The Role of Plasma Extracellular Vesicles in Remote Ischemic Conditioning and Exercise-Induced Ischemic Tolerance

Ischemic conditioning and exercise have been suggested for protecting against brain ischemia-reperfusion injury. However, the endogenous protective mechanisms stimulated by these interventions remain unclear. Here, in a comprehensive translational study, we investigated the protective role of extracellular vesicles (EVs) released after remote ischemic conditioning (RIC), blood flow restricted resistance exercise (BFRRE), or high-load resistance exercise (HLRE). Blood samples were collected from human participants before and at serial time points after intervention. RIC and BFRRE plasma EVs released early after stimulation improved viability of endothelial cells subjected to oxygen-glucose deprivation. Furthermore, post-RIC EVs accumulated in the ischemic area of a stroke mouse model, and a mean decrease in infarct volume was observed for post-RIC EVs, although not reaching statistical significance. Thus, circulating EVs induced by RIC and BFRRE can mediate protection, but the in vivo and translational effects of conditioned EVs require further experimental verification.     

Fuzzy Online Auto-Tuning for an Industrial PID Controller

This paper presents a fuzzy tuning system for real-time industrial PID （proportional-integral-derivative） controllers. The algorithm set the proportional gain, integral time and derivative time of a classical PID structure according to the set point, error and error derivative of the process, respectively. The tuning of the PID controller is based on a fuzzy inference machine. The set of rules of the fuzzy inference machine was obtained by experts engineering. The system is tested in an austempering process but can be applied in any industrial plant. Besides, an analysis between the response of the process with a PID controller and the system of fuzzy auto-tuning for P1D proposed was made.     

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10?000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.     

Expert system for problem solving in distance university education: The successful case of the subject “operations management”

Acquiring the skills needed to solve certain types of problems is one of the main challenges of distance university education, demanding extra motivation from students to tackle it. New technology should be one of our great allies in addressing these problems. This article proposes an expert system with a web‐based problem‐solving simulator for a multidevice environment in order to allow students to access an unlimited number of problems with their corresponding solutions, immediately, anytime and anywhere. The types of problems that can be used are those based on quantitative methods with a fixed methodology to be followed. A successful case study was carried out for the subject Operations Management at the Distance University of Madrid (UDIMA), with three different problem simulators having been developed. The results were very satisfactory compared with previous academic years in terms of motivation. A decrease in students that did not sit the final examination was observed, as was an increase in the number of visits to the Moodle classroom. Students also responded positively in their assessments of the initiative.     

A pipeline structure for the block QR update in digital signal processing

The Journal of Supercomputing - There exist problems in the field of digital signal processing, such as filtering of acoustic signals that require processing a large amount of data in real time....     

OWL‐based acquisition and editing of computer‐interpretable guidelines with the CompGuide editor

Computer‐Interpretable Guidelines (CIGs) are the dominant medium for the delivery of clinical decision support, given the evidence‐based nature of their source material. Therefore, these machine‐readable versions have the ability to improve practitioner performance and conformance to standards, with availability at the point and time of care. The formalisation of Clinical Practice Guideline knowledge in a machine‐readable format is a crucial task to make it suitable for the integration in Clinical Decision Support Systems. However, the current tools for this purpose reveal shortcomings with respect to their ease of use and the support offered during CIG acquisition and editing. In this work, we characterise the current landscape of CIG acquisition tools based on the properties of guideline visualisation, organisation, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, we describe the CompGuide Editor, a tool for the acquisition of CIGs in the CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. The Editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition.     

Boccia game simulator: Serious game adapted for people with disabilities

Integration in the world of sport is one way for individuals with disabilities or motor disorders to feel more socially integrated, independent, and confident. Boccia is a Paralympic sport, which is increasingly getting more attention around the world. These facts have contributed to the objectives of this work. Including it in the serious games category enables to develop and rehabilitate the cognitive capabilities. The main focus was BC3 classification athletes (users with limited motor characteristics that require the use of an assistive device—a ramp, in this case). This paper describes a realistic Boccia game simulator adapted for people with disabilities that integrates a set of features that includes real physics and social features. These features can be used to enhance the interest of nonpractitioners of the sport and to improve the training conditions. The official Boccia regulation was added to the design of the simulator. The usability and approximation to the reality of the simulator were tested and validated based on the tests performed and data collected via a survey of users with no motor or psychological disorders. Realism and usability rating was almost excellent, and good results were achieved at the assessment of the game experience.     

Low-cost deployment proposal to urban mobility in smart cities

Rational use of cars in smart cities can represent an economical and cheaper way to decrease the quantity of cars on the roads to better the life quality of the populations. This paper presents a low-cost deployment proposal called “URCa project” to reach these goals and proposes a paradigm change by sharing the cars considering some logistic aspects including car ride mechanism. Technical feasibility to deploy this solution was checked by means of a proof of concept. The concept was proven by passenger counting and license plate that are essential information in this solution were obtained taking photographs, applying two types of recognition algorithms and sending the results to be stored and evaluated by analytic data processes of a transit regulatory agency showing that this project is technically viable. The low-cost solution was justified by a financial analysis based on both costs (URCa solution and a bridge) that has shown a ratio of 1:10,000.