Using seawater in concrete can be considered as one of the sustainable approaches in construction industry not only to save the freshwater resource but also to promote the use of abandoned seawater resource, especiall...Using seawater in concrete can be considered as one of the sustainable approaches in construction industry not only to save the freshwater resource but also to promote the use of abandoned seawater resource, especially in the construction at the uninhabited area close to the sea where the procurement of fresh water is difficult. In this study, durability against chloride attack of seawater mixed concrete with different replacement ratio of BFS （blast furnace slag） and FA （fly ash） is discussed and the life time until the occurrence of corrosion crack is evaluated. The results show that： （1） Chloride penetration rate of seawater mixed specimens with BFS and FA is lower than that of freshwater mixed OPC （ordinary Portland cement） specimens; （2） Oxygen permeability of seawater mixed specimens with BFS and FA is almost the same or lower than that of freshwater mixed OPC specimens; （3） Total life time （corrosion incubation period and propagation period） of seawater mixed specimens with BFS and FA is almost the same or only slightly shorter than that of freshwater mixed OPC specimens. From the results, it was confirmed that the usage of seawater in concrete mixing is feasible in concrete with the appropriate BFS and FA replacement ratio.展开更多
Per-and Polyfluorinated alkyl substances(PFAS)are a broad class of synthetic compounds that have fluorine substituted for hydrogen in several or all locations and are globally categorized as PFCs(perfluorochemicals;co...Per-and Polyfluorinated alkyl substances(PFAS)are a broad class of synthetic compounds that have fluorine substituted for hydrogen in several or all locations and are globally categorized as PFCs(perfluorochemicals;commonly called fluorinated chemicals).These compounds have unique chemical and physical properties that enable their use in non-stick surfaces,fire-fighting efforts,and as slick coatings.However,recent concerns over the health effects of such compounds,specifically perfluorooctanoic acid and perfluorooctane sulfonic acid(PFOA,PFOS;PFOA/S),have led to increased attention and research by the global community into degradation methods.In this study,soil samples from PFAS-contamination sites were cultured and screened for microbes with PFOA/S degradation potential,which led to the identification of Delftia acidovorans.It was found that D.acidovorans isolated from PFAS-contaminated soils was capable of growth in minimal media with PFOA as a sole carbon resource,and an observable fluoride concentration increase was observed when cells were exposed to PFOA.This suggests potential activity of a dehalogenase enzyme that may be of use in PFOA or PFAS microbial remediation efforts.Several associated haloacid dehalogenases have been identified in the D.acidovorans genome and have been engineered for expression in Escherichia coli for rapid production and purification.These enzymes have shown potential for enzymatic defluorination,a significant step in biological degradation and removal of PFOA/S from the environment.We hypothesize that bioremediation of PFAS using naturally occurring microbial degradation pathways may represent a novel approach to remove PFAS contamination.展开更多
Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the sp...Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the speed limit,and reckless driving.This study analyzed motor vehicle crashes involving young drivers using New Jersey crash data.Specifically,four years of crash data(2016-2019)were gathered and analyzed.Different machine learning(ML)methods,such as Random Forest,Light GBM,Catboost,and XGBoost,were used to predict the injury severity.The performance of the models was evaluated using accuracy,precision,and recall scores.In addition,interpretable ML techniques like sensitivity analysis and Shapley values were conducted to assess the most influential factors’impacts on young driver-related crashes.The results revealed that XGBoost performed better than Random Forest,CatBoost,and LightGBM models in crash severity prediction.Results from the sensitivity analysis showed that multi-vehicle crashes,angular crashes,crashes at intersections,and dark-not-lit conditions had increased crash severity.A partial dependence plot of SHAP values revealed that speeding in clear weather had a higher likelihood of injury crashes,and multi-vehicle crashes at the intersection had more injury crashes.We expect that the results obtained from this study will help policymakers and practitioners take appropriate countermeasures to improve the safety of young drivers in New Jersey.展开更多
文摘Using seawater in concrete can be considered as one of the sustainable approaches in construction industry not only to save the freshwater resource but also to promote the use of abandoned seawater resource, especially in the construction at the uninhabited area close to the sea where the procurement of fresh water is difficult. In this study, durability against chloride attack of seawater mixed concrete with different replacement ratio of BFS （blast furnace slag） and FA （fly ash） is discussed and the life time until the occurrence of corrosion crack is evaluated. The results show that： （1） Chloride penetration rate of seawater mixed specimens with BFS and FA is lower than that of freshwater mixed OPC （ordinary Portland cement） specimens; （2） Oxygen permeability of seawater mixed specimens with BFS and FA is almost the same or lower than that of freshwater mixed OPC specimens; （3） Total life time （corrosion incubation period and propagation period） of seawater mixed specimens with BFS and FA is almost the same or only slightly shorter than that of freshwater mixed OPC specimens. From the results, it was confirmed that the usage of seawater in concrete mixing is feasible in concrete with the appropriate BFS and FA replacement ratio.
文摘Per-and Polyfluorinated alkyl substances(PFAS)are a broad class of synthetic compounds that have fluorine substituted for hydrogen in several or all locations and are globally categorized as PFCs(perfluorochemicals;commonly called fluorinated chemicals).These compounds have unique chemical and physical properties that enable their use in non-stick surfaces,fire-fighting efforts,and as slick coatings.However,recent concerns over the health effects of such compounds,specifically perfluorooctanoic acid and perfluorooctane sulfonic acid(PFOA,PFOS;PFOA/S),have led to increased attention and research by the global community into degradation methods.In this study,soil samples from PFAS-contamination sites were cultured and screened for microbes with PFOA/S degradation potential,which led to the identification of Delftia acidovorans.It was found that D.acidovorans isolated from PFAS-contaminated soils was capable of growth in minimal media with PFOA as a sole carbon resource,and an observable fluoride concentration increase was observed when cells were exposed to PFOA.This suggests potential activity of a dehalogenase enzyme that may be of use in PFOA or PFAS microbial remediation efforts.Several associated haloacid dehalogenases have been identified in the D.acidovorans genome and have been engineered for expression in Escherichia coli for rapid production and purification.These enzymes have shown potential for enzymatic defluorination,a significant step in biological degradation and removal of PFOA/S from the environment.We hypothesize that bioremediation of PFAS using naturally occurring microbial degradation pathways may represent a novel approach to remove PFAS contamination.
文摘Motor vehicle crashes are the leading cause of the death of teenagers in the United States.Young drivers have shown a higher propensity to get involved in crashes due to using a cellphone while driving,breaking the speed limit,and reckless driving.This study analyzed motor vehicle crashes involving young drivers using New Jersey crash data.Specifically,four years of crash data(2016-2019)were gathered and analyzed.Different machine learning(ML)methods,such as Random Forest,Light GBM,Catboost,and XGBoost,were used to predict the injury severity.The performance of the models was evaluated using accuracy,precision,and recall scores.In addition,interpretable ML techniques like sensitivity analysis and Shapley values were conducted to assess the most influential factors’impacts on young driver-related crashes.The results revealed that XGBoost performed better than Random Forest,CatBoost,and LightGBM models in crash severity prediction.Results from the sensitivity analysis showed that multi-vehicle crashes,angular crashes,crashes at intersections,and dark-not-lit conditions had increased crash severity.A partial dependence plot of SHAP values revealed that speeding in clear weather had a higher likelihood of injury crashes,and multi-vehicle crashes at the intersection had more injury crashes.We expect that the results obtained from this study will help policymakers and practitioners take appropriate countermeasures to improve the safety of young drivers in New Jersey.
