Spontaneous generation of optical activity in urea inclusion compounds vis-a-vis current theories

A novel test of recent theories of the origin of optical activity has been designed based on the inclusion of certain alkyl 2-methylhexanoates into urea channels.

Increasing ionic conductivity and mechanical strength of a plastic electrolyte by inclusion of a polymer

in this contribution we present a soft matter solid electrolyte which was obtained by inclusion of a polymer (polyacrylonitrile, PAN) in LiClO4/LiTFSI-succinonitrile (SN), a semi-solid organic plastic electrolyte. Addition of the polymer resulted in considerable enhancement in ionic conductivity as well as mechanical strength of LiX-SN (X=ClO4, TFSI) plastic electrolyte. Ionic conductivity of 92.5%-[1 M LiClO4-SN]:7.5%-PAN (PAN amount as per SN weight) composite at 25 degrees C recorded a remarkably high value of 7 x 10(-3) Omega(-1) cm(-1), higher by few tens of order in magnitude compared to 1 M LiClO4-SN. Composite conductivity at sub-ambient temperature is also quite high. At -20 degrees C, the ionic conductivity of (100 -x)%-[1 M LiClO4-SN]:x%-PAN composites are in the range 3 x 10(-5)-4.5 x 10(-4) Omega(-1) cm(-1), approximately one to two orders of magnitude higher with respect to 1 M LiClO4-SN electrolyte conductivity. Addition of PAN resulted in an increase of the Young's modulus (Y) from Y -> 0 for LiClO4-SN to a maximum of 0.4MPa for the composites. Microstructural studies based on X-ray diffraction, differential scanning calorimetry and Fourier transform infrared spectroscopy suggest that enhancement in composite ionic conductivity is a combined effect of decrease in crystallinity and enhanced trans conformer concentration. (c) 2008 Elsevier Ltd. All rights reserved.

The effects of cholesterol inclusion on the vesicular membranes of cationic lipids

Small unilamellar vesicles formed from four cationic lipids in the absence and the presence of varying amounts of cholesterol were studied using fluorescence polarization and H-1-NMR techniques. The fluorescence polarization data clearly indicate that the packing order in the cationic lipid bilayers are affected by inclusion of cholesterol. importantly, this effect exists also with a cationic lipid that is devoid of any formal linkage region where the interaction of the lipid with cholesterol through hydrogen bonding is not feasible. The interactions of cholesterol with different types of cationic lipids in excess water have also been examined in multilamellar dispersions using proton magnetic resonance spectroscopy. In all the cases, the methylene proton linewidths in the NMR spectra respond to the addition of cholesterol to vesicles. Hydrophobic association of the lipid and cholesterol imposes restriction on the chain (CH2)(n) motions, leaving the terminal CH3 groups relatively mobile. On the basis of energy-minimized structural models, a rationale of the cholesterol-cationic lipid assembly has also been presented.

On the probability that the determinant of an nxn matrix over a finite field vanishe

An expression is derived for the probability that the determinant of an n x n matrix over a finite field vanishes; from this it is deduced that for a fixed field this probability tends to 1 as n tends to.

Structure-reactivity correlation in inclusion complexes: deoxycholic acid di-tert-butyl thioketone

Ultraviolet irradiation of crystalline molecular inclusion complexes of deoxycholic acid with di-tert-butyl thioketone results in no reaction. The structure of the above complex has been determined via X-ray diffraction. The absence of expected photoreactions. namely, photoreduction and photooxidation, is rationalized on the basis of the X-ray structure analysis of the complex.

An Adaptive Scheme for Learning the Probability Threshold in Pattern Recognition

The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.

Sodium santalbate-dimethyl sulfate inclusion complex

A molecular inclusion complex has been obtained from the major acetylenic acid, santalbic acid (octadec-11-en-9-ynoic acid ortrans-11-octadecen-9-ynoic acid) of the seed oil ofSantalum album L. by a simple treatment of its sodium salt with dimethyl sulfate. Aqueous solutions (0.5–1%) of the complex produce good lather and have efficient cleansing (detergent) action on grease and dirt particles.

Theoretical gain optimization studies in CO2-N2 lasers. III. Inclusion of line shape effects

The influence of Lorentz and Doppler line-broadening mechanisms on the small-signal optical gain of lasers and, in particular, gasdynamic lasers, is discussed. A relationship between the critical parameter reflecting the line-broadening mechanisms and some of the important parameters arising out of the gain optimization studies in CO2-N2 gasdynamic lasers is established. Using this relationship, methods by which the deleterious effect of the Doppler mechanisms on small-signal gain can be suppressed are suggested. Journal of Applied Physics is copyrighted by The American Institute of Physics.

Sodium santalbate-dimethyl sulfate inclusion complex

A molecular inclusion complex has been obtained from the major acetylenic acid, santalbic acid (octadec-11-en-9-ynoic acid ortrans-11-octadecen-9-ynoic acid) of the seed oil ofSantalum album L. by a simple treatment of its sodium salt with dimethyl sulfate. Aqueous solutions (0.5–1%) of the complex produce good lather and have efficient cleansing (detergent) action on grease and dirt particles.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Stereospecific photodimerization of coumarins in crystalline inclusion complexes. Molecular and crystal structure of 1:2 complex of (S,S)-(-)-1,6-bis(o-chlorophenyl)-1,6-diphenyl-hexa-2,4-diyne-1,6-diol and coumarin

Proximity of molecules is a crucial factor in many solid- state photochemical processes.'S2 The biomolecular photodimerization reactions in the solid state depend on the relative geometry of reactant molecules in the crystal lattice with center-to-center distance of nearest neighbor double bonds of the order of ca. 4 A. This fact emanates from the incisive studies of Schmidt and Cohen.2 One of the two approaches to achieve this distance requirement is the so-called "Crystal-Engineering" of structures, which essentially involves the introduction of certain functional groups that display in-plane interstacking interactions (Cl...Cl, C-He-0, etc.) in the crystal The chloro group is by far the most successful in promoting the /3- packing m ~ d e ,th~o,u~gh recent studies have shown its limitations? Another approach involves the use of constrained media in which the reactants could hopefully be aligned.

A lower bound to the survival probability and an approximate first passage time distribution for Markovian and non-Markovian dynamics in phase space

We derive a very general expression of the survival probability and the first passage time distribution for a particle executing Brownian motion in full phase space with an absorbing boundary condition at a point in the position space, which is valid irrespective of the statistical nature of the dynamics. The expression, together with the Jensen's inequality, naturally leads to a lower bound to the actual survival probability and an approximate first passage time distribution. These are expressed in terms of the position-position, velocity-velocity, and position-velocity variances. Knowledge of these variances enables one to compute a lower bound to the survival probability and consequently the first passage distribution function. As examples, we compute these for a Gaussian Markovian process and, in the case of non-Markovian process, with an exponentially decaying friction kernel and also with a power law friction kernel. Our analysis shows that the survival probability decays exponentially at the long time irrespective of the nature of the dynamics with an exponent equal to the transition state rate constant.

Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains

We consider the problem of detecting statistically significant sequential patterns in multineuronal spike trains. These patterns are characterized by ordered sequences of spikes from different neurons with specific delays between spikes. We have previously proposed a data-mining scheme to efficiently discover such patterns, which occur often enough in the data. Here we propose a method to determine the statistical significance of such repeating patterns. The novelty of our approach is that we use a compound null hypothesis that not only includes models of independent neurons but also models where neurons have weak dependencies. The strength of interaction among the neurons is represented in terms of certain pair-wise conditional probabilities. We specify our null hypothesis by putting an upper bound on all such conditional probabilities. We construct a probabilistic model that captures the counting process and use this to derive a test of significance for rejecting such a compound null hypothesis. The structure of our null hypothesis also allows us to rank-order different significant patterns. We illustrate the effectiveness of our approach using spike trains generated with a simulator.

First passage probability during random vibration

The probability that a random process crosses an arbitrary level for the first time is expressed as a Gram—Charlier series, the leading term of which is the Poisson approximation. The coefficients of this series are related to the moments of the number of level crossings. The results are applicable to both stationary and non-stationary processes. Some numerical results are presented for the response process of a linear single-degree-of-freedom oscillator under Gaussian white noise excitation.

Spatial survival probability for one-dimensional fluctuating interfaces in the steady state

We report numerical and analytic results for the spatial survival probability for fluctuating one-dimensional interfaces with Edwards-Wilkinson or Kardar-Parisi-Zhang dynamics in the steady state. Our numerical results are obtained from analysis of steady-state profiles generated by integrating a spatially discretized form of the Edwards-Wilkinson equation to long times. We show that the survival probability exhibits scaling behavior in its dependence on the system size and the "sampling interval" used in the measurement for both "steady-state" and "finite" initial conditions. Analytic results for the scaling functions are obtained from a path-integral treatment of a formulation of the problem in terms of one-dimensional Brownian motion. A "deterministic approximation" is used to obtain closed-form expressions for survival probabilities from the formally exact analytic treatment. The resulting approximate analytic results provide a fairly good description of the numerical data.