993 resultados para runoff generation processes


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Assessing temporal variations in soil water flow is important, especially at the hillslope scale, to identify mechanisms of runoff and flood generation and pathways for nutrients and pollutants in soils. While surface processes are well considered and parameterized, the assessment of subsurface processes at the hillslope scale is still challenging since measurement of hydrological pathways is connected to high efforts in time, money and personnel work. The latter might not even be possible in alpine environments with harsh winter processes. Soil water stable isotope profiles may offer a time-integrating fingerprint of subsurface water pathways. In this study, we investigated the suitability of soil water stable isotope (d18O) depth profiles to identify water flow paths along two transects of steep subalpine hillslopes in the Swiss Alps. We applied a one-dimensional advection–dispersion model using d18O values of precipitation (ranging from _24.7 to _2.9‰) as input data to simulate the d18O profiles of soil water. The variability of d18O values with depth within each soil profile and a comparison of the simulated and measured d18O profiles were used to infer information about subsurface hydrological pathways. The temporal pattern of d18O in precipitation was found in several profiles, ranging from _14.5 to _4.0‰. This suggests that vertical percolation plays an important role even at slope angles of up to 46_. Lateral subsurface flow and/or mixing of soil water at lower slope angles might occur in deeper soil layers and at sites near a small stream. The difference between several observed and simulated d18O profiles revealed spatially highly variable infiltration patterns during the snowmelt periods: The d18O value of snow (_17.7 ± 1.9‰) was absent in several measured d18O profiles but present in the respective simulated d18O profiles. This indicated overland flow and/or preferential flow through the soil profile during the melt period. The applied methods proved to be a fast and promising tool to obtain time-integrated information on soil water flow paths at the hillslope scale in steep subalpine slopes.

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The RNome of a cell is highly diverse and consists besides messenger RNAs (mRNAs), transfer RNAs (tRNAs), and ribosomal RNAs (rRNAs) also of other small and long transcript entities without apparent coding potential. This class of molecules, commonly referred to as non-protein-coding RNAs (ncRNAs), is involved in regulating numerous biological processes and thought to contribute to cellular complexity. Therefore, much effort is put into their identification and further functional characterization. Here we provide a cost-effective and reliable method for cDNA library construction of small RNAs in the size range of 20-500 residues. The effectiveness of the described method is demonstrated by the analysis of ribosome-associated small RNAs in the eukaryotic model organism Trypanosoma brucei.

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Autophagy has been demonstrated to have an essential function in several cellular hematopoietic differentiation processes, for example, the differentiation of reticulocytes. To investigate the role of autophagy in neutrophil granulopoiesis, we studied neutrophils lacking autophagy-related (Atg) 5, a gene encoding a protein essential for autophagosome formation. Using Cre-recombinase mediated gene deletion, Atg5-deficient neutrophils showed no evidence of abnormalities in morphology, granule protein content, apoptosis regulation, migration, or effector functions. In such mice, however, we observed an increased proliferation rate in the neutrophil precursor cells of the bone marrow as well as an accelerated process of neutrophil differentiation, resulting in an accumulation of mature neutrophils in the bone marrow, blood, spleen, and lymph nodes. To directly study the role of autophagy in neutrophils, we employed an in vitro model of differentiating neutrophils that allowed modulating the levels of ATG5 expression, or, alternatively, intervening pharmacologically with autophagy-regulating drugs. We could show that autophagic activity correlated inversely with the rate of neutrophil differentiation. Moreover, pharmacological inhibition of p38 MAPK or mTORC1 induced autophagy in neutrophilic precursor cells and blocked their differentiation, suggesting that autophagy is negatively controlled by the p38 MAPK-mTORC1 signaling pathway. On the other hand, we obtained no evidence for an involvement of the PI3K-AKT or ERK1/2 signaling pathways in the regulation of neutrophil differentiation. Taken together, these findings show that, in contrast to erythropoiesis, autophagy is not essential for neutrophil granulopoiesis, having instead a negative impact on the generation of neutrophils. Thus, autophagy and differentiation exhibit a reciprocal regulation by the p38-mTORC1 axis.

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Acid rock drainage (ARD) is a problem of international relevance with substantial environmental and economic implications. Reactive transport modeling has proven a powerful tool for the process-based assessment of metal release and attenuation at ARD sites. Although a variety of models has been used to investigate ARD, a systematic model intercomparison has not been conducted to date. This contribution presents such a model intercomparison involving three synthetic benchmark problems designed to evaluate model results for the most relevant processes at ARD sites. The first benchmark (ARD-B1) focuses on the oxidation of sulfide minerals in an unsaturated tailing impoundment, affected by the ingress of atmospheric oxygen. ARD-B2 extends the first problem to include pH buffering by primary mineral dissolution and secondary mineral precipitation. The third problem (ARD-B3) in addition considers the kinetic and pH-dependent dissolution of silicate minerals under low pH conditions. The set of benchmarks was solved by four reactive transport codes, namely CrunchFlow, Flotran, HP1, and MIN3P. The results comparison focused on spatial profiles of dissolved concentrations, pH and pE, pore gas composition, and mineral assemblages. In addition, results of transient profiles for selected elements and cumulative mass loadings were considered in the intercomparison. Despite substantial differences in model formulations, very good agreement was obtained between the various codes. Residual deviations between the results are analyzed and discussed in terms of their implications for capturing system evolution and long-term mass loading predictions.

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This work is aimed at improving our current knowledge of the non-enzymatic inecl~anisins involved in brown-rot decay, as well as the exploration of potential applications of a brown-rot mimetic model system in paper recycling processes. The study was divided into two parts. The first part focussed on the chemical mechanisms involved in chelation and reduction of iron by a low molecular weight chelator (isolated from the brown-rot fungus Gloeophyllz~m tmbeum) and its model compound 2,3- dihydroxybenzoic acid (2,3-DHBA). Chelation as well as free radical generation mediated by this system were studied by ESR measurement. The results indicate that the effects of the chelator/iron ratio, the pH, and other reaction parameters on hydroxyl radical generation by a Fenton type system could be determined using ESR spin-trapping techniques. The results also support the hypothesis that superoxide radicals are involved in the chelator-mediated Fenton process. In the second part of the study, the effect of a chelator-mediated Fenton system for the improvement of deinking efficiency and the n~odification of fiber and paper properties was studied. For the deinking study, copy paper was laser printed with an identical standard pattern. Then repulping and flotation operations were performed to remove ink particles. Under properly controlled deinking conditions, the chelator mediated treatment (CMT) resulted in a reduction in dirt count over that of conventional deinking procedures with no significant loss of pulp strength. To study the effect of the chelator system treatment on the quality of pulp with different fines content, a fully bleached hardwood kraft pulp was beaten to different freeness levels and treated with the chelator-mediated free radical system. The result shows that virgin fiber and heavily beaten fiber respond differently to the free radical treatment. Unbeaten fibers become more flexible and easier to collapse after free radical treatment, while beaten fibers show a reduction in fines and small materials after mild free radical treatment.

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Based on an order-theoretic approach, we derive sufficient conditions for the existence, characterization, and computation of Markovian equilibrium decision processes and stationary Markov equilibrium on minimal state spaces for a large class of stochastic overlapping generations models. In contrast to all previous work, we consider reduced-form stochastic production technologies that allow for a broad set of equilibrium distortions such as public policy distortions, social security, monetary equilibrium, and production nonconvexities. Our order-based methods are constructive, and we provide monotone iterative algorithms for computing extremal stationary Markov equilibrium decision processes and equilibrium invariant distributions, while avoiding many of the problems associated with the existence of indeterminacies that have been well-documented in previous work. We provide important results for existence of Markov equilibria for the case where capital income is not increasing in the aggregate stock. Finally, we conclude with examples common in macroeconomics such as models with fiat money and social security. We also show how some of our results extend to settings with unbounded state spaces.

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This paper provides new sufficient conditions for the existence, computation via successive approximations, and stability of Markovian equilibrium decision processes for a large class of OLG models with stochastic nonclassical production. Our notion of stability is existence of stationary Markovian equilibrium. With a nonclassical production, our economies encompass a large class of OLG models with public policy, valued fiat money, production externalities, and Markov shocks to production. Our approach combines aspects of both topological and order theoretic fixed point theory, and provides the basis of globally stable numerical iteration procedures for computing extremal Markovian equilibrium objects. In addition to new theoretical results on existence and computation, we provide some monotone comparative statics results on the space of economies.

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In this survey, we examine the operations of innovation processes within industrial districts by exploring the ways in which differentiation, specialization, and integration affect the generation, diffusion, and use of new knowledge in such districts. We begin with an analysis of the importance of the division of labor and then investigate the effects of social embeddedness on innovation. We also consider the effect of forms of organization within industrial districts at various stages of product and process life, and we examine the negative aspects of embeddedness for innovation. We conclude with a discussion of the possible consequences of new information and communications technologies on innovation in industrial districts.

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Radiotherapy has been a method of choice in cancer treatment for a number of years. Mathematical modeling is an important tool in studying the survival behavior of any cell as well as its radiosensitivity. One particular cell under investigation is the normal T-cell, the radiosensitivity of which may be indicative to the patient's tolerance to radiation doses.^ The model derived is a compound branching process with a random initial population of T-cells that is assumed to have compound distribution. T-cells in any generation are assumed to double or die at random lengths of time. This population is assumed to undergo a random number of generations within a period of time. The model is then used to obtain an estimate for the survival probability of T-cells for the data under investigation. This estimate is derived iteratively by applying the likelihood principle. Further assessment of the validity of the model is performed by simulating a number of subjects under this model.^ This study shows that there is a great deal of variation in T-cells survival from one individual to another. These variations can be observed under normal conditions as well as under radiotherapy. The findings are in agreement with a recent study and show that genetic diversity plays a role in determining the survival of T-cells. ^

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The episodic occurrence of debris flow events in response to stochastic precipitation and wildfire events makes hazard prediction challenging. Previous work has shown that frequency-magnitude distributions of non-fire-related debris flows follow a power law, but less is known about the distribution of post-fire debris flows. As a first step in parameterizing hazard models, we use frequency-magnitude distributions and cumulative distribution functions to compare volumes of post-fire debris flows to non-fire-related debris flows. Due to the large number of events required to parameterize frequency-magnitude distributions, and the relatively small number of post-fire event magnitudes recorded in the literature, we collected data on 73 recent post-fire events in the field. The resulting catalog of 988 debris flow events is presented as an appendix to this article. We found that the empirical cumulative distribution function of post-fire debris flow volumes is composed of smaller events than that of non-fire-related debris flows. In addition, the slope of the frequency-magnitude distribution of post-fire debris flows is steeper than that of non-fire-related debris flows, evidence that differences in the post-fire environment tend to produce a higher proportion of small events. We propose two possible explanations: 1) post-fire events occur on shorter return intervals than debris flows in similar basins that do not experience fire, causing their distribution to shift toward smaller events due to limitations in sediment supply, or 2) fire causes changes in resisting and driving forces on a package of sediment, such that a smaller perturbation of the system is required in order for a debris flow to occur, resulting in smaller event volumes.

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Hydrology is the study of the properties, distribution and effects of water on the Earth?s soil, rocks and atmosphere. It also encompasses the study of the hydrologic cycle of precipitation, runoff, infiltration, storage, and evaporation, including the physical, biological and chemical reaction of water with the earth and its relation to life?.

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Laser Shock Processing is developing as a key technology for the improvement of surface mechanical and corrosion resistance properties of metals due to its ability to introduce intense compressive residual stresses fields into high elastic limit materials by means of an intense laser driven shock wave generated by laser with intensities exceeding the 109 W/cm2 threshold, pulse energies in the range of 1 Joule and interaction times in the range of several ns. However, because of the relatively difficult-to-describe physics of shock wave formation in plasma following laser-matter interaction in solid state, only limited knowledge is available in the way of full comprehension and predictive assessment of the characteristic physical processes and material transformations with a specific consideration of real material properties. In the present paper, an account of the physical issues dominating the development of LSP processes from a moderately high intensity laser-matter interaction point of view is presented along with the theoretical and computational methods developed by the authors for their predictive assessment and new experimental contrast results obtained at laboratory scale.

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There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

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Linked Data is the key paradigm of the Semantic Web, a new generation of the World Wide Web that promises to bring meaning (semantics) to data. A large number of both public and private organizations have published their data following the Linked Data principles, or have done so with data from other organizations. To this extent, since the generation and publication of Linked Data are intensive engineering processes that require high attention in order to achieve high quality, and since experience has shown that existing general guidelines are not always sufficient to be applied to every domain, this paper presents a set of guidelines for generating and publishing Linked Data in the context of energy consumption in buildings (one aspect of Building Information Models). These guidelines offer a comprehensive description of the tasks to perform, including a list of steps, tools that help in achieving the task, various alternatives for performing the task, and best practices and recommendations. Furthermore, this paper presents a complete example on the generation and publication of Linked Data about energy consumption in buildings, following the presented guidelines, in which the energy consumption data of council sites (e.g., buildings and lights) belonging to the Leeds City Council jurisdiction have been generated and published as Linked Data.

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El sector energético, en España en particular, y de forma similar en los principales países de Europa, cuenta con una significativa sobrecapacidad de generación, debido al rápido y significativo crecimiento de las energías renovables en los últimos diez años y la reducción de la demanda energética, como consecuencia de la crisis económica. Esta situación ha hecho que las centrales térmicas de generación de electricidad, y en concreto los ciclos combinados de gas, operen con un factor de utilización extremadamente bajo, del orden del 10%. Además de la reducción de ingresos, esto supone para las plantas trabajar continuamente fuera del punto de diseño, provocando una significativa pérdida de rendimiento y mayores costes de explotación. En este escenario, cualquier contribución que ayude a mejorar la eficiencia y la condición de los equipos, es positivamente considerada. La gestión de activos está ganando relevancia como un proceso multidisciplinar e integrado, tal y como refleja la reciente publicación de las normas ISO 55000:2014. Como proceso global e integrado, la gestión de activos requiere el manejo de diversos procesos y grandes volúmenes de información, incluso en tiempo real. Para ello es necesario utilizar tecnologías de la información y aplicaciones de software. Esta tesis desarrolla un concepto integrado de gestión de activos (Integrated Plant Management – IPM) aplicado a centrales de ciclo combinado y una metodología para estimar el beneficio aportado por el mismo. Debido a las incertidumbres asociadas a la estimación del beneficio, se ha optado por un análisis probabilístico coste-beneficio. Así mismo, el análisis cuantitativo se ha completado con una validación cualitativa del beneficio aportado por las tecnologías incorporadas al concepto de gestión integrada de activos, mediante una entrevista realizada a expertos del sector de generación de energía. Los resultados del análisis coste-beneficio son positivos, incluso en el desfavorable escenario con un factor de utilización de sólo el 10% y muy prometedores para factores de utilización por encima del 30%. ABSTRACT The energy sector particularly in Spain, and in a similar way in Europe, has a significant overcapacity due to the big growth of the renewable energies in the last ten years, and it is seriously affected by the demand decrease due to the economic crisis. That situation has forced the thermal plants and in particular, the combined cycles to operate with extremely low annual average capacity factors, very close to 10%. Apart from the incomes reduction, working in out-of-design conditions, means getting a worse performance and higher costs than expected. In this scenario, anything that can be done to improve the efficiency and the equipment condition is positively received. Asset Management, as a multidisciplinary and integrated process, is gaining prominence, reflected in the recent publication of the ISO 55000 series in 2014. Dealing Asset Management as a global, integrated process needs to manage several processes and significant volumes of information, also in real time, that requires information technologies and software applications to support it. This thesis proposes an integrated asset management concept (Integrated Plant Management-IPM) applied to combined cycle power plants and develops a methodology to assess the benefit that it can provide. Due to the difficulties in getting deterministic benefit estimation, a statistical approach has been adopted for the cot-benefit analysis. As well, the quantitative analysis has been completed with a qualitative validation of the technologies included in the IPM and their contribution to key power plant challenges by power generation sector experts. The cost- benefit analysis provides positive results even in the negative scenario of annual average capacity factor close to 10% and is promising for capacity factors over 30%.