Time-resolved resonance Raman spectroscopic studies on the triplet excited state of fluoranil

Perfluoro substituted organic compounds have attracted attention owing to their unique structure and reactivity induced by the perfluoro effect. Fluoranil, a perfluoro derivative of p-benzoquinone, is the subject of this paper. Although the perfluoro effect in the ground state seems to have been well understood there is no information available about such effects on the excited state. Here, the time-resolved resonance Raman spectra of the triplet excited state of fluoranil are reported along with the Raman excitation profiles (REPs) of the various vibrational modes. The vibrational spectral analyses have been carried out by analogy with the fluoranil ground state, triplet benzoquinone, and triplet chloranil vibrational spectral assignments. Also, the assignments are further supported by the calculated frequencies using ab initio theoretical methods. It is observed that for fluoranil in the triplet excited state, due to the perfluoro effect, the structure is considerably less distorted than benzoquinone and also the electron delocalization in the pi* antibonding orbital is less than that of triplet excited state of benzoquinone.

Time-Resolved Resonance Raman Spectroscopic Studies on the Triplet Excited State of Thioxanthone

Thioxanthone has been investigated extensively owing to its unique photochemical and photophysical applications and its solvatochromic behavior. Here, we report the time-resolved resonance Raman studies on the structure of the lowest triplet excited state of thioxanthone in carbon tetrachloride. In addition, FT-IR and FT-Raman techniques have been used to study the vibrational structure in the ground state. To corroborate the experimental findings, density functional theory calculations have been carried out. Isotopic calculations and normal coordinate analysis have been used to help in assigning the observed bands to Raman vibrational modes. Structural information derived from this study is expected to help in better understanding the triplet state photochemistry of thioxanthone.

On the Decidability of Model-Checking Information Flow Properties

Current standard security practices do not provide substantial assurance about information flow security: the end-to-end behavior of a computing system. Noninterference is the basic semantical condition used to account for information flow security. In the literature, there are many definitions of noninterference: Non-inference, Separability and so on. Mantel presented a framework of Basic Security Predicates (BSPs) for characterizing the definitions of noninterference in the literature. Model-checking these BSPs for finite state systems was shown to be decidable in [8]. In this paper, we show that verifying these BSPs for the more expressive system model of pushdown systems is undecidable. We also give an example of a simple security property which is undecidable even for finite-state systems: the property is a weak form of non-inference called WNI, which is not expressible in Mantel’s BSP framework.

Effect of dehydration on the mechanical properties of sodium saccharin dihydrate probed with nanoindentation

Nanoindentation is used to explore the variation of mechanical properties associated with the dehydration process in sodium saccharin dihydrate. Upon indenting using a Berkovich tip, (011) and (101) faces exhibit explicit mechanical anisotropy that is consistent with the underlying crystal structure and intermolecular interactions. For freshly grown crystals, (011) is stiffer than (101) by 14%, while (101) is harder than (011) by 8%. Being a heavily hydrated system, the measured mechanical responses contain information pertinent to the fluidity associated with lattice water. Indentation on (011) with a sharp cube-corner tip induces a fluid flow; this observation is uncommon in molecular crystals. The crystals effloresce over a period of time with the generation of a more compact crystal structure and consequently increasing H and E.

The effect of cell size and channel density on neuronal information encoding and energy efficiency

Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.

Speaker verification based on the fusion of speech acoustics and inverted articulatory signals

We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.

Influence of threshold stress on the estimation of the Weibull statistics

The influence of threshold stress on the estimation of the Weibull statistics is discussed in terms of the Akaike information criterion. Numerical simulations show that, if sample data are limited in number and threshold stress is not too large, the two-parameter Weibull distribution is still a preferred choice. For example, the fit of strength data of glass and ceramics to the two- and three-parameter Weibull distributions is compared.