Biologically and catalytically important magnesium oxide nanoparticles (MgONPs) have been synthesised successfully in an eco-friendly mode using Annona squamosa seeds. The synthesised nanoparticles were characterised by spectroscopic analysis methods. UV-vis, XRD powder diffraction and EDX were used to confirm the nanoparticles' stability, phase identification and element content, respectively. SEM and TEM were also used to predict the size and morphology of the nanoparticles. The biogenic synthesis of MgONP has been judged for its antibacterial activity against Pactobacterium carotovorum and for its catalytic activity in the synthesis of 2-benzimidazole and has been shown to be potentially effective against pathogenic strain and in terms of catalytic activity in the formation of benzimidazole.

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In this study, steroidal sitosteryl hydrogen phthalate (stigmast-5-en-3b-yl hydrogen phthalate) was synthesized by the reaction of 3b-sitosterol and phthalic anhydride using silica gel as a solid support under microwave irradiation (MWI). The comparative study of microwave assisted synthesis and conventional synthesis of the steroidal compound in a hazardous solvent revealed that the former method provided shortened reaction times at increased yields. The compounds obtained by the two procedures were characterized by infrared spectroscopy, proton, carbon-13 nuclear magnetic resonance (1H and 13C NMR) and high-resolution mass spectrometry. The synthesized compound was screened for in vitro antifungal activity against Aspergillus niger and Candida albicans by the Kirby-Bauer Well Diffusion method. The synthesized compound was subjected to the molecular docking simulation with a receptor (CYP51). The findings of the antifungal and docking studies revealed that the synthesized sitosteryl hydrogen phthalate could be considered as a suitable inhibitor of Lanosterol 14a-demethylase (CYP51). In addition, the molecular docking approach was applied to design hypothetical derivatives of sitosteryl hydrogen phthalate inhibitors against the antifungal target and to compare findings with the binding score of the molecular synthesized 3b-sitosteryl hydrogen phthalate.

Accuracy of English-language Question Answering (QA) systems has improved significantly in recent years with the advent of Transformer-based models (e.g., BERT). These models are pre-trained in a self-supervised fashion with a large English text corpus and further fine-tuned with a massive English QA dataset (e.g., SQuAD). However, QA datasets on such a scale are not available for most of the other languages. Multi-lingual BERT-based models (mBERT) are often used to transfer knowledge from high-resource languages to low-resource languages. Since these models are pre-trained with huge text corpora containing multiple languages, they typically learn language-agnostic embeddings for tokens from different languages. However, directly training an mBERT-based QA system for low-resource languages is challenging due to the paucity of training data. In this work, we augment the QA samples of the target language using translation and transliteration into other languages and use the augmented data to finetune an mBERT-based QA model, which is already pre-trained in English. Experiments on the Google ChAII dataset show that finetuning the mBERT model with translations from the same language family boosts the question-answering performance, whereas the performance degrades in the case of crosslanguage families. We further show that introducing a contrastive loss between the translated question-context feature pairs during the finetuning process, prevents such degradation with cross-lingual family translations and leads to marginal improvement. The code for this work is available at https://github.com/g okulkarthik/mucot.

Agni plays an important role in digestion of food. All the diseases are produced by Mandagni. Mandagni leads to the formation of Ama which is the root cause of Roga Utpatti. There are so many diseases originating beacause of Ama which are grouped under Ampradoshaja Vikara. Deepana and Pachana are considered under the heading of Shamanaushadhis. It is the first line of treatment selected in order to overcome Ampradoshaja Vikaras. They are very successfully utilised for the day to day practice.There are different views given by our Acharyas regarding Agni, Ama, Amaja Vikaras and role of Deepana and Pachana in their management which are highlighted in this article.