Image Encryption Based on Diffusion and Multiple Chaotic Maps

In the recent world, security is a prime important issue, and encryption is one of the best alternative way to ensure security. More over, there are many image encryption schemes have been proposed, each one of them has its own strength and weakness. This paper presents a new algorithm for the image encryption/decryption scheme. This paper is devoted to provide a secured image encryption technique using multiple chaotic based circular mapping. In this paper, first, a pair of sub keys is given by using chaotic logistic maps. Second, the image is encrypted using logistic map sub key and in its transformation leads to diffusion process. Third, sub keys are generated by four different chaotic maps. Based on the initial conditions, each map may produce various random numbers from various orbits of the maps. Among those random numbers, a particular number and from a particular orbit are selected as a key for the encryption algorithm. Based on the key, a binary sequence is generated to control the encryption algorithm. The input image of 2-D is transformed into a 1- D array by using two different scanning pattern (raster and Zigzag) and then divided into various sub blocks. Then the position permutation and value permutation is applied to each binary matrix based on multiple chaos maps. Finally the receiver uses the same sub keys to decrypt the encrypted images. The salient features of the proposed image encryption method are loss-less, good peak signal-to-noise ratio (PSNR), Symmetric key encryption, less cross correlation, very large number of secret keys, and key-dependent pixel value replacement.Comment: 14 pages,9 figures and 5 tables; http://airccse.org/journal/jnsa11_current.html, 201

ASPERGILLUS FLAVUS MEDIATED SILVER NANOPARTICLES SYNTHESIS AND EVALUATION OF ITS ANTIMICROBIAL ACTIVITY AGAINST DIFFERENT HUMAN PATHOGENS

Objective: Here, we report the extracellular synthesis of silver nanoparticles (AgNPs) using the cell-free extract of fungal isolate Aspergillus flavus and evaluation its inhibitory activity against bacterial pathogens. Methods: Synthesized AgNPs was characterized via high throughput instrumentation such as UV–Visible spectrophotometer (UV-Vis) and Fourier transform infrared spectroscopy, High-resolution transmission electron microscopy (HRTEM), X-ray Diffraction (XRD) and Energy dispersive X-ray spectroscopy (EDAX). Results: Formation of yellowish brown colour clearly indicates the synthesis of AgNPs which produces a SPR peak at 420 nm. Active protein metabolites present in the cell-free extract plays a crucial role in reduction and stabilization of AgNPs. It was clearly observed that synthesized AgNPs were faced-centered cubic crystalline in nature with the mean size of 22±11 nm. Further, synthesized AgNPs capped with protein moieties exhibits excellent inhibitory activity against tested bacterial pathogens. Conclusion: In this study, we have isolated the fungal strain A. flavus from the infected larvae of D. eucharis from the soil. The active metabolites of isolated A. flavus have been successfully used as an eco-friendly reducing agent to generate AgNPs and synthesized particles can be potentially developed as a drug candidature for antimicrobial therapy

Comparative Profiling of Volatile Compounds in Popular South Indian Traditional and Modern Rice Varieties by Gas Chromatography–Mass Spectrometry Analysis

Rice (Oryza sativa L.) is one of the major cereal crops cultivated across the world, particularly in Southeast Asia with 95% of global production. The present study was aimed to evaluate the total phenolic content (TPC) and to profile all the volatile organic compounds (VOCs) of eight popular traditional and two modern rice varieties cultivated in South India. Thirty-one VOCs were estimated by gas chromatography–mass spectrometry (GC-MS). The identified volatile compounds in the 10 rice varieties belong to the chemical classes of fatty acids, terpenes, alkanes, alkenes, alcohols, phenols, esters, amides, and others. Interestingly, most of the identified predominant components were not identical, which indicate the latent variation among the rice varieties. Significant variations exist for fatty acids (46.9–76.2%), total terpenes (12.6–30.7%), total phenols (0.9–10.0%), total aliphatic alcohols (0.8–5.9%), total alkanes (0.5–5.1%), and total alkenes (1.0–4.9%) among the rice varieties. Of all the fatty acid compounds, palmitic acid, elaidic acid, linoleic acid, and oleic acid predominantly varied in the range of 11.1–33.7, 6.1–31.1, 6.0–28.0, and 0.7–15.1%, respectively. The modern varieties recorded the highest palmitic acid contents (28.7–33.7%) than the traditional varieties (11.1–20.6%). However, all the traditional varieties had higher linoleic acid (10.0–28.0%) than the modern varieties (6.0–8.5%). Traditional varieties had key phenolic compounds, stearic acid, butyric acid, and glycidyl oleate, which are absent in the modern varieties. The traditional varieties Seeraga samba and Kichilli samba had the highest azulene and oleic acid, respectively. All these indicate the higher variability for nutrients and aroma in traditional varieties. These varieties can be used as potential parents to improve the largely cultivated high-yielding varieties for the evolving nutritionalmarket. The hierarchical cluster analysis showed three different clusters implying the distinctness of the traditional and modern varieties. This study provided a comprehensive volatile profile of traditional and modern rice as a staple food for energy as well as for aroma with nutrition

Maternal effects on anogenital distance in a wild marmot population

Peer reviewedPublisher PD

Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure

Higher COVID-19 pneumonia risk associated with anti-IFN-α than with anti-IFN-ω auto-Abs in children

We found that 19 (10.4%) of 183 unvaccinated children hospitalized for COVID-19 pneumonia had autoantibodies (auto-Abs) neutralizing type I IFNs (IFN-alpha 2 in 10 patients: IFN-alpha 2 only in three, IFN-alpha 2 plus IFN-omega in five, and IFN-alpha 2, IFN-omega plus IFN-beta in two; IFN-omega only in nine patients). Seven children (3.8%) had Abs neutralizing at least 10 ng/ml of one IFN, whereas the other 12 (6.6%) had Abs neutralizing only 100 pg/ml. The auto-Abs neutralized both unglycosylated and glycosylated IFNs. We also detected auto-Abs neutralizing 100 pg/ml IFN-alpha 2 in 4 of 2,267 uninfected children (0.2%) and auto-Abs neutralizing IFN-omega in 45 children (2%). The odds ratios (ORs) for life-threatening COVID-19 pneumonia were, therefore, higher for auto-Abs neutralizing IFN-alpha 2 only (OR [95% CI] = 67.6 [5.7-9,196.6]) than for auto-Abs neutralizing IFN-. only (OR [95% CI] = 2.6 [1.2-5.3]). ORs were also higher for auto-Abs neutralizing high concentrations (OR [95% CI] = 12.9 [4.6-35.9]) than for those neutralizing low concentrations (OR [95% CI] = 5.5 [3.1-9.6]) of IFN-omega and/or IFN-alpha 2

Autoantibodies against type I IFNs in patients with critical influenza pneumonia

In an international cohort of 279 patients with hypoxemic influenza pneumonia, we identified 13 patients (4.6%) with autoantibodies neutralizing IFN-alpha and/or -omega, which were previously reported to underlie 15% cases of life-threatening COVID-19 pneumonia and one third of severe adverse reactions to live-attenuated yellow fever vaccine. Autoantibodies neutralizing type I interferons (IFNs) can underlie critical COVID-19 pneumonia and yellow fever vaccine disease. We report here on 13 patients harboring autoantibodies neutralizing IFN-alpha 2 alone (five patients) or with IFN-omega (eight patients) from a cohort of 279 patients (4.7%) aged 6-73 yr with critical influenza pneumonia. Nine and four patients had antibodies neutralizing high and low concentrations, respectively, of IFN-alpha 2, and six and two patients had antibodies neutralizing high and low concentrations, respectively, of IFN-omega. The patients' autoantibodies increased influenza A virus replication in both A549 cells and reconstituted human airway epithelia. The prevalence of these antibodies was significantly higher than that in the general population for patients 70 yr of age (3.1 vs. 4.4%, P = 0.68). The risk of critical influenza was highest in patients with antibodies neutralizing high concentrations of both IFN-alpha 2 and IFN-omega (OR = 11.7, P = 1.3 x 10(-5)), especially those <70 yr old (OR = 139.9, P = 3.1 x 10(-10)). We also identified 10 patients in additional influenza patient cohorts. Autoantibodies neutralizing type I IFNs account for similar to 5% of cases of life-threatening influenza pneumonia in patients <70 yr old