996 resultados para including semiconductors


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Raman spectroscopy complimented with infrared spectroscopy has been used to study the rare earth based mineral decrespignyite (Y,REE)4Cu(CO3)4Cl(OH)5•2(H2O) and compared with the Raman spectra of a series of selected natural halogenated carbonates from different origins including bastnasite, parisite and northupite. The Raman spectrum of decrespignyite displays three bands are at 1056, 1070 and 1088 cm-1 attributed to the CO32- symmetric stretching vibration. The observation of three symmetric stretching vibrations is very unusual. The position of CO32- symmetric stretching vibration varies with mineral composition. Raman bands of decrespignyite show bands at 1391, 1414, 1489 and 1547 cm-1. Raman spectra of bastnasite, parisite and northupite show a single band at 1433, 1420 and 1554 cm-1 assigned to the ν3 (CO3)2- antisymmetric stretching mode. The observation of additional Raman bands for the ν3 modes for some halogenated carbonates is significant in that it shows distortion of the carbonate anion in the mineral structure. Four Raman bands are observed at 791, 815, 837 and 849 cm-1and assigned to the (CO3)2- ν2 bending modes. Raman bands are observed for decrespignyite at 694, 718 and 746 cm-1 and are assigned to the (CO3)2- ν4 bending modes. Raman bands are observed for the carbonate ν4 in phase bending modes at 722 cm-1 for bastnasite, 736 and 684 cm-1 for parisite, 714 cm-1 for northupite. Multiple bands are observed in the OH stretching region for decrespignyite, bastnasite and parisite indicating the presence of water and OH units in the mineral structure.

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This report is an update of an earlier one produced in January 2010 (see Carrington et al. 2010) which remains as an ePrint through the project’s home page. This report focuses on our examination of extant data which have been sourced with respect to unintentional serious and violent harm, including injuries, to males living in regional and remote Australia . and which were available in public data bases at production. Such harm typically might be caused by, for example, transport accidents, occupational exposures and hazards, burns and so on. Thus unintentional violent harm can cause physical trauma the consequences of which can lead to chronic conditions including psychological harm or substance abuse.

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The family Geminiviridae comprises a group of plant-infecting circular ssDNA viruses that severely constrain agricultural production throughout the temperate regions of the world, and are a particularly serious threat to food security in sub-Saharan Africa. While geminiviruses exhibit considerable diversity in terms of their nucleotide sequences, genome structures, host ranges and insect vectors, the best characterised and economically most important of these viruses are those in the genus Begomovirus. Whereas begomoviruses are generally considered to be either monopartite (one ssDNA component) or bipartite (two circular ssDNA components called DNA-A and DNA-B), many apparently monopartite begomoviruses are associated with additional subviral ssDNA satellite components, called alpha- (DNA-αs) or betasatellites (DNA-βs). Additionally, subgenomic molecules, also known as defective interfering (DIs) DNAs that are usually derived from the parent helper virus through deletions of parts of its genome, are also associated with bipartite and monopartite begomoviruses. The past three decades have witnessed the emergence and diversification of various new begomoviral species and associated DI DNAs, in southern Africa, East Africa, and proximal Indian Ocean islands, which today threaten important vegetable and commercial crops such as, tobacco, cassava, tomato, sweet potato, and beans. This review aims to describe what is known about these viruses and their impacts on sustainable production in this sensitive region of the world. © 2012 by the authors licensee MDPI, Basel, Switzerland.

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Articular cartilage is a complex structure with an architecture in which fluid-swollen proteoglycans constrained within a 3D network of collagen fibrils. Because of the complexity of the cartilage structure, the relationship between its mechanical behaviours at the macroscale level and its components at the micro-scale level are not completely understood. The research objective in this thesis is to create a new model of articular cartilage that can be used to simulate and obtain insight into the micro-macro-interaction and mechanisms underlying its mechanical responses during physiological function. The new model of articular cartilage has two characteristics, namely: i) not use fibre-reinforced composite material idealization ii) Provide a framework for that it does probing the micro mechanism of the fluid-solid interaction underlying the deformation of articular cartilage using simple rules of repartition instead of constitutive / physical laws and intuitive curve-fitting. Even though there are various microstructural and mechanical behaviours that can be studied, the scope of this thesis is limited to osmotic pressure formation and distribution and their influence on cartilage fluid diffusion and percolation, which in turn governs the deformation of the compression-loaded tissue. The study can be divided into two stages. In the first stage, the distributions and concentrations of proteoglycans, collagen and water were investigated using histological protocols. Based on this, the structure of cartilage was conceptualised as microscopic osmotic units that consist of these constituents that were distributed according to histological results. These units were repeated three-dimensionally to form the structural model of articular cartilage. In the second stage, cellular automata were incorporated into the resulting matrix (lattice) to simulate the osmotic pressure of the fluid and the movement of water within and out of the matrix; following the osmotic pressure gradient in accordance with the chosen rule of repartition of the pressure. The outcome of this study is the new model of articular cartilage that can be used to simulate and study the micromechanical behaviours of cartilage under different conditions of health and loading. These behaviours are illuminated at the microscale level using the socalled neighbourhood rules developed in the thesis in accordance with the typical requirements of cellular automata modelling. Using these rules and relevant Boundary Conditions to simulate pressure distribution and related fluid motion produced significant results that provided the following insight into the relationships between osmotic pressure gradient and associated fluid micromovement, and the deformation of the matrix. For example, it could be concluded that: 1. It is possible to model articular cartilage with the agent-based model of cellular automata and the Margolus neighbourhood rule. 2. The concept of 3D inter connected osmotic units is a viable structural model for the extracellular matrix of articular cartilage. 3. Different rules of osmotic pressure advection lead to different patterns of deformation in the cartilage matrix, enabling an insight into how this micromechanism influences macromechanical deformation. 4. When features such as transition coefficient were changed, permeability (representing change) is altered due to the change in concentrations of collagen, proteoglycans (i.e. degenerative conditions), the deformation process is impacted. 5. The boundary conditions also influence the relationship between osmotic pressure gradient and fluid movement at the micro-scale level. The outcomes are important to cartilage research since we can use these to study the microscale damage in the cartilage matrix. From this, we are able to monitor related diseases and their progression leading to potential insight into drug-cartilage interaction for treatment. This innovative model is an incremental progress on attempts at creating further computational modelling approaches to cartilage research and other fluid-saturated tissues and material systems.

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Biological systems involving proliferation, migration and death are observed across all scales. For example, they govern cellular processes such as wound-healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behaviour. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pair-wise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplication, in the form of a partial differential equation description for the evolution of pair-wise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behaviour in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before, and our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.

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The T-box family transcription factor gene TBX20 acts in a conserved regulatory network, guiding heart formation and patterning in diverse species. Mouse Tbx20 is expressed in cardiac progenitor cells, differentiating cardiomyocytes, and developing valvular tissue, and its deletion or RNA interference-mediated knockdown is catastrophic for heart development. TBX20 interacts physically, functionally, and genetically with other cardiac transcription factors, including NKX2-5, GATA4, and TBX5, mutations of which cause congenital heart disease (CHD). Here, we report nonsense (Q195X) and missense (I152M) germline mutations within the T-box DNA-binding domain of human TBX20 that were associated with a family history of CHD and a complex spectrum of developmental anomalies, including defects in septation, chamber growth, and valvulogenesis. Biophysical characterization of wild-type and mutant proteins indicated how the missense mutation disrupts the structure and function of the TBX20 T-box. Dilated cardiomyopathy was a feature of the TBX20 mutant phenotype in humans and mice, suggesting that mutations in developmental transcription factors can provide a sensitized template for adult-onset heart disease. Our findings are the first to link TBX20 mutations to human pathology. They provide insights into how mutation of different genes in an interactive regulatory circuit lead to diverse clinical phenotypes, with implications for diagnosis, genetic screening, and patient follow-up.

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Whether by using electronic banking, by using credit cards, or by synchronising a mobile telephone via Bluetooth to an in-car system, humans are a critical part in many cryptographic protocols daily. We reduced the gap that exists between the theory and the reality of the security of these cryptographic protocols involving humans, by creating tools and techniques for proofs and implementations of human-followable security. After three human research studies, we present a model for capturing human recognition; we provide a tool for generating values called Computer-HUman Recognisable Nonces (CHURNs); and we provide a model for capturing human perceptible freshness.

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This thesis is a comprehensive study of the synthesis of nanomaterials. It explores the synthetic methods on the control of the size, shape and phase of semiconductor nanocrystals. A number of important conclusions, including the mechanism behind crystal growth and the structure-relationship, have been drawn through the experimental and theoretical investigation. The synthesized nanocrystals have been tested for applications in gas sensing, photocatalysis and solar cells, which exhibit considerable commercialization potential.

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Liquid metal marbles that are droplets of liquid metal encapsulated by micro- or nanoparticles are introduced. Droplets of galinstan liquid metal are coated with insulators (including Teflon and silica) and semiconductors (including WO3, TiO2, MoO3, In2O3 and carbon nanotubes) by rolling over a powder bed and also by submerging in colloidal suspensions. It is shown that these marbles can be split and merged, can be suspended on water, and are even stable when moving under the force of gravity and impacting a flat solid surface. Furthermore, the marble coating can operate as an active electronic junction and the nanomaterial coated liquid metal marble can act as a highly sensitive electrochemical based heavy metal ion sensor. This new element thus represents a significant platform for the advancement of research into soft electronics.

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We demonstrate for the first time the ionic-liquid-mediated synthesis of nanostructured CuTCNQ by the simple immersion of copper in a solution of TCNQ where the viscosity of the medium significantly impacts the corrosion–crystallization process and the final morphology of the material.

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This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

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This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

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We present results of computational simulations of tungsten-inert-gas and metal-inert-gas welding. The arc plasma and the electrodes (including the molten weld pool when necessary) are included self-consistently in the computational domain. It is shown, using three examples, that it would be impossible to accurately estimate the boundary conditions on the weld-pool surface without including the arc plasma in the computational domain. First, we show that the shielding gas composition strongly affects the properties of the arc that influence the weld pool: heat flux density, current density, shear stress and arc pressure at the weld-pool surface. Demixing is found to be important in some cases. Second, the vaporization of the weld-pool metal and the diffusion of the metal vapour into the arc plasma are found to decrease the heat flux density and current density to the weld pool. Finally, we show that the shape of the wire electrode in metal-inert-gas welding has a strong influence on flow velocities in the arc and the pressure and shear stress at the weld-pool surface. In each case, we present evidence that the geometry and depth of the weld pool depend strongly on the properties of the arc.

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Purpose This study seeks to extend the existing literature on value creation by specifically focusing on service brand value creation (SBVC) and the role of brand marketing. Design/methodology/approach The authors first develop a model of SBVC and simultaneously investigate SBVC from the firm perspective (service brand value offering – SBVO) and from the customer perspective (service brand perceive value-in use – SBPVI). Subsequently, they investigate the effects of SBVO on SBPVI and integrate the moderation role of service brand marketing capability (SBMC) on the relationship between SBVO-SBPVI outcomes. SBVO is viewed as the firms' interpretation of and responsiveness to customer requirements via the delivery of superior performance the value offering through the service brand and SBPVI customers' perceived value from the firms' service brand. The contributions of SBVC to customer-based performance outcomes are then investigated. Hypotheses were tested using a sample of the senior managers of service firms in Cambodia and their customers. A survey was used to gather data via a drop-and-collect approach. Findings Results indicated that SBVO is positively related to SBPVI and SBPVI is positively related to customer-based performance. Noticeably, the results revealed that SBMC enhances the positive relationship between the firm SBVO and the customers SBPVI. Originality/value The paper extends the previous literature on value creation to capture SBVC. More significantly, the premise of the theoretical framework provides a breakthrough in the current SBVC literature which has so far neglected to take into account the dyadic approach (firm-customer) in understanding value creation and more specifically SBVC. The model is expanded by looking at the contingency role of SBMC in communicating value to customers.

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Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.