Alternative Granulation Technique: Melt Granulation

A melt granulation process has been investigated (1, 2) which efficiently agglomerates pharmaceutical powders for use in both immediate- and sustained-release solid dosage forms. The process utilizes materials that are effective as granulating fluids when they are in the molten state. Cooling of the agglomerated powders and the resultant solidification of the molten materials completes the granulation process. Both the molten agglomeration and cooling solidification were accomplished in a high shear Collette Gral mixer equipped with a jacketed bowl. Hence, the melt granulation process replaces the conventional granulation and drying operations which use water or alcohol solutions. The melt granulation process has been investigated using immediate- and sustained-release TAVIST® (clemastine fumarate USP) tablet formulations. The TAVIST granulations have been characterized by power consumption monitoring, measurement of the granulation particle size distribution, bulk and tapped density determinations, and loss-on-drying measurements. Scale-up of the melt granulation process for the sustained release TAVIST tablet formulation was judged successful based on a comparison of the hardness, friability, weight uniformity during compression, disintegration time, and dissolution rate data obtained at different manufacturing scales.     

Nanocrystalline Pt-doped TiO2 thin films prepared by spray pyrolysis for hydrogen gas detection

Nanostructured pure and Pt-doped TiO₂ thin films were prepared by chemical spray pyrolysis technique. Aqueous solution of TiCl₃·6H₂O (0·01 M) was chosen as the starting solution for the preparation of pure TiO₂ thin film. Aqueous solutions of PtCl₆·6H₂O (0·01 M) and TiCl₃·6H₂O (0·01 M) were mixed in volume % of 1 : 99, 2·5 : 97·5 and 5 : 95 respectively to obtain Pt-doped TiO₂ thin films. The solutions were sprayed onto quartz substrate heated at 350 °C temperature to obtain the films. These thin films were fired for one hour at 550 °C. The sensing performance of these films was tested for various gases such as LPG, H₂, CO₂, ethanol, NH₃ and Cl₂ (1000 ppm). The Pt-doped TiO₂ (1 : 99) was observed to be most sensitive (572) to H₂ at 400 °C with high selectivity against other gases. Its response time was short (10 s) and recovery was also fast (14 s). To understand the reasons behind the gas-sensing performance of the films, their structural and microstructral properties were studied using X-ray diffraction and electron microscopy (FE–SEM and TEM), respectively. Thicknesses of all these samples were determined using Surface Profiler. The results are interpreted.     

High Power Factor Operation of a Three-Phase Rectifier for an Adjustable-Speed Drive

This paper presents a novel approach to improve the power factor (PF) and reduce the harmonics generated by an adjustable-speed drive (ASD). A high-frequency (HF) current injection technique is used to improve the PF and harmonic performance. The HF current at the same switching frequency (33 kHz) is injected into the input of a front-end rectifier from the output of an HF inverter. The main feature of the circuit is that it does not require any additional active devices for current injection. The inverter driving the induction motor is operated using a sinusoidal pulsewidth-modulation technique. The circuit simulation and experimental prototype results are presented for 67-hp (50 kW) and 3-hp three-phase induction motors, respectively.     

Liquid-Phase Hydrogenation of Benzene to Cyclohexene Using Ruthenium-Based Heterogeneous Catalyst

Selective hydrogenation of benzene to cyclohexene has been studied in a high pressure slurry reactor using supported ruthenium catalysts. The organic base monoethanolamine (MEA) was found to give better selectivities than the conventional inorganic salt additive (zinc sulphate). Parameters studied were the effects of various supports such as alumina, silica, titania, zirconia, niobium oxide, etc., benzene to water ratio, catalyst weight, and presence of cyclohexane in the feed. Reusability of the catalyst was also studied. © 1997 SCI.     

Antagonism of microRNA function in zebrafish embryos by using locked nucleic acid enzymes (LNAzymes)

MicroRNAs (miRNAs) have crucial functions in many cellular processes, such as differentiation, proliferation and apoptosis; aberrant expression of miRNAs has been linked to human diseases, including cancer. Tools that allow specific and efficient knockdown of miRNAs would be of immense importance for exploring miRNA function. Zebrafish serves as an excellent vertebrate model system to understand the functions of miRNAs involved in a variety of biological processes. We designed and employed a strategy based on locked nucleic acid enzymes (LNAzymes) for in vivo knockdown of miRNA in zebrafish embryos. We demonstrate that LNAzyme can efficiently knockdown miRNAs with minimal toxicity to the zebrafish embryos.     

Reliability based optimization in aeroelastic stability problems using polynomial chaos based metamodels

In this work, reliability based design optimization (RBDO) of two aeroelastic stability problems is addressed: (i) divergence, which arises in static aeroelasticity, and (ii) flutter, which arises in dynamic aeroelasticity. A set of design variables is considered as random variables, and the mean mass is minimized for a given set of constraints — including the probability of failure by divergence or flutter. The optimization process requires repeated evaluation of reliability, which is a major contributor to the total computational cost. To reduce this cost, a polynomial chaos expansion (PCE)-based metamodel is created over a grid in the parameter space. These precomputed PCEs are then interpolated for reliability calculation at intermediate points in the parameter space, as demanded by the optimization algorithm. Two new modifications are made to this method in this work. First, the Gauss quadrature rule is used — instead of statistical simulation — to estimate the chaos coefficients for higher computational speed. Second, to increase this computational gain further, a non-uniform grid is chosen instead of a uniform one, based on relative importance of the design parameters. This relative importance is found from a global sensitivity analysis. This new modified method is applied on a rectangular unswept cantilever wing model. For both optimization problems, it is observed that the proposed method yields accurate results with a considerable computational cost reduction, when compared to simulation based methods. The effect of grid spacing is also explored to achieve the best computational efficiency.     

Adaptive Neural Fuzzy Inference System for the Detection of Inter-Turn Insulation and Bearing Wear Faults in Induction Motor

The positive features of neural networks and fuzzy logic are combined together for the detection of stator inter-turn insulation and bearing wear faults in single-phase induction motor. The adaptive neural fuzzy inference systems (ANFISs) are developed for the detection of these two faults. These faults are created experimentally on a single-phase induction motor in the laboratory. The experimental data is generated for the five measurable parameters, viz, motor intakes current, speed, winding temperature, bearing temperature, and the noise of the machine. Earlier, the ANFIS fault detectors are trained for the two input parameters, i.e., speed and current, and the performance is tested. Later, the three remaining parameters are added and the five input ANFIS fault detector is trained and tested. It observed from the simulation results that the five input parameter system predicts more accurate results