980 resultados para sequential reduction processes


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Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes

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We develop an approach for sparse representations of Gaussian Process (GP) models (which are Bayesian types of kernel machines) in order to overcome their limitations for large data sets. The method is based on a combination of a Bayesian online algorithm together with a sequential construction of a relevant subsample of the data which fully specifies the prediction of the GP model. By using an appealing parametrisation and projection techniques that use the RKHS norm, recursions for the effective parameters and a sparse Gaussian approximation of the posterior process are obtained. This allows both for a propagation of predictions as well as of Bayesian error measures. The significance and robustness of our approach is demonstrated on a variety of experiments.

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We develop an approach for sparse representations of Gaussian Process (GP) models (which are Bayesian types of kernel machines) in order to overcome their limitations for large data sets. The method is based on a combination of a Bayesian online algorithm together with a sequential construction of a relevant subsample of the data which fully specifies the prediction of the GP model. By using an appealing parametrisation and projection techniques that use the RKHS norm, recursions for the effective parameters and a sparse Gaussian approximation of the posterior process are obtained. This allows both for a propagation of predictions as well as of Bayesian error measures. The significance and robustness of our approach is demonstrated on a variety of experiments.

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A systematic survey of the possible methods of chemical extraction of iron by chloride formation has been presented and supported by a comparable study of :feedstocks, products and markets. The generation and evaluation of alternative processes was carried out by the technique of morphological analysis vihich was exploited by way of a computer program. The final choice was related to technical feasibility and economic viability, particularly capital cost requirements and developments were made in an estimating procedure for hydrometallurgjcal processes which have general applications. The systematic exploration included the compilation of relevant data, and this indicated a need.to investigate precipitative hydrolysis or aqueous ferric chloride. Arising from this study, two novel hydrometallurgical processes for manufacturing iron powder are proposed and experimental work was undertaken in the following .areas to demonstrate feasibility and obtain basic data for design purposes: (1) Precipitative hydrolysis of aqueous ferric chloride. (2) Gaseous chloridation of metallic iron, and oxidation of resultant ferrous chloride. (3) Reduction of gaseous ferric chloride with hydrogen. (4) Aqueous acid leaching of low grade iron ore. (5) Aqueous acid leaching of metallic iron. The experimentation was supported by theoretical analyses dealing with: (1) Thermodynamics of hydrolysis. (2) Kinetics of ore leaching. (3) Kinetics of metallic iron leaching. (4) Crystallisation of ferrous chloride. (5) Oxidation of anhydrous ferrous chloride. (6) Reduction of ferric chloride. Conceptual designs are suggested fbr both the processes mentioned. These draw attention to areas where further work is necessary, which are listed. Economic analyses have been performed which isolate significant cost areas, und indicate total production costs. Comparisons are mode with previous and analogous proposals for the production of iron powder.

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A wide range of molecules acting as apoptotic cell-associated ligands, phagocyte-associated receptors or soluble bridging molecules have been implicated within the complex sequential processes that result in phagocytosis and degradation of apoptotic cells. Intercellular adhesion molecule 3 (ICAM-3, also known as CD50), a human leukocyte-restricted immunoglobulin super-family (IgSF) member, has previously been implicated in apoptotic cell clearance, although its precise role in the clearance process is ill defined. The main objective of this work is to further characterise the function of ICAM-3 in the removal of apoptotic cells. Using a range of novel anti-ICAM-3 monoclonal antibodies (mAbs), including one (MA4) that blocks apoptotic cell clearance by macrophages, alongside apoptotic human leukocytes that are normal or deficient for ICAM-3, we demonstrate that ICAM-3 promotes a domain 1-2-dependent tethering interaction with phagocytes. Furthermore, we demonstrate an apoptosis-associated reduction in ICAM-3 that results from release of ICAM-3 within microparticles that potently attract macrophages to apoptotic cells. Taken together, these data suggest that apoptotic cell-derived microparticles bearing ICAM-3 promote macrophage chemoattraction to sites of leukocyte cell death and that ICAM-3 mediates subsequent cell corpse tethering to macrophages. The defined function of ICAM-3 in these processes and profound defect in chemotaxis noted to ICAM-3-deficient microparticles suggest that ICAM-3 may be an important adhesion molecule involved in chemotaxis to apoptotic human leukocytes. © 2012 Macmillan Publishers Limited All rights reserved.

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The assessment of the reliability of systems which learn from data is a key issue to investigate thoroughly before the actual application of information processing techniques to real-world problems. Over the recent years Gaussian processes and Bayesian neural networks have come to the fore and in this thesis their generalisation capabilities are analysed from theoretical and empirical perspectives. Upper and lower bounds on the learning curve of Gaussian processes are investigated in order to estimate the amount of data required to guarantee a certain level of generalisation performance. In this thesis we analyse the effects on the bounds and the learning curve induced by the smoothness of stochastic processes described by four different covariance functions. We also explain the early, linearly-decreasing behaviour of the curves and we investigate the asymptotic behaviour of the upper bounds. The effect of the noise and the characteristic lengthscale of the stochastic process on the tightness of the bounds are also discussed. The analysis is supported by several numerical simulations. The generalisation error of a Gaussian process is affected by the dimension of the input vector and may be decreased by input-variable reduction techniques. In conventional approaches to Gaussian process regression, the positive definite matrix estimating the distance between input points is often taken diagonal. In this thesis we show that a general distance matrix is able to estimate the effective dimensionality of the regression problem as well as to discover the linear transformation from the manifest variables to the hidden-feature space, with a significant reduction of the input dimension. Numerical simulations confirm the significant superiority of the general distance matrix with respect to the diagonal one.In the thesis we also present an empirical investigation of the generalisation errors of neural networks trained by two Bayesian algorithms, the Markov Chain Monte Carlo method and the evidence framework; the neural networks have been trained on the task of labelling segmented outdoor images.

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The nature and kinetics of electrode reactions and processes occurring for four lightweight anode systems which have been utilised in reinforced concrete cathodic protection systems have been studied. The anodes investigated were flame sprayed zinc, conductive paint and two activated titanium meshes. The electrochemical properties of each material were investigated in rapidly stirred de-oxygenated electrolytes using anodic potentiodynamic polarisation. Conductive coating electrodes were formed on glass microscope slides, whilst mesh strands were immersed directly. Oxygen evolution occurred preferentially for both mesh anodes in saturated Ca (OH)2/CaC12 solutions but was severely inhibited in less alkaline solutions and significant current only passed in chloride solutions. The main reactions for conductive paint was based on oxygen evolution in all electrolytes, although chlorides increased the electrical activity. Self-corrosion of zinc was controlled by electrolyte composition and the experimental set-up, chlorides increasing the electrical activity. Impressed current cathodic protection was applied to 25 externally exposed concrete slabs over a period of 18 months to investigate anode degradation mechanisms at normal and high current densities. Specimen chloride content, curing and reinforcement depth were also variables. Several destructive and non-destructive methods for assessing the performance of anodes were evaluated including a site instrument for quantitative "instant-off- potential measurements. The impact of cathodic protection on the concrete substrate was determined for a number of specimens using appropriate methods. Anodic degradation rates were primarily influenced by current density, followed by cemendtious alkalinity, chloride levels and by current distribution. Degradation of cementitious overlays and conductive paint substrates proceeded by sequential neutralisation of cement phases, with some evidence of paint binder oxidation. Sprayed zinc progressively formed an insulating layer of hydroxide complexes, which underwent pitting_ attack in the presence of sufficient chlorides, whilst substrate degradation was minimal. Adhesion of all anode systems decreased with increasing current density. The influence of anode material on the ionic gradients which can develop during cathodic protection was investigated. A constant current was passed through saturated cement paste prisms containing calcium chloride to central cathodes via anodes applied or embedded at each end. Pore solution was obtained from successive cut paste slices for anion and cation analyses. Various experimental errors reduced the value of the results. Characteristic S-shaped profiles were not observed and chloride ion profiles were ambiguous. Mesh anode specimens were significantly more durable than the conductive coatings in the high humidity environment. Limited results suggested zinc ion migration to the cathode region. Electrical data from each investigation clearly indicated a decreasing order of anode efficiency by specific anode material.

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This thesis is concerned with the role of diagenesis in forming ore deposits. Two sedimentary 'ore-types' have been examined; the Proterozoic copper-cobalt orebodies of the Konkola Basin on the Zambian Copperbelt, and the Permian Marl Slate of North East England. Facies analysis of the Konkola Basin shows the Ore-Shale to have formed in a subtidal to intertidal environment. A sequence of diagenetic events is outlined from which it is concluded that the sulphide ores are an integral part of the diagenetic process. Sulphur isotope data establish that the sulphides formed as a consequence of the bacterial reduction of sulphate, while the isotopic and geochemical composition of carbonates is shown to reflect changes in the compositions of diagenetic pore fluids. Geochemical studies indicate that the copper and cobalt bearing mineralising fluids probably had different sources. Veins which crosscut the orebodies contain hydrocarbon inclusions, and are shown to be of late diagenetic lateral secretion origin. RbiSr dating indicates that the Ore-Shale was subject to metamorphism at 529 A- 20 myrs. The sedimentology and petrology of the Marl Slate are described. Textural and geochemical studies suggest that much of the pyrite (framboidal) in the Marl Slate formed in an anoxic water column, while euhedral pyrite and base metal sulphides formed within the sediment during early diagenesis. Sulphur isotope data confirm that conditions were almost "ideal" for sulphide formation during Marl Slate deposition, the limiting factors in ore formation being the restricted supply of chalcophile elements. Carbon and oxygen isotope data, along with petrographic observations, indicate that much of the calcite and dolomite occurring in the Marl Slate is primary, and probably formed in isotopic equilibrium. A depositional model is proposed which explains all of the data presented and links the lithological variations with fluctuations in the anoxicioxic boundary layer of the water column.

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The work described in this thesis is directed towards the reduction of noise levels in the Hoover Turbopower upright vacuum cleaner. The experimental work embodies a study of such factors as the application of noise source identification techniques, investigation of the noise generating principles for each major source and evaluation of the noise reducing treatments. It was found that the design of the vacuum cleaner had not been optimised from the standpoint of noise emission. Important factors such as noise `windows', isolation of vibration at the source, panel rattle, resonances and critical speeds had not been considered. Therefore, a number of experimentally validated treatments are proposed. Their noise reduction benefit together with material and tooling costs are presented. The solutions to the noise problems were evaluated on a standard Turbopower and the sound power level of the cleaner was reduced from 87.5 dB(A) to 80.4 db(A) at a cost of 93.6 pence per cleaner.The designers' lack of experience in noise reduction was identified as one of the factors for the low priority given to noise during design of the cleaner. Consequently, the fundamentals of acoustics, principles of noise prediction and absorption and guidelines for good acoustical design were collated into a Handbook and circulated at Hoover plc.Mechanical variations during production of the motor and the cleaner were found to be important. These caused a vast spread in the noise levels of the cleaners. Subsequently, the manufacturing processes were briefly studied to identify their source and recommendations for improvement are made.Noise of a product is quality related and a high level of noise is considered to be a bad feature. This project suggested that the noise level be used constructively both as a test on the production line to identify cleaners above a certain noise level and also to promote the product by `designing' the characteristics of the sound so that the appliance is pleasant to the user. This project showed that good noise control principles should be implemented early in the design stage.As yet there are no mandatory noise limits or noise-labelling requirements for household appliances. However, the literature suggests that noise-labelling is likely in the near future and the requirement will be to display the A-weighted sound power level. However, the `noys' scale of perceived noisiness was found more appropriate to the rating of appliance noise both as it is linear and therefore, a sound level that seems twice as loud is twice the value in noys and also takes into consideration the presence of pure tones, which even in the absence of a high noise level can lead to annoyance.

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In many real applications of Data Envelopment Analysis (DEA), the decision makers have to deteriorate some inputs and some outputs. This could be because of limitation of funds available. This paper proposes a new DEA-based approach to determine highest possible reduction in the concern input variables and lowest possible deterioration in the concern output variables without reducing the efficiency in any DMU. A numerical example is used to illustrate the problem. An application in banking sector with limitation of IT investment shows the usefulness of the proposed method. © 2010 Elsevier Ltd. All rights reserved.

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Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.

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This study investigated group processes as potential mediators or moderators of positive development outcome and negative reduction intervention response by evaluating the utility of a group measure modified from a widely known measure of group impact found in the group therapy research literature. Four group processes were of primary interest, (1) Group Impact; (2) Facilitator Impact; (3) Skills Impact; and (4) Exploration Impact as assessed by the Session Evaluation Form (SEF). Outcome measures included the Personally Expressive Activities Questionnaire (PEAQ), Erikson Psycho-Social Index (EPSI) and the Zill Behavior Items, Behavior Problem Index (ZBI (BPI)). The sample consisted of 121 multi-ethnic participants drawn from four alternative high schools from the Miami-Dade County Public School system. Utilizing a Latent Growth Curve Modeling approach with Structural Equation Modeling (SEM) statistics, preliminary analyses were conducted to evaluate the psychometric properties of the SEF and its role in the mediation or moderation of intervention outcome. Preliminary results revealed evidence of a single higher order factor representing a "General" global reaction, which was hypothesized to be a "Positive Group Climate" construct to the program as opposed to the four distinct group processes that were initially hypothesized to affect outcomes. The results of the evaluation of the mediation or moderation role of intervention outcome of the single "General" global latent factor ("Positive Group Climate" construct) did not significantly predict treatment response on any of the outcome variables. Nevertheless, the evidence of an underlying "General" global latent factor ("Positive Group Climate" construct) has important future directions for research on positive youth development programs as well as in group therapy research.

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Rates of HIV infection continue to climb among minority populations and men who have sex with men (MSM), with African American/Black MSM being especially impacted. Numerous studies have found HIV transmission risk to be associated with many health and social disparities resulting from larger environmental and structural forces. Using anthropological and social environment-based theories of resilience that focus on individual agency and larger social and environmental structures, this dissertation employed a mixed methods design to investigate resilience processes among African American/Black MSM.^ Quantitative analyses compared African American/Black (N=108) and Caucasian/White (N=250) MSM who participated in a previously conducted randomized controlled trial (RCT) of sexual and substance use risk reduction interventions. At RCT study entry, using past 90 day recall periods, there were no differences in unprotected sex frequency, however African American/Black MSM reported higher frequencies of days high (P<0.000), and drugs and sex used in combination (P<0.000), and substance dependence (P<0.000) and lower levels of social support (P<0.024) compared to Caucasian/White MSM. At 12- month follow-up, multi-level statistical models found that African American/Black MSM reduced their frequencies of days high and unprotected sex at greater rates than Caucasian/White MSM (P<0.001).^ Qualitative data collected among a sub-sample of African American/Black MSM from the RCT (N=21) described the men's experiences of living with multiple health and social disparities and the importance of RCT study assessments in facilitating reductions in risk behaviors. A cross-case analysis showed different resilience processes undertaken by men who experienced low socioeconomic status, little family support, and homophobia (N=16) compared to those who did not (N=5).^ The dissertation concludes that resilience processes to HIV transmission risk and related health and social disparities among African American/Black MSM varies and are dependent on specific social environmental factors, including social relationships, structural homophobia, and access to social, economic, and cultural capital. Men define for themselves what it means to be resilient within their social environment. These conclusions suggest that both individual and structural-level resilience-based HIV prevention interventions are needed.^

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Purpose – The purpose of this paper is to provide an analysis of sistematización’s use as a research tool in the operationalization of a “neighborhood approach” to the implementation of disaster risk reduction (DRR) in informal urban settlements. Design/methodology/approach – The first section highlights sistematización’s historical origins in Latin America in the fields of popular adult education, social work, and rural development. The second explains why sistematización was made a required component of project implementation. The third section addresses the approach to sistematización used. The final discusses how this experience both contributes to sistematización’s theoretical development and practical application as a methodology. Findings – The introduction of “sistematización” as a research tool facilitated real-time assessment of project implementation, providing timely information that positively influenced decision-making processes. This on-going feedback, collective learning, and open-exchange of know-how between NGOs and partner institutions allowed for the evaluation of existing practices and development of new ways of collaborating to address disaster risk in complex and dynamic urban environments. Practical implications – Sistematización transcends the narrow focus of traditional monitoring and evaluation on final results, emphasizing a comprehensive understanding of processes and contexts. Originality/value – Its use in the implementation of DRR initiatives in informal urban environments is particularly novel, highlighting the capacity of the methodology to be tailored to a variety of needs, in this case, bridging the gap between NGOs, local governments, and vulnerable communities, as well as between urban, development, and disaster risk management planning.

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Since the Exxon Valdez accident in 1987, renewed interest has come forth to better understand and predict the fate and transport of crude oil lost to marine environments. The short-term fate of an Arabian Crude oil was simulated in laboratory experiments using artificial seawater. The time-dependent changes in the rheological and chemical properties of the oil under the influence of natural weathering processes were characterized, including dispersion behavior of the oil under simulated ocean turbulence. Methodology included monitoring the changes in the chemical composition of the oil by Gas Chromatography/Mass Spectrometry (GCMS), toxicity evaluations for the oil dispersions by Microtox analysis, and quantification of dispersed soluble aromatics by fluorescence spectrometry. Results for this oil show a sharp initial increase in viscosity, due to evaporative losses of lower molecular weight hydrocarbons, with the formation of stable water-in-oil emulsions occurring within one week. Toxicity evaluations indicate a decreased EC-50 value (higher toxicity) occurring after the oil has weathered eight hours, with maximum toxicity being observed after weathering seven days. Particle charge distributions, determined by electrophoretic techniques using a Coulter DELSA 440, reveal that an unstable oil dispersion exists within the size range of 1.5 to 2.5 um, with recombination processes being observed between sequential laser runs of a single sample.