Approach to chaos in ultracold atomic and molecular physics: Statistics of near-threshold bound states for Li+CaH and Li+CaF

We calculate near-threshold bound states and Feshbach resonance positions for atom–rigid-rotor models of the highly anisotropic systems Li+CaH and Li+CaF. We perform statistical analysis on the resonance positions to compare with the predictions of random matrix theory. For Li+CaH with total angular momentum J=0 we find fully chaotic behavior in both the nearest-neighbor spacing distribution and the level number variance. However, for J>0 we find different behavior due to the presence of a nearly conserved quantum number. Li+CaF (J=0) also shows apparently reduced levels of chaotic behavior despite its stronger effective coupling. This may indicate the development of another good quantum number relating to a bending motion of the complex. However, continuously varying the rotational constant over a wide range shows unexpected structure in the degree of chaotic behavior, including a dramatic reduction around the rotational constant of CaF. This demonstrates the complexity of the relationship between coupling and chaotic behavior.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

CaII K interstellar observations towards early-type disc and halo stars

We present high-resolution (R = lambda/Deltalambda similar to 40 000) Ca II K interstellar observations (lambda(air) = 3933.66Angstrom) towards 88 mainly B-type stars, of which 74 are taken from the Edinburgh-Cape or Palomar-Green surveys, and 81 have > 25degrees. The majority of the data come from previously existing spectroscopy, although also included are 18 new observations of stars with echelle spectra taken with UVES on the Very Large Telescope UT2 (Kueyen). Some 49 of the sample stars have distance estimates above the Galactic plane (z) greater than or equal to 1 kpc, and are thus good probes of the halo interstellar medium. Of the 362 interstellar Ca K components that we detect, 75 (21 per cent) have absolute values of their LSR velocity values exceeding 40 km s(-1). In terms of the deviation velocity for the sightlines with distance estimates, 46/273 (17 per cent) of components have velocity values exceeding those predicted by standard Galactic rotation by more than 40 km s(-1). Combining this data set with previous observations, we find that the median value of the reduced equivalent width (REW) of stars with z greater than or equal to 1 kpc (EW x sin ) is similar to 115 mAngstrom (n = 80), similar to that observed in extragalactic sightlines by Bowen. Using data of all z distances, the REW at infinity is found to be similar to 130 mAngstrom, with the scaleheight (1) of the Ca II K column density distribution being;z 800 pc (n = 196) and reduced column density at infinity of log[N(Ca II K) cm(-2)] similar to 12.24. This implies that similar to30 per cent of Ca II K absorption occurs at distances exceeding similar to1 kpc. For nine sightlines, with distance exceeding 1 kpc and with a companion object within 5degrees, we find that all but two have values of Ca II reduced equivalent width the same to within similar to20 per cent, when the REW of the nearest object is extrapolated to the distance of the further of the pair, and assuming 1 = 800 pc. For 29 of our sightlines with z greater than or equal to 1 kpc and a H I detection from the Leiden-Dwingeloo survey (beamsize of 0.5degrees), we find log(N(Ca II K)IN(H I)) ranging from -7.4 to - 8.4. Values of the Ca II K abundance relative to neutral hydrogen (log[N(Ca II K) cm(-2)] - log[N(H I) cm(-2)]) are found to be more than similar to0.5 dex higher in stars with distances exceeding approximate to100 pc, when compared with the (log[N(Ca II K) cm(-2)] -log[N(H-tot) cm(-2)]) values found in nearby sightlines such as those in Wakker & Mathis (2000). Finally, stellar Ca II K equivalent widths of the sample are determined for 26 objects.

A fast method for fuzzy neural modeling and refinement

In the identification of complex dynamic systems using fuzzy neural networks, one of the main issues is the curse of dimensionality, which makes it difficult to retain a large number of system inputs or to consider a large number of fuzzy sets. Moreover, due to the correlations, not all possible network inputs or regression vectors in the network are necessary and adding them simply increases the model complexity and deteriorates the network generalisation performance. In this paper, the problem is solved by first proposing a fast algorithm for selection of network terms, and then introducing a refinement procedure to tackle the correlation issue. Simulation results show the efficacy of the method.

Extruder Melt Temperature Control with Fuzzy Logic

In polymer extrusion, the delivery of a melt which is homogenous in composition and temperature is paramount for achieving high quality extruded products. However, advancements in process control are required to reduce temperature variations across the melt flow which can result in poor product quality. The majority of thermal monitoring methods provide only low accuracy point/bulk melt temperature measurements and cause poor controller performance. Furthermore, the most common conventional proportional-integral-derivative controllers seem to be incapable of performing well over the nonlinear operating region. This paper presents a model-based fuzzy control approach to reduce the die melt temperature variations across the melt flow while achieving desired average die melt temperature. Simulation results confirm the efficacy of the proposed controller.