Assessment of drillability of rocks is vital in the selection,operation,and performance evaluation of cutting tools used in various excavation machinery deployed in mining and tunneling.The commonly used rock drillabi...Assessment of drillability of rocks is vital in the selection,operation,and performance evaluation of cutting tools used in various excavation machinery deployed in mining and tunneling.The commonly used rock drillability prediction methods,namely,drilling rate index(DRI)and Cerchar hardness index(CHI)have limitations in predicting the penetration rate due to differential wear of the cutting tool in rocks with varied hardness and abrasivity.Since cutting tools get blunt differently in different rocks,the stress beneath the tip of the bit decreases until it reaches a threshold value beyond which the penetration rate becomes constant.In this research,a new composite penetration rate index(CPRI)is suggested based on the investigations on four metamorphic rocks viz.quartzite,gneiss,schist and phyllite with varied hardness-abrasivity values.The penetration-time behavior was classified into active,moderate,passive,and dormant phases based on the reduction in penetration rate at different stages of drilling.A comparison of predicted penetration rate values using DRI and CPRI with actual penetration rate values clearly establishes the supremacy of CPRI.Micro-structure and hardness-based index was also developed and correlated with CPRI.The new indices can help predict cutting tool penetration and its consumption more accurately.展开更多
Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire char...Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire characteristics,regional assessment of fire severity is crucial.The objectives of this study were:(1)to test the performance of different satellite imagery and spectral indices,and two field—measured severity indices,CBI(Composite Burn Index)and GeoCBI(Geometrically structured Composite Burn Index)to assess fire severity;(2)to calculate classification thresholds for spectral indices that performed best in the study areas;and(3)to generate fire severity maps that could be used to determine the ecological impact of forest fires.Five large fires in Pinus brutia(Turkish pine)and Pinus nigra subsp.pallasiana var.pallasiana(Anatolian black pine)—dominated forests during 2020 and 2021 were selected as study sites.The results show that GeoCBI provided more reliable estimates of field—measured fire severity than CBI.While Sentinel-2 and Landsat-8/OLI images performed similarly well,MODIS performed poorly.Fire severity classification thresholds were determined for Sentinel-2 based RdNBR,dNBR,dSAVI,dNDVI,and dNDMI and Landsat-8/OLI based dNBR,dNDVI,and dSAVI.Among several spectral indices,the highest accuracy for fire severity classification was found for Sentinel-2 based RdNBR(72.1%)and Landsat-8/OLI based dNBR(69.2%).The results can be used to assess and map fire severity in forest ecosystems similar to those in this study.展开更多
Remote sensing technology, as the most advanced method for collecting data, along with the common ways often used in the past on research of environmenal science, was integrated to study the relationship between envir...Remote sensing technology, as the most advanced method for collecting data, along with the common ways often used in the past on research of environmenal science, was integrated to study the relationship between environmental pollution of coal mine and spectral characteristics of nearby plants. With compositive index and mean refiectivity at near infrared, a regression equation was established, and a conclusion was made that spectral reflectivity can be used to distinguish regions with different pollution degree. Through testing with real status of the research region, it is verified that this kind of integration and conclusion not only are helpful for human being in controlling the movement law of pollutants and the corresponding change of coal mine environmental quality, but also bring a new way for the research of environment problems of coal mine.展开更多
As a type of non-renewable industrial resource,petroleum is of great strategic significance to the development of each nation.Ever since the 19th century,an array of oil crises have incurred certain downturn of the wo...As a type of non-renewable industrial resource,petroleum is of great strategic significance to the development of each nation.Ever since the 19th century,an array of oil crises have incurred certain downturn of the world economy.Pertinent studies have implied that financial crisis is always prone to be accompanied with oil crisis,yet the relevance of crude oil to the stock market,the barometer of the macro-economy,is ambiguous.In order to avoid the risks induced by the volatility of oil price,the oil futures market has appeared,and at the same time,the financial property of crude oil has become far more evident.Owing to lack of mature mining and refining technology,China still imports large amounts of oil from abroad at present.Thus,the economy of China is susceptible to fluctuation in petroleum price.As for Australia,the only net importer among the member countries of the International Energy Agency(IEA),it fails to attain the target of holding 90 days of fuel reserves set by the agency.However,in 2013,Australian Lincoln Energy announced that a gigantic shale oil field with an estimated value of 21 trillion US dollars was found in the South of Australia,and that if that field is mined,Australia has the possibility to turn into a net exporter of crude oil.It can be expected that the Australia’s economic conditions would be closely related to the international oil to a certain extent.Based on the approaches of the first difference and co-integration,this paper delves into the volatility spillover effect of crude oil futures on the Chinese and Australian stock markets.According to the empirical findings,in the short run,the price of crude oil futures has a greater impact on the Australian composite index than on the Chinese composite index.However,crude oil futures are negatively related to the Chinese composite index in the long run.The price of crude oil futures has no significant impact on the Chinese sector indices,but it has a certain impact on the Australian utilities,energy,materials,and industrial sector indices.In the Chinese stock market,the movement of short-run effect to long-run effect of crude oil futures on sector indices is in the reverse direction.Finally,the price of crude oil futures has a significant volatility spillover effect only on the Australian utilities sector index.展开更多
Uncertainty extremely interferes with the execution of farm machinery operation.Treating uncertainties is especially important for machinery cooperatives providing social service since they face more uncertain influen...Uncertainty extremely interferes with the execution of farm machinery operation.Treating uncertainties is especially important for machinery cooperatives providing social service since they face more uncertain influence factors(UIFs)than family farms.Under social service circumstance,uncertainties may arise from participants and environments.Classification and evaluation of UIFs were studied in this research.According to the production system,32 UIFs are defined and classified into six categories,which include supply,demand,interactivity,nature,society and others.Uncertainty composite index(UCI)is defined to evaluate the importance of UIFs,which is the square root of the product of occurrence frequency(OF)and impact degree(ID)calculated from the well-designed questionnaire responded by farm machinery operators.UCI is divided into five ranks based on normalization distribution test to illustrate the level of importance.Results from questionnaire showed that natural UIFs have an extreme impact on farm operation,UIFs of the demand and the supply have a serious influence on farm operation,UIFs of interactivity cannot be ignored,and social UIFs have a weak impact on farm operations.This study discovered the uncertainty problems under the specific circumstance of farm machinery service,which may provide a theoretical basis and potential methods for risk management of machinery cooperatives.展开更多
To address human dependence on natural resources and anthropogenic impacts on ecosystem health,understanding and management of the linkages between nature and human well-being(HWB)are urgently needed.One fundamental b...To address human dependence on natural resources and anthropogenic impacts on ecosystem health,understanding and management of the linkages between nature and human well-being(HWB)are urgently needed.One fundamental barrier is the lack of quantitative indicators and models that integrate HWB with direct and indirect drivers of change in natural resources.While primary surveys provide the most valid HWB measures,extensive new data collection is often costly,especially for large-scale studies.Therefore,it is vital to develop methods and indices based on existing data(e.g.,census data,survey data)for real-world application.To address this,we propose a new method of using structural equation modeling to construct robust,spatially explicit HWB indices from existing data and demonstrate its validity and usefulness in Cambodia.Our method is scale-free and applicable to different frameworks and data sources and thus supports relatively easy replication in many other contexts.Further application and refinement could improve understanding of human-nature interactions,move toward robust theory development,and guide natural resource management decisions.展开更多
Introduction:Quantifying fire severity is an important aspect of studying the response mechanism of terrestrial ecosystems to wildfire,and it is of great significance to fire ecology.In this paper we comprehensively i...Introduction:Quantifying fire severity is an important aspect of studying the response mechanism of terrestrial ecosystems to wildfire,and it is of great significance to fire ecology.In this paper we comprehensively introduce and compare the classification and quantification methods for fire severity;we discuss the development and application status of various methods,and we elucidate their existing problems.Results:1)According to features of the burned area,fire severity can be classified as light,moderate,and heavy.2)Using composite burn index(CBI)to quantify and record the fire severity.3)In quantifying fire severity with vegetation change,there are certain limitations and theoretical problems to be solved.4)Remote sensing could very well be an important means of measuring fire severity in the future,but there are still many problems that need to be solved before the remote sensing index can become a global fire severity indicator.Discussion and Conclusion:Only by clarifying the relationship between fire behavior,fire severity,time related variables and the pre-and post-fire ecosystem can the existing models be perfected or new,better fire severity measurement models be proposed for broad applications.展开更多
Business survey,which starts from the microeconomic level,is a widely used short-term forecasting tool in practice.In this study,the authors examine whether foreign trade survey data collected by China’s Ministry of ...Business survey,which starts from the microeconomic level,is a widely used short-term forecasting tool in practice.In this study,the authors examine whether foreign trade survey data collected by China’s Ministry of Commerce would provide reliable forecasts of China’s foreign trade.The research procedure is designed from three perspectives including forecast information test,turning point forecast,and out-of-sample value forecast.First,Granger causality test detects whether survey data lead exports and imports.Second,business cycle analysis,a non-model based method,is performed.The authors construct composite indexes with business survey data to forecast turning points of foreign trade.Third,model-based numerical forecasting methods,including the Autoregressive Integrated Moving Average Model with Exogenous Variables(ARIMAX)and the artificial neural networks(ANNs)models are estimated.Empirical results show that survey data granger cause imports and exports,the leading composite index provides signal for changes of trade cycles,and quantitative models including survey data generate more accurate forecasts than benchmark models.It is concluded that trade survey data has excellent predictive capabilities for imports and exports,which can offer some priorities for government policy-making and enterprise decision making.展开更多
In late July 2018, a compound drought and heat event(CDHE) occurred in the middle of the Yangtze River basin(MYRB) and caused great damage to the national economy. The CDHE over the MYRB has been documented to be link...In late July 2018, a compound drought and heat event(CDHE) occurred in the middle of the Yangtze River basin(MYRB) and caused great damage to the national economy. The CDHE over the MYRB has been documented to be linked with intraseasonal oscillations(ISOs) from different regions. However, specific roles of different ISOs on the development of the CDHE cannot be separated in the observational analysis. By using partial lateral forcing experiments driven by ISO in the Weather Research and Forecasting(WRF) model, we found that the midlatitude ISO generated by a westerly wave train in the upper troposphere played an important role in this heatwave and drought event in the northern MYRB, causing a regional average temperature rise of 1.65°C and intensification of drought over23.49% of the MYRB area. On the other hand, the ISO associated with the Pacific-Japan(PJ)-like teleconnection wave train in the lower troposphere induced a more pronounced impact on the event, causing an average temperature rise of 2.44°C, intensifying drought over 29.62% of the MYRB area. The MYRB was mainly affected by northward warm advection driven by the westward extension of the western North Pacific subtropical high in the early period of the CDHE development. In the late period, because of the establishment of a deep positive geopotential height field through the troposphere leading to intensive local subsidence, there was a remarkable temperature rise and moisture decrease in the MYRB. The results will facilitate a better understanding of the occurrence of CDHE and provide empirical precursory signals for subseasonal forecast of CDHE.展开更多
基金Authors thank the CPRI Project(NPP/2016/HY/1/13042016)for partially supporting the study.Support from NHPC Ltd.and NTPC Ltd.is also thankfully acknowledged.
文摘Assessment of drillability of rocks is vital in the selection,operation,and performance evaluation of cutting tools used in various excavation machinery deployed in mining and tunneling.The commonly used rock drillability prediction methods,namely,drilling rate index(DRI)and Cerchar hardness index(CHI)have limitations in predicting the penetration rate due to differential wear of the cutting tool in rocks with varied hardness and abrasivity.Since cutting tools get blunt differently in different rocks,the stress beneath the tip of the bit decreases until it reaches a threshold value beyond which the penetration rate becomes constant.In this research,a new composite penetration rate index(CPRI)is suggested based on the investigations on four metamorphic rocks viz.quartzite,gneiss,schist and phyllite with varied hardness-abrasivity values.The penetration-time behavior was classified into active,moderate,passive,and dormant phases based on the reduction in penetration rate at different stages of drilling.A comparison of predicted penetration rate values using DRI and CPRI with actual penetration rate values clearly establishes the supremacy of CPRI.Micro-structure and hardness-based index was also developed and correlated with CPRI.The new indices can help predict cutting tool penetration and its consumption more accurately.
基金funded by the Turkish General Directorate of Forestry(project number:19.9402/2020-2023)。
文摘Fire severity classifications determine fire damage and regeneration potential in post-fire areas for effective implementation of restoration applications.Since fire damage varies according to vegetation and fire characteristics,regional assessment of fire severity is crucial.The objectives of this study were:(1)to test the performance of different satellite imagery and spectral indices,and two field—measured severity indices,CBI(Composite Burn Index)and GeoCBI(Geometrically structured Composite Burn Index)to assess fire severity;(2)to calculate classification thresholds for spectral indices that performed best in the study areas;and(3)to generate fire severity maps that could be used to determine the ecological impact of forest fires.Five large fires in Pinus brutia(Turkish pine)and Pinus nigra subsp.pallasiana var.pallasiana(Anatolian black pine)—dominated forests during 2020 and 2021 were selected as study sites.The results show that GeoCBI provided more reliable estimates of field—measured fire severity than CBI.While Sentinel-2 and Landsat-8/OLI images performed similarly well,MODIS performed poorly.Fire severity classification thresholds were determined for Sentinel-2 based RdNBR,dNBR,dSAVI,dNDVI,and dNDMI and Landsat-8/OLI based dNBR,dNDVI,and dSAVI.Among several spectral indices,the highest accuracy for fire severity classification was found for Sentinel-2 based RdNBR(72.1%)and Landsat-8/OLI based dNBR(69.2%).The results can be used to assess and map fire severity in forest ecosystems similar to those in this study.
文摘Remote sensing technology, as the most advanced method for collecting data, along with the common ways often used in the past on research of environmenal science, was integrated to study the relationship between environmental pollution of coal mine and spectral characteristics of nearby plants. With compositive index and mean refiectivity at near infrared, a regression equation was established, and a conclusion was made that spectral reflectivity can be used to distinguish regions with different pollution degree. Through testing with real status of the research region, it is verified that this kind of integration and conclusion not only are helpful for human being in controlling the movement law of pollutants and the corresponding change of coal mine environmental quality, but also bring a new way for the research of environment problems of coal mine.
文摘As a type of non-renewable industrial resource,petroleum is of great strategic significance to the development of each nation.Ever since the 19th century,an array of oil crises have incurred certain downturn of the world economy.Pertinent studies have implied that financial crisis is always prone to be accompanied with oil crisis,yet the relevance of crude oil to the stock market,the barometer of the macro-economy,is ambiguous.In order to avoid the risks induced by the volatility of oil price,the oil futures market has appeared,and at the same time,the financial property of crude oil has become far more evident.Owing to lack of mature mining and refining technology,China still imports large amounts of oil from abroad at present.Thus,the economy of China is susceptible to fluctuation in petroleum price.As for Australia,the only net importer among the member countries of the International Energy Agency(IEA),it fails to attain the target of holding 90 days of fuel reserves set by the agency.However,in 2013,Australian Lincoln Energy announced that a gigantic shale oil field with an estimated value of 21 trillion US dollars was found in the South of Australia,and that if that field is mined,Australia has the possibility to turn into a net exporter of crude oil.It can be expected that the Australia’s economic conditions would be closely related to the international oil to a certain extent.Based on the approaches of the first difference and co-integration,this paper delves into the volatility spillover effect of crude oil futures on the Chinese and Australian stock markets.According to the empirical findings,in the short run,the price of crude oil futures has a greater impact on the Australian composite index than on the Chinese composite index.However,crude oil futures are negatively related to the Chinese composite index in the long run.The price of crude oil futures has no significant impact on the Chinese sector indices,but it has a certain impact on the Australian utilities,energy,materials,and industrial sector indices.In the Chinese stock market,the movement of short-run effect to long-run effect of crude oil futures on sector indices is in the reverse direction.Finally,the price of crude oil futures has a significant volatility spillover effect only on the Australian utilities sector index.
基金We acknowledge the support of National Key Research and Development Program of China(2016YFB0501805)partly supported by Chinese Universities Scientific Fund(2017QC140).
文摘Uncertainty extremely interferes with the execution of farm machinery operation.Treating uncertainties is especially important for machinery cooperatives providing social service since they face more uncertain influence factors(UIFs)than family farms.Under social service circumstance,uncertainties may arise from participants and environments.Classification and evaluation of UIFs were studied in this research.According to the production system,32 UIFs are defined and classified into six categories,which include supply,demand,interactivity,nature,society and others.Uncertainty composite index(UCI)is defined to evaluate the importance of UIFs,which is the square root of the product of occurrence frequency(OF)and impact degree(ID)calculated from the well-designed questionnaire responded by farm machinery operators.UCI is divided into five ranks based on normalization distribution test to illustrate the level of importance.Results from questionnaire showed that natural UIFs have an extreme impact on farm operation,UIFs of the demand and the supply have a serious influence on farm operation,UIFs of interactivity cannot be ignored,and social UIFs have a weak impact on farm operations.This study discovered the uncertainty problems under the specific circumstance of farm machinery service,which may provide a theoretical basis and potential methods for risk management of machinery cooperatives.
基金funding from the Gordon and Betty Moore Foundation(grant number 3519).
文摘To address human dependence on natural resources and anthropogenic impacts on ecosystem health,understanding and management of the linkages between nature and human well-being(HWB)are urgently needed.One fundamental barrier is the lack of quantitative indicators and models that integrate HWB with direct and indirect drivers of change in natural resources.While primary surveys provide the most valid HWB measures,extensive new data collection is often costly,especially for large-scale studies.Therefore,it is vital to develop methods and indices based on existing data(e.g.,census data,survey data)for real-world application.To address this,we propose a new method of using structural equation modeling to construct robust,spatially explicit HWB indices from existing data and demonstrate its validity and usefulness in Cambodia.Our method is scale-free and applicable to different frameworks and data sources and thus supports relatively easy replication in many other contexts.Further application and refinement could improve understanding of human-nature interactions,move toward robust theory development,and guide natural resource management decisions.
基金This work was supported by the Natural Science Foundation of Heilongjiang Province of China[LH2021C011]National Natural Science Foundation of China[31870644]National Key Research and Development Program of China[2017YFD0600106-2].
文摘Introduction:Quantifying fire severity is an important aspect of studying the response mechanism of terrestrial ecosystems to wildfire,and it is of great significance to fire ecology.In this paper we comprehensively introduce and compare the classification and quantification methods for fire severity;we discuss the development and application status of various methods,and we elucidate their existing problems.Results:1)According to features of the burned area,fire severity can be classified as light,moderate,and heavy.2)Using composite burn index(CBI)to quantify and record the fire severity.3)In quantifying fire severity with vegetation change,there are certain limitations and theoretical problems to be solved.4)Remote sensing could very well be an important means of measuring fire severity in the future,but there are still many problems that need to be solved before the remote sensing index can become a global fire severity indicator.Discussion and Conclusion:Only by clarifying the relationship between fire behavior,fire severity,time related variables and the pre-and post-fire ecosystem can the existing models be perfected or new,better fire severity measurement models be proposed for broad applications.
基金partially supported by the National Natural Science Foundation of China under Grant Nos.71422015,71988101the National Center for Mathematics and Interdisciplinary Sciences,Chinese Academy of Sciences。
文摘Business survey,which starts from the microeconomic level,is a widely used short-term forecasting tool in practice.In this study,the authors examine whether foreign trade survey data collected by China’s Ministry of Commerce would provide reliable forecasts of China’s foreign trade.The research procedure is designed from three perspectives including forecast information test,turning point forecast,and out-of-sample value forecast.First,Granger causality test detects whether survey data lead exports and imports.Second,business cycle analysis,a non-model based method,is performed.The authors construct composite indexes with business survey data to forecast turning points of foreign trade.Third,model-based numerical forecasting methods,including the Autoregressive Integrated Moving Average Model with Exogenous Variables(ARIMAX)and the artificial neural networks(ANNs)models are estimated.Empirical results show that survey data granger cause imports and exports,the leading composite index provides signal for changes of trade cycles,and quantitative models including survey data generate more accurate forecasts than benchmark models.It is concluded that trade survey data has excellent predictive capabilities for imports and exports,which can offer some priorities for government policy-making and enterprise decision making.
基金Supported by the National Natural Science Foundation of China(41875111 and 41975073)Special Program for Innovation and Development of China Meteorological Administration(CXFZ2022J031).
文摘In late July 2018, a compound drought and heat event(CDHE) occurred in the middle of the Yangtze River basin(MYRB) and caused great damage to the national economy. The CDHE over the MYRB has been documented to be linked with intraseasonal oscillations(ISOs) from different regions. However, specific roles of different ISOs on the development of the CDHE cannot be separated in the observational analysis. By using partial lateral forcing experiments driven by ISO in the Weather Research and Forecasting(WRF) model, we found that the midlatitude ISO generated by a westerly wave train in the upper troposphere played an important role in this heatwave and drought event in the northern MYRB, causing a regional average temperature rise of 1.65°C and intensification of drought over23.49% of the MYRB area. On the other hand, the ISO associated with the Pacific-Japan(PJ)-like teleconnection wave train in the lower troposphere induced a more pronounced impact on the event, causing an average temperature rise of 2.44°C, intensifying drought over 29.62% of the MYRB area. The MYRB was mainly affected by northward warm advection driven by the westward extension of the western North Pacific subtropical high in the early period of the CDHE development. In the late period, because of the establishment of a deep positive geopotential height field through the troposphere leading to intensive local subsidence, there was a remarkable temperature rise and moisture decrease in the MYRB. The results will facilitate a better understanding of the occurrence of CDHE and provide empirical precursory signals for subseasonal forecast of CDHE.
