Effect of photoaligning azo dye structure on liquid crystal anchoring energy

A method of controlling anchoring energy of surface interaction of liquid crystal photoaligning substances is considered to enhance the liquid crystal display performances. An important parameter of the dye's molecular structure that determines the ratio of polar and azimuthal anchoring energy is the ability to form dimers. The values of dimerization thermodynamic potentials have been found. The probability of the formation of dye molecules dimers is evaluated. The bonds conjugation transfer via intermolecular hydrogen bond is revealed, and anisotropy of polarizability of the hydrogen bond is evaluated. The effect of dimerization on polar and azimuthal anchoring energy of liquid crystal — azo dye system — is shown.     

Aggregate‐induced emission in light‐emitting liquid crystal display technology

Nowadays, liquid crystal displays (LCDs) with light‐emission are considered as energy‐efficient devices and are promising alternatives to conventional LCDs. To realize such possibility, strong fluorescent materials with a dichroic properties are required. Aggregate‐induced emission (AIE) is an unusual photophysical phenomenon shown by some luminogenic materials that will be highly emissive in their aggregate state. In this work, we studied the AIE effect of a luminescent liquid crystalline molecule TPE‐PPE in our LC system as a luminophore dopant. The result showed the excellent AIE effect that higher concentration of luminogen in the nematic LC host induced stronger luminescent intensity. Through exposure of a photoisomeriable alignment material sulfonic‐dye‐1, the photopatterning of a light‐emitting LC device was achieved with the use of the TPE‐PPE/nematic LC mixture.     

Ferroelectric liquid crystals: Excellent tool for modern displays and photonics

The ferroelectric liquid crystals, because of their fast electro‐optical response, are one of the most important classes of liquid crystals. Here, in this review, we have summarized the different electro‐optical modes for ferroelectric liquid crystals. Clark–Lagerwall effect (surface stabilized ferroelectric liquid crystal), deformed helix ferroelectric (DHF) effect, electrically suppressed helix (ESH) mode, DHF orientational Kerr effect, and ESH diffraction modes have been discussed. All of the crucial features, that is, optics, electro‐optics, dynamics, and their dependence on material parameters, operational regime, and applications, have been reviewed.     

Investigation of the structure of supersonic nitrogen microjets

Results of research on microjets escaping into an ambient space from nozzles with diameters of 341–10.4 μm are described. A special Pitot microtube is used for studying the structure of supersonic microjets. The main feature of this microtube is a small diameter of the intake hole (12 μm). The main parameters of supersonic underexpanded microjets are identified, including the size of shock cells and the supersonic core length of the microjet. The results show a significant increase in the supersonic core length of microjets compared to macrojets. The Reynolds numbers of the laminar–turbulent transition in microjets are found to be in the range of 1,100–2,100. In addition, a classification of supersonic underexpanded axisymmetric microjets escaping into the ambient space is proposed.     

On the Easy Use of Scientific Computing Services for Large Scale Linear Algebra and Parallel Decision Making with the P-Grade Portal

Scientific research is becoming increasingly dependent on the large-scale analysis of data using distributed computing infrastructures (Grid, cloud, GPU, etc.). Scientific computing (Petitet et al. 1999) aims at constructing mathematical models and numerical solution techniques for solving problems arising in science and engineering. In this paper, we describe the services of an integrated portal based on the P-Grade (Parallel Grid Run-time and Application Development Environment) portal (http://www.p-grade.hu) that enables the solution of large-scale linear systems of equations using direct solvers, makes easier the use of parallel block iterative algorithm and provides an interface for parallel decision making algorithms. The ultimate goal is to develop a single sign on integrated multi-service environment providing an easy access to different kind of mathematical calculations and algorithms to be performed on hybrid distributed computing infrastructures combining the benefits of large clusters, Grid or cloud, when needed.     

Approximation algorithm for coloring of dotted interval graphs

Dotted interval graphs were introduced by Aumann et al. [Y. Aumann, M. Lewenstein, O. Melamud, R. Pinter, Z. Yakhini, Dotted interval graphs and high throughput genotyping, in: ACM-SIAM Symposium on Discrete Algorithms, SODA 2005, pp. 339-348] as a generalization of interval graphs. The problem of coloring these graphs found application in high-throughput genotyping. Jiang [M. Jiang, Approximating minimum coloring and maximum independent set in dotted interval graphs, Information Processing Letters 98 (2006) 29-33] improves the approximation ratio of Aumann et al. [Y. Aumann, M. Lewenstein, O. Melamud, R. Pinter, Z. Yakhini, Dotted interval graphs and high throughput genotyping, in: ACM-SIAM Symposium on Discrete Algorithms, SODA 2005, pp. 339-348]. In this work we improve the approximation ratio of Jiang [M. Jiang, Approximating minimum coloring and maximum independent set in dotted interval graphs, Information Processing Letters 98 (2006) 29-33] and Aumann et al. [Y. Aumann, M. Lewenstein, O. Melamud, R. Pinter, Z. Yakhini, Dotted interval graphs and high throughput genotyping, in: ACM-SIAM Symposium on Discrete Algorithms, SODA 2005, pp. 339-348]. In the exposition we develop a generalization of the problem of finding the maximum number of non-attacking queens on a triangle.     

Boosted Bayesian network classifiers

The use of Bayesian networks for classification problems has received a significant amount of recent attention. Although computationally efficient, the standard maximum likelihood learning method tends to be suboptimal due to the mismatch between its optimization criteria (data likelihood) and the actual goal of classification (label prediction accuracy). Recent approaches to optimizing classification performance during parameter or structure learning show promise, but lack the favorable computational properties of maximum likelihood learning. In this paper we present boosted Bayesian network classifiers, a framework to combine discriminative data-weighting with generative training of intermediate models. We show that boosted Bayesian network classifiers encompass the basic generative models in isolation, but improve their classification performance when the model structure is suboptimal. We also demonstrate that structure learning is beneficial in the construction of boosted Bayesian network classifiers. On a large suite of benchmark data-sets, this approach outperforms generative graphical models such as naive Bayes and TAN in classification accuracy. Boosted Bayesian network classifiers have comparable or better performance in comparison to other discriminatively trained graphical models including ELR and BNC. Furthermore, boosted Bayesian networks require significantly less training time than the ELR and BNC algorithms.     

Multistable electro‐optical modes in ferroelectric liquid crystals

Abstract— Multistable electro‐optical modes exist under certain conditions in ferroelectric liquid‐crystal (FLC) cells, which means that any light‐transmission level can be memorized after the driving voltage is switched off. The multistability is responsible for three new electro‐optical modes with different shapes of the gray‐scale curve that can be either S‐shaped (double or single dependent upon the applied‐voltage pulse sequence and boundary conditions) or V‐shaped dependent upon boundary conditions and FLC cell parameters. The origin of these modes will be described.     

The differences in underground mines dewatering with the application of caving or backfilling mining methods

Zambia Consolidated Copper Mines Ltd. (ZCCM) is planning a substantial increase in ore production in several of their underground mines on the Zambian Copperbelt over the next 10 years. The future production strategy is based on development of productive and economic mining methods through the application of mechanization and backfilling. Mechanization is designed to provide the production capability and the backfilling is designed to reduce water inflow into the mines. A similar trend can be seen in world-wide changes in mining methods from open stoping and sub-level caving to cut-and-fill stoping. Backfill is being employed worldwide, including in Australia, Canada, Sweden, Latin America, Zambia, and the U.S.A. Plans for backfill mining methods are underway for future operations in Chile, Canada, Zambia, and Mexico. The principal reasons for these changes in mining methods are twofold:

? Increased ore recovery, and

? Decreased environmental impact.

The main difference in the environmental impacts between mining with sub-level caving or open stoping and mining with backfilling methods is the reduction in subsidence or the potential for subsidence. Backfilling reduces ground movements in the rock overlying and adjacent to mine openings as well as subsidence at the surface. Reduced ground movement decreases the number and size of fracture-controlled hydraulic flow paths into a mine and, thereby, the impact of mining on surface and ground water resources. This paper deals with: 1) The impacts caused by open stoping and sub-level caving in comparison to backfilling methods; 2) The approximate impact of backfill on dewatering strategies, and; 3) The environmental benefits of backfill mining. The differences in mine drainage strategies are supported by case histories from various mines.