The present work involves the development of siliconized epoxy resin to overcome the drawback of epoxy resin like poor impact strength, high rigidity and moisture absorbing nature because of which they are not applied...The present work involves the development of siliconized epoxy resin to overcome the drawback of epoxy resin like poor impact strength, high rigidity and moisture absorbing nature because of which they are not applied as corrosion resistant coating. By embedding silicone into the back bone of polymeric resin the above drawback can be reduced to substantial level. For achieving this, siliconised epoxy resins were prepared by reacting amine terminated silicone resin with novolac epoxy resin and meta-phenylenediamine was used as curing agent. The applied films of coating were baked at 150oC. Cured films were evaluated for their thermal, mechanical, chemical and corrosion resistance properties to ascertain the commercial utility of these eco-friendly resin for use in anti corrosive formulations. The siliconized epoxy resins system was found to exhibit good thermal and anticorrosive properties.展开更多
In spite of a steady improvement in the safety of cataract surgery since the inception of phacoemulsification, diagnosing and managing posterior capsular rent still remains a challenge. Identification of the pre-exist...In spite of a steady improvement in the safety of cataract surgery since the inception of phacoemulsification, diagnosing and managing posterior capsular rent still remains a challenge. Identification of the pre-existing risk factors is of utmost importance so that precautionary modifications are done in the surgery to prevent this complication. Once it happens, timely realization and appropriate management can have excellent outcomes.展开更多
COVID-19 is caused by the novel coronavirus severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)and smashed our society severely.Many efforts/measures have been taken worldwide to control coronavirus disease 20...COVID-19 is caused by the novel coronavirus severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)and smashed our society severely.Many efforts/measures have been taken worldwide to control coronavirus disease 2019(COVID-19)but it is spreading ceaselessly across the globe.Interestingly,Chinese medicine was used to treat COVID-19 and they found better recovery results.This has also drawn the attention of the scientific community to Ayurveda where traditional knowledge of this domain can be explored for finding COVID-19 a cure or prevention.展开更多
Objective Cardiovascular diseases(CVD)are one of the most prevalent diseases in India amounting for nearly 30%of total deaths.A dearth of research on CVD risk scores in Indian population,limited performance of convent...Objective Cardiovascular diseases(CVD)are one of the most prevalent diseases in India amounting for nearly 30%of total deaths.A dearth of research on CVD risk scores in Indian population,limited performance of conventional risk scores and inability to reproduce the initial accuracies in randomised clinical trials has led to this study on large-scale patient data.The objective is to develop an Artificial Intelligence-based Risk Score(AICVD)to predict CVD event(eg,acute myocardial infarction/acute coronary syndrome)in the next 10 years and compare the model with the Framingham Heart Risk Score(FHRS)and QRisk3.Methods Our study included 31599 participants aged 18–91 years from 2009 to 2018 in six Apollo Hospitals in India.A multistep risk factors selection process using Spearman correlation coefficient and propensity score matching yielded 21 risk factors.A deep learning hazards model was built on risk factors to predict event occurrence(classification)and time to event(hazards model)using multilayered neural network.Further,the model was validated with independent retrospective cohorts of participants from India and the Netherlands and compared with FHRS and QRisk3.Results The deep learning hazards model had a good performance(area under the curve(AUC)0.853).Validation and comparative results showed AUCs between 0.84 and 0.92 with better positive likelihood ratio(AICVD−6.16 to FHRS−2.24 and QRisk3−1.16)and accuracy(AICVD−80.15%to FHRS 59.71%and QRisk351.57%).In the Netherlands cohort,AICVD also outperformed the Framingham Heart Risk Model(AUC−0.737 vs 0.707).Conclusions This study concludes that the novel AI-based CVD Risk Score has a higher predictive performance for cardiac events than conventional risk scores in Indian population.展开更多
文摘The present work involves the development of siliconized epoxy resin to overcome the drawback of epoxy resin like poor impact strength, high rigidity and moisture absorbing nature because of which they are not applied as corrosion resistant coating. By embedding silicone into the back bone of polymeric resin the above drawback can be reduced to substantial level. For achieving this, siliconised epoxy resins were prepared by reacting amine terminated silicone resin with novolac epoxy resin and meta-phenylenediamine was used as curing agent. The applied films of coating were baked at 150oC. Cured films were evaluated for their thermal, mechanical, chemical and corrosion resistance properties to ascertain the commercial utility of these eco-friendly resin for use in anti corrosive formulations. The siliconized epoxy resins system was found to exhibit good thermal and anticorrosive properties.
文摘In spite of a steady improvement in the safety of cataract surgery since the inception of phacoemulsification, diagnosing and managing posterior capsular rent still remains a challenge. Identification of the pre-existing risk factors is of utmost importance so that precautionary modifications are done in the surgery to prevent this complication. Once it happens, timely realization and appropriate management can have excellent outcomes.
文摘COVID-19 is caused by the novel coronavirus severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)and smashed our society severely.Many efforts/measures have been taken worldwide to control coronavirus disease 2019(COVID-19)but it is spreading ceaselessly across the globe.Interestingly,Chinese medicine was used to treat COVID-19 and they found better recovery results.This has also drawn the attention of the scientific community to Ayurveda where traditional knowledge of this domain can be explored for finding COVID-19 a cure or prevention.
文摘Objective Cardiovascular diseases(CVD)are one of the most prevalent diseases in India amounting for nearly 30%of total deaths.A dearth of research on CVD risk scores in Indian population,limited performance of conventional risk scores and inability to reproduce the initial accuracies in randomised clinical trials has led to this study on large-scale patient data.The objective is to develop an Artificial Intelligence-based Risk Score(AICVD)to predict CVD event(eg,acute myocardial infarction/acute coronary syndrome)in the next 10 years and compare the model with the Framingham Heart Risk Score(FHRS)and QRisk3.Methods Our study included 31599 participants aged 18–91 years from 2009 to 2018 in six Apollo Hospitals in India.A multistep risk factors selection process using Spearman correlation coefficient and propensity score matching yielded 21 risk factors.A deep learning hazards model was built on risk factors to predict event occurrence(classification)and time to event(hazards model)using multilayered neural network.Further,the model was validated with independent retrospective cohorts of participants from India and the Netherlands and compared with FHRS and QRisk3.Results The deep learning hazards model had a good performance(area under the curve(AUC)0.853).Validation and comparative results showed AUCs between 0.84 and 0.92 with better positive likelihood ratio(AICVD−6.16 to FHRS−2.24 and QRisk3−1.16)and accuracy(AICVD−80.15%to FHRS 59.71%and QRisk351.57%).In the Netherlands cohort,AICVD also outperformed the Framingham Heart Risk Model(AUC−0.737 vs 0.707).Conclusions This study concludes that the novel AI-based CVD Risk Score has a higher predictive performance for cardiac events than conventional risk scores in Indian population.
