Emergence of classicality for primordial fluctuations: Concepts and analogies

We clarify the way in which cosmological perturbations of quantum origin, produced during inflation, assume classical properties. Two features play an important role in this process: First, the dynamics of fluctuations which are presently on large cosmological scales leads to a very peculiar state (highly squeezed) that is indistinguishable, in a precise sense, from a classical stochastic process. This holds for almost all initial quantum states. Second, the process of decoherence by interaction with the environment distinguishes the field amplitude basis as the robust pointer basis. We discuss in detail the interplay between these features and use simple analogies such as the free quantum particle to illustrate the main conceptual issues.     

Natural flavonoids interact with dinitrobenzene system in aprotic media: an electrochemical probing

Three structurally related natural flavonoids (FlOH), quercetin (Q), rutin (R) and morin (M), were investigated by cyclic voltammetry to probe their interactions with hazardous 1,4-dinitrobenzene (1,4-DNB) using a glassy carbon electrode. Scavenging of 1,4-DNB by FlOH was inferred from a positive shift in reduction potential, decrease in anodic peak current, and irreversible electrochemical behavior of 1,4-DNB on increasing the flavonoid concentration. The homogeneous bi-molecular rate constant (k2) was determined using the Nicholson-Shain equation and found to be higher for the dianion. Morin posed a comparatively higher k2 value for its interaction with the 1,4-DNB electrochemical system owing to its more acidic nature and least intramolecular hydrogen bonding. The cyclic voltammetric (CV) results were further supported by HyperchemPM3 quantum mechanical semi-empirical calculations, which point towards E(r)C(i) interactions between flavonoids and 1,4-DNB. The present investigation is biologically significant in terms of natural flavonoidal scavenging activity toward toxins such as dinitroaromatics.     

[Te8][NbOCl4]2 containing an infinite chain‐like {[Te–Te–Te–(Te5)]2+}n polycation

The title compound, [Te₈][NbOCl₄]₂, was obtained as translucent black crystals by reaction of elemental tellurium, niobium(V) chloride and niobium(V) oxychloride in the ionic liquid BMImCl (BMImCl is 1‐butyl‐3‐methylimidazolium chloride). The synthesis was performed in argon‐filled glass ampoules. According to X‐ray structure analysis based on single crystals, the title compound crystallizes with triclinic lattice symmetry and consists of infinite {[Te₈]²⁺}_n cations associated with pyramidal [NbOCl₄]⁻ anions. The novel catena‐octatellurium(2+) cation is composed of Te₅ rings that are linked via Te₃ units [Te—Te = 2.6455 (18)–2.8164 (19) Å]. The composition and purity of [Te₈][NbOCl₄]₂ were further confirmed by energy‐dispersive X‐ray diffraction (EDX) analysis.     

Aspects on Applications of IR Reflectivity- and Raman Scattering-Experiments on Polaritons in Solid State Chemistry and Biophysics

The coupled phonon-photon state called “polariton” is an elementary excitation which exists at all temperatures in single crystalline materials with well defined translational symmetries. In the view of this aspect polaritons turn out to be more important for the dynamics of crystal lattices in general than e.g. magnons or plasmons which normally can be excited only in certain low temperature ranges. The present article summarizes experimental results which all might be applied as analytical methods. An improved method for the determination of fundamental mode frequencies is described. Polariton interactions with localized modes, and second order phonons and the relation to the ferroelectric phase transition mechanism is reviewed. Furthermore experiments concerning parametric light scattering, the TM-reflection technique, the ATR-method, and nonlinear optical experiments are summarized. We finally discuss the question of mechanical-electromagnetic energy conversion and some tentative future aspects.     

Audience noise in concert halls during musical performances

Noise generated by the audience during musical performances is audible and sometimes disturbing. In this study, an attempt to estimate such audience noise was carried out. From the recordings of performances in five performance spaces (four concert halls and one opera house), probability density functions of the sound pressure levels were obtained in octave bands, which were fitted with three Gaussian distribution curves. The Gaussian distribution curve with the lowest mean value corresponds to a mixture of the technical background noise and audience generated noise, which is named the mixed background noise. Finally, the audience noise distribution is extracted by energy subtraction of the technical background noise levels measured in an empty condition from the mixed background noise levels. As a single index, L(90) of the audience noise distribution is named the audience noise level. Empirical prediction models were made using the four orchestra concert halls, revealing that the audience noise level is significantly correlated with the technical background noise level. It is therefore concluded that a relaxation of the current background noise recommendations for concert halls is not recommended.     

Benchmarking local classification methods

In recent years in the fields of statistics and machine learning an increasing amount of so called local classification methods has been developed. Local approaches to classification are not new, but have lately become popular. Well-known examples are the $k$ nearest neighbors method and classification trees. However, in most publications on this topic the term “local” is used without further explanation of its particular meaning. Only little is known about the properties of local methods and the types of classification problems for which they may be beneficial. We explain the basic principles and introduce the most important variants of local methods. To our knowledge there are very few extensive studies in the literature that compare several types of local methods and global methods across many data sets. In order to assess their performance we conduct a benchmark study on real-world and synthetic tasks. We cluster data sets and considered learning algorithms with regard to the obtained performance structures and try to relate our theoretical considerations and intuitions to these results. We also address some general issues of benchmark studies and cover some pitfalls, extensions and improvements.