Measuring the spatial extent of texture pooling using reverse correlation

The local image representation produced by early stages of visual analysis is uninformative regarding spatially extensive textures and surfaces. We know little about the cortical algorithm used to combine local information over space, and still less about the area over which it can operate. But such operations are vital to support perception of real-world objects and scenes. Here, we deploy a novel reverse-correlation technique to measure the extent of spatial pooling for target regions of different areas placed either in the central visual field, or more peripherally. Stimuli were large arrays of micropatterns, with their contrasts perturbed individually on an interval-by-interval basis. By comparing trial-by-trial observer responses with the predictions of computational models, we show that substantial regions (up to 13 carrier cycles) of a stimulus can be monitored in parallel by summing contrast over area. This summing strategy is very different from the more widely assumed signal selection strategy (a MAX operation), and suggests that neural mechanisms representing extensive visual textures can be recruited by attention. We also demonstrate that template resolution is much less precise in the parafovea than in the fovea, consistent with recent accounts of crowding. © 2014 The Authors.

New horizons in mouse immunoinformatics:reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity

Quantitative structure–activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide–protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2–Db, H2–Kb and H2–Kk. As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online (http://www.jenner.ac.uk/MHCPred).

Adaptation of a Task-oriented Training Environment to its Users

The problem of adapting teaching systems to the teacher has not been extensively covered in the specialised literature. The authors present the server-client architecture of a Task-Oriented Environment for Design of Virtual Labs (TOEDVL). The paper focuses on the computational models supporting its base of tasks (BT) and on two groups of behavioural tutor’s models for planning training sessions. Detailed examples are presented.

Fast Linear Algorithm for Active Rules Application in Transition P Systems

Transition P systems are computational models based on basic features of biological membranes and the observation of biochemical processes. In these models, membrane contains objects multisets, which evolve according to given evolution rules. In the field of Transition P systems implementation, it has been detected the necessity to determine whichever time are going to take active evolution rules application in membranes. In addition, to have time estimations of rules application makes possible to take important decisions related to the hardware / software architectures design. In this paper we propose a new evolution rules application algorithm oriented towards the implementation of Transition P systems. The developed algorithm is sequential and, it has a linear order complexity in the number of evolution rules. Moreover, it obtains the smaller execution times, compared with the preceding algorithms. Therefore the algorithm is very appropriate for the implementation of Transition P systems in sequential devices.

Analysis of P-Systems under a Multiagent Systems Perspective

Membrane computing is a recent area that belongs to natural computing. This field works on computational models based on nature's behavior to process the information. Recently, numerous models have been developed and implemented with this purpose. P-systems are the structures which have been defined, developed and implemented to simulate the behavior and the evolution of membrane systems which we find in nature. What we show in this paper is an application capable to simulate the P-systems based on a multiagent systems (MAS) technology. The main goal we want to achieve is to take advantage of the inner qualities of the multiagent systems. This way we can analyse the proper functioning of any given p-system. When we observe a P-system from a different perspective, we can be assured that it is a particular case of the multiagent systems. This opens a new possibility, in the future, to always evaluate the P-systems in terms of the multiagent systems technology.

Lattice Boltzmann modeling of fluid flow and solute transport in karst aquifers

A novel modeling approach is applied to karst hydrology. Long-standing problems in karst hydrology and solute transport are addressed using Lattice Boltzmann methods (LBMs). These methods contrast with other modeling approaches that have been applied to karst hydrology. The motivation of this dissertation is to develop new computational models for solving ground water hydraulics and transport problems in karst aquifers, which are widespread around the globe. This research tests the viability of the LBM as a robust alternative numerical technique for solving large-scale hydrological problems. The LB models applied in this research are briefly reviewed and there is a discussion of implementation issues. The dissertation focuses on testing the LB models. The LBM is tested for two different types of inlet boundary conditions for solute transport in finite and effectively semi-infinite domains. The LBM solutions are verified against analytical solutions. Zero-diffusion transport and Taylor dispersion in slits are also simulated and compared against analytical solutions. These results demonstrate the LBM’s flexibility as a solute transport solver. The LBM is applied to simulate solute transport and fluid flow in porous media traversed by larger conduits. A LBM-based macroscopic flow solver (Darcy’s law-based) is linked with an anisotropic dispersion solver. Spatial breakthrough curves in one and two dimensions are fitted against the available analytical solutions. This provides a steady flow model with capabilities routinely found in ground water flow and transport models (e.g., the combination of MODFLOW and MT3D). However the new LBM-based model retains the ability to solve inertial flows that are characteristic of karst aquifer conduits. Transient flows in a confined aquifer are solved using two different LBM approaches. The analogy between Fick’s second law (diffusion equation) and the transient ground water flow equation is used to solve the transient head distribution. An altered-velocity flow solver with source/sink term is applied to simulate a drawdown curve. Hydraulic parameters like transmissivity and storage coefficient are linked with LB parameters. These capabilities complete the LBM’s effective treatment of the types of processes that are simulated by standard ground water models. The LB model is verified against field data for drawdown in a confined aquifer.

Lattice Boltzmann Modeling of Fluid Flow and Solute Transport in Karst Aquifers

A novel modeling approach is applied to karst hydrology. Long-standing problems in karst hydrology and solute transport are addressed using Lattice Boltzmann methods (LBMs). These methods contrast with other modeling approaches that have been applied to karst hydrology. The motivation of this dissertation is to develop new computational models for solving ground water hydraulics and transport problems in karst aquifers, which are widespread around the globe. This research tests the viability of the LBM as a robust alternative numerical technique for solving large-scale hydrological problems. The LB models applied in this research are briefly reviewed and there is a discussion of implementation issues. The dissertation focuses on testing the LB models. The LBM is tested for two different types of inlet boundary conditions for solute transport in finite and effectively semi-infinite domains. The LBM solutions are verified against analytical solutions. Zero-diffusion transport and Taylor dispersion in slits are also simulated and compared against analytical solutions. These results demonstrate the LBM’s flexibility as a solute transport solver. The LBM is applied to simulate solute transport and fluid flow in porous media traversed by larger conduits. A LBM-based macroscopic flow solver (Darcy’s law-based) is linked with an anisotropic dispersion solver. Spatial breakthrough curves in one and two dimensions are fitted against the available analytical solutions. This provides a steady flow model with capabilities routinely found in ground water flow and transport models (e.g., the combination of MODFLOW and MT3D). However the new LBM-based model retains the ability to solve inertial flows that are characteristic of karst aquifer conduits. Transient flows in a confined aquifer are solved using two different LBM approaches. The analogy between Fick’s second law (diffusion equation) and the transient ground water flow equation is used to solve the transient head distribution. An altered-velocity flow solver with source/sink term is applied to simulate a drawdown curve. Hydraulic parameters like transmissivity and storage coefficient are linked with LB parameters. These capabilities complete the LBM’s effective treatment of the types of processes that are simulated by standard ground water models. The LB model is verified against field data for drawdown in a confined aquifer.

Influence of Outlet Boundary Conditions on Cerebrovascular Aneurysm Hemodynamics

Computational fluid dynamic (CFD) studies of blood flow in cerebrovascular aneurysms have potential to improve patient treatment planning by enabling clinicians and engineers to model patient-specific geometries and compute predictors and risks prior to neurovascular intervention. However, the use of patient-specific computational models in clinical settings is unfeasible due to their complexity, computationally intensive and time-consuming nature. An important factor contributing to this challenge is the choice of outlet boundary conditions, which often involves a trade-off between physiological accuracy, patient-specificity, simplicity and speed. In this study, we analyze how resistance and impedance outlet boundary conditions affect blood flow velocities, wall shear stresses and pressure distributions in a patient-specific model of a cerebrovascular aneurysm. We also use geometrical manipulation techniques to obtain a model of the patient’s vasculature prior to aneurysm development, and study how forces and stresses may have been involved in the initiation of aneurysm growth. Our CFD results show that the nature of the prescribed outlet boundary conditions is not as important as the relative distributions of blood flow through each outlet branch. As long as the appropriate parameters are chosen to keep these flow distributions consistent with physiology, resistance boundary conditions, which are simpler, easier to use and more practical than their impedance counterparts, are sufficient to study aneurysm pathophysiology, since they predict very similar wall shear stresses, time-averaged wall shear stresses, time-averaged pressures, and blood flow patterns and velocities. The only situations where the use of impedance boundary conditions should be prioritized is if pressure waveforms are being analyzed, or if local pressure distributions are being evaluated at specific time points, especially at peak systole, where the use of resistance boundary conditions leads to unnaturally large pressure pulses. In addition, we show that in this specific patient, the region of the blood vessel where the neck of the aneurysm developed was subject to abnormally high wall shear stresses, and that regions surrounding blebs on the aneurysmal surface were subject to low, oscillatory wall shear stresses. Computational models using resistance outlet boundary conditions may be suitable to study patient-specific aneurysm progression in a clinical setting, although several other challenges must be addressed before these tools can be applied clinically.

Multilingualism and conceptual modelling

One of the leading motivations behind the multilingual semantic web is to make resources accessible digitally in an online global multilingual context. Consequently, it is fundamental for knowledge bases to find a way to manage multilingualism and thus be equipped with those procedures for its conceptual modelling. In this context, the goal of this paper is to discuss how common-sense knowledge and cultural knowledge are modelled in a multilingual framework. More particularly, multilingualism and conceptual modelling are dealt with from the perspective of FunGramKB, a lexico-conceptual knowledge base for natural language understanding. This project argues for a clear division between the lexical and the conceptual dimensions of knowledge. Moreover, the conceptual layer is organized into three modules, which result from a strong commitment towards capturing semantic knowledge (Ontology), procedural knowledge (Cognicon) and episodic knowledge (Onomasticon). Cultural mismatches are discussed and formally represented at the three conceptual levels of FunGramKB.

Document Cohesion Flow: Striving towards Coherence

Text cohesion is an important element of discourse processing. This paper presents a new approach to modeling, quantifying, and visualizing text cohesion using automated cohesion flow indices that capture semantic links among paragraphs. Cohesion flow is calculated by applying Cohesion Network Analysis, a combination of semantic distances, Latent Semantic Analysis, and Latent Dirichlet Allocation, as well as Social Network Analysis. Experiments performed on 315 timed essays indicated that cohesion flow indices are significantly correlated with human ratings of text coherence and essay quality. Visualizations of the global cohesion indices are also included to support a more facile understanding of how cohesion flow impacts coherence in terms of semantic dependencies between paragraphs.

The Performance Characteristics of a Surface-Modified Cutting Tool

In the past, many papers have been presented which show that the coating of cutting tools often yields decreased wear rates and reduced coefficients of friction. Although different theories are proposed, covering areas such as hardness theory, diffusion barrier theory, thermal barrier theory, and reduced friction theory, most have not dealt with the question of how and why the coating of tool substrates with hard materials such as Titanium Nitride (TiN), Titanium Carbide (TiC) and Aluminium Oxide (Al203) transforms the performance and life of cutting tools. This project discusses the complex interrelationship that encompasses the thermal barrier function and the relatively low sliding friction coefficient of TiN on an undulating tool surface, and presents the result of an investigation into the cutting characteristics and performance of EDMed surface-modified carbide cutting tool inserts. The tool inserts were coated with TiN by the physical vapour deposition (PVD) method. PVD coating is also known as Ion-plating which is the general term of the coating method in which the film is created by attracting ionized metal vapour in this the metal was Titanium and ionized gas onto negatively biased substrate surface. Coating by PVD was chosen because it is done at a temperature of not more than 5000C whereas chemical Vapour Deposition CVD process is done at very high temperature of about 8500C and in two stages of heating up the substrates. The high temperatures involved in CVD affects the strength of the (tool) substrates. In this study, comparative cutting tests using TiN-coated control specimens with no EDM surface structures and TiN-coated EDMed tools with a crater-like surface topography were carried out on mild steel grade EN-3. Various cutting speeds were investigated, up to an increase of 40% of the tool manufacturer’s recommended speed. Fifteen minutes of cutting were carried out for each insert at the speeds investigated. Conventional tool inserts normally have a tool life of approximately 15 minutes of cutting. After every five cuts (passes) microscopic pictures of the tool wear profiles were taken, in order to monitor the progressive wear on the rake face and on the flank of the insert. The power load was monitored for each cut taken using an on-board meter on the CNC machine to establish the amount of power needed for each stage of operation. The spindle drive for the machine is an 11 KW/hr motor. Results obtained confirmed the advantages of cutting at all speeds investigated using EDMed coated inserts, in terms of reduced tool wear and low power loads. Moreover, the surface finish on the workpiece was consistently better for the EDMed inserts. The thesis discusses the relevance of the finite element method in the analysis of metal cutting processes, so that metal machinists can design, manufacture and deliver goods (tools) to the market quickly and on time without going through the hassle of trial and error approach for new products. Improvements in manufacturing technologies require better knowledge of modelling metal cutting processes. Technically the use of computational models has a great value in reducing or even eliminating the number of experiments traditionally used for tool design, process selection, machinability evaluation, and chip breakage investigations. In this work, much interest in theoretical and experimental investigations of metal machining were given special attention. Finite element analysis (FEA) was given priority in this study to predict tool wear and coating deformations during machining. Particular attention was devoted to the complicated mechanisms usually associated with metal cutting, such as interfacial friction; heat generated due to friction and severe strain in the cutting region, and high strain rates. It is therefore concluded that Roughened contact surface comprising of peaks and valleys coated with hard materials (TiN) provide wear-resisting properties as the coatings get entrapped in the valleys and help reduce friction at chip-tool interface. The contributions to knowledge: a. Relates to a wear-resisting surface structure for application in contact surfaces and structures in metal cutting and forming tools with ability to give wear-resisting surface profile. b. Provide technique for designing tool with roughened surface comprising of peaks and valleys covered in conformal coating with a material such as TiN, TiC etc which is wear-resisting structure with surface roughness profile compose of valleys which entrap residual coating material during wear thereby enabling the entrapped coating material to give improved wear resistance. c. Provide knowledge for increased tool life through wear resistance, hardness and chemical stability at high temperatures because of reduced friction at the tool-chip and work-tool interfaces due to tool coating, which leads to reduced heat generation at the cutting zones. d. Establishes that Undulating surface topographies on cutting tips tend to hold coating materials longer in the valleys, thus giving enhanced protection to the tool and the tool can cut faster by 40% and last 60% longer than conventional tools on the markets today.

Adsorption Calorimetry for Energy Conversion Technologies: Applications in Organic Photovoltaics, Catalysis, and Atomic Layer Deposition

Thesis (Ph.D.)--University of Washington, 2016-07

Ventilação e prescrições urbanísticas: uma aplicação simulada para a Orla da Praia do Meio em Natal/RN

This work analyses a study on natural ventilation and its relation to the urban legislation versus the building types in an urban fraction of coastal area of Praia do Meio in the city of Natal/RN, approaching the type or types of land use most appropriate to this limited urban fraction. The objective of this study is to analyse the effects of the present legislation as well as the types of buildings in this area on the natural ventilation. This urban fraction was selected because it is one of the sites from where the wind flows into the city of Natal. This research is based on the hypothesis stating that the reduction on the porosity of the urban soil (decrease in the set back/boundary clearance), and an increase in the form (height of the buildings) rise the level of the ventilation gradient, consequently causing a reduction on the wind speed at the lowest part of the buildings. Three-dimensional computational models were used to produce the modes of occupation allowed in the urban fraction within the area under study. A Computational Fluid Dynamics (CFD) software was also used to analyse the modes of land occupation. Following simulation, a statistical assessment was carried out for validation of the hypothesis. It was concluded that the reduction in the soil porosity as a consequence of the rates that defined the minimum boundary clearance between the building and the boundary of the plot (and consequently the set back), as well as the increase in the building form (height of the buildings) caused a reduction in the wind speed, thus creating heat islands

Mapeamento acústico como ferramenta para predição de ruído urbano na área de influência do estádio Arena das Dunas, Natal/ RN

The Noise Pollution causes degradation in the quality of the environment and presents itself as one of the most common environmental problems in the big cities. An Urban environment present scenario and their complex acoustic study need to consider the contribution of various noise sources. Accordingly to computational models through mapping and prediction of acoustic scene become important, because they enable the realization of calculations, analyzes and reports, allowing the interpretation of satisfactory results. The study neighborhood is the neighborhood of Lagoa Nova, a central area of the city of Natal, which will undergo major changes in urban space due to urban mobility projects planned for the area around the stadium and the consequent changes of urban form and traffic. Thus, this study aims to evaluate the noise impact caused by road and morphological changes around the stadium Arena das Dunas in the neighborhood of Lagoa Nova, through on-site measurements and mapping using the computational model SoundPLAN year 2012 and the scenario evolution acoustic for the year 2017. For this analysis was the construction of the first acoustic mapping based on current diagnostic acoustic neighborhood, physical mapping, classified vehicle count and measurement of sound pressure level, and to build the prediction of noise were observed for the area study the modifications provided for traffic, urban form and mobility work. In this study, it is concluded that the sound pressure levels of the year in 2012 and 2017 extrapolate current legislation. For the prediction of noise were numerous changes in the acoustic scene, in which the works of urban mobility provided will improve traffic flow, thus reduce the sound pressure level where interventions are expected

Calcium oscillations

Changes in cellular calcium concentration control a wide range of physiological processes, from the subsecond release of synaptic neurotransmitters, to the regulation of gene expression over months or years. Calcium can also trigger cell death through both apoptosis and necrosis, and so the regulation of cellular calcium concentration must be tightly controlled through the concerted action of pumps, channels and buffers that transport calcium into and out of the cell cytoplasm. A hallmark of cellular calcium signalling is its spatiotemporal complexity: stimulation of cells by a hormone or neurotransmitter leads to oscillations in cytoplasmic calcium concentration that can vary markedly in time course, amplitude, frequency, and spatial range. In this chapter we review some of the biological roles of calcium, the experimental characterisation of complex dynamic changes in calcium concentration, and attempts to explain this complexity using computational models. We consider the "toolkit" of cellular proteins which influence calcium concentration, describe mechanistic models of key elements of the toolkit, and fit these into the framework of whole cell models of calcium oscillations and waves. Finally, we will touch on recent efforts to use stochastic modelling to elucidate elementary calcium signal events, and how these may evolve into global signals.