In ghost imaging, an illumination light is split into test and reference beams which pass through two different optical systems respectively and an image is constructed with the second-order correlation between the tw...In ghost imaging, an illumination light is split into test and reference beams which pass through two different optical systems respectively and an image is constructed with the second-order correlation between the two light beams. Since both light beams are diffracted when passing through the optical systems, the spatial resolution of ghost imaging is in general lower than that of a corresponding conventional imaging system. When Gaussian-shaped light spots are used to illuminate an object, randomly scanning across the object plane, in the ghost imaging scheme, we show th√at by localizing central positions of the spots of the reference light beam, the resolution can be increased by a factor of 2^(1/2) same as that of the corresponding conventional imaging system. We also find that the resolution can be further enhanced by setting an appropriate threshold to the bucket measurement of ghost imaging.展开更多
Purpose: The present study aimed to assess the accuracies of arterial stimulation with simultaneous venous sampling(ASVS) in preoperative localization of insulinomas. Materials and Methods: A cohort consisting of 6 ma...Purpose: The present study aimed to assess the accuracies of arterial stimulation with simultaneous venous sampling(ASVS) in preoperative localization of insulinomas. Materials and Methods: A cohort consisting of 6 males and 14 females(median age, 48.5y; range, 28–62y) with pathologically proven insulinomas were included in this study. Selective angiographies were performed with the superior mesenteric artery(SMA), gastroduodenal artery(GDA), proximal splenic artery, and midsplenic artery in all individuals. Then ASVS procedures were followed after angiographies for these arteries. Clinical characteristics of the patient and the tumor number, location, and size were recorded. The accuracy of preoperative localization of insulinomas was tested. Results: A total of 22 tumors were identified by histopathological diagnosis. The mean size of the tumor was 1.40±0.60 cm. Five tumors were in the head/neck region and 17 in the body/tail region. ASVS accurately localized 17/20(85%) cases with only biochemical data and 19/20(95%) cases with biochemical data and angiography images. Variant pancreatic arterial anatomy was revealed in 2 false cases with inferior pancreatic artery replaced by the superior mesenteric artery. Conclusion: ASVS was highly accurate in localizing insulinomas and should be performed in most of the patients with suspected insulinomas before the operation.展开更多
In order to measure the position and orientation of in-vivo medical micro-devices without the line-of- sight constraints, a wireless magnetic sensor is developed for an electromagnetic localization method. In the elec...In order to measure the position and orientation of in-vivo medical micro-devices without the line-of- sight constraints, a wireless magnetic sensor is developed for an electromagnetic localization method. In the electromagnetic localization system, the wireless magnetic sensor is embedded in the micro-devices to measure alternating magnetic signals. The wireless magnetic sensor is composed of an induction coil, a signal processor, a radio frequency （R.F） transmitter, a power manager and batteries. Based on the principle of electromagnetic induction, the induction coil converts the alternating magnetic signals into electrical signals. Via the RF transmitter, the useful data am wirelessly sent outside the body. According to the relation between the magnetic signals and the location, the position and orientation of the micro-devices can be calculated. The experiments demonstrate the feasibility of localizing in-vivo medical micro-devices with the wireless magnetic sensor. The novel localization system is accurate and robust.展开更多
In the networking of loitering munitions during a battle,clustering and localizing algorithms become a major problem because of their highly dynamic topological structure,incomplete connectivity,and limited energy.Thi...In the networking of loitering munitions during a battle,clustering and localizing algorithms become a major problem because of their highly dynamic topological structure,incomplete connectivity,and limited energy.This paper proposed swarm intelligence based collaborative localizing,clustering,and routing scheme for an ad hoc network of loitering munitions in a satellite denied environment.A hybrid algorithm was first devised by integrating an improved coyote optimization algorithm with a simplified grey wolf optimizer under the sinusoidal crossover strategy.The performance of this algorithm was considerably improved thanks to integration.On this basis,a swarm intelligence based localizing algorithm was presented.Bounding cubes were created to reduce the initial search space,which effectively lowered the localizing error.Second,an energysaving clustering algorithm based on the hybrid algorithm was put forward to enhance the clustering efficiency by virtue of grey wolf hierarchy.Meanwhile,an analysis model was developed to determine the optimal number of clusters using the lowest possible number of transmissions.Ultimately,a compressed sensing routing scheme based on the hybrid algorithm was proposed to transmit data from a cluster head to a base station.This algorithm constructed an efficient routing tree from the cluster head to the base station,so as to reduce the routing delay and transmission count.As revealed in the results of simulation experiments,the proposed collaborative localizing,clustering and routing algorithms achieved better performance than other popular algorithms employed in various scenarios.展开更多
In this paper,we present a method for localization of a rail autonomous pesticide spraying and sampling robot working in greenhouse using an absolute localization system.Design and implementation of the localization s...In this paper,we present a method for localization of a rail autonomous pesticide spraying and sampling robot working in greenhouse using an absolute localization system.Design and implementation of the localization system comes from the usage of beacon systems each of which is composed of an RF single receiver and an ultrasonic transmitter.The RF single receiver gets the synchronization signal from the mobile robot,and the ultrasonic transmitter sends ultrasonic signal,thus the distance from the beacon to the ultrasonic receiver can be measured.The position of a beacon in coordinate system of robot can be calculated according to distance information from the beacons to two ultrasonic receivers which are mounted on the robot.Based on the coordinate transformation,the position of a mobile robot can be calculated from the beacon＇s absolute position information in the global coordinate system.Experiments demonstrate the effectiveness of the proposed method in real world applications.展开更多
Localizing a jammer in an indoor environment in wireless sensor networks becomes a significant research problem due to the ease of blocking the communication between legitimate nodes. An adversary may emit radio frequ...Localizing a jammer in an indoor environment in wireless sensor networks becomes a significant research problem due to the ease of blocking the communication between legitimate nodes. An adversary may emit radio frequency to prevent the transmission between nodes. In this paper, we propose detecting the position of the jammer indoor by using the received signal strength and Kalman filter (KF) to reduce the noise due to the multipath signal caused by obstacles in the indoor environment. We compare our work to the Linear Prediction Algorithm (LP) and Centroid Localization Algorithm (CL). We observed that the Kalman filter has better results when estimating the distance compared to other algorithms.展开更多
In this research, an arbitrarily oriented electric dipole at subsurface is used to simulate Seismogenic Electromagnetic(SEM) radiation emanating from a seismic zone during its gestation phase. Analytical synthesis of ...In this research, an arbitrarily oriented electric dipole at subsurface is used to simulate Seismogenic Electromagnetic(SEM) radiation emanating from a seismic zone during its gestation phase. Analytical synthesis of responses at the Lijiang magnetotelluric(MT) station has revealed that SEM radiation could induce identifiable anomalies in the electromagnetic(EM)spectrum, apparent resistivity and phase within specific frequency bands. Background variations were extracted from long-term observation data of Dali and Lijiang MT stations, enabling the identification of SEM anomalies related to the Yunlong and Yangbi earthquakes. Multiple parameters of dipole sources at subsurface were obtained by applying the Differential Ant Colony Optimization(DACO) algorithm to anomalous data of two stations with multi-frequencies and various response functions. The spatial distribution of these predicted dipoles is predominantly clustered in or around the seismogenic area, with their azimuthal orientation aligning towards the seismogenic fault in general. This study has demonstrated the potential of using subsurface electric dipole simulations for SEM radiation analysis, offering a feasible approach for the prediction and understanding of seismogenic zones.展开更多
Freight has become one of the major contributors to air pollution.This research proposes a method to systematically estimate truck vehicle emissions at the road segment level through localizing MOVES,a widely-used veh...Freight has become one of the major contributors to air pollution.This research proposes a method to systematically estimate truck vehicle emissions at the road segment level through localizing MOVES,a widely-used vehicle emission estimation model.We first design a protocol of converting percentage values of rotating speed and torque of engine to second-by-second vehicle speed to accommodate the differences between driving cycles adopted in local emission standards and those used in MOVES.In order to identify the best model year for estimating emissions under different local emission standards,we propose an approach of comparing emission outcomes rather than emission factors,considering the differences in unit used between MOVES and emission standards.To calculate road seg mentlevel emission factors,we weight original factors by integrating vehicle fleet informa tion which contains the shares of vehicles under different emission standards and at different ages.We apply the approach to a major freight corridor area in Shanghai and cal culate emission factors by air pollutant,average speed of road sections,and road type.Dynamic emissions of each road section per hour are calculated to reflect the spatial dis tribution of truck emissions.The research outcomes may help local departments,especially in developing countries,better estimate freight vehicle emissions and make policies corre spondingly to control their impacts on public health.展开更多
Machine learning algorithms operating in an unsupervised fashion has emerged as promising tools for detecting structural damage in an automated fashion.Its essence relies on selecting appropriate features to train the...Machine learning algorithms operating in an unsupervised fashion has emerged as promising tools for detecting structural damage in an automated fashion.Its essence relies on selecting appropriate features to train the model using the reference data set collected from the healthy structure and employing the trained model to identify outlier conditions representing the damaged state.In this paper,the coefficients and the residuals of the autoregressive model with exogenous input created using only the measured output signals are extracted as damage features.These features obtained at the baseline state for each sensor cluster are then utilized to train the one class support vector machine,an unsupervised classifier generating a decision function using only patterns belonging to this baseline state.Structural damage,once detected by the trained machine,a damage index based on comparison of the residuals between the trained class and the outlier state is implemented for localizing damage.The two-step damage assessment framework is first implemented on an eight degree-of-freedom numerical model with the effects of measurement noise integrated.Subsequently,vibration data collected from a one-story one-bay reinforced concrete frame inflicted with progressive levels of damage have been utilized to verify the accuracy and robustness of the proposed methodology.展开更多
In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):104...In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].展开更多
Oxygen release and electrolyte decomposition under high voltage endlessly exacerbate interfacial ramifications and structu ral degradation of high energy-density Li-rich layered oxide(LLO),leading to voltage and capac...Oxygen release and electrolyte decomposition under high voltage endlessly exacerbate interfacial ramifications and structu ral degradation of high energy-density Li-rich layered oxide(LLO),leading to voltage and capacity fading.Herein,the dual-strategy of Cr,B complex coating and local gradient doping is simultaneously achieved on LLO surface by a one-step wet chemical reaction at room temperature.Density functional theory(DFT)calculations prove that stable B-O and Cr-O bonds through the local gradient doping can significantly reduce the high-energy O 2p states of interfacial lattice O,which is also effective for the near-surface lattice O,thus greatly stabilizing the LLO surface,Besides,differential electrochemical mass spectrometry(DEMS)indicates that the Cr_(x)B complex coating can adequately inhibit oxygen release and prevents the migration or dissolution of transition metal ions,including allowing speedy Li^(+)migration,The voltage and capacity fading of the modified cathode(LLO-C_(r)B)are adequately suppressed,which are benefited from the uniformly dense cathode electrolyte interface(CEI)composed of balanced organic/inorganic composition.Therefore,the specific capacity of LLO-CrB after 200 cycles at 1C is 209.3 mA h g^(-1)(with a retention rate of 95.1%).This dual-strategy through a one-step wet chemical reaction is expected to be applied in the design and development of other anionic redox cathode materials.展开更多
The presence of a positive deep surgical margin in tongue squamous cell carcinoma(TSCC)significantly elevates the risk of local recurrence.Therefore,a prompt and precise intraoperative assessment of margin status is i...The presence of a positive deep surgical margin in tongue squamous cell carcinoma(TSCC)significantly elevates the risk of local recurrence.Therefore,a prompt and precise intraoperative assessment of margin status is imperative to ensure thorough tumor resection.In this study,we integrate Raman imaging technology with an artificial intelligence(AI)generative model,proposing an innovative approach for intraoperative margin status diagnosis.This method utilizes Raman imaging to swiftly and non-invasively capture tissue Raman images,which are then transformed into hematoxylin-eosin(H&E)-stained histopathological images using an AI generative model for histopathological diagnosis.The generated H&E-stained images clearly illustrate the tissue’s pathological conditions.Independently reviewed by three pathologists,the overall diagnostic accuracy for distinguishing between tumor tissue and normal muscle tissue reaches 86.7%.Notably,it outperforms current clinical practices,especially in TSCC with positive lymph node metastasis or moderately differentiated grades.This advancement highlights the potential of AI-enhanced Raman imaging to significantly improve intraoperative assessments and surgical margin evaluations,promising a versatile diagnostic tool beyond TSCC.展开更多
A multi-phase heterogeneous FeCoNi-based high-entropy alloy is developed to overcome the trade-off between strength and ductility.By alloying with a small amount of Cu and employing a rapid recrystalliza-tion process,...A multi-phase heterogeneous FeCoNi-based high-entropy alloy is developed to overcome the trade-off between strength and ductility.By alloying with a small amount of Cu and employing a rapid recrystalliza-tion process,it exhibits a good combination of yield strength(roughly 1300 MPa)and ductility(approach-ing 20%).Firstly,a multi-phase heterogeneous structure is tailored ranging from nano to micron.Cu is efficiently precipitated as nanoscale clusters(4.2 nm),high-density cuboidal L1_(2) particles(20-40 nm)and L2_(1) particles(500-800 nm)are found to be embedded in the matrix and a bimodal heterogeneous grain structure(1-40μm)is constructed.Secondly,the introduction of Cu effectively suppresses the pre-cipitation of coarse L21 phase at grain boundaries,reducing its volume fraction by 80%and replaced by smaller-scale continuous precipitations within the grains.Thirdly,the high mixing enthalpy gap of Cu and the matrix leads to the formation of local chemical fluctuation and the consequential rugged topog-raphy in the matrix,which result in retarded dislocation motion and promotes dislocation plugging and interlocking during strain,enhancing yield stress and work hardening rate.This study provides a valuable perspective to enhance strength and ductility via enlarged local chemical fluctuation-tailored multi-phase heterogeneous structures.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
Graphite-silicon species(Gr-Si)hybrid anodes have merged as potential candidates for high-energy lithium-ion batteries(LIBs),yet long been plagued by rapid capacity fading due to their unstable mechano-electrochemistr...Graphite-silicon species(Gr-Si)hybrid anodes have merged as potential candidates for high-energy lithium-ion batteries(LIBs),yet long been plagued by rapid capacity fading due to their unstable mechano-electrochemistry.The dominant approach to enhance electrochemical stability of the Gr-Si hybrid anodes typically involves the optimization of the electrode material structures and the employment of low active Si species content in electrode(<10 wt%in most instances).However,the electrode structure design,a factor of equal importance in determining the electrochemical performance of Gr-Si hybrid anodes,has received scant attention.In this study,three Gr-Si hybrid anodes with the identical material composition but distinct electrode structures are designed to investigate the mechanoelectrochemistry of the electrodes.It is revealed that the substantial volume change of Si species particles in Gr-Si hybrid anodes led to the local lattice stress of Gr at their contact interface during the charge/discharge processes,thereby increasing thermodynamic and kinetic barrier of Li-ion migration.Furthermore,the huge disparity in volume change of Si species and Gr particles trigger the separate agglomeration of these two materials,resulting in a considerable electrode volume change and increased electrochemical resistance.An advanced Gr/Si hybrid anode with upper Gr and lower Si species layer structure design addresses the above challenges using photovoltaic waste silicon sources under high Si species content(17 wt%)and areal capacity(2.0 mA h cm^(-2))in Ah-level full pouch cells with a low negative/positive(N/P)ratio of 1.09.The cell shows stable cycling for 100 cycles at 0.3 C with an impressively low capacity decay rate of 0.0546%per cycle,outperforming most reported Gr-Si hybrid anodes.展开更多
The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to indus...The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.展开更多
The Mg-9Li-1Zn(LZ91)alloy was subjected to an ultrasonic surface rolling process(USRP)with varying passes for the purpose of modifying its surface state.The USRP transformed surface residual stress from initial tensil...The Mg-9Li-1Zn(LZ91)alloy was subjected to an ultrasonic surface rolling process(USRP)with varying passes for the purpose of modifying its surface state.The USRP transformed surface residual stress from initial tensile stress to compressive stress,decreasing the surface roughness and increasing the ratio of the β-Li phase.The USRPed LZ91 sample(3 passes)showed superior corrosion resistance,with the corrosion current density changing from 57.11 to 24.70μA cm^(-2),and the polarization resistance increasing from 576.3 to 1146.1Ωcm^(2).According to the corrosion procedure evaluations,in situ observation revealed that the LZ91 alloy initially experiences pitting,which subsequently develops into cracking.The substantial area coverage of the β-Li phase facilitates the formation of a protective film on the surface,effectively delaying localized corrosion.展开更多
Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and m...Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).展开更多
Axonal regeneration following surgical nerve repair is slow and often incomplete,resulting in poor functional recovery which sometimes contributes to lifelong disability.Currently,there are no FDA-approved therapies a...Axonal regeneration following surgical nerve repair is slow and often incomplete,resulting in poor functional recovery which sometimes contributes to lifelong disability.Currently,there are no FDA-approved therapies available to promote nerve regeneration.Tacrolimus accelerates axonal regeneration,but systemic side effects presently outweigh its potential benefits for peripheral nerve surgery.The authors describe herein a biodegradable polyurethane-based drug delivery system for the sustained local release of tacrolimus at the nerve repair site,with suitable properties for scalable production and clinical application,aiming to promote nerve regeneration and functional recovery with minimal systemic drug exposure.Tacrolimus is encapsulated into co-axially electrospun polycarbonate-urethane nanofibers to generate an implantable nerve wrap that releases therapeutic doses of bioactive tacrolimus over 31 days.Size and drug loading are adjustable for applications in small and large caliber nerves,and the wrap degrades within 120 days into biocompatible byproducts.Tacrolimus released from the nerve wrap promotes axon elongation in vitro and accelerates nerve regeneration and functional recovery in preclinical nerve repair models while off-target systemic drug exposure is reduced by 80%compared with systemic delivery.Given its surgical suitability and preclinical efficacy and safety,this system may provide a readily translatable approach to support axonal regeneration and recovery in patients undergoing nerve surgery.展开更多
Introducing B2 ordering can effectively improve the mechanical properties of lightweight refractory high-entropy alloys(LRHEAs).However,(Zr,Al)-enriched B2 precipitates generally reduce the ductility because their ord...Introducing B2 ordering can effectively improve the mechanical properties of lightweight refractory high-entropy alloys(LRHEAs).However,(Zr,Al)-enriched B2 precipitates generally reduce the ductility because their ordering characteristic is destroyed after dislocation shearing.Meanwhile,the local chemical order(LCO)cannot provide an adequate strengthening effect due to its small size.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11534008,11605126,and 11804271)the Fund from the Ministry of Science and Technology of China(Grant No.2016YFA0301404)+2 种基金the Natural Science Basic Research Plan in Shaanxi Province,China(Grant No.2017JQ1025)the Doctoral Fund of the Ministry of Education of China(Grant Nos.2016M592772 and 2018M631137)the Fundamental Research Funds for the Central Universities
文摘In ghost imaging, an illumination light is split into test and reference beams which pass through two different optical systems respectively and an image is constructed with the second-order correlation between the two light beams. Since both light beams are diffracted when passing through the optical systems, the spatial resolution of ghost imaging is in general lower than that of a corresponding conventional imaging system. When Gaussian-shaped light spots are used to illuminate an object, randomly scanning across the object plane, in the ghost imaging scheme, we show th√at by localizing central positions of the spots of the reference light beam, the resolution can be increased by a factor of 2^(1/2) same as that of the corresponding conventional imaging system. We also find that the resolution can be further enhanced by setting an appropriate threshold to the bucket measurement of ghost imaging.
基金This work was supported by the Shanghai Pujiang Program(16PJ1406200)the Scientific Research Innovation Projects of Shanghai Municipal Education Commission(15ZZ060)
文摘Purpose: The present study aimed to assess the accuracies of arterial stimulation with simultaneous venous sampling(ASVS) in preoperative localization of insulinomas. Materials and Methods: A cohort consisting of 6 males and 14 females(median age, 48.5y; range, 28–62y) with pathologically proven insulinomas were included in this study. Selective angiographies were performed with the superior mesenteric artery(SMA), gastroduodenal artery(GDA), proximal splenic artery, and midsplenic artery in all individuals. Then ASVS procedures were followed after angiographies for these arteries. Clinical characteristics of the patient and the tumor number, location, and size were recorded. The accuracy of preoperative localization of insulinomas was tested. Results: A total of 22 tumors were identified by histopathological diagnosis. The mean size of the tumor was 1.40±0.60 cm. Five tumors were in the head/neck region and 17 in the body/tail region. ASVS accurately localized 17/20(85%) cases with only biochemical data and 19/20(95%) cases with biochemical data and angiography images. Variant pancreatic arterial anatomy was revealed in 2 false cases with inferior pancreatic artery replaced by the superior mesenteric artery. Conclusion: ASVS was highly accurate in localizing insulinomas and should be performed in most of the patients with suspected insulinomas before the operation.
基金Sup.ported by the High TechnologyResearch and Development Programme of China （No.2006AA04Z368）, the National Natural Science Foundation of China （No. 30900320, 30570485） and Innovation Program of Shanghai Municipal Education Commission （No. 10YZ93）.
文摘In order to measure the position and orientation of in-vivo medical micro-devices without the line-of- sight constraints, a wireless magnetic sensor is developed for an electromagnetic localization method. In the electromagnetic localization system, the wireless magnetic sensor is embedded in the micro-devices to measure alternating magnetic signals. The wireless magnetic sensor is composed of an induction coil, a signal processor, a radio frequency （R.F） transmitter, a power manager and batteries. Based on the principle of electromagnetic induction, the induction coil converts the alternating magnetic signals into electrical signals. Via the RF transmitter, the useful data am wirelessly sent outside the body. According to the relation between the magnetic signals and the location, the position and orientation of the micro-devices can be calculated. The experiments demonstrate the feasibility of localizing in-vivo medical micro-devices with the wireless magnetic sensor. The novel localization system is accurate and robust.
文摘In the networking of loitering munitions during a battle,clustering and localizing algorithms become a major problem because of their highly dynamic topological structure,incomplete connectivity,and limited energy.This paper proposed swarm intelligence based collaborative localizing,clustering,and routing scheme for an ad hoc network of loitering munitions in a satellite denied environment.A hybrid algorithm was first devised by integrating an improved coyote optimization algorithm with a simplified grey wolf optimizer under the sinusoidal crossover strategy.The performance of this algorithm was considerably improved thanks to integration.On this basis,a swarm intelligence based localizing algorithm was presented.Bounding cubes were created to reduce the initial search space,which effectively lowered the localizing error.Second,an energysaving clustering algorithm based on the hybrid algorithm was put forward to enhance the clustering efficiency by virtue of grey wolf hierarchy.Meanwhile,an analysis model was developed to determine the optimal number of clusters using the lowest possible number of transmissions.Ultimately,a compressed sensing routing scheme based on the hybrid algorithm was proposed to transmit data from a cluster head to a base station.This algorithm constructed an efficient routing tree from the cluster head to the base station,so as to reduce the routing delay and transmission count.As revealed in the results of simulation experiments,the proposed collaborative localizing,clustering and routing algorithms achieved better performance than other popular algorithms employed in various scenarios.
基金supported by the MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2010-C1090-1021-0010)
文摘In this paper,we present a method for localization of a rail autonomous pesticide spraying and sampling robot working in greenhouse using an absolute localization system.Design and implementation of the localization system comes from the usage of beacon systems each of which is composed of an RF single receiver and an ultrasonic transmitter.The RF single receiver gets the synchronization signal from the mobile robot,and the ultrasonic transmitter sends ultrasonic signal,thus the distance from the beacon to the ultrasonic receiver can be measured.The position of a beacon in coordinate system of robot can be calculated according to distance information from the beacons to two ultrasonic receivers which are mounted on the robot.Based on the coordinate transformation,the position of a mobile robot can be calculated from the beacon＇s absolute position information in the global coordinate system.Experiments demonstrate the effectiveness of the proposed method in real world applications.
文摘Localizing a jammer in an indoor environment in wireless sensor networks becomes a significant research problem due to the ease of blocking the communication between legitimate nodes. An adversary may emit radio frequency to prevent the transmission between nodes. In this paper, we propose detecting the position of the jammer indoor by using the received signal strength and Kalman filter (KF) to reduce the noise due to the multipath signal caused by obstacles in the indoor environment. We compare our work to the Linear Prediction Algorithm (LP) and Centroid Localization Algorithm (CL). We observed that the Kalman filter has better results when estimating the distance compared to other algorithms.
基金financially supported by the National Natural Science Foundation of China (Grant No. 41574064)the Independent Research Projects of State Key Laboratory of Earthquake Dynamics (Grant No. LED2023A07)the National Major Science and Technology Facilities Project (Grant No. 1512Z0000001)。
文摘In this research, an arbitrarily oriented electric dipole at subsurface is used to simulate Seismogenic Electromagnetic(SEM) radiation emanating from a seismic zone during its gestation phase. Analytical synthesis of responses at the Lijiang magnetotelluric(MT) station has revealed that SEM radiation could induce identifiable anomalies in the electromagnetic(EM)spectrum, apparent resistivity and phase within specific frequency bands. Background variations were extracted from long-term observation data of Dali and Lijiang MT stations, enabling the identification of SEM anomalies related to the Yunlong and Yangbi earthquakes. Multiple parameters of dipole sources at subsurface were obtained by applying the Differential Ant Colony Optimization(DACO) algorithm to anomalous data of two stations with multi-frequencies and various response functions. The spatial distribution of these predicted dipoles is predominantly clustered in or around the seismogenic area, with their azimuthal orientation aligning towards the seismogenic fault in general. This study has demonstrated the potential of using subsurface electric dipole simulations for SEM radiation analysis, offering a feasible approach for the prediction and understanding of seismogenic zones.
基金The research is also supported by the Shanghai sailing project(Grant ID 20YF1451700)Shanghai Municipal Bureau of Ecology and Environment(Grant ID Huhuanke 2022-25).
文摘Freight has become one of the major contributors to air pollution.This research proposes a method to systematically estimate truck vehicle emissions at the road segment level through localizing MOVES,a widely-used vehicle emission estimation model.We first design a protocol of converting percentage values of rotating speed and torque of engine to second-by-second vehicle speed to accommodate the differences between driving cycles adopted in local emission standards and those used in MOVES.In order to identify the best model year for estimating emissions under different local emission standards,we propose an approach of comparing emission outcomes rather than emission factors,considering the differences in unit used between MOVES and emission standards.To calculate road seg mentlevel emission factors,we weight original factors by integrating vehicle fleet informa tion which contains the shares of vehicles under different emission standards and at different ages.We apply the approach to a major freight corridor area in Shanghai and cal culate emission factors by air pollutant,average speed of road sections,and road type.Dynamic emissions of each road section per hour are calculated to reflect the spatial dis tribution of truck emissions.The research outcomes may help local departments,especially in developing countries,better estimate freight vehicle emissions and make policies corre spondingly to control their impacts on public health.
基金funding provided by the Scientific and Technological Research Council of Türkiye(TÜBİTAK).
文摘Machine learning algorithms operating in an unsupervised fashion has emerged as promising tools for detecting structural damage in an automated fashion.Its essence relies on selecting appropriate features to train the model using the reference data set collected from the healthy structure and employing the trained model to identify outlier conditions representing the damaged state.In this paper,the coefficients and the residuals of the autoregressive model with exogenous input created using only the measured output signals are extracted as damage features.These features obtained at the baseline state for each sensor cluster are then utilized to train the one class support vector machine,an unsupervised classifier generating a decision function using only patterns belonging to this baseline state.Structural damage,once detected by the trained machine,a damage index based on comparison of the residuals between the trained class and the outlier state is implemented for localizing damage.The two-step damage assessment framework is first implemented on an eight degree-of-freedom numerical model with the effects of measurement noise integrated.Subsequently,vibration data collected from a one-story one-bay reinforced concrete frame inflicted with progressive levels of damage have been utilized to verify the accuracy and robustness of the proposed methodology.
基金Supported by NSFC(Nos.11661025,12161024)Natural Science Foundation of Guangxi(Nos.2020GXNSFAA159118,2021GXNSFAA196045)+2 种基金Guangxi Science and Technology Project(No.Guike AD20297006)Training Program for 1000 Young and Middle-aged Cadre Teachers in Universities of GuangxiNational College Student's Innovation and Entrepreneurship Training Program(No.202110595049)。
文摘In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].
基金financially supported by the National Natural Science Foundation of China(No.12304077)the Natural Science Foundation of Science and Technology Department of Sichuan Province(No.23NSFSC6224)+3 种基金Sichuan Science and Technology Program(No.2024NSFSC0989)the Key Laboratory of Computational Physics of Sichuan Province(No.YBUJSWL-YB-2022-03)the Material Corrosion and Protection Key Laboratory of Sichuan Province(No.2023CL14 and No.2023CL01)the National Innovation Practice Project(No.202411079005S).
文摘Oxygen release and electrolyte decomposition under high voltage endlessly exacerbate interfacial ramifications and structu ral degradation of high energy-density Li-rich layered oxide(LLO),leading to voltage and capacity fading.Herein,the dual-strategy of Cr,B complex coating and local gradient doping is simultaneously achieved on LLO surface by a one-step wet chemical reaction at room temperature.Density functional theory(DFT)calculations prove that stable B-O and Cr-O bonds through the local gradient doping can significantly reduce the high-energy O 2p states of interfacial lattice O,which is also effective for the near-surface lattice O,thus greatly stabilizing the LLO surface,Besides,differential electrochemical mass spectrometry(DEMS)indicates that the Cr_(x)B complex coating can adequately inhibit oxygen release and prevents the migration or dissolution of transition metal ions,including allowing speedy Li^(+)migration,The voltage and capacity fading of the modified cathode(LLO-C_(r)B)are adequately suppressed,which are benefited from the uniformly dense cathode electrolyte interface(CEI)composed of balanced organic/inorganic composition.Therefore,the specific capacity of LLO-CrB after 200 cycles at 1C is 209.3 mA h g^(-1)(with a retention rate of 95.1%).This dual-strategy through a one-step wet chemical reaction is expected to be applied in the design and development of other anionic redox cathode materials.
基金supported by the National Natural Science Foundation of China(Grant Nos.82272955 and 22203057)the Natural Science Foundation of Fujian Province(Grant No.2021J011361).
文摘The presence of a positive deep surgical margin in tongue squamous cell carcinoma(TSCC)significantly elevates the risk of local recurrence.Therefore,a prompt and precise intraoperative assessment of margin status is imperative to ensure thorough tumor resection.In this study,we integrate Raman imaging technology with an artificial intelligence(AI)generative model,proposing an innovative approach for intraoperative margin status diagnosis.This method utilizes Raman imaging to swiftly and non-invasively capture tissue Raman images,which are then transformed into hematoxylin-eosin(H&E)-stained histopathological images using an AI generative model for histopathological diagnosis.The generated H&E-stained images clearly illustrate the tissue’s pathological conditions.Independently reviewed by three pathologists,the overall diagnostic accuracy for distinguishing between tumor tissue and normal muscle tissue reaches 86.7%.Notably,it outperforms current clinical practices,especially in TSCC with positive lymph node metastasis or moderately differentiated grades.This advancement highlights the potential of AI-enhanced Raman imaging to significantly improve intraoperative assessments and surgical margin evaluations,promising a versatile diagnostic tool beyond TSCC.
基金financial support from the National Natural Science Foundation of China(Nos.52104306,52274301,52334009)the Aeronautical Science Foundation of China(No.2023Z0530S6005)+3 种基金the National Key Research and Development Program of China(No.2023YFB3712401)the Science and Technology Commission of Shanghai Municipality(No.21DZ1208900)the Academician Workstation of Kunming University of Science and Technology(2024),the Ningbo Yongjiang Talent-Introduction Programme(No.2022A-023-C)the Zhejiang Phenomenological Materials Technology Co.,Ltd.,China.
文摘A multi-phase heterogeneous FeCoNi-based high-entropy alloy is developed to overcome the trade-off between strength and ductility.By alloying with a small amount of Cu and employing a rapid recrystalliza-tion process,it exhibits a good combination of yield strength(roughly 1300 MPa)and ductility(approach-ing 20%).Firstly,a multi-phase heterogeneous structure is tailored ranging from nano to micron.Cu is efficiently precipitated as nanoscale clusters(4.2 nm),high-density cuboidal L1_(2) particles(20-40 nm)and L2_(1) particles(500-800 nm)are found to be embedded in the matrix and a bimodal heterogeneous grain structure(1-40μm)is constructed.Secondly,the introduction of Cu effectively suppresses the pre-cipitation of coarse L21 phase at grain boundaries,reducing its volume fraction by 80%and replaced by smaller-scale continuous precipitations within the grains.Thirdly,the high mixing enthalpy gap of Cu and the matrix leads to the formation of local chemical fluctuation and the consequential rugged topog-raphy in the matrix,which result in retarded dislocation motion and promotes dislocation plugging and interlocking during strain,enhancing yield stress and work hardening rate.This study provides a valuable perspective to enhance strength and ductility via enlarged local chemical fluctuation-tailored multi-phase heterogeneous structures.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
基金the financial support by the National Natural Science Foundation of China(52072137)the National Natural Science Foundation of China(22205068)the"CUG Scholar"Scientific Research Funds at China University of Geosciences(Wuhan)(2022118)。
文摘Graphite-silicon species(Gr-Si)hybrid anodes have merged as potential candidates for high-energy lithium-ion batteries(LIBs),yet long been plagued by rapid capacity fading due to their unstable mechano-electrochemistry.The dominant approach to enhance electrochemical stability of the Gr-Si hybrid anodes typically involves the optimization of the electrode material structures and the employment of low active Si species content in electrode(<10 wt%in most instances).However,the electrode structure design,a factor of equal importance in determining the electrochemical performance of Gr-Si hybrid anodes,has received scant attention.In this study,three Gr-Si hybrid anodes with the identical material composition but distinct electrode structures are designed to investigate the mechanoelectrochemistry of the electrodes.It is revealed that the substantial volume change of Si species particles in Gr-Si hybrid anodes led to the local lattice stress of Gr at their contact interface during the charge/discharge processes,thereby increasing thermodynamic and kinetic barrier of Li-ion migration.Furthermore,the huge disparity in volume change of Si species and Gr particles trigger the separate agglomeration of these two materials,resulting in a considerable electrode volume change and increased electrochemical resistance.An advanced Gr/Si hybrid anode with upper Gr and lower Si species layer structure design addresses the above challenges using photovoltaic waste silicon sources under high Si species content(17 wt%)and areal capacity(2.0 mA h cm^(-2))in Ah-level full pouch cells with a low negative/positive(N/P)ratio of 1.09.The cell shows stable cycling for 100 cycles at 0.3 C with an impressively low capacity decay rate of 0.0546%per cycle,outperforming most reported Gr-Si hybrid anodes.
文摘The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.
基金financially supported by the National Natural Science Foundation of China(No.52271091)the National Key Research and Development Program of China(No.2021YFB3701100)the Natural Science Foundation Project of Ningxia Province(No.2023AAC03324).
文摘The Mg-9Li-1Zn(LZ91)alloy was subjected to an ultrasonic surface rolling process(USRP)with varying passes for the purpose of modifying its surface state.The USRP transformed surface residual stress from initial tensile stress to compressive stress,decreasing the surface roughness and increasing the ratio of the β-Li phase.The USRPed LZ91 sample(3 passes)showed superior corrosion resistance,with the corrosion current density changing from 57.11 to 24.70μA cm^(-2),and the polarization resistance increasing from 576.3 to 1146.1Ωcm^(2).According to the corrosion procedure evaluations,in situ observation revealed that the LZ91 alloy initially experiences pitting,which subsequently develops into cracking.The substantial area coverage of the β-Li phase facilitates the formation of a protective film on the surface,effectively delaying localized corrosion.
文摘Neurons are highly polarized cells with axons reaching over a meter long in adult humans.To survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and intensity.Such mechanisms include axonal transport,local synthesis,and liquid-liquid phase separations.Alterations and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).
基金supported by the German Research Foundation(DA 2255/1-1to SCD)+4 种基金a SickKids Research Training Competition(RESTRACOMP)Graduate Scholarship(to KJWS)an Ontario Graduate Scholarship(to KJWS)a grant from Natural Sciences and Engineering Research Council of Canada(NSERC)(to KJWS)a Kickstarter grant from the Institute of Biomedical Engineering(BME)at the University of Toronto(to KJWS)the Abe Frank Fund from the Riley’s Children Foundation(GHB)。
文摘Axonal regeneration following surgical nerve repair is slow and often incomplete,resulting in poor functional recovery which sometimes contributes to lifelong disability.Currently,there are no FDA-approved therapies available to promote nerve regeneration.Tacrolimus accelerates axonal regeneration,but systemic side effects presently outweigh its potential benefits for peripheral nerve surgery.The authors describe herein a biodegradable polyurethane-based drug delivery system for the sustained local release of tacrolimus at the nerve repair site,with suitable properties for scalable production and clinical application,aiming to promote nerve regeneration and functional recovery with minimal systemic drug exposure.Tacrolimus is encapsulated into co-axially electrospun polycarbonate-urethane nanofibers to generate an implantable nerve wrap that releases therapeutic doses of bioactive tacrolimus over 31 days.Size and drug loading are adjustable for applications in small and large caliber nerves,and the wrap degrades within 120 days into biocompatible byproducts.Tacrolimus released from the nerve wrap promotes axon elongation in vitro and accelerates nerve regeneration and functional recovery in preclinical nerve repair models while off-target systemic drug exposure is reduced by 80%compared with systemic delivery.Given its surgical suitability and preclinical efficacy and safety,this system may provide a readily translatable approach to support axonal regeneration and recovery in patients undergoing nerve surgery.
基金supported by the National Natural Science Foundation of China(Nos.52171166 and U20A20231)the Natural Science Foundation of Hunan Province,China(Nos.2024JJ2060 and 2024JJ5406)+1 种基金the Key Laboratory of Materials in Dynamic Extremes of Sichuan Province(No.2023SCKT1102)the Postgraduate Scientific Research Innovation Project of National University of Defense Technology(No.XJJC2024065).
文摘Introducing B2 ordering can effectively improve the mechanical properties of lightweight refractory high-entropy alloys(LRHEAs).However,(Zr,Al)-enriched B2 precipitates generally reduce the ductility because their ordering characteristic is destroyed after dislocation shearing.Meanwhile,the local chemical order(LCO)cannot provide an adequate strengthening effect due to its small size.
