Investigation on Nutritional, Phytochemical, and Antioxidant Abilities of Various Traditional Rice Varieties.

Rice (Oryza sativa L.) is a popular grain that is consumed by almost half of the world's population. Rice has several distinct breeds classified as traditional and ancient grains. The consumption of rice by 60% of the world's population is a staple food. Entire grain rice, often known as brown rice, is the unpolished counterpart of white rice, containing bran, germ, and endosperm. Eating whole-grain rice is linked to many health benefits; thus, scientists have focused on identifying and quantifying bioactive chemicals in this meal. The present study assessed the physio-chemical, cooking attributes, mineral contents, phytochemicals, and free radical scavenging capabilities of conventional rice cultivars using known approaches according to particle size analysis. Rice grain lengths varied between 4.10 ± 16 and 6.20 ± 007. The length and thickness ratios of rice were not substantially different (p > 0.05). Kattuyanam has the maximum protein content (9.99 ± 06%) of all the rice varieties that were physio-chemical investigated. It also has highest phenolic content and antioxidant properties compared to gallic acid equivalent (334.900 ± 61 g) (GAE)/100 g, followed by anthocyanins and flavonoids. Total phenolic content and phenolic fractions of the HPLC profile in tested landraces indicate the presence of bioactive substances derived from traditional rice cultivars and a range of phytonutrients, including phenol, revealing their healthy potentials in the present study.

Identification and characterization of spatio-temporal hotspots of forest fires in South Asia.

Forest fire is considered as one of the major threats to global biodiversity and a significant source of greenhouse gas emissions. Rising temperatures, weather conditions, and topography promote the incidences of fire due to human ignition in South Asia. Because of its synoptic, multi-spectral, and multi-temporal nature, remote sensing data can be a state of art technology for forest fire management. This study focuses on the spatio-temporal patterns of forest fires and identifying hotspots using the novel geospatial technique "emerging hotspot analysis tool" in South Asia. Daily MODIS active fire locations data of 15 years (2003-2017) has been aggregated in order to characterize fire frequency, fire density, and hotspots. A total of 522,348 active fire points have been used to analyze risk of fires across the forest types. Maximum number of forest fires in South Asia was occurring during the January to May. Spatial analysis identified areas of frequent burning and high fire density in South Asian countries. In South Asia, 51% of forest grid cells were affected by fires in 15 years. Highest number of fire incidences was recorded in tropical moist deciduous forest and tropical dry deciduous forest. The emerging hotspots analysis indicates prevalence of sporadic hotspots, followed by historical hotspots, consecutive hotspots, and persistent hotspots in South Asia. Of the seven South Asian countries, Bangladesh has highest emerging hotspot area (34.2%) in forests, followed by 32.2% in India and 29.5% in Nepal. Study results offer critical insights in delineation of fire vulnerable forest landscapes which will stand as a valuable input for strengthening management of fires in South Asia.

Facile hydrothermal bio-synthesis of cellulose acetate templated CuS nanorods like fibres: antibacterial, cytotoxicity effects and DNA cleavage properties against A549 lung cancer cells.

In this research, the hydrothermal method was used for synthesising cellulose acetate (CA) templated nanorods like CuS fibres using vegetable extract (Brassica oleracea var. italica). These extracts act as a reducing agent in the presence of CA. Surprisingly, when the same reaction was carried out in the absence of CA and broccoli extract, structural morphology disappeared and was found as agglomerated. In the presence of cellulose templated extract mediated CuS has revealed as nanorods like fibres and was confirmed by field emission scanning electron microscope analysis. Their crystallinity property of CuS nanoparticles (NPs) and cellulose templated biosynthesised CuS NPs was analysed and compared using X-ray diffraction technique. The biological activities of the obtained product were examined for antibacterial assessment against two bacterial strains that include two-gram negative strains (E.Coli and S. aureus). The nanostructured product found to exhibit excellent antibacterial agent against all the strains. Biosynthesised nanostructure showed its efficacy against A549 lung cancer cells which might attribute to a larger surface to volume ratio of nanorods like fibres. The authors observation suggest that CuS nanorods like fibres can significantly reduce the cell growth with IC50 value of 31.2 µg/ml.

Lung Cancer Detection Using Fuzzy Auto-Seed Cluster Means Morphological Segmentation and SVM Classifier.

An effective fuzzy auto-seed cluster means morphological algorithm developed in this work to segment the lung nodules from the consecutive slices of Computer Tomography (CT) images to detect the lung cancer. The initial cluster values were chosen automatically by averaging the minimum and maximum pixel values in each row of an image. The area and eccentricity features were used to eliminate the line like structure and very tiny clusters less than 3 mm in size. The change in centroid analysis was carried out to eliminate the blood vessels. The tissue clusters whose centroid varies much in consecutive slices must be blood vessels. After eliminating the blood vessels, the co-occurrence matrix based texture features contrast, homogeneity and auto correlation were computed on the remaining nodules from the consecutive CT slices to discriminate the calcifications. The extracted centroid shift and texture features were used as the inputs to the Support Vector Machine (SVM) kernel classifier in order to classify the real malignant nodules. This work was carried out on 56 malignant (cancerous) cases and 50 normal cases (with lung infections), which had a total of 56 malignant nodules and 745 benign nodules. Out of these, 60 % of subjects (34 cancerous & 30 non-cancerous) were used for training. The remaining 40 % subjects (22 cancerous & 20 non-cancerous) were used for testing. This work produced a good sensitivity, specificity and accuracy of 100 %, 93 % and 94 %, respectively. The False Positive (FP) per patient was calculated as 0.38.

Ligand-promoted intramolecular dehydrogenative cross-coupling using a Cu catalyst: direct access to polycyclic heteroarenes.

A copper(II)-promoted intramolecular C-H coupling reaction between indole-2 and imidazole-2 moieties has been developed for polycyclic heteroarene synthesis. The method provides direct access to biheteroaryl incorporated polycyclic frameworks, which are of huge interest in the area of functional materials and drug-discovery.