Vapor pressures and osmotic coefficients of the acetone solutions of three bis(tetraalkylammonium)tetrathiomolybdates at 298.15 K measured by head-space gas chromatography

The vapor pressures and osmotic coefficients of solutions of (R₄N)₂[MoS₄] (R = ethyl, n-propyl and n-butyl) in acetone have been measured by head space-gas chromatography (HS-GC). Experimental data for the osmotic coefficients have been expressed by three thermodynamic models including the ionic interaction model of Pitzer, the electrolyte non-random two liquid (e-NRTL) model and the non-random factor (NRF) model. The ability of the models to fit the osmotic coefficient was compared on the basis of the standard deviation of the fittings. The results show that the considered models provide reliable results, but the Pitzer's model gives better results than the NRTL and the NRF methods, especially in the dilute region.     

Improving the neural network method for finite element model updating using homogenous distribution of design points

In developing a neural network technique for a finite element model updating, researchers have been shown that the number of training samples and their quality, significantly affect the accuracy of the NN predication. In this study, based on the genetic algorithm (GA) method, we reduce the number of analyses required to develop the training pairs and reduce the amount of time for training the NN. In the other words, a uniform distribution of design points inside the design space will be obtained by means of this approach. To validate the efficiency of GA sample selection, random generation (RG) method is used for comparison. Two comparisons are made based on a numerical and experimental example. One is updated from 10 degrees of freedom lumped parameters system and the other is updated from a free–free beam using test data. The results indicate that the GA sample selection can reduce the number of training samples without affecting the accuracy of the NN predication. In our present study, also, the advantages of using frequency response function (FRF) data as input to the NN are kept and the drawback of having too many frequency points is overcome by the application of principal component analyses (PCA).     

Graphical Representations of Speed: Obstacles Preservice K‐8 Teachers Experience

This study examines the difficulties college students experience when creating and interpreting graphs in which speed is one of the variables. Nineteen students, all preservice elementary or middle school teachers, completed an upper‐level course exploring algebraic concepts. Although all of these preservice teachers had previously completed several mathematics courses, including calculus, they demonstrated widespread misconceptions about the variable speed. This study identifies four cognitive obstacles held by the students, provides excerpts of their graphical constructions and verbal interpretations, and discusses potential causes for the confusion. In particular, misconceptions arose when students interpreted the behavior and nature of speed within a graphical context, as well as in situations where they were required to construct a graph involving speed as a variable. The study concludes by offering implications for the teaching and learning of speed and its interpretation within a graphical setting.     

Copper and iron interactions with angiotensin-converting enzyme inhibitors. A study by fast-atom bombardment tandem mass spectrometry

Fast atom bombardment, combined with high-energy collision-induced tandem mass spectrometry, has been used to investigate gas-phase metal-ion interactions with captopril, enalaprilat and lisinopril, all angiotensin-converting enzyme inhibitors.Suggestions for the location of metal-binding sites are presented. For captopril, metal binding occurs most likely at both the sulphur and the nitrogen atom. For enalaprilat and lisinopril, binding preferably occurs at the amine nitrogen. Copyright 1999 John Wiley & Sons, Ltd.     

An efficient method for nonlinear aeroelasticy of slender wings

This paper aims the nonlinear aeroelastic analysis of slender wings using a nonlinear structural model coupled with the linear unsteady aerodynamic model. High aspect ratio and flexibility are the specific characteristic of this type of wings. Wing flexibility, coupled with long wingspan can lead to large deflections during normal flight operation of an aircraft; therefore, a wing in vertical/forward-afterward/torsional motion using a third-order form of nonlinear general flexible Euler–Bernoulli beam equations is used for structural modeling. Unsteady linear aerodynamic strip theory based on the Wagner function is used for determination of aerodynamic loading on the wing. Combining these two types of formulation yields nonlinear integro-differentials aeroelastic equations. Using the Galerkin’s method and a mode summation technique, the governing equations will be solved by introducing a numerical method without the need to adding any aerodynamic state space variables and the corresponding equations related to these variables of the problem. The obtained equations are solved to predict the aeroelastic response of the problem. The obtained results for a test case are compared with those of some other works and show a good agreement between results.     

Supercontinuum generation with femtosecond optical pulse compression in silicon photonic crystal fibers at 2500 nm

In this paper, femtosecond optical pulses compression and supercontinuum generation in a triangular silicon photonic crystal fiber at 2500 nm are investigated. A region of large minimum anomalous group velocity dispersion, negligible higher order dispersions and unique nonlinearity of silicon are used to demonstrate compression of 100 fs initial input optical pulses to 2.5 fs and ultra-broadband supercontinuum generation with very low input pulse energy over short distances of the fiber.     

Synthesis and characterization of copper(II) complexes incorporating pyrazolyl-derived N,S-donor bidentate ligands

The novel bidentate N,S-donor anionic ligands [PhNCSIndz]^?, [PhNCSImz]^?, [PhNCSPz^Me3]^?, and [EtNCSPz]^?, where Indz?=?indazole, Imz?=?imidazole, Pz^Me3?=?3,4,5-trimethylpyrazole, and Pz?=?pyrazole, were synthesized and used to prepare Cu(II) complexes of general formula [Cu(N^S)₂]. The ligands were synthesized via direct addition of phenylisothiocyanate or ethylisothiocyanate into THF suspensions of the corresponding sodium-pyrazolate salts. All of the synthesized compounds, including the ligands and the complexes, were characterized by physico-chemical and spectroscopic methods, and crystal structures of [Cu(EtNCSPz)₂] and [Cu(PhNCSPz^Me2)₂] were determined by X-ray diffraction analysis, showing a trans-square planar geometry for [Cu(EtNCSPz)₂] and a distorted tetrahedral geometry for [Cu(PhNCSPz^Me2)₂].     

Unreliable Transfer Lines: Decomposition/Aggregation and Optimization

Complexity has been a long standing obstacle to efficient buffer assignment in transfer lines. For fixed buffer sizes, an approximate transfer line decomposition/aggregation algorithm is developed and its ability to predict line performance is demonstrated via Monte-Carlo simulations. It equates the line with a collection of isolated, unreliable multi-state machines with recursively related statistical parameters. For scalability enhancement, state merging is used to reduce the number of machine states from up to 6 down to 2. An efficient dynamic programming based buffering optimization algorithm which minimizes a combined measure of storage and backlog costs in the transfer line is then presented. Numerical results and comparisons with alternative algorithms are reported.