overall identification time while keeping the same probability of losing tags