877 resultados para Decomposition algorithms
Resumo:
Necrotrophic parasites of above-ground plant parts survive saprophytically, between growing seasons in host crop residues. In an experiment conducted under field conditions, the time required in months for corn and soybean residues to be completely decomposed was quantified. Residues were laid on the soil surface to simulate no-till farming. Crop debris of the two plant species collected on the harvesting day cut into pieces of 5.0cm-long and a 200g mass was added to nylon mesh bags. At monthly intervals, bags were taken to the laboratory for weighing. Corn residues were decomposed within 37.0 months and those of soybean, within 34.5 months. Hw main necrotrophic fungi diagnosed in the corn residues were Colletotrichum gramicola, Diplodia spp. and Gibberella zeae, and those in soybeans residues were Cercospora kikuchii, Colletotrichum spp, Glomerella sp. and Phomopsis spp. Thus, those periods shoulb be observed in crop rotation aimed at to eliminating contaminated residues and, consequently, the inoculum from the cultivated area.
Resumo:
Litter fall consists of all organic material deposited on the forest floor, being of extremely important for the structure and maintenance of the ecosystem through nutrient cycling. This study aimed to evaluate the production and decomposition of litter fall in a secondary Atlantic forest fragment of secondary Atlantic Forest, at the Guarapiranga Ecological Park, in São Paulo, SP. The litter samples were taken monthly from May 2012 to May 2013. To assess the contribution of litter fall forty collectors were installed randomly within an area of 0.5 ha. The collected material was sent to the laboratory to be dried at 65 °C for 72 hours, being subsequently separated into fractions of leaves, twigs, reproductive parts and miscellaneous, and weighed to obtain the dry biomass. Litterbags were placed and tied close to the collectors to estimate the decomposition rate in order to evaluate the loss of dry biomass at 30, 60, 90, 120 and 150 days. After collection, the material was sent to the laboratory to be dried and weighed again. Total litter fall throughout the year reached 5.7 Mg.ha-1.yr-1 and the major amount of the material was collected from September till March. Leaves had the major contribution for total litter fall (72%), followed by twigs (14%), reproductive parts (11%) and miscellaneous (3%). Reproductive parts had a peak during the wet season. Positive correlation was observed between total litter and precipitation, temperature and radiation (r = 0.66, p<0.05; r = 0.76, p<0.05; r = 0.58, p<0.05, respectively). The multiple regression showed that precipitation and radiation contributed significantly to litter fall production. Decomposition rate was in the interval expected for secondary tropical forest and was correlated to rainfall. It was concluded that this fragment of secondary forest showed a seasonality effect driven mainly by precipitation and radiation, both important components of foliage renewal for the plant community and that decomposition was in an intermediate rate.
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Forest litter decomposition is a major process in returning nutrients to soils and thus promoting wood productivity in the humid tropic. This study aimed to assess decomposition of eucalypt litter in the Rio Doce region, Brazil. Leaf litter was sampled under clonal eucalypt stands aged 2, 4 and 6 years on hillslopes and footslopes. Soil and soil+litter samples were incubated at two levels of soil moisture, temperature and fertilization. C-CO2 emissions from soil measured during 106 days were higher at 32 °C than at 23°C, mainly for the 2-yr-old stand on footslope. When leaf litter was added on soils, C-CO2 emissions were eight times higher, mainly on footslopes, with no effect of stand age. Leaf decomposition in situ, assessed with a litterbag experiment showed a mean weight loss of at least 50% during 365 days, reaching 74% for 2 yr-old stands on footslopes. In comparison with data from the native forest and the literature, no apparent restrictions were found in eucalypt litter decomposition. Differences between in vitro and in situ results, and between eucalypt and native forest, were most likely related to the response of diverse decomposer communities and to substrate quality.
Resumo:
This study was conducted to evaluate the decomposition kinetics of gaseous ozone in peanut grains. This evaluation was made with 1-kg peanut samples, moisture contents being 7.1 and 10.5% wet basis (w.b.), placed in 3-liter glass containers. The peanut grains were ozonated at the concentration of 450 µg L-1, at 25 and 35 ºC, with gas flow rates of 1.0 and 3.0 L min-1. Time of saturation was determined by quantifying the residual concentration of ozone after the gas passed through the grains to constant mass. The decomposition kinetics of ozone was evaluated after the grain mass was ozone-saturated. For the peanut grains whose moisture content was 7.1% (w.b.), at 25 and 35ºC and with flow rates of 1.0 and 3.0 L min-1, the values obtained for time of saturation of gaseous ozone ranged between 173 and 192 min; the concentration of saturation was approximately 260 µg L-1. For the grains whose moisture content was 10.5% (w.b.), a higher residual concentration of gaseous ozone was obtained at 25 ºC, that of 190 µg L-1. As regards the half-life of ozone, the highest value obtained was equivalent to 7.7 min for grains ozonated at 25 ºC, while for those with moisture content of 10.5% at 35 ºC, half-life was 3.2 min. In the process of ozone decomposition in peanut grains, temperature was concluded to be the key factor. An increase of 10 ºC in the temperature of the grains results in a decrease of at least 43% in the half-life of ozone.
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Among the challenges of pig farming in today's competitive market, there is factor of the product traceability that ensures, among many points, animal welfare. Vocalization is a valuable tool to identify situations of stress in pigs, and it can be used in welfare records for traceability. The objective of this work was to identify stress in piglets using vocalization, calling this stress on three levels: no stress, moderate stress, and acute stress. An experiment was conducted on a commercial farm in the municipality of Holambra, São Paulo State , where vocalizations of twenty piglets were recorded during the castration procedure, and separated into two groups: without anesthesia and local anesthesia with lidocaine base. For the recording of acoustic signals, a unidirectional microphone was connected to a digital recorder, in which signals were digitized at a frequency of 44,100 Hz. For evaluation of sound signals, Praat® software was used, and different data mining algorithms were applied using Weka® software. The selection of attributes improved model accuracy, and the best attribute selection was used by applying Wrapper method, while the best classification algorithms were the k-NN and Naive Bayes. According to the results, it was possible to classify the level of stress in pigs through their vocalization.
Poultry carcass decomposition and physicochemical analysis of compounds in different Composter types
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This study aimed to assess five composter types in poultry carcasses decomposition and to perform a physicochemical analysis of the compounds obtained. Composter types used were six-hole brick, wood, screen, windrow with three PVC pipes with six holes and windrow with three PVC pipes with 10 holes. Composting was followed by four periods using wood shaving like substrate with one bird carcass placed in each composter. Pile turning was performed every 10 days and temperature in each layer was measured on 1st, 7th, 14th, 19th and 29th day, at 3 p.m., as well as room temperature. Temperature during pile turning was also measured at five points per layer and carcass weighing performed to calculate decomposition percentage. Physicochemical parameters evaluated in substrates were moisture, ash, phosphorus, potassium, nitrogen, pH, organic carbon and C/N ratio, up to 30 days. Data were analyzed by repeated measures model, using MIXED method of SAS software. All values of final physicochemical composition of substrates were found according to values of IN-25, except nitrogen. The composter types were efficient in decomposition of poultry carcasses.
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Vaahdotusta käytetään yleisesti erottamaan eri mineraaleja malmista. Tässä menetelmässä käytetään erityisiä pinta-aktiivisia aineita, joita kutsutaan kokoojakemikaaleiksi, muuntamaan halutut mineraalit hydrofobisiksi ja erottamaan ne hydrofiilisistä partikkeleista ilmakuplien avulla. Eräs tärkeimmistä kokoojakemikaalien ryhmistä on ksantaatit. Ksantaateilla on havaittu taipumusta hajota useiksi erilaisiksi hajoamistuotteiksi vaahdotusprosessin aikana. Näillä hajoamistuotteilla voi olla monia haitallisia vaikutuksia vaahdotuksen tuloksiin. Näiden tuotteiden tunnistaminen ja määrittäminen on tärkeää vaahdotusprosessin paremman ymmärtämisen kannalta. Työn kirjallisuusosassa vaahdotusprosessi, ksantaatit ja niiden yleisimmät hajoamistuotteet on esitelty, kuten myös käytetty analyysimenetelmä, kapillaarielektroforeesi. Työn kokeellisessa osassa etsittiin sopivaa erotusmenetelmää etyyliksantaatin, etyylitiokarbonaatin, etyyliperksantaatin ja etyyliksantyylitiosulfaatin erottamiseksi kapillaarilelektroforeesilla. Pääasiassa keskityttiin kahteen eri erotusmenetelmään. Ensimmäinen menetelmä kykeni erottamaan kaikki tutkitut tuotteet puhdasvesinäytteissä, ja toinen menetelmä oli sopiva näiden tuotteiden erottamiseen prosessivesinäytteissä. Jälkimmäistä menetelmää kokeiltiin käytännössä rikastamolla, jossa sillä kyettiin erottamaan isobutyyliksantaatti, isobutyylitiokarbonaatti, ja suurella todennäköisyydellä myös isobutyyliperksantaatti.
Resumo:
Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.
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Green sugarcane harvesting may promote great changes in the dynamics of herbicides in the environment. Our goal was to evaluate the influence of straw decomposition degree on leaching and weed (Ipomoea grandifolia) control efficacy by (14C) tebuthiuron and hexazinone. The presence of straw on the soil surface affected leaching, mainly for hexazinone (leaching reduced from 37 to 5% of the applied amount in the presence of straw). Overall, tebuthiuron showed more efficient control of Ipomoea than hexazinone. The straw decomposition degree affected only hexazinone efficacy that was lowest for the least decomposed straw. Further studies are needed to evaluate the effects of sugarcane straw on herbicides dissipation, particularly on volatilization and photolysis, to better predict their efficacy and environmental fate.
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Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.
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Gasification of biomass is an efficient method process to produce liquid fuels, heat and electricity. It is interesting especially for the Nordic countries, where raw material for the processes is readily available. The thermal reactions of light hydrocarbons are a major challenge for industrial applications. At elevated temperatures, light hydrocarbons react spontaneously to form higher molecular weight compounds. In this thesis, this phenomenon was studied by literature survey, experimental work and modeling effort. The literature survey revealed that the change in tar composition is likely caused by the kinetic entropy. The role of the surface material is deemed to be an important factor in the reactivity of the system. The experimental results were in accordance with previous publications on the subject. The novelty of the experimental work lies in the used time interval for measurements combined with an industrially relevant temperature interval. The aspects which are covered in the modeling include screening of possible numerical approaches, testing of optimization methods and kinetic modelling. No significant numerical issues were observed, so the used calculation routines are adequate for the task. Evolutionary algorithms gave a better performance combined with better fit than the conventional iterative methods such as Simplex and Levenberg-Marquardt methods. Three models were fitted on experimental data. The LLNL model was used as a reference model to which two other models were compared. A compact model which included all the observed species was developed. The parameter estimation performed on that model gave slightly impaired fit to experimental data than LLNL model, but the difference was barely significant. The third tested model concentrated on the decomposition of hydrocarbons and included a theoretical description of the formation of carbon layer on the reactor walls. The fit to experimental data was extremely good. Based on the simulation results and literature findings, it is likely that the surface coverage of carbonaceous deposits is a major factor in thermal reactions.
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This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.