Metal organic framework(MOF) assembled with coordination bonds has the disadvantage of poor stability that limits its application in the field of stationary phase,while covalent organic framework(COF)assembled through...Metal organic framework(MOF) assembled with coordination bonds has the disadvantage of poor stability that limits its application in the field of stationary phase,while covalent organic framework(COF)assembled through covalent bonds exhibits excellent structural stability.It has been shown that the stationary phases prepared by combining MOF and COF can make up for the poor stability of MOF@SiO_(2),and the MOF/COF composites have superior chromatographic separation performance.However,the traditional methods for preparing COF/MOF based stationary phases are generally solvent thermal synthesis.In this study,a green and low-cost synthesis method was proposed for the preparation of MOF/COF@SiO_(2) stationary phase.Firstly,COF@SiO_(2) was prepared in a choline chloride/ethylene glycol based deep eutectic solvent(DES).Secondly,another acid-base tunable DES prepared by mixing p-toluenesulfonic acid(PTSA)and 2-methylimidazole in different proportions was introduced as the reaction solvent and reactant for rapid synthesis of MOF/COF@SiO_(2).Compared with the toxic transition metal-based MOFs selected in most previous studies,a lightweight and non-toxic S-zone metal(calcium) based MOF was employed in this study.PTSA and calcium will form the calcium/oxygen-containing organic acid framework in acidic DES,which assembles with terephthalic acid dissolved in basic DES to form MOF.The strong hydrogen bonding effect of DES can facilitate rapid assembly of Ca-MOF.The obtained Ca-MOF/COF@SiO_(2) can be used for multi-mode chromatography to efficiently separate multiple isomeric/hydrophilic/hydrophobic analytes.The synthesis method of Ca-MOF/COF@SiO_(2) is green and mild,especially the use of acid-base tunable DES promotes the rapid synthesis of non-toxic Ca-MOF/COF@silica composites,which offers an innovative approach of greenly synthesizing novel MOF/COF stationary phases and extends their applications in the field of chromatography.展开更多
This paper presents a multi-mode control scheme for a soft-switched flyback converter to achieve high efficiency and excellent load regulation over the entire load range. At heavy load, critical conduction mode with v...This paper presents a multi-mode control scheme for a soft-switched flyback converter to achieve high efficiency and excellent load regulation over the entire load range. At heavy load, critical conduction mode with valley switching (CCMVS) is employed to realize soft switching so as to reduce turn-on loss of power switch as well as conducted electromagnetic interference (EMI). At light load, the converter operates in discontinuous conduction mode (DCM) with valley switching and adaptive off-time control (AOT) to limit the switching frequency range and maintain load regulation. At extremely light load or in standby mode, burst mode operation is adopted to provide low power consumption through reducing both switching frequency and static power dissipation of the controller. The multi-mode control is implemented by an oscillator whose pulse duration is adjusted by output feedback. An accurate valley switching control circuit guarantees the minimum turn-on voltage drop of power switch. The pro-totype of the controller IC was fabricated in a 1.5-μm BiCMOS process and applied to a 310 V/20 V, 90 W flyback DC/DC converter circuitry. Experimental results showed that all expected functions were realized successfully. The flyback converter achieved a high efficiency of over 80% from full load down to 2.5 W, with the maximum reaching 88.8%, while the total power consumption in standby mode was about 300 mW.展开更多
Carbon dots(CDs)-based composites have shown impressive performance in fields of information encryption and sensing,however,a great challenge is to simultaneously implement multi-mode luminescence and room-temperature...Carbon dots(CDs)-based composites have shown impressive performance in fields of information encryption and sensing,however,a great challenge is to simultaneously implement multi-mode luminescence and room-temperature phosphorescence(RTP)detection in single system due to the formidable synthesis.Herein,a multifunctional composite of Eu&CDs@p RHO has been designed by co-assembly strategy and prepared via a facile calcination and impregnation treatment.Eu&CDs@p RHO exhibits intense fluorescence(FL)and RTP coming from two individual luminous centers,Eu3+in the free pores and CDs in the interrupted structure of RHO zeolite.Unique four-mode color outputs including pink(Eu^(3+),ex.254 nm),light violet(CDs,ex.365 nm),blue(CDs,254 nm off),and green(CDs,365 nm off)could be realized,on the basis of it,a preliminary application of advanced information encoding has been demonstrated.Given the free pores of matrix and stable RTP in water of confined CDs,a visual RTP detection of Fe^(3+)ions is achieved with the detection limit as low as 9.8μmol/L.This work has opened up a new perspective for the strategic amalgamation of luminous vips with porous zeolite to construct the advanced functional materials.展开更多
Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials prov...Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials provide a promising prospect for imaging-guided precision therapy.Considering that tumor-derived alkaline phosphatase(ALP)is over-expressed in metastatic PCa,it makes a great chance to develop a theranostics system with ALP responsive in the TME.Herein,an ALP-responsive aggregationinduced emission luminogens(AIEgens)nanoprobe AMNF self-assembly was designed for enhancing the diagnosis and treatment of metastatic PCa.The nanoprobe exhibited self-aggregation in the presence of ALP resulted in aggregation-induced fluorescence,and enhanced accumulation and prolonged retention period at the tumor site.In terms of detection,the fluorescence(FL)/computed tomography(CT)/magnetic resonance(MR)multi-mode imaging effect of nanoprobe was significantly improved post-aggregation,enabling precise diagnosis through the amalgamation of multiple imaging modes.Enhanced CT/MR imaging can achieve assist preoperative tumor diagnosis,and enhanced FL imaging technology can achieve“intraoperative visual navigation”,showing its potential application value in clinical tumor detection and surgical guidance.In terms of treatment,AMNF showed strong absorption in the near infrared region after aggregation,which improved the photothermal treatment effect.Overall,our work developed an effective aggregation-enhanced theranostic strategy for ALP-related cancers.展开更多
Low-carbon smart parks achieve selfbalanced carbon emission and absorption through the cooperative scheduling of direct current(DC)-based distributed photovoltaic,energy storage units,and loads.Direct current power li...Low-carbon smart parks achieve selfbalanced carbon emission and absorption through the cooperative scheduling of direct current(DC)-based distributed photovoltaic,energy storage units,and loads.Direct current power line communication(DC-PLC)enables real-time data transmission on DC power lines.With traffic adaptation,DC-PLC can be integrated with other complementary media such as 5G to reduce transmission delay and improve reliability.However,traffic adaptation for DC-PLC and 5G integration still faces the challenges such as coupling between traffic admission control and traffic partition,dimensionality curse,and the ignorance of extreme event occurrence.To address these challenges,we propose a deep reinforcement learning(DRL)-based delay sensitive and reliable traffic adaptation algorithm(DSRTA)to minimize the total queuing delay under the constraints of traffic admission control,queuing delay,and extreme events occurrence probability.DSRTA jointly optimizes traffic admission control and traffic partition,and enables learning-based intelligent traffic adaptation.The long-term constraints are incorporated into both state and bound of drift-pluspenalty to achieve delay awareness and enforce reliability guarantee.Simulation results show that DSRTA has lower queuing delay and more reliable quality of service(QoS)guarantee than other state-of-the-art algorithms.展开更多
A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is fir...A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is first built and decoupled according to the force analysis.The control set with corresponding precise model set is then optimized according to different working conditions.The multi-model switching strategy is studied using machine learning algorithm.The simulation experiments indicate that a multi-model controller comprised of the proportional-integral-derivative(PID),fuzzy PID(FPID)and model predictive controllers with support vector machine(SVM)switching strategy can realize the continuous submarine depth control under full working condition,showing a good control performance compared with a single PID controller.展开更多
Coherent perfect absorption(CPA)and coherent perfect transmission(CPT)are two extreme states arising from the manipulation of optical fields.Generally,CPA and CPT occur under different input-field phases.Therefore,we ...Coherent perfect absorption(CPA)and coherent perfect transmission(CPT)are two extreme states arising from the manipulation of optical fields.Generally,CPA and CPT occur under different input-field phases.Therefore,we propose a scheme to realize an all-optical switch based on phase-dependent CPA–CPT conversion.In our proposal,the CPT state and the CPA state are treated as the on state and the off state,respectively.Consequently,the efficiency of this all-optical switch can reach the maximum value of 1.With the introduction of an incoherent pump field,the CPA state can be achieved under a weaker input probe field or can be converted into a CPT state.The results show that the optical switch can operate with weaker fields and can be further optimized by the application of an incoherent field.展开更多
In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing method...In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.展开更多
Field-effect nanofluidic transistors(FENTs),biomimicking the structure and functionality of neuron,act as biological transistors with the ability to gate switching responses to external stimuli.The switching ratio has...Field-effect nanofluidic transistors(FENTs),biomimicking the structure and functionality of neuron,act as biological transistors with the ability to gate switching responses to external stimuli.The switching ratio has been verified to evaluate the performance of FENTs,but until recently,the response time,another crucial indicator,has been ignored.Employing finite-element method,we investigated the relationship among gate charge,switching ratio and response time by divisionally manipulating gate charge,including entrance surface and the surface of confinement space,for ion transport to optimize switching capability.The dual-split gate charge on FENTs exhibits synergistic effect on switching response.Based on the two regional gate charge on FENTs,multivalence ions in lower concentration,high aspect ratio and single channel show higher switching ratio but longer response time compared to monovalent ions.The findings highlight the necessity of balancing these two signals in FENTs and offer insights for optimizing their design and expanding applications to dual-signal-detection iontronics.展开更多
This paper considers the problem of time varying congestion pricing to determine optimal time-varying tolls at peak periods for a queuing network with the interactions between buses and private cars.Through the combin...This paper considers the problem of time varying congestion pricing to determine optimal time-varying tolls at peak periods for a queuing network with the interactions between buses and private cars.Through the combined applications of the space-time expanded network（STEN） and the conventional network equilibrium modeling techniques,a multi-class,multi-mode and multi-criteria traffic network equilibrium model is developed.Travelers of different classes have distinctive value of times（VOTs）,and travelers from the same class perceive their travel disutility or generalized costs on a route according to different weights of travel time and travel costs.Moreover,the symmetric cost function model is extended to deal with the interactions between buses and private cars.It is found that there exists a uniform（anonymous） link toll pattern which can drive a multi-class,multi-mode and multi-criteria user equilibrium flow pattern to a system optimum when the system＇s objective function is measured in terms of money.It is also found that the marginal cost pricing models with a symmetric travel cost function do not reflect the interactions between traffic flows of different road sections,and the obtained congestion pricing toll is smaller than the real value.展开更多
Gas Turbine Engines （GTEs） are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gaspath components of a GTE are exposed ...Gas Turbine Engines （GTEs） are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gaspath components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measure- ments and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estima- tion scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System （ANFIS）. To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under （a） diverse ambient conditions and control settings, （b） every possible combination of degradation symptoms, and （c） a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.展开更多
For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to p...For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.展开更多
A new multi-mode resistivity imaging sonde, with toroidal coils as source, can conduct three resistivity measurements: azimuthal resistivity, lateral resistivity, and bit resistivity measurements. Thus, the logging ti...A new multi-mode resistivity imaging sonde, with toroidal coils as source, can conduct three resistivity measurements: azimuthal resistivity, lateral resistivity, and bit resistivity measurements. Thus, the logging time and cost are greatly saved. The toroidal coils are simplified as an extended voltage dipole and the response equations are derived for a homogenous formation. Based on 3D FEM, the depth of investigation(DOI), vertical resolution, circumferential azimuthal capacity, borehole diameter, mud resistivity, thickness of target formation, and the resistivity of the surrounding formation and mud invasion are simulated. The results suggest that the three measurement modes of the new sonde are different in vertical resolutions and DOIs. The circumferential detection ability of the azimuth button depends on the contrast between the anomaly and formation resistivity and the open angle of the anomaly. Whether the borehole is truncated at the bit or not has a great influence on the simulation results. The borehole and mud invasion affect the apparent resistivity in all modes, but the effects of resistivity of surrounding formation and thickness of the target formation are only corrected for lateral resistivity measurement.展开更多
There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because the...There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.展开更多
In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression ...In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results.展开更多
In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are ...In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.展开更多
The digital communication in a system of two multi-mode solid state chaotic lasers is investigated theoretically. If the usual method working well in a single-mode laser system is applied to a multi-mode laser system,...The digital communication in a system of two multi-mode solid state chaotic lasers is investigated theoretically. If the usual method working well in a single-mode laser system is applied to a multi-mode laser system, the memory effect of the two nearest digits can cause high rate of mistakes when the digits are decoded through the subtraction of receiver output from the transmittal. By introducing the deviations of two nearest maximum and minimum fluctuationsof the signal to decode the digit, the message can be decoded correctly. Also, this communication method does not critically depend on the quality of the chaotic synchronization of the two multi-mode lasers.展开更多
Multi-mode power internet of things(PIoT)combines various communication media to provide spatio-temporal coverage for low-carbon operation in smart park.Edge-end collaboration is feasible to achieve the full utilizati...Multi-mode power internet of things(PIoT)combines various communication media to provide spatio-temporal coverage for low-carbon operation in smart park.Edge-end collaboration is feasible to achieve the full utilization of heterogeneous resources and anti-eavesdropping.However,edge-end collaboration-based multi-mode PIoT faces challenges of mutual contradiction in communication and security quality of service(QoS)guarantee,inadaptability of resource management,and multi-mode access conflict.We propose an Adaptive learning based delAysensitive and seCure Edge-End Collaboration algorithm(ACE_(2))to optimize multi-mode channel selection and split device power into artificial noise(AN)transmission and data transmission for secure data delivery.ACE_(2) can achieve multi-attribute QoS guarantee,adaptive resource management and security enhancement,and access conflict elimination with the combined power of deep actor-critic(DAC),“win or learn fast(WoLF)”mechanism,and edge-end collaboration.Simulations demonstrate its superior performance in queuing delay,energy consumption,secrecy capacity,and adaptability to differentiated low-carbon services.展开更多
基金supported by National Natural Science Foundation of China (Nos.21906124,32302202)Natural Science Foundation of Hubei Province (No.2017CFB220)Natural Science Foundation of Shandong Province (No.ZR2023MH278)。
文摘Metal organic framework(MOF) assembled with coordination bonds has the disadvantage of poor stability that limits its application in the field of stationary phase,while covalent organic framework(COF)assembled through covalent bonds exhibits excellent structural stability.It has been shown that the stationary phases prepared by combining MOF and COF can make up for the poor stability of MOF@SiO_(2),and the MOF/COF composites have superior chromatographic separation performance.However,the traditional methods for preparing COF/MOF based stationary phases are generally solvent thermal synthesis.In this study,a green and low-cost synthesis method was proposed for the preparation of MOF/COF@SiO_(2) stationary phase.Firstly,COF@SiO_(2) was prepared in a choline chloride/ethylene glycol based deep eutectic solvent(DES).Secondly,another acid-base tunable DES prepared by mixing p-toluenesulfonic acid(PTSA)and 2-methylimidazole in different proportions was introduced as the reaction solvent and reactant for rapid synthesis of MOF/COF@SiO_(2).Compared with the toxic transition metal-based MOFs selected in most previous studies,a lightweight and non-toxic S-zone metal(calcium) based MOF was employed in this study.PTSA and calcium will form the calcium/oxygen-containing organic acid framework in acidic DES,which assembles with terephthalic acid dissolved in basic DES to form MOF.The strong hydrogen bonding effect of DES can facilitate rapid assembly of Ca-MOF.The obtained Ca-MOF/COF@SiO_(2) can be used for multi-mode chromatography to efficiently separate multiple isomeric/hydrophilic/hydrophobic analytes.The synthesis method of Ca-MOF/COF@SiO_(2) is green and mild,especially the use of acid-base tunable DES promotes the rapid synthesis of non-toxic Ca-MOF/COF@silica composites,which offers an innovative approach of greenly synthesizing novel MOF/COF stationary phases and extends their applications in the field of chromatography.
基金the National Natural Science Foundation of China (No. 90707002)the Natural Science Foundation of Zheji-ang Province, China (No. Z104441)
文摘This paper presents a multi-mode control scheme for a soft-switched flyback converter to achieve high efficiency and excellent load regulation over the entire load range. At heavy load, critical conduction mode with valley switching (CCMVS) is employed to realize soft switching so as to reduce turn-on loss of power switch as well as conducted electromagnetic interference (EMI). At light load, the converter operates in discontinuous conduction mode (DCM) with valley switching and adaptive off-time control (AOT) to limit the switching frequency range and maintain load regulation. At extremely light load or in standby mode, burst mode operation is adopted to provide low power consumption through reducing both switching frequency and static power dissipation of the controller. The multi-mode control is implemented by an oscillator whose pulse duration is adjusted by output feedback. An accurate valley switching control circuit guarantees the minimum turn-on voltage drop of power switch. The pro-totype of the controller IC was fabricated in a 1.5-μm BiCMOS process and applied to a 310 V/20 V, 90 W flyback DC/DC converter circuitry. Experimental results showed that all expected functions were realized successfully. The flyback converter achieved a high efficiency of over 80% from full load down to 2.5 W, with the maximum reaching 88.8%, while the total power consumption in standby mode was about 300 mW.
基金supported by the National Natural Science Foundation of China(No.22288101)the 111 Project(No.B17020)。
文摘Carbon dots(CDs)-based composites have shown impressive performance in fields of information encryption and sensing,however,a great challenge is to simultaneously implement multi-mode luminescence and room-temperature phosphorescence(RTP)detection in single system due to the formidable synthesis.Herein,a multifunctional composite of Eu&CDs@p RHO has been designed by co-assembly strategy and prepared via a facile calcination and impregnation treatment.Eu&CDs@p RHO exhibits intense fluorescence(FL)and RTP coming from two individual luminous centers,Eu3+in the free pores and CDs in the interrupted structure of RHO zeolite.Unique four-mode color outputs including pink(Eu^(3+),ex.254 nm),light violet(CDs,ex.365 nm),blue(CDs,254 nm off),and green(CDs,365 nm off)could be realized,on the basis of it,a preliminary application of advanced information encoding has been demonstrated.Given the free pores of matrix and stable RTP in water of confined CDs,a visual RTP detection of Fe^(3+)ions is achieved with the detection limit as low as 9.8μmol/L.This work has opened up a new perspective for the strategic amalgamation of luminous vips with porous zeolite to construct the advanced functional materials.
基金supported by Natural Science Foundation of Jilin Province(No.SKL202302002)Key Research and Development project of Jilin Provincial Science and Technology Department(No.20210204142YY)+2 种基金The Science and Technology Development Program of Jilin Province(No.2020122256JC)Beijing Kechuang Medical Development Foundation Fund of China(No.KC2023-JX-0186BQ079)Talent Reserve Program(TRP),the First Hospital of Jilin University(No.JDYY-TRP-2024007)。
文摘Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials provide a promising prospect for imaging-guided precision therapy.Considering that tumor-derived alkaline phosphatase(ALP)is over-expressed in metastatic PCa,it makes a great chance to develop a theranostics system with ALP responsive in the TME.Herein,an ALP-responsive aggregationinduced emission luminogens(AIEgens)nanoprobe AMNF self-assembly was designed for enhancing the diagnosis and treatment of metastatic PCa.The nanoprobe exhibited self-aggregation in the presence of ALP resulted in aggregation-induced fluorescence,and enhanced accumulation and prolonged retention period at the tumor site.In terms of detection,the fluorescence(FL)/computed tomography(CT)/magnetic resonance(MR)multi-mode imaging effect of nanoprobe was significantly improved post-aggregation,enabling precise diagnosis through the amalgamation of multiple imaging modes.Enhanced CT/MR imaging can achieve assist preoperative tumor diagnosis,and enhanced FL imaging technology can achieve“intraoperative visual navigation”,showing its potential application value in clinical tumor detection and surgical guidance.In terms of treatment,AMNF showed strong absorption in the near infrared region after aggregation,which improved the photothermal treatment effect.Overall,our work developed an effective aggregation-enhanced theranostic strategy for ALP-related cancers.
基金supported by the Science and Technology Project of State Grid Corporation of China under grant 52094021N010(5400-202199534A-0-5-ZN)。
文摘Low-carbon smart parks achieve selfbalanced carbon emission and absorption through the cooperative scheduling of direct current(DC)-based distributed photovoltaic,energy storage units,and loads.Direct current power line communication(DC-PLC)enables real-time data transmission on DC power lines.With traffic adaptation,DC-PLC can be integrated with other complementary media such as 5G to reduce transmission delay and improve reliability.However,traffic adaptation for DC-PLC and 5G integration still faces the challenges such as coupling between traffic admission control and traffic partition,dimensionality curse,and the ignorance of extreme event occurrence.To address these challenges,we propose a deep reinforcement learning(DRL)-based delay sensitive and reliable traffic adaptation algorithm(DSRTA)to minimize the total queuing delay under the constraints of traffic admission control,queuing delay,and extreme events occurrence probability.DSRTA jointly optimizes traffic admission control and traffic partition,and enables learning-based intelligent traffic adaptation.The long-term constraints are incorporated into both state and bound of drift-pluspenalty to achieve delay awareness and enforce reliability guarantee.Simulation results show that DSRTA has lower queuing delay and more reliable quality of service(QoS)guarantee than other state-of-the-art algorithms.
基金the National Natural Science Foundation of China(No.51579201)。
文摘A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is first built and decoupled according to the force analysis.The control set with corresponding precise model set is then optimized according to different working conditions.The multi-model switching strategy is studied using machine learning algorithm.The simulation experiments indicate that a multi-model controller comprised of the proportional-integral-derivative(PID),fuzzy PID(FPID)and model predictive controllers with support vector machine(SVM)switching strategy can realize the continuous submarine depth control under full working condition,showing a good control performance compared with a single PID controller.
基金supported by the National Natural Science Foundation of China(Grants Nos.12304405,12275203,and 12075176)the Natural Science Foundation of Shaanxi Provincial Department of Education(Grant No.23JK0483)+2 种基金the Natural Science Basic Research Program of Shaanxi(Grant Nos.2024JC-YBMS-521 and 2024JC-YBMS-039)the 2022 Shaanxi University Youth Innovation Team Project(Grant No.K20220186)the College Students’Innovative Entrepreneurial Training Plan Program of Shaanxi(Grant No.S202410702178)。
文摘Coherent perfect absorption(CPA)and coherent perfect transmission(CPT)are two extreme states arising from the manipulation of optical fields.Generally,CPA and CPT occur under different input-field phases.Therefore,we propose a scheme to realize an all-optical switch based on phase-dependent CPA–CPT conversion.In our proposal,the CPT state and the CPA state are treated as the on state and the off state,respectively.Consequently,the efficiency of this all-optical switch can reach the maximum value of 1.With the introduction of an incoherent pump field,the CPA state can be achieved under a weaker input probe field or can be converted into a CPT state.The results show that the optical switch can operate with weaker fields and can be further optimized by the application of an incoherent field.
基金funded by“the Fanying Special Program of the National Natural Science Foundation of China,grant number 62341307”“the Scientific research project of Jiangxi Provincial Department of Education,grant number GJJ200839”“theDoctoral startup fund of JiangxiUniversity of Technology,grant number 205200100402”.
文摘In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.
基金supported by the Natural Science Foundation of Guangdong Province,China (No.2025A1515011654)the National Natural Science Foundation of China (No.22090053)+3 种基金the Fundamental Research Funds for National Universities,China University of Geosciences (Wuhan)support from the program of China Scholarships Council (No.202406410155)Young Elite Scientists Sponsorship Program by CAST-Doctoral Student Special Plansupport from the S&T Special Program of Huzhou (No.2024GZ07)。
文摘Field-effect nanofluidic transistors(FENTs),biomimicking the structure and functionality of neuron,act as biological transistors with the ability to gate switching responses to external stimuli.The switching ratio has been verified to evaluate the performance of FENTs,but until recently,the response time,another crucial indicator,has been ignored.Employing finite-element method,we investigated the relationship among gate charge,switching ratio and response time by divisionally manipulating gate charge,including entrance surface and the surface of confinement space,for ion transport to optimize switching capability.The dual-split gate charge on FENTs exhibits synergistic effect on switching response.Based on the two regional gate charge on FENTs,multivalence ions in lower concentration,high aspect ratio and single channel show higher switching ratio but longer response time compared to monovalent ions.The findings highlight the necessity of balancing these two signals in FENTs and offer insights for optimizing their design and expanding applications to dual-signal-detection iontronics.
基金supported by the National Key R&D Program of China(2023YFA1406200)the National Natural Science Foundation of China(T2521005,12174144,12474009,12174146,and 124B2059)the Special Construction Project Fund for Shan-dong Province Taishan Scholars.
文摘Multifunctional optical responsive materials have grown increasingly pivotal in addressingthe escalating demands of sensing,detection,and anti-counterfeiting applications[1,2].These materials exhibit distinct visible optical variations upon exposure to external stimuli,such as pressure,temperature,light,solvents,pH fluctuations,or mechanical force.Fluorescent sensing and anti-counterfeiting technologies leveraging these optical responses have emerged as highly promising solutions.
基金The National High Technology Research and Development Program of China (863 Program) (No. 2007AA11Z202)the National Key Technology R & D Program of China during the 11th Five-Year Plan Period(No. 2006BAJ18B03)the Fundamental Research Funds for the Central Universities (No. DUT10RC(3) 112)
文摘This paper considers the problem of time varying congestion pricing to determine optimal time-varying tolls at peak periods for a queuing network with the interactions between buses and private cars.Through the combined applications of the space-time expanded network（STEN） and the conventional network equilibrium modeling techniques,a multi-class,multi-mode and multi-criteria traffic network equilibrium model is developed.Travelers of different classes have distinctive value of times（VOTs）,and travelers from the same class perceive their travel disutility or generalized costs on a route according to different weights of travel time and travel costs.Moreover,the symmetric cost function model is extended to deal with the interactions between buses and private cars.It is found that there exists a uniform（anonymous） link toll pattern which can drive a multi-class,multi-mode and multi-criteria user equilibrium flow pattern to a system optimum when the system＇s objective function is measured in terms of money.It is also found that the marginal cost pricing models with a symmetric travel cost function do not reflect the interactions between traffic flows of different road sections,and the obtained congestion pricing toll is smaller than the real value.
基金financially co-supported by Fond de Recherche Nature et Technologies (FRQNT) from the Quebec government in Canadathe Natural Sciences and Engineering Research Council (NSERC) of CanadaLife Prediction Technologies Inc. (LPTi) in Ottawa, Canada
文摘Gas Turbine Engines （GTEs） are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gaspath components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measure- ments and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estima- tion scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System （ANFIS）. To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under （a） diverse ambient conditions and control settings, （b） every possible combination of degradation symptoms, and （c） a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.
基金supported by the National Natural Science Foundation of China(61371172)the International S&T Cooperation Program of China(2015DFR10220)+1 种基金the Ocean Engineering Project of National Key Laboratory Foundation(1213)the Fundamental Research Funds for the Central Universities(HEUCF1608)
文摘For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.
基金sponsored by Study on High-Precision Logging While Drilling Imaging Technology of Low-Permeability Reservoirs(No.2016ZX05021-002)
文摘A new multi-mode resistivity imaging sonde, with toroidal coils as source, can conduct three resistivity measurements: azimuthal resistivity, lateral resistivity, and bit resistivity measurements. Thus, the logging time and cost are greatly saved. The toroidal coils are simplified as an extended voltage dipole and the response equations are derived for a homogenous formation. Based on 3D FEM, the depth of investigation(DOI), vertical resolution, circumferential azimuthal capacity, borehole diameter, mud resistivity, thickness of target formation, and the resistivity of the surrounding formation and mud invasion are simulated. The results suggest that the three measurement modes of the new sonde are different in vertical resolutions and DOIs. The circumferential detection ability of the azimuth button depends on the contrast between the anomaly and formation resistivity and the open angle of the anomaly. Whether the borehole is truncated at the bit or not has a great influence on the simulation results. The borehole and mud invasion affect the apparent resistivity in all modes, but the effects of resistivity of surrounding formation and thickness of the target formation are only corrected for lateral resistivity measurement.
基金Project(61374140)supported by the National Natural Science Foundation of China
文摘There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.
基金the 973 Program of China (No.2002CB312200)the National Science Foundation of China (No.60574019)
文摘In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results.
基金National Key Research and Development Program of China(Grant No.2020YFB2009702)National Natural Science Foundation of China(Grant Nos.52075055,U21A20124 and 52111530069)Chongqing Natural Science Foundation of China(Grant No.cstc2020jcyj-msxmX0780)。
文摘In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.
基金The project supported by Natural Science Foundation of Jiangsu Province of China under Grant No.BK2001138
文摘The digital communication in a system of two multi-mode solid state chaotic lasers is investigated theoretically. If the usual method working well in a single-mode laser system is applied to a multi-mode laser system, the memory effect of the two nearest digits can cause high rate of mistakes when the digits are decoded through the subtraction of receiver output from the transmittal. By introducing the deviations of two nearest maximum and minimum fluctuationsof the signal to decode the digit, the message can be decoded correctly. Also, this communication method does not critically depend on the quality of the chaotic synchronization of the two multi-mode lasers.
基金supported by the Science and Technology Project of State Grid Corporation of China under Grant Number 52094021N010 (5400202199534A-0-5-ZN)
文摘Multi-mode power internet of things(PIoT)combines various communication media to provide spatio-temporal coverage for low-carbon operation in smart park.Edge-end collaboration is feasible to achieve the full utilization of heterogeneous resources and anti-eavesdropping.However,edge-end collaboration-based multi-mode PIoT faces challenges of mutual contradiction in communication and security quality of service(QoS)guarantee,inadaptability of resource management,and multi-mode access conflict.We propose an Adaptive learning based delAysensitive and seCure Edge-End Collaboration algorithm(ACE_(2))to optimize multi-mode channel selection and split device power into artificial noise(AN)transmission and data transmission for secure data delivery.ACE_(2) can achieve multi-attribute QoS guarantee,adaptive resource management and security enhancement,and access conflict elimination with the combined power of deep actor-critic(DAC),“win or learn fast(WoLF)”mechanism,and edge-end collaboration.Simulations demonstrate its superior performance in queuing delay,energy consumption,secrecy capacity,and adaptability to differentiated low-carbon services.
