In response to the downlink synchronization requirements of the user equipment(UE)or third-party radio equipment in fifth-generation(5G)mobile communication systems,a synchronization algorithm of primary synchroni-zat...In response to the downlink synchronization requirements of the user equipment(UE)or third-party radio equipment in fifth-generation(5G)mobile communication systems,a synchronization algorithm of primary synchroni-zation signal(PSS)was designed and developed in the 5G system based on block cross-correlation.According to the new characteristics of the 5G synchronization channel and broadcast channel,starting from the traditional downlink synchronization algorithm of long-term evolution(LTE),the detection performance of the algorithm under a low signal-to-noise ratio(SNR)is improved by introducing an incoherent accumulation,and the new scheme of joint coarse frequency offset estimation is used to improve the frequency offset estimation performance.Finally,the performance of the proposed synchronization algorithm is verified by conducting a simulation on a 5G downlink simulation platform based on MATLAB software.Simulation results show that the improved downlink synchronization algorithm has stable performance in the tapped delay line-C(TDL-C)and additive white Gaussian noise(AWGN)channels with large frequency deviation and low SNR.展开更多
To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ens...To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.展开更多
The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured o...The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured one from the database of the collected spectra by employing the cross-correlation operation,subsequently deriving the predicted value via weighted calculation.As the algorithm uses the complete information in the measured raw spectrum,more accurate results and larger measurement range can be obtained.Additionally,the improved cross-correlation algorithm also has the potential to improve the measurement speed compared to current standards due to the possibility for the collection using low sampling rate.This work presents an important algorithm towards a simpler,faster way to improve the demodulation performance of VE-OFS.展开更多
Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with ot...Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.展开更多
Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ult...Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ultrasonic temperature measurement.To this end,this paper proposes an ultrasonic temperature measurement method that combines YOLOv11 target detection with energy-type weighted cross-correlation algorithm.The YOLOv11 model is utilized to conduct target detection and key area positioning on the ultrasonic signal waveform diagram,automatically identifying characteristic waveforms such as node waves and end face waves,and achieving adaptive extraction of the effective signal interval.Further introduce the energy-based weighted cross-correlation algorithm.Based on the signal energy distribution,the cross-correlation results are weighted and processed to enhance the main wave response and suppress noise interference.Experiments show that the YOLOv11 model has high detection accuracy(Precision=0.987,Recall=0.958,mAP@50=0.988);The proposed method maintains the stability of time delay estimation under strong noise and high temperature(>1200℃),with the average time delay error reduced by approximately 35%to 50%compared to traditional algorithms.This verifies its high robustness and temperature measurement accuracy in complex environments,and it has a promising engineering application prospect.展开更多
In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and...In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and G(z)=∑^(N)_(i)=1 A_(−i)z^(i),A_(i)ae culants.展开更多
When patients initially present with atrial fibrillation along with an enlarged heart and heart failure, followed by atrioventricular block, it's essential to consider genetic factors.^([1])Genetic testing can off...When patients initially present with atrial fibrillation along with an enlarged heart and heart failure, followed by atrioventricular block, it's essential to consider genetic factors.^([1])Genetic testing can offer crucial diagnostic evidence, aiding in prognosis assessment and the adoption of appropriate treatment strategies.展开更多
The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytot...The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytotoxicity.These limitations have catalyzed the development of intelligent stimuli-responsive block copolymers-based bioimaging agents,which was engineered to dynamically respond to endogenous biochemical cues(e.g.,p H gradients,redox potential,enzyme activity,hypoxia environment) or exogenous physical triggers(e.g.,photoirradiation,thermal gradients,ultrasound(US)/magnetic stimuli).Through spatiotemporally controlled structural transformations,stimuli-responsive block copolymers enable precise contrast targeting,activatable signal amplification,and theranostic integration,thereby substantially enhancing signal-to-noise ratios of bioimaging and diagnostic specificity.Hence,this mini-review systematically examines molecular engineering principles for designing p H-,redox-,enzyme-,light-,thermo-,and US/magnetic-responsive polymers,with emphasis on structure-property relationships governing imaging performance modulation.Furthermore,we critically analyze emerging strategies for optical imaging,US synergies,and magnetic resonance imaging(MRI).Multimodal bioimaging has also been elaborated,which could overcome the inherent trade-offs between resolution,penetration depth,and functional specificity in single-modal approaches.By elucidating mechanistic insights and translational challenges,this mini-review aims to establish a design framework of stimuli-responsive block copolymersbased for high fidelity bioimaging agents and accelerate their clinical translation in precise diagnosis and therapy.展开更多
Switchable polymerization is emerging as a powerful tool to construct block copolymers directly from mixtures of monomers.However,current achievements typically iterate between two polymerization cycles to afford prod...Switchable polymerization is emerging as a powerful tool to construct block copolymers directly from mixtures of monomers.However,current achievements typically iterate between two polymerization cycles to afford products with fixed sequences and compositions.Herein,we report the triethylborane/1,8-diazabicyclo[5.4.0]undec-7-ene(Et_3B/DBU)pair-mediated four-component switchable polymerization of propylene oxide(PO),CO_(2),phthalic anhydride(PA),and racemic lactide(rac-LA),which enables the on-demand synthesis of four different block copolymers,i.e.,poly(propylene phthalate)-b-polylactide(PPE-b-PLA),PPE-b-PLA-b-poly(propylene carbonate)(PPC),PPE-b-PPC-b-PLA,and PPE-b-PPCb-poly(propylene oxide)(PPO),through rationally modulating the Lewis pair(LP)ratio.Core to this protocol is that increasing the loading of Et_(3)B accelerates the ring-opening of PO while impeding the reactivity of rac-LA,thus allowing for fine-tuning of the thermodynamic and kinetic of the switchable polymerization.Therefore,the four polymerization cycles involving PO/PA ring-opening copolymerization(ROCOP),PO/CO_(2) ROCOP,rac-LA ring-opening polymerization(ROP),and PO ROP can be connected and discriminated in precisely programmed manners.展开更多
This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material u...This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material usage,and costs.In the first stage,an extended key block analysis identifies key blocks and key block groups,accounting for progressive failure and force interactions.The second stage uses AI algorithms to optimise rockbolting design,balancing stability,cost,and material use.The most efficient algorithms include the multi-objective tree-structured Parzen estimator(MOTPE)and non-dominated sorting genetic algorithms(NSGA-II and NSGA-III).Applied to the Larvik rock slope,the optimised solution uses 18 pre-tensioned cablebolts,providing 13.2 MN of active force and achieving a factor of safety of 1.31 while reducing the average anchorage length by approximately 16%compared to traditional design.The AI-assisted approach also reduces computation time by over 90%compared to Quasi-Monte Carlo(QMC)methods,demonstrating its efficiency for small-scale civil engineering projects and large-scale mining operations.The developed tool is practical,compatible with Building Information Modelling(BIM),and ready for engineering implementation,supporting sustainable and cost-effective rock slope stabilisation.While the method is largely automated,professional judgement remains crucial for verifying ground conditions and selecting the final solution.Future work will focus on integrating data uncertainties,addressing complex block deformation mechanisms,refining optimisation objectives,and improving the performance of multi-objective optimisation for slope rockboling applications to further enhance the method's versatility.展开更多
Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphi...Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphite.This study utilizes the porous“defect advantage”of a cathode carbon block matrix to prepare silicon-doped and asphalt-coated detoxified and purified waste graphitization cathode carbon blocks for use as high-performance silicon/carbon composite anode materials.The results show that the uniformly silicondoped silicon/carbon composite material features a unique amorphous carbon-encapsulated“locked silicon”structure,which effectively addresses issues such as cathode volume expansion,excessive growth of the solid electrolyte interphase(SEI)film,and poor electrical contact between active materials.Consequently,electrochemical performance is enhanced.After assembly in a half-cell,the PSCC/10%Si@C(purified waste graphitization cathode carbon/10%Si@C)material exhibits optimal electrochemical stability,with an initial charging specific capacity of 514.5 mAh/g at 0.1 C(1 C=170 mA/g)and a capacity retention rate of 95.1%after 100 cycles.At a charge rate of 2.0 C,a specific capacity of 216.9 mAh/g is achieved.This technology provides a new pathway for the economical and high-value utilization of waste cathode carbon blocks and the development of low-cost,high-performance anode materials.展开更多
Star-shaped six-arm polymers with hexaaza[2_(6)]orthoparacyclophane core and arms of block copolymers of poly-2-ethyl-5,6-dihydrooxazine with poly-2-isopropyl-5,6-dihydrooxazine were synthesized successfully using cat...Star-shaped six-arm polymers with hexaaza[2_(6)]orthoparacyclophane core and arms of block copolymers of poly-2-ethyl-5,6-dihydrooxazine with poly-2-isopropyl-5,6-dihydrooxazine were synthesized successfully using cationic ring-opening polymerization.The ratio of blocks,the order of their attachment to the core,and arm length were varied.Conformation of synthesized stars was determined by methods of molecular hydrodynamics and optics.It has been shown that star-shaped molecules were characterized by high intramolecular density,and the arm folding increased with their lengthening.The influence of the structure of block copolymers and their molar mass on the critical micelle concentration has been established.Complexes of synthesized star-shaped block copolymers with curcumin were obtained and the efficient binding of curcumin to polymer molecules was demonstrated.The behavior of the aqueous solutions of the prepared polymer stars and their complexes with curcumin was investigated by light scattering and turbidimetry methods.The influence of the structure and molar mass of star polymers on their thermoresponsiveness and the phase separation temperatures in aqueous solutions was analyzed.A slight increase in the phase separation temperature was found on passage from polymer solutions to solutions of polymer complexes with hydrophobic curcumin.展开更多
Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time se...Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.展开更多
In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(...In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(RSCCT)for BOC(kn,n)signals is proposed.In this paper,the principle of signal decomposition is combined with the traditional acquisition algorithm structure,and then based on the method of reconstructing the correlation function.The method firstly gets the sub-pseudorandom noise(PRN)code by decomposing the local PRN code,then uses BOC(kn,n)and the sub-PRN code cross-correlation to get the sub cross-correlation function.Finally,the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed.The simulation shows that RSCCT can completely eliminate the side peaks of BOC(kn,n)group signals while maintaining the narrow correlation of BOC,and its computational complexity is equivalent to sub carrier phase cancellation(SCPC)and autocorrelation side-peak cancellation technique(ASPeCT),and it reduces the computational complexity relative to BPSK-like.For BOC(n,n),the acquisition sensitivity of RSCCT is 3.25 dB,0.81 dB and 0.25 dB higher than binary phase shift keying(BPSK)-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.91,3.0 and 3.7 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.For BOC(2n,n),the acquisition sensitivity of RSCCT is 5.5 dB,1.25 dB and 2.69 dB higher than BPSK-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.02,1.68 and 2.12 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.展开更多
This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then clou...This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.展开更多
Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven method...Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.展开更多
In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads o...In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.展开更多
The algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an e...The algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an effective algorithm for particle identification from consecutive images, the accurate velocity vector field can be obtained. The real velocity field in a valve chamber was measured by BICC in this study. From the full-field velocity information, the pressure and vorticity fields were also extracted by post-processing. (Edited author abstract) 6 Refs.展开更多
The amount of seismological data is rapidly increasing with accumulating observational time and increasing number of stations, requiring modern technique to provide adequate computing power. In present study, we propo...The amount of seismological data is rapidly increasing with accumulating observational time and increasing number of stations, requiring modern technique to provide adequate computing power. In present study, we proposed a framework to calculate large-scale noise crosscorrelation functions(NCFs) using public cloud service from ALIYUN. The entire computation is factorized into small pieces which are performed parallelly on specified number of virtual servers provided by the cloud. Using data from most seismic stations in China, five NCF databases are built. The results show that, comparing to the time cost using a single server, the entire time can be reduced over two orders of magnitude depending number of evoked virtual servers. This could reduce computation time from months to less than 12 hours. Based on obtained massive NCFs, the global body waves are retrieved through array interferometry and agree well with those from earthquakes. This leads to a solution to process massive seismic dataset within an affordable time and is applicable to other large-scale computing in seismological researches.展开更多
基金The Social Development Projects of Jiangsu Science and Technology Department(No.BE2018704).
文摘In response to the downlink synchronization requirements of the user equipment(UE)or third-party radio equipment in fifth-generation(5G)mobile communication systems,a synchronization algorithm of primary synchroni-zation signal(PSS)was designed and developed in the 5G system based on block cross-correlation.According to the new characteristics of the 5G synchronization channel and broadcast channel,starting from the traditional downlink synchronization algorithm of long-term evolution(LTE),the detection performance of the algorithm under a low signal-to-noise ratio(SNR)is improved by introducing an incoherent accumulation,and the new scheme of joint coarse frequency offset estimation is used to improve the frequency offset estimation performance.Finally,the performance of the proposed synchronization algorithm is verified by conducting a simulation on a 5G downlink simulation platform based on MATLAB software.Simulation results show that the improved downlink synchronization algorithm has stable performance in the tapped delay line-C(TDL-C)and additive white Gaussian noise(AWGN)channels with large frequency deviation and low SNR.
基金supported by National Natural Science Foundation of China(No.61973234)Tianjin Science and Technology Plan Project(No.22YDTPJC00090)。
文摘To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.
文摘The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured one from the database of the collected spectra by employing the cross-correlation operation,subsequently deriving the predicted value via weighted calculation.As the algorithm uses the complete information in the measured raw spectrum,more accurate results and larger measurement range can be obtained.Additionally,the improved cross-correlation algorithm also has the potential to improve the measurement speed compared to current standards due to the possibility for the collection using low sampling rate.This work presents an important algorithm towards a simpler,faster way to improve the demodulation performance of VE-OFS.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 11875042 and 11505114)the Shanghai Project for Construction of Top Disciplines (Grant No. USST-SYS-01)。
文摘Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.
文摘Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ultrasonic temperature measurement.To this end,this paper proposes an ultrasonic temperature measurement method that combines YOLOv11 target detection with energy-type weighted cross-correlation algorithm.The YOLOv11 model is utilized to conduct target detection and key area positioning on the ultrasonic signal waveform diagram,automatically identifying characteristic waveforms such as node waves and end face waves,and achieving adaptive extraction of the effective signal interval.Further introduce the energy-based weighted cross-correlation algorithm.Based on the signal energy distribution,the cross-correlation results are weighted and processed to enhance the main wave response and suppress noise interference.Experiments show that the YOLOv11 model has high detection accuracy(Precision=0.987,Recall=0.958,mAP@50=0.988);The proposed method maintains the stability of time delay estimation under strong noise and high temperature(>1200℃),with the average time delay error reduced by approximately 35%to 50%compared to traditional algorithms.This verifies its high robustness and temperature measurement accuracy in complex environments,and it has a promising engineering application prospect.
文摘In this paper,we present a necessary and sufficient condition for hyponormal block Toeplitz operators T on the vector-valued weighted Bergman space with symbolsΦ(z)=G^(*)(z)+F(z),where F(z)=∑^(N)_(i)=1 A_(i)z^(i)and G(z)=∑^(N)_(i)=1 A_(−i)z^(i),A_(i)ae culants.
基金Military Healthcare Special Scientific Research Project(25BJZ31, awarded to SHI XM)。
文摘When patients initially present with atrial fibrillation along with an enlarged heart and heart failure, followed by atrioventricular block, it's essential to consider genetic factors.^([1])Genetic testing can offer crucial diagnostic evidence, aiding in prognosis assessment and the adoption of appropriate treatment strategies.
基金supported by the National Natural Science Foundation of China (Nos.22208218,22078196,and 22278268)the Natural Science Foundation of Shanghai (No.22ZR1460400)Collaborative Innovation Center of Fragrance Flavour and Cosmetics,and Collaborative Innovation Project of Shanghai Institute of Technology (No.XTCX2023-07)。
文摘The diagnostic efficacy of contemporary bioimaging technologies remains constrained by inherent limitations of conventional imaging agents,including suboptimal sensitivity,off-target biodistribution,and inherent cytotoxicity.These limitations have catalyzed the development of intelligent stimuli-responsive block copolymers-based bioimaging agents,which was engineered to dynamically respond to endogenous biochemical cues(e.g.,p H gradients,redox potential,enzyme activity,hypoxia environment) or exogenous physical triggers(e.g.,photoirradiation,thermal gradients,ultrasound(US)/magnetic stimuli).Through spatiotemporally controlled structural transformations,stimuli-responsive block copolymers enable precise contrast targeting,activatable signal amplification,and theranostic integration,thereby substantially enhancing signal-to-noise ratios of bioimaging and diagnostic specificity.Hence,this mini-review systematically examines molecular engineering principles for designing p H-,redox-,enzyme-,light-,thermo-,and US/magnetic-responsive polymers,with emphasis on structure-property relationships governing imaging performance modulation.Furthermore,we critically analyze emerging strategies for optical imaging,US synergies,and magnetic resonance imaging(MRI).Multimodal bioimaging has also been elaborated,which could overcome the inherent trade-offs between resolution,penetration depth,and functional specificity in single-modal approaches.By elucidating mechanistic insights and translational challenges,this mini-review aims to establish a design framework of stimuli-responsive block copolymersbased for high fidelity bioimaging agents and accelerate their clinical translation in precise diagnosis and therapy.
基金financially supported by National Key R&D Program Young Scientists Project(No.2023YFC3903100)the National Natural Science Foundation of China(No.22322503)analytical and testing assistance from the Analysis and Testing Center of HUST。
文摘Switchable polymerization is emerging as a powerful tool to construct block copolymers directly from mixtures of monomers.However,current achievements typically iterate between two polymerization cycles to afford products with fixed sequences and compositions.Herein,we report the triethylborane/1,8-diazabicyclo[5.4.0]undec-7-ene(Et_3B/DBU)pair-mediated four-component switchable polymerization of propylene oxide(PO),CO_(2),phthalic anhydride(PA),and racemic lactide(rac-LA),which enables the on-demand synthesis of four different block copolymers,i.e.,poly(propylene phthalate)-b-polylactide(PPE-b-PLA),PPE-b-PLA-b-poly(propylene carbonate)(PPC),PPE-b-PPC-b-PLA,and PPE-b-PPCb-poly(propylene oxide)(PPO),through rationally modulating the Lewis pair(LP)ratio.Core to this protocol is that increasing the loading of Et_(3)B accelerates the ring-opening of PO while impeding the reactivity of rac-LA,thus allowing for fine-tuning of the thermodynamic and kinetic of the switchable polymerization.Therefore,the four polymerization cycles involving PO/PA ring-opening copolymerization(ROCOP),PO/CO_(2) ROCOP,rac-LA ring-opening polymerization(ROP),and PO ROP can be connected and discriminated in precisely programmed manners.
基金support from Research Council of Norway via STIPINST PhD grant(Grant No.323307),Bever Control AS,and Bane NOR.
文摘This paper presents a novel artificial intelligence(AI)-assisted two-stage method for optimising rock slope stability by integrating advanced 3D modelling with rock support design,aiming at minimising risks,material usage,and costs.In the first stage,an extended key block analysis identifies key blocks and key block groups,accounting for progressive failure and force interactions.The second stage uses AI algorithms to optimise rockbolting design,balancing stability,cost,and material use.The most efficient algorithms include the multi-objective tree-structured Parzen estimator(MOTPE)and non-dominated sorting genetic algorithms(NSGA-II and NSGA-III).Applied to the Larvik rock slope,the optimised solution uses 18 pre-tensioned cablebolts,providing 13.2 MN of active force and achieving a factor of safety of 1.31 while reducing the average anchorage length by approximately 16%compared to traditional design.The AI-assisted approach also reduces computation time by over 90%compared to Quasi-Monte Carlo(QMC)methods,demonstrating its efficiency for small-scale civil engineering projects and large-scale mining operations.The developed tool is practical,compatible with Building Information Modelling(BIM),and ready for engineering implementation,supporting sustainable and cost-effective rock slope stabilisation.While the method is largely automated,professional judgement remains crucial for verifying ground conditions and selecting the final solution.Future work will focus on integrating data uncertainties,addressing complex block deformation mechanisms,refining optimisation objectives,and improving the performance of multi-objective optimisation for slope rockboling applications to further enhance the method's versatility.
基金supported by the National Natural Science Foundation of China(No.52274346).
文摘Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphite.This study utilizes the porous“defect advantage”of a cathode carbon block matrix to prepare silicon-doped and asphalt-coated detoxified and purified waste graphitization cathode carbon blocks for use as high-performance silicon/carbon composite anode materials.The results show that the uniformly silicondoped silicon/carbon composite material features a unique amorphous carbon-encapsulated“locked silicon”structure,which effectively addresses issues such as cathode volume expansion,excessive growth of the solid electrolyte interphase(SEI)film,and poor electrical contact between active materials.Consequently,electrochemical performance is enhanced.After assembly in a half-cell,the PSCC/10%Si@C(purified waste graphitization cathode carbon/10%Si@C)material exhibits optimal electrochemical stability,with an initial charging specific capacity of 514.5 mAh/g at 0.1 C(1 C=170 mA/g)and a capacity retention rate of 95.1%after 100 cycles.At a charge rate of 2.0 C,a specific capacity of 216.9 mAh/g is achieved.This technology provides a new pathway for the economical and high-value utilization of waste cathode carbon blocks and the development of low-cost,high-performance anode materials.
基金financially supported by the Russian Science Foundation(No.23-13-00205)。
文摘Star-shaped six-arm polymers with hexaaza[2_(6)]orthoparacyclophane core and arms of block copolymers of poly-2-ethyl-5,6-dihydrooxazine with poly-2-isopropyl-5,6-dihydrooxazine were synthesized successfully using cationic ring-opening polymerization.The ratio of blocks,the order of their attachment to the core,and arm length were varied.Conformation of synthesized stars was determined by methods of molecular hydrodynamics and optics.It has been shown that star-shaped molecules were characterized by high intramolecular density,and the arm folding increased with their lengthening.The influence of the structure of block copolymers and their molar mass on the critical micelle concentration has been established.Complexes of synthesized star-shaped block copolymers with curcumin were obtained and the efficient binding of curcumin to polymer molecules was demonstrated.The behavior of the aqueous solutions of the prepared polymer stars and their complexes with curcumin was investigated by light scattering and turbidimetry methods.The influence of the structure and molar mass of star polymers on their thermoresponsiveness and the phase separation temperatures in aqueous solutions was analyzed.A slight increase in the phase separation temperature was found on passage from polymer solutions to solutions of polymer complexes with hydrophobic curcumin.
基金Projects(61271321,61573253,61401303)supported by the National Natural Science Foundation of ChinaProject(14ZCZDSF00025)supported by Tianjin Key Technology Research and Development Program,China+1 种基金Project(13JCYBJC17500)supported by Tianjin Natural Science Foundation,ChinaProject(20120032110068)supported by Doctoral Fund of Ministry of Education of China
文摘Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.
基金supported by the National Science Foundation of China(61561016 61861008+4 种基金 11603041)the Guangxi Natural Science Foundation Project(2018JJA170090)the Innovation Project of Guet Graduate Education(2018YJCX19 2018YJCX31)Guangxi Key Laboratory of Precision Navigation Technology and Application,Guilin University of Electronic Technology(DH201707)
文摘In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(RSCCT)for BOC(kn,n)signals is proposed.In this paper,the principle of signal decomposition is combined with the traditional acquisition algorithm structure,and then based on the method of reconstructing the correlation function.The method firstly gets the sub-pseudorandom noise(PRN)code by decomposing the local PRN code,then uses BOC(kn,n)and the sub-PRN code cross-correlation to get the sub cross-correlation function.Finally,the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed.The simulation shows that RSCCT can completely eliminate the side peaks of BOC(kn,n)group signals while maintaining the narrow correlation of BOC,and its computational complexity is equivalent to sub carrier phase cancellation(SCPC)and autocorrelation side-peak cancellation technique(ASPeCT),and it reduces the computational complexity relative to BPSK-like.For BOC(n,n),the acquisition sensitivity of RSCCT is 3.25 dB,0.81 dB and 0.25 dB higher than binary phase shift keying(BPSK)-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.91,3.0 and 3.7 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.For BOC(2n,n),the acquisition sensitivity of RSCCT is 5.5 dB,1.25 dB and 2.69 dB higher than BPSK-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.02,1.68 and 2.12 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.
文摘This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.
基金financially supported by the Important National Science&Technology Specific Project of China(Grant No.2017ZX05018-005)
文摘Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.
基金supported by the Science Foundation of Jiangsu Province of China (Grant No.BK2011759)
文摘In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.
基金The project supported by the National Natural Science Foundation of China
文摘The algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an effective algorithm for particle identification from consecutive images, the accurate velocity vector field can be obtained. The real velocity field in a valve chamber was measured by BICC in this study. From the full-field velocity information, the pressure and vorticity fields were also extracted by post-processing. (Edited author abstract) 6 Refs.
基金supported by National Key R&D Program of China(No.2018YFC1503200)National Natural Science Foundation of China(Nos.41674061,41790463 and 41674058)
文摘The amount of seismological data is rapidly increasing with accumulating observational time and increasing number of stations, requiring modern technique to provide adequate computing power. In present study, we proposed a framework to calculate large-scale noise crosscorrelation functions(NCFs) using public cloud service from ALIYUN. The entire computation is factorized into small pieces which are performed parallelly on specified number of virtual servers provided by the cloud. Using data from most seismic stations in China, five NCF databases are built. The results show that, comparing to the time cost using a single server, the entire time can be reduced over two orders of magnitude depending number of evoked virtual servers. This could reduce computation time from months to less than 12 hours. Based on obtained massive NCFs, the global body waves are retrieved through array interferometry and agree well with those from earthquakes. This leads to a solution to process massive seismic dataset within an affordable time and is applicable to other large-scale computing in seismological researches.
