991 resultados para Modeling Geomorphological Processes


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Dissertation to obtain the degree of Doctor of Philosophy in Biomedical Engineering

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Dissertation presented to obtain the Ph.D degree in Biology

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Dissertação para obtenção do Grau de Doutor em Engenharia Informática

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Software development is a discipline that is almost as old as the history of computers. With the advent of the Internet and all of its related technologies, software development has been on high demand. But, and especially in SME (small and medium enterprise), this was not accompanied with a comparable effort to develop a set of sustainable and standardized activities of project management, which lead to increasing inefficiencies and costs. Given the actual economic situation, it makes sense to engage in an effort to reduce said inefficiencies and rising costs. For that end, this work will analyze the current state of software development’s project management processes on a Portuguese SME, along with its problems and inefficiencies in an effort to create a standardized model to manage software development, with special attention given to critical success factors in an agile software development environment, while using the best practices in process modeling. This work also aims to create guidelines to correctly integrate these changes in the existing IS structure of a company.

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Modeling Extract-Transform-Load (ETL) processes of a Data Warehousing System has always been a challenge. The heterogeneity of the sources, the quality of the data obtained and the conciliation process are some of the issues that must be addressed in the design phase of this critical component. Commercial ETL tools often provide proprietary diagrammatic components and modeling languages that are not standard, thus not providing the ideal separation between a modeling platform and an execution platform. This separation in conjunction with the use of standard notations and languages is critical in a system that tends to evolve through time and which cannot be undermined by a normally expensive tool that becomes an unsatisfactory component. In this paper we demonstrate the application of Relational Algebra as a modeling language of an ETL system as an effort to standardize operations and provide a basis for uncommon ETL execution platforms.

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The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

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The effect of varying separator membrane physical parameters such as degree of porosity, tortuosity and thickness, on battery delivered capacity was studied in order to optimize performance of lithium-ion batteries. This was achieved by a theoretical mathematical model relating the Bruggeman coefficient with the degree of porosity and tortuosity. The inclusion of the separator membrane in the simulation model of the battery system does not affect the delivered capacity of the battery. The ionic conductivity of the separator and consequently the delivered capacity values obtained at different discharge rates depends on the value of the Bruggeman coefficient, which is related with the degree of porosity and tortuosity of the membrane. Independently of scan rate, the optimal value of the degree of porosity is above 50% and the separator thickness should range between 1 μm at 32 μm for improved battery performance.

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This study focuses on the granite mountain known as Monte Pindo (627 m above sea level) in the Autonomous Community of Galicia (NW Spain). This territory is included in the area classified as “Costa da Morte” in the “Politica de Ordenación Litoral” (POL) (Coastal Planning Policy) for the region of Galicia. This coastal unit, located between “Rías Baixas” and “Cape Fisterra” has great potential for demonstrating geological processes and its geomorphological heritage is characterized by a high degree of geodiversity of granite landforms. The main objective of our work is to assess the geomorphological heritage of the site, thus revealing its wide geodiversity. We shall analyze and highlight: its scientific value, developing an inventory of granite landforms; its educational valuel and its geotouristic potential. It must be ensured that the Administration understands that natural diversity is composed of both geodiversity and biodiversity. Only then will the sustainable management of Monte Pindo become possible by integrating natural and cultural heritage values. The goal is to ensure that Monte Pindo and its immediate surroundings become a geopark with the aim of promoting local development projects based on the conservation and valorization of its geological heritage.

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Mathematical and computational models play an essential role in understanding the cellular metabolism. They are used as platforms to integrate current knowledge on a biological system and to systematically test and predict the effect of manipulations to such systems. The recent advances in genome sequencing techniques have facilitated the reconstruction of genome-scale metabolic networks for a wide variety of organisms from microbes to human cells. These models have been successfully used in multiple biotechnological applications. Despite these advancements, modeling cellular metabolism still presents many challenges. The aim of this Research Topic is not only to expose and consolidate the state-of-the-art in metabolic modeling approaches, but also to push this frontier beyond the current edge through the introduction of innovative solutions. The articles presented in this e-book address some of the main challenges in the field, including the integration of different modeling formalisms, the integration of heterogeneous data sources into metabolic models, explicit representation of other biological processes during phenotype simulation, and standardization efforts in the representation of metabolic models and simulation results.

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MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

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MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

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Aim: The aim of the study was to investigate the influence of dietary intake of commercial hydrolyzed collagen (Gelatine Royal ®) on bone remodeling in pre-pubertal children. Methods: A randomized double-blind study was carried out in 60 children (9.42 ± 1.31 years) divided into three groups according to the amount of partially hydrolyzed collagen taken daily for 4 months: placebo (G-I, n = 18), collagen (G-II, n = 20) and collagen + calcium (G-III, n = 22) groups. Analyses of the following biochemical markers were carried out: total and bone alkaline phosphatase (tALP and bALP), osteocalcin, tartrate-resistant acid phosphatase (TRAP), type I collagen carboxy terminal telopeptide, lipids, calcium, 25-hydroxyvitamin D, insulin-like growth factor 1 (IGF-1), thyroid-stimulating hormone, free thyroxin and intact parathormone. Results: There was a significantly greater increase in serum IGF-1 in G-III than in G II (p < 0.01) or G-I (p < 0.05) during the study period, and a significantly greater increase in plasma tALP in G-III than in G-I (p < 0.05). Serum bALP behavior significantly (p < 0.05) differed between G-II (increase) and G-I (decrease). Plasma TRAP behavior significantly differed between G-II and G-I (p < 0.01) and between G-III and G-II (p < 0.05). Conclusion: Daily dietary intake of hydrolyzed collagen seems to have a potential role in enhancing bone remodeling at key stages of growth and development.

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This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

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In recent decades, recognition of both cultural and natural heritage has grown in the Alps. This tendency illustrates a collective identity building (local, national, alpine), but it also highlights, in the current context of global change, a renewed reflection of man's relationship with the environment. Thus, a fundamental and scientific intrinsic value (as a part of wilderness) tends to be recognized in the natural heritage as a whole. However, geoheritage (and geodiversity) is still often perceived as a secondary natural component, compared with bioheritage (and biodiversity). In this context, we study the geomorphological heritage (landforms and the processes that shape them) of Les Contamines-Montjoie Natural Reserve. Indeed, despite the high geomorphological richness (especially glacial) of the reserve, which covers more than 4000 ha of the Mont-Blanc Massif, local recognition of this heritage is still limited. In order to recognize and protect it, and starting with a scientific study, this research identifies the main local richness and assesses the geotourist and educational potentials. Finally, several tools to educate and promote geoheritage (educational paths and website) are proposed.

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Currently in Brazil, as in other parts of the world, the concern is great with the increase of degraded agricultural soil, which is mostly related to the occurrence of soil compaction. Although soil texture is recognized as a very important component in the soil compressive behaviors, there are few studies that quantify its influence on the structural changes of Latosols in the Brazilian Cerrado region. This study aimed to evaluate structural changes and the compressive behavior of Latosols in Rio Verde, Goiás, through the modeling of additional soil compaction. The study was carried out using five Latosols with very different textures, under different soil compaction levels. Water retention and soil compression curves, and bearing capacity models were determined from undisturbed samples collected on the B horizons. Results indicated that clayey and very clayey Latosols were more susceptible to compression than medium-textured soils. Soil compression curves at density values associate with edaphic functions were used to determine the beneficial pressure (σ b) , i.e., pressure with optimal water retention, and critical pressure (σcrMAC), i.e., pressure with macroporosity below critical levels. These pressure values were higher than the preconsolidation pressure (σp), and therefore characterized as additional compaction. Based on the compressive behavior of these Latosols, it can be concluded that the combined preconsolidation pressure, beneficial pressure and critical pressure allow a better understanding of compression processes of Latosols.