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In the present study silver nanoparticles were synthesized using aqueous extract of fresh flowers of Tagetes erecta. The aqueous silver ions when exposed to fresh flower extract were reduced and resulted in green synthesis of silver nanoparticles. The synthesized silver nanoparticles were characterized by UV-visible spectroscopy, determination of zeta potential, FTIR, X-ray diffraction and SEM analysis. The UV spectrum of synthesized silver nanoparticles showed maximum absorbance at 430nm i.e. at a conc. of 1.5 ml of extract/10 ml silver nitrate solution. Different functional groups were identified by FTIR image, which contributed to antimicrobial activity. From SEM analysis crystalline nature of synthesized nanoparticles was evident. XRD peaks indicated the structure of nanoparticles and proved that nanoparticles are crystalline in nature. Zeta potential of synthesized nanoparticles was found to be -31.9mv which showed that the green synthesized nanoparticles are stable. Synergistic antimicrobial activity of selected concentration of the plant extract along with the antibiotics A(Penicillin) B(cefixime) showed more antibacterial activity against the selected gram positive and gram negative bacteria (Staphylococcus aureus, Klebsiella, Pneumonia, Escherichia coli, Bacillus subtilis.).Among different combinations the synergistic effect of penicillin is more with the synthesized silver nanoparticles against Klebsiella pneumoniae showing a zone of inhibition of 4.5 cm. The synergistic effect of cefixime is more with the synthesized silver nanoparticles against Bacillus subtilis showing a zone of inhibition of 3.5 cm. KEYWORDS: nanoparticles, characterization, Synergy, antimicrobial activity

Background: A Knowledge, Attitude and Practices (KAP) survey is a quantitative method (predefined questions formatted in standardized questionnaires) that provides qualitative and quantitative information. Measure the extent of a known situation; provides new tangents of a situations reality This has resulted in the public becoming more cautious, thereby minimizing the transmission of the disease to a certain level. Introduction: COVID-19 (COVID-19 is disease caused by a new strain of Coronavirus. ’CO’ stands for corona, ’VI’ for virus, and ‘D’ for disease. the most common symptoms which appear 2-14 days after exposure [1].Headache, abdominal pain, diarrhea, sore throat and muscle weakness are some of the less common symptoms experienced by some people, while some others may not develop any symptoms until later. This study is conducted to understand the extent of awareness among the general public and the importance of preventing the spread of Coronavirus infection in the community. An online questionnaire survey is conducted consisting the essential parameters about the important aspects of disease spread. Objective: To assess Coronavirus awareness among people. To understand the attitude of people towards Coronavirus Results: A total number of 564 participants took part In this study during the study period of 6months. Among which 325 were male and 239 were female. The male participants compromised the majority percentage (57%) of the total number of participants while the female participants comprised only (42.4%) of the participants. The result showed a significant correlation between female gender, higher age, and higher education, with knowledge, attitude, and practice. Conclusion: To adhere to the guidelines released by the Government and the guidelines provided by the WHO have played an extremely vital role in improving the knowledge and awareness among the general population which in turn brought positive effects in people’s attitude and practices towards Coronavirus since the WHO’s declaration of Coronavirus as a pandemic. This has resulted in the public becoming more cautious, thereby minimizing the transmission of the disease to a certain level. Several public health measures which are now being implemented around the world will hopefully diminish the spread of the virus while safe and effective treatments and vaccines are being developed to terminate it.

Allograft has emerged as a preeminent province in medical management. In today's contemporary world, many emerging technologies have evolved and are digitally automatized with the help of Artificial intelligence, Cloud, Blockchain, etc, and it brings innovative solutions for the critical problems to make new vogue [7]. practitioners are given the challenge of forcibly acquiring, and companionating health records [18]. The most highly demanded aspects of the interweb are privacy and security, and this is where blockchain plays a predominant role. It has features such as transparency, decentralization, and immutability that make it indispensable. This technology has captivated remarkable attention from researchers as well as government organizations [6]. By using blockchain, electronic medical records (EMR) and donor details can be stored securely. The electronic medical records are hashed through a distributed IFPS file server that is secure and it is immutable. It is done with the aid of user signs acquired digitally at the time of saving, which cannot be redo anymore. This paper aims to/ design a web portal to collect unused medicine and give those to needy people through hospitals or NGOs that will be beneficial to them. It can be done after checking the medicines and it is approved by the admin or hospitals.

Background: Soybean rust caused by Phakopsora pachyrhizi Syd. is one of the major constraints in the production of soybean. Nanotechnology is a new scientific approach that includes use of materials and equipment capable of using physical and chemical properties of a substance at molecular level to explore the biological and material worlds in nanometer-scale and use it in various carriers from medicine to agriculture. Nanotechnology has emerged as one of the most innovative scientific field in agriculture. Among various synthesis methods, green synthesis of nanoparticles is widely used by researchers because it is simple, convenient, eco-friendly and requires less reaction time. Methods: The chitosan based zinc oxide nanoparticles (Ch-ZnONPs), pomegranate aril based sulphur nanoparticles (PA-SNPs) and pomegranate aril based silver nanoparticles (PA-AgNPs) were synthesised, characterised and evaluated under in vitro conditions against soybean rust pustules. Result: The maximum per cent spore inhibition of 70.25, 74.70 and 86.68 per cent over control was recorded in Ch-ZnONPs (1250 ppm), PA-SNPs (2000 ppm) and PA-AgNPs (500 ppm) respectively.

Background: Nanotechnology is emerging approach, which involves the process of reduction of bulk material into nano size particles. Metal based and green based particles can be used in crop management against disease causing pathogens. This study focuses on synthesis of nanoparticles to evaluate its effect on Colletotrichum truncatum that causes pod blight disease in soybean crop. Methods: In this study, green nanoformulation namely, Chitosan based zinc oxide nanoformulation (ChZnNF), P. fluorescens based zinc nanoformulation (PfZnNF), Pomegranate aril-based Sulphur (PASNF) and Pomegranate aril-based silver nano formulations (PAAgNF) were synthesised through irradiation method. These nanoformulations were evaluated against C. truncatum through in vitro technique using poison food technique. The effective concentration of each formulation was also evaluated against C. Truncatum challenge inoculated soybean plants (two varieties). Percent disease index in the glasshouse condition was recorded. Result: In the in vitro analysis, it was found that among the four nanoformulations, PAAgNF was found to be the effective one to inhibit the mycelial growth of C. truncatum with per cent inhibition of 84.71. In the glasshouse study, PAAgNF did not record any disease symptoms besides no record of phytotoxicity symptoms. Thus the outcome indicated that PAAgNF is the effective green nanoformulation against C. truncatum.

Background: Anthracnose is a major foliar disease of soybean associated with Colletotrichum species. In India, C. truncatum is the most widely associated species, whereas, other species are also being reported to cause anthracnose disease in soybean. Methods: Twenty-eight soybean infected samples were collected from different location of India, in order to obtain the pure cultures and were subjected to pathogenicity test. Microscopic observations were made for morphological characterization of all the isolates. Molecular detection was carried out using ITS primers and the sequences were deposited in the NCBI GenBank. Phylogenetic analysis was made using the MegaX bioinformatics tool. Result: The pure cultures were subjected to pathogenicity test, which had reproduced similar symptoms found under field conditions. Microscopic observations on spore morphology were made which revealed that truncate conidia were associated in twenty-seven isolates and cylindrical conidia in one isolate. Molecular detection made showed sequence similarity to Colletotrichum truncatum and the isolate with cylindrical spore was sharing homology with C. plurivorum. Phylogeny analysis clustered the two species into two groups. Hence, the study shows the association of two distinct species in causing anthracnose of soybean.

Growth and yield attributes of cotton were evaluated with the application of varying doses of plant growth regulators during kharif 2020. The experiment was laid out in Randomized Block Design and replicated thrice, conducted at Agricultural College Farm, Bapatla. The treatments comprised of T1: control, T2: Mepiquat chloride 50 ppm at 45 DAS; T3: Mepiquat chloride 50 ppm at 75 DAS; T4: Maleic hydrazide 30ppm at 45 DAS; T5: Maleic hydrazide 30ppm at 75 DAS; T6: Cycocel 60ppm at 45 DAS; T7: Cycocel 60ppm at 75 DAS; T8: Mepiquat chloride 50 ppm at 45 DAS and 75DAS; T9: Maleic hydrazide 30ppm at 45 DAS and 75 DAS; T10: Cycocel 60ppm at 45 DAS and 75 DAS. The results indicated that the highest drymatter accumulation at harvest and stalk yield were recorded in control plot. Maximum number of bolls plant-1, number of picked bolls plant-1 and seed cotton yield were noticed in Mepiquat chloride 50 ppm at 45 + 75 DAS which was on par with T9: Maleic hydrazide 30 ppm at 45 DAS and 75 DAS; T10: Cycocel 60 ppm at 45 DAS and 75 DAS.

Wireless Sensor Node (WSN) helps to track inpatient and remote patient (home/working) health information. Mishandling of the electronic system, patient behaviour and environmental changes which are all lead to incorrect data generation while using WSN for medical purposes. It leads to a false alarm being raised, network resource wastage, a false node priority level and low reliability. We have introduced the Mutual Trust Model (MTM) for Wireless Body Area Network (WBAN) with the help of Fog-Node (FN) to address these issues and to ensure the trustworthiness of the information acquired. In this, First-Hand Trust Method calculates the confidence value of the individual sensor node. Then, with neighbor node support, the Stigmercy Trust Method (STM) is implemented to reinforce the trust source node. Ultimately, the individual patient’s confidence value for the MTM model is determined. With the assistance of the wireless-mininet network emulator and the RYU controller, the network environment model implement, and the results have been obtained. MTM predicts the confidence level of the collected data significantly and produces an accuracy of 92.3 percentage to prevent the emergency band from being used dispensable.

Lysosomal storage diseases comprise different forms of autosomal recessive disorders from which GM1 gangliosidosis has categorized by the accumulation of complex glycolipids associated with a range of progressive neurologic phenotypes. GM1 gangliosidosis is an inherited disorder that progressively destroys nerve cells (neurons) in the brain and spinal cord. GM1 has three main types of onsets, namely infantile (type I), juvenile (type II), and adult (type III) forms. This study provides a series of computational methods that examine the mutations that occurred in GLB1 protein. Initially, the mutational analysis started with 689 amino acid variants for a sequence-based screening and it was done with quite a few In-silico tools to narrow down the most significant variants by utilizing the standard tools; namely, Evolutionary analysis (77 variants), Pathogenicity prediction (44 variants), Stability predictions (30 variants), Biophysical functions (19 variants) and according to the binding site of protein structure with PDB ID 3THC, seven variants (Y83D, Y83H, Y270S, Y270D, W273R, W273D, and Y333H) were narrowed down. Structure based analysis was performed to understand the interacting profile of the native protein and variants with Miglustat; which is the currently used FDA drug as an alternative to enzyme replacement therapy. Molecular Docking study was done to analyze the protein interaction with Miglustat (ligand), as a result native (3THC) structure had a binding affinity of −8.18 kcal/mol and two variant structures had an average binding affinities of −2.61 kcal/mol (Y83D) and − 7.63 kcal/mol (Y270D). Finally, Molecular Dynamics Simulation was performed to know the mutational activity of the protein structures on Miglustat for 50,000 ps. The Y83D variant showed higher deviation than native protein and Y270D in all trajectory analysis. The analysis was done to the protein structures to check the structural variations happened through simulations. This study aids to understand the most deleterious mutants, the activity of the drug to the protein structure and also gives an insight on the stability of the drug with the native and selected variants.

Bacterial blight in pomegranate caused by Xanthomonas axonopodis pv. punicae (Xap) is an increasing threat to pomegranate cultivation in India. To prevent economic losses, it is pivotal to detect the infection in latent stages rather than in symptomatic stages. We have developed an enhanced loop-mediated isothermal amplification (LAMP) technique for the detection of latent Xap infection in pomegranate using six sets of pathovar-specific primers. The DNA-intercalating dye ethidium bromide was standardized for visualizing positive amplification in the LAMP assay. The optimum reaction time was 30 min or more at 65 °C, and assay sensitivity was enhanced down to femtogram (fg) amounts of template DNA (0.153 fg) in the LAMP assay. In artificially inoculated plants, the enhanced LAMP assay detected Xap on the 7th day post inoculation (dpi), while PCR detected Xap only after the 11th dpi. Finally, the specificity of the LAMP assay for Xap was validated against 31 bacterial strains belonging to 22 species. The LAMP assay developed in this study is highly specific, sensitive and robust and can be used as an improved alternative for PCR-based methods for the early detection of Xap infection in pomegranate. Early detection of Xap in pomegranate ensures quality fruits with increased yield by adopting precautionary measures that ensure improved monetary benefit to farmers.

Diabetic retinopathy is becoming a more prevalent disease in diabetic patients nowadays. The surprising fact about the disease is it leaves no symptoms at the beginning stage and the patient can realize the disease only when his vision starts to fall. If the disease is not found at the earliest it leads to a stage where the probability of curing the disease is less. But if we find the disease at that stage, the patient might be in a situation of losing the vision completely. Hence, this paper aims at finding the disease at the earliest possible stage by extracting two features from the retinal image namely Microaneurysms which is found to be the starting symptom showing feature and Hemorrhage which shows symptoms of the other stages. Based on these two features we classify the stage of the disease as normal, beginning, mild and severe using convolutional neural network, a deep learning technique which reduces the burden of manual feature extraction and gives higher accuracy. We also locate the position of these features in the disease affected retinal images to help the doctors offer better medical treatment.

Nowadays, there is an imperative need of synthesising nanomaterials from industrial wastes in an eco-friendly manner. In this concern, Cu and CuO nanoparticles (NPs) were successfully synthesised f...