The accuracy of laser-induced breakdown spectroscopy(LIBS) quantitative method is greatly dependent on the amount of certified standard samples used for training. However, in practical applications, only limited stand...The accuracy of laser-induced breakdown spectroscopy(LIBS) quantitative method is greatly dependent on the amount of certified standard samples used for training. However, in practical applications, only limited standard samples with labeled certified concentrations are available. A novel semi-supervised LIBS quantitative analysis method is proposed, based on co-training regression model with selection of effective unlabeled samples. The main idea of the proposed method is to obtain better regression performance by adding effective unlabeled samples in semisupervised learning. First, effective unlabeled samples are selected according to the testing samples by Euclidean metric. Two original regression models based on least squares support vector machine with different parameters are trained by the labeled samples separately, and then the effective unlabeled samples predicted by the two models are used to enlarge the training dataset based on labeling confidence estimation. The final predictions of the proposed method on the testing samples will be determined by weighted combinations of the predictions of two updated regression models. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples were carried out, in which 5 samples with labeled concentrations and 11 unlabeled samples were used to train the regression models and the remaining 7 samples were used for testing. With the numbers of effective unlabeled samples increasing, the root mean square error of the proposed method went down from 1.80% to 0.84% and the relative prediction error was reduced from 9.15% to 4.04%.展开更多
Biochar added to soil can improve crop growth through both direct and indirect effects, particularly in acidic, highly weathered soils in subtropical and tropical regions. However, the mechanisms of biochar improving ...Biochar added to soil can improve crop growth through both direct and indirect effects, particularly in acidic, highly weathered soils in subtropical and tropical regions. However, the mechanisms of biochar improving crop growth are not well understood. The objectives of this study were i) to determine the crop responses to biochar addition and ii) to understand the effect of biochar addition on N use efficiency. Seven acidic red soils varying in texture, p H, and soil nutrient were taken from southern China and subjected to four treatments: zero biochar and fertilizer as a control(CK), 10 g kg-1biochar(BC), NPK fertilizers(NPK), and 10 g kg-1biochar plus NPK fertilizers(BC+NPK).15N-labeled fertilizer was used as a tracer to assess N use efficiency. After a 46-d pot experiment,biochar addition increased soil p H and available P, and decreased soil exchangable Al3+, but did not impact soil availabe N and cation exchange capacity(P > 0.05). The N use efficiency and N retained in the soil were not significantly affected by biochar application except for the soil with the lowest available P(3.81 mg kg-1) and highest exchanageable Al3+(4.54 cmol kg-1). Greater maize biomass was observed in all soils amended with biochar compared to soils without biochar(BC vs. CK, BC+NPK vs. NPK). This agronomic effect was negatively related to the concentration of soil exchangeable Al3+(P < 0.1). The results of this study implied that the liming effect of biochar improved plant growth through alleviating Al toxicity and P deficiency, especially in poor acidic red soils.展开更多
Energy expenditure is a key variable in the study of ageing, and the fruit fly Drosophila melanogaster is a model organism that has been used to make step changes in our understanding of the ageing process. Standard m...Energy expenditure is a key variable in the study of ageing, and the fruit fly Drosophila melanogaster is a model organism that has been used to make step changes in our understanding of the ageing process. Standard methods for measurement of energy expenditure involve placing individuals in metabolic chambers where their oxygen consumption and CO2 production can be quantified. These measurements require separating individuals from any social context, and may only poorly reflect the environment in which the animals normally live. The doubly-labeled water （DLW） method is an isotope-based technique for measuring energy expenditure which overcomes these problems. However, technical challenges mean that the smallest animals this method has been previously applied to weighed 50-200 mg. We overcame these technical challenges to measure energy demands in Drosophila weighing 0.78 mg. Mass-specific energy expenditure varied between 43 and 65 mW·g^-1. These estimates are considerably higher than estimates using indirect calorimetry of Drosophila in small metabolic chambers （around 18 mW·g^-1）. The methodology we have established extends downwards by three orders of magnitude the size of animals that can be measured using DLW. This approach may be of considerable value in future ageing research attempting to understand the genetic and genomic basis of ageing.展开更多
基金supported by National Natural Science Foundation of China (No. 51674032)
文摘The accuracy of laser-induced breakdown spectroscopy(LIBS) quantitative method is greatly dependent on the amount of certified standard samples used for training. However, in practical applications, only limited standard samples with labeled certified concentrations are available. A novel semi-supervised LIBS quantitative analysis method is proposed, based on co-training regression model with selection of effective unlabeled samples. The main idea of the proposed method is to obtain better regression performance by adding effective unlabeled samples in semisupervised learning. First, effective unlabeled samples are selected according to the testing samples by Euclidean metric. Two original regression models based on least squares support vector machine with different parameters are trained by the labeled samples separately, and then the effective unlabeled samples predicted by the two models are used to enlarge the training dataset based on labeling confidence estimation. The final predictions of the proposed method on the testing samples will be determined by weighted combinations of the predictions of two updated regression models. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples were carried out, in which 5 samples with labeled concentrations and 11 unlabeled samples were used to train the regression models and the remaining 7 samples were used for testing. With the numbers of effective unlabeled samples increasing, the root mean square error of the proposed method went down from 1.80% to 0.84% and the relative prediction error was reduced from 9.15% to 4.04%.
基金Supported by the National Key Technology R&D Program of China(No.2011BAD31B04)the National Natural Science Foundation of China(Nos.41371235 and 41171191)
文摘Biochar added to soil can improve crop growth through both direct and indirect effects, particularly in acidic, highly weathered soils in subtropical and tropical regions. However, the mechanisms of biochar improving crop growth are not well understood. The objectives of this study were i) to determine the crop responses to biochar addition and ii) to understand the effect of biochar addition on N use efficiency. Seven acidic red soils varying in texture, p H, and soil nutrient were taken from southern China and subjected to four treatments: zero biochar and fertilizer as a control(CK), 10 g kg-1biochar(BC), NPK fertilizers(NPK), and 10 g kg-1biochar plus NPK fertilizers(BC+NPK).15N-labeled fertilizer was used as a tracer to assess N use efficiency. After a 46-d pot experiment,biochar addition increased soil p H and available P, and decreased soil exchangable Al3+, but did not impact soil availabe N and cation exchange capacity(P > 0.05). The N use efficiency and N retained in the soil were not significantly affected by biochar application except for the soil with the lowest available P(3.81 mg kg-1) and highest exchanageable Al3+(4.54 cmol kg-1). Greater maize biomass was observed in all soils amended with biochar compared to soils without biochar(BC vs. CK, BC+NPK vs. NPK). This agronomic effect was negatively related to the concentration of soil exchangeable Al3+(P < 0.1). The results of this study implied that the liming effect of biochar improved plant growth through alleviating Al toxicity and P deficiency, especially in poor acidic red soils.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 13030000) a 1000 talents professorship
文摘Energy expenditure is a key variable in the study of ageing, and the fruit fly Drosophila melanogaster is a model organism that has been used to make step changes in our understanding of the ageing process. Standard methods for measurement of energy expenditure involve placing individuals in metabolic chambers where their oxygen consumption and CO2 production can be quantified. These measurements require separating individuals from any social context, and may only poorly reflect the environment in which the animals normally live. The doubly-labeled water （DLW） method is an isotope-based technique for measuring energy expenditure which overcomes these problems. However, technical challenges mean that the smallest animals this method has been previously applied to weighed 50-200 mg. We overcame these technical challenges to measure energy demands in Drosophila weighing 0.78 mg. Mass-specific energy expenditure varied between 43 and 65 mW·g^-1. These estimates are considerably higher than estimates using indirect calorimetry of Drosophila in small metabolic chambers （around 18 mW·g^-1）. The methodology we have established extends downwards by three orders of magnitude the size of animals that can be measured using DLW. This approach may be of considerable value in future ageing research attempting to understand the genetic and genomic basis of ageing.
