File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most ...File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.展开更多
Objective:To profile the secondary metabolites and to evaluate the antidiabetic potential of hydroethanolic leaf extracts of Conocarpus lancifolius.Methods:The various hydroethanolic extracts of Conocarpus lancifolius...Objective:To profile the secondary metabolites and to evaluate the antidiabetic potential of hydroethanolic leaf extracts of Conocarpus lancifolius.Methods:The various hydroethanolic extracts of Conocarpus lancifolius leaf were prepared by ultrasonication assisted freezedrying.Total phenolic contents,flavonoid contents,antioxidant activity,α-glucosidase andα-amylase inhibitions of leaf extracts were determined.The metabolite profiling was accomplished by UHPLC-Q-TOF-MS/MS analysis.The antidiabetic assessment of the most potent extract was carried out by measuring the hypoglycemic and hypolipidemic effect in the high fat diet-fed diabetic albino mice.The blood glucose level,haemoglobin,total cholesterol,high-density lipoproteins(HDL)and low-density lipoproteins(LDL)were determined.Results:The 60%ethanolic extract exhibited the highest phenolic and flavonoid contents of(349.39±2.13)mg GAE/g dry extract and(116.95±2.34)mg RE/g dry extracts,respectively,and the highest DPPH scavenging activity with an IC50 value of(32.87±1.11)μg/mL.The IC50 values forα-glucosidase andα-amylase inhibitions were(38.64±0.93)μg/mL and(44.80±1.57)μg/mL,respectively.UHPLC-Q-TOF-MS/MS analysis confirmed the presence of gallic acid,ellagic acid,corilagin,kaempherol-3-O-rutinoside,caffeic acid derivative,isorhamnetin and galloyl derivatives in the 60%ethanolic extract.Plant extract at a dose of 450 mg/kg body weight reduced blood glucose level,total cholesterol,LDL and HDL,and increased haemoglobin in alloxan-induced diabetic mice,Conclusions:Conocarpus lancifolius leaves are proved as a good source of biologically functional metabolites and possess antidiabetic activity which may be further explored to treat diabetes.展开更多
Objective:To evaluate the antioxidant potential and pancreatic lipase inhibitory action of optimized hydroethanolic extracts of Solanum nigrum.Methods:Optimized extraction for maximum recovery of metabolites was perfo...Objective:To evaluate the antioxidant potential and pancreatic lipase inhibitory action of optimized hydroethanolic extracts of Solanum nigrum.Methods:Optimized extraction for maximum recovery of metabolites was performed using a combination of freeze-drying and ultrasonication followed by determination of antioxidant and antiobesity properties.The ultra-high performance liquid chromatography equipped with mass spectrometry was used to analyze metabolite profiling of Solanum nigrum.Computational studies were performed using molecular docking and electrostatic potential analysis for individual compounds.The hypolipidemic potential of the most potent extract was assessed in the obese mice fed on fat rich diet.Results:The 80%hydroethanolic extract exhibited the highest extract yield,total phenolic contents,total flavonoid contents along with the strongest 2,2-diphenyl-1-picrylhydrazyl scavenging activity,total antioxidant power,and pancreatic lipase inhibitory properties.The 80%hydroethanolic extract not only regulated the lipid profile of obese mice but also restricted the weight gain in the liver,kidney,and heart.The 80%hydroethanolic extract also reduced alanine transaminase and aspartate transaminase concentrations in serum.The effects of plant extract at 300 mg/kg body weight were quite comparable with the standard drug orlistat.Conclusions:Solanum nigrum is proved as an excellent and potent source of secondary metabolites that might be responsible for obesity mitigation.展开更多
The distribution transformer is the mainstay of the power system.Its internal temperature study is desirable for its safe operation in the power system.The purpose of the present study is to determine direct comprehen...The distribution transformer is the mainstay of the power system.Its internal temperature study is desirable for its safe operation in the power system.The purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading conditions.To achieve this goal,the temperature distribution in the oil,core,and windings are studied at each loading.An experimental study is performed with a 10/0.38 kV,10 kVA oil–immersed transformer equipped with forty–two PT100 sensors(PTs)for temperature measurement installed inside during its manufacturing process.All possible locations for the hottest spot temperature(HST)are considered that made by finite element analysis(FEA)simulation and losses calculations.A resistive load is made to achieve 80%to 120%loading of the test transformer for this experiment.Working temperature is measured in each part of the transformer at all provided loading conditions.It is observed that temperature varies with loading throughout the transformer,and a detailed map of temperature is obtained in the whole test transformer.From these results,the HST stays in the critical section of the primary winding at all loading conditions.This work is helpful to understand the complete internal temperature layout and the location of the HST in distribution transformers.展开更多
In the world of big data,it’s quite a task to organize different files based on their similarities.Dealing with heterogeneous data and keeping a record of every single file stored in any folder is one of the biggest ...In the world of big data,it’s quite a task to organize different files based on their similarities.Dealing with heterogeneous data and keeping a record of every single file stored in any folder is one of the biggest problems encountered by almost every computer user.Much of file management related tasks will be solved if the files on any operating system are somehow categorized according to their similarities.Then,the browsing process can be performed quickly and easily.This research aims to design a system to automatically organize files based on their similarities in terms of content.The proposed methodology is based on a novel strategy that employs the charactaristics of both supervised and unsupervised machine learning approaches for learning categories of digital files stored on any computer system.The results demonstrate that the proposed architecture can effectively and efficiently address the file organization challenges using real-world user files.The results suggest that the proposed system has great potential to automatically categorize almost all of the user files based on their content.The proposed system is completely automated and does not require any human effort in managing the files and the task of file organization become more efficient as the number of files grows.展开更多
文摘File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.
文摘Objective:To profile the secondary metabolites and to evaluate the antidiabetic potential of hydroethanolic leaf extracts of Conocarpus lancifolius.Methods:The various hydroethanolic extracts of Conocarpus lancifolius leaf were prepared by ultrasonication assisted freezedrying.Total phenolic contents,flavonoid contents,antioxidant activity,α-glucosidase andα-amylase inhibitions of leaf extracts were determined.The metabolite profiling was accomplished by UHPLC-Q-TOF-MS/MS analysis.The antidiabetic assessment of the most potent extract was carried out by measuring the hypoglycemic and hypolipidemic effect in the high fat diet-fed diabetic albino mice.The blood glucose level,haemoglobin,total cholesterol,high-density lipoproteins(HDL)and low-density lipoproteins(LDL)were determined.Results:The 60%ethanolic extract exhibited the highest phenolic and flavonoid contents of(349.39±2.13)mg GAE/g dry extract and(116.95±2.34)mg RE/g dry extracts,respectively,and the highest DPPH scavenging activity with an IC50 value of(32.87±1.11)μg/mL.The IC50 values forα-glucosidase andα-amylase inhibitions were(38.64±0.93)μg/mL and(44.80±1.57)μg/mL,respectively.UHPLC-Q-TOF-MS/MS analysis confirmed the presence of gallic acid,ellagic acid,corilagin,kaempherol-3-O-rutinoside,caffeic acid derivative,isorhamnetin and galloyl derivatives in the 60%ethanolic extract.Plant extract at a dose of 450 mg/kg body weight reduced blood glucose level,total cholesterol,LDL and HDL,and increased haemoglobin in alloxan-induced diabetic mice,Conclusions:Conocarpus lancifolius leaves are proved as a good source of biologically functional metabolites and possess antidiabetic activity which may be further explored to treat diabetes.
文摘Objective:To evaluate the antioxidant potential and pancreatic lipase inhibitory action of optimized hydroethanolic extracts of Solanum nigrum.Methods:Optimized extraction for maximum recovery of metabolites was performed using a combination of freeze-drying and ultrasonication followed by determination of antioxidant and antiobesity properties.The ultra-high performance liquid chromatography equipped with mass spectrometry was used to analyze metabolite profiling of Solanum nigrum.Computational studies were performed using molecular docking and electrostatic potential analysis for individual compounds.The hypolipidemic potential of the most potent extract was assessed in the obese mice fed on fat rich diet.Results:The 80%hydroethanolic extract exhibited the highest extract yield,total phenolic contents,total flavonoid contents along with the strongest 2,2-diphenyl-1-picrylhydrazyl scavenging activity,total antioxidant power,and pancreatic lipase inhibitory properties.The 80%hydroethanolic extract not only regulated the lipid profile of obese mice but also restricted the weight gain in the liver,kidney,and heart.The 80%hydroethanolic extract also reduced alanine transaminase and aspartate transaminase concentrations in serum.The effects of plant extract at 300 mg/kg body weight were quite comparable with the standard drug orlistat.Conclusions:Solanum nigrum is proved as an excellent and potent source of secondary metabolites that might be responsible for obesity mitigation.
文摘The distribution transformer is the mainstay of the power system.Its internal temperature study is desirable for its safe operation in the power system.The purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading conditions.To achieve this goal,the temperature distribution in the oil,core,and windings are studied at each loading.An experimental study is performed with a 10/0.38 kV,10 kVA oil–immersed transformer equipped with forty–two PT100 sensors(PTs)for temperature measurement installed inside during its manufacturing process.All possible locations for the hottest spot temperature(HST)are considered that made by finite element analysis(FEA)simulation and losses calculations.A resistive load is made to achieve 80%to 120%loading of the test transformer for this experiment.Working temperature is measured in each part of the transformer at all provided loading conditions.It is observed that temperature varies with loading throughout the transformer,and a detailed map of temperature is obtained in the whole test transformer.From these results,the HST stays in the critical section of the primary winding at all loading conditions.This work is helpful to understand the complete internal temperature layout and the location of the HST in distribution transformers.
文摘In the world of big data,it’s quite a task to organize different files based on their similarities.Dealing with heterogeneous data and keeping a record of every single file stored in any folder is one of the biggest problems encountered by almost every computer user.Much of file management related tasks will be solved if the files on any operating system are somehow categorized according to their similarities.Then,the browsing process can be performed quickly and easily.This research aims to design a system to automatically organize files based on their similarities in terms of content.The proposed methodology is based on a novel strategy that employs the charactaristics of both supervised and unsupervised machine learning approaches for learning categories of digital files stored on any computer system.The results demonstrate that the proposed architecture can effectively and efficiently address the file organization challenges using real-world user files.The results suggest that the proposed system has great potential to automatically categorize almost all of the user files based on their content.The proposed system is completely automated and does not require any human effort in managing the files and the task of file organization become more efficient as the number of files grows.
