Stochastic modeling of a billiard in a gravitational field: Power law behavior of Lyapunov exponents

We consider the motion of a point particle (billiard) in a uniform gravitational field constrained to move in a symmetric wedge-shaped region. The billiard is reflected at the wedge boundary. The phase space of the system naturally divides itself into two regions in which the tangent maps are respectively parabolic and hyperbolic. It is known that the system is integrable for two values of the wedge half-angle ₁ and ₂ and chaotic for ₁<< ₂. We study the system at three levels of approximation: first, where the deterministic dynamics is replaced by a random evolution; second, where, in addition, the tangent map in each region is, replaced by its average; and third, where the tangent map is replaced by a single global average. We show that at all three levels the Lyapunov exponent exhibits power law behavior near ₁ and ₂ with exponents 1/2 and 1, respectively. We indicate the origin of the exponent 1, which has not been observed in unaccelerated billiards.     

遗传算法在构象搜寻中的应用

遗传算法是一种模仿自然进化进程的新颖的启发式优化方法。通过它，人们可以在计算机上对所需的各种问题实施进化操作，最终产生理想的结果。遗传算法现已被广泛于计算机辅助设计、工程设计、系统模拟等领域并取得了极大的成功。本文拟对遗传算法在对大、中、小分子的构象搜寻中的应用作一较全面的综述。     

How electrons guard the space: shape optimization with probability distribution criteria

Efficient formulas for computing the probabilities of finding exactly electrons in an arbitrarily chosen volume ³ for Hartree–Fock wavefunctions are presented. These formulas allow the use of shape optimization techniques, such as level set methods, for optimizing with respect to various criteria involving such probabilities. The criterion defined as the difference between the Hartree–Fock and the independent-particle model probabilities of finding electrons in stresses the quantum effects due to the Pauli principle. We have implemented a 2D level set method for optimizing this criterion in order to study spatial separation of electron pairs in linear molecules. The method is described and the illustrative example of the BH molecule is reported.Contribution to the Jacopo Tomasi Honorary Issue     

Multivariate calibration of near infrared spectra by orthogonal WAVElet correction using a genetic algorithm

Orthogonal WAVElet correction (OWAVEC) is a pre-processing method aimed at simultaneously accomplishing two essential needs in multivariate calibration, signal correction and data compression, by combining the application of an orthogonal signal correction algorithm to remove information unrelated to a certain response with the great potential that wavelet analysis has shown for signal processing. In the previous version of the OWAVEC method, once the wavelet coefficients matrix had been computed from NIR spectra and deflated from irrelevant information in the orthogonalization step, effective data compression was achieved by selecting those largest correlation/variance wavelet coefficients serving as the basis for the development of a reliable regression model. This paper presents an evolution of the OWAVEC method, maintaining the first two stages in its application procedure (wavelet signal decomposition and direct orthogonalization) intact but incorporating genetic algorithms as a wavelet coefficients selection method to perform data compression and to improve the quality of the regression models developed later. Several specific applications dealing with diverse NIR regression problems are analyzed to evaluate the actual performance of the new OWAVEC method. Results provided by OWAVEC are also compared with those obtained with original data and with other orthogonal signal correction methods.     

Dynamic optimization problems with bounded terminal conditions

Bounded terminal conditions of nonlinear optimization problems are converted to equality terminal conditions via the Valentine's device. In so doing, additional unknown parameters are introduced into the problem. The transformed problems can still be easily solved using the sequential gradient-restoration algorithm (SGRA) via a simple augmentation of the unknown parameter vector . Three example problems with bounded terminal conditions are solved to verify this technique.This research was supported in part by the National Aeronautics and Space Administration under NASA Grant No. NCC 2-106.     

On the statistical mechanics of the traveling salesman problem

We consider the statistical mechanics of the traveling salesman problem (TSP) and develop some representations to study it. In one representation the mean field theory has a simple form and brings out some of the essential features of the problem. It shows that the system has spontaneous symmetry breaking at any nonzero temperature. In general the phase progressively changes as one decreases the temperature. At low temperatures the mean field theory solution is very sensitive to any small perturbations, due to the divergence of some local susceptibilities. This critical region extends down to zero temperature. We perform the quenched average for a nonmetric TSP in the second representation and the resulting problem is more complicated than the infinite-range spin-glass problem, suggesting that the free energy landscape may be more complex. The role played by frustration in this problem appears explicitly through the localization property of a random matrix, which resembles the tight binding matrix of an electron in a random lattice.     

Optical biosensor for pharmaceuticals, antibiotics, hormones, endocrine disrupting chemicals and pesticides in water: Assay optimization process for estrone as example

Certain contaminants at trace concentrations in surface waters can have dramatic effects on the hormonal system of organisms in the aquatic environment. Therefore, immunoanalytical methods at a very low limit of detection (LOD) and a low limit of quantification (LOQ) are becoming more and more important for environmental analysis and especially for monitoring drinking water quality. Environmental monitoring of antibiotics, hormones, endocrine disrupting chemicals, and pesticides in real water samples (e.g. surface, ground or drinking water) with difficult matrices places high demands on chemical analysis. Biosensors have suitable characteristics such as efficiency in allowing very fast, sensitive, and cost-effective detection. Here we describe an assay optimization process with a fully automated immunoassay for estrone which resulted in a LOD below 0.20 ng L⁻¹ and a LOQ below 1.40 ng L⁻¹. In contrast to common analytical methods such as GC-MS or HPLC-MS, the biosensor used requires no sample pre-treatment and pre-concentration. The very low validation parameters for estrone are the result of the continuous optimization of the immunoassay. The basis of our sensitive assay is the antibody with a high affinity constant towards estrone. During the optimization process, we reduced the amount of antibody per sample and improved the chip surface modification. Finally, this proceeding led to a calibration routine with an amount of antibody of only 3.0 ng per sample (sample volume: 1.0 mL). The reduction of the amount of antibody per sample results in better validation parameters (LOD, LOQ, and IC₅₀), but this reduction leads to the current device-related limitation of the River Analyser (RIANA).For some endocrine disrupting compounds, no effect levels (NOELs) in the lower nanogram per liter range are reported. This defines the challenge, which analytical methods have to compete with and our RIANA instrument with its improved sensitivity for the detection of a single hormone in the lower nanogram per liter range is a powerful tool in aquatic analytics in addition to the common analytical methods.     

A conformational analysis method for understanding the energy landscapes of clusters.

A newly developed unbiased structural optimization method, named dynamic lattice searching (DLS), is proposed as an approach for conformational analysis of atomic/molecular clusters and used in understanding the energy landscape of large clusters. The structures of clusters are described in terms of the number of basic tetrahedron (BT) units they contain. We found that the hit numbers of different structural motifs in DLS runs is proportional to the number of BTs. A parameter T(max) is defined to limit the maximal number of atoms moved in a structural transition. Results show that T(max) is a key parameter for modulating the efficiency of the DLS method and has a great influence on the hit number of different motifs in DLS runs. Finally, the effect of potential range on the conformational distribution of the (Morse)(98) cluster is also discussed with different potential-range parameters.     

聚醚醚酮微结构及反应特性的量子化学研究

利用AM1对聚醚醚酮重复单元进行条件优化,得出了此分子的最优构型,明确了聚醚醚酮分子链的微观构象,并在此构象基础上进行量子化学计算,给出了健序、净电荷、前线轨道等信息,从理论上研究了聚醚醚酮的磺化反应及热分解反应的一些特性.