The present study is the result of an investigation of the organization of milk producers in the region of Fartura, SP, relations between the various actors in this chain of milk, the benefits obtained from this relat...The present study is the result of an investigation of the organization of milk producers in the region of Fartura, SP, relations between the various actors in this chain of milk, the benefits obtained from this relationship and classification of these properties in the dairy chain, allowing to measure productivity through the proposed indicators. Research has shown that dairy farmers in the region of Fartura had several benefits to organizing themselves as a Local Productive Arrangement or Social Networks, especially in relation to a better pay the price of a gallon of milk. To achieve these results, farmers had to invest to improve technological standards and production processes and thereby increase milk quality and productivity.展开更多
The fraction of photosynthetically active radiation （FPAR） is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles. Based on ground-measured corn hyperspectral reflectance and...The fraction of photosynthetically active radiation （FPAR） is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles. Based on ground-measured corn hyperspectral reflectance and FPAR data over Northeast China, the correlations between corn-canopy FPAR and hyperspectral reflectance were analyzed, and the FPAR estimation performances using vegetation index （VI） and neural network （NN） methods with different two-band-combination hyperspectral reflectance were investigated. The results indicated that the corn-canopy FPAR retained almost a constant value in an entire day. The negative correlations between FPAR and visible and shortwave infrared reflectance （SWIR） bands are stronger than the positive correlations between FPAR and near-infrared band re- flectance （NIR）. For the six VIs, the normalized difference vegetation index （NDVI） and simple ratio （SR） performed best for estimating corn FPAR （the maximum R2 of 0.8849 and 0.8852, respectively）. However, the NN method esti- mated results （the maximum Rz is 0.9417） were obviously better than all of the VIs. For NN method, the two-band combinations showing the best corn FPAR estimation performances were from the NIR and visible bands; for VIs, however, they were from the SWIR and NIR bands. As for both the methods, the SWIR band performed exceptionally well for corn FPAR estimation. This may be attributable to the fact that the reflectance of the SWIR band were strongly controlled by leaf water content, which is a key component of corn photosynthesis and greatly affects the absorption of photosynthetically active radiation （APAR）, and makes further impact on corn-canopy FPAR.展开更多
It is a great challenge to match and predict the production performance of coalbed methane (CBM) wells in the initial production stage due to heterogeneity of coalbed, uniqueness of CBM production process, complexity ...It is a great challenge to match and predict the production performance of coalbed methane (CBM) wells in the initial production stage due to heterogeneity of coalbed, uniqueness of CBM production process, complexity of porosity-permeability variation and difficulty in obtaining some key parameters which are critical for the conventional prediction methods (type curve, material balance and numerical simulation). BP neural network, a new intelligent technique, is an effective method to deal with nonlinear, instable and complex system problems and predict the short-term change quantitatively. In this paper a BP neural model for the CBM productivity of high-rank CBM wells in Qinshui Basin was established and used to match the past gas production and predict the futural production performance. The results from two case studies showed that this model has high accuracy and good reliability in matching and predicting gas production with different types and different temporal resolutions, and the accuracy increases as the number of outliers in gas production data decreases. Therefore, the BP network can provide a reliable tool to predict the production performance of CBM wells without clear knowledge of coalbed reservoir and sufficient production data in the early development stage.展开更多
Drawing on cognitive linguistic theories, this study investigates the various meanings of the Chinese verb 吃（chi） and the types of objects that it takes. It is concluded that the many meanings of吃 are organized in...Drawing on cognitive linguistic theories, this study investigates the various meanings of the Chinese verb 吃（chi） and the types of objects that it takes. It is concluded that the many meanings of吃 are organized in a radial network, with the primary meaning at the center and extended meanings at the periphery and that extended meanings are derived from, and thus can be traced back to, the primary meaning. This study also suggests that the productivity of the 吃 ＋ object construction is affected by the meaning of 吃, the interpretation of its objects, as well as social and linguistic convention.展开更多
文摘The present study is the result of an investigation of the organization of milk producers in the region of Fartura, SP, relations between the various actors in this chain of milk, the benefits obtained from this relationship and classification of these properties in the dairy chain, allowing to measure productivity through the proposed indicators. Research has shown that dairy farmers in the region of Fartura had several benefits to organizing themselves as a Local Productive Arrangement or Social Networks, especially in relation to a better pay the price of a gallon of milk. To achieve these results, farmers had to invest to improve technological standards and production processes and thereby increase milk quality and productivity.
基金Under the auspices of National Key Research Program of Global Change Research (No.2010CB951302)National Natural Science Fundation of China (No.40771146)China Postdoctoral Science Foundation Funded Project (No.07Z7601MZ1)
文摘The fraction of photosynthetically active radiation （FPAR） is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles. Based on ground-measured corn hyperspectral reflectance and FPAR data over Northeast China, the correlations between corn-canopy FPAR and hyperspectral reflectance were analyzed, and the FPAR estimation performances using vegetation index （VI） and neural network （NN） methods with different two-band-combination hyperspectral reflectance were investigated. The results indicated that the corn-canopy FPAR retained almost a constant value in an entire day. The negative correlations between FPAR and visible and shortwave infrared reflectance （SWIR） bands are stronger than the positive correlations between FPAR and near-infrared band re- flectance （NIR）. For the six VIs, the normalized difference vegetation index （NDVI） and simple ratio （SR） performed best for estimating corn FPAR （the maximum R2 of 0.8849 and 0.8852, respectively）. However, the NN method esti- mated results （the maximum Rz is 0.9417） were obviously better than all of the VIs. For NN method, the two-band combinations showing the best corn FPAR estimation performances were from the NIR and visible bands; for VIs, however, they were from the SWIR and NIR bands. As for both the methods, the SWIR band performed exceptionally well for corn FPAR estimation. This may be attributable to the fact that the reflectance of the SWIR band were strongly controlled by leaf water content, which is a key component of corn photosynthesis and greatly affects the absorption of photosynthetically active radiation （APAR）, and makes further impact on corn-canopy FPAR.
基金supported by the National Basic Research Program of Chi-na ("973" Project ) (Grant No. 2009CB219600)the Major National Sci-ence and Technology Special Projects (Grant Nos. 2008ZX05034-001, 2009ZX05038-002)
文摘It is a great challenge to match and predict the production performance of coalbed methane (CBM) wells in the initial production stage due to heterogeneity of coalbed, uniqueness of CBM production process, complexity of porosity-permeability variation and difficulty in obtaining some key parameters which are critical for the conventional prediction methods (type curve, material balance and numerical simulation). BP neural network, a new intelligent technique, is an effective method to deal with nonlinear, instable and complex system problems and predict the short-term change quantitatively. In this paper a BP neural model for the CBM productivity of high-rank CBM wells in Qinshui Basin was established and used to match the past gas production and predict the futural production performance. The results from two case studies showed that this model has high accuracy and good reliability in matching and predicting gas production with different types and different temporal resolutions, and the accuracy increases as the number of outliers in gas production data decreases. Therefore, the BP network can provide a reliable tool to predict the production performance of CBM wells without clear knowledge of coalbed reservoir and sufficient production data in the early development stage.
文摘Drawing on cognitive linguistic theories, this study investigates the various meanings of the Chinese verb 吃（chi） and the types of objects that it takes. It is concluded that the many meanings of吃 are organized in a radial network, with the primary meaning at the center and extended meanings at the periphery and that extended meanings are derived from, and thus can be traced back to, the primary meaning. This study also suggests that the productivity of the 吃 ＋ object construction is affected by the meaning of 吃, the interpretation of its objects, as well as social and linguistic convention.
