Gd-doped Ceria (GCO:Gd_(0.1)Ce_(0.9)O_(1.95)) sensing films have been fabricated successfully on glasses and porous Al_2O_3 ceramic substrates by RF magnetron sputtering.Sputtering conditions such as power and tempera...Gd-doped Ceria (GCO:Gd_(0.1)Ce_(0.9)O_(1.95)) sensing films have been fabricated successfully on glasses and porous Al_2O_3 ceramic substrates by RF magnetron sputtering.Sputtering conditions such as power and temperature have been investigated and the sample was characterized in detail by XRD,SEM and AC impedance spectroscopy.The results show that the films grow preferentially along the (111) compact plane with a pure fluorite structure and the crystal grain grows more sufficiently with increasing of the annealing temperature.In addition,a high oxygen ion conductivity of 2.24×10^(-2) S.cm^(-1) is achieved at 800℃.展开更多
This research measures the reliability of audit firms in predicting bankruptcy for United States （US） listed financial institutions. The object of analysis is the going concern opinion （GCO）, widely considered as ...This research measures the reliability of audit firms in predicting bankruptcy for United States （US） listed financial institutions. The object of analysis is the going concern opinion （GCO）, widely considered as a bankruptcy warning signal to stakeholders. The sample is composed of 42 US listed financial companies that filed for Chapter 11 between 1998 and 2011. To highlight the differences between bankrupting and healthy firms, a matching sample composed of 42 randomly picked healthy US listed financial companies is collected. We concentrate on financial institutions, whereas the existing literature pays considerably greater attention to the industrial sector. This research imbalance is remarkable and particularly unexpected in the wake of recent financial scandals. Literature points out two main approaches on bankruptcy prediction： （1） purely mathematical; and （2） approaches based on a combination of auditor knowledge, expertise, and experience. The use of data mining techniques allows us to benefit from the best features of both approaches. Statistical tools used in the analysis are： Logit regression, support vector machines （SVMs）, and an AdaBoost meta-algorithm. Findings show a quite low reliability of GCOs in predicting bankruptcy. It is likely that auditors consider further information in supporting their audit opinions, aside from financial-economic ratios. The scant predictive ability of auditors might be due to critical relationships with distressed clients, as suggested by recent literature.展开更多
This paper describes the real-time mapping displacement of buildings onto the polygon model of base terrain of geo-spatial information,The buildings are represented as height maps,lcading to low memory requirements an...This paper describes the real-time mapping displacement of buildings onto the polygon model of base terrain of geo-spatial information,The buildings are represented as height maps,lcading to low memory requirements and not involving changes of the original geometry（i.e.no vertices are created or displaced）.The displacement of buildings is mapped toward the protruding direction,The base of textrue which represents the ground in topography is correctly mapped onto base polygon without any distortion.This approach can exhibit the correct,occlusions between buildings and ground due to parallax and correct self-occlusion.展开更多
Soil microorganisms play a key role in soil organic matter dynamics, nutrient cycling, and soil fertility maintenance in forest ecosystems, and they are influenced by stand age and soil depth. However, few studies hav...Soil microorganisms play a key role in soil organic matter dynamics, nutrient cycling, and soil fertility maintenance in forest ecosystems, and they are influenced by stand age and soil depth. However, few studies have simultaneously considered these two factors. In this study, we measured soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), soil basal respiration (SBR) rate, and potential extracellular enzyme activity (EEA) in soil to a depth of 60 cm under 10-, 30-, and 40-year-old Scots pine (Pinus sylvestris var. mongolica) stands (Y10, Y30, and Y40, respectively) in plantations in northern China in 2011. Soil water content (SWC), soil pH, soil organic carbon (SOC), and soil total nitrogen (STN) were also measured to explore their effects on soil microbial indices across different stand ages and soil depths. Our results showed that SMBC, SMBN, and the SBR rate were generally higher for the Y30 stand than for the Y10 and Y40 stands. Potential EEA, except forα-glucosidase, decreased significantly with increasing stand age. Soil organic carbon,STN, SWC, and soil pH explained 67%of the variation in soil microbial attributes among the three stand ages. For the same stand age, soil microbial biomass and the SBR rate decreased with soil depth. Lower microbial biomass, lower SBR rate, and lower EEA for the mature Y40 stand indicate lower substrate availability for soil microorganisms, lower soil quality, and lower microbial adaptability to the environment. Our results suggest that changes in soil quality with stand age should be considered when determining the optimum rotation length of plantations and the best management practices for afforestation programs.展开更多
文摘Gd-doped Ceria (GCO:Gd_(0.1)Ce_(0.9)O_(1.95)) sensing films have been fabricated successfully on glasses and porous Al_2O_3 ceramic substrates by RF magnetron sputtering.Sputtering conditions such as power and temperature have been investigated and the sample was characterized in detail by XRD,SEM and AC impedance spectroscopy.The results show that the films grow preferentially along the (111) compact plane with a pure fluorite structure and the crystal grain grows more sufficiently with increasing of the annealing temperature.In addition,a high oxygen ion conductivity of 2.24×10^(-2) S.cm^(-1) is achieved at 800℃.
文摘This research measures the reliability of audit firms in predicting bankruptcy for United States （US） listed financial institutions. The object of analysis is the going concern opinion （GCO）, widely considered as a bankruptcy warning signal to stakeholders. The sample is composed of 42 US listed financial companies that filed for Chapter 11 between 1998 and 2011. To highlight the differences between bankrupting and healthy firms, a matching sample composed of 42 randomly picked healthy US listed financial companies is collected. We concentrate on financial institutions, whereas the existing literature pays considerably greater attention to the industrial sector. This research imbalance is remarkable and particularly unexpected in the wake of recent financial scandals. Literature points out two main approaches on bankruptcy prediction： （1） purely mathematical; and （2） approaches based on a combination of auditor knowledge, expertise, and experience. The use of data mining techniques allows us to benefit from the best features of both approaches. Statistical tools used in the analysis are： Logit regression, support vector machines （SVMs）, and an AdaBoost meta-algorithm. Findings show a quite low reliability of GCOs in predicting bankruptcy. It is likely that auditors consider further information in supporting their audit opinions, aside from financial-economic ratios. The scant predictive ability of auditors might be due to critical relationships with distressed clients, as suggested by recent literature.
文摘This paper describes the real-time mapping displacement of buildings onto the polygon model of base terrain of geo-spatial information,The buildings are represented as height maps,lcading to low memory requirements and not involving changes of the original geometry（i.e.no vertices are created or displaced）.The displacement of buildings is mapped toward the protruding direction,The base of textrue which represents the ground in topography is correctly mapped onto base polygon without any distortion.This approach can exhibit the correct,occlusions between buildings and ground due to parallax and correct self-occlusion.
基金This study was supported by projects of the National Natural Science Foundation of China(Nos.31972939,31630009 and 31670325)the National Basic Research Pro-gram of China(No.2016YFC0500701)+1 种基金the Research Fund of the State Key Laboratory of Soil and Sustainable Agri-culture,Nanjing Institute of Soil Science,Chinese Academy of Sciences(No.Y412201439)the University Con-struction Projects from the Central Authorities in Beiing of China.
文摘Soil microorganisms play a key role in soil organic matter dynamics, nutrient cycling, and soil fertility maintenance in forest ecosystems, and they are influenced by stand age and soil depth. However, few studies have simultaneously considered these two factors. In this study, we measured soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), soil basal respiration (SBR) rate, and potential extracellular enzyme activity (EEA) in soil to a depth of 60 cm under 10-, 30-, and 40-year-old Scots pine (Pinus sylvestris var. mongolica) stands (Y10, Y30, and Y40, respectively) in plantations in northern China in 2011. Soil water content (SWC), soil pH, soil organic carbon (SOC), and soil total nitrogen (STN) were also measured to explore their effects on soil microbial indices across different stand ages and soil depths. Our results showed that SMBC, SMBN, and the SBR rate were generally higher for the Y30 stand than for the Y10 and Y40 stands. Potential EEA, except forα-glucosidase, decreased significantly with increasing stand age. Soil organic carbon,STN, SWC, and soil pH explained 67%of the variation in soil microbial attributes among the three stand ages. For the same stand age, soil microbial biomass and the SBR rate decreased with soil depth. Lower microbial biomass, lower SBR rate, and lower EEA for the mature Y40 stand indicate lower substrate availability for soil microorganisms, lower soil quality, and lower microbial adaptability to the environment. Our results suggest that changes in soil quality with stand age should be considered when determining the optimum rotation length of plantations and the best management practices for afforestation programs.
