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

A nonlinear equation system approach to the dynamic stochastic user equilibrium simultaneous route and departure time choice problem

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Does prohibitin expression regulate sperm mitochondrial membrane potential, sperm motility, and male fertility?

Prohibitin (PHB) is a highly conserved major sperm mitochondrial membrane protein whose absence in somatic cells is associated with mitochondrial membrane depolarization and increased generation of reactive oxygen species (ROS). Our recent findings suggest that high levels of oxidants in human semen may contribute to male infertility and that sperm motility could be the earliest and most sensitive indicator of oxidative damage. Based on PHB's roles in mitochondrial sub-compartmentalization and respiratory chain assembly, we examine sperm PHB expression and mitochondrial membrane potential (MITO) in infertile men with poor sperm motility (asthenospermia, A) and/or low sperm concentrations (oligoasthenospermia, OA). Here, we demonstrate that MITO is significantly lower in sperm from A and OA subjects than in normospermic (N) subjects; the decrease is more severe for OA than for A subjects. PHB expression is also significantly lower in sperm from A and OA subjects. Significantly positive correlations are found among PHB expression, MITO, and sperm motility in normospermic, asthenospermic, and oligoasthenospermic subjects. Collectively, our observations lead to the hypothesis that PHB expression is an indicator of sperm quality in infertile men, and that it regulates sperm motility via an alteration in MITO and increased ROS levels. © Copyright 2012, Mary Ann Liebert, Inc.published_or_final_versio

The nonlinear equation system approach to solving dynamic user optimal simultaneous route and departure time choice problems

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Characterization of Shewanella oneidensis MtrC: a cell-surface decaheme cytochrome involved in respiratory electron transport to extracellular electron acceptors

MtrC is a decaheme c-type cytochrome associated with the outer cell membrane of Fe(III)-respiring species of the Shewanella genus. It is proposed to play a role in anaerobic respiration by mediating electron transfer to extracellular mineral oxides that can serve as terminal electron acceptors. The present work presents the first spectropotentiometric and voltammetric characterization of MtrC, using protein purified from Shewanella oneidensis MR-1. Potentiometric titrations, monitored by UV–vis absorption and electron paramagnetic resonance (EPR) spectroscopy, reveal that the hemes within MtrC titrate over a broad potential range spanning between approximately +100 and approximately -500 mV (vs. the standard hydrogen electrode). Across this potential window the UV–vis absorption spectra are characteristic of low-spin c-type hemes and the EPR spectra reveal broad, complex features that suggest the presence of magnetically spin-coupled low-spin c-hemes. Non-catalytic protein film voltammetry of MtrC demonstrates reversible electrochemistry over a potential window similar to that disclosed spectroscopically. The voltammetry also allows definition of kinetic properties of MtrC in direct electron exchange with a solid electrode surface and during reduction of a model Fe(III) substrate. Taken together, the data provide quantitative information on the potential domain in which MtrC can operate

Tracing magnetism and pairing in FeTe-based systems

In order to examine the interplay between magnetism and superconductivity, we monitor the non- superconducting chalcogenide FeTe and follow its transitions under insertion of oxygen, doping with Se and vacancies of Fe using spin-polarized band structure methods (LSDA with GGA) starting from the collinear and bicollinear magnetic arrangements. We use a supercell of Fe8Te8 as our starting point so that it can capture local changes in magnetic moments. The calculated values of magnetic moments agree well with available experimental data while oxygen insertions lead to significant changes in the bicollinear or collinear magnetic moments. The total energies of these systems indicate that the collinear-derived structure is the more favorable one prior to a possible superconducting transition. Using a 8-site Betts-cluster-based lattice and the Hubbard model, we show why this structure favors electron or hole pairing and provides clues to a common understanding of charge and spin pairing in the cuprates, pnictides and chalcogenides

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Recent changes of water discharge and sediment load in the Yellow River basin, China

The Yellow River basin contributes approximately 6% of the sediment load from all river systems globally, and the annual runoff directly supports 12% of the Chinese population. As a result, describing and understanding recent variations of water discharge and sediment load under global change scenarios are of considerable importance. The present study considers the annual hydrologic series of the water discharge and sediment load of the Yellow River basin obtained from 15 gauging stations (10 mainstream, 5 tributaries). The Mann-Kendall test method was adopted to detect both gradual and abrupt change of hydrological series since the 1950s. With the exception of the area draining to the Upper Tangnaihai station, results indicate that both water discharge and sediment load have decreased significantly (p<0.05). The declining trend is greater with distance downstream, and drainage area has a significant positive effect on the rate of decline. It is suggested that the abrupt change of the water discharge from the late 1980s to the early 1990s arose from human extraction, and that the abrupt change in sediment load was linked to disturbance from reservoir construction.Geography, PhysicalGeosciences, MultidisciplinarySCI(E)43ARTICLE4541-5613

CRISPR-Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity.

Hexanucleotide-repeat expansions in the C9ORF72 gene are the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (c9ALS/FTD). The nucleotide-repeat expansions are translated into dipeptide-repeat (DPR) proteins, which are aggregation prone and may contribute to neurodegeneration. We used the CRISPR-Cas9 system to perform genome-wide gene-knockout screens for suppressors and enhancers of C9ORF72 DPR toxicity in human cells. We validated hits by performing secondary CRISPR-Cas9 screens in primary mouse neurons. We uncovered potent modifiers of DPR toxicity whose gene products function in nucleocytoplasmic transport, the endoplasmic reticulum (ER), proteasome, RNA-processing pathways, and chromatin modification. One modifier, TMX2, modulated the ER-stress signature elicited by C9ORF72 DPRs in neurons and improved survival of human induced motor neurons from patients with C9ORF72 ALS. Together, our results demonstrate the promise of CRISPR-Cas9 screens in defining mechanisms of neurodegenerative diseases