Line-source modeling and estimation with magnetoencephalography

We propose a number of source models that are spatially distributed on a line for magnetoencephalography (MEG) using both a spherical head with radial sensors for more efficient computation and a realistic head model for more accurate results. We develop these models with increasing degrees of freedom, derive forward solutions, maximum-likelihood (ML) estimates, and Cramér-Rao bound (CRB) expressions for the unknown source parameters. A model selection method is applied to select the most appropriate model. We also present numerical examples to compare the performances and computational costs of the different models, to determine the regions where better estimates are possible and when it is possible to distinguish between line and focal sources. We demonstrate the usefulness of the proposed line-source models over the previously available focal source model in certain distributed source cases. Finally, we apply our methods to real MEG data, the N2O response after electric stimulation of the median nerve known to be an extended source.     

Relative importance of Al(V) and reinforcement to the flexural strength of geopolymer composites

We prepared 1 cm × 1 cm × 10 cm geopolymer bars from sodium silicate and six commercial metakaolins, both unreinforced and reinforced with 20 wt% of 55-μm wollastonite (CaO·SiO₂) needles, to evaluate the relative contributions of five-coordinated aluminum in the metakaolin and the presence of a reinforcing phase to the flexural strength of geopolymers. Two metakaolins, with about 20 at% and lower of five-coordinated aluminum content, did not react sufficiently with our processing method and could not be tested. The flexural strengths of the other four geopolymers were similar at about 11–14 MPa unreinforced and 22–29 MPa reinforced. The effect of reinforcement on flexure strength is more significant than the choice of metakaolin provided that the metakaolin is reactive. The geopolymerization reaction depends on the amount of five-coordinated aluminum present in the metakaolin and is the primary difference between the samples that reacted and those that did not react.     

Quantum-well infrared photodetector structure synthesis: methodology and experimental verification

A numerical method for global optimization of quantum-well infrared photodetector (QWIP) performance parameters is presented and experimentally verified. The single-band effective-mass Schroedinger equation is solved by employing the argument principle method (APM) to extract both the bound and quasibound eigen-energies of the quantum heterostructure. APM is combined with a simulated annealing algorithm to determine a set of device design parameters such as potential barrier height V/sub i/, layer thickness d/sub i/, number of material layers N, total device length, applied bias V/sub Bias/ etc., for which the QWIP performance is within a predetermined convergence criterion. The method presented incorporates the effect of energy-dependent effective mass of electrons in nonparabolic conduction bands. The present model can handle many optimization parameters and can incorporate fabrication constraints to achieve physically realizable devices. In addition, the method is not limited to the optimization of absorption structures, and can be used for other intersubband devices such as electron-wave Fabry-Perot filters and quantum-cascade lasers. The strength and versatility of the present method are demonstrated by the design of a bicolor equal-absorption-peak QWIP structure, and experimental verification of the zero-bias absorption spectrum is presented.     

Fatigue and microstructural properties of quenched Ti- 6Al- 4V

The mechanical properties and microstructures of Ti-6A1-4V were determined for specimens heat treated at temperatures from 843 °C to 1065 °C for 10 minutes and water quenched; these properties were compared with those of α-β annealed specimens. Specimens heat treated at 900 °C and water quenched had higher fatigue lives by a factor of four to ten relative to the other treatments; in addition, this treatment resulted in high ductility, yield strength, tensile strength, and elastic modulus. Micro-structure studies utilizing optical and transmission microscopy showed that the improved fatigue lives were a result of a strain induced transformation of retained β to martensite. The amount of retainedβ and its relative stability were shown to depend upon the heat treatment temperature. The lower the heat treatment temperature below theβ transus the smaller the amount ofβ phase present before the quench and the richer theβ phase inβ stabilizer. The greater the concentration ofβ stabilizer in theβ phase the greater the probability that theβ phase was retained. High heat treatment temperatures resulted in a greater amount ofβ that was less stable and more probable to transform to martensite during a water quench.     

Expression of a gene encoding chitinase (pCA 8 ORF) from Aeromonas sp. no. 10S-24 in Escherichia coli and enzyme characterization

A gene encoding chitinase from Aeromonas sp. no. 10S-24 was expressed using pTrc99A in Escherichia coli JM 105 which yielded a 5-fold higher activity than when pUC19 was used. Three different truncated enzymes (SA-1, SA-2 and SA-3) were obtained after purification. Their isoelectric points were 7.0, 6.9, and 6.7, respectively. The enzymes showed two optimum pHs, 4.0 and 7.0, when incubated with ethylene glycol chitin as the substrate, and were stable over a wide pH range (3.0–9.0). The optimum temperature was 60°C and the enzymes were stable up to 50°C. The chitinases exhibited wide substrate specificities for chitin-related compounds.     

A novel approach for measuring hyperspectral similarity

Hyperspectral measures are used to capture the degree of similarity between two spectra. Spectral angle mapper (SAM) is an example of such measures. SAM similarity values range from 0 to 1. These values do not indicate whether the two spectra are similar or not. A static similarity threshold is imposed to recognize similar and dissimilar spectra. Adjusting such threshold is a troublesome process. To overcome this problem, the proposed approach aims to develop learnable hyperspectral measures. This is done through using hyperspectral measures values as similarity patterns and employing a classifier. The classifier acts as an adaptive similarity threshold. The derived similarity patterns are flexible, as they are able to capture the specific notion of similarity that is appropriate for each spectral region. Two similarity patterns are proposed. The first pattern is the cosine similarity vector for the second spectral derivative pair. The second pattern is a composite vector of different similarity measures values. The proposed approach is applied on full hyperspectral space and subspaces. Experiments were conducted on a challenging benchmark dataset. Experimental results showed that, classifications based on second patterns were far better than first patterns. This is because first patterns were concerned only with the geometrical features of the spectral signatures, while second patterns combined various discriminatory features such as: orthogonal projections information, correlation coefficients, and probability distributions produced by the spectral signatures. The proposed approach results are statistically significant. This implies that using simple learnable measures outperforms complex and manually tuned techniques used in classification.     

Emulsion stability of clove oil in chitosan and sodium alginate matrix

Clove oil was emulsified in 1% w/w chitosan (CC emulsions) and 2.5% w/w sodium alginate matrix (CA emulsions) containing Tween 80 as the surfactant. Different homogenization speeds (5,000, 10,000, 15,000 and 20,000 rpm) were used to produce the emulsions, and the stability of the emulsions during storage (29 days) was determined. The stability of the emulsions containing clove oil prior to the solidification process was assessed when chitosan and sodium alginate were used as encapsulating materials. Different homogenization speeds resulted in polydisperse emulsions with a size of 2–3 μm and 90% of stability after 29 days of storage. Different homogenization speeds did not significantly affect the concentrations of the active compounds contained in the emulsions. However, these concentrations changed significantly after 29 days of storage when sodium alginate was used to make the emulsions and the homogenization speeds were ≥ 10,000 rpm. High temperature caused by the high viscosity of the solution and high energy dissipation during homogenization suggested that the emulsions composed of sodium alginate were unstable. Chitosan enabled a longer processing time during the clove oil encapsulation process compared to sodium alginate, when emulsification by homogenization was used. The stability of the emulsion of the clove oil-in-chitosan matrix prior to the solidification step was superior.     

Synchrotron X-ray absorption fine structure study and dielectric performance of Li0.5Fe2.5O4/BaTiO3 multiferroic

Journal of Materials Science: Materials in Electronics - Multiferroic nanocomposites (1?y)Li0.5Fe2.5O4/(y)BaTiO3 (y?=?0.0, 0.2, 0.4, 0.6, 0.8, and1.0) were synthesized by modified...     

Group Sparse Representation Approach for Recognition of Cattle on Muzzle Point Images

The usage of computer vision adds a new paradigm in the field of animal biometric, and has recently received more attention due to the growing importance of identification and tracking of animal species or individual animals. Biometric characteristics help to develop a better representation and a better identification of different animal species and individual animals. In this work, we propose an effective approach for automatic cattle recognition based on the multiple features of muzzle points and the cattle face images. The proposed method deals the cattle recognition problem as a classification problem among the multiple linear regression models and provides a new theory for the recognition of individual cattle. The group sparse signal representation based classification offers the key to addressing this problem using L2-minimization. In this paper, a comparative study among the well-established handcrafted texture feature extraction techniques and the appearance-based feature extraction techniques is also presented. A detailed set of experimental results on muzzle point image database is also carried to prove the theory. Our method has achieved 93.87% identification accuracy which demonstrates the superiority of the proposed method than the other existing machine learning based recognition algorithms.