999 resultados para geospatial modeling


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A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

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By manipulation of applied pressure or voltage, pressurized flow capillary electrochromatography (P-CEC) permits unique control of selectivity for ionic solutes. A simple mathematical model has been developed to describe the quantitative relationship between the electrochromatographic retention factor (k(*)) of charged solutes and the applied voltage and pressure. The validity of the model was verified experimentally with hydrophilic interaction mode CEC (HI-CEC). On the basis of the model developed, it was found that the value of k(*) could be predicted accurately using only a limited number of data points from the initial experiments at different voltages or pressures. Correlation between the experimentally measured and calculated k(*) was excellent, with a correlation coefficient greater than 0.999. Optimization for the separation of peptides by P-CEC was also performed successfully on the basis of the proposed model.

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A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

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Temporal trends in total ozone for the St. Lawrence estuary were estimated from ground-based measurements at the NOAA/CMDL station in Caribou, Maine. Linear regression analysis showed that from 1979 to 1999 total ozone has decreased by about 3.3% per decade on an annual basis and ≤6.2% per decade on a monthly basis relative to unperturbed (pre-CFC) levels. The influence of increased ultraviolet-B (280–320 nm) radiation associated with ozone depletion on water column photochemical processes was evaluated by modeling the photobleaching of chromophoric dissolved organic material (CDOM). Linear regression analysis showed small (<0.5% per decade), but statistically significant upward trends in maximum noontime photobleaching rates. Most notably, positive trends in relative rates for May, June, and July, when maximum absolute rates are expected, were predicted. A global model based on TOMS ozone data revealed increases in photobleaching of ≤3% per decade at high latitudes in the Southern Hemisphere. Radiation amplification factors for increases in photochemically weighted UV (280–400 nm) in response to ozone depletion were estimated at 0.1 and 0.08 for photobleaching of CDOM absorbance at 300 and 350 nm, respectively. Application of the laboratory-based model to conditions that more closely resembled those in situ were variable with both overestimation and underestimation of measured rates. The differences between modeled rates and observed rates under quasi-natural conditions were as large or larger than the predicted increases due to ozone depletion. These comparisons suggest that biological activity and mixing play an important, but as yet ill-defined, role in modifying photochemical processes.

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We propose the exploding-reflector method to simulate a monostatic survey with a single simulation. The exploding reflector, used in seismic modeling, is adapted for ground-penetrating radar (GPR) modeling by using the analogy between acoustic and electromagnetic waves. The method can be used with ray tracing to obtain the location of the interfaces and estimate the properties of the medium on the basis of the traveltimes and reflection amplitudes. In particular, these can provide a better estimation of the conductivity and geometrical details. The modeling methodology is complemented with the use of the plane-wave method. The technique is illustrated with GPR data from an excavated tomb of the nineteenth century.

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Univ SE Calif, Ctr Syst & Software Engn, ABB, Microsoft Res, IEEE, ACMSIGSOFT, N Carolina State Univ Comp Sci

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Chinese Acad Sci, ISCAS Lab Internet Software Technologies

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National Science Fund for Distinguished Young Scholars of China [40225004]; National Natural Science Foundation of China [40471048]

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Funding and support for this project was provided by NSFC (Grant No. 40771015), and Key International Science and Technology Cooperation Projects (Grant No. 22007DFC20180). The authors also gratefully acknowledge the support of Key Projects in the National Science & Technology Pillar Program in the Eleventh Five-year Plan Period (Grant No. 2006BAD01B06-02). The authors thank the CDCs of Daqing, Beijing, Tianjin, Zhengzhou, Changsha and Shenzhen cities for field and laboratory technical support.

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The surface solar radiation (SSR) is of great importance to bio-chemical cycle and life activities. However, it is impossible to observe SSR directly over large areas especially for rugged surfaces such as the Qinghai-Tibet Plateau. This paper presented an improved parameterized model for predicting all-sky global solar radiation on rugged surfaces using Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric products and Digital Elevation Model (DEM). The global solar radiation was validated using 11 observations within the plateau. The correlation coefficients of daily data vary between 0.67-0.86, while those of the averages of 10-day data are between 0.79-0.97. The model indicates that the attenuation of SSR is mainly caused by cloud under cloudy sky, and terrain is an important factor influencing SSR over rugged surfaces under clear sky. A positive relationship can also be inferred between the SSR and slope. Compared with horizontal surfaces, the south-facing slope receives more radiation, followed by the west- and east-facing slopes with less SSR, and the SSR of the north-facing slope is the least.

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We model the electrical behavior of organic light-emitting diodes whose emissive multilayer is formed by blends of an electron transporting material, tris-(8-hydroxyquinoline) aluminum (Alq(3)) and a hole transporting material, N,N-'-diphenyl-N,N-'-bis(1,1(')-biphenyl)-4,4-diamine. The multilayer is composed of layers of different concentration. The Alq(3) concentration gradually decreases from the cathode to the anode. We demonstrate that these graded devices have higher efficiency and operate at lower applied voltages than devices whose emissive layer is made of nominally homogeneous blends. Our results show an important advantage of graded devices, namely, the low values of the recombination rate distribution near the cathode and the anode, so that electrode quenching is expected to be significantly suppressed in these devices.