A new gravitational N-body simulation algorithm for investigation of cosmological chaotic advection

Recently alternative approaches in cosmology seeks to explain the nature of dark matter as a direct result of the non-linear spacetime curvature due to different types of deformation potentials. In this context, a key test for this hypothesis is to examine the effects of deformation on the evolution of large scales structures. An important requirement for the fine analysis of this pure gravitational signature (without dark matter elements) is to characterize the position of a galaxy during its trajectory to the gravitational collapse of super clusters at low redshifts. In this context, each element in an gravitational N-body simulation behaves as a tracer of collapse governed by the process known as chaotic advection (or lagrangian turbulence). In order to develop a detailed study of this new approach we develop the COsmic LAgrangian TUrbulence Simulator (COLATUS) to perform gravitational N-body simulations based on Compute Unified Device Architecture (CUDA) for graphics processing units (GPUs). In this paper we report the first robust results obtained from COLATUS.Comment: Proceedings of Sixth International School on Field Theory and Gravitation-2012 - by American Institute of Physic

The viability of treated piggery wastewater for reuse in agricultural irrigation

Artigo publicado em:International Journal of Recycling of Organic Waste in AgricultureThe swine production is a very important economic matter, occupying prominent position in the worldwide market. However, it appears as the greater impacting activity for the water resources. Researches point a swine manure production of 105.6 million m3/year in Brazil, which resulted in a piggery wastewater rich in solids, nutrients, heavy metals, and pathogens. Moreover, the water consumption for swine production is approximately 15 L/animal/day in southern Brazil, resulting in an unsustainable water resource demand. Thereby, this study verifies the viability of two parallel stabilization reservoirs as a technology for polishing treated piggery wastewater. This technology has been shown effective in reducing organic matter, nutrients, and pathogens in the treatment of the effluents with low or high organic load rate. The reservoirs can improve effluent quality with minimal energy costs to simple operations. The technique would promote the value of the effluent through its reuse for agricultural irrigation. The study was conducted at a farm in the city of Braço do Norte, Santa Catarina, in southern Brazil; this region has one of the largest densities of pigs in the world, which causes serious environmental problems

Estimation of emission rate from experimental data

The estimation of the source pollutant strength is a relevant issue for atmospheric environment. This characterizes an inverse problem in the atmospheric pollution dispersion studies. In the inverse analysis, a time-dependent pollutant source is considered, where the location of such source term is assumed known. The inverse problem is formulated as a non-linear optimization approach, whose objective function is given by the least-square difference between the measured and simulated by the mathematical model, pollutant concentration, associated with a regularization operator. The forward problem is addressed by a Lagrangian model, and a quasi-Newton method is employed for minimizing the objective function. The second-order Tikhonov regularization is applied and the regularization parameter is computed by using the L-curve scheme. The inverse-problem methodology is verified with data from the tracer Copenhagen experiment

Production of annual ryegrass with different doses of nitrogen fertilization in topdressing.

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Nutrient recovery from swine waste and protein biomass production using duckweed ponds (Landoltia punctata): Southern Brazil

Artigo publicado em: IWA - Water Sciencie et TechnologyBrazil is one of the most important countries in pork production worldwide, ranking third. This activity has an important role in the national economic scenario. However, the fast growth of this activity has caused major environmental impacts, especially in developing countries. The large amount of nitrogen and phosphorus compounds found in pig manure has caused ecological imbalances, with eutrophication of major river basins in the producing regions. Moreover, much of the pig production in developing countries occurs on small farms, and therefore causes diffuse pollution. Therefore, duckweed pond have been successfully used in the swine waste polishing, generating further a biomass with high protein content. The present study evaluated the efficiency of two full scale duckweed ponds for the polishing of a small pig farm effluent, biomass yield and crude protein (CP) content. Duckweed pond series received the effluent from a biodigester-storage pond, with a flow rate of 1 m3/day (chemical oxygen demand rate ¼ 186 kg/ha day) produced by 300 animals. After 1 year a great improvement of effluent quality was observed, with removal of 96% of total Kjeldahl nitrogen (TKN) and 89% of total phosphorus (TP), on average. Nitrogen removal rate is one of the highest ever found (4.4 g TKN/m2 day). Also, the dissolved oxygen rose from 0.0 to 3.0 mg/L. The two ponds produced together over 13 tons of fresh biomass (90.5% moisture), with 35% of CP content, which represents a productivity of 24 tonsCP/ha year. Due to the high rate of nutrient removal, and also the high protein biomass production, duckweed ponds revealed, under the presented conditions, a great potential for the polishing and valorization of swine waste. Nevertheless, this technology should be better exploited to improve the sustainability of small pig farms in order to minimize the impacts of this activity on the environment

Specific insulin and proinsulin secretion in glucokinase-deficient individuals

Glucokinase (GCK) is an enzyme that regulates insulin secretion, keeping glucose levels within a narrow range. Mutations in the glucokinase gene cause a rare form of diabetes called maturity-onset diabetes of the young (MODY). An early onset (less than 25 years), autosomal dominant inheritance and low insulin secretion stimulated by glucose characterize MODY patients. Specific insulin and proinsulin were measured in serum by immunofluorimetric assays (IFMA) during a 75-g oral glucose tolerance test (OGTT). Two kindreds (SA and LZ) were studied and compared to non-diabetic unrelated individuals (control group 1) matched for age and body mass index (BMI). In one kindred, some of these subjects were also obese (BMI >26 kg/m2), and other family members also presented with obesity and/or late-onset NIDDM. The MODY patients were also compared to a group of five of their first-degree relatives with obesity and/or late-onset NIDDM. The proinsulin profile was different in members of the two MODY kindreds. Fasting proinsulin and the proinsulin/insulin ratio were similar in MODY members of kindred LZ and subjects from control group 1, but were significantly lower than in MODY members of kindred SA (P<0.02 and P<0.01, for proinsulin and proinsulin/insulin ratio, respectively). Moreover, MODY members of family SA had higher levels of proinsulin and proinsulin/insulin ratio, although not significantly different, when compared to their first-degree relatives and to subjects from control group 2. In conclusion, we observed variable degrees of proinsulin levels and proinsulin/insulin ratio in MODY members of two different kindreds. The higher values of these parameters found in MODY and non-MODY members of kindred SA is probably related to the obesity and late-onset NIDDM background present in this family.Hospital Santa CasaHôpital Saint-LouisFondation Jean DaussetUniversidade Federal de São Paulo (UNIFESP)UNIFESPSciEL

Fair Resource Sharing for Dynamic Scheduling of Workflows on Heterogeneous Systems

International audienceScheduling independent workflows on shared resources in a way that satisfy users Quality of Service is a significant challenge. In this study, we describe methodologies for off-line scheduling, where a schedule is generated for a set of knownworkflows, and on-line scheduling, where users can submit workflows at any moment in time. We consider the on-line scheduling problem in more detail and present performance comparisons of state-of-the-art algorithms for a realistic model of a heterogeneous system

Decision Tree Classifiers for Star/Galaxy Separation

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of $884,126$ SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: $14\le r\le21$ ($85.2$) and $r\ge19$ ($82.1$). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT and Ball et al. (2006). We find that our FT classifier is comparable or better in completeness over the full magnitude range $15\le r\le21$, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes ($r>19$), our classifier is the only one able to maintain high completeness ($>$80%) while still achieving low contamination ($\sim2.5$). Finally, we apply our FT classifier to separate stars from galaxies in the full set of $69,545,326$ SDSS photometric objects in the magnitude range $14\le r\le21$.Comment: Submitted to A