Ayurveda is a renowned traditional medicine practiced in India from ancient times and Clitoria ternatea is one such prospective medicinal herb incorporated as an essential constituent in a brain tonic called as medhya...Ayurveda is a renowned traditional medicine practiced in India from ancient times and Clitoria ternatea is one such prospective medicinal herb incorporated as an essential constituent in a brain tonic called as medhya rasayan for treating neurological disorders.This work emphasises the significance of the plant as a brain drug there by upholding Indian medicine.The phytochemicals from the root extract were extricated using gas chromatography–mass spectrometry assay and molecular docking against the protein Monoamine oxidase was performed with four potential compounds along with four reference compounds of the plant.This persuades the prospect of C.ternatea as a remedy for neurodegenerative diseases and depression.The in silico assay enumerates that a major compound(Z)-9,17-octadecadienal obtained from the chromatogram with a elevated retention time of 32.99 furnished a minimum binding affinity energy value of-6.5 kcal/mol against monoamine oxidase(MAO-A).The interactions with the amino acid residues ALA 68,TYR 60 and TYR 69 were analogous to the reference compound kaempferol-3-monoglucoside with a least score of-13.90/-12.95 kcal/mol against the isoforms(MAO)A and B.This study fortifies the phytocompounds of C.ternatea as MAO-inhibitors and to acquire a pharmaceutical approach in rejuvenating Ayurvedic medicine.展开更多
With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex...With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline.Abstractive summarization task is framed as seq2seq modeling.Existing seq2seq methods perform better on short sequences;however,for long sequences,the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this paper.The novelty is to parallelize the sequence computation training by incorporating feed-forward,the self-normalized neural network in the Extractive phase using Intra Cosine Attention Similarity(Ext-ICAS)with sentence dependency position.Also,it does not require any normalization technique explicitly.Our proposed abstractive Bidirectional Long Short Term Memory(Bi-LSTM)encoder sequence model performs better than the Bidirectional Gated Recurrent Unit(Bi-GRU)encoder with minimum training loss and with fast convergence.The proposed model was evaluated on the Cable News Network(CNN)/Daily Mail dataset and an average rouge score of 0.435 was achieved also computational training in the extractive phase was reduced by 59%with an average number of similarity computations.展开更多
文摘Ayurveda is a renowned traditional medicine practiced in India from ancient times and Clitoria ternatea is one such prospective medicinal herb incorporated as an essential constituent in a brain tonic called as medhya rasayan for treating neurological disorders.This work emphasises the significance of the plant as a brain drug there by upholding Indian medicine.The phytochemicals from the root extract were extricated using gas chromatography–mass spectrometry assay and molecular docking against the protein Monoamine oxidase was performed with four potential compounds along with four reference compounds of the plant.This persuades the prospect of C.ternatea as a remedy for neurodegenerative diseases and depression.The in silico assay enumerates that a major compound(Z)-9,17-octadecadienal obtained from the chromatogram with a elevated retention time of 32.99 furnished a minimum binding affinity energy value of-6.5 kcal/mol against monoamine oxidase(MAO-A).The interactions with the amino acid residues ALA 68,TYR 60 and TYR 69 were analogous to the reference compound kaempferol-3-monoglucoside with a least score of-13.90/-12.95 kcal/mol against the isoforms(MAO)A and B.This study fortifies the phytocompounds of C.ternatea as MAO-inhibitors and to acquire a pharmaceutical approach in rejuvenating Ayurvedic medicine.
文摘With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline.Abstractive summarization task is framed as seq2seq modeling.Existing seq2seq methods perform better on short sequences;however,for long sequences,the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this paper.The novelty is to parallelize the sequence computation training by incorporating feed-forward,the self-normalized neural network in the Extractive phase using Intra Cosine Attention Similarity(Ext-ICAS)with sentence dependency position.Also,it does not require any normalization technique explicitly.Our proposed abstractive Bidirectional Long Short Term Memory(Bi-LSTM)encoder sequence model performs better than the Bidirectional Gated Recurrent Unit(Bi-GRU)encoder with minimum training loss and with fast convergence.The proposed model was evaluated on the Cable News Network(CNN)/Daily Mail dataset and an average rouge score of 0.435 was achieved also computational training in the extractive phase was reduced by 59%with an average number of similarity computations.
