Control of calcium hexaluminate grain morphology in in-situ toughened ceramic composites

The influence of processing conditions on the morphology of calcium hexaluminate (CA₆) grains in Al₂O₃: 30 vol% CaO·6Al₂O₃ (CA₆) ceramic composites was investigated. Specimens were prepared by in-situ reaction sintering using precursor powders of alumina, and either calcium carbonate or calcium oxide. In some samples, 1 vol% anorthite glass was added as a sintering aid. X-ray diffraction was used to study the phase development in the as-calcined and sintered states. The resultant microstructures were characterized using both scanning electron microscopy (SEM), and imaging secondary ion mass spectrometry (SIMS). It was found that the CA₆ grains developed a platelike morphology when CaCO₃ was used as the starting calcium-rich powder. In contrast, samples prepared using CaO resulted in equiaxed CA₆ grains. This result was observed to be independent of the anorthite glass addition. The findings are rationalized in terms of distinct CA₆ reaction mechanisms, resulting from differences in the reactivity of the powders during the early stages of calcining.Cement Nomenclature C CaO - A Al₂O₃     

Synthesis and characterization of acidic properties of Al-SBA-15 materials with varying Si/Al ratios

Al-SBA-15 of varying Si/Al ratios in the range 11.4–78.4 was synthesized using tri-block copolymer P123. The calcined materials were examined by XRD, pore size distribution, surface area, ²⁷Al NMR spectroscopy. The acidity and acid strength distribution were studied using microcalorimetric adsorption of NH₃. The acidic properties were also examined by cumene cracking reaction as a function of Si/Al ratios. Systematic variation of acidity and activity was observed as a function of Si/Al ratio. The initial heats of NH₃ adsorption correlated well with activity indicate that acid sites with ΔH > 100 kJ/mole is responsible for cumene cracking activity. Linear correlations were obtained with total acidity and cumene cracking activities. The tetrahedral aluminum was found to be responsible for the observed acidities and catalytic activities.     

Plumbagin,a Biomolecule with (Anti)Osteoclastic Properties

Plumbagin is a plant-derived naphthoquinone that is widely used in traditional Asian medicine due to its anti-inflammatory and anti-microbial properties. Additionally, plumbagin is cytotoxic for cancer cells due to its ability to trigger reactive oxygen species (ROS) formation and subsequent apoptosis. Since it was reported that plumbagin may inhibit the differentiation of bone resorbing osteoclasts in cancer-related models, we wanted to elucidate whether plumbagin interferes with cytokine-induced osteoclastogenesis. Using C57BL/6 mice, we unexpectedly found that plumbagin treatment enhanced osteoclast formation and that this effect was most pronounced when cells were pre-treated for 24 h with plumbagin before subsequent M-CSF/RANKL stimulation. Plumbagin caused a fast induction of NFATc1 signalling and mTOR-dependent activation of p70S6 kinase which resulted in the initiation of protein translation. In line with this finding, we observed an increase in RANK surface expression after Plumbagin stimulation that enhanced the responsiveness for subsequent RANKL treatment. However, in Balb/c mice and Balb/c-derived RAW264.7 macrophages, these findings could not be corroborated and osteoclastogenesis was inhibited. Our results suggest that the effects of plumbagin depend on the model system used and can therefore either trigger or inhibit osteoclast formation.     

Morphological and microchemical phenomena in the high-temperature oxidation of binary Al-Li alloys

The high-temperature oxidation behavior of binary Al-Li alloys has been characterized by scanning electron microscopy and secondary ion mass spectrometry in order to understand the mechanism of rapid oxidation in these alloys and to correlate the oxide morphology to its microchemistry. The oxide scale developed on polished specimens during short exposures in air at 530°C shows characteristic nodules that usually nucleate at grain boundaries. Examination of the alloy surface after removal of the oxide layer shows that the initial growth of the oxide nodules occurs laterally in addition to thickening normal to the oxide/alloy interface. Microchemical analysis of the oxide film with a scanning ion microprobe reveals a thick Li-oxide layer at the oxide/gas interface indicating preferential oxidation of Li at the free surface; the rest of the oxide film is composed of both Al- and Li-rich oxides, probably Li₂O and LiAlO₂ The presence of trace impurities (K, Na, F, and Cl) in the oxide scale was also detected. A microstructural model for the development of the oxide film in the Al-Li system is presented on the basis of both morphological and microanalytical data obtained in this study; this new model is compared with existing models.     

Text-dependent speaker verification using classical LBG,adaptive LBG and FCM vector quantization

An important task of speaker verification is to generate speaker specific models and match an input speaker’s utterance with these models. This paper focuses on comparing the performance of text dependent speaker verification system using Mel Frequency Cepstral Coefficients feature and different Vector Quantization (VQ) based speaker modelling techniques to generate the speaker specific models. Speaker-specific information is mainly represented by spectral features and using these features we have developed the model which serves as an important entity for determining the claimed identity of the speaker. In the modelling part, we used Linde, Buzo, Gray (LBG) VQ, proposed adaptive LBG VQ and Fuzzy C Means (FCM) VQ for generating speaker specific model. The experimental results that are performed on microphonic database shows that accuracy significantly depends on the size of the codebook in all VQ techniques, and on FCM VQ accuracy also depend on the value of learning parameter of the objective function. Experiment results shows that how the accuracy of speaker verification system is depend on different representations of the codebook, different size of codebook in VQ modelling techniques and learning parameter in FCM VQ.     

Experimental investigation of impact of diesel particulate filter on smoke and NO<Subscript>x</Subscript> emissions of a Euro-I compression ignition engine with active and off-board regeneration

Old engines (Euro III or earlier) produce more emissions, and it will be difficult to entirely stop their usage especially in developing and under-developed nations; hence, it is desired that appropriate emission reduction technologies are tested on such engines to analyze their feasibility and economical acceptability. While most such studies have been conducted on constant speed stationary engines and modern engines, this study tried to analyze the effectiveness of an uncoated wall-flow type ceramic diesel particulate filter on a Euro-I, water-cooled, direct injection, variable speed, compression ignition engine in a laboratory set-up in India. Also, this study focused on diesel particulate filter regeneration by two methods: active regeneration by diesel injection in the particulate filter using an electronic control unit and off-board regeneration by taking out and heating the diesel particulate filter in an electrical resistance furnace at 650 °C for 10 h. The results, in the form of smoke emission, NO_x emission and engine performance, obtained using both the regeneration methods were analyzed, and conclusions were drawn. It was found that using diesel particulate filter, particulate matter emissions (smoke) were almost entirely eliminated. It was also found that off-board regeneration had numerous advantages compared to active regeneration. Since a furnace would be needed for off-board regeneration, an exchange process for diesel particulate filter is suggested.     

Robust kernelized approach to clustering by incorporating new distance measure

A new data clustering algorithm Density oriented Kernelized version of Fuzzy c-means with new distance metric (DKFCM-new) is proposed. It creates noiseless clusters by identifying and assigning noise points into separate cluster. In an earlier work, Density Based Fuzzy C-Means (DOFCM) algorithm with Euclidean distance metric was proposed which only considered the distance between cluster centroid and data points. In this paper, we tried to improve the performance of DOFCM by incorporating a new distance measure that has also considered the distance variation within a cluster to regularize the distance between a data point and the cluster centroid. This paper presents the kernel version of the method. Experiments are done using two-dimensional synthetic data-sets, standard data-sets referred from previous papers like DUNN data-set, Bensaid data-set and real life high dimensional data-sets like Wisconsin Breast cancer data, Iris data. Proposed method is compared with other kernel methods, various noise resistant methods like PCM, PFCM, CFCM, NC and credal partition based clustering methods like ECM, RECM, CECM. Results shown that proposed algorithm significantly outperforms its earlier version and other competitive algorithms.