Minimum ignition energy of methanol-air mixtures

A method for computing minimum ignition energies for gaseous fuel mixtures with detailed and reduced chemistry, by numerical integration of time-dependent conservation equations in a spherically symmetrical configuration, is presented and discussed, testing its general characteristics and accuracy. The method is applied to methanol-air mixtures described by a 38-step Arrhenius chemistry description and by an 8-step chemistry description based on steady-state approximations for reaction intermediaries. Comparisons of predictions with results of available experimental measurements produced reasonable agreements and supported both the robustness of the computational method and the usefulness of the 8-step reduction in achieving accurate predictions.This work was supported by the Spanish MCINN through Projects # CSD2010-00011, ENE2012-33213 and ENE2015-65852-C2-1-R

A multipurpose reduced chemical-kinetic mechanism for methanol combustion

A multipurpose reduced chemical-kinetic mechanism for methanol combustion comprising 8 overall reactions and 11 reacting chemical species is presented. The development starts by investigating the minimum set of elementary reactions needed to describe methanol combustion with reasonable accuracy over a range of conditions of temperature, pressure, and composition of interest in combustion. Starting from a 27-step mechanism that has been previously tested and found to give accurate predictions of ignition processes for these conditions, it is determined that the addition of 11 elementary reactions taken from its basis (San Diego) mechanism extends the validity of the description to premixed-flame propagation, strain-induced extinction of non-premixed flames, and equilibrium composition and temperatures, giving results that compare favourably with experimental measurements and also with computations using the 247-step detailed San Diego mechanism involving 50 reactive species. Specifically, premixed-flame propagation velocities and extinction strain rates for non-premixed counterflow flames calculated with the 38-step mechanism show departures from experimental measurements and detailed-chemistry computations that are roughly on the order of 10%, comparable with expected experimental uncertainties. Similar accuracy is found in comparisons of autoignition times over the range considered, except at very high temperatures, under which conditions the computations tend to overpredict induction times for all of the chemistry descriptions tested. From this 38-step mechanism, the simplification is continued by introducing steady-state approximations for the intermediate species CH3, CH4, HCO, CH3O, CH2OH, and O, leading to an 8-step reduced mechanism that provides satisfactory accuracy for all conditions tested.This work was supported by the Spanish MCINN [projects numbers CSD2010-00011, ENE2012-33213 and ENE2015-65852-C2-1-R

Dynamically biased statistical model for the ortho/para conversion in the H2 + H3+ → H3+ + H2 reaction

In this work we present a dynamically biased statistical model to describe the evolution of the title reaction from statistical to a more direct mechanism, using quasi-classical trajectories (QCT). The method is based on the one previously proposed by Park and Light [J. Chem. Phys. 126, 044305 (2007)10.1063/1.2430711]. A recent global potential energy surface is used here to calculate the capture probabilities, instead of the long-range ion-induced dipole interactions. The dynamical constraints are introduced by considering a scrambling matrix which depends on energy and determine the probability of the identity/hop/exchange mechanisms. These probabilities are calculated using QCT. It is found that the high zero-point energy of the fragments is transferred to the rest of the degrees of freedom, what shortens the lifetime of H 5+ complexes and, as a consequence, the exchange mechanism is produced with lower proportion. The zero-point energy (ZPE) is not properly described in quasi-classical trajectory calculations and an approximation is done in which the initial ZPE of the reactants is reduced in QCT calculations to obtain a new ZPE-biased scrambling matrix. This reduction of the ZPE is explained by the need of correcting the pure classical level number of the H 5+ complex, as done in classical simulations of unimolecular processes and to get equivalent quantum and classical rate constants using Rice-Ramsperger-Kassel-Marcus theory. This matrix allows to obtain a ratio of hop/exchange mechanisms, α(T), in rather good agreement with recent experimental results by Crabtree [J. Chem. Phys. 134, 194311 (2011)10.1063/1.3587246] at room temperature. At lower temperatures, however, the present simulations predict too high ratios because the biased scrambling matrix is not statistical enough. This demonstrates the importance of applying quantum methods to simulate this reaction at the low temperatures of astrophysical interestThis work has been supported by the program CONSOLIDER-INGENIO 2010 of Ministerio de Ciencia e Innovación under Grant No. CSD2009-00038, entitled “Molecular strophysics: the Herschel and Alma era,” and by Grant Nos. FIS2011-29596-C02 and QCQ2008-02578, and by Comunidad Autónoma de Madrid (CAM) under Grant No. S-2009/MAT/146

Ordinal and nominal classication of wind speed from synoptic pressure patterns

Wind speed reconstruction is a challenging problem in areas (mainly wind farms) where there are not direct wind measures available. Di erent approaches have been applied to this reconstruction, such as measure-correlatepredict algorithms, approaches based on physical models such as reanalysis methods, or more recently, indirect measures such as pressure, and its relation to wind speed. This paper adopts the latter method, and deals with wind speed estimation in wind farms from pressure measures, but including different novelties in the problem treatment. Existing synoptic pressure-based indirect approaches for wind speed estimation are based on considering the wind speed as a continuous target variable, estimating then the corresponding wind series of continuous values. However, the exact wind speed is not always needed by wind farms managers, and a general idea of the level of speed is, in the majority of cases, enough to set functional operations for the farm (such as wind turbines stop, for example). Moreover, the accuracy of the models obtained is usually improved for the classi cation task, given that the problem is simpli ed. Thus, this paper tackles the problem of wind speed prediction from synoptic pressure patterns by considering wind speed as a discrete variable and, consequently, wind speed prediction as a classi cation problem, with four wind level categories: low, moderate, high or very high. Moreover, taking into account that these four di erent classes are associated to four values in an ordinal scale, the problem can be considered as an ordinal regression problem. The performance of several ordinal and nominal classi- ers and the improvement achieved by considering the ordering information are evaluated. The results obtained in this paper present the Support Vector Machine as the best tested classi er for this task. In addition, the use of the intrinsic ordering information of the problem is shown to signi cantly improve ranks with respect to nominal classi cation, although di erences in accuracy are smal

Detection of peanut (Arachis hypogaea) allergens in processed foods by immunoassay: Influence of selected target protein and ELISA format applied

Direct competitive and sandwich ELISA formats developed to determine Ara h1 and Ara h2 proteins were applied in the detection of peanut in model biscuits prepared with a commercial peanut butter as ingredient. The sandwich format for Ara h2 protein could detect the addition of 2.5% peanut butter, whereas the same format for Ara h1 could not detect 5% added peanut. Direct competitive formats for Ara h1 and Ara h2 proteins could detect the addition of 1% and 0.05% peanut butter, respectively. Therefore, competitive format for Ara h2 was selected to be evaluated by four laboratories, obtaining adequate results in term of repeatability and reproducibility. Results obtained indicate that processing decreased the level of extracted proteins and underestimated the amount of Ara h1 and Ara h2 proteins, the effect being more severe for Ara h1. The selection of the target protein and the ELISA format applied greatly influence the detection of peanut in processed foods

Wildlife and Antibiotic Resistance

Antibiotic resistance is a major human health problem. While health care facilities are main contributors to the emergence, evolution and spread of antibiotic resistance, other ecosystems are involved in such dissemination. Wastewater, farm animals and pets have been considered important contributors to the development of antibiotic resistance. Herein, we review the impact of wildlife in such problem. Current evidence supports that the presence of antibiotic resistance genes and/or antibiotic resistant bacteria in wild animals is a sign of anthropic pollution more than of selection of resistance. However, once antibiotic resistance is present in the wild, wildlife can contribute to its transmission across different ecosystems. Further, the finding that antibiotic resistance genes, currently causing problems at hospitals, might spread through horizontal gene transfer among the bacteria present in the microbiomes of ubiquitous animals as cockroaches, fleas or rats, supports the possibility that these organisms might be bioreactors for the horizontal transfer of antibiotic resistance genes among human pathogens. The contribution of wildlife in the spread of antibiotic resistance among different hosts and ecosystems occurs at two levels. Firstly, in the case of non-migrating animals, the transfer will take place locally; a One Health problem. Paradigmatic examples are the above mentioned animals that cohabit with humans and can be reservoirs and vehicles for antibiotic resistance dissemination. Secondly, migrating animals, such as gulls, fishes or turtles may participate in the dissemination of antibiotic resistance across different geographic areas, even between different continents, which constitutes a Global Health issue. Copyright © 2022 Laborda, Sanz-García, Ochoa-Sánchez, Gil-Gil, Hernando-Amado and Martínez

Effects of Topography and Surface Soil Cover on Erosion for Mining Reclamation: The Experimental Spoil Heap at El Machorro Mine (Central Spain)

Mining reclamation tries to reduce environmental impacts, including accelerated runoff, erosion and sediment load in the nearby fluvial networks and their ecosystems. This study compares the effects of topography and surface soil cover on erosion on man-made slopes coming from surface mining reclamation in Central Spain. Two topographic profiles, linear and concave, with two surface soil covers, subsoil and topsoil, were monitored for two hydrologic years. Sediment load, rill development and plant colonization from the four profiles were measured under field conditions. The results show that, in the case of this experiment, a thick and non-compacted topsoil cover on a linear slope yielded less sediment than carbonate colluvium or topsoil cover on a concave slope. This study also shows that vegetation establishment, which plays an important role in erosion control, depends on topography. Plant cover was more widespread and more homogeneous on linear profiles with topsoil cover. On concave slopes, plant establishment was severely limited on the steepest upper part and favoured in the bottom. This study suggests that management of topography and surface soil cover should be approached systematically, taking three outcomes into consideration: (i) topsoil can lead to a successful mining reclamation regardless of topography, (ii) created concave slopes can lead to a successful mining reclamation and (iii) topography determines the vegetation colonization pattern.The experiment was funded by a research contract between the Spanish mining company 602 CAOBAR S.A. and the Department of Geodynamics of the Complutense University of Madrid 603 (research contract numbers 234/2007, 290/2008 261/2009). The data analyses and manuscript 604 production were developed within two Research Projects, CGL2009-14508-C02-01 and 605 CGL2010-21754-C02, of the Spanish Ministry of Science and Technology and by the 606 Ecological Restoration network REMEDINAL-2 (S2009/AMB-1783).Peer reviewe

Phases I–III Clinical Trials Using Adult Stem Cells

First randomized clinical trials have demonstrated that stem cell therapy can improve cardiac recovery after the acute phase of myocardial ischemia and in patients with chronic ischemic heart disease. Nevertheless, some trials have shown that conflicting results and uncertainties remain in the case of mechanisms of action and possible ways to improve clinical impact of stem cells in cardiac repair. In this paper we will examine the evidence available, analyze the main phase I and II randomized clinical trials and their limitations, discuss the key points in the design of future trials, and depict new directions of research in this fascinating field

Aggregation methods in dynamical systems and applications in population and community dynamics

Approximate aggregation techniques allow one to transform a complex system involving many coupled variables into a simpler reduced model with a lesser number of global variables in such a way that the dynamics of the former can be approximated by that of the latter. In ecology, as a paradigmatic example, we are faced with modelling complex systems involving many variables corresponding to various interacting organization levels. This review is devoted to approximate aggregation methods that are based on the existence of different time scales, which is the case in many real systems as ecological ones where the different organization levels (individual, population, community and ecosystem) possess a different characteristic time scale. Two main goals of variables aggregation are dealt with in this work. The first one is to reduce the dimension of the mathematical model to be handled analytically and the second one is to understand how different organization levels interact and which properties of a given level emerge at other levels. The review is organized in three sections devoted to aggregation methods associated to different mathematical formalisms: ordinary differential equations, infinite-dimensional evolution equations and difference equations

Discrete Models of Disease and Competition

The aim of this work is to analyze the influence of the fast development of a disease on competition dynamics. To this end we present two discrete time ecoepidemic models. The first one corresponds to the case of one parasite affecting demography and intraspecific competition in a single host, whereas the second one contemplates the more complex case of competition between two different species, one of which is infected by the parasite. We carry out a complete mathematical analysis of the asymptotic behavior of the solutions of the corresponding systems of difference equations and derive interesting ecological information about the influence of a disease in competition dynamics. This includes an assessment of the impact of the disease on the equilibrium population of both species as well as some counterintuitive behaviors in which although we would expect the outbreak of the disease to negatively affect the infected species, the contrary happens