Development and Validation Method for Silica Determination by Spectrophotometry in Some Herbs and Pharmaceutical Formulations

ABSTRACT

A spectrophotometric method for determination of silica in herbs and herbal pharmaceutical products has been developed and validated. The method showed excellent accuracy and precision with S.D. 1.67 and RSD 1.72%, 2.75%, respectively. The established linearity range was 0.05–0.5 μg/mL(r² > 0.99974). The recovery of silica from spiked placebo was > 95% over the linear range. The method has been successfully used in the analysis of silica in raw material and herbal pharmaceutical formulations. This validated method proved to be rapid and less costly.     

Scanning schemes in white light Photoelasticity – Part I: Critical assessment of existing schemes

The use of white light based Three Fringe Photoelasticity (TFP)/RGB Photoelasticity has gained importance in the recent years. With recent advances in TFP, it is possible to resolve fringe orders upto twelve. The main advantage of this technique is that it requires only a single image for isochromatic demodulation, which makes it suitable especially for problems where recording multiple images is difficult. The accuracy of isochromatic data obtained using TFP/RGB Photoelasticity is dependent on the scanning scheme used to refine the data, which is necessary to incorporate fringe order continuity. In this paper, the existing scanning schemes are critically evaluated for their ability to scan the entire model domain, influence of seed point selection and noise propagation. The scanning schemes are assessed using four problems of increasing level of geometric complexity – Circular disc under compression (simply connected), bi-axially loaded cruciform specimen with an inclined crack, a thick ring subjected to internal pressure and a finite plate with a hole (multiply connected).     

Digital photoelasticity of glass: A comprehensive review

The recent advances in digital photoelasticity have made it possible to use it conveniently for the stress analysis of articles and components made of glass. Depending on the application, the retardation levels to be measured range from a few nanometres to several thousand nanometres, which necessitates different techniques and associated equipments. This paper reviews the recent advances in the photoelasticity of glass with a focus on the techniques/methods developed in the last decade. A brief introduction to the residual stress in glass is provided initially to bring out its tensorial nature. The subsequent sections are organised thematically rather than chronologically, for better readability and easy access of information.     

Experimental investigation of the effect of temperature on the strength of polyimide contact structures

A new photogrammetry based measurement technique for contact areas in line contact structures is developed. From the data collected by this technique, a method for measuring the contact strength of contact structures in high temperature applications is proposed. The contact strength of a line contact structure of polyimide at different temperatures is measured; the results show that the increase in temperature decreases the contact strength of the structure. The effect of temperature on the contact strength is studied by investigating the occurrence and evolution of yielding core within the structure at different temperatures. The decrease in the yield strength and elastic modulus of the polyimide material at high temperature induces core yielding at lower loads and eases the propagation of core yielding to the surface.     

Error evaluation for Zernike polynomials fitting based phase compensation of digital holographic microscopy

Combining the experimental research with the simulation calculation, the error evaluation for Zernike polynomials fitting (ZPF) based phase compensation of digital holographic microscopy (DHM) is performed. The obtained results show that the reconstructed phase with high precision can be obtained by ZPF phase compensation algorithm. Moreover, the phase error for ZPF based phase compensation algorithm increases with both the variation of object height and object transverse area, the larger variation of object height, the larger of phase error, and the larger of object transverse area, the faster increase of RMS phase error. To decrease the error of ZPF phase compensation algorithm, it is required to ensure one of the variations of object height and object transverse area to be a small value. Importantly, the proposed method supplies a useful tool for the error evaluation of phase compensation algorithm.     

Multi-scale retinex improvement for nighttime image enhancement

We propose a retinex improvement for nighttime image enhancement. Retinex is often used on images under non-uniform illumination in terms of either color or lightness and has satisfactory results to achieve color constancy and dynamic range compression. Few studies focus retinex on nighttime images, especially those under extreme conditions (i.e., images with over-lighted or extremely under-lighted areas or with noise speckles), on which retinex operation can perform badly. Original multi-scale retinex (MSR) is extremely sensitive to noise speckles that cameras produce in low light areas, and it has unsatisfactory effect on areas with normal or intensive illumination. Moreover, original MSR uses a gain-offset method for prior-to-display treatment and can lead to apparent data loss on nighttime images. This paper replaces the logarithm function in MSR with a customized sigmoid function to minimize data loss, and adapts MSR to nighttime images by merging results from sigmoid-MSR with original images. Experiments show our framework, when applied to nighttime images, can preserve areas with normal or intensive lighting and suppress noise speckles in extreme low light areas.     

Hierarchical Model-Based Clustering for Large Datasets

In recent years, hierarchical model-based clustering has provided promising results in a variety of applications. However, its use with large datasets has been hindered by a time and memory complexity that are at least quadratic in the number of observations. To overcome this difficulty, this article proposes to start the hierarchical agglomeration from an efficient classification of the data in many classes rather than from the usual set of singleton clusters. This initial partition is derived from a subgraph of the minimum spanning tree associated with the data. To this end, we develop graphical tools that assess the presence of clusters in the data and uncover observations difficult to classify. We use this approach to analyze two large, real datasets: a multiband MRI image of the human brain and data on global precipitation climatology. We use the real datasets to discuss ways of integrating the spatial information in the clustering analysis. We focus on two-stage methods, in which a second stage of processing using established methods is applied to the output from the algorithm presented in this article, viewed as a first stage.     

Flexible sheet with radiophotoluminescence glass beads for remotely monitoring high beta-surface-contamination

A flexible sheet was made with radiophotoluminescence (RPL) glass beads on an experimental basis for visualization of high beta-surface-contamination. A simple RPL observation system for remote contamination monitoring was constructed with a homemade UV floodlight and a commercially available digital camera with supplementary optical lenses and filters. In preliminary experiments, RPL images were well observed with the digital camera of the present system. Their precise RPL intensity was determined after the correction of nonlinear response of the camera. It was expected from experiments that RPL images of beta-surface-contamination could be quantitatively evaluated through calibration, i.e., the conversion of camera images to dose data on the sheet-type glass dosimeter.     

Good match exploration for thermal infrared face recognition based on YWF-SIFT with multi-scale fusion

Stable local feature detection is a critical prerequisite in the problem of infrared (IR) face recognition. Recently, Scale Invariant Feature Transform (SIFT) is introduced for feature detection in an infrared face frame, which is achieved by applying a simple and effective averaging window with SIFT termed as Y-styled Window Filter (YWF). However, the thermal IR face frame has an intrinsic characteristic such as lack of feature points (keypoints); therefore, the performance of the YWF-SIFT method will be inevitably influenced when it was used for IR face recognition. In this paper, we propose a novel method combining multi-scale fusion with YWF-SIFT to explore more good feature matches. The multi-scale fusion is performed on a thermal IR frame and a corresponding auxiliary visual frame generated from an off-the-shelf low-cost visual camera. The fused image is more informative, and typically contains much more stable features. Besides, the use of YWF-SIFT method enables us to establish feature correspondences more accurately. Quantitative experimental results demonstrate that our algorithm is able to significantly improve the quantity of feature points by approximately 38%. As a result, the performance of YWF-SIFT with multi-scale fusion is enhanced about 12% in infrared human face recognition.     

Optical multiresolution analysis with spatial localization

Multiresolution analysis is very useful for characterization of textures, segmentation tasks, and feature enhancement. The development of optical methods to perform such procedures is highly promissory for real-time applications. Usually, the optical implementations of multiresolution analysis consist in the decomposition of the input scene in different frequency bands, obtaining various filtered versions of the scene. However, under certain circumstances it could be useful to provide just one version of the scene where the different filters are applied in different regions. This procedure could be specially interesting for biological and medical applications in situations when the approximate localization of the scale information is known a priori. In this paper we present a fully optical method to perform multiresolution analysis with spatial localization. By means of the proposed technique, the multi-scale analysis is performed at once in a unique image. The experimental set-up consist of a double-pass convergent optical processor. The first stage of the device allows the multiple band decomposition, while the second stage confines the information of each band to different regions of the object and recombines it to achieve the desired operation. Numerical simulations and experimental results, which prove the very good performance of the method, are presented.