Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and sof...Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and soft sensor systems exhibit multi-dynamic characteristics. Thus, the first contribution is improving the model in the previous study with multi-time-constant. The characteristics-separation-based model will be identified in substep way,and the stochastic Newton recursive(SNR) algorithm is adopted. Considering the dual-rate characteristics of soft sensor systems, the proposed model cannot be identified directly. Thus, two auxiliary models are first proposed to offer the intersample estimations at each update period, based on which the improved algorithm(DAM-SNR) is derived. These two auxiliary models function in switching mechanism which has been illustrated in detail. This algorithm serves for the identification of the proposed model together with the SNR algorithm, and the identification procedure is then presented. Finally, the laboratorial case confirms the effectiveness of the proposed soft sensor model and the algorithms.展开更多
Dendroctonus spp. is one of the most portable pests in imported and ex- ported timber and wooden packages, and it is an important object of the port quarantine. Making rapid and accurate identification of Dendroctonus...Dendroctonus spp. is one of the most portable pests in imported and ex- ported timber and wooden packages, and it is an important object of the port quarantine. Making rapid and accurate identification of Dendroctonus spp. is an im- portant method to reduce the invasion risk of Dendroctonus spp. for China. In this paper, Dendroctonus punctatus, which belongs to the Dendroctonus spp., is intro- duced in detail from the aspects of taxonomic status, biological characteristics, mor- phological characteristics and the invasion risk, providing reference for the identifica- tion of Dendroctonus punctatus in inspection and quarantine.展开更多
In intricate aquatic environments, enhancing the sensory performance of underwater actuators to ensure successful task execution is a significant challenge. To address this, a biomimetic tactile multimodal sensing app...In intricate aquatic environments, enhancing the sensory performance of underwater actuators to ensure successful task execution is a significant challenge. To address this, a biomimetic tactile multimodal sensing approach is introduced in this study, based on TriboElectric NanoGenerator (TENG) and Micro-ThermoElectric Generator (MTEG). This method enables actuators to identify the material properties of underwater target objects and to sense grasping states, such as pressure and relative sliding. In this study, a multi-dimensional underwater bionic tactile perception theoretical model is established, and a bionic sensing prototype with a sandwich-type structure is designed. To verify the performance of pressure feedback and material perception, pertinent experiments are conducted. The experimental results reveal that within a pressure measurement range of 0–16 N, the detection error of the sensor is 1.81%, and the maximum pressure response accuracy achieves 2.672 V/N. The sensing response time of the sensor is 0.981 s. The recovery time of the sensor is 0.97 s. Furthermore, the exceptional fatigue resistance of the sensor is also demonstrated. Based on the frequency of the output voltage from the prototype, the sliding state of the target object relative to the actuator can be sensed. In terms of material identification, the temperature response accuracy of the sensor is 0.072 V/°C. With the assistance of machine learning methods, six characteristic materials are identified by the sensor under 7 N pressure, with a recognition accuracy of 92.4%. In complex marine environments, this method has great application potential in the field of underwater tactile perception.展开更多
CCCH(C3 H) Zinc finger(Znf) transcription factors(TFs), as a novel type of Znf gene, regulate the expression of genes by binding to their mRNAs and play important roles in plant growth and development and abiotic stre...CCCH(C3 H) Zinc finger(Znf) transcription factors(TFs), as a novel type of Znf gene, regulate the expression of genes by binding to their mRNAs and play important roles in plant growth and development and abiotic stress resistance.Longan(Dimocarpous longan) is a tropical/subtropical fruit tree of great economic importance in Southeast Asia.However, genomic information on C3 H and their functions in longan are still unknown. In this study, a comprehensive analysis of the longan C3 H(DlC3 H) gene family was carried out. A total of 49 DlC3 H genes in three clades were identified from the longan genome database. Characteristics of the genes were analyzed with respect to gene structure,motif composition, phylogenetic tree and potential functions. The analysis of alternative splicing(AS) events suggested that AS events in DlC3 H genes were related to the transformation from longan non-embryonic to embryonic cultures.Promoter analysis indicated that most of the DlC3 H genes included cis-acting elements associated with hormones and stresses responses. Quantitative real-time PCR(qRT-PCR) analysis indicated that 26 of the 49 DlC3 Hs, which possess methyl jasmonate(MeJA) and abscisic acid(ABA) responsive cis-acting elements, showed differential expression patterns under treatment with ABA, MeJA and their endogenous inhibitors, suggesting that DlC3 Hs might be involved in the ABA and MeJA signaling pathways. The expression profiles of 17 of the 49 DlC3 Hs in non-embryonic callus and three tissues of embryonic cultures showed that only five of the 17 DlC3 Hs had the same expression trends as the FPKM trends in transcriptome data;the expression levels of DlC3 H07/14/16/36/49 in embryogenic callus and DlC3 H04/38 in globular embryos were high, suggesting that they have different functions in embryonic development. Further, we verified that DlC3 H01/03/05/11/19/39 were regulated by sRNAs by a modified 5’ RLM-RACE method. This study provides the first systematic analysis of C3 H genes in longan, and found that C3 H genes may be involved in hormone and stress responses, and somatic embryogenesis. Our preliminary investigation may provide clues to further studies on the characteristics and functions of this family in longan.展开更多
It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer stud...It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope（SEM）micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found（1） Rosa xanthina Lindl（shrub species） had greater retention efficiency than Broussonetia papyrifera（broadleaf species） and Pinus bungeana Zucc.（coniferous species）, in terms of particle number and particle area cover.（2） 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.（3） 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes.展开更多
This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed m...This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model.展开更多
The velocity of an over-burst coal seam based on laboratory test results. This seam is about 1/3 compared to a normal coal can be considered as a basis to confirm the area of coal and gas burst by seismic exploration ...The velocity of an over-burst coal seam based on laboratory test results. This seam is about 1/3 compared to a normal coal can be considered as a basis to confirm the area of coal and gas burst by seismic exploration technique. Similarly, the simulation result of the theoretical seismic model shows that there is obvious distinction between over-burst coal and normal coal based on the coal reflection＇s travel-time, energy and frequency. The results from the actual seismic data acquired in the coal and gas over-burst cases is consistent with that of the laboratory and seismic modeling; that is, in the coal and gas burst region, seismic reflection travel time is delayed, seismic amplitude is weakened and seismic frequency is reduced. Therefore, it can be concluded that seismic exploration tech- nique is promising for use in distinguishing coal and gas over-burst regions based on the variation of seismic reflection travel time, amplitude and frequency.展开更多
Road feel is a feature of steering resistance from the road perceived by drivers.A sound road feel design can improve the comfort and stability of drivers’steering maneuvers.However,currently available steering syste...Road feel is a feature of steering resistance from the road perceived by drivers.A sound road feel design can improve the comfort and stability of drivers’steering maneuvers.However,currently available steering systems do not adapt well to the real-time changes in drivers’muscle strength decline,which increases their strain and reduces the stability of steering after long driving.To solve this problem,a personalized road feel control strategy that accounts for drivers’strength decline and comprises a strength decline identification layer,and a road feel control layer is proposed.On the identification layer,the drivers’strength decline characteristics are obtained from hardware-in-loop experimental data.The recursive least squares algorithm with adaptive forgetting factor is proposed to realize an online identification of the mechanical properties of the drivers’arms,and their mapping relationship with the strength decline characteristics is established using the long shortterm memory neural network.On the road feel control layer,considering the uncertainty of the muscle model’s parameters,a personalized road feel controller is designed,where unfixed parameters are kept within an invariant set,and the optimal road feel torque is derived from the muscle’s strength decline characteristics.Experiments show that this strategy can effectively curb drivers’muscle strength decline and improve the smoothness of the torque after long driving.展开更多
基金Supported by the Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents(2016RCJJ046)the National Basic Research Program of China(2012CB720500)
文摘Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and soft sensor systems exhibit multi-dynamic characteristics. Thus, the first contribution is improving the model in the previous study with multi-time-constant. The characteristics-separation-based model will be identified in substep way,and the stochastic Newton recursive(SNR) algorithm is adopted. Considering the dual-rate characteristics of soft sensor systems, the proposed model cannot be identified directly. Thus, two auxiliary models are first proposed to offer the intersample estimations at each update period, based on which the improved algorithm(DAM-SNR) is derived. These two auxiliary models function in switching mechanism which has been illustrated in detail. This algorithm serves for the identification of the proposed model together with the SNR algorithm, and the identification procedure is then presented. Finally, the laboratorial case confirms the effectiveness of the proposed soft sensor model and the algorithms.
基金Supported by Quarantine Industry Research Special Funds for Public Welfare Projects(201310075-2)Research Project of General Administration of Quality Supervision,Inspection and Quarantine(2012IK276)Changzhou Science and Technology Project(CJ20120027,CJ20130036)~~
文摘Dendroctonus spp. is one of the most portable pests in imported and ex- ported timber and wooden packages, and it is an important object of the port quarantine. Making rapid and accurate identification of Dendroctonus spp. is an im- portant method to reduce the invasion risk of Dendroctonus spp. for China. In this paper, Dendroctonus punctatus, which belongs to the Dendroctonus spp., is intro- duced in detail from the aspects of taxonomic status, biological characteristics, mor- phological characteristics and the invasion risk, providing reference for the identifica- tion of Dendroctonus punctatus in inspection and quarantine.
基金supported by the National Natural Science Foundation of China(62372077,61976124)supported by the Fundamental Research Funds for the National Key R&D Project from the Minister of Science and Technology(2021YFA1201604).
文摘In intricate aquatic environments, enhancing the sensory performance of underwater actuators to ensure successful task execution is a significant challenge. To address this, a biomimetic tactile multimodal sensing approach is introduced in this study, based on TriboElectric NanoGenerator (TENG) and Micro-ThermoElectric Generator (MTEG). This method enables actuators to identify the material properties of underwater target objects and to sense grasping states, such as pressure and relative sliding. In this study, a multi-dimensional underwater bionic tactile perception theoretical model is established, and a bionic sensing prototype with a sandwich-type structure is designed. To verify the performance of pressure feedback and material perception, pertinent experiments are conducted. The experimental results reveal that within a pressure measurement range of 0–16 N, the detection error of the sensor is 1.81%, and the maximum pressure response accuracy achieves 2.672 V/N. The sensing response time of the sensor is 0.981 s. The recovery time of the sensor is 0.97 s. Furthermore, the exceptional fatigue resistance of the sensor is also demonstrated. Based on the frequency of the output voltage from the prototype, the sliding state of the target object relative to the actuator can be sensed. In terms of material identification, the temperature response accuracy of the sensor is 0.072 V/°C. With the assistance of machine learning methods, six characteristic materials are identified by the sensor under 7 N pressure, with a recognition accuracy of 92.4%. In complex marine environments, this method has great application potential in the field of underwater tactile perception.
基金funded by the National Natural Science Foundation of China(31672127 and 31572088)the Scientific Research Foundation of Horticulture College of Fujian Agriculture and Forestry University,China(2018S02)+1 种基金the Construction of Plateau Discipline of Fujian Province,China(102/71201801101)the Project of Fujian Academy of Agricultural Sciences,China(AB2017-4)。
文摘CCCH(C3 H) Zinc finger(Znf) transcription factors(TFs), as a novel type of Znf gene, regulate the expression of genes by binding to their mRNAs and play important roles in plant growth and development and abiotic stress resistance.Longan(Dimocarpous longan) is a tropical/subtropical fruit tree of great economic importance in Southeast Asia.However, genomic information on C3 H and their functions in longan are still unknown. In this study, a comprehensive analysis of the longan C3 H(DlC3 H) gene family was carried out. A total of 49 DlC3 H genes in three clades were identified from the longan genome database. Characteristics of the genes were analyzed with respect to gene structure,motif composition, phylogenetic tree and potential functions. The analysis of alternative splicing(AS) events suggested that AS events in DlC3 H genes were related to the transformation from longan non-embryonic to embryonic cultures.Promoter analysis indicated that most of the DlC3 H genes included cis-acting elements associated with hormones and stresses responses. Quantitative real-time PCR(qRT-PCR) analysis indicated that 26 of the 49 DlC3 Hs, which possess methyl jasmonate(MeJA) and abscisic acid(ABA) responsive cis-acting elements, showed differential expression patterns under treatment with ABA, MeJA and their endogenous inhibitors, suggesting that DlC3 Hs might be involved in the ABA and MeJA signaling pathways. The expression profiles of 17 of the 49 DlC3 Hs in non-embryonic callus and three tissues of embryonic cultures showed that only five of the 17 DlC3 Hs had the same expression trends as the FPKM trends in transcriptome data;the expression levels of DlC3 H07/14/16/36/49 in embryogenic callus and DlC3 H04/38 in globular embryos were high, suggesting that they have different functions in embryonic development. Further, we verified that DlC3 H01/03/05/11/19/39 were regulated by sRNAs by a modified 5’ RLM-RACE method. This study provides the first systematic analysis of C3 H genes in longan, and found that C3 H genes may be involved in hormone and stress responses, and somatic embryogenesis. Our preliminary investigation may provide clues to further studies on the characteristics and functions of this family in longan.
基金supported by the “One-Hundred Talents” program of the Chinese Academy of Sciences (No. N234)the National Natural Science Foundation of China(Nos. 41430638 and 41301199)the project “Major Special Project-The China High-Resolution Earth Observation System”
文摘It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope（SEM）micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found（1） Rosa xanthina Lindl（shrub species） had greater retention efficiency than Broussonetia papyrifera（broadleaf species） and Pinus bungeana Zucc.（coniferous species）, in terms of particle number and particle area cover.（2） 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.（3） 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes.
文摘This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model.
基金Supported by the Key Program of National Basic Research Program(973)of China(2006CB202208)the CBM Important Project of 2008ZX05040-003 in China
文摘The velocity of an over-burst coal seam based on laboratory test results. This seam is about 1/3 compared to a normal coal can be considered as a basis to confirm the area of coal and gas burst by seismic exploration technique. Similarly, the simulation result of the theoretical seismic model shows that there is obvious distinction between over-burst coal and normal coal based on the coal reflection＇s travel-time, energy and frequency. The results from the actual seismic data acquired in the coal and gas over-burst cases is consistent with that of the laboratory and seismic modeling; that is, in the coal and gas burst region, seismic reflection travel time is delayed, seismic amplitude is weakened and seismic frequency is reduced. Therefore, it can be concluded that seismic exploration tech- nique is promising for use in distinguishing coal and gas over-burst regions based on the variation of seismic reflection travel time, amplitude and frequency.
基金supported by the National Natural Science Foundation of China(Grant Nos.U24A20199,52372390)the Major Science and Technology Special Project of Nanjing(Grant No.202209008).
文摘Road feel is a feature of steering resistance from the road perceived by drivers.A sound road feel design can improve the comfort and stability of drivers’steering maneuvers.However,currently available steering systems do not adapt well to the real-time changes in drivers’muscle strength decline,which increases their strain and reduces the stability of steering after long driving.To solve this problem,a personalized road feel control strategy that accounts for drivers’strength decline and comprises a strength decline identification layer,and a road feel control layer is proposed.On the identification layer,the drivers’strength decline characteristics are obtained from hardware-in-loop experimental data.The recursive least squares algorithm with adaptive forgetting factor is proposed to realize an online identification of the mechanical properties of the drivers’arms,and their mapping relationship with the strength decline characteristics is established using the long shortterm memory neural network.On the road feel control layer,considering the uncertainty of the muscle model’s parameters,a personalized road feel controller is designed,where unfixed parameters are kept within an invariant set,and the optimal road feel torque is derived from the muscle’s strength decline characteristics.Experiments show that this strategy can effectively curb drivers’muscle strength decline and improve the smoothness of the torque after long driving.
