Using Multi-Agent Transport Simulations to Assess the Impact of EV Charging Infrastructure Deployment

Over the last two decades, electrification has gained importance as a means to decarbonise the transport sector. As the number of Electric Vehicles (EVs)increases, it is important to consider broader system aspects as well, especially when deciding the type, coverage, size and location of the charging infrastructure required. In this article, a Multi-Agent model depicting long distance transport in Sweden is proposed, allowing to simulate different scenarios and enabling a more detailed analysis of the interaction between these vehicles and the charging infrastructure

Computing Safe Contention Bounds for Multicore Resources with Round-Robin and FIFO Arbitration

Numerous researchers have studied the contention that arises among tasks running in parallel on a multicore processor. Most of those studies seek to derive a tight and sound upper-bound for the worst-case delay with which a processor resource may serve an incoming request, when its access is arbitrated using time-predictable policies such as round-robin or FIFO. We call this value upper-bound delay ( ubd ). Deriving trustworthy ubd statically is possible when sufficient public information exists on the timing latency incurred on access to the resource of interest. Unfortunately however, that is rarely granted for commercial-of-the-shelf (COTS) processors. Therefore, the users resort to measurement observations on the target processor and thus compute a “measured” ubdm . However, using ubdm to compute worst-case execution time values for programs running on COTS multicore processors requires qualification on the soundness of the result. In this paper, we present a measurement-based methodology to derive a ubdm under round-robin (RoRo) and first-in-first-out (FIFO) arbitration, which accurately approximates ubd from above, without needing latency information from the hardware provider. Experimental results, obtained on multiple processor configurations, demonstrate the robustness of the proposed methodology.The research leading to this work has received funding from: the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644080(SAFURE); the European Space Agency under Contract 789.2013 and NPI Contract 40001102880; and COST Action IC1202, Timing Analysis On Code-Level (TACLe). This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. The authors would like to thanks Paul Caheny for his help with the proofreading of this document.Peer ReviewedPostprint (author's final draft

Methods for autonomous wristband placement with a search-and-rescue aerial manipulator

A new robotic system for Search And Rescue (SAR) operations based on the automatic wristband placement on the victims’ arm, which may provide identification, beaconing and remote sensor readings for continuous health monitoring. This paper focuses on the development of the automatic target localization and the device placement using an unmanned aerial manipulator. The automatic wrist detection and localization system uses an RGB-D camera and a convolutional neural network based on the region faster method (Faster R-CNN). A lightweight parallel delta manipulator with a large workspace has been built, and a new design of a wristband in the form of a passive detachable gripper, is presented, which under contact, automatically attaches to the human, while disengages from the manipulator. A new trajectory planning method has been used to minimize the torques caused by the external forces during contact, which cause attitude perturbations. Experiments have been done to evaluate the machine learning method for detection and location, and for the assessment of the performance of the trajectory planning method. The results show how the VGG-16 neural network provides a detection accuracy of 67.99%. Moreover, simulation experiments have been done to show that the new trajectories minimize the perturbations to the aerial platform.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

LD Manager and ld tools: new software to operate lagragian drifters

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New lagragian drifter for coastal applications

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Circular RNA-centered regulatory networks in the physiopathology of cardiovascular diseases

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Non-coding regulatory RNAs are generated as a core output of the eukaryotic genomes, being essential players in cell biology. At the organism level, they are key functional actors in those tissues and organs with limited proliferation capabilities such as the heart. The role of regulatory networks mediated by non-coding RNAs in the pathophysiology of cardiovascular conditions is starting to be unveiled. However, a deeper knowledge of the functional interactions among the diverse non-coding RNA families and their phenotypic consequences is required. This review presents the current knowledge about the functional crosstalk between circRNAs and other biomolecules in the framework of the cardiovascular diseases.This work is supported by COST (European Cooperation in Science and Technology) Action EU-CardioRNA CA17129 and Portuguese Foundation for Science and Technology (FCT) under the framework of the research grant PTDC-MED-GEN-29389-2017.info:eu-repo/semantics/publishedVersio

Robust design optimization in aeronautics using stochastic analysis and evolutionary algorithms

Uncertainties are a daily issue to deal with in aerospace engineering and applications. Robust optimization methods commonly use a random generation of the inputs and take advantage of multi-point criteria to look for robust solutions accounting with uncertainty definition. From the computational point of view, the application to coupled problems, like computational fluid dynamics (CFD) or fluid–structure interaction (FSI), can be extremely expensive. This study presents a coupling between stochastic analysis techniques and evolutionary optimization algorithms for the definition of a stochastic robust optimization procedure. At first, a stochastic procedure is proposed to be applied into optimization problems. The proposed method has been applied to both CFD and FSI problems for the reduction of drag and flutter, respectively

Combined therapies of antithrombotics and antioxidants delay in silico brain tumor progression

Glioblastoma multiforme, the most frequent type of primary brain tumor, is a rapidly evolving and spatially heterogeneous high-grade astrocytoma that presents areas of necrosis, hypercellularity and microvascular hyperplasia. The aberrant vasculature leads to hypoxic areas and results in an increase of the oxidative stress selecting for more invasive tumor cell phenotypes. In our study we assay in silico different therapeutic approaches which combine antithrombotics, antioxidants and standard radiotherapy. To do so, we have developed a biocomputational model of glioblastoma multiforme that incorporates the spatio-temporal interplay among two glioma cell phenotypes corresponding to oxygenated and hypoxic cells, a necrotic core and the local vasculature whose response evolves with tumor progression. Our numerical simulations predict that suitable combinations of antithrombotics and antioxidants may diminish, in a synergetic way, oxidative stress and the subsequent hypoxic response. This novel therapeutical strategy, with potentially low or no toxicity, might reduce tumor invasion and further sensitize glioblastoma multiforme to conventional radiotherapy or other cytotoxic agents, hopefully increasing median patient overall survival time.Comment: 8 figure

Multicore Early Design Stage Guaranteed Performance Estimates for the Space Domain

The ability to produce early guaranteed performance (worst-case execution time) estimates for multicores, i.e. before software from different providers gets integrated onto the same critical system, is pivotal. This helps reducing lately-detected costly-to-handle timing violations. An existing methodology creates ‘copy’ (surrogate) applications from the execution in isolation of each target application. Surrogate applications can be used to upperbound multicore contention delay, and hence WCET estimates in multicores. However, this methodology has only been shown to work on a simulation environment. In this paper we show the work we have carried out to adapt this technology to a real multicore processor for the space domain.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant TIN2015-65316-P, and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoc fellowship RYC-2013-14717.Peer ReviewedPostprint (author's final draft

Design and deployment of Low-Cost Drifting Buoys for coastal monitoring applications

Several Low-Coast Drifting Buoys (LCDB) have been designed and constructed at ICMAN-CSIC to determine flow characteristics of The Guadalquivir Estuary. Position and velocity of the driftes can be sent to a local server every ten minutes. The battery module has been dimensioned to provide experiment duration longer than two weeks. Flow patterns registered by the LCDB successfully match Acoustic Doppler Current (ADC) data from some others moored ADC profilers.Peer Reviewe