Multi-Objective Big Data Optimization with jMetal and Spark

Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi-objective Big Data Optimization problems. Our purpose is to study the influence of accessing data stored in the Hadoop File System (HDFS) in each evaluation step of a metaheuristic and to provide a software tool to solve these kinds of problems. This tool combines the jMetal multi-objective optimization framework with Apache Spark. We have carried out experiments to measure the performance of the proposed parallel infrastructure in an environment based on virtual machines in a local cluster comprising up to 100 cores. We obtained interesting results for computational e ort and propose guidelines to face multi-objective Big Data Optimization problems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

N 2 O emissions and NO 3 − leaching from two contrasting regions in Austria and influence of soil, crops and climate: a modelling approach

National emission inventories for UN FCCC reporting estimate regional soil nitrous oxide (N 2 O) fluxes by considering the amount of N input as the only influencing factor for N 2 O emissions. Our aim was to deepen the understanding of N 2 O fluxes from agricultural soils, including region specific soil and climate properties into the estimation of emission to find targeted mitigation measures for the reduction of nitrogen losses and GHG emissions. Within this project, N 2 O emissions and nitrate (NO 3 − ) leaching were modelled under spatially distinct environmental conditions in two agricultural regions in Austria taking into account region specific soil and climatic properties, management practices and crop rotations. The LandscapeDNDC ecosystem model was used to calculate N 2 O emissions and NO 3 − leaching reflecting different types of vegetation, management operations and crop rotations. In addition, N input and N fluxes were assessed and N 2 O emissions were calculated. This approach allowed identifying hot spots of N 2 O emissions. Results show that certain combinations of soil type, weather conditions, crop and management can lead to high emissions. Mean values ranged from 0.15 to 1.29 kg N 2 O–N ha −1  year −1 (Marchfeld) and 0.26 to 0.52 kg N 2 O–N ha −1  year −1 (Grieskirchen). Nitrate leaching, which strongly dominated N-losses, often reacted opposite to N 2 O emissions. Larger quantities of NO 3 − were lost during years of higher precipitation, especially if winter barley was cultivated on sandy soils. Taking into account the detected hot spots of N 2 O emissions and NO 3 − leaching most efficient measures can be addressed to mitigate environmental impacts while maximising crop production. © 2018, The Author(s)

The direct evaluation of attosecond chirp from a streaking measurement

We derive an analytical expression, from classical electron trajectories in a laser field, that relates the breadth of a streaked photoelectron spectrum to the group-delay dispersion of an isolated attosecond pulse. Based on this analytical expression, we introduce a simple, efficient and robust procedure to instantly extract the attosecond pulse's chirp from the streaking measurement.Comment: 4 figure

Enhanced ionization of acetylene in intense laser pulses is due to energy upshift and field coupling of multiple orbitals

Synopsis We describe a new enhanced ionization mechanism for polyatomic molecules. It works via a significant energy up-shift of valence orbitals for stretched bonds and a strong concomitant increase in the coupling between multiple molecular orbitals

The abundance of nitrogen cycle genes and potential greenhouse gas fluxes depends on land use type and little on soil aggregate size

Soil structure is known to influence microbial communities in soil and soil aggregates are the fundamental ecological unit of organisation that support soil functions. However, still little is known about the distribution of microbial communities and functions between soil aggregate size fractions in relation to land use. Thus, the objective of this study was to determine the gene abundance of microbial communities related to the nitrogen cycle and potential greenhouse gas (GHG) fluxes in six soil aggregate sizes (0–0.25, 0.25–0.5, 0.5–1.0, 1–2, 2–5, 5–10 mm) in four land uses (i.e. grassland, cropland, forest, young forest). Quantitative-PCR (Q-PCR) was used to investigate the abundance of bacteria, archaea and fungi, and functional guilds involved in N-fixation (nifH gene), nitrification (bacterial and archaeal amoA genes) and denitrification (narG, nirS, and nosZ genes). Land use leads to significantly different abundances for all genes analysed, with the cropland site showing the lowest abundance for all genes except amoA bacteria and archaea. In contrast, not a single land use consistently showed the highest gene abundance for all the genes investigated. Variation in gene abundance between aggregate size classes was also found, but the patterns were gene specific and without common trends across land uses. However, aggregates within the size class of 0.5–1.0 mm showed high bacterial 16S, nifH, amoA bacteria, narG, nirS and nosZ gene abundance for the two forest sites but not for fungal ITS and archaeal 16S. The potential GHG fluxes were affected by land use but the effects were far less pronounced than for microbial gene abundance, inconsistent across land use and soil aggregates. However, few differences in GHG fluxes were found between soil aggregate sizes. From this study, land use emerges as the dominant factor that explains the distribution of N functional communities and potential GHG fluxes in soils, with less pronounced and less generalized effects of aggregate size

Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 2: Untangling climatic, edaphic, management and nitrogen deposition effects on carbon sequestration potentials

The effects of atmospheric nitrogen deposition (N$_{dep}$) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of N$_{dep}$ across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry+wet) reactive nitrogen (N$_{r}$) deposition.We propose a methodology for untangling the effects of N$_{dep}$ from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO$_{2}$ exchange fluxes from a Europe-wide network of 22 forest flux towers. Total N$_{r}$ deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP= dN$_{dep}$) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP/dN$_{dep}$ value. This model-enhanced analysis of the C and N$_{dep}$ flux observations at the scale of the European network suggests a mean overall dNEP/dN$_{dep}$ response of forest lifetime C sequestration to N$_{dep}$ of the order of 40–50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus N$_{dep}$ were non-linear, with no further growth responses at high N$_{dep}$ levels (N$_{dep}$ >2.5–3 gNm$^{-2}$ yr$^{-1}$) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high N$_{dep}$ levels implies that the forecast increased N$_{r}$ emissions and increased Ndep levels in large areas of Asia may not positively impact the continent’s forest CO$_{2}$ sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC/dN response