Micro and nanocrystalline cellulose based oral dispersible film; preparation and evaluation of in vitro/in vivo rapid release studies for donepezil

Oral fast-dispersible film was prepared by utlizing donepezil hydrochloride (drug) and various cellulose derivatives such as hydroxypropyl methyl cellulose (hypermellose) (HPMC), microcrystalline cellulose (MCC) and nanocrystalline cellulose (NCC) to treat Alzheimer’s disease. NCC was synthesized by ultra-sonication method using MCC and this was converted to thinfilm formulation (NCC-F) using solvent casting technique. The interaction between the polymer and the drug was investigated by spectral analysis such as UV, FTIR, and 1H- NMR. FTIR confirmed that the compatibility of drug and polymer in ODF formulation. NCC-F has shown an average surface roughness of 77.04 nm from AFM and the average particle size of 300 nm from SEM analysis. Nano sized particle of NCC-F leads faster in vitro dissolution rate (94.53%) when compared with MCC-F and F3 formulation. Animal model (in vivo) studies of NCC-F formulation has reached peak plasma concentration (Cmax) up to 19.018 ng/mL in the span of (tmax) 4 h with greater relative bioavailability of 143.1%. These results suggested that high surface roughness with nanosized NCC-F formulation attained extended drug availability up to (t1/2) 70 h

An image steganography using improved hyper-chaotic Henon map and fractal Tromino

Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. First, the cover image is converted into a wavelet environment using the integer wavelet transform (IWT), which protects the cover images from false mistakes. The grey wolf optimizer (GWO) is used to choose the pixel’s image that would be utilized to insert the hidden image in the cover image. GWO effectively selects pixels by calculating entropy, pixel intensity, and fitness function using the cover images. Moreover, the secret image was encrypted by utilizing a proposed hyper-chaotic improved Henon map and fractal Tromino. The suggested method increases computational security and efficiency with increased embedding capacity. Following the embedding algorithm of the secret image and the alteration of the cover image, the least significant bit (LSB) is utilized to locate the tempered region and to provide self-recovery characteristics in the digital image. According to the findings, the proposed technique provides a more secure transmission network with lower complexity in terms of peak signal-to-noise ratio (PSNR), normalized cross correlation (NCC), structural similarity index (SSIM), entropy and mean square error (MSE). As compared to the current approaches, the proposed method performed better in terms of PSNR 70.58% Db and SSIM 0.999 respectively

Pharmacovigilance programme of India: revival of the renaissance

Adverse drug reactions (ADRs) are the fourth leading cause of morbidity in the world. In order to safeguard the health of the community, Pharmacovigilance Programme of India (PvPI) is implemented as the monitoring body by Indian Pharmacopoeia Commission (IPC). It is leading national authority. National Coordinating Centre (NCC) PvPI works as the World Health Organization (WHO) collaborating centre for pharmacovigilance. Adverse drug reactions are reported to NCC PvPI which are then directed towards WHO Uppsala Monitoring Centre (UMC) Sweden which is the global monitoring centre for worldwide data. Central Drugs Standard Control Organization (CDSCO) is the regulatory authority of India under the Ministry of Health and Family Welfare (MOHFW), Government of India. This article focusses on the various strands of pharmacovigilance at the healthcare professional and consumer level. It also discusses the pitfalls in the journey of pharmacovigilance thus helping in enhancing the quality of health safety. Even a minuscule contribution by a health care professional or a consumer can voluminously help in promotion of drug safety. Therefore, there is a need of inculcating the culture of adverse drug reaction reporting for the welfare of the vulnerable masses

On equivariant Serre problem for principal bundles

Let $E_G$ be a $\Gamma$--equivariant algebraic principal $G$--bundle over a normal complex affine variety $X$ equipped with an action of $\Gamma$, where $G$ and $\Gamma$ are complex linear algebraic groups. Suppose $X$ is contractible as a topological $\Gamma$--space with a dense orbit, and $x_0 \in X$ is a $\Gamma$--fixed point. We show that if $\Gamma$ is reductive, then $E_G$ admits a $\Gamma$--equivariant isomorphism with the product principal $G$--bundle $X \times_{\rho} E_G(x_0)$, where $\rho\,:\, \Gamma \, \longrightarrow\, G$ is a homomorphism between algebraic groups. As a consequence, any torus equivariant principal $G$-bundle over an affine toric variety is equivariantly trivial. This leads to a classification of torus equivariant principal $G$-bundles over any complex toric variety.Comment: References added. To appear in the International Journal of Mathematic

A Comprehensive Review on Digital Image Watermarking

The advent of the Internet led to the easy availability of digital data like images, audio, and video. Easy access to multimedia gives rise to the issues such as content authentication, security, copyright protection, and ownership identification. Here, we discuss the concept of digital image watermarking with a focus on the technique used in image watermark embedding and extraction of the watermark. The detailed classification along with the basic characteristics, namely visual imperceptibility, robustness, capacity, security of digital watermarking is also presented in this work. Further, we have also discussed the recent application areas of digital watermarking such as healthcare, remote education, electronic voting systems, and the military. The robustness is evaluated by examining the effect of image processing attacks on the signed content and the watermark recoverability. The authors believe that the comprehensive survey presented in this paper will help the new researchers to gather knowledge in this domain. Further, the comparative analysis can enkindle ideas to improve upon the already mentioned techniques

An Efficient Hybrid Fuzzy-Clustering Driven 3D-Modeling of Magnetic Resonance Imagery for Enhanced Brain Tumor Diagnosis

Brain tumor detection and its analysis are essential in medical diagnosis. The proposed work focuses on segmenting abnormality of axial brain MR DICOM slices, as this format holds the advantage of conserving extensive metadata. The axial slices presume the left and right part of the brain is symmetric by a Line of Symmetry (LOS). A semi-automated system is designed to mine normal and abnormal structures from each brain MR slice in a DICOM study. In this work, Fuzzy clustering (FC) is applied to the DICOM slices to extract various clusters for di erent k. Then, the best-segmented image that has high inter-class rigidity is obtained using the silhouette fitness function. The clustered boundaries of the tissue classes further enhanced by morphological operations. The FC technique is hybridized with the standard image post-processing techniques such as marker controlled watershed segmentation (MCW), region growing (RG), and distance regularized level sets (DRLS). This procedure is implemented on renowned BRATS challenge dataset of di erent modalities and a clinical dataset containing axial T2 weighted MR images of a patient. The sequential analysis of the slices is performed using the metadata information present in the DICOM header. The validation of the segmentation procedures against the ground truth images authorizes that the segmented objects of DRLS through FC enhanced brain images attain maximum scores of Jaccard and Dice similarity coe cients. The average Jaccard and dice scores for segmenting tumor part for ten patient studies of the BRATS dataset are 0.79 and 0.88, also for the clinical study 0.78 and 0.86, respectively. Finally, 3D visualization and tumor volume estimation are done using accessible DICOM information.Ministerio de Desarrollo de Recursos Humanos, India SPARC/2018-2019/P145/SLUniversidad Politécnica de Tomsk, Rusia RRSG/19/500

ANDROID BASED HOME AUTOMATION AND ENERGY CONSERVATION

Wireless Sensor Network (WSN) consists of three main components: nodes, gateways, and software. The spatially distributed measurement nodes interface with sensors to monitor assets or their environment. In a WSN network the devices are connected to WSN nodes wherein the entire nodes uses Zigbee network to transfer the status of connected applications to a controller which controls the whole applications but the main drawback of Wireless sensor networks is its high interference, low coverage area and ability to control only low power devices. In order to overcome these drawbacks Android equipped devices are used to control the applications over GPRS network. Android equipped devices allow the user to control various applications over wireless networks. Being an open sourced platform it allows the user to design a custom module which controls the home applications by connecting the android equipped device and its corresponding home applications to an MCU wherein it uses relay circuits to connect the entire applications using GPRS network to connect the application controller and the android device. These devices can be used to control industrial applications, home applications like light, fan etc., and thereby conserving electricity

A Hybrid Digital Watermarking Approach Using Wavelets and LSB

The present paper proposed a novel approach called Wavelet based Least Significant Bit Watermarking (WLSBWM) for high authentication, security and copyright protection. Alphabet Pattern (AP) approach is used to generate shuffled image in the first stage and Pell’s Cat Map (PCM) is used for providing more security and strong protection from attacks. PCM applied on each 5×5 sub images. A wavelet concept is used to reduce the dimensionality of the image until it equals to the size of the watermark image. Discrete Cosign Transform is applied in the first stage; later N level Discrete Wavelet Transform (DWT) is applied for reducing up to the size of the watermark image. The water mark image is inserted in LHn Sub band of the wavelet image using LSB concept. Simulation results show that the proposed technique produces better PSNR and similarity measure. The experimental results indicate that the present approach is more reliable and secure efficient.The robustness of the proposed scheme is evaluated against various image-processing attacks

A High Result in Wavelet Watermarking Using Singular Value Decomposition

Internet that has developed into a good distribution tool for digital data, causing a large increase in digital data sharing, especially in the form of digital images, and causing problems that need attention. One of them is about copyright protection. Watermarking is one technique that aims to protect digital image copyright. In this study, watermarking was carried out using the Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) algorithms in digital images with different file extensions. Transformation of 2 levels of DWT and SVD on the host image and SVD transformation on the watermarked image that inserted in the LL2 sub-band of the host image. Watermarking with the proposed method produces good image quality with PSNR values exceeding 40 dB, SSIM reaching 0.99 and NCC reaching 1. This shows a robust and imperceptible watermarking image

CMFRI Newsletter No.153 April - June 2017

Our institute which has completed 70 years of service to the nation can rightly feel proud of its accomplishments during the quarter. The institute made its pioneering foray into breeding and seed production of several marine finfishes of high commercial value, a few years ago. Presently sustained large scale seed production technology is available for several species like cobia, silver pompano and orange grouper. In recognition of the institute's achievements, DADF has announced a substantial funding support to establish the Brood Banks of cobia and silver pompano