National Academy Science Letters最新文献

Climate change ends up increasing ambient temperature. North Gujarat region falls under hot and dry climatic zone. This research focused on assessing the effect of high temperature women who were working outdoors. Multistage random sampling method was used to select farm women. Total sample size was eighty farm women. Environmental parameters were measured at the farm where farm women were working. Biological parameters of farm women were measured after working at least half an hour at their farms during summer season. A positive significant relationship was found between air temperature and oral temperature of farm women. A significant negative relationship was found between air velocity and heart rate of farm women.

This study examines skeletal deformities in Labeo catla (Hamilton, 1822) (Teleostei: Cyprinidae) collected from Wainganga River near Pauni city, District Bhandara, Maharashtra. Morphological features of abnormal fish specimens were compared with those of normal fish from the same location. While no marked differences were observed in meristic characters, minor changes were noted in morphometric characters, particularly in the caudal peduncle region. Specifically, the distance between the post-anal fin and the base of the caudal peduncle was shorter in the abnormal specimen (15.4 mm, 4.78% of standard length) compared to the normal specimen (48.37 mm, 11.80% of standard length). Radiographic examinations were conducted to further analyze the deformities. Potential factors contributing to the deformities include insufficient essential nutrients, variations in water quality or chemical contaminants, and genetic mutations during larval development. The study discusses these potential causes and emphasizes the importance of such research in environmental monitoring. This study presents the first documented report of skeletal abnormalities in Labeo catla from the Wainganga River in Maharashtra, India.

API pipeline steels are designed in such a way that they can survive in high temperatures and high pressure in different environments. The API X70 pipeline steel has a very fine-grained microstructure so it has high strength and ductility. In present work, the heat treatment of API X70 steel was performed at different tempering temperature and microstructural analysis was studied. Mechanical and microstructural behavior of base metal and heat-treated API X70 steel was studied. The distinct phases such as ferrite, pearlite and some carbides that form during the heat treatment are visible in the microstructure of the heat-treated samples, XRD as well as SEM analysis of base and heat-treated specimens were performed. Major peaks of iron were observed for both base and heat-treated samples during XRD analysis. XRD analysis of API X70 steel in which maximum peak intensity was present at an angle 2Ɵ = 40.18 and 44.6. SEM analysis of base as well as heat treated API X70 steel exhibit different phases such as Acicular, ferrite-pearlite and small inclusions of carbides. Various phases such as ferrite as well as pearlite were observed for the specimen tempered at 650 °C for 3 Hours. Base metal typically exhibits acicular ferrite microstructure. The microhardness of base metal (28.25 HRC) is higher as compared to the heat-treated steel (6.87 HRC).

Deep learning softwares are designed using artificial neural networks for various applications by training and testing them with an appropriate dataset. The raw image samples available in the dataset may contain noisy and unclear information due to radiation, heat and poor lighting conditions. Therefore, the researchers are trying to filter and enhance such noisy images through preprocessing steps for providing a valid feature information to the neural network layers included in the deep learning software. However, there are certain claims that roam around the researchers such as an image may lose some useful information when it is not preprocessed with an appropriate filter or enhancement technique. Hence, the work reviews the efficacy of the methodologies that are designed with and without a preprocessing step. Also, the work summarizes the common reasons and statements highlighted by the researchers for using and avoiding the preprocessing steps on designing a deep learning approach. The study is conducted to provide a clarity toward the requirement and non-requirement of preprocessing step in a deep learning software.

This study is to isolate and identify the endophytic bacteria from Mirabilis jalapa L. and evaluate the enzyme production by these isolates. Two distinct bacteria were isolated from the tuber referred to as UCMJ1 and UCMJ2. UCMJ1 isolate formed whitish-yellow opaque colonies and were Gram-negative, motile, rod-shaped bacteria without endospore whereas UCMJ2 isolate formed translucent colonies, and were rod-shaped, Gram-negative, non-endosporic motile bacteria. The sequence obtained after 16S rRNA gene sequencing of both the strains were compared with corresponding sequences of related organisms retrieved from the GenBank database with the BLAST (Basic Local Alignment Search Tool) algorithm for identifying the isolated strains. The isolates UCMJ1 and UCMJ2 were, thus specified as Enterobacter mori and Pseudomonas entomophila respectively. On evaluation for their possible hydrolytic enzyme activity for industrially valuable enzymes including protease, xylanase, cellulase, amylase, and lipase, P. entomophila had shown prominent activity for the enzyme lipase. The present study forms the first report on the isolation of lipase-producing P. entomophila as an endophyte from M. jalapa L. root tuber.

Chrysanthemums are highly acceptable worldwide due to their attractive flower colour, shape and size. Keeping in view their ever increasing demand during the off season also, the investigations were carried out in the year 2019. The aim of this study was to standardize the covering material and variety suitable for off season flower production. The treatments consisted of five different varieties, viz. (Banglori Local, Yellow Delight, Reagan Emperor, Regan White and Nanako), and four covering materials (viz. tarpaulin, high-density polyethylene (HDPE), black satin cloth and 50% green shade net) along with natural photoperiod that was considered as control treatment were used. The trial was replicated thrice using factorial completely randomized design. The results revealed that among the different covering materials, the highest plant height (47.05 cm), flowers per plant (32.35), flower per shoot (9.75), with least days taken for peak flowering (140.13 days), were observed under HDPE covering material. The study concludes that HDPE was found to be the most suitable covering material for off season flower production of variety ‘Yellow Delight’.

Some problems in producing good quality clove seeds were the seed's slow growth and the absence of technology to accelerate its growth. Therefore, we performed the research to get one natural Plant Growth Regulator and its concentration potential to enhance clove seed growth. The study was arranged in a completely randomized design, with two factors and four replications. The first factor was five kinds of natural plant growth regulators (PGRs): (1) Leucaena leucocephala leaf extract (auxin source) + coconut water (Cytokinin), (2) Leucaena leucocephala seedling extract (auxin source) + coconut water, (3) gliricidia shoot extract + coconut water and (4) sprouted onion bulb extract (Eleutherine bulbosa) + coconut water. The second factor was the concentration of PGRs: (1) control (no PGRs), (2) 2.5 ml l⁻¹, (3) 5.0 ml l⁻¹, (4) 10 ml l⁻¹, and (5) 20 ml l⁻¹. Parameters observed were plant growth (plant height, leaf number, leaf length, leaf width, and stem diameter), the chlorophyll content of leaves, and the auxin and cytokinin content of each extract. Clove seedlings' growth was observed until four months old. PGRs from the extract of sprouted onion (Eleutherine bulbosa) and Gliricidia shoots could be developed due to their high auxin content, which can boost clove seed growth at the concentration of 10 ml l⁻¹.

In the present study, growth performance, antioxidant activities and cadmium (Cd) accumulation in eco-friendly bacterial consortium inoculated Mentha arvensis grown in Cd contaminated soils were evaluated. Eco-friendly bacterial consortium inoculation significantly enhanced growth, biomass and antioxidant efficacy of M. arvensis plants grown in contaminated soil, i.e. wastewater irrigated and Cd-spiked soils over the non-inoculated plants (p < 0.05). Cd accumulation in roots, stems and leaves of M. arvensis inoculated with eco-friendly bacterial consortium decreased significantly as compared to plant without bacterial consortium (p < 0.05) in wastewater irrigated (5.3%, 48.5% and 5.8%, respectively) and Cd spiked (2.2%, 20.9% and 27.1%, respectively) soils. Thus, the present study concludes that application of Cd resistant eco-friendly bacterial consortium in polluted soils could be helpful in improving growth of M. arvensis and preventing entry of Cd in food chain.

Farming is the strength of a nation in terms of economy and survival of the people. Numerous methodologies based on plant leaf disease detection are developed with deep learning, but it does not precisely categorize the plant leaf disease. This research work introduces a plant leaf disease detection using an optimized evolutionary gravitational neocognitron neural network (EGNNN) for classifying the normal and diseased region of the plant image. Here, the EGNNN is utilized to categorize leaf images with their diseases. The Giza pyramids construction optimization algorithm (GPCOA) is utilized to maximize the accuracy of the network. The introduced approach is implemented in Python programming. The two standard datasets such as plant village datasets and augmented datasets are utilized to evaluate performance of the proposed techniques and achieve 99.92 and 99.98% of accuracy for both datasets. Also, Wilcoxon signed-rank test is performed to demonstrate the effectiveness of the introduced method.

This study aimed to evaluate the effects of aflatoxin B₁ and quercetin-enriched diets on histomorphological response of the liver, in freshwater fish Labeo rohita for 90 days. The fingerlings were divided into five groups (D1, control diet), AFB₁ 100 (D2), AFB₁ 25 QC (D3), AFB₁ 50 QC (D4), and AFB₁ 100 QC (D5). The study was carried out in fibre-reinforced plastic pools with three replicates for each group. After 90 days, fish from treatment were randomly caught, anaesthetized, and euthanized. Then, histological sections of the tissues were prepared. Results showed that fish exposed to 100 ppb AFB₁ showed cytoplasmic vacuolization in hepatocytes, hepatic tissue showing loss of membrane integrity resulting in the cell fusion along with diffused hepatocytes, hyperplasia, blood congestion, and invasion of nuclei in the central vein. However, fish diet supplementation of D3 led to a significant improvement in the histomorphological responses of the liver.