Running Genetic Algorithms in the Edge: A First Analysis

Nowadays, the volume of data produced by different kinds of devices is continuously growing, making even more difficult to solve the many optimization problems that impact directly on our living quality. For instance, Cisco projected that by 2019 the volume of data will reach 507.5 zettabytes per year, and the cloud traffic will quadruple. This is not sustainable in the long term, so it is a need to move part of the intelligence from the cloud to a highly decentralized computing model. Considering this, we propose a ubiquitous intelligent system which is composed by different kinds of endpoint devices such as smartphones, tablets, routers, wearables, and any other CPU powered device. We want to use this to solve tasks useful for smart cities. In this paper, we analyze if these devices are suitable for this purpose and how we have to adapt the optimization algorithms to be efficient using heterogeneous hardware. To do this, we perform a set of experiments in which we measure the speed, memory usage, and battery consumption of these devices for a set of binary and combinatorial problems. Our conclusions reveal the strong and weak features of each device to run future algorihms in the border of the cyber-physical system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This research has been partially funded by the Spanish MINECO and FEDER projects TIN2014-57341-R (http://moveon.lcc.uma.es), TIN2016-81766-REDT (http://cirti.es), TIN2017-88213-R (http://6city.lcc.uma.es), the Ministry of Education of Spain (FPU16/02595

Overall evaluation of Skylab imagery for mapping of Latin America

The author has identified the following significant results. Skylab imagery is both desired and needed by the Latin American catographic agencies. The imagery is cost beneficial for the production of new mapping and maintenance of existing maps at national topographic series scales. If this information was available on a near time routine coverage basis, it would provide an excellent additional data base to the Latin American cartographic community, specifically Argentina, Bolivia, Chile, Colombia, Dominican Republic, Guatemala, Paraguay, and Venezuela

A Deep Learning Approach to Estimate Multi-Level Mental Stress from EEG using Serious Games

Stress is revealed by the inability of individuals to cope with their environment, which is frequently evidenced by a failure to achieve their full potential in tasks or goals. This study aims to assess the feasibility of estimating the level of stress that the user is perceiving related to a specific task through an electroencephalograpic (EEG) system. This system is integrated with a Serious Game consisting of a multi-level stress driving tool, and Deep Learning (DL) neural networks are used for classification. The game involves controlling a vehicle to dodge obstacles, with the number of obstacles increasing based on complexity. Assuming that there is a direct correlation between the difficulty level of the game and the stress level of the user, a recurrent neural network (RNN) with a structure based on gated recurrent units (GRU) was used to classify the different levels of stress. The results show that the RNN model is able to predict stress levels above current state-of-the-art with up to 94% accuracy in some cases, suggesting that the use of EEG systems in combination with Serious Games and DL represents a promising technique in the prediction and classification of mental stress levels

Disease Knowledge Transfer across Neurodegenerative Diseases

We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal biomarker trajectories in rare neurodegenerative diseases even when only limited, unimodal data is available, by transferring information from larger multimodal datasets from common neurodegenerative diseases. DKT is a joint-disease generative model of biomarker progressions, which exploits biomarker relationships that are shared across diseases. Our proposed method allows, for the first time, the estimation of plausible, multimodal biomarker trajectories in Posterior Cortical Atrophy (PCA), a rare neurodegenerative disease where only unimodal MRI data is available. For this we train DKT on a combined dataset containing subjects with two distinct diseases and sizes of data available: 1) a larger, multimodal typical AD (tAD) dataset from the TADPOLE Challenge, and 2) a smaller unimodal Posterior Cortical Atrophy (PCA) dataset from the Dementia Research Centre (DRC), for which only a limited number of Magnetic Resonance Imaging (MRI) scans are available. Although validation is challenging due to lack of data in PCA, we validate DKT on synthetic data and two patient datasets (TADPOLE and PCA cohorts), showing it can estimate the ground truth parameters in the simulation and predict unseen biomarkers on the two patient datasets. While we demonstrated DKT on Alzheimer's variants, we note DKT is generalisable to other forms of related neurodegenerative diseases. Source code for DKT is available online: https://github.com/mrazvan22/dkt.Comment: accepted at MICCAI 2019, 13 pages, 5 figures, 2 table

Th Ages for Metal-Poor Stars

With a sample of 22 metal-poor stars, we demonstrate that the heavy element abundance pattern (Z > 55) is the same as the r-process contributions to the solar nebula. This bolsters the results of previous studies that there is a universal r-process production pattern. We use the abundance of thorium in five metal-poor stars, along with an estimate of the initial Th abundance based on the abundances of stable r-process elements, to measure their ages. We have four field red giants with errors of 4.2 Gyr in their ages and one M92 giant with an error of 5.6 Gyr, based on considering the sources of observational error only. We obtain an average age of 11.4 Gyr, which depends critically on the assumption of an initial production ratio of Th/Eu of 0.496. If the Universe is 15 Gyr old, then the initial Th/Eu value should be 0.590, in agreement with some theoretical models of the r-process.Comment: 26 pages, to be published in Ap

Simplified, Enhanced Protein Purification Using an Inducible, Autoprocessing Enzyme Tag

We introduce a new method for purifying recombinant proteins expressed in bacteria using a highly specific, inducible, self-cleaving protease tag. This tag is comprised of the Vibrio cholerae MARTX toxin cysteine protease domain (CPD), an autoprocessing enzyme that cleaves exclusively after a leucine residue within the target protein-CPD junction. Importantly, V. cholerae CPD is specifically activated by inositol hexakisphosphate (InsP6), a eukaryotic-specific small molecule that is absent from the bacterial cytosol. As a result, when His6-tagged CPD is fused to the C-terminus of target proteins and expressed in Escherichia coli, the full-length fusion protein can be purified from bacterial lysates using metal ion affinity chromatography. Subsequent addition of InsP6 to the immobilized fusion protein induces CPD-mediated cleavage at the target protein-CPD junction, releasing untagged target protein into the supernatant. This method condenses affinity chromatography and fusion tag cleavage into a single step, obviating the need for exogenous protease addition to remove the fusion tag(s) and increasing the efficiency of tag separation. Furthermore, in addition to being timesaving, versatile, and inexpensive, our results indicate that the CPD purification system can enhance the expression, integrity, and solubility of intractable proteins from diverse organisms

Economic impact of improving patient safety using Sugammadex for routine reversal of neuromuscular blockade in Spain

Background: Neuromuscular blocking (NMB) agents are often administered to facilitate tracheal intubation and prevent patient movement during surgical procedures requiring the use of general anesthetics. Incomplete reversal of NMB, can lead to residual NMB, which can increase the risk of post-operative pulmonary complications. Sugammadex is indicated to reverse neuromuscular blockade induced by rocuronium or vecuronium in adults. The aim of this study is to estimate the clinical and economic impact of introducing sugammadex to routine reversal of neuromuscular blockade (NMB) with rocuronium in Spain. Methods: A decision analytic model was constructed reflecting a set of procedures using rocuronium that resulted in moderate or deep NMB at the end of the procedure. Two scenarios were considered for 537, 931 procedures using NMB agents in Spain in 2015: a scenario without sugammadex versus a scenario with sugammadex. Comparators included neostigmine (plus glycopyrrolate) and no reversal agent. The total costs for the healthcare system were estimated from the net of costs of reversal agents and overall cost offsets via reduction in postoperative pneumonias and atelectasis for which incidence rates were based on a Spanish real-world evidence (RWE) study. The model time horizon was assumed to be one year. Costs were expressed in 2019 euros (€) and estimated from the perspective of a healthcare system. One-way sensitivity analysis was carried out by varying each parameter included in the model within a range of +/- 50%. Results: The estimated budget impact of the introduction of sugammadex to the routine reversal of neuromuscular blockade in Spanish hospitals was a net saving of €57.1 million annually. An increase in drug acquisition costs was offset by savings in post-operative pulmonary events, including 4806 post-operative pneumonias and 13, 996 cases of atelectasis. The total cost of complications avoided was €70.4 million. All parameters included in the model were tested in sensitivity analysis and were favorable to the scenario with sugammadex. Conclusions: This economic analysis shows that sugammadex can potentially lead to cost savings for the reversal of rocuronium-induced moderate or profound NMB compared to no reversal and reversal with neostigmine in the Spanish health care setting. The economic model was based on data obtained from Spain and from assumptions from clinical practice and may not be valid for other countries