894 resultados para Numerical approximation and analysis
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Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.
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With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.
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Predicting the evolution of a coastal cell requires the identification of the key drivers of morphology. Soft coastlines are naturally dynamic but severe storm events and even human intervention can accelerate any changes that are occurring. However, when erosive events such as barrier breaching occur with no obvious contributory factors, a deeper understanding of the underlying coastal processes is required. Ideally conclusions on morphological drivers should be drawn from field data collection and remote sensing over a long period of time. Unfortunately, when the Rossbeigh barrier beach in Dingle Bay, County Kerry, began to erode rapidly in the early 2000’s, eventually leading to it breaching in 2008, no such baseline data existed. This thesis presents a study of the morphodynamic evolution of the Inner Dingle Bay coastal system. The study combines existing coastal zone analysis approaches with experimental field data collection techniques and a novel approach to long term morphodynamic modelling to predict the evolution of the barrier beach inlet system. A conceptual model describing the long term evolution of Inner Dingle Bay in 5 stages post breaching was developed. The dominant coastal processes driving the evolution of the coastal system were identified and quantified. A new methodology of long term process based numerical modelling approach to coastal evolution was developed. This method was used to predict over 20 years of coastal evolution in Inner Dingle Bay. On a broader context this thesis utilised several experimental coastal zone data collection and analysis methods such as ocean radar and grain size trend analysis. These were applied during the study and their suitability to a dynamic coastal system was assessed.
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The literature clearly links the quality and capacity of a country’s infrastructure to its economic growth and competitiveness. This thesis analyses the historic national and spatial distribution of investment by the Irish state in its physical networks (water, wastewater and roads) across the 34 local authorities and examines how Ireland is perceived internationally relative to its economic counterparts. An appraisal of the current status and shortcomings of Ireland’s infrastructure is undertaken using key stakeholders from foreign direct investment companies and national policymakers to identify Ireland's infrastructural gaps, along with current challenges in how the country is delivering infrastructure. The output of these interviews identified many issues with how infrastructure decision-making is currently undertaken. This led to an evaluation of how other countries are informing decision-making, and thus this thesis presents a framework of how and why Ireland should embrace a Systems of Systems (SoS) methodology approach to infrastructure decision-making going forward. In undertaking this study a number of other infrastructure challenges were identified: significant political interference in infrastructure decision-making and delivery the need for a national agency to remove the existing ‘silo’ type of mentality to infrastructure delivery how tax incentives can interfere with the market; and their significance. The two key infrastructure gaps identified during the interview process were: the need for government intervention in the rollout of sufficient communication capacity and at a competitive cost outside of Dublin; and the urgent need to address water quality and capacity with approximately 25% of the population currently being served by water of unacceptable quality. Despite considerable investment in its national infrastructure, Ireland’s infrastructure performance continues to trail behind its economic partners in the Eurozone and OECD. Ireland is projected to have the highest growth rate in the euro zone region in 2015 and 2016, albeit that it required a bailout in 2010, and, at the time of writing, is beginning to invest in its infrastructure networks again. This thesis proposes the development and implementation of a SoS approach for infrastructure decision-making which would be based on: existing spatial and capacity data of each of the constituent infrastructure networks; and scenario computation and analysis of alternative drivers eg. Demographic change, economic variability and demand/capacity constraints. The output from such an analysis would provide valuable evidence upon which policy makers and decision makers alike could rely, which has been lacking in historic investment decisions.
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This paper is about a PhD thesis and includes the study and analysis of the performance of an onshore wind energy conversion system. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as integer-order controllers, fractional-order controllers, fuzzy logic controllers, adaptive controllers and predictive controllers and the study of a supervisor based on finite state machines is also studied. The controllers are included in the lower level of a hierarchical structure composed by two levels whose objective is to control the electric output power around the rated power. The supervisor included at the higher level is based on finite state machines whose objective is to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the wind energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. The wind energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two mass drive train, a gearbox, a doubly fed induction generator rotor and by a two level converter.
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The scalar Schrödinger equation models the probability density distribution for a particle to be found in a point x given a certain potential V(x) forming a well with respect to a fixed energy level E_0. Formally two real inversion points a,b exist such that V(a)=V(b)=E_0, V(x)<0 in (a,b) and V(x)>0 for xb. Following the work made by D.Yafaev and performing a WKB approximation we obtain solutions defined on specific intervals. The aim of the first part of the thesis is to find a condition on E, which belongs to a neighbourhood of E_0, such that it is an eigenvalue of the Schrödinger operator, obtaining in this way global and linear dependent solutions in L2. In quantum mechanics this condition is known as Bohr-Sommerfeld quantization. In the second part we define a Schrödinger operator referred to two potential wells and we study the quantization conditions on E in order to have a global solution in L2xL2 with respect to the mutual position of the potentials. In particular their wells can be disjoint,can have an intersection, can be included one into the other and can have a single point intersection. For these cases we refer to the works of A.Martinez, S. Fujiié, T. Watanabe, S. Ashida.
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In the last few decades, offshore field has grown fast especially after the notable development of technologies, explorations of oil and gas in deep water and the high concern of offshore companies in renewable energy mainly Wind Energy. Fatigue damage was noticed as one of the main problems causing failure of offshore structures. The purpose of this research is to focus on the evaluation of Stress Concentration Factor and its influence on Fatigue Life for 2 tubular KT-Joints in offshore Jacket structure using different calculation methods. The work is done by using analytical calculations, mainly Efthymiou’s formulations, and numerical solutions, FEM analysis, using ABAQUS software. As for the analytical formulations, the calculations were done according to the geometrical parameters of each method using excel sheets. As for the numerical model, 2 different types of tubular KT-Joints are present where for each model 5 shell element type, 3 solid element type and 3 solid-with-weld element type models were built on ABAQUS. Meshing was assigned according to International Institute of Welding (IIW) recommendations, 5 types of mesh element, to evaluate the Hot-spot stresses. 23 different types of unitary loading conditions were assigned, 9 axial, 7 in-plane bending moment and 7 out-plane bending moment loads. The extraction of Hot-spot stresses and the evaluation of the Stress Concentration Factor were done using PYTHON scripting and MATLAB. Then, the fatigue damage evaluation for a critical KT tubular joint based on Simplified Fatigue Damage Rule and Local Approaches (Strain Damage Parameter and Stress Damage Parameter) methods were calculated according to the maximum Stress Concentration Factor conducted from DNV and FEA methods. In conclusion, this research helped us to compare different results of Stress Concentration Factor and Fatigue Life using different methods and provided us with a general overview about what to study next in the future.
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The main purpose of this work is to develop a numerical platform for the turbulence modeling and optimal control of liquid metal flows. Thanks to their interesting thermal properties, liquid metals are widely studied as coolants for heat transfer applications in the nuclear context. However, due to their low Prandtl numbers, the standard turbulence models commonly used for coolants as air or water are inadequate. Advanced turbulence models able to capture the anisotropy in the flow and heat transfer are then necessary. In this thesis, a new anisotropic four-parameter turbulence model is presented and validated. The proposed model is based on explicit algebraic models and solves four additional transport equations for dynamical and thermal turbulent variables. For the validation of the model, several flow configurations are considered for different Reynolds and Prandtl numbers, namely fully developed flows in a plane channel and cylindrical pipe, and forced and mixed convection in a backward-facing step geometry. Since buoyancy effects cannot be neglected in liquid metals-cooled fast reactors, the second aim of this work is to provide mathematical and numerical tools for the simulation and optimization of liquid metals in mixed and natural convection. Optimal control problems for turbulent buoyant flows are studied and analyzed with the Lagrange multipliers method. Numerical algorithms for optimal control problems are integrated into the numerical platform and several simulations are performed to show the robustness, consistency, and feasibility of the method.
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Background: WGS is increasingly used as a first-line diagnostic test for patients with rare genetic diseases such as neurodevelopmental disorders (NDD). Clinical applications require a robust infrastructure to support processing, storage and analysis of WGS data. The identification and interpretation of SVs from WGS data also needs to be improved. Finally, there is a need for a prioritization system that enables downstream clinical analysis and facilitates data interpretation. Here, we present the results of a clinical application of WGS in a cohort of patients with NDD. Methods: We developed highly portable workflows for processing WGS data, including alignment, quality control, and variant calling of SNVs and SVs. A benchmark analysis of state-of-the-art SV detection tools was performed to select the most accurate combination for SV calling. A gene-based prioritization system was also implemented to support variant interpretation. Results: Using a benchmark analysis, we selected the most accurate combination of tools to improve SV detection from WGS data and build a dedicated pipeline. Our workflows were used to process WGS data from 77 NDD patient-parent families. The prioritization system supported downstream analysis and enabled molecular diagnosis in 32% of patients, 25% of which were SVs and suggested a potential diagnosis in 20% of patients, requiring further investigation to achieve diagnostic certainty. Conclusion: Our data suggest that the integration of SNVs and SVs is a main factor that increases diagnostic yield by WGS and show that the adoption of a dedicated pipeline improves the process of variant detection and interpretation.
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Tsunamis are rare events. However, their impact can be devastating and it may extend to large geographical areas. For low-probability high-impact events like tsunamis, it is crucial to implement all possible actions to mitigate the risk. The tsunami hazard assessment is the result of a scientific process that integrates traditional geological methods, numerical modelling and the analysis of tsunami sources and historical records. For this reason, analysing past events and understanding how they interacted with the land is the only way to inform tsunami source and propagation models, and quantitatively test forecast models like hazard analyses. The primary objective of this thesis is to establish an explicit relationship between the macroscopic intensity, derived from historical descriptions, and the quantitative physical parameters measuring tsunami waves. This is done first by defining an approximate estimation method based on a simplified 1D physical onshore propagation model to convert the available observations into one reference physical metric. Wave height at the coast was chosen as the reference due to its stability and independence of inland effects. This method was then implemented for a set of well-known past events to build a homogeneous dataset with both macroseismic intensity and wave height. By performing an orthogonal regression, a direct and invertible empirical relationship could be established between the two parameters, accounting for their relevant uncertainties. The target relationship is extensively tested and finally applied to the Italian Tsunami Effect Database (ITED), providing a homogeneous estimation of the wave height for all existing tsunami observations in Italy. This provides the opportunity for meaningful comparison for models and simulations, as well as quantitatively testing tsunami hazard models for the Italian coasts and informing tsunami risk management initiatives.
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This thesis deals with the sizing and analysis of the electrical power system of a petrochemical plant. The activity was carried out in the framework of an electrical engineering internship. The sizing and electrical calculations, as well as the study of the dynamic behavior of network quantities, are accomplished by using the ETAP (Electrical Transient Analyzer Program) software. After determining the type and size of the loads, the calculation of power flows is carried out for all possible network layout and different power supply configurations. The network is normally operated in a double radial configuration. However, the sizing must be carried out taking into account the most critical configuration, i.e., the temporary one of single radial operation, and also considering the most unfavorable power supply conditions. The calculation of shortcircuit currents is then carried out and the appropriate circuit breakers are selected. Where necessary, capacitor banks are sized in order to keep power factor at the point of common coupling within the preset limits. The grounding system is sized by using the finite element method. For loads with the highest level of criticality, UPS are sized in order to ensure their operation even in the absence of the main power supply. The main faults that can occur in the plant are examined, determining the intervention times of the protections to ensure that, in case of failure on one component, the others can still properly operate. The report concludes with the dynamic and stability analysis of the power system during island operation, in order to ensure that the two gas turbines are able to support the load even during transient conditions.
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Lawsonia inermis mediated synthesis of silver nanoparticles (Ag-NPs) and its efficacy against Candida albicans, Microsporum canis, Propioniabacterium acne and Trichophyton mentagrophytes is reported. A two-step mechanism has been proposed for bioreduction and formation of an intermediate complex leading to the synthesis of capped nanoparticles was developed. In addition, antimicrobial gel for M. canis and T. mentagrophytes was also formulated. Ag-NPs were synthesized by challenging the leaft extract of L. inermis with 1 mM AgNO₃. The Ag-NPs were characterized by Ultraviolet-Visible (UV-Vis) spectrophotometer and Fourier transform infrared spectroscopy (FTIR). Transmission electron microscopy (TEM), nanoparticle tracking and analysis sytem (NTA) and zeta potential was measured to detect the size of Ag-NPs. The antimicrobial activity of Ag-NPs was evaluated by disc diffusion method against the test organisms. Thus these Ag-NPs may prove as a better candidate drug due to their biogenic nature. Moreover, Ag-NPs may be an answer to the drug-resistant microorganisms.
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This study aims to evaluate the frequency and severity of nausea and vomiting using two different instruments and relate them to quality of life (QOL) in patients with cancer receiving antineoplastic treatment. Severity of chemotherapy-induced nausea and vomiting (CINV) was measured by Common Terminology Criteria for Adverse Events (CTCAE) and a numerical scale. QOL was assessed using the Functional Assessment of Cancer Therapy-General questionnaire. Of the 50 patients studied, 60.0% reported nausea (40.0% CTCAE grade 1; 66.7% moderate intensity on numerical scale) and 30.0% reported vomiting (46.7% CTCAE grades 1 and 2, each; 66.7% moderate intensity on numerical scale). CINV did not influence overall QOL. The frequency of CINV was high. There was no association between nausea/vomiting and overall QOL.
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Universidade Estadual de Campinas . Faculdade de Educação Física
Acupuncture for the prevention of radiation-induced xerostomia in patients with head and neck cancer
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The aim of this study was to evaluate the effectiveness of acupuncture in minimizing the severity of radiation-induced xerostomia in patients with head and neck cancer. A total of 24 consecutive patients receiving > 5000 cGy radiotherapy (RT) involving the major salivary glands bilaterally were assigned to either the preventive acupuncture group (PA, n = 12), treated with acupuncture before and during RT, or the control group (CT, n = 12), treated with RT and not receiving acupuncture. After RT completion, clinical response was assessed in all patients by syalometry, measuring the resting (RSFR) and stimulated (SSFR) salivary flow rates, and by the visual analogue scale (VAS) regarding dry mouth-related symptoms. Statistical analyses were performed with repeated-measures using a mixed-effect modeling procedure and analysis of variance. An alpha level of 0.05 was accepted for statistical significance. Although all patients exhibited some degree of impairment in salivary gland functioning after RT, significant differences were found between the groups. Patients in the PA group showed improved salivary flow rates (RSFR, SSFR; p < 0.001) and decreased xerostomia-related symptoms (VAS, p < 0.05) compared with patients in the CT group. Although PA treatment did not prevent the oral sequelae of RT completely, it significantly minimized the severity of radiation-induced xerostomia. The results suggest that acupuncture focused in a preventive approach can be a useful therapy in the management of patients with head and neck cancer undergoing RT.