914 resultados para Multi-phase Modelling
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Une nouvelle méthode d'extraction en phase solide (SPE) couplée à une technique d'analyse ultrarapide a été développée pour la détermination simultanée de neuf contaminants émergents (l'atrazine, le déséthylatrazine, le 17(béta)-estradiol, l'éthynylestradiol, la noréthindrone, la caféine, la carbamazépine, le diclofénac et le sulfaméthoxazole) provenant de différentes classes thérapeutiques et présents dans les eaux usées. La pré-concentration et la purification des échantillons a été réalisée avec une cartouche SPE en mode mixte (Strata ABW) ayant à la fois des propriétés échangeuses de cations et d'anions suivie d'une analyse par une désorption thermique par diode laser/ionisation chimique à pression atmosphérique couplée à la spectrométrie de masse en tandem (LDTD-APCI-MS/MS). La LDTD est une nouvelle méthode d'introduction d'échantillon qui réduit le temps total d'analyse à moins de 15 secondes par rapport à plusieurs minutes avec la chromatographie liquide couplée à la spectrométrie de masse en tandem traditionnelle (LC-MS/MS). Plusieurs paramètres SPE ont été évalués dans le but d'optimiser l'efficacité de récupération lors de l'extraction des analytes provenant des eaux usées, tels que la nature de la phase stationnaire, le débit de chargement, le pH d'extraction, le volume et la composition de la solution de lavage et le volume de l'échantillon initial. Cette nouvelle méthode a été appliquée avec succès à de vrais échantillons d'eaux usées provenant d'un réservoir de décantation primaire. Le recouvrement des composés ciblés provenant des eaux usées a été de 78 à 106%, la limite de détection a été de 30 à 122 ng L-1, alors que la limite de quantification a été de 88 à 370 ng L-1. Les courbes d'étalonnage dans les matrices d'eaux usées ont montré une bonne linéarité (R2 > 0,991) pour les analytes cibles ainsi qu’une précision avec un coefficient de variance inférieure à 15%.
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Department of Statistics, Cochin University of Science and Technology
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Multi-component reactions are effective in building complex molecules in a single step in a minimum amount of time and with facile isolation procedures; they have high economy1–7 and thus have become a powerful synthetic strategy in recent years.8–10 The multicomponent protocols are even more attractive when carried out in aqueous medium. Water offers several benefits, including control over exothermicity, and the isolation of products can be carried out by single phase separation technique. Pyranopyrazoles are a biologically important class of heterocyclic compounds and in particular dihydropyrano[2,3-c]pyrazoles play an essential role in promoting biological activity and represent an interesting template in medicinal chemistry. Heterocyclic compounds bearing the 4-H pyran unit have received much attention in recent years as they constitute important precursors for promising drugs.11–13 Pyrano[2,3-c]pyrazoles exhibit analgesic,14 anti-cancer,15 anti-microbial and anti-inflammatory16 activity. Furthermore dihydropyrano[2,3-c]pyrazoles show molluscidal activity17,18 and are used in a screening kit for Chk 1 kinase inhibitor activity.19,20 They also find applications as pharmaceutical ingredients and bio-degradable agrochemicals.21–29 Junek and Aigner30 first reported the synthesis of pyrano[2,3-c]pyrazole derivatives from 3-methyl-1-phenylpyrazolin-5-one and tetracyanoethylene in the presence of triethylamine. Subsequently, a number of synthetic approaches such as the use of triethylamine,31 piperazine,32 piperidine,33 N-methylmorpholine in ethanol,34 microwave irradiation,35,36 solvent-free conditions,37–39 cyclodextrins (CDs),40 different bases in water,41 γ -alumina,42 and l-proline43 have been reported for the synthesis of 6-amino-4-alkyl/aryl-3-methyl- 2,4-dihydropyrano[2,3-c]pyrazole-5-carbonitriles. Recently, tetraethylammonium bromide (TEABr) has emerged as mild, water-tolerant, eco-friendly and inexpensive catalyst. To the best of our knowledge, quaternary ammonium salts, more specifically TEABr, have notbeen used as catalysts for the synthesis of pyrano[2,3-c]pyrazoles, and we decided to investigate the application of TEABr as a catalyst for the synthesis of a series of pyrazole-fused pyran derivatives via multi-component reactions
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Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.
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Context-aware multimodal interactive systems aim to adapt to the needs and behavioural patterns of users and offer a way forward for enhancing the efficacy and quality of experience (QoE) in human-computer interaction. The various modalities that constribute to such systems each provide a specific uni-modal response that is integratively presented as a multi-modal interface capable of interpretation of multi-modal user input and appropriately responding to it through dynamically adapted multi-modal interactive flow management , This paper presents an initial background study in the context of the first phase of a PhD research programme in the area of optimisation of data fusion techniques to serve multimodal interactivite systems, their applications and requirements.
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A multi-scale framework for decision support is presented that uses a combination of experiments, models, communication, education and decision support tools to arrive at a realistic strategy to minimise diffuse pollution. Effective partnerships between researchers and stakeholders play a key part in successful implementation of this strategy. The Decision Support Matrix (DSM) is introduced as a set of visualisations that can be used at all scales, both to inform decision making and as a communication tool in stakeholder workshops. A demonstration farm is presented and one of its fields is taken as a case study. Hydrological and nutrient flow path models are used for event based simulation (TOPCAT), catchment scale modelling (INCA) and field scale flow visualisation (TopManage). One of the DSMs; The Phosphorus Export Risk Matrix (PERM) is discussed in detail. The PERM was developed iteratively as a point of discussion in stakeholder workshops, as a decision support and education tool. The resulting interactive PERM contains a set of questions and proposed remediation measures that reflect both expert and local knowledge. Education and visualisation tools such as GIS, risk indicators, TopManage and the PERM are found to be invaluable in communicating improved farming practice to stakeholders. (C) 2008 Elsevier Ltd. All rights reserved.
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Fine sediment delivery to and storage in stream channel reaches can disrupt aquatic habitats, impact river hydromorphology, and transfer adsorbed nutrients and pollutants from catchment slopes to the fluvial system. This paper presents a modelling toot for simulating the time-dependent response of the fine sediment system in catchments, using an integrated approach that incorporates both land phase and in-stream processes of sediment generation, storage and transfer. The performance of the model is demonstrated by applying it to simulate in-stream suspended sediment concentrations in two lowland catchments in southern England, the Enborne and the Lambourn, which exhibit contrasting hydrological and sediment responses due to differences in substrate permeability. The sediment model performs well in the Enborne catchment, where direct runoff events are frequent and peak suspended sediment concentrations can exceed 600 mg l(-1). The general trends in the in-stream concentrations in the Lambourn catchment are also reproduced by the model, although the observed concentrations are low (rarely exceeding 50 mg l(-1)) and the background variability in the concentrations is not fully characterized by the model. Direct runoff events are rare in this highly permeable catchment, resulting in a weak coupling between the sediment delivery system and the catchment hydrology. The generic performance of the model is also assessed using a generalized sensitivity analysis based on the parameter bounds identified in the catchment applications. Results indicate that the hydrological parameters contributing to the sediment response include those controlling (1) the partitioning of runoff between surface and soil zone flows and (2) the fractional loss of direct runoff volume prior to channel delivery. The principal sediment processes controlling model behaviour in the simulations are the transport capacity of direct runoff and the in-stream generation, storage and release of the fine sediment fraction. The in-stream processes appear to be important in maintaining the suspended sediment concentrations during low flows in the River Enborne and throughout much of the year in the River Lambourn. Copyright (c) 2007 John Wiley & Sons, Ltd.
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A new model, RothPC-1, is described for the turnover of organic C in the top metre of soil. RothPC-1 is a version of RothC-26.3, an earlier model for the turnover of C in topsoils. In RothPC-1 two extra parameters are used to model turnover in the top metre of soil: one, p, which moves organic C down the profile by an advective process, and the other, s, which slows decomposition with depth. RothPC-1 is parameterized and tested using measurements (described in Part 1, this issue) of total organic C and radiocarbon on soil profiles from the Rothamsted long-term field experiments, collected over a period of more than 100 years. RothPC-1 gives fits to measurements of organic C and radiocarbon in the 0-23, 23-46, 46-69 and 69-92 cm layers of soil that are almost all within (or close to) measurement error in two areas of regenerating woodland (Geescroft and Broadbalk Wildernesses) and an area of cultivated land from the Broadbalk Continuous Wheat Experiment. The fits to old grassland (the Park Grass Experiment) are less close. Two other sites that provide the requisite pre- and post-bomb data are also fitted; a prairie Chernozem from Russia and an annual grassland from California. Roth-PC-1 gives a close fit to measurements of organic C and radiocarbon down the Chernozem profile, provided that allowance is made for soil age; with the annual grassland the fit is acceptable in the upper part of the profile, but not in the clay-rich Bt horizon below. Calculations suggest that treating the top metre of soil as a homogeneous unit will greatly overestimate the effects of global warming in accelerating the decomposition of soil C and hence on the enhanced release of CO2 from soil organic matter; more realistic estimates will be obtained from multi-layer models such as RothPC-1.
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This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5-10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970-1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061 +/- 0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models' inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.
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Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.
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Northern hemisphere snow water equivalent (SWE) distribution from remote sensing (SSM/I), the ERA40 reanalysis product and the HadCM3 general circulation model are compared. Large differences are seen in the February climatologies, particularly over Siberia. The SSM/I retrieval algorithm may be overestimating SWE in this region, while comparison with independent runoff estimates suggest that HadCM3 is underestimating SWE. Treatment of snow grain size and vegetation parameterizations are concerns with the remotely sensed data. For this reason, ERA40 is used as `truth' for the following experiments. Despite the climatology differences, HadCM3 is able to reproduce the distribution of ERA40 SWE anomalies when assimilating ERA40 anomaly fields of temperature, sea level pressure, atmospheric winds and ocean temperature and salinity. However when forecasts are released from these assimilated initial states, the SWE anomaly distribution diverges rapidly from that of ERA40. No predictability is seen from one season to another. Strong links between European SWE distribution and the North Atlantic Oscillation (NAO) are seen, but forecasts of this index by the assimilation scheme are poor. Longer term relationships between SWE and the NAO, and SWE and the El Ni\~no-Southern Oscillation (ENSO) are also investigated in a multi-century run of HadCM3. SWE is impacted by ENSO in the Himalayas and North America, while the NAO affects SWE in North America and Europe. While significant connections with the NAO index were only present in DJF (and to an extent SON), the link between ENSO and February SWE distribution was seen to exist from the previous JJA ENSO index onwards. This represents a long lead time for SWE prediction for hydrological applications such as flood and wildfire forecasting. Further work is required to develop reliable large scale observation-based SWE datasets with which to test these model-derived connections.
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To construct Biodiversity richness maps from Environmental Niche Models (ENMs) of thousands of species is time consuming. A separate species occurrence data pre-processing phase enables the experimenter to control test AUC score variance due to species dataset size. Besides, removing duplicate occurrences and points with missing environmental data, we discuss the need for coordinate precision, wide dispersion, temporal and synonymity filters. After species data filtering, the final task of a pre-processing phase should be the automatic generation of species occurrence datasets which can then be directly ’plugged-in’ to the ENM. A software application capable of carrying out all these tasks will be a valuable time-saver particularly for large scale biodiversity studies.
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Recent coordinated observations of interplanetary scintillation (IPS) from the EISCAT, MERLIN, and STELab, and stereoscopic white-light imaging from the two heliospheric imagers (HIs) onboard the twin STEREO spacecraft are significant to continuously track the propagation and evolution of solar eruptions throughout interplanetary space. In order to obtain a better understanding of the observational signatures in these two remote-sensing techniques, the magnetohydrodynamics of the macro-scale interplanetary disturbance and the radio-wave scattering of the micro-scale electron-density fluctuation are coupled and investigated using a newly constructed multi-scale numerical model. This model is then applied to a case of an interplanetary shock propagation within the ecliptic plane. The shock could be nearly invisible to an HI, once entering the Thomson-scattering sphere of the HI. The asymmetry in the optical images between the western and eastern HIs suggests the shock propagation off the Sun–Earth line. Meanwhile, an IPS signal, strongly dependent on the local electron density, is insensitive to the density cavity far downstream of the shock front. When this cavity (or the shock nose) is cut through by an IPS ray-path, a single speed component at the flank (or the nose) of the shock can be recorded; when an IPS ray-path penetrates the sheath between the shock nose and this cavity, two speed components at the sheath and flank can be detected. Moreover, once a shock front touches an IPS ray-path, the derived position and speed at the irregularity source of this IPS signal, together with an assumption of a radial and constant propagation of the shock, can be used to estimate the later appearance of the shock front in the elongation of the HI field of view. The results of synthetic measurements from forward modelling are helpful in inferring the in-situ properties of coronal mass ejection from real observational data via an inverse approach.
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A model was devised to describe simultaneously the grain masses of water and dry matter against thermal time during grain filling and maturation of winter wheat. The model accounted for a linear increase in water mass of duration anthesis-m(1) (end of rapid water assimilation phase) and rate a, followed by a more stable water mass until in,, after which water mass declined rapidly at rate e. Grain dry matter was described as a linear increase of rate bgf until a maximum size (maxgf) was attained at m(2).The model was fitted to plot data from weekly samples of grains taken from replicated field experiments investigating effects of grain position (apical or medial), fungicide (five contrasting treatments), sowing date (early or late), cultivar (Malacca or Shamrock) and season (2001/2002 and 2002/2003) on grain filling. The model accounted for between 83 and 99% of the variation ( 2) when fitted to data from individual plots, and between 97 and 99% when fitted to treatment means. Endosperm cell number of grains from early-sown plots in the first season were also counted. Differences in maxgf between grain positions and also between cultivars were mostly the result of effects on bgf and were empirically associated with water mass at nil. Fungicide application controlled S. tritici and powdery mildew infection, delayed flag leaf senescence, increased water mass at m(1) (wm(1)), and also increased m(2), bgf and maxgf. Fungicide effects on water mass were detected before fungicide effects on dry matter, but comparison of the effects of individual fungicide treatments showed no evidence that effects on wm(1), nor on endosperm cell numbers at about m(1), were required for fungicide effects on maxgf, (c) 2005 Elsevier B.V. All rights reserved.
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The aim of a phase H clinical trial is to decide whether or not to develop an experimental therapy further through phase III clinical evaluation. In this paper, we present a Bayesian approach to the phase H trial, although we assume that subsequent phase III clinical trials will hat,e standard frequentist analyses. The decision whether to conduct the phase III trial is based on the posterior predictive probability of a significant result being obtained. This fusion of Bayesian and frequentist techniques accepts the current paradigm for expressing objective evidence of therapeutic value, while optimizing the form of the phase II investigation that leads to it. By using prior information, we can assess whether a phase II study is needed at all, and how much or what sort of evidence is required. The proposed approach is illustrated by the design of a phase II clinical trial of a multi-drug resistance modulator used in combination with standard chemotherapy in the treatment of metastatic breast cancer. Copyright (c) 2005 John Wiley & Sons, Ltd.