Crossed Molecular Beams and Theoretical Studies of the O(3P)+1,2-Butadiene Reaction: Dominant Formation of Propene+CO and Ethylidene+Ketene Molecular Channels

Detailed understanding of the mechanism of the combustion relevant multichannel reactions of O(³P) with unsaturated hydrocarbons (UHs) requires the identification of all primary reaction products, the determination of their branching ratios and assessment of intersystem crossing (ISC) between triplet and singlet potential energy surfaces (PESs). This can be best achieved combining crossed-molecular-beam (CMB) experiments with universal, soft ionization, mass-spectrometric detection and time-of-flight analysis to high-level ab initio electronic structure calculations of triplet/singlet PESs and RRKM/Master Equation computations of branching ratios (BRs) including ISC. This approach has been recently demonstrated to be successful for O(³P) reactions with the simplest UHs (alkynes, alkenes, dienes) containing two or three carbon atoms. Here, we extend the combined CMB/theoretical approach to the next member in the diene series containing four C atoms, namely 1,2-butadiene (methylallene) to explore how product distributions, branching ratios and ISC vary with increasing molecular complexity going from O(³P))+propadiene to O(³P)+1,2-butadiene. In particular, we focus on the most important, dominant molecular channels, those forming propene+CO (with branching ratio ∽0.5) and ethylidene+ketene (with branching ratio ∽0.15), that lead to chain termination, to be contrasted to radical forming channels (branching ratio ∽0.35) which lead to chain propagation in combustion systems.     

Digital twin of a combustion furnace operating in flameless conditions: reduced-order model development from CFD simulations

The present paper presents the first-of-its-kind digital twin for a furnace operating in flameless combustion conditions. A methodology combining data compression, by means of Proper Orthogonal Decomposition (POD), and interpolation, using Kriging, was developed to design physics-based, reduced-order models (ROMs) for the prediction of combustion data at unexplored operating conditions. Three-dimensional simulations with detailed chemistry were carried out, spanning a wide range of operating conditions in terms of fuel composition (methane-hydrogen mixtures from pure methane to pure hydrogen), equivalence ratio (from 0.7 to 1) and air injector diameter (to adjust the air jet entrainment). Based on the available simulations, a ROM was developed, to predict both spatial fields, local and integral values of thermochemical variables at working conditions not included in the ROM development. Results showed that the developed ROM could reliably predict the temperature and main chemical species distribution in the furnace with an overall error below 10%, proving the effectiveness of the approach for the development of digital twins of combustion systems. A remarkable accuracy was observed for the prediction of specific quantities, including wall temperatures, OH decay length, OH peak value and location and exhaust gas composition, including pollutants, with prediction errors always below 5%, showing the potential of the approach to develop soft sensors.     

Synthetic Access to Aromatic α-Haloketones

α-Haloketones play an essential role in the synthesis of complex N-, S-, O-heterocycles; of which some exhibit a remarkable biological activity. Research further illustrated that α-bromo-, α-chloro-, and α-iodoketones are key precursors for blockbuster pharmacological compounds. Over the past twenty years, substantial advances have been made in the synthesis of these industrially relevant building blocks. Efforts have focused on rendering the synthetic protocols greener, more effective and versatile. In this survey, we summarised and thoroughly evaluated the progress of the field, established in the past two decades, in terms of generality, efficacy and sustainability.     

On the Randomized Error of Polynomial Methods for Eigenvector and Eigenvalue Estimates

In this paper we consider the problem of estimating the largest eigenvalue and the corresponding eigenvector of a symmetric matrix. In particular, we consider iterative methods, such as the power method and the Lanczos method. These methods need a starting vector which is usually chosen randomly. We analyze the behavior of these methods when the initial vector is chosen with uniform distribution over the unitn-dimensional sphere. We extend and generalize the results reported earlier. In particular, we give upper and lower bounds on the _pnorm of the randomized error, and we improve previously known bounds with a detailed analysis of the role of the multiplicity of the largest eigenvalue.     

Berberine Derivatives as Pseudomonas aeruginosa MexXY-OprM Inhibitors: Activity and In Silico Insights

The natural alkaloid berberine has been demonstrated to inhibit the Pseudomonas aeruginosa multidrug efflux system MexXY-OprM, which is responsible for tobramycin extrusion by binding the inner membrane transporter MexY. To find a structure with improved inhibitory activity, we compared by molecular dynamics investigations the binding affinity of berberine and three aromatic substituents towards the three polymorphic sequences of MexY found in P. aeruginosa (PAO1, PA7, and PA14). The synergy of the combinations of berberine or berberine derivatives/tobramycin against the same strains was then evaluated by checkerboard and time-kill assays. The in silico analysis evidenced different binding modes depending on both the structure of the berberine derivative and the specific MexY polymorphism. In vitro assays showed an evident MIC reduction (32-fold and 16-fold, respectively) and a 2–3 log greater killing effect after 2 h of exposure to the combinations of 13-(2-methylbenzyl)- and 13-(4-methylbenzyl)-berberine with tobramycin against the tobramycin-resistant strain PA7, a milder synergy (a 4-fold MIC reduction) against PAO1 and PA14, and no synergy against the ΔmexXY strain K1525, confirming the MexY-specific binding and the computational results. These berberine derivatives could thus be considered new hit compounds to select more effective berberine substitutions and their common path of interaction with MexY as the starting point for the rational design of novel MexXY-OprM inhibitors.     

An Evaluation of Entropy Measures for Microphone Identification

Research findings have shown that microphones can be uniquely identified by audio recordings since physical features of the microphone components leave repeatable and distinguishable traces on the audio stream. This property can be exploited in security applications to perform the identification of a mobile phone through the built-in microphone. The problem is to determine an accurate but also efficient representation of the physical characteristics, which is not known a priori. Usually there is a trade-off between the identification accuracy and the time requested to perform the classification. Various approaches have been used in literature to deal with it, ranging from the application of handcrafted statistical features to the recent application of deep learning techniques. This paper evaluates the application of different entropy measures (Shannon Entropy, Permutation Entropy, Dispersion Entropy, Approximate Entropy, Sample Entropy, and Fuzzy Entropy) and their suitability for microphone classification. The analysis is validated against an experimental dataset of built-in microphones of 34 mobile phones, stimulated by three different audio signals. The findings show that selected entropy measures can provide a very high identification accuracy in comparison to other statistical features and that they can be robust against the presence of noise. This paper performs an extensive analysis based on filter features selection methods to identify the most discriminating entropy measures and the related hyper-parameters (e.g., embedding dimension). Results on the trade-off between accuracy and classification time are also presented.     

Weil Representation and Metaplectic Groups over an Integral Domain

Given F a locally compact, nondiscrete, non-archimedean field of characteristic ≠ 2 and R an integral domain such that a non-trivial smooth character χ: F → R ^× exists, we construct the (reduced) metaplectic group attached to χ and R. We show that it is in the expected cases a double cover of the symplectic group over F. Finally, we define a faithful infinite dimensional R-representation of the metaplectic group analogue to the Weil representation in the complex case.     

Simple synthetic routes to ruthenium-indenylidene olefin metathesis catalysts

An efficient synthetic protocol involving reactions between the free carbene and [RuCl(2)(PPh(3))(2)(Ind)] followed by addition of pyridine leads to the isolation of olefin metathesis active [RuCl(2)(L)(Py)(Ind)] (L = SIMes and SIPr) complexes. This novel approach circumvents the use of costly tricyclohexylphosphine.     

Determination of the tricyclic compound adosupine and its three metabolites in plasma and brain of rat using high-performance liquid chromatography.

An analytical method for the detection in biological samples of the novel tricyclic compound adosupine (10-acetoamido-5-methyl-5,6-dihydro-11H-dibenzo[b,e]azepin-6 ,11-dione), which is capable of influencing various forms of urinary bladder hyperreflexia has been developed using high-performance liquid chromatography with UV detection. Liquid-liquid extraction was used to isolate the parent compound, three metabolites and an analogue (added as internal standard) from plasma and brain of rat. Adosupine was well separated from its three metabolites with 0.01 M disodium hydrogenphosphate-acetonitrile-methanol-nonylamine (59.986:38:2:0.014) at pH 4.5 as mobile phase using a C18 reversed-phase column. The standard curves were linear in the range 50-5000 ng/ml (or ng/g) for adosupine and metabolites in both plasma and brain. The between- and within-assay variations for high and low concentrations of the parent compound and the three metabolites were 8.2-14%. In the range 50-5000 ng/ml (or ng/g) the accuracy of the method was satisfactory, with the relative error always lower than 10%. Analytical recoveries of added adosupine and the three metabolites were higher than 82%. The method has been applied successfully, to investigate the pharmacokinetics of the drug and its distribution in the central nervous system of rats.     

Mimetic finite difference method for the Stokes problem on polygonal meshes

Various approaches to extend finite element methods to non-traditional elements (general polygons, pyramids, polyhedra, etc.) have been developed over the last decade. The construction of basis functions for such elements is a challenging task and may require extensive geometrical analysis. The mimetic finite difference (MFD) method works on general polygonal meshes and has many similarities with low-order finite element methods. Both schemes try to preserve the fundamental properties of the underlying physical and mathematical models. The essential difference between the two schemes is that the MFD method uses only the surface representation of discrete unknowns to build the stiffness and mass matrices. Since no extension of basis functions inside the mesh elements is required, practical implementation of the MFD method is simple for polygonal meshes that may include degenerate and non-convex elements. In this article, we present a new MFD method for the Stokes problem on arbitrary polygonal meshes and analyze its stability. The method is developed for the general case of tensor coefficients, which allows us to apply it to a linear elasticity problem, as well. Numerical experiments show, for the velocity variable, second-order convergence in a discrete L² norm and first-order convergence in a discrete H¹ norm. For the pressure variable, first-order convergence is shown in the L² norm.