892 resultados para Towards Seamless Integration of Geoscience Models and Data


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Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

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Characterisation of a number of key wood properties utilising ‘state of the art’ tools was achieved for four commercial Australian hardwood species: Corymbia citriodora, Eucalyptus pilularis, Eucalyptus marginata and Eucalyptus obliqua. The wood properties were measured for input into microscopic (cellular level) and macroscopic (board level) vacuum drying models currently under development. Morphological characterisation was completed using a combination of ESEM, optical microscopy and a custom vector-based image analysis software. A clear difference in wood porosity, size, wall thickness and orientation was evident between species. Wood porosity was measured using a combination of fibre and vessel porosity. A highly sensitive microbalance and scanning laser micrometres were used to measure loss of moisture content in conjunction with directional shrinkage on micro-samples of E. obliqua to investigate the validity of measuring collapse-free shrinkage in very thin sections. Collapse-free shrinkage was characterised, and collapse propensity was verified when testing thicker samples. Desorption isotherms were calculated for each species using wood–water relations data generated from shrinkage experiments. Fibre geometry and wood shrinkage anisotropy were used to explain the observed difficulty in drying of the different species in terms of collapse and drying stress-related degrade.

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MEMS resonators are designed for a fixed resonant frequency. Therefore, any shift in the resonant frequency of the final fabricated structure can be a denting factor for its suitability towards a desired application. There are numerous factors which alter the designed resonant frequency of the fabricated resonator such as the metal layer deposited on top of the beam and the residual stresses present in the fabricated structure. While the metal coating, which acts as electrode, increases the stiffness and the effective mass of the composite structure, the residual stress increases or decreases the net stiffness if it is a tensile or compressive type respectively. In this paper, we investigate both these cases by taking two different structures, namely, the micro cantilever beam with gold layer deposited on its top surface and the MEMS gyroscope with residual stresses. First, we carry out experiments to characterize both these structures to find their resonant frequencies. Later, we analytically model those effects and compare them with the experimentally obtained values. Finally, it is found that the analytical models give an error of less than 10% with respect to the experimental results in both the cases.

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Stem cells are responsible for tissue turnover throughout lifespan. Only highly controlled specific environment, the stem cell niche , can sustain undifferentiated stem cell-pool. The balance between maintenance and differentiation is crucial for individual s health: uncontrolled stem cell self-renewal or proliferation can lead to hyperplasia and mutations that further provoke malignant transformation of the cells. On the other hand, uninhibited differentiation may result in diminished stem cell population, which is unable to maintain tissue turnover. The mechanisms that control the switch from maintenance to differentiation in stem cells are not well known. The same mechanisms that direct the self-renewal and proliferation in normal stem cells are likely to be also involved in maintenance of cancer stem cell . Cancer stem cells exhibit stem cell like properties such as self-renewal- and differentiation capacity and they can also regenerate the tumor tissue. In this thesis, I have investigated the effect of classical oncogenes E6/E7 and c-Myc, tumor suppressors p53 and retinoblastoma (pRb) family, and vascular endothelial growth factor (VEGF) subfamily and glial cell line-derived neurothropic factor (GDNF) family ligands on behavior of embryonic neural stem cells (NSCs) and progenitors. The study includes also the characterization of cytoskeletal tumor suppressor neurofibromatosis 2 (NF2) protein merlin and ezrin-radixin-moesin (ERM) protein ezrin expression in neural progenitors cells and their progeny. This study reveals some potential mechanisms regarding to NSCs maintenance. In summary, the studied molecules are able to shift the balance either towards stem cell maintenance or differentiation; tumor suppressor p53 represses whereas E6/E7 oncogenes and c-Myc increase the proportion of self-renewing and proliferating NSCs or progenitors. The data suggests that active MEK-ERK signaling is critical for self-renewal of normal and oncogene expressing NSCs. In addition, the results indicate that expression of cytoskeletal tumor suppressor merlin and ERM protein ezrin in central nervous system (CNS) tissue and progenitors indicates their role in cell differentiation. Furthermore, the data suggests that VEGF-C a factor involved in lymphatic system development, angiogenesis, neovascularization and metastasis but also in maintenance of some neural populations in brain is a novel thropic factor for progenitors in early sympathetic nervous system (SNS). It seems that VEGF-C dose dependently through ERK-pathway supports the proliferation and survival of early sympathetic progenitor cells, and the effect is comparable to that of GDNF family ligands.

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Objective: To systematically review studies reporting the prevalence in general adult inpatient populations of foot disease disorders (foot wounds, foot infections, collective ‘foot disease’) and risk factors (peripheral arterial disease (PAD), peripheral neuropathy (PN), foot deformity). Methods: A systematic review of studies published between 1980 and 2013 was undertaken using electronic databases (MEDLINE, EMBASE and CINAHL). Keywords and synonyms relating to prevalence, inpatients, foot disease disorders and risk factors were used. Studies reporting foot disease or risk factor prevalence data in general inpatient populations were included. Included study's reference lists and citations were searched and experts consulted to identify additional relevant studies. 2 authors, blinded to each other, assessed the methodological quality of included studies. Applicable data were extracted by 1 author and checked by a second author. Prevalence proportions and SEs were calculated for all included studies. Pooled prevalence estimates were calculated using random-effects models where 3 eligible studies were available. Results: Of the 4972 studies initially identified, 78 studies reporting 84 different cohorts (total 60 231 517 participants) were included. Foot disease prevalence included: foot wounds 0.01–13.5% (70 cohorts), foot infections 0.05–6.4% (7 cohorts), collective foot disease 0.2–11.9% (12 cohorts). Risk factor prevalence included: PAD 0.01–36.0% (10 cohorts), PN 0.003–2.8% (6 cohorts), foot deformity was not reported. Pooled prevalence estimates were only able to be calculated for pressure ulcer-related foot wounds 4.6% (95% CI 3.7% to 5.4%)), diabetes-related foot wounds 2.4% (1.5% to 3.4%), diabetes-related foot infections 3.4% (0.2% to 6.5%), diabetes-related foot disease 4.7% (0.3% to 9.2%). Heterogeneity was high in all pooled estimates (I2=94.2–97.8%, p<0.001). Conclusions: This review found high heterogeneity, yet suggests foot disease was present in 1 in every 20 inpatients and a major risk factor in 1 in 3 inpatients. These findings are likely an underestimate and more robust studies are required to provide more precise estimates.

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Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

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Many biological environments are crowded by macromolecules, organelles and cells which can impede the transport of other cells and molecules. Previous studies have sought to describe these effects using either random walk models or fractional order diffusion equations. Here we examine the transport of both a single agent and a population of agents through an environment containing obstacles of varying size and shape, whose relative densities are drawn from a specified distribution. Our simulation results for a single agent indicate that smaller obstacles are more effective at retarding transport than larger obstacles; these findings are consistent with our simulations of the collective motion of populations of agents. In an attempt to explore whether these kinds of stochastic random walk simulations can be described using a fractional order diffusion equation framework, we calibrate the solution of such a differential equation to our averaged agent density information. Our approach suggests that these kinds of commonly used differential equation models ought to be used with care since we are unable to match the solution of a fractional order diffusion equation to our data in a consistent fashion over a finite time period.

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The independent manufacturer’s furniture showroom, as defined by Herman Miller and Knoll in the mid-twentieth century, presented a highly controlled and controllable context in which both companies and their designers familiarized American architects, designers and consumers with new ideas about living with modern furniture and architecture. Embracing consumerism within a modernist idiom, these mid-century furniture showrooms provided a unique interior typology wherein the reconciliation of modernism, mass-produced goods and personal expression was not only possible, but also accessible. Challenging long-held practices and beliefs within the nation’s conservative home furnishings market, Herman Miller and Knoll superseded retail buyers by reaching out directly to customers. The independently-run showrooms allowed both companies to engage their customers in a sophisticated and sustained proposition about the role of modern furniture and architecture in daily life. Examining the showrooms designed for Herman Miller and Knoll Associates during the latter 1940s and early 1950s, this article explores the ways in which these spaces were utilized as both laboratories and showcases, demonstrating the adaptability of modern furniture and interiors to individual lifestyles. Key words Charles and Ray Eames display design furniture Herman Miller Knoll Associates modernism showrooms

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(CH3)4NGeCl3 is prepared, characterized and studied using 1H NMR spin lattice relaxation time and second moment to understand the internal motions and quantum rotational tunneling. Proton second moment is measured at 7 MHz as function of temperature in the range 300-77 K and spin lattice relaxation time (T1) is measured at two Larmor frequencies, as a function of temperature in the range 270-17 K employing a homemade wide-line/pulsed NMR spectrometers. T1 data are analyzed in two temperature regions using relevant theoretical models. The relaxation in the higher temperatures (270-115 K) is attributed to the hindered reorientations of symmetric groups (CH3 and (CH3)4N). Broad asymmetric T1 minima observed below 115 K down to 17 K are attributed to quantum rotational tunneling of the inequivalent methyl groups.

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The aim of this study was to identify and describe the types of errors in clinical reasoning that contribute to poor diagnostic performance at different levels of medical training and experience. Three cohorts of subjects, second- and fourth- (final) year medical students and a group of general practitioners, completed a set of clinical reasoning problems. The responses of those whose scores fell below the 25th centile were analysed to establish the stage of the clinical reasoning process - identification of relevant information, interpretation or hypothesis generation - at which most errors occurred and whether this was dependent on problem difficulty and level of medical experience. Results indicate that hypothesis errors decrease as expertise increases but that identification and interpretation errors increase. This may be due to inappropriate use of pattern recognition or to failure of the knowledge base. Furthermore, although hypothesis errors increased in line with problem difficulty, identification and interpretation errors decreased. A possible explanation is that as problem difficulty increases, subjects at all levels of expertise are less able to differentiate between relevant and irrelevant clinical features and so give equal consideration to all information contained within a case. It is concluded that the development of clinical reasoning in medical students throughout the course of their pre-clinical and clinical education may be enhanced by both an analysis of the clinical reasoning process and a specific focus on each of the stages at which errors commonly occur.

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This paper deals with the development of simplified semi-empirical relations for the prediction of residual velocities of small calibre projectiles impacting on mild steel target plates, normally or at an angle, and the ballistic limits for such plates. It has been shown, for several impact cases for which test results on perforation of mild steel plates are available, that most of the existing semi-empirical relations which are applicable only to normal projectile impact do not yield satisfactory estimations of residual velocity. Furthermore, it is difficult to quantify some of the empirical parameters present in these relations for a given problem. With an eye towards simplicity and ease of use, two new regression-based relations employing standard material parameters have been discussed here for predicting residual velocity and ballistic limit for both normal and oblique impact. The latter expressions differ in terms of usage of quasi-static or strain rate-dependent average plate material strength. Residual velocities yielded by the present semi-empirical models compare well with the experimental results. Additionally, ballistic limits from these relations show close correlation with the corresponding finite element-based predictions.

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The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.