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     

A design advisor for the optimal inspection of circularity tolerance

In the wake of growing importance for quality and the need to reduce inspection costs simultaneously, the need for a scientific method of selecting an optimum inspection strategy for coordinate measuring machine (CMM) based inspection has become very important. The inspection error resulting from CMM inspection is greatly affected by the profile irregularities and the sampling strategy, which includes sample size, sampling methods, and algorithms used for form evaluation. This paper describes a system that can recommend an optimal inspection plan based on the needs of the user. A design of experiments (DOE) based approach is used to relate the inspection error with sampling strategies. Surface irregularities are included in the form of lobes formed on the profile. A new two-way model is proposed that works in both directions between the sampling strategy and the performance metrics. The results indicate that the number of lobes and the sampling method used have little impact on the inspection error, while the sample size and form evaluation algorithms have a significant influence. An inspection plan advisor is presented, which provides an inspection plan based on the estimated shape and acceptable measurement error.     

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.     

Mechanical,electrical, and thermal expansion properties of carbon nanotube-based silver and silver-palladium alloy composites

The mechanical, electrical, and thermal expansion properties of carbon nanotube（CNT）-based silver and silver–palladium（10：1, w/w） alloy nanocomposites are reported. To tailor the properties of silver, CNTs were incorporated into a silver matrix by a modified molecular level-mixing process. CNTs interact weakly with silver because of their non-reactive nature and lack of mutual solubility. Therefore, palladium was utilized as an alloying element to improve interfacial adhesion. Comparative microstructural characterizations and property evaluations of the nanocomposites were performed. The structural characterizations revealed that decorated type-CNTs were dispersed, embedded, and anchored into the silver matrix. The experimental results indicated that the modification of the silver and silver–palladium nanocomposite with CNT resulted in increases in the hardness and Young＇s modulus along with concomitant decreases in the electrical conductivity and the coefficient of thermal expansion（CTE）. The hardness and Young＇s modulus of the nanocomposites were increased by 30%？40% whereas the CTE was decreased to 50%-60% of the CTE of silver. The significantly improved CTE and the mechanical properties of the CNT-reinforced silver and silver–palladium nanocomposites are correlated with the intriguing properties of CNTs and with good interfacial adhesion between the CNTs and silver as a result of the fabrication process and the contact action of palladium as an alloying element.     

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.     

Learning Noise-Assisted Robust Image Features for Fine-Grained Image Retrieval

Fine-grained image search is one of the most challenging tasks in computer vision that aims to retrieve similar images at the fine-grained level for a given query image. The key objective is to learn discriminative fine-grained features by training deep models such that similar images are clustered, and dissimilar images are separated in the low embedding space. Previous works primarily focused on defining local structure loss functions like triplet loss, pairwise loss, etc. However, training via these approaches takes a long training time, and they have poor accuracy. Additionally, representations learned through it tend to tighten up in the embedded space and lose generalizability to unseen classes. This paper proposes a noise-assisted representation learning method for fine-grained image retrieval to mitigate these issues. In the proposed work, class manifold learning is performed in which positive pairs are created with noise insertion operation instead of tightening class clusters. And other instances are treated as negatives within the same cluster. Then a loss function is defined to penalize when the distance between instances of the same class becomes too small relative to the noise pair in that class in embedded space. The proposed approach is validated on CARS-196 and CUB-200 datasets and achieved better retrieval results (85.38% recall@1 for CARS-196% and 70.13% recall@1 for CUB-200) compared to other existing methods.