Sensor scheduling is essential to collaborative target tracking in wireless sensor networks （WSNs）. In the existing works for target tracking in WSNs, such as the information-driven sensor query （IDSQ）, the taskin...Sensor scheduling is essential to collaborative target tracking in wireless sensor networks （WSNs）. In the existing works for target tracking in WSNs, such as the information-driven sensor query （IDSQ）, the tasking sensors are scheduled to maximize the information gain while minimizing the resource cost based on the uniform sampling intervals, ignoring the changing of the target dynamics and the specific desirable tracking goals. This paper proposes a novel energy-efficient adaptive sensor scheduling approach that jointly selects tasking sensors and determines their associated sampling intervals according to the predicted tracking accuracy and tracking energy cost. At each time step, the sensors are scheduled in alternative tracking mode, namely, the fast tracking mode with smallest sampling interval or the tracking maintenance mode with larger sampling interval, according to a specified tracking error threshold. The approach employs an extended Kalman filter （EKF）-based estimation technique to predict the tracking accuracy and adopts an energy consumption model to predict the energy cost. Simulation results demonstrate that, compared to a non-adaptive sensor scheduling approach, the proposed approach can save energy cost significantly without degrading the tracking accuracy.展开更多
Rice production accounts for approximately half of the freshwater resources utilized in agriculture,result-ing in greenhouse gas emissions such as methane(CH4)from flooded paddy fields.To address this chal-lenge,envir...Rice production accounts for approximately half of the freshwater resources utilized in agriculture,result-ing in greenhouse gas emissions such as methane(CH4)from flooded paddy fields.To address this chal-lenge,environmentally friendly and cost-effective water-saving techniques have become widely adopted in rice cultivation.However,the implementation of water-saving treatments(WsTs)in paddy-field rice has been associated with a substantial yield loss of up to 50%as well as a reduction in nitrogen use efficiency(NUE).In this study,we discovered that the target of rapamycin(TOR)signaling pathway is compromised in rice under WsT.Polysome profiling-coupled transcriptome sequencing(polysome-seq)analysis unveiled a substantial reduction in global translation in response to WST associated with the downregulation of TOR activity.Molecular,biochemical,and genetic analyses revealed new insights into the impact of the positive TOR-S6K-RPS6 and negative TOR-MAF1 modules on translation repression under WST.Intriguingly,ammonium exhibited a greater ability to alleviate growth constraints under WsT by enhancing TOR signaling,which simultaneously promoted uptake and utilization of ammonium and nitrogen allocation.We further demonstrated that TOR modulates the ammonium transporter AMT1;1 as well as the amino acid permease APP1 and dipeptide transporter NPF7.3 at the translational level through the 5'untranslated region.Collectively,these findings reveal that enhancing TOR signaling could mitigate rice yield penalty due to WST by regulating the processes involved in protein synthesis and NUE.Our study will contribute to the breeding of new rice varieties with increased water and fertilizer utilization efficiency.展开更多
基金partly supported by the Agency for Science,Technology and Research(A*Star)SERC(No.0521010037,0521210082)
文摘Sensor scheduling is essential to collaborative target tracking in wireless sensor networks （WSNs）. In the existing works for target tracking in WSNs, such as the information-driven sensor query （IDSQ）, the tasking sensors are scheduled to maximize the information gain while minimizing the resource cost based on the uniform sampling intervals, ignoring the changing of the target dynamics and the specific desirable tracking goals. This paper proposes a novel energy-efficient adaptive sensor scheduling approach that jointly selects tasking sensors and determines their associated sampling intervals according to the predicted tracking accuracy and tracking energy cost. At each time step, the sensors are scheduled in alternative tracking mode, namely, the fast tracking mode with smallest sampling interval or the tracking maintenance mode with larger sampling interval, according to a specified tracking error threshold. The approach employs an extended Kalman filter （EKF）-based estimation technique to predict the tracking accuracy and adopts an energy consumption model to predict the energy cost. Simulation results demonstrate that, compared to a non-adaptive sensor scheduling approach, the proposed approach can save energy cost significantly without degrading the tracking accuracy.
基金Thise research was supported by the Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City City(320LH031 and HSPHDSRF-2023-04-016)Zhejiang Provincial Natural Science Foundation of China(LY21C020003)+3 种基金Zhejiang University Global Partnership Fund,Fundamental Research Funds for the Central Universities for the Central Universities(K20200168)the Key Research and Development Program of Zhejiang(2020C02002)National Natural Science Foundation of China(32201819)China Postdoctoral Science Foundation(2022M712807).
文摘Rice production accounts for approximately half of the freshwater resources utilized in agriculture,result-ing in greenhouse gas emissions such as methane(CH4)from flooded paddy fields.To address this chal-lenge,environmentally friendly and cost-effective water-saving techniques have become widely adopted in rice cultivation.However,the implementation of water-saving treatments(WsTs)in paddy-field rice has been associated with a substantial yield loss of up to 50%as well as a reduction in nitrogen use efficiency(NUE).In this study,we discovered that the target of rapamycin(TOR)signaling pathway is compromised in rice under WsT.Polysome profiling-coupled transcriptome sequencing(polysome-seq)analysis unveiled a substantial reduction in global translation in response to WST associated with the downregulation of TOR activity.Molecular,biochemical,and genetic analyses revealed new insights into the impact of the positive TOR-S6K-RPS6 and negative TOR-MAF1 modules on translation repression under WST.Intriguingly,ammonium exhibited a greater ability to alleviate growth constraints under WsT by enhancing TOR signaling,which simultaneously promoted uptake and utilization of ammonium and nitrogen allocation.We further demonstrated that TOR modulates the ammonium transporter AMT1;1 as well as the amino acid permease APP1 and dipeptide transporter NPF7.3 at the translational level through the 5'untranslated region.Collectively,these findings reveal that enhancing TOR signaling could mitigate rice yield penalty due to WST by regulating the processes involved in protein synthesis and NUE.Our study will contribute to the breeding of new rice varieties with increased water and fertilizer utilization efficiency.
