The naturally fermented Inner Mongolian cheese’s flavor and nutritional value make it a popular choice among customers.In this work,to create multi-functional peptides that have taste and biological activity,peptidom...The naturally fermented Inner Mongolian cheese’s flavor and nutritional value make it a popular choice among customers.In this work,to create multi-functional peptides that have taste and biological activity,peptidomics and bioinformatics were used to screen flavor peptides from Inner Mongolian cheese and further assess their antioxidant and angiotensin I-converting enzyme(ACE)inhibitory properties.According to sensory data,YH8 and IL7 had detectable bitter tastes with low thresholds of 0.03 and 0.06 mmol/L,respectively.With an umami threshold range of 0.24‒0.81 mmol/L,VQ6,FK13,HP13 and QT14 exhibited a range of flavors dominated by umami,including sweet,bitter,salty,sour and kokumi.Antioxidant activity wise,YH8,VQ6,HP13 and QT14 were well represented.The above-mentioned peptides all had some ACE inhibitory effect.The bitter peptide IL7(IC_(50)=0.08 mmol/L)had the highest level of ACE inhibitory activity,followed by YH8(IC_(50)=0.33 mmol/L).These multi-functional peptides,which have been assessed for bioactive and taste features in Inner Mongolian cheese,may have positive impacts on health and harmonize the cheese’s overall flavor.These results suggest that some flavor peptides produced in fermented foods might be with bioactivities while providing a basis for the exploration and application of multi-functional peptides.展开更多
Figure 6(a)in the paper[Chin.Phys.B 33074203(2024)]was incorrect due to editorial oversight.The correct figure is provided.This modification does not affect the result presented in the paper.
Accurate calibration of China's new generation ground-based polarimetric radar(GR) network is crucial yet challenging. Although application of the Dual-frequency Precipitation Radar(DPR) of the Global Precipitatio...Accurate calibration of China's new generation ground-based polarimetric radar(GR) network is crucial yet challenging. Although application of the Dual-frequency Precipitation Radar(DPR) of the Global Precipitation Measurement Core Observatory for GR assessment is well-established, current methodologies are inherently limited. Focusing on three GRs in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)—strategically selected for their high overlapping coverage(>65%) and distinct from single GR or less dense coverage studies—this work introduces key refinements by integrating innovative enhancements into the volume-matching method(VMM), reflecting a systematic approach to mitigating potential error sources. Specifically, we integrate: 1) a novel frequency correction method that adapts to DPR-observed precipitation phase and type, replacing assumption-based polynomial fitting;and 2) a precise beam time-difference matching approach(accuracy < 1 s) to minimize temporal mismatch errors, which improves upon coarser time averaging methods. Furthermore, we developed statistically robust, optimized threshold criteria based on systematic sensitivity analyses using 11 quality control factors, including precipitation type, bright band effects, and attenuation correction limitations. These criteria establish an enhanced protocol designed to minimize errors arising from instrumental, frequency, and scanning differences. Application of this enhanced methodology to the GBA GRs(2021–2023) yielded a significantly improved matching accuracy(correlation coefficient, CC: 0.90–0.95;standard deviation,STD: 1.2–1.6 dB). A unique contribution of this work is the quantitative estimation of historical calibration errors and operational stability, which was achieved by linking VMM results with operational GR calibration and maintenance records. This analysis revealed decreasing STD trends and identified specific calibration-related events, such as an underestimation of approximately 2.43 dB for the Shenzhen radar following calibration in 2023. Consequently, the refined methodology provides a robust framework for ongoing GR network monitoring and offers a validated pathway for authenticating China's Fengyun-3G(FY-3G) satellite precipitation measurement radar(PMR) data.展开更多
China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the qua...China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the quantitative measurement ability of the PMR is critical.China operates more than 250 weather radars over the mainland.Consistency of the spaceborne radar with ground-based radars will enhance precipitation measurement ability,especially over oceans and mountains where observations are sparse.Additionally,the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network.This paper focuses on comparing the PMR onboard the FY-3G satellite with S-band China New Generation Weather Radars(CINRADs).A comparison algorithm between the PMR and CINRADs has been developed,incorporating detailed quality control,attenuation correction,data optimization,spatiotemporal matching,non-uniform beam filling constraint,uniformity constraint,and frequency correction.The matched data in typical months of four seasons were selected to carry out the comparison.The data consistency between the PMR and CINRADs was analyzed.The correlation coefficient is 0.87,the deviation is 0.89 dB,and the standard deviation is 2.50 dB,based on 98226 matching samples.The results show the radar reflectivity of the PMR is quite comparable to that of the CINRADs,demonstrating that the PMR data quality is satisfactory and can be used to verify and correct data consistency among multiple ground-based radars.This work also paves the way for data fusion and joint application of satellite and ground radars in the future.展开更多
Dual-polarization(dual-pol)radar variables provide information about the quantity,type,size,and water content of hydrometeors.Assimilating these dual-pol radar variables into numerical weather prediction models can en...Dual-polarization(dual-pol)radar variables provide information about the quantity,type,size,and water content of hydrometeors.Assimilating these dual-pol radar variables into numerical weather prediction models can enhance forecast accuracy.Observation operators are essential for radar data assimilation.This study focuses on applying a realistic dual-pol radar observation operator to more accurately calculate dual-pol radar variables.Previously reported dual-pol radar observation operators tended to overestimate radar variables near 0℃ in convective precipitation and simulate unrealistic dual-pol radar variables in subfreezing regions.To address this,the improved operator(KNU dual-pol radar observation operator;K-DROP)limits the distribution of mixed-phase hydrometeors,which have both solid and liquid properties,in areas with strong updrafts and downdrafts,improving the overestimation of radar variables near the melting layer.Additionally,by applying the observed snow axis ratio during winter to K-DROP,the issue of differential reflectivity(Z_(DR))being calculated as a constant value in subfreezing regions has been improved.By incorporating the observed maximum radius of hydrometeors into K-DROP,the overestimation of reflectivity(Z_(H))in subfreezing regions,the overestimation of Z_(DR)in warm regions,and the underestimation of specific differential phase(K_(DP))in subfreezing regions and overestimation in warm regions,are improved.Compared to previous operators,the enhanced version reported in the present work produces more realistic dual-pol radar variables.展开更多
Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostation...Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostationary(GEO)weather satellites provide continuous observations with seamless coverage with advanced imager, despite their limited capability to penetrate clouds. Combining satellite and ground-radar observations could exploit the advantages of both techniques, providing tracking capability close to that of ground radar while maintaining full spatial coverage. This study presents a novel method called Multi-dimensional satellite Observation information for Radar Estimation(MORE) to reconstruct radar composite reflectivity(CREF). Deep learning techniques are important components of MORE for estimating CREF from China's Fengyun-4B(FY-4B) GEO satellite observations. Two models are developed: an infraredonly(IR-Single) model available for all times, and a visible-infrared(VIS+IR) model for daytime applications. These models incorporate multi-dimensional satellite observation information, including temporal, spatial, spectral, and viewing angle information, to enhance the accuracy of radar echo reconstruction. Results demonstrate that the VIS+IR model outperforms the IR-Single model, and both models achieves a root-mean-square error(RMSE) of less than 6 dBZ and a coefficient of determination(R~2) of greater than 0.7. The models effectively reconstruct radar echoes, including strong echoes exceeding 50 dBZ, and show good agreement with precipitation data in radar-blind areas. This study offers a valuable solution for severe weather monitoring and tracking in regions lacking ground-based radar observations, and provides a potential tool for enhanced data assimilation in numerical weather prediction(NWP) models.展开更多
This paper addresses weak target detection problem for bistatic radar via a pseudo-spectrum(PS)based track-before-detect(TBD).Generally,PS-TBD estimates target position and velocity by means of pseudo-spectrum constru...This paper addresses weak target detection problem for bistatic radar via a pseudo-spectrum(PS)based track-before-detect(TBD).Generally,PS-TBD estimates target position and velocity by means of pseudo-spectrum construction in the discrete measurement space and accurate energy accumulation in mixed coordinates.However,the grids within the polar sensing region of the receivers in the bistatic radar are not aligned.Traditional PS-TBD can not directly process these measurements.In this paper,a PS-TBD method for bistatic radar is proposed to overcome this problem.Each cell in the measurement space of the receivers is mapped to the aligned Cartesian coordinates and predicted to the integration frame according to the assumed filter velocity.A PS is formulated centered on the predicted Cartesian position.Then the samples of the pseudo-spectra are accumulated to the nearest cell around the predicted Cartesian position.The procedure of the energy integration is derived in detail.Simulation results validate the efficacy of the proposed method in terms of detection accuracy and parameter estimation.展开更多
To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framewor...To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framework integrating Deep Reinforcement Learning(DRL)and Graph Neural Network(GNN)is proposed.This framework models resource allocation as a Partially Observable Markov Game(POMG),designs a weighted reward function to balance radar and communication efficiencies,adopts the Multi-Agent Proximal Policy Optimization(MAPPO)framework,and integrates Graph Convolutional Networks(GCN)and Graph Sample and Aggregate(Graph-SAGE)to optimize information interaction.Simulations show that,compared with traditional methods and pure DRL methods,the proposed framework achieves improvements in performance metrics such as communication success rate,Average Age of Information(AoI),and policy convergence speed,effectively enabling resource management in complex environments.Moreover,the proposed GNN-DRL-based intelligent optimization framework obtains significantly better performance for resource management in multi-agent JRC systems than traditional methods and pure DRL methods.展开更多
In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These j...In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These jamming signals severely degrade radar detection performance.Precise recognition of these unknown and compound jamming signals is critical to enhancing the anti-jamming capabilities and overall reliability of radar systems.To address this challenge,this article proposes a novel open-set compound jamming cognition(OSCJC)method.The proposed method employs a detection-classification dual-network architecture,which not only overcomes the false alarm and misdetection issues of traditional closed-set recognition methods when dealing with unknown jamming but also effectively addresses the performance bottleneck of existing open-set recognition techniques focusing on single jamming scenarios in compound jamming environments.To achieve unknown jamming detection,we first employ a consistency labeling strategy to train the detection network using diverse known jamming samples.This strategy enables the network to acquire highly generalizable jamming features,thereby accurately localizing candidate regions for individual jamming components within compound jamming.Subsequently,we introduce contrastive learning to optimize the classification network,significantly enhancing both intra-class clustering and inter-class separability in the jamming feature space.This method not only improves the recognition accuracy of the classification network for known jamming types but also enhances its sensitivity to unknown jamming types.Simulations and experimental data are used to verify the effectiveness of the proposed OSCJC method.Compared with the state-of-the-art open-set recognition methods,the proposed method demonstrates superior recognition accuracy and enhanced environmental adaptability.展开更多
In this paper,the joint design of transmit and receive beamformers for transmit subaperturing multiple-input-multiple-output(TS-MIMO)radar is investigated,aiming to enhance its low probability of intercept(LPI)capabil...In this paper,the joint design of transmit and receive beamformers for transmit subaperturing multiple-input-multiple-output(TS-MIMO)radar is investigated,aiming to enhance its low probability of intercept(LPI)capability.The main objective is to simultaneously minimize the transmission power,suppress the transmit sidelobe levels,and minimize the probability of intercept,thus bolstering the LPI performance of the radar system while maintaining the desired target detection performance.An alternative optimization method is proposed to jointly optimize the transmit and receive beamformers,yielding an unified LPI optimization framework.Particularly,the proposed iterative algorithm based on the Lagrange duality theory for transmit beamforming is more efficient than the conventional convex optimization method.Numerical experiments highlight the effectiveness of the proposed approach in sidelobe suppression and computational efficiency.展开更多
Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for ...Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.展开更多
Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of ...Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of managing finite transmit and receive antennas and transmit power systematically to enhance detection performance.To tackle the multidimensional resource optimization challenge,we introduce a Cooperative Transmit-Receive Antenna Selection and Power Allocation(CTRSPA)strategy.It employs a perception-action cycle that incorporates uncertain external support information to optimize worst-case detection performance with multiple targets.First,we derive a closed-form expression that incorporates uncertainty for the noncoherent integration squared-law detection probability using the Neyman-Pearson criterion.Subsequently,a joint optimization model for antenna selection and power allocation in CFAR detection is formulated,incorporating practical radar resource constraints.Mathematically,this represents an NPhard problem involving coupled continuous and Boolean variables.We propose a three-stage method—Reformulation,Node Picker,and Convex Power Allocation—that capitalizes on the independent convexity of the optimization model for each variable,ensuring a near-optimal result.Simulations confirm the approach's effectiveness,efficiency,and timeliness,particularly for large-scale radar networks,and reveal the impact of threat levels,system layout,and detection parameters on resource allocation.展开更多
Multi-functional Al-matrix composites with high volume fraction （55%-57%） of SiC particles are produced with the new pressureless infiltration fabrication technology. X-ray detection and microscopic observation disp...Multi-functional Al-matrix composites with high volume fraction （55%-57%） of SiC particles are produced with the new pressureless infiltration fabrication technology. X-ray detection and microscopic observation display the composites which are macroscopically homogeneous without porosity. The investigation further reveals that the SiC/Al composites possess low density （2.94 g/cm^3）, high elastic modulus （220 GPa）, prominent thermal management function as a result of low coefficient of thermal expansion （8 × 10^4 K^-1） and high thermal conductivity （235 W/（m.K）） as well as unique preventability of resonance vibration. By adopting a series of developed techniques, the multi-functional SiC/Al composites have managed to be made into near-net-shape parts. Many kinds of precision components of space-based optomechanical structures and airborne optoelectronic platform have been turned out. Of them, several typical products are being under test in practices.展开更多
To cope with the problem of emitter identification caused by the radar words＇ uncertainty of measured multi-function radar emitters, this paper proposes a new identification method based on stochastic syntax-directed...To cope with the problem of emitter identification caused by the radar words＇ uncertainty of measured multi-function radar emitters, this paper proposes a new identification method based on stochastic syntax-directed translation schema（SSDTS）. This method, which is deduced from the syntactic modeling of multi-function radars, considers the probabilities of radar phrases appearance in different radar modes as well as the probabilities of radar word errors occurrence in different radar phrases. It concludes that the proposed method can not only correct the defective radar words by using the stochastic translation schema, but also identify the real radar phrases and working modes of measured emitters concurrently. Furthermore, a number of simulations are presented to demonstrate the identification capability and adaptability of the SSDTS algorithm.The results show that even under the condition of the defective radar words distorted by noise,the proposed algorithm can infer the phrases, work modes and types of measured emitters correctly.展开更多
Metal-organic frameworks（MOFs） are a unique class of porous crystalline materials that have shown promise for a wide range of applications. MOFs have been explored as a new type of heterogeneous catalytic materials,...Metal-organic frameworks（MOFs） are a unique class of porous crystalline materials that have shown promise for a wide range of applications. MOFs have been explored as a new type of heterogeneous catalytic materials, because of their high surface area, uniform and tunable pores, facile functionalization and incorporation of catalytic active sites. The use of multi-functional sites MOF materials as catalysts for synergistic catalysis and tandem reactions has attracted increasing attention. In this review, we aim to introduce the construction of bi-or multi-functional MOF catalysts with cooperative or cascade functions via post-synthetic modification（PSM）.展开更多
To fulfill the demands for higher quality,efficiency and flexibility in aviation industry,a multi-functional end effector is designed to automate the drilling and riveting processes in assembling carbon fiber reinforc...To fulfill the demands for higher quality,efficiency and flexibility in aviation industry,a multi-functional end effector is designed to automate the drilling and riveting processes in assembling carbon fiber reinforced polymer(CFRP)and aluminum components for a robotic aircraft assembly system.To meet the specific functional requirements for blind rivet installation on CFRP and aluminum materials,additional modules are incorporated on the end effector aside of the basic processing modules for drilling.And all of these processing modules allow for a onestep-drilling-countersinking process,hole inspection,automatic rivet feed,rivet geometry check,sealant application,rivet insertion and installation.Besides,to guarantee the better quality of the hole drilled and joints riveted,several online detection and adjustment measures are applied to this end effector,including the reference detection and perpendicular calibration,which could effectively ensure the positioning precision and perpendicular accuracy as demanded.Finally,the test result shows that this end effector is capable of producing each hole to a positioning precision within ±0.5 mm,aperpendicular accuracy within 0.3°,a diameter tolerance of H8,and a countersink depth tolerance of±0.01 mm.Moreover,it could drill and rivet up to three joints per minute,with acceptable shearing and tensile strength.展开更多
Folate receptor(FR)overexpression occurs in a variety of cancers,including pancreatic cancer.In addition,enhanced macropinocytosis exists in K-Ras mutant pancreatic cancer.Furthermore,the occurrence of intensive desmo...Folate receptor(FR)overexpression occurs in a variety of cancers,including pancreatic cancer.In addition,enhanced macropinocytosis exists in K-Ras mutant pancreatic cancer.Furthermore,the occurrence of intensive desmoplasia causes a hypoxic microenvironment in pancreatic cancer.In this study,a novel FR-directed,macropinocytosis-enhanced,and highly cytotoxic bioconjugate folate(F)-human serum albumin(HSA)-apoprotein of lidamycin(LDP)-active enediyne(AE)derived from lidamycin was designed and prepared.F-HSA-LDP-AE consisted of four moieties:F,HSA,LDP,and AE.F-HSA-LDP presented high binding efficiency with the FR and pancreatic cancer cells.Its uptake in wild-type cells was more extensive than in K-Ras mutant-type cells.By in vivo optical imaging,F-HSA-LDP displayed prominent tumor-specific biodistribution in pancreatic cancer xenograft-bearing mice,showing clear and lasting tumor localization for 360 h.In the MTT assay,F-HSA-LDP-AE demonstrated potent cytotoxicity in three types of pancreatic cancer cell lines.It also induced apoptosis and caused G2/M cell cycle arrest.F-HSALDP-AE markedly suppressed the tumor growth of AsPc-1 pancreatic cancer xenografts in athymic mice.At well-tolerated doses of 0.5 and 1 mg/kg,(i.v.,twice),the inhibition rates were 91.2%and 94.8%,respectively(P<0.01).The results of this study indicate that the F-HSA-LDP multi-functional bioconjugate might be effective for treating K-Ras mutant pancreatic cancer.展开更多
Photonic spin Hall effect(PSHE), as a novel physical effect in light–matter interaction, provides an effective metrological method for characterizing the tiny variation in refractive index(RI). In this work, we propo...Photonic spin Hall effect(PSHE), as a novel physical effect in light–matter interaction, provides an effective metrological method for characterizing the tiny variation in refractive index(RI). In this work, we propose a multi-functional PSHE sensor based on VO_(2), a material that can reveal the phase transition behavior. By applying thermal control, the mutual transformation into different phase states of VO_(2) can be realized, which contributes to the flexible switching between multiple RI sensing tasks. When VO_(2) is insulating, the ultrasensitive detection of glucose concentrations in human blood is achieved. When VO_(2) is in a mixed phase, the structure can be designed to distinguish between the normal cells and cancer cells through no-label and real-time monitoring. When VO_(2) is metallic, the proposed PSHE sensor can act as an RI indicator for gas analytes. Compared with other multi-functional sensing devices with the complex structures, our design consists of only one analyte and two VO_(2) layers, which is very simple and elegant. Therefore, the proposed VO_(2)-based PSHE sensor has outstanding advantages such as small size, high sensitivity, no-label, and real-time detection, providing a new approach for investigating tunable multi-functional sensors.展开更多
We propose a novel and efficient multi-functional optical fiber sensor system based on a dense wavelength division multiplexer(DWDM).This system consists of an optical fiber temperature sensor, an optical fiber strain...We propose a novel and efficient multi-functional optical fiber sensor system based on a dense wavelength division multiplexer(DWDM).This system consists of an optical fiber temperature sensor, an optical fiber strain sensor, and a 48-channel DWDM.This system can monitor temperature and strain changes at the same time.The ranges of these two sensors are from-20℃ to 100℃ and from-1000 με to 2000 με, respectively.The sensitivities of the temperature sensor and strain sensor are 0.03572 nm/℃ and 0.03808 nm/N, respectively.With the aid of a broadband source and spectrometer,different kinds and ranges of parameters in the environment can be monitored by using suitable sensors.展开更多
A compound multi-functional sensor was designed by the study on the on-line testing technology of wood-based panels, and its properties of shape, functions, size, resistance to special environment were studied in deta...A compound multi-functional sensor was designed by the study on the on-line testing technology of wood-based panels, and its properties of shape, functions, size, resistance to special environment were studied in details. The operational principles of different sensors, technical flow of manufacturing, development of software systems of special functions, and the assessments of technical specification were also be introduced. This sensor adopted many new technologies, such as the applications of piezoresistant effect and heat sensitive effect can effectively measure the pressure and temperature, digital signal processing technology was used to extract and treat signals, and resist interference, encapsulation technology was used to keep the normal run of sensor under a harsh environment. Thus, the on-line compound multi-functional temperature/pressure sensor can be applied better to supervise the production of wood-based panels. All technical specifications of the compound multi-functional sensor were tested and the results met the requirements of the equipments.展开更多
基金supported by the central government and guides local funds for science and technology development(2022ZY0109).
文摘The naturally fermented Inner Mongolian cheese’s flavor and nutritional value make it a popular choice among customers.In this work,to create multi-functional peptides that have taste and biological activity,peptidomics and bioinformatics were used to screen flavor peptides from Inner Mongolian cheese and further assess their antioxidant and angiotensin I-converting enzyme(ACE)inhibitory properties.According to sensory data,YH8 and IL7 had detectable bitter tastes with low thresholds of 0.03 and 0.06 mmol/L,respectively.With an umami threshold range of 0.24‒0.81 mmol/L,VQ6,FK13,HP13 and QT14 exhibited a range of flavors dominated by umami,including sweet,bitter,salty,sour and kokumi.Antioxidant activity wise,YH8,VQ6,HP13 and QT14 were well represented.The above-mentioned peptides all had some ACE inhibitory effect.The bitter peptide IL7(IC_(50)=0.08 mmol/L)had the highest level of ACE inhibitory activity,followed by YH8(IC_(50)=0.33 mmol/L).These multi-functional peptides,which have been assessed for bioactive and taste features in Inner Mongolian cheese,may have positive impacts on health and harmonize the cheese’s overall flavor.These results suggest that some flavor peptides produced in fermented foods might be with bioactivities while providing a basis for the exploration and application of multi-functional peptides.
文摘Figure 6(a)in the paper[Chin.Phys.B 33074203(2024)]was incorrect due to editorial oversight.The correct figure is provided.This modification does not affect the result presented in the paper.
基金National Key Research and Development Program of China (2023YFB3905801)。
文摘Accurate calibration of China's new generation ground-based polarimetric radar(GR) network is crucial yet challenging. Although application of the Dual-frequency Precipitation Radar(DPR) of the Global Precipitation Measurement Core Observatory for GR assessment is well-established, current methodologies are inherently limited. Focusing on three GRs in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)—strategically selected for their high overlapping coverage(>65%) and distinct from single GR or less dense coverage studies—this work introduces key refinements by integrating innovative enhancements into the volume-matching method(VMM), reflecting a systematic approach to mitigating potential error sources. Specifically, we integrate: 1) a novel frequency correction method that adapts to DPR-observed precipitation phase and type, replacing assumption-based polynomial fitting;and 2) a precise beam time-difference matching approach(accuracy < 1 s) to minimize temporal mismatch errors, which improves upon coarser time averaging methods. Furthermore, we developed statistically robust, optimized threshold criteria based on systematic sensitivity analyses using 11 quality control factors, including precipitation type, bright band effects, and attenuation correction limitations. These criteria establish an enhanced protocol designed to minimize errors arising from instrumental, frequency, and scanning differences. Application of this enhanced methodology to the GBA GRs(2021–2023) yielded a significantly improved matching accuracy(correlation coefficient, CC: 0.90–0.95;standard deviation,STD: 1.2–1.6 dB). A unique contribution of this work is the quantitative estimation of historical calibration errors and operational stability, which was achieved by linking VMM results with operational GR calibration and maintenance records. This analysis revealed decreasing STD trends and identified specific calibration-related events, such as an underestimation of approximately 2.43 dB for the Shenzhen radar following calibration in 2023. Consequently, the refined methodology provides a robust framework for ongoing GR network monitoring and offers a validated pathway for authenticating China's Fengyun-3G(FY-3G) satellite precipitation measurement radar(PMR) data.
基金jointly supported by the National Natural Science Foundation of China(Grant U2442214)the China Meteorological Administration Youth Innovation Team(Grant No.CMA2024QN10)+1 种基金the National Defense Science and Technology Bureau’s 14th Five-Year Civil Aerospace Preresearch Project(Grant Nos.D030303 and D040204)the International Space Water Cycle Observation Constellation Program(Grant No.183311KYSB20200015).
文摘China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the quantitative measurement ability of the PMR is critical.China operates more than 250 weather radars over the mainland.Consistency of the spaceborne radar with ground-based radars will enhance precipitation measurement ability,especially over oceans and mountains where observations are sparse.Additionally,the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network.This paper focuses on comparing the PMR onboard the FY-3G satellite with S-band China New Generation Weather Radars(CINRADs).A comparison algorithm between the PMR and CINRADs has been developed,incorporating detailed quality control,attenuation correction,data optimization,spatiotemporal matching,non-uniform beam filling constraint,uniformity constraint,and frequency correction.The matched data in typical months of four seasons were selected to carry out the comparison.The data consistency between the PMR and CINRADs was analyzed.The correlation coefficient is 0.87,the deviation is 0.89 dB,and the standard deviation is 2.50 dB,based on 98226 matching samples.The results show the radar reflectivity of the PMR is quite comparable to that of the CINRADs,demonstrating that the PMR data quality is satisfactory and can be used to verify and correct data consistency among multiple ground-based radars.This work also paves the way for data fusion and joint application of satellite and ground radars in the future.
基金supported by the National Research Foundation(NRF)funded by the Korean government(MSIT)(Grant Nos.2022R1A2C1012361,2022R1A6A3A 13073165 and RS-2025-02242970).
文摘Dual-polarization(dual-pol)radar variables provide information about the quantity,type,size,and water content of hydrometeors.Assimilating these dual-pol radar variables into numerical weather prediction models can enhance forecast accuracy.Observation operators are essential for radar data assimilation.This study focuses on applying a realistic dual-pol radar observation operator to more accurately calculate dual-pol radar variables.Previously reported dual-pol radar observation operators tended to overestimate radar variables near 0℃ in convective precipitation and simulate unrealistic dual-pol radar variables in subfreezing regions.To address this,the improved operator(KNU dual-pol radar observation operator;K-DROP)limits the distribution of mixed-phase hydrometeors,which have both solid and liquid properties,in areas with strong updrafts and downdrafts,improving the overestimation of radar variables near the melting layer.Additionally,by applying the observed snow axis ratio during winter to K-DROP,the issue of differential reflectivity(Z_(DR))being calculated as a constant value in subfreezing regions has been improved.By incorporating the observed maximum radius of hydrometeors into K-DROP,the overestimation of reflectivity(Z_(H))in subfreezing regions,the overestimation of Z_(DR)in warm regions,and the underestimation of specific differential phase(K_(DP))in subfreezing regions and overestimation in warm regions,are improved.Compared to previous operators,the enhanced version reported in the present work produces more realistic dual-pol radar variables.
基金supported by the National Natural Science Foundation of China (NSFC) (Grant No.42205044)Feng Yun Application Pioneering Project (FY-APP) Innovation Center for Feng Yun Meteorological Satellite (FYSIC) Special Project (FY-APP-XC-2023.04)the Wuxi University Research Start-up Fund for Recruited Talent。
文摘Ground-based radar is the primary means by which severe storms are monitored and tracked;however, due to limited coverage, important data is often missed over ocean and mountainous areas. On the other hand, geostationary(GEO)weather satellites provide continuous observations with seamless coverage with advanced imager, despite their limited capability to penetrate clouds. Combining satellite and ground-radar observations could exploit the advantages of both techniques, providing tracking capability close to that of ground radar while maintaining full spatial coverage. This study presents a novel method called Multi-dimensional satellite Observation information for Radar Estimation(MORE) to reconstruct radar composite reflectivity(CREF). Deep learning techniques are important components of MORE for estimating CREF from China's Fengyun-4B(FY-4B) GEO satellite observations. Two models are developed: an infraredonly(IR-Single) model available for all times, and a visible-infrared(VIS+IR) model for daytime applications. These models incorporate multi-dimensional satellite observation information, including temporal, spatial, spectral, and viewing angle information, to enhance the accuracy of radar echo reconstruction. Results demonstrate that the VIS+IR model outperforms the IR-Single model, and both models achieves a root-mean-square error(RMSE) of less than 6 dBZ and a coefficient of determination(R~2) of greater than 0.7. The models effectively reconstruct radar echoes, including strong echoes exceeding 50 dBZ, and show good agreement with precipitation data in radar-blind areas. This study offers a valuable solution for severe weather monitoring and tracking in regions lacking ground-based radar observations, and provides a potential tool for enhanced data assimilation in numerical weather prediction(NWP) models.
基金supported by the National Natural Science Foundation of China(62371155)the Heilongjiang Outstanding Youth Science Fund(JQ2022F002)。
文摘This paper addresses weak target detection problem for bistatic radar via a pseudo-spectrum(PS)based track-before-detect(TBD).Generally,PS-TBD estimates target position and velocity by means of pseudo-spectrum construction in the discrete measurement space and accurate energy accumulation in mixed coordinates.However,the grids within the polar sensing region of the receivers in the bistatic radar are not aligned.Traditional PS-TBD can not directly process these measurements.In this paper,a PS-TBD method for bistatic radar is proposed to overcome this problem.Each cell in the measurement space of the receivers is mapped to the aligned Cartesian coordinates and predicted to the integration frame according to the assumed filter velocity.A PS is formulated centered on the predicted Cartesian position.Then the samples of the pseudo-spectra are accumulated to the nearest cell around the predicted Cartesian position.The procedure of the energy integration is derived in detail.Simulation results validate the efficacy of the proposed method in terms of detection accuracy and parameter estimation.
基金funded by Shandong Provincial Natural Science Foundation,grant number ZR2023MF111.
文摘To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framework integrating Deep Reinforcement Learning(DRL)and Graph Neural Network(GNN)is proposed.This framework models resource allocation as a Partially Observable Markov Game(POMG),designs a weighted reward function to balance radar and communication efficiencies,adopts the Multi-Agent Proximal Policy Optimization(MAPPO)framework,and integrates Graph Convolutional Networks(GCN)and Graph Sample and Aggregate(Graph-SAGE)to optimize information interaction.Simulations show that,compared with traditional methods and pure DRL methods,the proposed framework achieves improvements in performance metrics such as communication success rate,Average Age of Information(AoI),and policy convergence speed,effectively enabling resource management in complex environments.Moreover,the proposed GNN-DRL-based intelligent optimization framework obtains significantly better performance for resource management in multi-agent JRC systems than traditional methods and pure DRL methods.
文摘In high-intensity electromagnetic warfare,radar systems are persistently subjected to multi-jammer attacks,including potentially novel unknown jamming types that may emerge exclusively under wartime conditions.These jamming signals severely degrade radar detection performance.Precise recognition of these unknown and compound jamming signals is critical to enhancing the anti-jamming capabilities and overall reliability of radar systems.To address this challenge,this article proposes a novel open-set compound jamming cognition(OSCJC)method.The proposed method employs a detection-classification dual-network architecture,which not only overcomes the false alarm and misdetection issues of traditional closed-set recognition methods when dealing with unknown jamming but also effectively addresses the performance bottleneck of existing open-set recognition techniques focusing on single jamming scenarios in compound jamming environments.To achieve unknown jamming detection,we first employ a consistency labeling strategy to train the detection network using diverse known jamming samples.This strategy enables the network to acquire highly generalizable jamming features,thereby accurately localizing candidate regions for individual jamming components within compound jamming.Subsequently,we introduce contrastive learning to optimize the classification network,significantly enhancing both intra-class clustering and inter-class separability in the jamming feature space.This method not only improves the recognition accuracy of the classification network for known jamming types but also enhances its sensitivity to unknown jamming types.Simulations and experimental data are used to verify the effectiveness of the proposed OSCJC method.Compared with the state-of-the-art open-set recognition methods,the proposed method demonstrates superior recognition accuracy and enhanced environmental adaptability.
基金supported by the National Natural Science Foundation of China(62271247)the Natural Science Foundation of Jiangsu Province(BK20240181)+4 种基金the Dreams Foundation of Jianghuai Advance Technology Center(2023-ZM01D001)the National Aerospace Science Foundation of China(20220055052001)the Qing Lan Project of Jiangsu Provincethe Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronauticsthe Key Laboratory of Radar Imaging and Microwave Photonics(Nanjing University of Aeronautics and Astronautics),Ministry of Education。
文摘In this paper,the joint design of transmit and receive beamformers for transmit subaperturing multiple-input-multiple-output(TS-MIMO)radar is investigated,aiming to enhance its low probability of intercept(LPI)capability.The main objective is to simultaneously minimize the transmission power,suppress the transmit sidelobe levels,and minimize the probability of intercept,thus bolstering the LPI performance of the radar system while maintaining the desired target detection performance.An alternative optimization method is proposed to jointly optimize the transmit and receive beamformers,yielding an unified LPI optimization framework.Particularly,the proposed iterative algorithm based on the Lagrange duality theory for transmit beamforming is more efficient than the conventional convex optimization method.Numerical experiments highlight the effectiveness of the proposed approach in sidelobe suppression and computational efficiency.
基金National Natural Science Foundation of China under Grant 62571248 and Grant 62201266Key Laboratory of Intelligent Space TTC&O(Space Engineering University),Ministry of Education under Grant CYK2025-01-12。
文摘Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.
基金supported by the National Natural Science Foundation of China(Nos.62071482 and 62471348)the Shaanxi Association of Science and Technology Youth Talent Support Program Project,China(No.20230137)+1 种基金the Innovative Talents Cultivate Program for Technology Innovation Team of Shaanxi Province,China(No.2024RS-CXTD-08)the Youth Innovation Team of Shaanxi Universities,China。
文摘Within the domain of Intelligent Group Systems(IGSs),this paper develops a resourceaware multitarget Constant False Alarm Rate(CFAR)detection framework for multisite MIMO radar systems.It underscores the necessity of managing finite transmit and receive antennas and transmit power systematically to enhance detection performance.To tackle the multidimensional resource optimization challenge,we introduce a Cooperative Transmit-Receive Antenna Selection and Power Allocation(CTRSPA)strategy.It employs a perception-action cycle that incorporates uncertain external support information to optimize worst-case detection performance with multiple targets.First,we derive a closed-form expression that incorporates uncertainty for the noncoherent integration squared-law detection probability using the Neyman-Pearson criterion.Subsequently,a joint optimization model for antenna selection and power allocation in CFAR detection is formulated,incorporating practical radar resource constraints.Mathematically,this represents an NPhard problem involving coupled continuous and Boolean variables.We propose a three-stage method—Reformulation,Node Picker,and Convex Power Allocation—that capitalizes on the independent convexity of the optimization model for each variable,ensuring a near-optimal result.Simulations confirm the approach's effectiveness,efficiency,and timeliness,particularly for large-scale radar networks,and reveal the impact of threat levels,system layout,and detection parameters on resource allocation.
基金Foundation items： High-technology Research and Development Programme of China （2007AA03Z544） Aeronautical Science Foundation of China （20075221001）
文摘Multi-functional Al-matrix composites with high volume fraction （55%-57%） of SiC particles are produced with the new pressureless infiltration fabrication technology. X-ray detection and microscopic observation display the composites which are macroscopically homogeneous without porosity. The investigation further reveals that the SiC/Al composites possess low density （2.94 g/cm^3）, high elastic modulus （220 GPa）, prominent thermal management function as a result of low coefficient of thermal expansion （8 × 10^4 K^-1） and high thermal conductivity （235 W/（m.K）） as well as unique preventability of resonance vibration. By adopting a series of developed techniques, the multi-functional SiC/Al composites have managed to be made into near-net-shape parts. Many kinds of precision components of space-based optomechanical structures and airborne optoelectronic platform have been turned out. Of them, several typical products are being under test in practices.
基金supported by the National Natural Science Foundation of China (No. 61002026)
文摘To cope with the problem of emitter identification caused by the radar words＇ uncertainty of measured multi-function radar emitters, this paper proposes a new identification method based on stochastic syntax-directed translation schema（SSDTS）. This method, which is deduced from the syntactic modeling of multi-function radars, considers the probabilities of radar phrases appearance in different radar modes as well as the probabilities of radar word errors occurrence in different radar phrases. It concludes that the proposed method can not only correct the defective radar words by using the stochastic translation schema, but also identify the real radar phrases and working modes of measured emitters concurrently. Furthermore, a number of simulations are presented to demonstrate the identification capability and adaptability of the SSDTS algorithm.The results show that even under the condition of the defective radar words distorted by noise,the proposed algorithm can infer the phrases, work modes and types of measured emitters correctly.
基金supported by the National Natural Science Foundation of China (Nos. 21371069 and 21621001)
文摘Metal-organic frameworks（MOFs） are a unique class of porous crystalline materials that have shown promise for a wide range of applications. MOFs have been explored as a new type of heterogeneous catalytic materials, because of their high surface area, uniform and tunable pores, facile functionalization and incorporation of catalytic active sites. The use of multi-functional sites MOF materials as catalysts for synergistic catalysis and tandem reactions has attracted increasing attention. In this review, we aim to introduce the construction of bi-or multi-functional MOF catalysts with cooperative or cascade functions via post-synthetic modification（PSM）.
基金supported by the National Natural Science Foundations of China(Nos.5157051626,51475225)
文摘To fulfill the demands for higher quality,efficiency and flexibility in aviation industry,a multi-functional end effector is designed to automate the drilling and riveting processes in assembling carbon fiber reinforced polymer(CFRP)and aluminum components for a robotic aircraft assembly system.To meet the specific functional requirements for blind rivet installation on CFRP and aluminum materials,additional modules are incorporated on the end effector aside of the basic processing modules for drilling.And all of these processing modules allow for a onestep-drilling-countersinking process,hole inspection,automatic rivet feed,rivet geometry check,sealant application,rivet insertion and installation.Besides,to guarantee the better quality of the hole drilled and joints riveted,several online detection and adjustment measures are applied to this end effector,including the reference detection and perpendicular calibration,which could effectively ensure the positioning precision and perpendicular accuracy as demanded.Finally,the test result shows that this end effector is capable of producing each hole to a positioning precision within ±0.5 mm,aperpendicular accuracy within 0.3°,a diameter tolerance of H8,and a countersink depth tolerance of±0.01 mm.Moreover,it could drill and rivet up to three joints per minute,with acceptable shearing and tensile strength.
基金supported by grants from CAMS Innovation Fund for Medical Sciences(Grant No.:2021-I2M-1-026)Scientific Research Project of Tianjin Education Commission(Grant No.:2020KJ140)Tianjin Health Research Project(Grant No.:KJ20017)。
文摘Folate receptor(FR)overexpression occurs in a variety of cancers,including pancreatic cancer.In addition,enhanced macropinocytosis exists in K-Ras mutant pancreatic cancer.Furthermore,the occurrence of intensive desmoplasia causes a hypoxic microenvironment in pancreatic cancer.In this study,a novel FR-directed,macropinocytosis-enhanced,and highly cytotoxic bioconjugate folate(F)-human serum albumin(HSA)-apoprotein of lidamycin(LDP)-active enediyne(AE)derived from lidamycin was designed and prepared.F-HSA-LDP-AE consisted of four moieties:F,HSA,LDP,and AE.F-HSA-LDP presented high binding efficiency with the FR and pancreatic cancer cells.Its uptake in wild-type cells was more extensive than in K-Ras mutant-type cells.By in vivo optical imaging,F-HSA-LDP displayed prominent tumor-specific biodistribution in pancreatic cancer xenograft-bearing mice,showing clear and lasting tumor localization for 360 h.In the MTT assay,F-HSA-LDP-AE demonstrated potent cytotoxicity in three types of pancreatic cancer cell lines.It also induced apoptosis and caused G2/M cell cycle arrest.F-HSALDP-AE markedly suppressed the tumor growth of AsPc-1 pancreatic cancer xenografts in athymic mice.At well-tolerated doses of 0.5 and 1 mg/kg,(i.v.,twice),the inhibition rates were 91.2%and 94.8%,respectively(P<0.01).The results of this study indicate that the F-HSA-LDP multi-functional bioconjugate might be effective for treating K-Ras mutant pancreatic cancer.
基金Project supported by the National Natural Science Foundation of China(Grant No.NSFC 12175107)the Natural Science Foundation of Nanjing Vocational University of Industry Technology,China(Grant No.YK22-02-08)+3 种基金the Qing Lan Project of Jiangsu Province,Chinathe Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(Grant No.KYCX23_0964)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20230347)the Fund from the Research Center of Industrial Perception and Intelligent Manufacturing Equipment Engineering of Jiangsu Province,China(Grant No.ZK21-05-09)。
文摘Photonic spin Hall effect(PSHE), as a novel physical effect in light–matter interaction, provides an effective metrological method for characterizing the tiny variation in refractive index(RI). In this work, we propose a multi-functional PSHE sensor based on VO_(2), a material that can reveal the phase transition behavior. By applying thermal control, the mutual transformation into different phase states of VO_(2) can be realized, which contributes to the flexible switching between multiple RI sensing tasks. When VO_(2) is insulating, the ultrasensitive detection of glucose concentrations in human blood is achieved. When VO_(2) is in a mixed phase, the structure can be designed to distinguish between the normal cells and cancer cells through no-label and real-time monitoring. When VO_(2) is metallic, the proposed PSHE sensor can act as an RI indicator for gas analytes. Compared with other multi-functional sensing devices with the complex structures, our design consists of only one analyte and two VO_(2) layers, which is very simple and elegant. Therefore, the proposed VO_(2)-based PSHE sensor has outstanding advantages such as small size, high sensitivity, no-label, and real-time detection, providing a new approach for investigating tunable multi-functional sensors.
基金Project supported by the National Key Research and Development Program of China(Grant No.2016YFB0402504)the National Natural Science Foundation of China(Grant Nos.61875069 and 61575076)+1 种基金Hong Kong Scholars Program,China(Grant No.XJ2016026)the Science and Technology Development Plan of Jilin Province,China(Grant Nos.20190302010GX and 20160520091JH)
文摘We propose a novel and efficient multi-functional optical fiber sensor system based on a dense wavelength division multiplexer(DWDM).This system consists of an optical fiber temperature sensor, an optical fiber strain sensor, and a 48-channel DWDM.This system can monitor temperature and strain changes at the same time.The ranges of these two sensors are from-20℃ to 100℃ and from-1000 με to 2000 με, respectively.The sensitivities of the temperature sensor and strain sensor are 0.03572 nm/℃ and 0.03808 nm/N, respectively.With the aid of a broadband source and spectrometer,different kinds and ranges of parameters in the environment can be monitored by using suitable sensors.
基金This project was supported by China Postdoctoral Science Funds, Jiangsu Planned Projects for Postdoctoral Research Funds and Northeast Forestry University Research Funds.
文摘A compound multi-functional sensor was designed by the study on the on-line testing technology of wood-based panels, and its properties of shape, functions, size, resistance to special environment were studied in details. The operational principles of different sensors, technical flow of manufacturing, development of software systems of special functions, and the assessments of technical specification were also be introduced. This sensor adopted many new technologies, such as the applications of piezoresistant effect and heat sensitive effect can effectively measure the pressure and temperature, digital signal processing technology was used to extract and treat signals, and resist interference, encapsulation technology was used to keep the normal run of sensor under a harsh environment. Thus, the on-line compound multi-functional temperature/pressure sensor can be applied better to supervise the production of wood-based panels. All technical specifications of the compound multi-functional sensor were tested and the results met the requirements of the equipments.
