914 resultados para Application of Data-driven Modelling in Water Sciences


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Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

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PI kinematic trajectory model is used to investigate potential pathways of dust transport from Australia to New Zealand. Historically, these have been assumed to follow rather direct west-east trajectories spanning 2 to 3 days, often resulting in red snow events in the Southern Alps of New Zealand. However, results from the present study which examined the route taken by air parcels originating in southern Australia during dust storms on 24 and 25 May 1994, indicate that trans-Tasman dust transport trajectories are more diverse than previously thought, and display considerable variation during single events. These mon divergent pathways tie in more closely with aeolian dust sedimentation patterns identified by ocean coring in the Tasman Sea, and may account for the deposition of Australian dust on sub-Antarctic islands located well south of the Australian continent. Copyright 2000 John Wiley Sons, Ltd.

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Rockburst is characterized by a violent explosion of a block causing a sudden rupture in the rock and is quite common in deep tunnels. It is critical to understand the phenomenon of rockburst, focusing on the patterns of occurrence so these events can be avoided and/or managed saving costs and possibly lives. The failure mechanism of rockburst needs to be better understood. Laboratory experiments are undergoing at the Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUE) of Beijing and the system is described. A large number of rockburst tests were performed and their information collected, stored in a database and analyzed. Data Mining (DM) techniques were applied to the database in order to develop predictive models for the rockburst maximum stress (σRB) and rockburst risk index (IRB) that need the results of such tests to be determined. With the developed models it is possible to predict these parameters with high accuracy levels using data from the rock mass and specific project.

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The widespread implementation of GIS-based 3D topographical models has been a great aid in the development and testing of archaeological hypotheses. In this paper, a topographical reconstruction of the ancient city of Tarraco, the Roman capital of the Tarraconensis province, is presented. This model is based on topographical data obtained through archaeological excavations, old photographic documentation, georeferenced archive maps depicting the pre-modern city topography, modern detailed topographical maps and differential GPS measurements. The addition of the Roman urban architectural features to the model offers the possibility to test hypotheses concerning the ideological background manifested in the city shape. This is accomplished mainly through the use of 3D views from the main city accesses. These techniques ultimately demonstrate the ‘theatre-shaped’ layout of the city (to quote Vitrubius) as well as its southwest oriented architecture, whose monumental character was conceived to present a striking aspect to visitors, particularly those arriving from the sea.

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The purpose of the research is to define practical profit which can be achieved using neural network methods as a prediction instrument. The thesis investigates the ability of neural networks to forecast future events. This capability is checked on the example of price prediction during intraday trading on stock market. The executed experiments show predictions of average 1, 2, 5 and 10 minutes’ prices based on data of one day and made by two different types of forecasting systems. These systems are based on the recurrent neural networks and back propagation neural nets. The precision of the predictions is controlled by the absolute error and the error of market direction. The economical effectiveness is estimated by a special trading system. In conclusion, the best structures of neural nets are tested with data of 31 days’ interval. The best results of the average percent of profit from one transaction (buying + selling) are 0.06668654, 0.188299453, 0.349854787 and 0.453178626, they were achieved for prediction periods 1, 2, 5 and 10 minutes. The investigation can be interesting for the investors who have access to a fast information channel with a possibility of every-minute data refreshment.

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The epiphytic macroinvertebrate communities associated with the Common Reed, Phragmites australis (Cav.) Trin. ex Steudel, were examined seasonally from summer 2004 to spring 2005 in eleven coastal lagoons of the Llobregat Delta (NE Spain) following the method proposed by Kornijów & Kairesalo (1994). The aims of the study were to: 1) characterise and quantify changes in epiphytic macroinvertebrate communities along environmental gradients; 2) assess the contribution of elements of the epiphytic compartment to structuring the community; 3) define the optima and tolerances of selected epiphytic macroinvertebrate taxa for the most relevant ecological factors responsible for assemblage composition; and 4) identify possible epiphytic species assemblages that would allow a lagoon"s typology to be established, as well as their representative indicator species. Communities showed statistically significant seasonal variation, with two faunal peaks: one in summer, with high chironomid densities, and the other in winter, with high naidid densities. These peaks showed a clear response to the influence of environmental factors. Salinity explained the highest percentage of total variance (36%), while trophic variables (nutrients, phytoplanktonic chlorophyll-a, and total organic carbon) and epiphyton biomass (19.2 and 4% of total variance explained, respectively) were secondary. Three different epiphytic macroinvertebrate species assemblages could be defined. These assemblages were directly linked to conductivity conditions, which determined the rate of survival of certain taxa, and to the existence of a direct connection with the sea, which permitted the establishment of 'brackish-water' species. In spite of the existence of these species assemblages, the species composition and biomass of epiphytic macroinvertebrates and epiphyton differed substantially between lagoons; both elements were subject to changes in the environment, which finally determined the site-to-site variation in the density and composition of the macroinvertebrate population

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The Differential Scanning Calorimetry (DSC) was used to study the thermal behavior of hair samples and to verify the possibility of identifying an individual based on DSC curves from a data bank. Hair samples of students and officials from Instituto de Química de Araraquara, UNESP were obtained to build up a data bank. Thus to sought an individual, under incognito participant of this data bank, was identified using DSC curves.

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Scarcity of long-term series of sediment-related variables has led watershed managers to apply mathematical models to simulate sediment fluxes. Due to the high efforts for installation and maintenance of sedimentological gauges, tracers have been pointed out as an alternative to validate soil redistribution modelling. In this study, the 137Cs technique was used to assess the WASA-SED model performance at the Benguê watershed (933 km²), in the Brazilian semiarid. Qualitatively, good agreement was found among the 137Cs technique and the WASA-SED model results. Nonetheless, quantitatively great differences, up to two orders of magnitude, were found between the two methods. Among the uncertainties inherent to the 137Cs technique, definition of the reference inventory seems to be a major source of imprecision. In addition, estimations of water and sediment fluxes with mathematical models usually also present high uncertainty, contributing to the quantitative differences of the soil redistribution estimates with the two methods.

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The objective of this study was to evaluate the viability of using microwave-roasted rice bran as an ingredient in high-fiber cereal bars to obtain a product with good acceptability. The influence of the rice flakes, corn flakes, and roasted rice bran levels on the physical and chemical characteristics of the cereal bars was studied. The overall acceptability of three selected formulations was also evaluated. An increase in the roasted rice bran level in the formulation reduced the force of rupture and water activity, resulted in intermediate density, and caused darkening of the bars. The contents of lipid and total dietary fiber were higher in the formulation with the highest rice bran content, which was therefore classified as functional food. The formulation containing 0.34; 0.32; and 0.34 roasted rice bran, rice flakes, and corn flakes, respectively, seemed to be the best outcome. Cereal bars with roasted rice bran levels between 10 and 20% were accepted by consumers.

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Solubilities of 4-nitrobenzoic acid at 25°, 35° and 42°C have been determined in water and in the presence of several concentrations of electrolytes. The free energies, enthalpies and entropies of transfer are also reported. The data have been rationalized by considering the structure-breaking effects of the ions of the salts and the requirement of the localized hydrolysis model. The theory of Symons is not satisfactory to rationalise the experimental data.

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Second language acquisition researchers often face particular challenges when attempting to generalize study findings to the wider learner population. For example, language learners constitute a heterogeneous group, and it is not always clear how a study’s findings may generalize to other individuals who may differ in terms of language background and proficiency, among many other factors. In this paper, we provide an overview of how mixed-effects models can be used to help overcome these and other issues in the field of second language acquisition. We provide an overview of the benefits of mixed-effects models and a practical example of how mixed-effects analyses can be conducted. Mixed-effects models provide second language researchers with a powerful statistical tool in the analysis of a variety of different types of data.

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There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.