Photon level chemical classification using digital compressive detection

A key bottleneck to high-speed chemical analysis, including hyperspectral imaging and monitoring of dynamic chemical processes, is the time required to collect and analyze hyperspectral data. Here we describe, both theoretically and experimentally, a means of greatly speeding up the collection of such data using a new digital compressive detection strategy. Our results demonstrate that detecting as few as ∼10 Raman scattered photons (in as little time as ∼30 μs) can be sufficient to positively distinguish chemical species. This is achieved by measuring the Raman scattered light intensity transmitted through programmable binary optical filters designed to minimize the error in the chemical classification (or concentration) variables of interest. The theoretical results are implemented and validated using a digital compressive detection instrument that incorporates a 785 nm diode excitation laser, digital micromirror spatial light modulator, and photon counting photodiode detector. Samples consisting of pairs of liquids with different degrees of spectral overlap (including benzene/acetone and n-heptane/n-octane) are used to illustrate how the accuracy of the present digital compressive detection method depends on the correlation coefficients of the corresponding spectra. Comparisons of measured and predicted chemical classification score plots, as well as linear and non-linear discriminant analyses, demonstrate that this digital compressive detection strategy is Poisson photon noise limited and outperforms total least squares-based compressive detection with analog filters.     

Nonlinear Neural Mapping Analysis of the Adverse Effects of Drugs

Abstract

Numerous drugs have been identified as presenting adverse effects towards the driving of vehicles. A large set of these drugs was compiled and classified into ten categories. Nonlinear neural mapping (N2M) was used to derive a typology of these molecules and also to link their adverse effects to therapeutic categories and structural information.     

Structure and dynamics of water dangling OH bonds in hydrophobic hydration shells. Comparison of simulation and experiment

Molecular dynamics and electric field strength simulations are performed in order to quantify the structural, dynamic, and vibrational properties of non-H-bonded (dangling) OH groups in the hydration shell of neopentane, as well as in bulk water. The results are found to be in good agreement with the experimentally observed high-frequency (～3660 cm(-1)) OH band arising from the hydration shell of neopentanol dissolved in HOD/D(2)O, obtained by analyzing variable concentration Raman spectra using multivariate curve resolution (Raman-MCR). The simulation results further indicate that hydration shell dangling OH groups preferentially point toward the central carbon atom of neopentane to a degree that increases with the lifetime of the dangling OH.     

e-Statistics for deriving QSAR models

This paper presents some freeware, shareware, and commercial statistical tools available via the Internet and which could be used in QSAR for deriving models. Programming environments useful in Statistics, newsgroups and FAQs are also introduced due to their interest for the discipline.     

Do baryons trace dark matter in the early universe?

Baryon-density perturbations of large amplitude may exist if they are compensated by dark-matter perturbations such that the total density is unchanged. Primordial abundances and galaxy clusters allow these compensated isocurvature perturbations (CIPs) to have amplitudes as large as ~10%. CIPs will modulate the power spectrum of cosmic microwave background (CMB) fluctuations--those due to the usual adiabatic perturbations--as a function of position on the sky. This leads to correlations between different spherical-harmonic coefficients of the temperature and/or polarization maps, and induces polarization B modes. Here, the magnitude of these effects is calculated and techniques to measure them are introduced. While a CIP of this amplitude can be probed on large scales with existing data, forthcoming CMB experiments should improve the sensitivity to CIPs by at least an order of magnitude.     

Primordial non-Gaussianity from the 21 cm power spectrum during the epoch of reionization

Primordial non-Gaussianity is a crucial test of inflationary cosmology. We consider the impact of non-Gaussianity on the ionization power spectrum from 21 cm emission at the epoch of reionization. We focus on the power spectrum on large scales at redshifts of 7 to 8 and explore the expected constraint on the local non-Gaussianity parameter f(NL) for current and next-generation 21 cm experiments. We show that experiments such as SKA and MWA could measure f(NL) values of order 10. This can be improved by an order of magnitude with a fast-Fourier transform telescope like Omniscope.     

Chronopotentiometric Determination of Redox States of Peptides

Reduced and oxidized forms of peptides were studied by different electrochemical methods at carbon and hanging mercury drop (HMDE) electrodes. Striking differences between the reduced and oxidized peptides were obtained by constant current chronopotentiometric stripping analysis (CPSA) at HMDE. Peptides yielded electrocatalytic peak H at highly negative potentials (ca. ?1.75 V). Reduced peptides adsorbed at positively charged HMDE produced substantially higher peak H than the oxidized forms. Voltammetry reflected the peptide redox state less efficiently. Different orientation of reduced and oxidized molecules at the positively charged electrode and very fast potential changes in CPSA were probably responsible for the observed effects.     

Prediction of biological activity profiles of cyanobacterial secondary metabolites

Over the past decade cyanobacteria have become an interesting source of new classes of pharmacologically active natural products. Some cyanobacterial secondary metabolites (CSMs) are also well known for their toxic effects on living species. The PASS (Prediction of Activity Spectra for Substances) computer program, which is able to simultaneously predict more than one thousand biological and toxicological activities from only the structural formulas of the chemicals, was used to predict the biological activity profile of 681 CSMs. Multivariate methods were employed to structure and analyse this wealth of biological and chemical information. PASS predictions were successfully compared to the available information on the pharmacological and toxicological activity of these compounds.