Polyamide-6,6/in situ silica hybrid nanocomposites by sol-gel technique: synthesis, characterization and properties

The organic-inorganic hybrid nanocomposites comprising of poly(iminohexamethyleneiminoadipoyl), better known as Polyamide-6,6 (abbreviated henceforth as PA66), and silica (SiO₂) were synthesized through sol-gel technique at ambient temperature. The inorganic phase was generated in situ by hydrolysis-condensation of tetraethoxysilane (TEOS) in different concentrations, under acid catalysis, in presence of the organic phase, PA66, dissolved in formic acid. Infrared (IR) spectroscopy was used to monitor the microstructural evolution of the silica phase in the PA66 matrix. Wide angle X-ray scattering (WAXS) studies showed that the crystallinity in PA66 phase decreased with increasing silica content. Atomic force microscopy (AFM) of the nanocomposite films revealed the dispersion of SiO₂ particle with dimensions of <100 nm in the form of network as well as linear structure. X-ray silicon mapping further confirmed the homogeneous dispersion of the silica phase in the bulk of the organic phase. The melting peak temperatures slightly decreased compared to neat PA66, while an improvement in thermal stability by about 20 °C was achieved with hybrid nanocomposite films, as indicated by thermogravimetric analysis (TGA). Dynamic mechanical analysis (DMA) exhibited significant improvement in storage modulus (E′) for the hybrid nanocomposites over the control specimen. An increase in Young's modulus and tensile strength of the hybrid films was also observed with an increase in silica content, indicating significant reinforcement of the matrix in the presence of nanoparticles. Some properties of the in situ prepared PA66-silica nanocomposites were compared with those of conventional composites prepared using precipitated silica as the filler by solution casting from formic acid.     

Welfare of calves - 2. Increase in vertebral artery blood flow following exsanguination by neck sticking and evaluation of chest sticking as an alternative slaughter method

The role of the vertebral arteries in delaying loss of sensibility following neck sticking in slaughter calves was investigated. Vertebral artery blood flow was measured using probes before, during and after electrical stunning and slaughter. Systemic blood pressure, electrocorticogram, visually evoked responses and the occurrence of carotid occlusions were also recorded. When carotid occlusion occurred, the time to onset of brain failure was delayed based on the development of an isoelectric state. In addition, when carotid occlusion occurred the mean arterial blood pressure was sustained for longer following slaughter, and concurrently vertebral artery blood flow could be maintained at about 30% of its initial level for up to 3 min. In some animals vertebral artery flow increased substantially following sticking. When chest sticking was used no occlusion of vessels occurred, mean arterial blood pressure fell promptly (within 8 s) and the onset of an isoelectric state did not extend beyond one minute. In addition, visually evoked responses were not present after 5 s following chest sticking.     

Classification Based on Hybridization of Parametric and Nonparametric Classifiers

Parametric methods of classification assume specific parametric models for competing population densities (e.g., Gaussian population densities can lead to linear and quadratic discriminant analysis) and they work well when these model assumptions are valid. Violation in one or more of these parametric model assumptions often leads to a poor classifier. On the other hand, nonparametric classifiers (e.g., nearest-neighbor and kernel-based classifiers) are more flexible and free from parametric model assumptions. But, the statistical instability of these classifiers may lead to poor performance when we have small numbers of training sample observations. Nonparametric methods, however, do not use any parametric structure of population densities. Therefore, even when one has some additional information about population densities, that important information is not used to modify the nonparametric classification rule. This paper makes an attempt to overcome these limitations of parametric and nonparametric approaches and combines their strengths to develop some hybrid classification methods. We use some simulated examples and benchmark data sets to examine the performance of these hybrid discriminant analysis tools. Asymptotic results on their misclassification rates have been derived under appropriate regularity conditions.     

A steerable complex wavelet construction and its application to image denoising.

This work addresses the design of a novel complex steerable wavelet construction, the generation of transform-space feature measurements associated with corner and edge presence and orientation properties, and the application of these measurements directly to image denoising. The decomposition uses pairs of bandpass filters that display symmetry and antisymmetry about a steerable axis of orientation. While the angular characterization of the bandpass filters is similar to those previously described, the radial characteristic is new, as is the manner of constructing the interpolation functions for steering. The complex filters have been engineered into a multirate system, providing a synthesis and analysis subband filtering system with good reconstruction properties. Although the performance of our proposed denoising strategy is currently below that of recently reported state-of-the-art techniques in denoising, it does compare favorably with wavelet coring approaches employing global thresholds and with an "Oracle" shrinkage technique, and presents a very promising avenue for exploring structure-based denoising in the wavelet domain.     

Properties of a consistent estimation procedure in ultrastructural model when reliability ratio is known

To overcome the problem of inconsistency of the ordinary least squares (OLS) estimators for regression coefficients in a linear measurement error model, we assume the reliability ratio to be known a priori and utilize this information to form consistent estimators in an ultrastructural models. Assuming the distributions of measurement errors and the random error component to be not necessarily normal, the efficiency properties of the estimator for slope parameter have been analysed and the effect of departure from normality is examined.     

Fabrication, Microstructural Characterization, and Mechanical Properties of Polycrystalline t'-Zirconia

Large-grained (100- to 200-μm), yttria-doped, polycrystalline t '-zirconia ceramics were fabricated by heat-treating presintered samples at temperatures 2100°C. Polarized light microscopy revealed the ferroelastic domain structure in the t ' samples. XRD showed that no monoclinic phase was detected on as-polished, ground and fracture surfaces, or on surfaces while under a tensile stress as high as 400 MPa. By contrast, relative changes occurred in the tetragonal peak intensities, which were attributed to ferroelasatic domain switching. The higher toughness of 3-mol%-Y₂O₃-doped t ' samples (7.7 MPa · m^1/2) compared to that of 8 mol% Y₂O₃ cubic samples (2.4 MPa · m^1/2) was explained in part by ferroelastic domain switching.     

Grinding-Induced Texture in Ferroelastic Tetragonal Zirconia

Ceria- and yttria-doped tetragonal polycrystalline zirconia ceramics were ground at temperatures as high as 1100°C. X-ray diffraction revealed that the intensity ratio I ₍₀₀₂₎/ I ₍₂₀₀₎ increased (to as high as ∼4.5) compared with that from the as-sintered surfaces (∼0.55). The enhancement in I ₍₀₀₂₎/ I ₍₂₀₀₎ at temperatures well above the m → t transition temperature shows that it is not related to transformation, reversible or otherwise, but can be explained by ferroelastic domain switching.     

Multichannel ECG data compression based on multiscale principal component analysis

In this paper, multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression. In wavelet domain, principal components analysis (PCA) of multiscale multivariate matrices of multichannel signals helps reduce dimension and remove redundant information present in signals. The selection of principal components (PCs) is based on average fractional energy contribution of eigenvalue in a data matrix. Multichannel compression is implemented using uniform quantizer and entropy coding of PCA coefficients. The compressed signal quality is evaluated quantitatively using percentage root mean square difference (PRD), and wavelet energy-based diagnostic distortion (WEDD) measures. Using dataset from CSE multilead measurement library, multichannel compression ratio of 5.98:1 is found with PRD value 2.09% and the lowest WEDD value of 4.19%. Based on, gold standard subjective quality measure, the lowest mean opinion score error value of 5.56% is found.     

Detection of repolarization alternans with an implantable cardioverter defibrillator lead in a porcine model

Mechanistic links have been suggested between repolarization alternans (RPA) and the onset of ventricular tachycardia (VT) and/or fibrillation. Endocardial detection of RPA may, therefore, be an important step in future device-based treatments of arrhythmias. Here, we investigate if RPA could be detected during acute ischemia using an implantable cardioverter defibrillator (ICD) lead (tip to distal coil) located in the right ventricular apex. In 18 pigs, the right coronary (n = 10) or left anterior descending coronary (n = 8) artery was occluded for 10 min using a balloon catheter, followed by reperfusion for 30 min, and re-occlusion for 30 min. RPA magnitude, computed using the modified moving average (MMA) method, showed a sharp increase in all 18 animals, from a mean baseline level of 1.9 +/- 1.3 mV to 3.0 +/- 1.3 mV during first occlusion (p < 0.001). RPA magnitude showed a prominent increase in 10 animals during re-occlusion, from a mean baseline level of 1.7 +/- 1.0 mV to 3.3 +/- 1.5 mV (p < 0.001). The protocol was terminated during the first two stages of occlusion and reperfusion for the remaining 8 animals due to the occurrence of ventricular fibrillation (VF). These results confirm that RPA increases under ischemic conditions and that it is possible to detect and track RPA dynamics with an ICD lead that is positioned in a clinically realistic location. Such an approach may be useful in formulating improved arrhythmia detection and control algorithms.     

Evaluation of Thermal Resistance Matrix Method for an Embedded Power Electronic Module

Thermal characterization provides data on the thermal performance of electronic components under given cooling conditions. The most common thermal characterization parameter used to characterize the behavior of electronic components is the thermal resistance. In this work, experiments are conducted to obtain thermal characterization data for different chips in a multichip package. Using this data, it is shown that the assumption of a linear temperature rise with input power is valid within the expected range of operation of the electronic module. Secondly, the applicability of a resistance matrix superposition methodology to the packaging structure of an integrated power electronic module is evaluated. The temperatures and the associated uncertainties involved in using the resistance matrix superposition method are compared to those obtained directly by powering all chips. It is shown that for any arbitrary power losses from the chips, the resistance matrix superposition method can predict the temperatures of a multichip package with reasonable accuracy for temperature rise up to 50degC.