Ultra-processed foods(UPFs)are believed to contribute to the development of multiple chronic inflammatory diseases,including inflammatory bowel diseases and metabolic syndrome,based on epidemiological studies and emer...Ultra-processed foods(UPFs)are believed to contribute to the development of multiple chronic inflammatory diseases,including inflammatory bowel diseases and metabolic syndrome,based on epidemiological studies and emerging preclinical and clinical research.Several aspects of food processing and for-mulation in the development of chronic inflammatory diseases are currently being studied.Ongoing research emphasizes epidemiological evidence and mechanistic insights regarding UPFs and their interaction with the intestinal microbiota.In this review,we explore UPFs,their interaction with the intestinal microbiota,and the implications for gastrointestinal health.展开更多
With cloud computing,large chunks of data can be handled at a small cost.However,there are some reservations regarding the security and privacy of cloud data stored.For solving these issues and enhancing cloud computi...With cloud computing,large chunks of data can be handled at a small cost.However,there are some reservations regarding the security and privacy of cloud data stored.For solving these issues and enhancing cloud computing security,this research provides a Three-Layered Security Access model(TLSA)aligned to an intrusion detection mechanism,access control mechanism,and data encryption system.The TLSA underlines the need for the protection of sensitive data.This proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard(AES).For data transfer and storage,this encryption guarantees the data’s authenticity and secrecy.Surprisingly,the solution employs the AES encryption algorithm to secure essential data before storing them in the Cloud to minimize unauthorized access.Role-based access control(RBAC)implements the second strategic level,which ensures specific personnel access certain data and resources.In RBAC,each user is allowed a specific role and Permission.This implies that permitted users can access some data stored in the Cloud.This layer assists in filtering granular access to data,reducing the risk that undesired data will be discovered during the process.Layer 3 deals with intrusion detection systems(IDS),which detect and quickly deal with malicious actions and intrusion attempts.The proposed TLSA security model of e-commerce includes conventional levels of security,such as encryption and access control,and encloses an insight intrusion detection system.This method offers integrated solutions for most typical security issues of cloud computing,including data secrecy,method of access,and threats.An extensive performance test was carried out to confirm the efficiency of the proposed three-tier security method.Comparisons have been made with state-of-art techniques,including DES,RSA,and DUAL-RSA,keeping into account Accuracy,QILV,F-Measure,Sensitivity,MSE,PSNR,SSIM,and computation time,encryption time,and decryption time.The proposed TLSA method provides an accuracy of 89.23%,F-Measure of 0.876,and SSIM of 0.8564 at a computation time of 5.7 s.A comparison with existing methods shows the better performance of the proposed method,thus confirming the enhanced ability to address security issues in cloud computing.展开更多
SARS-CoV-2 transmission and detection on academic campuses in low-to middle-income countries has not been explored.The present study explored wastewater surveillance of SARS-CoV-2 in a campus setting in Pune,Maharasht...SARS-CoV-2 transmission and detection on academic campuses in low-to middle-income countries has not been explored.The present study explored wastewater surveillance of SARS-CoV-2 in a campus setting in Pune,Maharashtra,India,offering insights into variant-specific trends and their correlation with clinical cases over a 2.5 year period from November 2021 to April 2024.We collected 242 wastewater samples from the campus sewershed and processed them to extract RNA and perform RT-qPCR and sequencing,followed by lineage assignment using the LCS tool.Early signals of different SARS-CoV-2 variants,such as BA.2.X,JN.1.X,and KP.2.X,were detected in wastewater prior to its first clinical report in Maharashtra,India.Wastewater viral load strongly correlated with clinical cases during the Omicron phase(ρ=0.73−0.81)compared to the post-Omicron phase(ρ=−0.06 to 0.31).This study also highlights that alerts and warnings issued on the basis of wastewater viral hikes have proven instrumental in preventing outbreaks of SARS-CoV-2 variants on campus.However,downgrading COVID-19 from pandemic status by the WHO resulted in a subsequent decrease in public vigilance,changing the viral dynamic in the last phase of the study.This study showcases the utility of wastewater surveillance in a campus setting as an early warning system and understands the interplay of public health policy effects in viral dynamics within controlled ecosystems,such as campuses or offices.展开更多
文摘Ultra-processed foods(UPFs)are believed to contribute to the development of multiple chronic inflammatory diseases,including inflammatory bowel diseases and metabolic syndrome,based on epidemiological studies and emerging preclinical and clinical research.Several aspects of food processing and for-mulation in the development of chronic inflammatory diseases are currently being studied.Ongoing research emphasizes epidemiological evidence and mechanistic insights regarding UPFs and their interaction with the intestinal microbiota.In this review,we explore UPFs,their interaction with the intestinal microbiota,and the implications for gastrointestinal health.
基金funded by UKRI EPSRC Grant EP/W020408/1 Project SPRITE+2:The Security,Privacy,Identity and Trust Engagement Network plus(phase 2)for this studyThe authors also have been funded by PhD project RS718 on Explainable AI through UKRI EPSRC Grant funded Doctoral Training Centre at Swansea University.
文摘With cloud computing,large chunks of data can be handled at a small cost.However,there are some reservations regarding the security and privacy of cloud data stored.For solving these issues and enhancing cloud computing security,this research provides a Three-Layered Security Access model(TLSA)aligned to an intrusion detection mechanism,access control mechanism,and data encryption system.The TLSA underlines the need for the protection of sensitive data.This proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard(AES).For data transfer and storage,this encryption guarantees the data’s authenticity and secrecy.Surprisingly,the solution employs the AES encryption algorithm to secure essential data before storing them in the Cloud to minimize unauthorized access.Role-based access control(RBAC)implements the second strategic level,which ensures specific personnel access certain data and resources.In RBAC,each user is allowed a specific role and Permission.This implies that permitted users can access some data stored in the Cloud.This layer assists in filtering granular access to data,reducing the risk that undesired data will be discovered during the process.Layer 3 deals with intrusion detection systems(IDS),which detect and quickly deal with malicious actions and intrusion attempts.The proposed TLSA security model of e-commerce includes conventional levels of security,such as encryption and access control,and encloses an insight intrusion detection system.This method offers integrated solutions for most typical security issues of cloud computing,including data secrecy,method of access,and threats.An extensive performance test was carried out to confirm the efficiency of the proposed three-tier security method.Comparisons have been made with state-of-art techniques,including DES,RSA,and DUAL-RSA,keeping into account Accuracy,QILV,F-Measure,Sensitivity,MSE,PSNR,SSIM,and computation time,encryption time,and decryption time.The proposed TLSA method provides an accuracy of 89.23%,F-Measure of 0.876,and SSIM of 0.8564 at a computation time of 5.7 s.A comparison with existing methods shows the better performance of the proposed method,thus confirming the enhanced ability to address security issues in cloud computing.
基金supported by Rockefeller Foundation,USA(2021HTH018).
文摘SARS-CoV-2 transmission and detection on academic campuses in low-to middle-income countries has not been explored.The present study explored wastewater surveillance of SARS-CoV-2 in a campus setting in Pune,Maharashtra,India,offering insights into variant-specific trends and their correlation with clinical cases over a 2.5 year period from November 2021 to April 2024.We collected 242 wastewater samples from the campus sewershed and processed them to extract RNA and perform RT-qPCR and sequencing,followed by lineage assignment using the LCS tool.Early signals of different SARS-CoV-2 variants,such as BA.2.X,JN.1.X,and KP.2.X,were detected in wastewater prior to its first clinical report in Maharashtra,India.Wastewater viral load strongly correlated with clinical cases during the Omicron phase(ρ=0.73−0.81)compared to the post-Omicron phase(ρ=−0.06 to 0.31).This study also highlights that alerts and warnings issued on the basis of wastewater viral hikes have proven instrumental in preventing outbreaks of SARS-CoV-2 variants on campus.However,downgrading COVID-19 from pandemic status by the WHO resulted in a subsequent decrease in public vigilance,changing the viral dynamic in the last phase of the study.This study showcases the utility of wastewater surveillance in a campus setting as an early warning system and understands the interplay of public health policy effects in viral dynamics within controlled ecosystems,such as campuses or offices.
