Since its discovery in the 1980s,the insect cell-baculovirus expression vector system(IC-BEVS)has been widely used in biomedical applications,such as recombinant protein expression,drug screening,vaccine development,g...Since its discovery in the 1980s,the insect cell-baculovirus expression vector system(IC-BEVS)has been widely used in biomedical applications,such as recombinant protein expression,drug screening,vaccine development,gene therapy and so on[1].As a eukaryotic system,IC-BEVS has great development prospects due to its advantages such as high safety,simple operation,simultaneous expression of multi-subunit proteins,and suitability for large-scale cultivation[2].展开更多
In this paper, we consider the eigenvalue problem of a class of fourth-order operator matrices appearing in mechan- ics, including the geometric multiplicity, algebraic index, and algebraic multiplicity of the eigenva...In this paper, we consider the eigenvalue problem of a class of fourth-order operator matrices appearing in mechan- ics, including the geometric multiplicity, algebraic index, and algebraic multiplicity of the eigenvalue, the symplectic orthogonality, and completeness of eigen and root vector systems. The obtained results are applied to the plate bending problem.展开更多
In this study,we constructed dual-transgene vectors（pDT1,pDT7,and pDT7G） that simultaneously co-expressed two genes in plants.ACTIN2 and UBQ10 promoters were used to control the expression of these two genes.The 4&#...In this study,we constructed dual-transgene vectors（pDT1,pDT7,and pDT7G） that simultaneously co-expressed two genes in plants.ACTIN2 and UBQ10 promoters were used to control the expression of these two genes.The 4×Myc.3×HA,and 3×Flag reporter genes allowed for the convenient identification of a tunable co-expression system in plants,whereas the dexamethasone（Dex） inducible reporter gene C-terminus of the glucocorticoid receptor（cGR） provided Dex-dependent translocation of the fusion gene between the nucleus and cytoplasm.The function of pDT vectors was validated using four pairwise genes in Nicotiana benthamiana or Anihidopsis thaliana.The co-expression efficiency of two genes from the pDT1 and pDT7 G vectors was 35%and 42%,respectively,which ensured the generation of sufficient transgenic materials.These pDT vectors are simple,reliable,efficient,and time-saving tools for the co-expression of two genes through a single transformation event and can be used in the study of protein-protein interactions or multi-component complexes.展开更多
Exoplants of tomato(Lycopersicon esculentum) leaf were transformed with Ti plasmids using binary vector system.After screening.with selection culture, kanamycin-resistant seedling were obtained from callus. Molecular ...Exoplants of tomato(Lycopersicon esculentum) leaf were transformed with Ti plasmids using binary vector system.After screening.with selection culture, kanamycin-resistant seedling were obtained from callus. Molecular hybridization proved the integration of Km gene into plant cell genome via A.tumefaciens. Higher activity of Nos-NPTase was demonstrated in the transformed plant,thus confirming the successful expression of the resistance gene in recipient cells.展开更多
Thrust-vectoring capability has become a critical feature for propulsion systems as space missions move from static to dynamic.Thrust-vectoring is a well-developed area of rocket engine science.For electric propulsion...Thrust-vectoring capability has become a critical feature for propulsion systems as space missions move from static to dynamic.Thrust-vectoring is a well-developed area of rocket engine science.For electric propulsion,however,it is an evolving field that has taken a new leap forward in recent years.A review and analysis of thrust-vectoring schemes for electric propulsion systems have been conducted.The scope of this review includes thrust-vectoring schemes that can be implemented for electrostatic,electromagnetic,and beam-driven thrusters.A classification of electric propulsion schemes that provide thrust-vectoring capability is developed.More attention is given to schemes implemented in laboratory prototypes and flight models.The final part is devoted to a discussion on the suitability of different electric propulsion systems with thrust-vectoring capability for modern space mission operations.The thrust-vectoring capability of electric propulsion is necessary for inner and outer space satellites,which are at a disadvantage with conventional unidirectional propulsion systems due to their limited maneuverability.展开更多
Avian metapneumovirus(aMPV),a paramyxovirus,causes acute respiratory diseases in turkeys and swollen head syndrome in chickens.This study established a reverse genetics system for aMPV subtype B LN16-A strain based on...Avian metapneumovirus(aMPV),a paramyxovirus,causes acute respiratory diseases in turkeys and swollen head syndrome in chickens.This study established a reverse genetics system for aMPV subtype B LN16-A strain based on T7 RNA polymerase.Full-length cDNA of the LN16-A strain was constructed by assembling 5 cDNA fragments between the T7 promoter and hepatitis delta virus ribozyme.Transfection of this plasmid,along with the supporting plasmids encoding the N,P,M2-1,and L proteins of LN16-A into BSR-T7/5 cells,resulted in the recovery of aMPV subtype B.To identify an effective insertion site,the enhanced green fluorescent protein(EGFP)gene was inserted into different sites of the LN16-A genome to generate recombinant LN16-As.The results showed that the expression levels of EGFP at the site between the G and L genes of LN16-A were significantly higher than those at the other two sites(between the leader and N genes or replacing the SH gene).To verify the availability of the site between G and L for foreign gene expression,the VP2 gene of very virulent infectious bursal disease virus(vvIBDV)was inserted into this site,and recombinant LN16-A(rLN16A-vvVP2)was successfully rescued.Single immunization of specificpathogen-free chickens with rLN16A-vvVP2 induced high levels of neutralizing antibodies and provided 100%protection against the virulent aMPV subtype B and vvIBDV.Establishing a reverse genetics system here provides an important foundation for understanding aMPV pathogenesis and developing novel vector vaccines.展开更多
Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CA...Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CAR-NK cell therapy has enabled the development of“off-the-shelf”products that bypass the lengthy and expensive cell manufacturing process1.展开更多
Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the p...Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the pushing force acting on the wellbore in different sizes and directions within a circular range,ultimately allowing the wellbore trajectory to be drilled in a predetermined direction.By analyzing its mathematical principles and the actual characteristics of the instrument,a vector force closed-loop control method,including steering and holding modes,was designed.The adjustment criteria for the three hydraulic modules are determined to achieve rapid adjustment of the vector force.The theoretical feasibility of the developed method was verified by comparing its results with the on-site application data of an imported rotary guidance system.展开更多
Vector magnetic measurement is increasingly widely used.In order to improve the accuracy of vector magnetic measurement system on board a vehicle,researchers have proposed various calibration methods.Most of them requ...Vector magnetic measurement is increasingly widely used.In order to improve the accuracy of vector magnetic measurement system on board a vehicle,researchers have proposed various calibration methods.Most of them require altering the magnetic vector in the vehicle coordinate system.Exploring the use of geomagnetic variation to change the geomagnetic vector in the vehicle coordinate system,this paper proposes a novel vector magnetic measurement calibration method.In this method,a vector magnetometer mounted on a vehicle and an accurate vector magnetometer separately measure the geomagnetic field at diff erent locations within the same area.Based on the physical principle that the geomagnetic variation at two nearby locations is equal,the calibration parameters of the magnetometer on the vehicle can be determined through a set of equations containing the measurements from the two magnetometers.The theoretical derivation and simulation experiment results demonstrate the feasibility of this method.Therefore,it can serve as a new alternative calibration method,especially in scenarios where a high degree of accuracy in the estimation of calibration parameters is not required.展开更多
With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter ...With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter switching frequency of the inverter is one of the impacting factors.At the same time,the control accuracy of the system also needs to be considered,and the torque ripple and flux ripple are usually considered to be its important indexes.This paper proposes a three-stage series Model Predictive Torque and Flux Control system(three-stage series MPTFC)based on fast optimal voltage vector selection to reduce switching frequency and suppress torque ripple and flux ripple.Firstly,the analytical model of the PMSM is established and the multi-stage series control method is used to reduce the switching frequency.Secondly,selectable voltage vectors are extended from 8 to 26 and a fast selection method for optimal voltage vector sectors is designed based on the hysteresis comparator,which can suppress the torque ripple and flux ripple to improve the control accuracy.Thirdly,a three-stage series control is obtained by expanding the two-stage series control using the P-Q torque decomposition theory.Finally,a model predictive torque and flux control experimental platform is built,and the feasibility and effectiveness of this method are verified through comparison experiments.展开更多
With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as...With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.展开更多
The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates ...The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.展开更多
Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme ...Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme of co-directional secondary flow was designed based on a 30 kgf thrust turbojet engine,an equivalent rudder deflection control variable of Mass Flow Combination(MFC)was proposed,and a control model was established to form a FTV control system scheme,which was integrated with the flight control system of a 100 kg tailless flying wing with medium aspect ratio to achieve closed-loop control of the yaw attitude based on FTV.The heading stability augmentation and maneuvering control characteristics and time response characteristics of tailless flying wing by FTV were quantitatively studied through virtual flight test in a wind tunnel at a wind speed of 35 m/s.The results show that the control strategy based on MFC achieves bidirectional continuous and stable control of thrust vector angle in a range of±11°,and the thrust vector angle varies monotonically with MFC;the co-directional FTV realizes bidirectional continuous and stable control of the yaw attitude of tailless flying wing,without longitudinal/lateral coupling moment.The increment of the maximum yawing moment coefficient is 0.0029,the maximum yaw rate is 7.55(°)/s,and the response time of the yaw rate of the vectoring nozzle actuated by the secondary flow is about 0.06 s,which satisfies the heading stability augmentation and maneuvering control response requirements of the aircraft with statically unstable heading,and provides new control means for the heading rudderless attitude control of tailless flying wing.展开更多
Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural netwo...Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural networks learn new classes sequentially,they suffer from catastrophic forgetting—the tendency to lose knowledge of earlier classes.This challenge,which lies at the core of class-incremental learning,severely limits the deployment of continual learning systems in real-world applications with streaming data.Existing approaches,including rehearsalbased methods and knowledge distillation techniques,have attempted to address this issue but often struggle to effectively preserve decision boundaries and discriminative features under limited memory constraints.To overcome these limitations,we propose a support vector-guided framework for class-incremental learning.The framework integrates an enhanced feature extractor with a Support Vector Machine classifier,which generates boundary-critical support vectors to guide both replay and distillation.Building on this architecture,we design a joint feature retention strategy that combines boundary proximity with feature diversity,and a Support Vector Distillation Loss that enforces dual alignment in decision and semantic spaces.In addition,triple attention modules are incorporated into the feature extractor to enhance representation power.Extensive experiments on CIFAR-100 and Tiny-ImageNet demonstrate effective improvements.On CIFAR-100 and Tiny-ImageNet with 5 tasks,our method achieves 71.68%and 58.61%average accuracy,outperforming strong baselines by 3.34%and 2.05%.These advantages are consistently observed across different task splits,highlighting the robustness and generalization of the proposed approach.Beyond benchmark evaluations,the framework also shows potential in few-shot and resource-constrained applications such as edge computing and mobile robotics.展开更多
The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects acc...The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.展开更多
Disruption of host physiological processes,leading to symptom expression,is a common hallmark during plant virus infections.The concept of“symptoms as strategy”is rapidly reshaping our understanding of plant virolog...Disruption of host physiological processes,leading to symptom expression,is a common hallmark during plant virus infections.The concept of“symptoms as strategy”is rapidly reshaping our understanding of plant virology.An emerging theme is that symptom expressions—such as stunting,curling,and yellowing,which devastate yield—may themselves be evolved viral adaptation strategies rather than collateral damage.展开更多
Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using d...Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.展开更多
The laser gyro is most su it able for building the strap down inertial navigation system (SINS), and its acc uracy of attitude algorithm can enormously affect that of the laser SINS. This p aper develops three improv...The laser gyro is most su it able for building the strap down inertial navigation system (SINS), and its acc uracy of attitude algorithm can enormously affect that of the laser SINS. This p aper develops three improved algorithmal expressions for strap down attitude ut ilizing the angular increment output by the laser gyro from the last two and cur rent updating periods according to the number of gyro samples, and analyses the algorithm error in the classical coning motion. Compared with the conventional algorithms, simulational results show that this improved algorithm has higher precision. A new way to improve the rotation vector algorithms is provided.展开更多
Multivariables, strong coupling, nonlinearity, and large delays characterize the boiler-turbine coordinated control systems for ship power equipment. To better deal with these conditions, a compound control strategy b...Multivariables, strong coupling, nonlinearity, and large delays characterize the boiler-turbine coordinated control systems for ship power equipment. To better deal with these conditions, a compound control strategy based on a support vector machine （SVM） with inverse identification was proposed and applied to research simulating coordinated control systems. This method combines SVM inverse control and fuzzy control, taking advantage of the merits of SVM inverse controls which can be designed easily and have high reliability, and those of fuzzy controls, which respond rapidly and have good anti-jamming capability and robustness. It ensures the controller can be controlled with near instantaneous adjustments to maintain a steady state, even if the SVM is not trained well. The simulation results show that the control quality of this fuzzy-SVM compound control algorithm is high, with good performance in dynamic response speed, static stability, restraint of overshoot, and robustness.展开更多
A novel adaptive support vector regression neural network （SVR-NN） is proposed, which combines respectively merits of support vector machines and a neural network. First, a support vector regression approach is appl...A novel adaptive support vector regression neural network （SVR-NN） is proposed, which combines respectively merits of support vector machines and a neural network. First, a support vector regression approach is applied to determine the initial structure and initial weights of the SVR-NN so that the network architecture is easily determined and the hidden nodes can adaptively be constructed based on support vectors. Furthermore, an annealing robust learning algorithm is presented to adjust these hidden node parameters as well as the weights of the SVR-NN. To test the validity of the proposed method, it is demonstrated that the adaptive SVR-NN can be used effectively for the identification of nonlinear dynamic systems. Simulation results show that the identification schemes based on the SVR-NN give considerably better performance and show faster learning in comparison to the previous neural network method.展开更多
文摘Since its discovery in the 1980s,the insect cell-baculovirus expression vector system(IC-BEVS)has been widely used in biomedical applications,such as recombinant protein expression,drug screening,vaccine development,gene therapy and so on[1].As a eukaryotic system,IC-BEVS has great development prospects due to its advantages such as high safety,simple operation,simultaneous expression of multi-subunit proteins,and suitability for large-scale cultivation[2].
基金supported by the National Natural Science Foundation of China (Grant Nos. 11061019 and 10962004)the Chunhui Program of Ministry of Education of China (Grant No. Z2009-1-01010)+1 种基金the Natural Science Foundation of Inner Mongolia, China(Grant Nos. 2010MS0110 and 2009BS0101)the Cultivation of Innovative Talent of ‘211 Project’ of Inner Mongolia University
文摘In this paper, we consider the eigenvalue problem of a class of fourth-order operator matrices appearing in mechan- ics, including the geometric multiplicity, algebraic index, and algebraic multiplicity of the eigenvalue, the symplectic orthogonality, and completeness of eigen and root vector systems. The obtained results are applied to the plate bending problem.
基金supported by the National Natural Science Foundation of China(Grant No.31171176)the Cooperative Innovation Center of Engineering and New Products for Developmental Biology of Hunan Province(Grant No.20134486)
文摘In this study,we constructed dual-transgene vectors（pDT1,pDT7,and pDT7G） that simultaneously co-expressed two genes in plants.ACTIN2 and UBQ10 promoters were used to control the expression of these two genes.The 4×Myc.3×HA,and 3×Flag reporter genes allowed for the convenient identification of a tunable co-expression system in plants,whereas the dexamethasone（Dex） inducible reporter gene C-terminus of the glucocorticoid receptor（cGR） provided Dex-dependent translocation of the fusion gene between the nucleus and cytoplasm.The function of pDT vectors was validated using four pairwise genes in Nicotiana benthamiana or Anihidopsis thaliana.The co-expression efficiency of two genes from the pDT1 and pDT7 G vectors was 35%and 42%,respectively,which ensured the generation of sufficient transgenic materials.These pDT vectors are simple,reliable,efficient,and time-saving tools for the co-expression of two genes through a single transformation event and can be used in the study of protein-protein interactions or multi-component complexes.
文摘Exoplants of tomato(Lycopersicon esculentum) leaf were transformed with Ti plasmids using binary vector system.After screening.with selection culture, kanamycin-resistant seedling were obtained from callus. Molecular hybridization proved the integration of Km gene into plant cell genome via A.tumefaciens. Higher activity of Nos-NPTase was demonstrated in the transformed plant,thus confirming the successful expression of the resistance gene in recipient cells.
基金performed at large-scale research facility"Beam-M"of Bauman Moscow State Technical University following the government task by the Ministry of Science and Higher Education of the Russian Federation(No.FSFN-2024-0007).
文摘Thrust-vectoring capability has become a critical feature for propulsion systems as space missions move from static to dynamic.Thrust-vectoring is a well-developed area of rocket engine science.For electric propulsion,however,it is an evolving field that has taken a new leap forward in recent years.A review and analysis of thrust-vectoring schemes for electric propulsion systems have been conducted.The scope of this review includes thrust-vectoring schemes that can be implemented for electrostatic,electromagnetic,and beam-driven thrusters.A classification of electric propulsion schemes that provide thrust-vectoring capability is developed.More attention is given to schemes implemented in laboratory prototypes and flight models.The final part is devoted to a discussion on the suitability of different electric propulsion systems with thrust-vectoring capability for modern space mission operations.The thrust-vectoring capability of electric propulsion is necessary for inner and outer space satellites,which are at a disadvantage with conventional unidirectional propulsion systems due to their limited maneuverability.
基金supported by the grants from the National Key Research and Development Program of China(2022YFD1800604)the China Agriculture Research System(CARS-41)the Heilongjiang Touyan Innovation Team Program,China。
文摘Avian metapneumovirus(aMPV),a paramyxovirus,causes acute respiratory diseases in turkeys and swollen head syndrome in chickens.This study established a reverse genetics system for aMPV subtype B LN16-A strain based on T7 RNA polymerase.Full-length cDNA of the LN16-A strain was constructed by assembling 5 cDNA fragments between the T7 promoter and hepatitis delta virus ribozyme.Transfection of this plasmid,along with the supporting plasmids encoding the N,P,M2-1,and L proteins of LN16-A into BSR-T7/5 cells,resulted in the recovery of aMPV subtype B.To identify an effective insertion site,the enhanced green fluorescent protein(EGFP)gene was inserted into different sites of the LN16-A genome to generate recombinant LN16-As.The results showed that the expression levels of EGFP at the site between the G and L genes of LN16-A were significantly higher than those at the other two sites(between the leader and N genes or replacing the SH gene).To verify the availability of the site between G and L for foreign gene expression,the VP2 gene of very virulent infectious bursal disease virus(vvIBDV)was inserted into this site,and recombinant LN16-A(rLN16A-vvVP2)was successfully rescued.Single immunization of specificpathogen-free chickens with rLN16A-vvVP2 induced high levels of neutralizing antibodies and provided 100%protection against the virulent aMPV subtype B and vvIBDV.Establishing a reverse genetics system here provides an important foundation for understanding aMPV pathogenesis and developing novel vector vaccines.
基金supported by grants from the Noncommunicable Chronic Diseases-National Science and Technology Major Project(Grant No.2023ZD0501300)Science Technology Department of Zhejiang Province(Grant No.2021C03117)+2 种基金National Natural Science Foundation of China(Grant No.82350104 and 82170219)Natural Science Foundation of Zhejiang Province,China(Grant No.LY23H080004 and LY24H080001)Medical Health Science and Technology Project of Zhejiang Provincial Health Commission(Grant No.2021KY199)。
文摘Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CAR-NK cell therapy has enabled the development of“off-the-shelf”products that bypass the lengthy and expensive cell manufacturing process1.
基金supported by the Opening Foundation of China National Logging Corporation(CNLC20229C06)the China Petroleum Technical Service Corporation's science project'Development and application of 475 rotary steering system'(2024T-001001)。
文摘Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the pushing force acting on the wellbore in different sizes and directions within a circular range,ultimately allowing the wellbore trajectory to be drilled in a predetermined direction.By analyzing its mathematical principles and the actual characteristics of the instrument,a vector force closed-loop control method,including steering and holding modes,was designed.The adjustment criteria for the three hydraulic modules are determined to achieve rapid adjustment of the vector force.The theoretical feasibility of the developed method was verified by comparing its results with the on-site application data of an imported rotary guidance system.
基金General Project of Basic Research Plan for Natural Sciences in Shaanxi Province,grant number 2023-JC-YB-244Youth Project of Basic Research Plan for Natural Sciences in Shaanxi Province,grant number 2024JC-YBQN-0253.
文摘Vector magnetic measurement is increasingly widely used.In order to improve the accuracy of vector magnetic measurement system on board a vehicle,researchers have proposed various calibration methods.Most of them require altering the magnetic vector in the vehicle coordinate system.Exploring the use of geomagnetic variation to change the geomagnetic vector in the vehicle coordinate system,this paper proposes a novel vector magnetic measurement calibration method.In this method,a vector magnetometer mounted on a vehicle and an accurate vector magnetometer separately measure the geomagnetic field at diff erent locations within the same area.Based on the physical principle that the geomagnetic variation at two nearby locations is equal,the calibration parameters of the magnetometer on the vehicle can be determined through a set of equations containing the measurements from the two magnetometers.The theoretical derivation and simulation experiment results demonstrate the feasibility of this method.Therefore,it can serve as a new alternative calibration method,especially in scenarios where a high degree of accuracy in the estimation of calibration parameters is not required.
基金co-supported by the National Natural Science Foundation of China(No.52477063)the National Key Research and Development Program of China(No.2023YFF0719100)。
文摘With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter switching frequency of the inverter is one of the impacting factors.At the same time,the control accuracy of the system also needs to be considered,and the torque ripple and flux ripple are usually considered to be its important indexes.This paper proposes a three-stage series Model Predictive Torque and Flux Control system(three-stage series MPTFC)based on fast optimal voltage vector selection to reduce switching frequency and suppress torque ripple and flux ripple.Firstly,the analytical model of the PMSM is established and the multi-stage series control method is used to reduce the switching frequency.Secondly,selectable voltage vectors are extended from 8 to 26 and a fast selection method for optimal voltage vector sectors is designed based on the hysteresis comparator,which can suppress the torque ripple and flux ripple to improve the control accuracy.Thirdly,a three-stage series control is obtained by expanding the two-stage series control using the P-Q torque decomposition theory.Finally,a model predictive torque and flux control experimental platform is built,and the feasibility and effectiveness of this method are verified through comparison experiments.
文摘With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.
基金supported by grants PID2020-120308RB-I00 and PID2023-147802OB-I00 funded by MICIU/AEI/10.13039/501100011033FEDER,UE,by Aligning Science Across Parkinson’s(ref.ASAP-020505)through the Michael J.Fox Foundation for Parkinson’s Research+1 种基金by CiberNed Intramural Collaborative Projects(ref.PI2020/09)by the Spanish Fundación Mutua Madrile?a de Investigación Médica(to JLL)。
文摘The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.
文摘Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme of co-directional secondary flow was designed based on a 30 kgf thrust turbojet engine,an equivalent rudder deflection control variable of Mass Flow Combination(MFC)was proposed,and a control model was established to form a FTV control system scheme,which was integrated with the flight control system of a 100 kg tailless flying wing with medium aspect ratio to achieve closed-loop control of the yaw attitude based on FTV.The heading stability augmentation and maneuvering control characteristics and time response characteristics of tailless flying wing by FTV were quantitatively studied through virtual flight test in a wind tunnel at a wind speed of 35 m/s.The results show that the control strategy based on MFC achieves bidirectional continuous and stable control of thrust vector angle in a range of±11°,and the thrust vector angle varies monotonically with MFC;the co-directional FTV realizes bidirectional continuous and stable control of the yaw attitude of tailless flying wing,without longitudinal/lateral coupling moment.The increment of the maximum yawing moment coefficient is 0.0029,the maximum yaw rate is 7.55(°)/s,and the response time of the yaw rate of the vectoring nozzle actuated by the secondary flow is about 0.06 s,which satisfies the heading stability augmentation and maneuvering control response requirements of the aircraft with statically unstable heading,and provides new control means for the heading rudderless attitude control of tailless flying wing.
基金supported by the Gansu Provincial Natural Science Foundation(grant number 25JRRA074)the Gansu Provincial Key R&D Science and Technology Program(grant number 24YFGA060)the National Natural Science Foundation of China(grant number 62161019).
文摘Modern intelligent systems,such as autonomous vehicles and face recognition,must continuously adapt to new scenarios while preserving their ability to handle previously encountered situations.However,when neural networks learn new classes sequentially,they suffer from catastrophic forgetting—the tendency to lose knowledge of earlier classes.This challenge,which lies at the core of class-incremental learning,severely limits the deployment of continual learning systems in real-world applications with streaming data.Existing approaches,including rehearsalbased methods and knowledge distillation techniques,have attempted to address this issue but often struggle to effectively preserve decision boundaries and discriminative features under limited memory constraints.To overcome these limitations,we propose a support vector-guided framework for class-incremental learning.The framework integrates an enhanced feature extractor with a Support Vector Machine classifier,which generates boundary-critical support vectors to guide both replay and distillation.Building on this architecture,we design a joint feature retention strategy that combines boundary proximity with feature diversity,and a Support Vector Distillation Loss that enforces dual alignment in decision and semantic spaces.In addition,triple attention modules are incorporated into the feature extractor to enhance representation power.Extensive experiments on CIFAR-100 and Tiny-ImageNet demonstrate effective improvements.On CIFAR-100 and Tiny-ImageNet with 5 tasks,our method achieves 71.68%and 58.61%average accuracy,outperforming strong baselines by 3.34%and 2.05%.These advantages are consistently observed across different task splits,highlighting the robustness and generalization of the proposed approach.Beyond benchmark evaluations,the framework also shows potential in few-shot and resource-constrained applications such as edge computing and mobile robotics.
基金supported by the China Agriculture Research System of MOF and MARAthe National Natural Science Foundation of China (31872337 and 31501919)the Agricultural Science and Technology Innovation Project,China (ASTIP-IAS02)。
文摘The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.
基金supported by the National Natural Science Foundation of China(32272482)the Innovation Research 2035 Pilot Plan of Southwest University(SWU-XDZD22002).
文摘Disruption of host physiological processes,leading to symptom expression,is a common hallmark during plant virus infections.The concept of“symptoms as strategy”is rapidly reshaping our understanding of plant virology.An emerging theme is that symptom expressions—such as stunting,curling,and yellowing,which devastate yield—may themselves be evolved viral adaptation strategies rather than collateral damage.
基金The work described in this paper was fully supported by a grant from Hong Kong Metropolitan University(RIF/2021/05).
文摘Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.
文摘The laser gyro is most su it able for building the strap down inertial navigation system (SINS), and its acc uracy of attitude algorithm can enormously affect that of the laser SINS. This p aper develops three improved algorithmal expressions for strap down attitude ut ilizing the angular increment output by the laser gyro from the last two and cur rent updating periods according to the number of gyro samples, and analyses the algorithm error in the classical coning motion. Compared with the conventional algorithms, simulational results show that this improved algorithm has higher precision. A new way to improve the rotation vector algorithms is provided.
文摘Multivariables, strong coupling, nonlinearity, and large delays characterize the boiler-turbine coordinated control systems for ship power equipment. To better deal with these conditions, a compound control strategy based on a support vector machine （SVM） with inverse identification was proposed and applied to research simulating coordinated control systems. This method combines SVM inverse control and fuzzy control, taking advantage of the merits of SVM inverse controls which can be designed easily and have high reliability, and those of fuzzy controls, which respond rapidly and have good anti-jamming capability and robustness. It ensures the controller can be controlled with near instantaneous adjustments to maintain a steady state, even if the SVM is not trained well. The simulation results show that the control quality of this fuzzy-SVM compound control algorithm is high, with good performance in dynamic response speed, static stability, restraint of overshoot, and robustness.
文摘A novel adaptive support vector regression neural network （SVR-NN） is proposed, which combines respectively merits of support vector machines and a neural network. First, a support vector regression approach is applied to determine the initial structure and initial weights of the SVR-NN so that the network architecture is easily determined and the hidden nodes can adaptively be constructed based on support vectors. Furthermore, an annealing robust learning algorithm is presented to adjust these hidden node parameters as well as the weights of the SVR-NN. To test the validity of the proposed method, it is demonstrated that the adaptive SVR-NN can be used effectively for the identification of nonlinear dynamic systems. Simulation results show that the identification schemes based on the SVR-NN give considerably better performance and show faster learning in comparison to the previous neural network method.
