Preparation, patterning and luminescence properties of rare earth-doped YVO4 nanocrystalline phosphor films via sol-gel soft lithography

In this presentation, nanocrystalline YVO4:A (A=Eu3+, Dy3+, SM3+, Er3+) phosphor films and their patterning were fabricated by a Pechini sol-gel process combined with a soft lithography (micro-molding in capillaries). XRD, FT-IR, AFM and optical microscope, absorption spectra, photoluminescence (PL) spectra as well as lifetimes were used to characterize the resulting films. The results of XRD indicated that the films began to crystallize at 400 degrees C and the crystallinity increased with the increase of annealing temperatures. Transparent nonpattemed phosphor films were uniform and crack free, which mainly consisted of grains with an average size of 90nm. Patterned crystalline phosphor film bands with different widths (5-30 mu m) were obtained. The doped rare earth ions (A) showed their characteristic emission in crystalline YVO4 phosphor films due to an efficient energy transfer from vanadate groups to them. The Sm3+ and Er3+ ions also showed upconversion luminescence in YVO4 film host. The optimum concentration for Eu3+ was determined to be 7 mol% and those for Dy3+, Sm3+, Er3+ were 2 Mol% of Y3+ in YVO4 films, respectively.

Double twist in helical polymer "soft" crystals

In natural and synthetic materials having non-racemic chiral centers, chirality and structural ordering each play a distinct role in the formation of ordered states. Configurational chirality can be extended to morphological chirality when the phase, structures possess low liquid crystalline order. In the crystalline states the crystallization process suppresses the chiral helical morphology due to strong ordering interactions, In this Letter, we report the first observation of helical single lamellar crystals of synthetic non-racemic chiral polymers. Experimental evidence shows that the molecular chains twist along both the long and short axes of the helical lamellar crystals, which is the first time a double-twist molecular orientation in a helical crystal has been observed.

Surface roughness characterization of soft x-ray multilayer films on the nanometer scale

The soft x-ray reflectivity of multilayer films is affected by the surface roughness on the transverse nanometer scale. Scanning tunneling microscopy (STM) is an ideal instrument for providing high-lateral-resolution roughness measurements for soft x-ray multilayer films that cannot be obtained with other types of instruments on the transverse nanometer scale. The surface roughnesses of Mo/Si, Mo/C, and W/Si soft x-ray multilayer films prepared by an ion-beam-sputtering technique were measured with a STM on the vertical and transverse attributes. The film roughnesses and average spatial wavelengths added to the substrates depend on the multilayer film fabrication conditions, i.e., material combinations, number of layers, and individual layer thickness. These were estimated to lead to a loss of specular reflectivity and variations of the soft x-ray scattering angle distribution. This method points the way to further studies of soft x-ray multilayer film functional properties and can be used as basic guidance for selecting the best coating conditions in the fabrications of soft x-ray multilayer films. (C) 1996 American Vacuum Society.

A novel hydroperoxyl substituted cembranolide diterpene from marine soft coral Lobophytum crassum

A new cembranolide diterpene with a hydroperoxyl substitution was isolated from the marine soft coral Lobophytum crassum. The structure was elucidated on the basis of chemical and spectral methods.

Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model

With the intermediate-complexity Zebiak-Cane model, we investigate the 'spring predictability barrier' (SPB) problem for El Nino events by tracing the evolution of conditional nonlinear optimal perturbation (CNOP), where CNOP is superimposed on the El Nino events and acts as the initial error with the biggest negative effect on the El Nino prediction. We show that the evolution of CNOP-type errors has obvious seasonal dependence and yields a significant SPB, with the most severe occurring in predictions made before the boreal spring in the growth phase of El Nino. The CNOP-type errors can be classified into two types: one possessing a sea-surface-temperature anomaly pattern with negative anomalies in the equatorial central-western Pacific, positive anomalies in the equatorial eastern Pacific, and a thermocline depth anomaly pattern with positive anomalies along the Equator, and another with patterns almost opposite to those of the former type. In predictions through the spring in the growth phase of El Nino, the initial error with the worst effect on the prediction tends to be the latter type of CNOP error, whereas in predictions through the spring in the decaying phase, the initial error with the biggest negative effect on the prediction is inclined to be the former type of CNOP error. Although the linear singular vector (LSV)-type errors also have patterns similar to the CNOP-type errors, they cover a more localized area than the CNOP-type errors and cause a much smaller prediction error, yielding a less significant SPB. Random errors in the initial conditions are also superimposed on El Nino events to investigate the SPB. We find that, whenever the predictions start, the random errors neither exhibit an obvious season-dependent evolution nor yield a large prediction error, and thus may not be responsible for the SPB phenomenon for El Nino events. These results suggest that the occurrence of the SPB is closely related to particular initial error patterns. The two kinds of CNOP-type error are most likely to cause a significant SPB. They have opposite signs and, consequently, opposite growth behaviours, a result which may demonstrate two dynamical mechanisms of error growth related to SPB: in one case, the errors grow in a manner similar to El Nino; in the other, the errors develop with a tendency opposite to El Nino. The two types of CNOP error may be most likely to provide the information regarding the 'sensitive area' of El Nino-Southern Oscillation (ENSO) predictions. If these types of initial error exist in realistic ENSO predictions and if a target method or a data assimilation approach can filter them, the ENSO forecast skill may be improved. Copyright (C) 2009 Royal Meteorological Society

Numerical modeling of water wave interaction with a soft mud bed

A vertical 2-D numerical model is presented for simulating the interaction between water waves and a soft mud bed. Taking into account nonlinear rheology, a semi-empirical rheological model is applied to this water-mud model, reflecting the combined visco-elasto-plastic properties of soft mud under such oscillatory external forces as water waves. In order to increase the resolution of the flow in the neighborhood of both sides of the inter-surface, a logarithmic grid in the vertical direction is employed for numerical treatment. Model verifications are given through comparisons between the calculated and the measured mud mass transport velocities as well as wave height changes.

Affine Matching with Bounded Sensor Error: A Study of Geometric Hashing and Alignment

Affine transformations are often used in recognition systems, to approximate the effects of perspective projection. The underlying mathematics is for exact feature data, with no positional uncertainty. In practice, heuristics are added to handle uncertainty. We provide a precise analysis of affine point matching, obtaining an expression for the range of affine-invariant values consistent with bounded uncertainty. This analysis reveals that the range of affine-invariant values depends on the actual $x$-$y$-positions of the features, i.e. with uncertainty, affine representations are not invariant with respect to the Cartesian coordinate system. We analyze the effect of this on geometric hashing and alignment recognition methods.

The Alignment of Objects With Smooth Surfaces: Error Analysis of the Curvature Method

The recognition of objects with smooth bounding surfaces from their contour images is considerably more complicated than that of objects with sharp edges, since in the former case the set of object points that generates the silhouette contours changes from one view to another. The "curvature method", developed by Basri and Ullman [1988], provides a method to approximate the appearance of such objects from different viewpoints. In this paper we analyze the curvature method. We apply the method to ellipsoidal objects and compute analytically the error obtained for different rotations of the objects. The error depends on the exact shape of the ellipsoid (namely, the relative lengths of its axes), and it increases a sthe ellipsoid becomes "deep" (elongated in the Z-direction). We show that the errors are usually small, and that, in general, a small number of models is required to predict the appearance of an ellipsoid from all possible views. Finally, we show experimentally that the curvature method applies as well to objects with hyperbolic surface patches.

On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions

In this paper, we bound the generalization error of a class of Radial Basis Function networks, for certain well defined function learning tasks, in terms of the number of parameters and number of examples. We show that the total generalization error is partly due to the insufficient representational capacity of the network (because of its finite size) and partly due to insufficient information about the target function (because of finite number of samples). We make several observations about generalization error which are valid irrespective of the approximation scheme. Our result also sheds light on ways to choose an appropriate network architecture for a particular problem.

Error Detection and Recovery for Robot Motion Planning with Uncertainty

Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and uncertainty in the geometry of the environment. The last, which is called model error, has received little previous attention. We present a framework for computing motion strategies that are guaranteed to succeed in the presence of all three kinds of uncertainty. The motion strategies comprise sensor-based gross motions, compliant motions, and simple pushing motions.

The effect of the product cost factor on error handling in industrial robots

N.W. Hardy and M.H. Lee. The effect of the product cost factor on error handling in industrial robots. In Maria Gini, editor, Detecting and Resolving Errors in Manufacturing Systems. Papers from the 1994 AAAI Spring Symposium Series, pages 59-64, Menlo Park, CA, March 1994. The AAAI Press. Technical Report SS-94-04, ISBN 0-929280-60-1.

Research into error recovery for sensory robots

Lee, M., Barnes, D. P., Hardy, N. (1985). Research into error recovery for sensory robots. Sensor Review, 5 (4), 194-197.

Research into automatic error recovery

Lee, M., Hardy, N., & Barnes, D. P. (1984). Research into automatic error recovery. 65-69. Paper presented at 4th International Conference on Robot Vision and Sensory Controls, London, London, United Kingdom.