2024年12月在Labelexpo South China 2024开展首日,Esko、Fiery与弘博智能&弘源数码全球战略合作签约仪式隆重举办。在签约仪式上,全球包装及标签行业解决方案的领先者Esko,数字印刷流程解决方案佼佼者Fiery,以及专业的标签数字喷...2024年12月在Labelexpo South China 2024开展首日,Esko、Fiery与弘博智能&弘源数码全球战略合作签约仪式隆重举办。在签约仪式上,全球包装及标签行业解决方案的领先者Esko,数字印刷流程解决方案佼佼者Fiery,以及专业的标签数字喷墨制造及方案解决商弘博智能&弘源数码。展开更多
One hundred and five raw cow milk samples were collected from cattle farms located in Fieri from 2007 to 2009 and have been analyzed for presence of coagulase positive Staphylococcus aureus. Nineteen samples were conf...One hundred and five raw cow milk samples were collected from cattle farms located in Fieri from 2007 to 2009 and have been analyzed for presence of coagulase positive Staphylococcus aureus. Nineteen samples were confirmed positive for the presence of this pathogen. Stapylococcus aureus isolates identified appeared typically and atypically characteristics of growth colonies in Baird Parker agar plates at 37°C for 24-48 h. 6 out of 19 strains showed typical characteristics and 13 out 19 （68%） isolates had atypical characteristics. Coagulase positive Staphylococcus aureus was found in 18% （1911 05） of fresh milk samples. Milk produced by cows with subclinical mastitis largely influences Staphylococcus aureus count of bulk tank milk than contamination of milking and milk handling equipment by this pathogen. All S. aureus isolates were coagulase positive. 5 （or about 25%） of isolates of S. aureus identified were resistant to penicillin, 7 out 19 isolates or 36% resistant to methicilin and 9 out 19 strains or 47% resistant to vancomycin. Another objective of this study was the evaluation of the number of S. aureus per mL raw milk. The results confirmed that II （57.8%） out of 19 positive cases had more than 100 cfu/mL, indicating a possible risk for intoxication caused by production of entertoxines of coagulase positive S. aureus.展开更多
Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes.This condition,known as hot-hole blasting,is dangerous due to the inc...Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes.This condition,known as hot-hole blasting,is dangerous due to the increased possibility of premature explosions in loaded blastholes.Thus,it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of blastholes.Additionally,it will help achieve the desired fragment size.This study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery seam.Data on blast design,rock mass,and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational techniques.The coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute error(MAE),mean square error(MSE),variance account for(VAF)and coefficient of efficiency in percentage(CE)were calculated to validate the results.It indicates that the random forest algorithm(RFA)outperforms the artificial neural network(ANN),response surface method(RSM),and decision tree(DT).The values of R^(2),RMSE,MAE,MSE,VAF,and CE for RFA are 0.94,0.034,0.027,0.001,93.58,and 93.01,respectively.Multiple parametric sensitivity analyses(MPSAs)of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment size.The analysis was finally used to define the best blast design variables to achieve optimum fragment size from blasting.The optimum factor values for RFA of S/B,ld/B and ls/ld are 1.03,1.85 and 0.7,respectively.展开更多
文摘2024年12月在Labelexpo South China 2024开展首日,Esko、Fiery与弘博智能&弘源数码全球战略合作签约仪式隆重举办。在签约仪式上,全球包装及标签行业解决方案的领先者Esko,数字印刷流程解决方案佼佼者Fiery,以及专业的标签数字喷墨制造及方案解决商弘博智能&弘源数码。
文摘One hundred and five raw cow milk samples were collected from cattle farms located in Fieri from 2007 to 2009 and have been analyzed for presence of coagulase positive Staphylococcus aureus. Nineteen samples were confirmed positive for the presence of this pathogen. Stapylococcus aureus isolates identified appeared typically and atypically characteristics of growth colonies in Baird Parker agar plates at 37°C for 24-48 h. 6 out of 19 strains showed typical characteristics and 13 out 19 （68%） isolates had atypical characteristics. Coagulase positive Staphylococcus aureus was found in 18% （1911 05） of fresh milk samples. Milk produced by cows with subclinical mastitis largely influences Staphylococcus aureus count of bulk tank milk than contamination of milking and milk handling equipment by this pathogen. All S. aureus isolates were coagulase positive. 5 （or about 25%） of isolates of S. aureus identified were resistant to penicillin, 7 out 19 isolates or 36% resistant to methicilin and 9 out 19 strains or 47% resistant to vancomycin. Another objective of this study was the evaluation of the number of S. aureus per mL raw milk. The results confirmed that II （57.8%） out of 19 positive cases had more than 100 cfu/mL, indicating a possible risk for intoxication caused by production of entertoxines of coagulase positive S. aureus.
文摘Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes.This condition,known as hot-hole blasting,is dangerous due to the increased possibility of premature explosions in loaded blastholes.Thus,it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of blastholes.Additionally,it will help achieve the desired fragment size.This study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery seam.Data on blast design,rock mass,and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational techniques.The coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute error(MAE),mean square error(MSE),variance account for(VAF)and coefficient of efficiency in percentage(CE)were calculated to validate the results.It indicates that the random forest algorithm(RFA)outperforms the artificial neural network(ANN),response surface method(RSM),and decision tree(DT).The values of R^(2),RMSE,MAE,MSE,VAF,and CE for RFA are 0.94,0.034,0.027,0.001,93.58,and 93.01,respectively.Multiple parametric sensitivity analyses(MPSAs)of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment size.The analysis was finally used to define the best blast design variables to achieve optimum fragment size from blasting.The optimum factor values for RFA of S/B,ld/B and ls/ld are 1.03,1.85 and 0.7,respectively.
