Electro-optical properties of an orthoconic liquid crystal mixture (W-182) and its molecular dynamics

We observed that the perfect dark state problem could be solved by using orthoconic antiferroelectric liquid crystal (OAFLC) instead of normal AFLC by comparing the properties of isocontrast and dispersion chromaticity of W-182 OAFLC and normal AFLC CS-4001. We electro-optically observed that several subphases such as SmCγ*, SmC*β, SmC*α and antiferroelectric SmI*A phases exist in W-182 OAFLC. We dielectrically observed in 4 μm thin cell that during heating, several new phases appeared. In the high temperature antiferroelectric region, a higher order than SmC* phase could be detected dielectrically, in the temperature range of 91–98 °C, behaving similar to SmCγ* and also, another phase below SmC* region could be dielectrically detected in the temperature range of 103–1100 °C, behaving similar to SmCα*, and an antiferroelectric, similar to SmIA* phase, was observed in the lower temperature region of the antiferroelectric phase; those are definitely arising due to surface force and interfacial charges interactions. We observed both PH and PL relaxation modes in both cells, although they differed in their strength and relaxation frequency. We studied extensively our observations of PH and PL modes in the antiferroelectric region, a Goldstone mode in the ferroelectric region and a soft mode in the ferroelectric region and SmA* phases

Identification of piecewise-linear mechanical oscillators via Bayesian model selection and parameter estimation

The problem of identifying single degree-of-freedom (SDOF) nonlinear mechanical oscillators with piecewise-linear (PWL) restoring forces is considered. PWL nonlinear systems are a class of models that specify or approximate nonlinear systems via a set of locally-linear maps, each defined over different operating regions. They are useful in modelling hybrid phenomena common in practical situations, such as, systems with different modes of operation, or systems whose dynamics change because of physical limits or thresholds. However, identifying PWL models can be a challenging task when the number of operating regions and their partitions are unknown. This paper formulates the identification of oscillators with PWL restoring forces as a task of concurrent model selection and parameter estimation, where the selection of the number of linear regions is treated as a model selection task and identifying the associated system parameters as a task of parameter estimation. In this study, PWL maps in restoring forces with up to four regions are considered, and the task of model selection and parameter estimation task is addressed in a Bayesian framework. A likelihood-free Approximate Bayesian Computation (ABC) scheme is followed, which is easy to implement and provides a simplified way of doing model selection. The proposed approach has been demonstrated using two numerical examples and an experimental study, where ABC has been used to select models and identify parameters from among four SDOF PWL systems with different number of PWL regions. The results demonstrate the flexibility of using the proposed Bayesian approach for identifying the correct model and parameters of PWL systems, in addition to furnishing uncertainty estimates of the identified parameters

Complete Genome Sequences of the Novel Cluster BP Phages Infecting Streptomyces sanglieri, AxeJC, Cumberbatch, Eastland, Eklok, HFrancette, Ignacio, Piccadilly, and Vondra

Article describes the Streptomyces sanglieri bacteriophages AxeJC, Cumberbatch, Eastland,Eklok, HFrancette, Ignacio, Piccadilly, and Vondra form a novel actinobacteriophage cluster,BP. These siphoviruses have circularly permuted genomes with an average size of 37,700 bp and a GC content of 71%. Each genome contains approximately 58 protein-coding genes, with no tRNAs

On spike-and-slab priors for Bayesian equation discovery of nonlinear dynamical systems via sparse linear regression

This paper presents the use of spike-and-slab (SS) priors for discovering governing differential equations of motion of nonlinear structural dynamic systems. The problem of discovering governing equations is cast as that of selecting relevant variables from a predetermined dictionary of basis functions and solved via sparse Bayesian linear regression. The SS priors, which belong to a class of discrete-mixture priors and are known for their strong sparsifying (or shrinkage) properties, are employed to induce sparse solutions and select relevant variables. Three different variants of SS priors are explored for performing Bayesian equation discovery. As the posteriors with SS priors are analytically intractable, a Markov chain Monte Carlo (MCMC)-based Gibbs sampler is employed for drawing posterior samples of the model parameters; the posterior samples are used for basis function selection and parameter estimation in equation discovery. The proposed algorithm has been applied to four systems of engineering interest, which include a baseline linear system, and systems with cubic stiffness, quadratic viscous damping, and Coulomb damping. The results demonstrate the effectiveness of the SS priors in identifying the presence and type of nonlinearity in the system. Additionally, comparisons with the Sparse Bayesian (SBL) – that uses a Student’s-t prior – indicate that the SS priors can achieve better model selection consistency, reduce false discoveries, and derive models that have superior predictive accuracy. Finally, the Silverbox experimental benchmark is used to validate the proposed methodology

Equation discovery for nonlinear dynamical systems : a Bayesian viewpoint

This paper presents a new Bayesian approach to equation discovery -- combined structure detection and parameter estimation -- for system identification (SI) in nonlinear structural dynamics. The structure detection is accomplished via a sparsity-inducing prior within a Relevance Vector Machine (RVM) framework; the prior ensures that terms making no contribution to the model are driven to zero coefficient values. Motivated by the idea of compressive sensing (CS) and recent results from the machine learning community on sparse linear regression, the paper adopts the use of an over-complete dictionary to represent a large number of candidate terms for the equation describing the system. Unlike other sparse learners, like the Lasso and its derivatives, which are potentially sensitive to hyperparameter selection, the proposed method exploits the principled means of fixing priors and hyperpriors that are available via a hierarchical Bayesian approach. The approach is successfully demonstrated and validated via a number of simulated case studies of common Single-Degree-of-Freedom (SDOF) nonlinear dynamic systems, and on two challenging experimental data sets

Effect of conducting polymer poly (3,4-ethylenedioxythiophene) (PEDOT) nanotubes on electro-optical and dielectric properties of a ferroelectric liquid crystal

A detailed comparative study of the dielectric and electro-optical properties of a ferroelectric liquid crystal (FLC) and FLC after having doped with conducting polymer Poly (3,4-ethylenedioxythiophene) (PEDOT) nanotubes is done. The electro-optic study reveals a lower electrical response time, rotational viscosity and spontaneous polarization in the FLC/PEDOT nanocomposite system. By fitting the capacitance with voltage in a Preisach model, four dipolar species in both FLC and composites system have been obtained. The orientation of the four dipolar species in the composites system is such that the effective dipole moment in the transverse direction of the FLC molecule is less than that in FLC compound

Reaction of sterically congested NHC-Zn(CH 2CH 3) 2 with substituted phenols leading to zincate complexes

We report the reaction of a sterically congested NHC-Zn(CH 2CH3)2 Lewis adduct (1) prepared through reaction of an equimolar ratio of 1,3-di-tert-butylimidazol-2-ylidene and diethyl zinc, with various substituted phenols (4-tert-butyl-phenol, 2,6-di-tert-butyl-4-methyl phenol, and 1-bromo-4,6-di-tert-butyl phenol). The NHC-Zn dative bond was cleaved in each of the reactions with the substituted phenols to afford the corresponding ionic complexes of imidazolium cation and aryloxo-zincate, [{(4-CMe3C6H4O) 2Zn(-OC6H4-4-CMe3)} 2{(1,3-(CMe3)2-ImCH}2] (2), [{(2,6-(CMe3)2-4-Me-C6H3O) 2}Zn{(1,3-(Cme3)2-ImCH}] (3), and [{(1-Br-3,5-(Cme3)2C6H2O) 2}2-Zn{(1,3-(CMe3)2-ImCH}] (4), where 1,3-(CMe3)2-ImCH) is imidazolium carbocation. The molecular structures of 1-4 were established by X-ray diffraction analyses and from the solid-state structures of 2-4, it was confirmed that, in all the compounds, zinc ions are coordinated through substituted phenolate group

Heavier alkaline earth metal complexes with phosphinoselenoic amides: Evidence of direct M-Se contact (M = Ca, Sr, Ba)

We report here a series of heavier alkaline earth metal complexes with a phosphinoselenoic amide ligand using two synthetic routes. In the first route, the heavier alkaline earth metal bis(trimethylsilyl)amides [M{N(SiMe 3)2}2(THF)n] (M = Ca, Sr, Ba) were treated with phosphinoselenoic amine [Ph2P(Se)NH(CHPh2)] (3), prepared by the treatment of bulky phosphinamines [Ph 2PNH(CHPh2)] (1) with elemental selenium in THF, and afforded homoleptic alkaline earth metal complexes of composition [M(THF) 2{Ph2P(Se)N(CHPh2)}2] (M = Ca (7), Sr (8), Ba (9)). The metal complexes 7-9 can also be obtained via salt metathesis route where the alkali metal phosphinoselenoic amides of composition [{(THF)2M'Ph2P(Se)N(CHPh2)}2] (M' = Na (5) and K (6)) were reacted with respective metal diiodides in THF at ambient temperature. The solid state structures of the alkali metal complexes 5-6 and alkaline earth metal complexes 7-9 were established by single crystal X-ray diffraction analysis. In the solid state, alkali metal complexes 5 and 6 are dimeric and form a poly-metallacyclic structural motif. In contrast, complexes 7-9 are monomeric and a direct metal-selenium bond is observed in each cas