The age hardening behavior of gravity cast B356 aluminum alloy was investigated by differential scanning calorimetry(DSC), hardness measurements and tensile tests. Three different artificial aging temperatures were se...The age hardening behavior of gravity cast B356 aluminum alloy was investigated by differential scanning calorimetry(DSC), hardness measurements and tensile tests. Three different artificial aging temperatures were selected, namely 155, 165 and 180 °C, with heat treatment time from 40 min to 32 h. DSC analysis results show that cluster formation begins below room temperature(at around-10 °C). Since cluster formation influences the subsequent precipitation of the main strengthening β'' phase, it can be inferred that a delay between solutionizing and artificial aging has a detrimental effect on the mechanical properties of the alloy. It was also confirmed that the hardness and the tensile properties of the alloy reach the maximum values when β'' phase is completely developed during the artificial aging. This happens after 16 h for samples aged at 155 °C, after 6 h for samples aged at 165 °C and after 4 h for samples aged at 180 °C. A subsequent decrease of the mechanical properties, observed only in the sample aged at the highest temperature, with increasing aging time can be associated with the transformation of the coherent β'' phase into the semi-coherent β' phase. Finally, the activation energy associated with the precipitation of β'' phase was calculated to be 57.2 k J/mol.展开更多
Bothriocephalus acheilognathi is a potentially serious pathogen in wild or cultured fish in worldwide distribution. We examined 58-farmed grass carp from Nanchang in the Changjiang (Yangtze) River drainage, from which...Bothriocephalus acheilognathi is a potentially serious pathogen in wild or cultured fish in worldwide distribution. We examined 58-farmed grass carp from Nanchang in the Changjiang (Yangtze) River drainage, from which 20.7% were found to harbor the parasite with an infection intensity of 36.9 ± 54.7. The parasites were identified based on morphology and rDNA ITS sequence analysis. The present report represents the first record of the parasite in grass carp Ctenopharyngodon idella in the river drainage.展开更多
Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural hazard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting d...Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural hazard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting debris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and useful in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time series of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collected in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.展开更多
The SWI/SNF chromatin-remodeling complexes utilize energy from ATP hydrolysis to reposition nucleosomes and regulate the expression of human genes. Here, we studied the roles of human Brahma （hBrm） and Brahma-relate...The SWI/SNF chromatin-remodeling complexes utilize energy from ATP hydrolysis to reposition nucleosomes and regulate the expression of human genes. Here, we studied the roles of human Brahma （hBrm） and Brahma-related gene 1 （Brgl）, the ATPase subunits of the SWI/SNF complexes, in regulating human genes. Our results indicate that both hBrm and Brgl interact with Signal transducer and activator of transcription （Stat） 1 in vitro. However, Statl in its native form only recruits hBrm to IFNy-activated sequences （GAS） of individual genes; by contrast, in a stress- induced phosphorylated form, Statl mainly binds to Brgl. Under basal conditions, hBrm is recruited by native Statl to the GAS and exists in a mSin3/HDAC co-repressor complex on the hsp90a gene, which shows a compact chromatin structure. Upon heat-shock, hBrm is acetylated by p300 and dissociates from the co-repressor complex, which the phosphorylated St^tl is increased, and binds and recruits Brgl to the GAS, leading to elevated induction of the gene. This hBrm/Brgl switch also occurs at the GAS of all of the three examined immune genes in heat-shocked cells; how- ever, this switch only occurs in specific cell types upon exposure to IFNy. Regardless of the stimulus, the hBrm/Brgl switch at the GAS elicits an increase in gene activity. Our data are consistent with the hypothesis that the hBrm/Brgl switch is an indicator of the responsiveness of a gene to heat-shock or IFNy stimulation and may represent an ＂on-off switch＂ of gene expression in vivo.展开更多
The need for accurate rainfall prediction is readily apparent when considering many benefits in which such information would provide for river control, reservoir operation, forestry interests, flood mitigation, etc.. ...The need for accurate rainfall prediction is readily apparent when considering many benefits in which such information would provide for river control, reservoir operation, forestry interests, flood mitigation, etc.. Due to importance of rainfall in many aspects, studies on rainfall forecast have been conducted since a few decades ago. Although many methods have been introduced, all the researches describe the study as complex because it involves numerous variables and still need to be improved. Nowadays, there are various traditional techniques and mathematical models available, yet, there are no result on which method provide the most reliable estimation. AR （auto-regressive）, ARMA （auto-regressive moving average）, ARIMA （auto-regressive integrated moving average） and ANNs （artificial neural networks） were introduced as a useful and efficient tool for modeling and forecasting. The conventional time series provide reasonable accuracy but suffer from the assumptions of stationary and linearity. The concept of neurons was introduced first which then developed to ANNs with back propagation training algorithm. Although certain ANNs） models are equivalent to time series model, but it is limited to short term forecasting. This Paper presents a mathematical approach for rainfall forecasting for Iran on monthly basic. The model is trained for monthly rainfall forecasting and tested to evaluate the performance of the model. The result Shows reasonably good accuracy for monthly rainfall forecasting.展开更多
Time series are an important object of study in sciences, engineering and business, especially in cases where it is expected to know, predict and optimize behaviors. In this context, we intend to show the feasibility ...Time series are an important object of study in sciences, engineering and business, especially in cases where it is expected to know, predict and optimize behaviors. In this context, we intend to show the feasibility of using artificial neural networks in the study of several time series in an engineering course, especially those that have no overt behavior or are not able to be modeled mathematically in a simple way and have direct application in the education of future engineers.展开更多
基金funded by Regione Lombardia-MIUR (Research Program "2 MILLIMETRI" ID 30152773)
文摘The age hardening behavior of gravity cast B356 aluminum alloy was investigated by differential scanning calorimetry(DSC), hardness measurements and tensile tests. Three different artificial aging temperatures were selected, namely 155, 165 and 180 °C, with heat treatment time from 40 min to 32 h. DSC analysis results show that cluster formation begins below room temperature(at around-10 °C). Since cluster formation influences the subsequent precipitation of the main strengthening β'' phase, it can be inferred that a delay between solutionizing and artificial aging has a detrimental effect on the mechanical properties of the alloy. It was also confirmed that the hardness and the tensile properties of the alloy reach the maximum values when β'' phase is completely developed during the artificial aging. This happens after 16 h for samples aged at 155 °C, after 6 h for samples aged at 165 °C and after 4 h for samples aged at 180 °C. A subsequent decrease of the mechanical properties, observed only in the sample aged at the highest temperature, with increasing aging time can be associated with the transformation of the coherent β'' phase into the semi-coherent β' phase. Finally, the activation energy associated with the precipitation of β'' phase was calculated to be 57.2 k J/mol.
基金Supported by the Earmarked Fund for China Agriculture Research System (No. CARS-46)
文摘Bothriocephalus acheilognathi is a potentially serious pathogen in wild or cultured fish in worldwide distribution. We examined 58-farmed grass carp from Nanchang in the Changjiang (Yangtze) River drainage, from which 20.7% were found to harbor the parasite with an infection intensity of 36.9 ± 54.7. The parasites were identified based on morphology and rDNA ITS sequence analysis. The present report represents the first record of the parasite in grass carp Ctenopharyngodon idella in the river drainage.
文摘Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural hazard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting debris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and useful in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time series of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collected in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.
基金Acknowledgments We thank Drs XY Fu, CM Horvath, AN Imbalzano, HB Zhang, S Cadelwood and K Shuai for kindly providing plasmids, antibodies and chemicals used in this work. We thank Dr Robert A Casero, Jr of the Johns Hopkins University School of Medicine for his critical reading of the manuscript, and Dr Weimin Zhong of the Yale University for his contribution to the work. This work was supported by the National Natural Science Foundation of China （90408007, 30871382 and 30721063）, the National Basic Research Program of China （973 Program） （2005CB522405）, the National Key Scientific Program （2011CB964902） and Special Funds of State Key Laboratories （2060204）.
文摘The SWI/SNF chromatin-remodeling complexes utilize energy from ATP hydrolysis to reposition nucleosomes and regulate the expression of human genes. Here, we studied the roles of human Brahma （hBrm） and Brahma-related gene 1 （Brgl）, the ATPase subunits of the SWI/SNF complexes, in regulating human genes. Our results indicate that both hBrm and Brgl interact with Signal transducer and activator of transcription （Stat） 1 in vitro. However, Statl in its native form only recruits hBrm to IFNy-activated sequences （GAS） of individual genes; by contrast, in a stress- induced phosphorylated form, Statl mainly binds to Brgl. Under basal conditions, hBrm is recruited by native Statl to the GAS and exists in a mSin3/HDAC co-repressor complex on the hsp90a gene, which shows a compact chromatin structure. Upon heat-shock, hBrm is acetylated by p300 and dissociates from the co-repressor complex, which the phosphorylated St^tl is increased, and binds and recruits Brgl to the GAS, leading to elevated induction of the gene. This hBrm/Brgl switch also occurs at the GAS of all of the three examined immune genes in heat-shocked cells; how- ever, this switch only occurs in specific cell types upon exposure to IFNy. Regardless of the stimulus, the hBrm/Brgl switch at the GAS elicits an increase in gene activity. Our data are consistent with the hypothesis that the hBrm/Brgl switch is an indicator of the responsiveness of a gene to heat-shock or IFNy stimulation and may represent an ＂on-off switch＂ of gene expression in vivo.
文摘The need for accurate rainfall prediction is readily apparent when considering many benefits in which such information would provide for river control, reservoir operation, forestry interests, flood mitigation, etc.. Due to importance of rainfall in many aspects, studies on rainfall forecast have been conducted since a few decades ago. Although many methods have been introduced, all the researches describe the study as complex because it involves numerous variables and still need to be improved. Nowadays, there are various traditional techniques and mathematical models available, yet, there are no result on which method provide the most reliable estimation. AR （auto-regressive）, ARMA （auto-regressive moving average）, ARIMA （auto-regressive integrated moving average） and ANNs （artificial neural networks） were introduced as a useful and efficient tool for modeling and forecasting. The conventional time series provide reasonable accuracy but suffer from the assumptions of stationary and linearity. The concept of neurons was introduced first which then developed to ANNs with back propagation training algorithm. Although certain ANNs） models are equivalent to time series model, but it is limited to short term forecasting. This Paper presents a mathematical approach for rainfall forecasting for Iran on monthly basic. The model is trained for monthly rainfall forecasting and tested to evaluate the performance of the model. The result Shows reasonably good accuracy for monthly rainfall forecasting.
文摘Time series are an important object of study in sciences, engineering and business, especially in cases where it is expected to know, predict and optimize behaviors. In this context, we intend to show the feasibility of using artificial neural networks in the study of several time series in an engineering course, especially those that have no overt behavior or are not able to be modeled mathematically in a simple way and have direct application in the education of future engineers.
