943 resultados para Discreet Element Modelling


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The identification of compositional changes in fumarolic gases of active and quiescent volcanoes is one of the mostimportant targets in monitoring programs. From a general point of view, many systematic (often cyclic) and randomprocesses control the chemistry of gas discharges, making difficult to produce a convincing mathematical-statisticalmodelling.Changes in the chemical composition of volcanic gases sampled at Vulcano Island (Aeolian Arc, Sicily, Italy) fromeight different fumaroles located in the northern sector of the summit crater (La Fossa) have been analysed byconsidering their dependence from time in the period 2000-2007. Each intermediate chemical composition has beenconsidered as potentially derived from the contribution of the two temporal extremes represented by the 2000 and 2007samples, respectively, by using inverse modelling methodologies for compositional data. Data pertaining to fumarolesF5 and F27, located on the rim and in the inner part of La Fossa crater, respectively, have been used to achieve theproposed aim. The statistical approach has allowed us to highlight the presence of random and not random fluctuations,features useful to understand how the volcanic system works, opening new perspectives in sampling strategies and inthe evaluation of the natural risk related to a quiescent volcano

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We present the study of the geochemical processes associated with the first successful remediation of a marine shore tailings deposit in a coastal desert environment (Bahia de Ite, in the Atacama Desert of Peru). The remediation approach implemented a wetland on top of the oxidized tailings. The site is characterized by a high hydrauliz gradient produced by agricultural irrigation on upstream gravel terraces that pushed river water (similar to 500 mg/L SO(4)) toward the sea and through the tailings deposit. The geochemical and isotopic (delta(2)H(water) and delta(18)O(water), delta(34)S(sulfate) , delta(18)O(sulfate)) approach applied here revealed that evaporite horizons (anhydrite and halite) in the gravel terraces are the source of increased concentrations of SO(4), Cl, and Na up to similar to 1500 mg/L in the springs at the base of the gravel terraces. Deeper groundwater interacting with underlying marine sequences increased the concentrations of SO(4), Cl, and Na up to 6000 mg/L and increased the alkalinity up to 923 mg/L CaCO(3) eq. in the coastal aquifer. These waters infiltrated into the tailings deposit at the shelf-tailings interface. Nonremediated tailings had a low-pH oxidation zone (pH 1-4) with significant accumulations of efflorescent salts (10-20 cm thick) at the surface because of upward capillary transport of metal cations in the arid climate. Remediated tailings were characterized by neutral pH and reducing conditions (pH similar to 7, Eh similar to 100 mV). As a result, most bivalent metals such as Cu, Zn, and Ni had very low concentrations (around 0.01 mg/L or below detection limit) because of reduction and sorption processes. In contrast, these reducing conditions increased the mobility of iron from two sources in this system: (1) The originally Fe(III)-rich oxidation zone, where Fe(II) was reduced during the remediation process and formed an Fe(II) plume, and (2) reductive dissolution of Fe(III) oxides present in the original shelf lithology formed an Fe-Mn plume at 10-m depth. These two Fe-rich plumes were pushed toward the shoreline where more oxidizing and higher pH conditions triggered the precipitation of Fe(HI)hydroxide coatings on silicates. These coatings acted as a filter for the arsenic, which naturally infiltrated with the river water (similar to 500 mu g/L As natural background) into the tailings deposit.

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A four compartment model of the cardiovascular system is developed. To allow for easy interpretation and to minimise the number of parameters, an effort was made to keep the model as simple as possible. A sensitivity analysis is first carried out to determine which are the most important model parameters to characterise the blood pressure signal. A four stage process is then described which accurately determines all parameter values. This process is applied to data from three patients and good agreement is shown in all cases.

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One of the world's largest wollastonite deposits was formed at the contact of the northern Hunter Mountain Batholith (California, USA) in Paleozoic sediments. Wollastonite occurs as zones of variable thickness surrounding layers or nodules of quartzite in limestones. A minimum formation temperature of 650 degrees C is estimated from isolated periclase-bearing lenses in that area. Contact metamorphism of siliceous carbonates has produced mineral assemblages that are consistent with heterogeneous, and partly limited infiltration of water-rich fluids, compatible with O-18/O-16 and C-13/C-12 isotopic patterns recorded in carbonates. Oxygen isotope compositions of wollastonites in the study area may also not require infiltration of large quantities of externally-derived fluids that were out of equilibrium with the rocks. 8180 values of wollastonite are high (14.8 parts per thousand to 25.0 parts per thousand; median: 19.7 parts per thousand) and close to those of the host limestone (19.7 parts per thousand to 28 parts per thousand; median: 24.9 parts per thousand) and quartz (18.0 parts per thousand. to 29.1 parts per thousand; median: 22.6 parts per thousand). Isotopic disequilibrium exists at quartz/wollastonite and wollastonite/calcite boundaries. Therefore, classical batch/Rayleigh fractionation models based on reactant and product equilibrium are not applicable to the wollastonite rims. An approach that relies on local instantaneous mass balance for the reactants, based on the wollastonite-forming reaction is suggested as an alternative way to model wollastonite reaction rims. This model reproduces many of the measured delta O-18 values of wollastonite reaction rims of the current study to within +/- 1 parts per thousand, even though the wollastonite compositions vary by almost 10 parts per thousand. (C) 2011 Elsevier B.V. All rights reserved.

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Background: Excessive exposure to solar Ultra-Violet (UV) light is the main cause of most skin cancers in humans. Factors such as the increase of solar irradiation at ground level (anthropic pollution), the rise in standard of living (vacation in sunny areas), and (mostly) the development of outdoor activities have contributed to increase exposure. Thus, unsurprisingly, incidence of skin cancers has increased over the last decades more than that of any other cancer. Melanoma is the most lethal cutaneous cancer, while cutaneous carcinomas are the most common cancer type worldwide. UV exposure depends on environmental as well as individual factors related to activity. The influence of individual factors on exposure among building workers was investigated in a previous study. Posture and orientation were found to account for at least 38% of the total variance of relative individual exposure. A high variance of short-term exposure was observed between different body locations, indicating the occurrence of intense, subacute exposures. It was also found that effective short-term exposure ranged between 0 and 200% of ambient irradiation, suggesting that ambient irradiation is a poor predictor of effective exposure. Various dosimetric techniques enable to assess individual effective exposure, but dosimetric measurements remain tedious and tend to be situation-specific. As a matter of facts, individual factors (exposure time, body posture and orientation in the sun) often limit the extrapolation of exposure results to similar activities conducted in other conditions. Objective: The research presented in this paper aims at developing and validating a predictive tool of effective individual exposure to solar UV. Methods: Existing computer graphic techniques (3D rendering) were adapted to reflect solar exposure conditions and calculate short-term anatomical doses. A numerical model, represented as a 3D triangular mesh, is used to represent the exposed body. The amount of solar energy received by each "triangle is calculated, taking into account irradiation intensity, incidence angle and possible shadowing from other body parts. The model take into account the three components of the solar irradiation (direct, diffuse and albedo) as well as the orientation and posture of the body. Field measurements were carried out using a forensic mannequin at the Payerne MeteoSwiss station. Short-term dosimetric measurements were performed in 7 anatomical locations for 5 body postures. Field results were compared to the model prediction obtained from the numerical model. Results: The best match between prediction and measurements was obtained for upper body parts such as shoulders (Ratio Modelled/Measured; Mean = 1.21, SD = 0.34) and neck (Mean = 0.81, SD = 0.32). Small curved body parts such as forehead (Mean = 6.48, SD = 9.61) exhibited a lower matching. The prediction is less accurate for complex postures such as kneeling (Mean = 4.13, SD = 8.38) compared to standing up (Mean = 0.85, SD = 0.48). The values obtained from the dosimeters and the ones computed from the model are globally consistent. Conclusion: Although further development and validation are required, these results suggest that effective exposure could be predicted for a given activity (work or leisure) in various ambient irradiation conditions. Using a generic modelling approach is of high interest in terms of implementation costs as well as predictive and retrospective capabilities.

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Nessie is an Autonomous Underwater Vehicle (AUV) created by a team of students in the Heriot Watt University to compete in the Student Autonomous Underwater Competition, Europe (SAUC-E) in August 2006. The main objective of the project is to find the dynamic equation of the robot, dynamic model. With it, the behaviour of the robot will be easier to understand and movement tests will be available by computer without the need of the robot, what is a way to save time, batteries, money and the robot from water inside itself. The object of the second part in this project is setting a control system for Nessie by using the model

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Silencing of the transcriptional repressor REST is required for terminal differentiation of neuronal and beta-cells. In this study, we hypothesized that REST expression is controlled by hairy and enhancer of split 1 (HES-1), a transcriptional repressor that plays an important role in brain and pancreas development. We identified several N elements (CTNGTG) within the promoter of REST and confirmed that HES-1 associates with the endogenous promoter of REST. Moreover, using a cells model that overexpress HES-1 and a combination of experimental approaches, we demonstrated that HES-1 reduces endogenous REST expression. Taken together, these results indicate that HES-1 is an upstream negative regulator of REST expression.

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The terminal differentiation of neuronal and pancreatic beta-cells requires the specific expression of genes that are targets of an important transcriptional repressor named RE-1 silencing transcription factor (REST). The molecular mechanism by which these REST target genes are expressed only in neuronal and beta-cells and are repressed by REST in other tissues is a central issue in differentiation program of neuronal and beta-cells. Herein, we showed that the transcriptional factor Sp1 was required for expression of most REST target genes both in insulin-secreting cells and neuronal-like cells where REST is absent. Inhibition of REST in a non-beta and a non-neuronal cell model restored the transcriptional activity of Sp1. This activity was also restored by trichostatin A indicating the requirement of histone deacetylases for the REST-mediated silencing of Sp1. Conversely, exogenous introduction of REST blocked Sp1-mediated transcriptional activity. The REST inhibitory effect was mediated through its C-terminal repressor domain, which could interact with Sp1. Taken together, these data show that the inhibition of Sp1 by REST is required for the silencing of its target genes expression in non-neuronal and in non-beta-cells. We conclude that the interplay between REST and Sp1 determines the cell-specific expression of REST target genes.

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Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

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[1] We present new analytical data of major and trace elements for the geological MPI-DING glasses KL2-G, ML3B-G, StHs6/80-G, GOR128-G, GOR132-G, BM90/21-G, T1-G, and ATHO-G. Different analytical methods were used to obtain a large spectrum of major and trace element data, in particular, EPMA, SIMS, LA-ICPMS, and isotope dilution by TIMS and ICPMS. Altogether, more than 60 qualified geochemical laboratories worldwide contributed to the analyses, allowing us to present new reference and information values and their uncertainties ( at 95% confidence level) for up to 74 elements. We complied with the recommendations for the certification of geological reference materials by the International Association of Geoanalysts (IAG). The reference values were derived from the results of 16 independent techniques, including definitive ( isotope dilution) and comparative bulk ( e. g., INAA, ICPMS, SSMS) and microanalytical ( e. g., LA-ICPMS, SIMS, EPMA) methods. Agreement between two or more independent methods and the use of definitive methods provided traceability to the fullest extent possible. We also present new and recently published data for the isotopic compositions of H, B, Li, O, Ca, Sr, Nd, Hf, and Pb. The results were mainly obtained by high-precision bulk techniques, such as TIMS and MC-ICPMS. In addition, LA-ICPMS and SIMS isotope data of B, Li, and Pb are presented.