Plots under conservation tillage may require higher amount of potassium(K) application for augmenting productivity due to its stratification in upper soil layers, thereby reducing K supplying capacity in a medium or l...Plots under conservation tillage may require higher amount of potassium(K) application for augmenting productivity due to its stratification in upper soil layers, thereby reducing K supplying capacity in a medium or long-term period. To test this hypothesis, a field experiment was performed in 2002-2003 and 2006-2007 to study the effect of K and several crop rotations on yield, water productivity, carbon sequestration, grain quality, soil K status and economic benefits derived in maize(Zea mays L)/cowpea(Vigna sinensis L.) based cropping system under minimum tillage(MT). All crops recorded higher grain yield with a higher dose of K(120 kg K2 O ha-1) than recommended K(40 kg K2 O ha-1). The five years' average yield data showed that higher K application(120 kg K2 O ha-1) produced 16.4%(P<0.05)more maize equivalent yield. Cowpea based rotation yielded 14.2%(P<0.05) higher production than maize based rotation. The maximum enhancement was found in cowpea-mustard rotation. Relationship between yield and sustainable indices revealed that only agronomic efficiency of fertilizer input was significantly correlated with yield. Similarly, higherdoses of K application not only increased the water use efficiency(WUE) of all crops, but also reduced runoff and soil loss by 16.5% and 15.8% under maize and 23.3% and 19.7% under cowpea cover, respectively. This study also revealed that on an average 16.5% of left over carbon input contributed to soil organic carbon(SOC). Here, cowpea based rotation with the higher K application increased carbon sequestration in soil. Potassium fertilization also significantly improved the nutritional value of harvested grain by increasing the protein content for maize(by 9.5%) and cowpea(by 10.6%). The oil content in mustard increased by 5.0% and 6.0% after maize and cowpea, respectively. Net return also increased with the application of the higher K than recommended K and the trend was similar to yield. Hence, the present study demonstrated the potential yield and profit gains along with resource conservation in the Indian Himalayas due to annual additions of higher amount of K than the recommended dose. The impact of high K application was maximum in the cowpea-mustard rotation.展开更多
The body channel based wireless power transfer(BC-WPT)method utilizes the human body as the medium to transfer power for bioelectronics,which can achieve a lower transmission loss due to its higher conductivity.Howeve...The body channel based wireless power transfer(BC-WPT)method utilizes the human body as the medium to transfer power for bioelectronics,which can achieve a lower transmission loss due to its higher conductivity.However,except for the channel length,different on-body loca-tions of the transmitter and receiver also influence the power supply performance.This paper fo-cuses on the wrist-to-forehead path to show the potential of BC-WPT for the brain bioelectronics such as the brain computer interface device.The channel characteristics from 10 MHz to 60 MHz are measured by a vector network analyzer(VNA)and a prototype BC-WPT system with differ-ent copper electrodes and the lowest power loss locates between-22 dB and-33 dB.Furthermore,the minimum path loss limit is simulated in Advanced Design System(ADS)software and the low-est optimum path loss can reach nearly-13 dB.Finally,a rectifier circuit is also built at the receiv-er side to harvest d.c.voltage.The results show that the open-circuit voltage(OCV)can reach 1.75 V with the transmitter of 50Ωoutput impedance supplying 5V_(pp)sine voltage at 60 MHz when adopt-ing 1 cm-diameter circular electrodes.展开更多
With the rapid progress in data-driven approaches,artificial intelligence,and big data analytics technologies,utilizing electroencephalogram(EEG)signals for emotion analysis in the field of the Internet of Medical Thi...With the rapid progress in data-driven approaches,artificial intelligence,and big data analytics technologies,utilizing electroencephalogram(EEG)signals for emotion analysis in the field of the Internet of Medical Things can effectively assist in the diagnosis of specific diseases.While existing emotion analysis methods focus on the utilization of effective deep models for data-driven and big data analytics technology,they often struggle to extract long-range dependencies and accurately model local relationships within multi-channel EEG signals.In addition,the subjective scores of the subjects may not match the predefined emotional labels.To overcome these limitations,this paper proposes a new data-driven dynamic graph-embedded Transformer network(DGETN)that has emerged in different tasks of graph data mining for emotion analysis of EEG signals in the scene of IoMT.Firstly,we extract the frequency features differential entropy(DE)and use the linear dynamic system(LDS)method to alleviate the redundancy and noise information.Secondly,to effectively explore the long-range information and local modeling ability,a novel feature extraction module is designed by embedding the dynamic graph convolution operations in the Transformer encoder for mining the discriminant features of data.Moreover,the graph convolution operations can effectively exploit the spatial information between different channels.At last,we introduce the minimum category confusion(MCC)loss to alleviate the fuzziness of classification.We take two commonly used EEG sentiment analysis datasets as a study.The DGETN has achieved state-of-the-art accuracies of 99.38%on the SEED dataset,and accuracies of 99.24%and 98.85%for valence and arousal prediction on the DEAP dataset,respectively.展开更多
Based on the minimum loss probability criterion,this paper discusses the optimal strategy in multi-asset liquidation.First,we give the framework of the multi-asset liquidation problem and obtain the boundary condition...Based on the minimum loss probability criterion,this paper discusses the optimal strategy in multi-asset liquidation.First,we give the framework of the multi-asset liquidation problem and obtain the boundary conditions of the optimal liquidation strategy under the assumption of linear price impact functions and transform the multi-asset liquidation problem into the portfolio liquidation problem.On this basis,the asymptotic solution and numerical solution of the optimal liquidation strategy are obtained.Then,we simulate the trajectories of the optimal liquidation strategy and analyze the effects of parameters changes.展开更多
基金funded by the Indian Council of Agricultural Research(ICAR),New Delhi
文摘Plots under conservation tillage may require higher amount of potassium(K) application for augmenting productivity due to its stratification in upper soil layers, thereby reducing K supplying capacity in a medium or long-term period. To test this hypothesis, a field experiment was performed in 2002-2003 and 2006-2007 to study the effect of K and several crop rotations on yield, water productivity, carbon sequestration, grain quality, soil K status and economic benefits derived in maize(Zea mays L)/cowpea(Vigna sinensis L.) based cropping system under minimum tillage(MT). All crops recorded higher grain yield with a higher dose of K(120 kg K2 O ha-1) than recommended K(40 kg K2 O ha-1). The five years' average yield data showed that higher K application(120 kg K2 O ha-1) produced 16.4%(P<0.05)more maize equivalent yield. Cowpea based rotation yielded 14.2%(P<0.05) higher production than maize based rotation. The maximum enhancement was found in cowpea-mustard rotation. Relationship between yield and sustainable indices revealed that only agronomic efficiency of fertilizer input was significantly correlated with yield. Similarly, higherdoses of K application not only increased the water use efficiency(WUE) of all crops, but also reduced runoff and soil loss by 16.5% and 15.8% under maize and 23.3% and 19.7% under cowpea cover, respectively. This study also revealed that on an average 16.5% of left over carbon input contributed to soil organic carbon(SOC). Here, cowpea based rotation with the higher K application increased carbon sequestration in soil. Potassium fertilization also significantly improved the nutritional value of harvested grain by increasing the protein content for maize(by 9.5%) and cowpea(by 10.6%). The oil content in mustard increased by 5.0% and 6.0% after maize and cowpea, respectively. Net return also increased with the application of the higher K than recommended K and the trend was similar to yield. Hence, the present study demonstrated the potential yield and profit gains along with resource conservation in the Indian Himalayas due to annual additions of higher amount of K than the recommended dose. The impact of high K application was maximum in the cowpea-mustard rotation.
文摘The body channel based wireless power transfer(BC-WPT)method utilizes the human body as the medium to transfer power for bioelectronics,which can achieve a lower transmission loss due to its higher conductivity.However,except for the channel length,different on-body loca-tions of the transmitter and receiver also influence the power supply performance.This paper fo-cuses on the wrist-to-forehead path to show the potential of BC-WPT for the brain bioelectronics such as the brain computer interface device.The channel characteristics from 10 MHz to 60 MHz are measured by a vector network analyzer(VNA)and a prototype BC-WPT system with differ-ent copper electrodes and the lowest power loss locates between-22 dB and-33 dB.Furthermore,the minimum path loss limit is simulated in Advanced Design System(ADS)software and the low-est optimum path loss can reach nearly-13 dB.Finally,a rectifier circuit is also built at the receiv-er side to harvest d.c.voltage.The results show that the open-circuit voltage(OCV)can reach 1.75 V with the transmitter of 50Ωoutput impedance supplying 5V_(pp)sine voltage at 60 MHz when adopt-ing 1 cm-diameter circular electrodes.
文摘With the rapid progress in data-driven approaches,artificial intelligence,and big data analytics technologies,utilizing electroencephalogram(EEG)signals for emotion analysis in the field of the Internet of Medical Things can effectively assist in the diagnosis of specific diseases.While existing emotion analysis methods focus on the utilization of effective deep models for data-driven and big data analytics technology,they often struggle to extract long-range dependencies and accurately model local relationships within multi-channel EEG signals.In addition,the subjective scores of the subjects may not match the predefined emotional labels.To overcome these limitations,this paper proposes a new data-driven dynamic graph-embedded Transformer network(DGETN)that has emerged in different tasks of graph data mining for emotion analysis of EEG signals in the scene of IoMT.Firstly,we extract the frequency features differential entropy(DE)and use the linear dynamic system(LDS)method to alleviate the redundancy and noise information.Secondly,to effectively explore the long-range information and local modeling ability,a novel feature extraction module is designed by embedding the dynamic graph convolution operations in the Transformer encoder for mining the discriminant features of data.Moreover,the graph convolution operations can effectively exploit the spatial information between different channels.At last,we introduce the minimum category confusion(MCC)loss to alleviate the fuzziness of classification.We take two commonly used EEG sentiment analysis datasets as a study.The DGETN has achieved state-of-the-art accuracies of 99.38%on the SEED dataset,and accuracies of 99.24%and 98.85%for valence and arousal prediction on the DEAP dataset,respectively.
基金the National Natural Science Foundation of China(Grant No.71671017).
文摘Based on the minimum loss probability criterion,this paper discusses the optimal strategy in multi-asset liquidation.First,we give the framework of the multi-asset liquidation problem and obtain the boundary conditions of the optimal liquidation strategy under the assumption of linear price impact functions and transform the multi-asset liquidation problem into the portfolio liquidation problem.On this basis,the asymptotic solution and numerical solution of the optimal liquidation strategy are obtained.Then,we simulate the trajectories of the optimal liquidation strategy and analyze the effects of parameters changes.
