Caracterização do reservatório Marlim por inversão acústica

Exploracionistas tem grande interesse em sistemas turbidíticos, pois em geral estes compõem prolíficos plays exploratórios. No entanto, estes potenciais reservatórios se encontram muitas vezes perto ou abaixo de resolução sísmica. Dessa forma, no processo de inversão, é importante integrar os dados sísmicos com qualidade de resolução obtida a partir do seu pré-condicionamento, para que o resultado final possua características detalhadas das camadas. O pré-condicionamento possibilita melhora na resolução dos dados sísmicos, através da atenuação dos ruídos aleatórios. Como objetivo final, foi realizada a inversão acústica em dados sísmicos post stack, migrados em tempo, a um sistema de turbiditos na Bacia de Campos. O principal objetivo da inversão sísmica é transformar o dado de reflexão em propriedades petrofísicas quantitativas. A inversão para impedância acústica é comumente utilizada para predição de porosidade. O fluxo de trabalho proposto foi dividido em cinco estágios principais: pré-condicionamento sísmico do dado 3D, correlação poço-sísmica, construção do modelo de baixa frequência, inversão do dado, e estimativa da porosidade. Os resultados mostraram que o cubo de impedância acústica invertido possui resolução muito superior quando comparado com o dado em amplitude sísmica, possibilitando melhor visualização das feições geológicas do Campo de Marlim. Além de suas limitações, como desconsiderando os efeitos das variações de fluido e variações litológicas complexas sobre a relação porosidade/impedância, o método fornece uma ferramenta confiável para exploração sísmica. Detalhes mais precisos das propriedades petrofísicas podem ser obtidos através de métodos de inversão mais sofisticados, a partir de dados pre stack.

Environmental and social impact monitoring of the Bujagali Hydropower Project (BHPP), Uganda Fisheries Component: monthly patterns in physico-chemical conditions and fish catch in the immediate vicinity of the Bujagali Hydropower construction site, 29th September - 28th October 2007

Following the commencement of construction works of a 250 MW hydropower plant at Dumbbell Island in the Upper Victoria Nile in September 2007, BEL requested NaFIRRI to conduct continuous monitoring of fish catches at two transects i.e. the immediate upstream transect of the project site (Kalange-Makwanzi) and the immediate downstream .transect (Buyala-Kikubamutwe). The routine monitoring surveys were designed to be conducted twice a week at each of the tWo transects. It was anticipated that major immediate impacts were to occur during construction, and these needed to be known by BEL as part of a mitigation strategy. For example, the construction of it cofferdam could be accompanied by rapid changes in water quality and quantity downstream of the construction. These changes in turn could affect the fish catch and would probably be missed by the quarterly monitoring already in place. Therefore, a major cbjective of the more regular and rapid monitoring was to discern immediate impacts of construction activities by focusing on selected water quality parameters (total suspended solids, water conductivity, temperature, dissolved oxygen and pH) and fish catch characteristics (total catch, catch rates and value of the catch)

Decision tree-based context clustering based on cross validation and hierarchical priors

The standard, ad-hoc stopping criteria used in decision tree-based context clustering are known to be sub-optimal and require parameters to be tuned. This paper proposes a new approach for decision tree-based context clustering based on cross validation and hierarchical priors. Combination of cross validation and hierarchical priors within decision tree-based context clustering offers better model selection and more robust parameter estimation than conventional approaches, with no tuning parameters. Experimental results on HMM-based speech synthesis show that the proposed approach achieved significant improvements in naturalness of synthesized speech over the conventional approaches. © 2011 IEEE.

The topological configuration and conformational analysis of mRNA in translation

The theoretical model construction of mRNA hairpin structure and single-stranded structure as well as the simulation studies on RNA structure determined by the X-ray crystal diffraction and nuclear magnetic resonance revealed that in translation, after mRNA being unfolded into single-stranded structure, its topological configuration was closely correlative with the original hairpin structure. The conformational features of single-stranded mRNA appeared as helical regions alternating with curly regions to different extents, which might exert the influence on the folding of nascent polypeptide by various regulating effects including different translational rates.

Shape Recognition of Linear Construction Entities from Construction Site Images

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of Image Processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based shape recognition model is presented. This model was devised to enhance the recognition capabilities of our existing material based image retrieval model. The shape recognition model is based on clustering techniques, and specifically those related with material and object segmentation. The model detects the borders of each previously detected material depicted in the image, examines its linearity (length/width ratio) and detects its orientation (horizontal/vertical). The results emonstrate the suitability of this model for construction site image retrieval purposes and reveal the capability of existing clustering technologies to accurately identify the shape of a wealth of materials from construction site images.

Bayesian non-parametrics and the probabilistic approach to modelling.

Modelling is fundamental to many fields of science and engineering. A model can be thought of as a representation of possible data one could predict from a system. The probabilistic approach to modelling uses probability theory to express all aspects of uncertainty in the model. The probabilistic approach is synonymous with Bayesian modelling, which simply uses the rules of probability theory in order to make predictions, compare alternative models, and learn model parameters and structure from data. This simple and elegant framework is most powerful when coupled with flexible probabilistic models. Flexibility is achieved through the use of Bayesian non-parametrics. This article provides an overview of probabilistic modelling and an accessible survey of some of the main tools in Bayesian non-parametrics. The survey covers the use of Bayesian non-parametrics for modelling unknown functions, density estimation, clustering, time-series modelling, and representing sparsity, hierarchies, and covariance structure. More specifically, it gives brief non-technical overviews of Gaussian processes, Dirichlet processes, infinite hidden Markov models, Indian buffet processes, Kingman's coalescent, Dirichlet diffusion trees and Wishart processes.

Characterization of vertical Mo/diamond Schottky barrier diode from non-ideal I-V and C-V measurements based on MIS model

In this study, we investigated non-ideal characteristics of a diamond Schottky barrier diode with Molybdenum (Mo) Schottky metal fabricated by Microwave Plasma Chemical Vapour Deposition (MPCVD) technique. Extraction from forward bias I-V and reverse bias C- 2-V measurements yields ideality factor of 1.3, Schottky barrier height of 1.872 eV, and on-resistance of 32.63 mö·cm2. The deviation of extracted Schottky barrier height from an ideal value of 2.24 eV (considering Mo workfunction of 4.53 eV) indicates Fermi level pinning at the interface. We attributed such non-ideal behavior to the existence of thin interfacial layer and interface states between metal and diamond which forms Metal-Interfacial layer-Semiconductor (MIS) structure. Oxygen surface treatment during fabrication process might have induced them. From forward bias C-V characteristics, the minimum thickness of the interfacial layer is approximately 0.248 nm. Energy distribution profile of the interface state density is then evaluated from the forward bias I-V characteristics based on the MIS model. The interface state density is found to be uniformly distributed with values around 1013 eV - 1·cm- 2. © 2013 Elsevier B.V.

Model-based influences on humans' choices and striatal prediction errors.

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.

Interaction between heavy vehicles and roads

This paper discusses road damage caused by heavy commercial vehicles. Chapter 1 presents some important terminology and a brief historical review of road construction and vehicle-road interaction, from ancient times to the present day. The main types of vehicle-generated road damage, and the methods that are used by pavement engineers to analyze them are discussed in Chapter 2. Attention is also given to the main features of the response of road surfaces to vehicle loads and mathematical models that have been developed to predict road response. Chapter 3 reviews the effects on road damage of vehicle features which can be studied without consideration of vehicle dynamics. These include gross vehicle weight, axle and tire configurations, tire contact conditions and static load sharing in axle group suspensions. The dynamic tire forces generated by heavy vehicles are examined in Chapter 4. The discussion includes their simulation and measurement, their principal characteristics, the effects of tires and suspension design on dynamic forces, and the potential benefits of using advanced suspensions for minimizing dynamic tire forces. Chapter 5 discusses methods for estimating the effects of dynamic tire forces on road damage. The two main approaches are either to examine the statistics of the forces themselves; or to calculate the response of a pavement model to the forces, and to calculate the resulting wear using a material damage model. The issues involved in assessing vehicles for 'road friendliness' are discussed in Chapter 6. Possible assessment methods include measuring strains in an instrumented pavement traversed by the vehicle, measuring dynamic tire forces, or measuring vehicle parameters such as the 'natural frequency' and 'damping ratio'. Each of these measurements involves different assumptions and analysis methods for converting the results into some measure of road damage. Chapter 7 includes a summary of the main conclusions of the paper and recommendations for tire and suspension design, road design and construction, and for vehicle regulations.

Behaviour of cast-iron tunnel segmental joint from the 3D FE analyses and development of a new bolt-spring model

The behaviour of cast-iron tunnel segments used in London Underground tunnels was investigated using the 3-D finite element (FE) method. A numerical model of the structural details of cast-iron segmental joints such as bolts, panel and flanges was developed and its performance was validated against a set of full-scale tests. Using the verified model, the influence of structural features such as caulking groove and bolt pretension was examined for both rotational and shear loading conditions. Since such detailed modelling of bolts increases the computational time when a full scale segmental tunnel is analysed, it is proposed to replace the bolt model to a set of spring models. The parameters for the bolt-spring models, which consider the geometry and material properties of the bolt, are proposed. The performance of the combined bolt-spring and solid segmental models are evaluated against a more conventional shell-spring model. © 2014 Elsevier Ltd.

Bead-probe complex capture a couple of SINE and LINE family from genomes of two closely related species of East Asian cyprinid directly using magnetic separation

Background: Short and long interspersed elements (SINEs and LINEs, respectively), two types of retroposons, are active in shaping the architecture of genomes and powerful tools for studies of phylogeny and population biology. Here we developed special protocol to apply biotin-streptavidin bead system into isolation of interspersed repeated sequences rapidly and efficiently, in which SINEs and LINEs were captured directly from digested genomic DNA by hybridization to bead-probe complex in solution instead of traditional strategy including genomic library construction and screening. Results: A new couple of SINEs and LINEs that shared an almost identical 3'tail was isolated and characterized in silver carp and bighead carp of two closely related species. These SINEs (34 members), designated HAmo SINE family, were little divergent in sequence and flanked by obvious TSD indicated that HAmo SINE was very young family. The copy numbers of this family was estimated to 2 x 10(5) and 1.7 x 10(5) per haploid genome by Real-Time qPCR, respectively. The LINEs, identified as the homologs of LINE2 in other fishes, had a conserved primary sequence and secondary structures of the 3'tail region that was almost identical to that of HAmo SINE. These evidences suggest that HAmo SINEs are active and amplified recently utilizing the enzymatic machinery for retroposition of HAmoL2 through the recognition of higher-order structures of the conserved 42-tail region. We analyzed the possible structures of HAmo SINE that lead to successful amplification in genome and then deduced that HAmo SINE, SmaI SINE and FokI SINE that were similar in sequence each other, were probably generated independently and created by LINE family within the same lineage of a LINE phylogeny in the genomes of different hosts. Conclusion: The presented results show the advantage of the novel method for retroposons isolation and a pair of young SINE family and its partner LINE family in two carp fishes, which strengthened the hypotheses containing the slippage model for initiation of reverse transcription, retropositional parasitism of SINEs on LINEs, the formation of the stem loop structure in 3'tail region of some SINEs and LINEs and the mechanism of template switching in generating new SINE family.

Calibrating the Gaussian multi-target tracking model

We present novel batch and online (sequential) versions of the expectation-maximisation (EM) algorithm for inferring the static parameters of a multiple target tracking (MTT) model. Online EM is of particular interest as it is a more practical method for long data sets since in batch EM, or a full Bayesian approach, a complete browse of the data is required between successive parameter updates. Online EM is also suited to MTT applications that demand real-time processing of the data. Performance is assessed in numerical examples using simulated data for various scenarios. For batch estimation our method significantly outperforms an existing gradient based maximum likelihood technique, which we show to be significantly biased. © 2014 Springer Science+Business Media New York.

Novel fluid grid and voidage calculation techniques for a discrete element model of a 3D cylindrical fluidized bed

A discrete element model (DEM) combined with computational fluid dynamics (CFD) was developed to model particle and fluid behaviour in 3D cylindrical fluidized beds. Novel techniques were developed to (1) keep fluid cells, defined in cylindrical coordinates, at a constant volume in order to ensure the conditions for validity of the volume-averaged fluid equations were satisfied and (2) smoothly and accurately measure voidage in arbitrarily shaped fluid cells. The new technique for calculating voidage was more stable than traditional techniques, also examined in the paper, whilst remaining computationally-effective. The model was validated by quantitative comparison with experimental results from the magnetic resonance imaging of a fluidised bed analysed to give time-averaged particle velocities. Comparisons were also made between theoretical determinations of slug rise velocity in a tall bed. It was concluded that the DEM-CFD model is able to investigate aspects of the underlying physics of fluidisation not readily investigated by experiment. © 2014 The Authors.

Classical two-site fidelity and quantum phase transitions in the Ising model and the extended Hubbard model

In this Letter, the classical two-site-ground-state fidelity (CTGF) is exploited to identify quantum phase transitions (QPTs) for the transverse field Ising model (TFIM) and the one-dimensional extended Hubbard model (EHM). Our results show that the CTGF exhibits an abrupt change around the regions of criticality and can be used to identify QPTs in spin and fermionic systems. The method is especially convenient when it is connected with the density-matrix renormalization group (DMRG) algorithm. (C) 2008 Elsevier B.V. All rights reserved.

automatic construction of finite algebras

This paper deals withmodel generation for equational theories, i.e., automatically generating (finite) models of a given set of (logical) equations. Our method of finite model generation and a tool for automatic construction of finite algebras is described. Some examples are given to show the applications of our program. We argue that, the combination of model generators and theorem provers enables us to get a better understanding of logical theories. A brief comparison between our tool and other similar tools is also presented.