Statistical analysis of microscale gas flows and stock price changes

First, recent studies on the information preservation (IP) method, a particle approach for low-speed micro-scale gas flows, are reviewed. The IP method was validated for benchmark issues such as Couette, Poiseuille and Rayleigh flows, compared well with measured data for typical internal flows through micro-channels and external flows past micro flat plates, and combined with the Navier-Stokes equations to be a hybrid scheme for subsonic, rarefied gas flows. Second, the focus is moved to the microscopic characteristic of China stock market, particularly the price correlation between stock deals. A very interesting phenomenon was found that showed a reverse transition behaviour between two neighbouring price changes. This behaviour significantly differs from the transition rules for atomic and molecular energy levels, and it is very helpful to understand the essential difference between stock markets and nature.

Bonding and correlation analysis of various SiCO isomers

The structural properties for various SiCO isomers in the singlet and triplet states have been investigated using CASSCF methods with a 6-311 +G* basis set and also using three DFT and MP2 with same basis set for those systems except for the linear singlet state. The detailed bonding character is discussed, and the state-state correlations and the isomerization mechanism are also determined. Results indicate that there are four different isomers for each spin state, and for all isomers, the triplet state is more stable than the corresponding singlet state. The most stable is the linear SiCO ((3)Sigma(-)) species and may be refer-red to the ground state. At the CASSCF-MP2(full)/6-311+G* level, the state-state energy separations of the other triplet states relative to the ground state are 43.2 (cyclic), 45.2 (linear SiOC), and 75.6 kcal/mol (linear CSiO), respectively, whereas the triplet-singlet state excitation energies for each configuration are 17.3 (linear SiCO), 2.2 (cyclic SiCO), 10.2 (linear SiOC), and 18.5 kcal/mol (linear CSiO), respectively. SiCo ((3)Sigma(-)) may be classified as silene (carbonylsilene), and its COdelta- moiety possesses CO- property. The dissociation energy of the ground state is 42.5 kcal/mol at the CASSCF-MP2(full)/6-311+G* level and falls within a range of 36.5-41.5 kcal/mol at DFT level, and of 23.7-28.9 kcal/mol at the wave function-correlated level, whereas the vertical IP is 188.8 kcal/mol at the CASSCF-MP2(full)/6-311+G* level and is very close to the first IP of Si atom. Three linear isomers (SiCO, SiOC, and CSiO) have similar structural bonding character. SiOC may be referred to the iso-carbonyl Si instead of the aether compound, whereas the CSiO isomer may be considered as the combination of C (the analogue of Si) with SiO (the analogue of CO). The bonding is weak for all linear species, and the corresponding potential energy surfaces are flat, and thus these linear molecules are facile. Another important isomer is of cyclic structure, it may be considered as the combination of CO with Si by the side pi bond. This structure has the smallest triplet state-singlet state excitation energy (similar to2.2 kcal/mol); the C-O bonds are longer, and the corresponding vibrational frequencies are significantly smaller than those of the other linear species. This cyclic species is not classified as an epoxy compound. State-state correlation analysis and the isomerization pathway searches have indicated that there are no direct correlations among three linear structures for each spin state, but they may interchange by experiencing two transition states and one cyclic intermediate. The easiest pathway is to break the Si-O bond to go to the linear SiCO, but its inverse process is very difficult. The most difficult process is to break the C-O bond and to go to the linear CSiO.

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Probabilistic Solution of Inverse Problems

In this thesis we study the general problem of reconstructing a function, defined on a finite lattice from a set of incomplete, noisy and/or ambiguous observations. The goal of this work is to demonstrate the generality and practical value of a probabilistic (in particular, Bayesian) approach to this problem, particularly in the context of Computer Vision. In this approach, the prior knowledge about the solution is expressed in the form of a Gibbsian probability distribution on the space of all possible functions, so that the reconstruction task is formulated as an estimation problem. Our main contributions are the following: (1) We introduce the use of specific error criteria for the design of the optimal Bayesian estimators for several classes of problems, and propose a general (Monte Carlo) procedure for approximating them. This new approach leads to a substantial improvement over the existing schemes, both regarding the quality of the results (particularly for low signal to noise ratios) and the computational efficiency. (2) We apply the Bayesian appraoch to the solution of several problems, some of which are formulated and solved in these terms for the first time. Specifically, these applications are: teh reconstruction of piecewise constant surfaces from sparse and noisy observationsl; the reconstruction of depth from stereoscopic pairs of images and the formation of perceptual clusters. (3) For each one of these applications, we develop fast, deterministic algorithms that approximate the optimal estimators, and illustrate their performance on both synthetic and real data. (4) We propose a new method, based on the analysis of the residual process, for estimating the parameters of the probabilistic models directly from the noisy observations. This scheme leads to an algorithm, which has no free parameters, for the restoration of piecewise uniform images. (5) We analyze the implementation of the algorithms that we develop in non-conventional hardware, such as massively parallel digital machines, and analog and hybrid networks.

Covariance analysis of the Coulomb explosion of ammonia induced by intense nanosecond laser at 532 nm

The Coulomb explosion of ammonia clusters induced by nanosecond laser at 532 not with an intensity of similar to 10(12) Wcm(-2) has been studied by time of flight mass spectrometry. The dominant multiply charged ions are N3+ and N2+ with kinetic energies of 110 and 50 eV respectively. The electrons generated from the multiphoton ionization are heated through inverse bremsstrahlung by the laser field when colliding with neutral or ionic particles. When their energies surpass the corresponding ionization potentials of the molecules or ions, the subsequent electron impact ionization may take place thus resulting in multi-charged nitrogen ions. Covariance analysis is made to study the possible pathways of the Coulomb explosion.

Artificial opal photonic crystals and inverse opal structures - fundamentals and applications from optics to energy storage

Photonic crystals (PhCs) influence the propagation of light by their periodic variation in dielectric contrast or refractive index. This review outlines the attractive optical qualities inherent to most PhCs namely the presence of full or partial photonic band gaps and the possibilities they present towards the inhibition of spontaneous emission and the localization of light. Colloidal self-assembly of polymer or silica spheres is one of the most favoured and low cost methods for the formation of PhCs as artificial opals. The state of the art in growth methods currently used for colloidal self-assembly are discussed and the use of these structures for the formation of inverse opal architectures is then presented. Inverse opal structures with their porous and interconnected architecture span several technological arenas - optics and optoelectronics, energy storage, communications, sensor and biological applications. This review presents several of these applications and an accessible overview of the physics of photonic crystal optics that may be useful for opal and inverse opal researchers in general, with a particular emphasis on the recent use of these three-dimensional porous structures in electrochemical energy storage technology. Progress towards all-optical integrated circuits may lie with the concepts of the photonic crystal, but the unique optical and structural properties of these materials and the convergence of PhC and energy storage disciplines may facilitate further developments and non-destructive optical analysis capabilities for (electro)chemical processes that occur within a wide variety of materials in energy storage research.

Thermodynamic analysis of ligand-induced changes in protein thermal unfolding applied to high-throughput determination of ligand affinities with extrinsic fluorescent dyes.

The quantification of protein-ligand interactions is essential for systems biology, drug discovery, and bioengineering. Ligand-induced changes in protein thermal stability provide a general, quantifiable signature of binding and may be monitored with dyes such as Sypro Orange (SO), which increase their fluorescence emission intensities upon interaction with the unfolded protein. This method is an experimentally straightforward, economical, and high-throughput approach for observing thermal melts using commonly available real-time polymerase chain reaction instrumentation. However, quantitative analysis requires careful consideration of the dye-mediated reporting mechanism and the underlying thermodynamic model. We determine affinity constants by analysis of ligand-mediated shifts in melting-temperature midpoint values. Ligand affinity is determined in a ligand titration series from shifts in free energies of stability at a common reference temperature. Thermodynamic parameters are obtained by fitting the inverse first derivative of the experimental signal reporting on thermal denaturation with equations that incorporate linear or nonlinear baseline models. We apply these methods to fit protein melts monitored with SO that exhibit prominent nonlinear post-transition baselines. SO can perturb the equilibria on which it is reporting. We analyze cases in which the ligand binds to both the native and denatured state or to the native state only and cases in which protein:ligand stoichiometry needs to treated explicitly.

Inversion of light scattering data by singular system analysis

We consider the problem of inverting experimental data obtained in light scattering experiments described by linear theories. We discuss applications to particle sizing and we describe fast and easy-to-implement algorithms which permit the extraction, from noisy measurements, of reliable information about the particle size distribution. © 1987, SPIE.

Linear inverse problems with discrete data: II. Stability and regularization

For pt.I. see ibid. vol.1, p.301 (1985). In the first part of this work a general definition of an inverse problem with discrete data has been given and an analysis in terms of singular systems has been performed. The problem of the numerical stability of the solution, which in that paper was only briefly discussed, is the main topic of this second part. When the condition number of the problem is too large, a small error on the data can produce an extremely large error on the generalised solution, which therefore has no physical meaning. The authors review most of the methods which have been developed for overcoming this difficulty, including numerical filtering, Tikhonov regularisation, iterative methods, the Backus-Gilbert method and so on. Regularisation methods for the stable approximation of generalised solutions obtained through minimisation of suitable seminorms (C-generalised solutions), such as the method of Phillips (1962), are also considered.

Sensitivity characteristics of inverse Class-E power amplifier

In this paper, an analysis is performed in order to determine the effects that variations in circuit component values, frequency, and duty cycle have on the performance of the newly introduced inverse Class-E amplifier. Analysis of the inverse Class-E amplifier under the generalized condition of arbitrary duty cycle is performed and it is shown that the inverse Class-E amplifier is reasonably tolerant to circuit parameter variations. When compared to the conventional Class-E amplifier the inverse Class-E amplifier offers the potential for high efficiency at increased output power as well as higher peak output power levels than are available with a conventional Class-E amplifier. Further the inverse Class-E amplifier provides more flexibility for deployment with a pulsewidth modulator as the means of producing full-carrier amplitude modulation (AM) due to its ability to operate to high AM modulation indices.

Can physical activity modulate pancreatic cancer risk?:a systematic review and meta-analysis

Numerous epidemiological studies have examined the association between physical activity and pancreatic cancer; however, findings from individual cohorts have largely not corroborated a protective effect. Among other plausible mechanisms, physical activity may reduce abdominal fat depots inducing metabolic improvements in glucose tolerance and insulin sensitivity, thereby potentially attenuating pancreatic cancer risk. We performed a systematic review to examine associations between physical activity and pancreatic cancer. Six electronic databases were searched from their inception through July 2009, including MEDLINE and EMBASE, seeking observational studies examining any physical activity measure with pancreatic cancer incidence/mortality as an outcome. A random effects model was used to pool individual effect estimates evaluating highest vs. lowest categories of activity. Twenty-eight studies were included. Pooled estimates indicated a reduction in pancreatic cancer risk with higher levels of total (five prospective studies, RR: 0.72, 95% CI: 0.52-0.99) and occupational activity (four prospective studies, RR: 0.75, 95% CI: 0.59-0.96). Nonsignificant inverse associations were seen between risks and recreational and transport physical activity. When examining exercise intensity, moderate activity appeared more protective (RR: 0.79, 95% CI: 0.52-1.20) than vigorous activity (RR: 0.97, 95% CI: 0.85-1.11), but results were not statistically significant and the former activity variable incorporated marked heterogeneity. Despite indications of an inverse relationship with higher levels of work and total activity, there was little evidence of such associations with recreational and other activity exposures.

Estimation of Clarinet Reed Parameters by Inverse Modelling

Analysis of the acoustical functioning of musical instruments invariably involves the estimation of model parameters. The broad aim of this paper is to develop methods for estimation of clarinet reed parameters that are representative of actual playing conditions. This presents various challenges because of the di?culties of measuring the directly relevant variables without interfering with the control of the instrument. An inverse modelling approach is therefore proposed, in which the equations governing the sound generation mechanism of the clarinet
are employed in an optimisation procedure to determine the reed parameters from the mouthpiece pressure and volume ?ow signals. The underlying physical model captures most of the reed dynamics and is simple enough to be used in an inversion process. The optimisation procedure is ?rst tested by applying it to numerically synthesised signals, and then applied to mouthpiece signals acquired during notes blown by a human player. The proposed inverse modelling approach raises the possibility of revealing information about the way in which the embouchure-related reed parameters are controlled by the player, and also facilitates physics-based re-synthesis of clarinet sounds.

Error analysis of FFT architectures for digital video applications

This paper describes how worst-case error analysis can be applied to solve some of the practical issues in the development and implementation of a low power, high performance radix-4 FFT chip for digital video applications. The chip has been fabricated using a 0.6 µm CMOS technology and can perform a 64 point complex forward or inverse FFT on real-time video at up to 18 Megasamples per second. It comprises 0.5 million transistors in a die area of 7.8×8 mm and dissipates 1 W, leading to a cost-effective silicon solution for high quality video processing applications. The analysis focuses on the effect that different radix-4 architectural configurations and finite wordlengths has on the FFT output dynamic range. These issues are addressed using both mathematical error models and through extensive simulation.

Do perinatal and early life exposures influence the risk of malignant melanoma?:A Northern Ireland birth cohort analysis

Aim: Intrauterine, early life and maternal exposures may have important consequences for cancer development in later life. The aim of this study was to examine perinatal and birth characteristics with respect to Cutaneous malignant melanoma (CMM) risk. Methods: The Northern Ireland Child Health System database was used to examine gestational age adjusted birth weight, infant feeding practices, parental age and socioeconomic factors at birth in relation to CMM risk amongst 447,663 infants delivered between January 1971 and December 1986. Follow-up of histologically verified CMM cases was undertaken from the beginning of 1993 to 31st December 2007. Multivariable adjusted unconditional logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI) of CMM risk. Results: A total of 276 CMM cases and 440,336 controls contributed to the final analysis. In reference to normal (gestational age-adjusted) weight babies, those heaviest at birth were twice as likely to develop CMM OR 2.4 (95% CI 1.1-5.1). Inverse associations with CMM risk were observed with younger (

Inverse Gaussian Modeling of Turbulence-Induced Fading in Free-Space Optical Systems

We propose the inverse Gaussian distribution, as a less complex alternative to the classical log-normal model, to describe turbulence-induced fading in free-space optical (FSO) systems operating in weak turbulence conditions and/or in the presence of aperture averaging effects. By conducting goodness of fit tests, we define the range of values of the scintillation index for various multiple-input multiple-output (MIMO) FSO configurations, where the two distributions approximate each other with a certain significance level. Furthermore, the bit error rate performance of two typical MIMO FSO systems is investigated over the new turbulence model; an intensity-modulation/direct detection MIMO FSO system with Q-ary pulse position modulation that employs repetition coding at the transmitter and equal gain combining at the receiver, and a heterodyne MIMO FSO system with differential phase-shift keying and maximal ratio combining at the receiver. Finally, numerical results are presented that validate the theoretical analysis and provide useful insights into the implications of the model parameters on the overall system performance. © 2011 IEEE.