Determination of Propranolol Hydrochloride in Pharmaceutical Preparations Using Near Infrared Spectrometry with Fiber Optic Probe and Multivariate Calibration Methods

A method for determination of propranolol hydrochloride in pharmaceutical preparation using near infrared spectrometry with fiber optic probe (FTNIR/PROBE) and combined with chemometric methods was developed. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). The treatments based on the mean centered data and multiplicative scatter correction (MSC) were selected for models construction. A root mean square error of prediction (RMSEP) of 8.2 mg g −1 was achieved using siPLS (s2i20PLS) algorithm with spectra divided into 20 intervals and combination of 2 intervals (8501 to 8801 and 5201 to 5501 cm −1 ). Results obtained by the proposed method were compared with those using the pharmacopoeia reference method and significant difference was not observed. Therefore, proposed method allowed a fast, precise, and accurate determination of propranolol hydrochloride in pharmaceutical preparations. Furthermore, it is possible to carry out on-line analysis of this active principle in pharmaceutical formulations with use of fiber optic probe

Anatomy of a Duality

The nature of M-theory on K3 X I, where I is a line interval, is considered, with a view towards formulating a `matrix theory' representation of that situation. Various limits of this compactification of M-theory yield a number of well known N=1 six dimensional compactifications of the heterotic and type I string theories. Geometrical relations between these limits give rise to string/string dualities between some of these compactifications. At a special point in the moduli space of compactifications, this motivates a partial definition of the matrix theory representation of the M-theory on K3 X I as the large N limit of a certain type IA orientifold model probed by a conglomerate of N D-branes. Such a definition in terms of D-branes and orientifold planes is suggestive, but necessarily incomplete, due to the low amount of superymmetry. It is proposed - following hints from the orientifold model - that the complete matrix theory representation of the K3 X I compactified M-theory is given by the large N limit of compactification - on a suitable `dual' surface - of the `little heterotic string' N = 1 six dimensional quantum theories.Comment: 55 pages, harvmac.tex (`b' mode), epsf.tex for 3 figures, (Some references were corrected. Small adjustments to text and abstract. Physics unchanged

Orientifold dual for stuck NS5 branes

We establish T-duality between NS5 branes stuck on an orientifold 8-plane in type I' and an orientifold construction in type IIB with D7 branes intersecting at angles. Two applications are discussed. For one we obtain new brane constructions, realizing field theories with gauge group a product of symplectic factors, giving rise to a large new class of conformal N=1 theories embedded in string theory. Second, by studying a D2 brane probe in the type I' background, we get some information on the still elusive (0,4) linear sigma model describing a perturbative heterotic string on an ADE singularity.Comment: 24 pages, LaTeX, references adde

Calabi-Yau mirror symmetry as a gauge theory duality

Using brane set-ups we construct dual gauge theories in two dimensions with calN = (2,2) supersymmetry. Two different dualities are realized. One is basically a consequence of three-dimensional mirror symmetry. The nonlinear sigma model with a Calabi-Yau target space on the Higgs branch of the gauge theory is mapped into an equivalent non-linear sigma model on the Coulomb branch on the dual, realizing a T-dual target space with torsion. The second dual is genuine to two dimensions. In addition to swapping Higgs and Coulomb branches it trades twisted for untwisted multiplets, implying a sign flip of the left-moving U (1)R charge. Successive application of both dualities leads to geometric mirror symmetry for the Calabi-Yau target space

Validation of data analysis routines for a thermal probe apparatus using numerical data sets

Most thermal properties of construction materials used in the analysis of building performance have been measured under laboratory conditions, using a guarded hot box or hot plate apparatus. As a consequence, these properties seldom reflect the impact of actual conditions (especially moisture content) on the values of conductivity and diffusivity. Hence there is a need to develop techniques that allow to take into account local conditions, and measure building material properties in situ. One option available is the use of a thermal probe. The thermal probe technique is based on creating a line source in a material sample, and measuring the temperature rise in the sample in reaction to heat being applied. Obviously the data analysis routines used to calculate thermal conductivity and thermal diffusivity based on the temperature rise observed are crucial to the success of the technique. Transient thermal simulation of a of a model representing a line source in an infinite material sample has been used to generate a set of numerical data sets to validate analysis routines in conjunction with an experimental thermal probe apparatus. Findings show that by careful application of these routines, a close agreement with simulation input values can be achieved, with errors of less than one percent. This validates the analysis routines and provides a deeper appreciation of the theoretical behaviour of a thermal probe

2.5D multi-view gait recognition based on point cloud registration

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM

Observational bounds on the cosmic radiation density

We consider the inference of the cosmic radiation density, traditionally parameterised as the effective number of neutrino species N_eff, from precision cosmological data. Paying particular attention to systematic effects, notably scale-dependent biasing in the galaxy power spectrum, we find no evidence for a significant deviation of N_eff from the standard value of N_eff^0=3.046 in any combination of cosmological data sets, in contrast to some recent conclusions of other authors. The combination of all available data in the linear regime prefers, in the context of a ``vanilla+N_eff'' cosmological model, 1.1<N_eff<4.8 (95% C.L.) with a best-fit value of 2.6. Adding data at smaller scales, notably the Lyman-alpha forest, we find 2.2<N_eff<5.8 (95% C.L.) with 3.8 as the best fit. Inclusion of the Lyman-alpha data shifts the preferred N_eff upwards because the sigma_8 value derived from the SDSS Lyman-alpha data is inconsistent with that inferred from CMB. In an extended cosmological model that includes a nonzero mass for N_eff neutrino flavours, a running scalar spectral index and a w parameter for the dark energy, we find 0.8<N_eff<6.1 (95% C.L.) with 3.0 as the best fit.Comment: 23 pages, 3 figures, uses iopart.cls; v2: 1 new figure, references added, matches published versio

Optimal change-point estimation from indirect observations

We study nonparametric change-point estimation from indirect noisy observations. Focusing on the white noise convolution model, we consider two classes of functions that are smooth apart from the change-point. We establish lower bounds on the minimax risk in estimating the change-point and develop rate optimal estimation procedures. The results demonstrate that the best achievable rates of convergence are determined both by smoothness of the function away from the change-point and by the degree of ill-posedness of the convolution operator. Optimality is obtained by introducing a new technique that involves, as a key element, detection of zero crossings of an estimate of the properly smoothed second derivative of the underlying function.Comment: Published at http://dx.doi.org/10.1214/009053605000000750 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org