During the COVID-19 outbreak,the use of single-use medical supplies increased significantly.It is essential to select suitable sites for establishing medical waste treatment stations.It is a big challenge to solve the...During the COVID-19 outbreak,the use of single-use medical supplies increased significantly.It is essential to select suitable sites for establishing medical waste treatment stations.It is a big challenge to solve the medical waste treatment station selection problem due to some conflicting factors.This paper proposes a multi-attribute decision-making(MADM)method based on the partitioned Maclaurin symmetric mean(PMSM)operator.For the medical waste treatment station selection problem,the factors or attributes(these two terms can be interchanged.)in the same clusters are closely related,and the attributes in different clusters have no relationships.The partitioned Maclaurin symmetric mean function(PMSMF)can handle these complex attribute relationships.Hence,we extend the PMSM operator to process the linguistic q-rung orthopair fuzzy numbers(Lq-ROFNs)and propose the linguistic q-rung orthopair fuzzy partitioned Maclaurin symmetric mean(Lq-ROFPMSM)operator and its weighted form(Lq-ROFWPMSM).To reduce the negative impact of unreasonable data on the final output results,we propose the linguistic q-rung orthopair fuzzy partitioned dual Maclaurin symmetric mean(Lq-ROFPDMSM)operator and its weighted form(Lq-ROFWPDMSM).We also discuss the characteristics and typical examples of the above operators.A novel MADM method uses the Lq-ROFWPMSM operator and the Lq-ROFWPDMSM operator to solve the medical waste treatment station selection problem.Finally,the usability and superiority of the proposed method are verified by comparing it with previous methods.展开更多
Bioaerosols from wastewater treatment processes are a significant subgroup of atmospheric aerosols. In the present study,airborne microorganisms generated from a wastewater treatment station（WWTS） that uses an oxida...Bioaerosols from wastewater treatment processes are a significant subgroup of atmospheric aerosols. In the present study,airborne microorganisms generated from a wastewater treatment station（WWTS） that uses an oxidation ditch process were diminished by ventilation.Conventional sampling and detection methods combined with cloning/sequencing techniques were applied to determine the groups,concentrations,size distributions,and species diversity of airborne microorganisms before and after ventilation. There were 3021 ± 537 CFU/m3 of airborne bacteria and 926 ± 132 CFU/m3 of airborne fungi present in the WWTS bioaerosol.Results showed that the ventilation reduced airborne microorganisms significantly compared to the air in the WWTS. Over 60% of airborne bacteria and airborne fungi could be reduced after4 hr of air exchange. The highest removal（92.1% for airborne bacteria and 89.1% for fungi） was achieved for 0.65–1.1 μm sized particles. The bioaerosol particles over 4.7 μm were also reduced effectively. Large particles tended to be lost by gravitational settling and small particles were generally carried away,which led to the relatively easy reduction of bioaerosol particles0.65–1.1 μm and over 4.7 μm in size. An obvious variation occurred in the structure of the bacterial communities when ventilation was applied to control the airborne microorganisms in enclosed spaces.展开更多
基金This research work was supported by the National Natural Science Foundation of China under Grant No.U1805263.
文摘During the COVID-19 outbreak,the use of single-use medical supplies increased significantly.It is essential to select suitable sites for establishing medical waste treatment stations.It is a big challenge to solve the medical waste treatment station selection problem due to some conflicting factors.This paper proposes a multi-attribute decision-making(MADM)method based on the partitioned Maclaurin symmetric mean(PMSM)operator.For the medical waste treatment station selection problem,the factors or attributes(these two terms can be interchanged.)in the same clusters are closely related,and the attributes in different clusters have no relationships.The partitioned Maclaurin symmetric mean function(PMSMF)can handle these complex attribute relationships.Hence,we extend the PMSM operator to process the linguistic q-rung orthopair fuzzy numbers(Lq-ROFNs)and propose the linguistic q-rung orthopair fuzzy partitioned Maclaurin symmetric mean(Lq-ROFPMSM)operator and its weighted form(Lq-ROFWPMSM).To reduce the negative impact of unreasonable data on the final output results,we propose the linguistic q-rung orthopair fuzzy partitioned dual Maclaurin symmetric mean(Lq-ROFPDMSM)operator and its weighted form(Lq-ROFWPDMSM).We also discuss the characteristics and typical examples of the above operators.A novel MADM method uses the Lq-ROFWPMSM operator and the Lq-ROFWPDMSM operator to solve the medical waste treatment station selection problem.Finally,the usability and superiority of the proposed method are verified by comparing it with previous methods.
基金financially supported by the National Key Technology R & D Program of China (No.2012BAC13B04-08)the National Natural Science Foundation of China (Nos.51178451 and 51221892)
文摘Bioaerosols from wastewater treatment processes are a significant subgroup of atmospheric aerosols. In the present study,airborne microorganisms generated from a wastewater treatment station（WWTS） that uses an oxidation ditch process were diminished by ventilation.Conventional sampling and detection methods combined with cloning/sequencing techniques were applied to determine the groups,concentrations,size distributions,and species diversity of airborne microorganisms before and after ventilation. There were 3021 ± 537 CFU/m3 of airborne bacteria and 926 ± 132 CFU/m3 of airborne fungi present in the WWTS bioaerosol.Results showed that the ventilation reduced airborne microorganisms significantly compared to the air in the WWTS. Over 60% of airborne bacteria and airborne fungi could be reduced after4 hr of air exchange. The highest removal（92.1% for airborne bacteria and 89.1% for fungi） was achieved for 0.65–1.1 μm sized particles. The bioaerosol particles over 4.7 μm were also reduced effectively. Large particles tended to be lost by gravitational settling and small particles were generally carried away,which led to the relatively easy reduction of bioaerosol particles0.65–1.1 μm and over 4.7 μm in size. An obvious variation occurred in the structure of the bacterial communities when ventilation was applied to control the airborne microorganisms in enclosed spaces.
