The reduction of systematic errors is a continuing challenge for model development. Feedbacks and compensating errors in climate models often make finding the source of a systematic error difficult. In this paper, it is shown how model development can benefit from the use of the same model across a range of temporal and spatial scales. Two particular systematic errors are examined: tropical circulation and precipitation distribution, and summer land surface temperature and moisture biases over Northern Hemisphere continental regions. Each of these errors affects the model performance on time scales ranging from a few days to several decades. In both cases, the characteristics of the long-time-scale errors are found to develop during the first few days of simulation, before any large-scale feedbacks have taken place. The ability to compare the model diagnostics from the first few days of a forecast, initialized from a realistic atmospheric state, directly with observations has allowed physical deficiencies in the physical parameterizations to be identified that, when corrected, lead to improvements across the full range of time scales. This study highlights the benefits of a seamless prediction system across a wide range of time scales.
Quantitative two-dimensional dopant profiling of a gatelike structure is achieved by scanning capacitance microscopy (SCM). A processed silicon wafer is sectioned then polished such that a cross section is made through a gatelike structure. This structure consists of two n+ doped regions separated by a lighter doped n region. The two-dimensional SCM data are converted to dopant density through a physical model of the SCM–silicon interaction. Improvements to the physical model and SCM data to dopant profile algorithm are discussed. Advances in sample preparation are described. Adjustment of the conversion model parameters allows for fitting of the SCM dopant profile to a vertical secondary-ion-mass-spectroscopy profile. The accuracy of this fit is better than 20%. This fit also gives strong evidence that the full two-dimensional profile is truly quantitative.
Oncolytic adenoviruses (Ad) have been developed for the eradication of tumors. Although they hold much promise as a cancer therapy, they have a short blood circulation time and high liver toxicity. An effective strategy to overcome these problems has been complexing Ad with shielding materials. However, the therapeutic efficacy of the Ad complexes has also been an issue because passive accumulation does not allow for sufficient delivery of Ad to the cancer cells. To enhance the therapeutic efficacy of the polymer-coated Ads, the attachment of a targeting moiety to polymer-coated Ad vectors is inescapable. Our lab has previously reported the potential use of Arg-Gly-Asp (RGD)-targeted bioreducible polymers with a polyethylene glycol (PEG) linker for delivering oncolytic Ads. We have shown the enhanced in vitro transduction efficiency and increased cancer-killing effect with producing progeny oncolytic Ad particles. In addition, we have shown significant tumor-growth inhibition of the polymer-shielded Ad in an in vivo lung orthotopic tumor model. The shielding effect of the Ad surface with the polymers allowed evasion of host immune responses and reduction of liver toxicity. This data demonstrates that the RGD-conjugated bioreducible polymer for delivering the oncolytic Ad vectors could be utilized for cancer therapy via systemic administration.
SUMMARYThe material point method (MPM) developed by Sulsky and colleagues is currently being used to solve many challenging problems involving large deformations and/or fragementations with some success. In order to understand the properties of this method, an analysis of the considerable computational properties of MPM is undertaken in the context of model problems from gas dynamics. The MPM method in the form used here is shown both theoretically and computationally to have first-order accuracy for a standard gas dynamics test problem.
Articles you may be interested inLimitations of the calibration curve method for determining dopant profiles from scanning capacitance microscope measurements Two dimensional dopant and carrier profiles obtained by scanning capacitance microscopy on an actively biased cross-sectioned metal-oxide-semiconductor field-effect transistor Quantitative two-dimensional ͑2D͒ dopant profiling of a gatelike structure is achieved by scanning capacitance microscopy ͑SCM͒ on a cross-sectioned polished silicon wafer. The gatelike structures consist of heavily implanted nϩ regions separated by a lighter doped n region underneath a 0.56 m gate. The SCM is operated in the constant change capacitance mode while scanning with a 37 nm radius tip. The 2D SCM data are converted to dopant density through a physical model of the SCM/silicon interaction. The model parameters are adjusted so that the SCM dopant profile far from the gate edge fits the vertical secondary ion mass spectrometry ͑SIMS͒ profile. A 15% error in average accuracy is found between SCM and SIMS profiles evaluated over the dopant range of 10 20 -10 17 cm Ϫ3 . The same model parameters are used for all points in converting the 2D SCM data, indicating that the accuracy of the full 2D result should be comparable to that of the vertical profile. A direct comparison of the 2D SCM and 2D TSUPREM4 results is made for the first time. The agreement is generally good, but there are some notable differences.
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