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
Timely acquisition of chicken behavioral information is crucial for assessing chicken health status and production performance.Video-based behavior recognition has emerged as a primary technique for obtaining such inf...Timely acquisition of chicken behavioral information is crucial for assessing chicken health status and production performance.Video-based behavior recognition has emerged as a primary technique for obtaining such information due to its accuracy and robustness.Video-based models generally predict a single behavior from a single video segment of a fixed duration.However,during periods of high activity in poultry,behavior transition may occur within a video segment,and existing models often fail to capture such transitions effectively.This limitation highlights the insufficient temporal resolution of video-based behavior recognition models.This study presents a chicken behavior recognition and localization model,CBLFormer,which is based on spatiotemporal feature learning.The model was designed to recognize behaviors that occur before and after transitions in video segments and to localize the corresponding time interval for each behavior.An improved transformer block,the cascade encoder-decoder network(CEDNet),a transformer-based head,and weighted distance intersection over union(WDIoU)loss were integrated into CBLFormer to enhance the model's ability to distinguish between different behavior categories and locate behavior boundaries.For the training and testing of CBLFormer,a dataset was created by collecting videos from 320 chickens across different ages and rearing densities.The results showed that CBLFormer achieved a mAP@0.5:0.95 of 98.34%on the test set.The integration of CEDNet contributed the most to the performance improvement of CBLFormer.The visualization results confirmed that the model effectively captured the behavioral boundaries of chickens and correctly recognized behavior categories.The transfer learning results demonstrated that the model is applicable to chicken behavior recognition and localization tasks in real-world poultry farms.The proposed method handles cases where poultry behavior transitions occur within the video segment and improves the temporal resolution of video-based behavior recognition models.展开更多
Visible and infrared(RGB-IR)fusion object detection plays an important role in security,disaster relief,etc.In recent years,deep-learning-based RGB-IR fusion detection methods have been developing rapidly,but still st...Visible and infrared(RGB-IR)fusion object detection plays an important role in security,disaster relief,etc.In recent years,deep-learning-based RGB-IR fusion detection methods have been developing rapidly,but still struggle to deal with the complex and changing scenarios captured by drones,mainly due to two reasons:(A)RGB-IR fusion detectors are susceptible to inferior inputs that degrade performance and stability.(B)RGB-IR fusion detectors are susceptible to redundant features that reduce accuracy and efficiency.In this paper,an innovative RGB-IR fusion detection framework based on global-local feature optimization,named GLFDet,is proposed to improve the detection performance and efficiency of drone-captured objects.The key components of GLFDet include a Global Feature Optimization(GFO)module,a Local Feature Optimization(LFO)module and a Channel Separation Fusion(CSF)module.Specifically,GFO calculates the information content of the input image from the frequency domain and optimizes the features holistically.Then,LFO dynamically selects high-value features and filters out low-value features before fusion,which significantly improves the efficiency of fusion.Finally,CSF fuses the RGB and IR features across the corresponding channels,which avoids the rearrangement of the channel relationships and enhances the model stability.Extensive experimental results show that the proposed method achieves the best performance on three popular RGB-IR datasets Drone Vehicle,VEDAI,and LLVIP.In addition,GLFDet is more lightweight than other comparable models,making it more appealing to edge devices such as drones.The code is available at https://github.com/lao chen330/GLFDet.展开更多
The laboratory established an efficient reversed-phase ultra-high-performance liquid chromatographyquadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS)qualitative method for screening more than 2000 kinds of ris...The laboratory established an efficient reversed-phase ultra-high-performance liquid chromatographyquadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS)qualitative method for screening more than 2000 kinds of risk substances(including local anesthetics,LAs)in cosmetics,which has been successfully applied in the analysis of actual samples.This work aims to develop a more convenient high performance liquid chromatography triple quadrupole mass spectrometry(HPLC-QQQ-MS/MS)method for the quantitative determination of LAs.Samples were ultrasonically extracted with methanol,separated on an Agilent Poroshell 120 EC-C18 column(2.1 mm×100 mm,2.7μm),and eluted with a gradient mobile phase consisting of 0.1%formic acid aqueous solution and methanol.Quantification was performed using the external standard method.The results show that all 23 LAs are effectively separated within 12 minutes,with good linearity in the corresponding concentration ranges and the correlation coefficients all greater than 0.99.The limits of detection(LOD)range from 0.0025 to 0.05μg/g,and the limits of quantification(LOQ)range from 0.01 to 0.1μg/g.The average recoveries of the 23 LAs in 5 blank cosmetic matrices are 80.68%-117.57%,with the relative standard deviations(RSDs)less than 5.98%.This method has good precision and high accuracy,and is suitable for the determination of LAs in 5 cosmetic matrices.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
Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevatio...Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevations along the mid-sagittal plane further contribute to a three-dimensional auditory experience.This study aimed to characterize the variability in vertical sound localization abilities among normal-hearing(NH)individuals using spatialized audio.Materials and Methods:Fifty-one NH participants(aged 18 to 35 years)completed three vertical localization tasks under headphones as part of a single-group,within-subject experimental study.These tasks included two-plane identification:(1)top-down localization,(2)front-back localization,and one discrimination task in the front plane.Hierarchical Cluster Analysis(HCA)was employed to identify distinct patterns in spatial localization profiles specific to the vertical-median plane.Fisher's Discriminant Function Analysis(FDA)was used to validate the accuracy of HCA and estimate classification error.Results:HCA revealed three distinct listener clusters:(1)cluster 1 with good performance across all three tasks,(2)cluster 2 with selective impairment in top-bottom identification,and(3)cluster 3 with selective deficits in front-back identification.FDA validated group membership of the clusters identified by the HCA,with a prediction accuracy of 98%.Conclusions:Individuals with clinically NH exhibited three distinct vertical localization profiles:uniform performers,those impaired in top-bottom identification,and those impaired in front-back identification.These profiles may be linked to the interplay between acoustic and non-acoustic perceptual factors.展开更多
BEIJING,Feb.25(Xinhua)-In a territory more than twice the size of the European Union and where per capita GDP varies up to fourfold across provincia level regions,the challenge of modernizing China with the right solu...BEIJING,Feb.25(Xinhua)-In a territory more than twice the size of the European Union and where per capita GDP varies up to fourfold across provincia level regions,the challenge of modernizing China with the right solutions for diverse localities has become a test of governance wisdom.展开更多
Heart disease remains a leading cause of mortality worldwide,emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention.However,existing Deep Learni...Heart disease remains a leading cause of mortality worldwide,emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention.However,existing Deep Learning(DL)approaches often face several limitations,including inefficient feature extraction,class imbalance,suboptimal classification performance,and limited interpretability,which collectively hinder their deployment in clinical settings.To address these challenges,we propose a novel DL framework for heart disease prediction that integrates a comprehensive preprocessing pipeline with an advanced classification architecture.The preprocessing stage involves label encoding and feature scaling.To address the issue of class imbalance inherent in the personal key indicators of the heart disease dataset,the localized random affine shadowsampling technique is employed,which enhances minority class representation while minimizing overfitting.At the core of the framework lies the Deep Residual Network(DeepResNet),which employs hierarchical residual transformations to facilitate efficient feature extraction and capture complex,non-linear relationships in the data.Experimental results demonstrate that the proposed model significantly outperforms existing techniques,achieving improvements of 3.26%in accuracy,3.16%in area under the receiver operating characteristics,1.09%in recall,and 1.07%in F1-score.Furthermore,robustness is validated using 10-fold crossvalidation,confirming the model’s generalizability across diverse data distributions.Moreover,model interpretability is ensured through the integration of Shapley additive explanations and local interpretable model-agnostic explanations,offering valuable insights into the contribution of individual features to model predictions.Overall,the proposed DL framework presents a robust,interpretable,and clinically applicable solution for heart disease prediction.展开更多
Local residents,artists,and entrepreneurs who converge on Haikou’s historical Qilou Street are contributing to a new chapter in the story of Hainan’s opening-up.MORE than 100 years ago,the area alongQilou(Sotto Port...Local residents,artists,and entrepreneurs who converge on Haikou’s historical Qilou Street are contributing to a new chapter in the story of Hainan’s opening-up.MORE than 100 years ago,the area alongQilou(Sotto Portico)Street in Haikou,capital of Hainan Province,served asthe embarkation point for Hainanesesetting out on their maritime voyages to seek greener pastures.展开更多
BACKGROUND Data comparing the outcomes of hepatocellular carcinoma(HCC)ablation by multibipolar radiofrequency ablation(mbp-RFA)and microwave ablation(MWA)are lacking.This study compares safety and efficacy of the two...BACKGROUND Data comparing the outcomes of hepatocellular carcinoma(HCC)ablation by multibipolar radiofrequency ablation(mbp-RFA)and microwave ablation(MWA)are lacking.This study compares safety and efficacy of the two techniques in treatment-naive HCC.AIM To compare the risk of local tumor progression(LTP)according to the technique;secondary endpoints included technique efficacy rate at one-month,overall survival and major complication rate.METHODS A bi-institutional retrospective analysis of patients undergoing treatment-naive HCC ablation by either technique was performed.Inverse probability of treatment weighting was used to compare the two groups.Mixed effects multivariate Cox regression was applied to identify risk factors for LTP.RESULTS A total of 362 patients(mean age,66.1±6.2 years,308 men)were included,of which 242(323 tumors)treated by mbp-RFA and 120(168 tumors)by MWA.After a median follow-up of 27 months,cumulative LTP was 11.4%after mbp-RFA and 25.2%after MWA.Independent risk factors for LTP at multivariate analysis were MWA(hazard ratio=2.85,P<0.001)and tumor size(hazard ratio=1.08,P<0.001).Two-year LTP-free survival was higher after mbp-RFA than MWA regardless of size(<3 cm:96%vs 87.1%,P<0.01;≥3 cm:87.5%vs 74%,P=0.04).Technique efficacy rate was higher after mbp-RFA(94.1%vs 87.5%,P=0.01).No difference was observed in major complication rate(9.5%vs 7.5%,P=0.59),nor 5-year overall survival(63.6%vs 58.3%,P=0.33).CONCLUSION Mbp-RFA leads to better local tumor control of treatment-naïve HCC than MWA regardless of tumor size and has better primary efficacy,while maintaining a comparable safety profile.展开更多
Cellular asymmetry,which represents a fundamental characteristic of cell polarity,is prominently illustrated by the apical-basal localization of PINFORMED(PIN)auxin efflux carriers in Arabidopsis thaliana.Although the...Cellular asymmetry,which represents a fundamental characteristic of cell polarity,is prominently illustrated by the apical-basal localization of PINFORMED(PIN)auxin efflux carriers in Arabidopsis thaliana.Although the maintenance of PIN polarity at the plasma membrane(PM)relies on endomembrane trafficking,the pivotal factors responsible for recruiting PIN proteins to the PM remain largely unknown.In this study,we discover that EXO70G1displays a polarized distribution at the PM in root cells.Acting as a putative subunit of the exocyst complex,which mediates the tethering of exocytic vesicles to the PM,EXO70G1 exhibits continuous recycling foci at the PM,and its dynamic behavior is akin to that of SEC6 and SEC8.Disruption of EXO70G1 and its homolog EXO70G2 in Arabidopsis reduces auxin accumulation and primary root length.Importantly,the recycling of PIN2 from the brefeldin A(BFA)compartment to the PM is compromised,and the abundance of PIN2 at the PM is reduced in the exo70G1 exo70G2 backgrounds.Interestingly,live-cell imaging reveals that the polarity of EXO70G1 is established during cytokinesis,prior to that of PIN2,and is maintained throughout the subsequent phases of cell elongation and differentiation.When the lipid raft was disturbed,the accumulation of EXO70G1 at the PM decreased.Our findings highlight the crucial role of EXO70G1 in root development by providing positional cues that facilitate the recycling efficiency of PIN2 to the PM.展开更多
The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structur...The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structures,manual visual inspection,short inspection window times,and limited GPS positioning accuracy.To address these issues,this paper proposes a deep learning-based method for detecting and locating stator surface damage.This study establishes a maglev track stator surface image dataset,trains different object detection models,and compares their performance.Ultimately,YOLO and ByteTrack object tracking algorithms were chosen as the basic framework and enhanced to achieve automatic identification of high-speed maglev track stator surface damage images and track and count stator surface localization feature images.By matching the identified damaged images with their corresponding stator segment and beam segment sequence numbers,the location of the damage is pinpointed to the corresponding stator segment,enabling rapid and accurate identification and localization of complex damage to the maglev track stator surface.展开更多
Controllable synthesis of ultrathin metallene nanosheets and rational design of their spatial arrangement in favor of electrochemical catalysis are critical for their renewable energy applications.Here,a biomimetic de...Controllable synthesis of ultrathin metallene nanosheets and rational design of their spatial arrangement in favor of electrochemical catalysis are critical for their renewable energy applications.Here,a biomimetic design of“Trunk-Branch-Leaf”strategy is proposed to prepare the ultrathin edge-riched Zn-ene“leaves”with a thickness of~2.5 nm,adjacent Zn-ene cross-linked with each other,which are supported by copper nanoneedle“branches”on copper mesh“trunks,”named as Zn-ene/Cu-CM.The resulting superstructure enables the formation of an interconnected network and multiple channels,which can be used as an electrocatalytic CO_(2) reduction reaction(CO_(2)RR)electrode to allow a fast charge and mass transfer as well as a large electrolyte reservoir.By virtue of the distinctive structure,the obtained Zn-ene/Cu-CM electrode exhibits excellent selectivity and activity toward CO production with a maximum Faradaic efficiency of 91.3%and incredible partial current density up to 40 mA cm^(−2),outperforming most of the state-of-the-art Zn-based electrodes for CO_(2) reduction.The phenolphthalein color probe combined with in situ attenuated total reflection-infrared spectroscopy uncovered the formation of the localized pseudo-alkaline microenvironment at the interface of the Zn-ene/Cu-CM electrode.Theoretical calculations confirmed that the localized pH as the origin is responsible for the adsorption of CO_(2) at the interface and the generation of *COOH and *CO intermediates.This study offers valuable insights into developing efficient electrodes through synergistic regulation of reaction microenvironments and active sites,thereby facilitating the electrolysis of practical CO_(2) conversion.展开更多
BACKGROUND The liver represents a common site of distant metastasis in patients with esophageal cancer(EC).Conventional chemotherapy(CMT)presents limited efficacy for EC,and EC patients with liver metastases typically...BACKGROUND The liver represents a common site of distant metastasis in patients with esophageal cancer(EC).Conventional chemotherapy(CMT)presents limited efficacy for EC,and EC patients with liver metastases typically experience a poor prognosis,highlighting an urgent need to explore novel treatment approaches.This study evaluated the overall efficacy and safety of CMT vs CMT combined with immune checkpoint inhibitors(ICIs)in the treatment of EC patients with liver metastases.Furthermore,prognostic factors influencing outcomes in this patient population were identified.AIM To evaluate the efficacy and safety of first-line chemoimmunotherapy for EC patients with liver metastases and to analyze prognostic factors.METHODS This retrospective study included 126 EC patients with liver metastases at Zhejiang Cancer Hospital between 2014 and 2024.Patients receiving CMT were compared with those receiving CMT+ICI.Analyzed variables included clinicopathological features,treatment history,characteristics of metastasis,systemic and local treatments,overall survival(OS),and treatment-related adverse events(TRAEs).Prognostic factors were evaluated using univariate and multivariate Cox proportional-hazards regression models.Finally,efficacy outcomes and TRAE profiles were compared between the two groups.RESULTS A significant difference in median OS was identified between the two groups(10.8 months in the CMT group vs 20.8 months in the CMT+ICI group,P=0.004).The CMT+ICI group also demonstrated a significantly longer median progression-free survival of 11.7 months(P<0.001).Patients receiving combination therapy exhibited significantly improved systemic objective response rate and disease control rate.Multivariate analysis identified key factors significantly influencing OS in EC patients with liver metastases:Karnofsky Performance Status score≥70,receipt of local therapy for liver metastases,and the number of cycles of CMT and immunotherapy received.Furthermore,the incidence of TRAEs did not significantly differ between the CMT+ICI and CMT groups.CONCLUSION For EC patients with liver metastases,the combination of CMT and ICIs demonstrates significantly superior efficacy compared with CMT alone,while maintaining manageable TRAEs.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Supported by Scientific Research Fund of Zhejiang Provincial Education Department(Y202457020).
文摘Timely acquisition of chicken behavioral information is crucial for assessing chicken health status and production performance.Video-based behavior recognition has emerged as a primary technique for obtaining such information due to its accuracy and robustness.Video-based models generally predict a single behavior from a single video segment of a fixed duration.However,during periods of high activity in poultry,behavior transition may occur within a video segment,and existing models often fail to capture such transitions effectively.This limitation highlights the insufficient temporal resolution of video-based behavior recognition models.This study presents a chicken behavior recognition and localization model,CBLFormer,which is based on spatiotemporal feature learning.The model was designed to recognize behaviors that occur before and after transitions in video segments and to localize the corresponding time interval for each behavior.An improved transformer block,the cascade encoder-decoder network(CEDNet),a transformer-based head,and weighted distance intersection over union(WDIoU)loss were integrated into CBLFormer to enhance the model's ability to distinguish between different behavior categories and locate behavior boundaries.For the training and testing of CBLFormer,a dataset was created by collecting videos from 320 chickens across different ages and rearing densities.The results showed that CBLFormer achieved a mAP@0.5:0.95 of 98.34%on the test set.The integration of CEDNet contributed the most to the performance improvement of CBLFormer.The visualization results confirmed that the model effectively captured the behavioral boundaries of chickens and correctly recognized behavior categories.The transfer learning results demonstrated that the model is applicable to chicken behavior recognition and localization tasks in real-world poultry farms.The proposed method handles cases where poultry behavior transitions occur within the video segment and improves the temporal resolution of video-based behavior recognition models.
基金supported by the National Natural Science Foundation of China(No.62276204)the Fundamental Research Funds for the Central Universities,China(No.YJSJ24011)+1 种基金the Natural Science Basic Research Program of Shaanxi,China(Nos.2022JM-340 and 2023-JC-QN-0710)the China Postdoctoral Science Foundation(Nos.2020T130494 and 2018M633470)。
文摘Visible and infrared(RGB-IR)fusion object detection plays an important role in security,disaster relief,etc.In recent years,deep-learning-based RGB-IR fusion detection methods have been developing rapidly,but still struggle to deal with the complex and changing scenarios captured by drones,mainly due to two reasons:(A)RGB-IR fusion detectors are susceptible to inferior inputs that degrade performance and stability.(B)RGB-IR fusion detectors are susceptible to redundant features that reduce accuracy and efficiency.In this paper,an innovative RGB-IR fusion detection framework based on global-local feature optimization,named GLFDet,is proposed to improve the detection performance and efficiency of drone-captured objects.The key components of GLFDet include a Global Feature Optimization(GFO)module,a Local Feature Optimization(LFO)module and a Channel Separation Fusion(CSF)module.Specifically,GFO calculates the information content of the input image from the frequency domain and optimizes the features holistically.Then,LFO dynamically selects high-value features and filters out low-value features before fusion,which significantly improves the efficiency of fusion.Finally,CSF fuses the RGB and IR features across the corresponding channels,which avoids the rearrangement of the channel relationships and enhances the model stability.Extensive experimental results show that the proposed method achieves the best performance on three popular RGB-IR datasets Drone Vehicle,VEDAI,and LLVIP.In addition,GLFDet is more lightweight than other comparable models,making it more appealing to edge devices such as drones.The code is available at https://github.com/lao chen330/GLFDet.
文摘The laboratory established an efficient reversed-phase ultra-high-performance liquid chromatographyquadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS)qualitative method for screening more than 2000 kinds of risk substances(including local anesthetics,LAs)in cosmetics,which has been successfully applied in the analysis of actual samples.This work aims to develop a more convenient high performance liquid chromatography triple quadrupole mass spectrometry(HPLC-QQQ-MS/MS)method for the quantitative determination of LAs.Samples were ultrasonically extracted with methanol,separated on an Agilent Poroshell 120 EC-C18 column(2.1 mm×100 mm,2.7μm),and eluted with a gradient mobile phase consisting of 0.1%formic acid aqueous solution and methanol.Quantification was performed using the external standard method.The results show that all 23 LAs are effectively separated within 12 minutes,with good linearity in the corresponding concentration ranges and the correlation coefficients all greater than 0.99.The limits of detection(LOD)range from 0.0025 to 0.05μg/g,and the limits of quantification(LOQ)range from 0.01 to 0.1μg/g.The average recoveries of the 23 LAs in 5 blank cosmetic matrices are 80.68%-117.57%,with the relative standard deviations(RSDs)less than 5.98%.This method has good precision and high accuracy,and is suitable for the determination of LAs in 5 cosmetic matrices.
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.
文摘Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevations along the mid-sagittal plane further contribute to a three-dimensional auditory experience.This study aimed to characterize the variability in vertical sound localization abilities among normal-hearing(NH)individuals using spatialized audio.Materials and Methods:Fifty-one NH participants(aged 18 to 35 years)completed three vertical localization tasks under headphones as part of a single-group,within-subject experimental study.These tasks included two-plane identification:(1)top-down localization,(2)front-back localization,and one discrimination task in the front plane.Hierarchical Cluster Analysis(HCA)was employed to identify distinct patterns in spatial localization profiles specific to the vertical-median plane.Fisher's Discriminant Function Analysis(FDA)was used to validate the accuracy of HCA and estimate classification error.Results:HCA revealed three distinct listener clusters:(1)cluster 1 with good performance across all three tasks,(2)cluster 2 with selective impairment in top-bottom identification,and(3)cluster 3 with selective deficits in front-back identification.FDA validated group membership of the clusters identified by the HCA,with a prediction accuracy of 98%.Conclusions:Individuals with clinically NH exhibited three distinct vertical localization profiles:uniform performers,those impaired in top-bottom identification,and those impaired in front-back identification.These profiles may be linked to the interplay between acoustic and non-acoustic perceptual factors.
文摘BEIJING,Feb.25(Xinhua)-In a territory more than twice the size of the European Union and where per capita GDP varies up to fourfold across provincia level regions,the challenge of modernizing China with the right solutions for diverse localities has become a test of governance wisdom.
基金funded by Ongoing Research Funding Program for Project number(ORF-2025-648),King Saud University,Riyadh,Saudi Arabia.
文摘Heart disease remains a leading cause of mortality worldwide,emphasizing the urgent need for reliable and interpretable predictive models to support early diagnosis and timely intervention.However,existing Deep Learning(DL)approaches often face several limitations,including inefficient feature extraction,class imbalance,suboptimal classification performance,and limited interpretability,which collectively hinder their deployment in clinical settings.To address these challenges,we propose a novel DL framework for heart disease prediction that integrates a comprehensive preprocessing pipeline with an advanced classification architecture.The preprocessing stage involves label encoding and feature scaling.To address the issue of class imbalance inherent in the personal key indicators of the heart disease dataset,the localized random affine shadowsampling technique is employed,which enhances minority class representation while minimizing overfitting.At the core of the framework lies the Deep Residual Network(DeepResNet),which employs hierarchical residual transformations to facilitate efficient feature extraction and capture complex,non-linear relationships in the data.Experimental results demonstrate that the proposed model significantly outperforms existing techniques,achieving improvements of 3.26%in accuracy,3.16%in area under the receiver operating characteristics,1.09%in recall,and 1.07%in F1-score.Furthermore,robustness is validated using 10-fold crossvalidation,confirming the model’s generalizability across diverse data distributions.Moreover,model interpretability is ensured through the integration of Shapley additive explanations and local interpretable model-agnostic explanations,offering valuable insights into the contribution of individual features to model predictions.Overall,the proposed DL framework presents a robust,interpretable,and clinically applicable solution for heart disease prediction.
文摘Local residents,artists,and entrepreneurs who converge on Haikou’s historical Qilou Street are contributing to a new chapter in the story of Hainan’s opening-up.MORE than 100 years ago,the area alongQilou(Sotto Portico)Street in Haikou,capital of Hainan Province,served asthe embarkation point for Hainanesesetting out on their maritime voyages to seek greener pastures.
文摘BACKGROUND Data comparing the outcomes of hepatocellular carcinoma(HCC)ablation by multibipolar radiofrequency ablation(mbp-RFA)and microwave ablation(MWA)are lacking.This study compares safety and efficacy of the two techniques in treatment-naive HCC.AIM To compare the risk of local tumor progression(LTP)according to the technique;secondary endpoints included technique efficacy rate at one-month,overall survival and major complication rate.METHODS A bi-institutional retrospective analysis of patients undergoing treatment-naive HCC ablation by either technique was performed.Inverse probability of treatment weighting was used to compare the two groups.Mixed effects multivariate Cox regression was applied to identify risk factors for LTP.RESULTS A total of 362 patients(mean age,66.1±6.2 years,308 men)were included,of which 242(323 tumors)treated by mbp-RFA and 120(168 tumors)by MWA.After a median follow-up of 27 months,cumulative LTP was 11.4%after mbp-RFA and 25.2%after MWA.Independent risk factors for LTP at multivariate analysis were MWA(hazard ratio=2.85,P<0.001)and tumor size(hazard ratio=1.08,P<0.001).Two-year LTP-free survival was higher after mbp-RFA than MWA regardless of size(<3 cm:96%vs 87.1%,P<0.01;≥3 cm:87.5%vs 74%,P=0.04).Technique efficacy rate was higher after mbp-RFA(94.1%vs 87.5%,P=0.01).No difference was observed in major complication rate(9.5%vs 7.5%,P=0.59),nor 5-year overall survival(63.6%vs 58.3%,P=0.33).CONCLUSION Mbp-RFA leads to better local tumor control of treatment-naïve HCC than MWA regardless of tumor size and has better primary efficacy,while maintaining a comparable safety profile.
基金supported by National Natural Science Foundation of China(31571467)Shandong Province Natural Science Foundation(ZR2021MC141)。
文摘Cellular asymmetry,which represents a fundamental characteristic of cell polarity,is prominently illustrated by the apical-basal localization of PINFORMED(PIN)auxin efflux carriers in Arabidopsis thaliana.Although the maintenance of PIN polarity at the plasma membrane(PM)relies on endomembrane trafficking,the pivotal factors responsible for recruiting PIN proteins to the PM remain largely unknown.In this study,we discover that EXO70G1displays a polarized distribution at the PM in root cells.Acting as a putative subunit of the exocyst complex,which mediates the tethering of exocytic vesicles to the PM,EXO70G1 exhibits continuous recycling foci at the PM,and its dynamic behavior is akin to that of SEC6 and SEC8.Disruption of EXO70G1 and its homolog EXO70G2 in Arabidopsis reduces auxin accumulation and primary root length.Importantly,the recycling of PIN2 from the brefeldin A(BFA)compartment to the PM is compromised,and the abundance of PIN2 at the PM is reduced in the exo70G1 exo70G2 backgrounds.Interestingly,live-cell imaging reveals that the polarity of EXO70G1 is established during cytokinesis,prior to that of PIN2,and is maintained throughout the subsequent phases of cell elongation and differentiation.When the lipid raft was disturbed,the accumulation of EXO70G1 at the PM decreased.Our findings highlight the crucial role of EXO70G1 in root development by providing positional cues that facilitate the recycling efficiency of PIN2 to the PM.
基金supported in part by the National Natural Science Foundation of China under Grant 52432012in part by the Shanghai Science and Technology Project with 25ZR1402508。
文摘The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structures,manual visual inspection,short inspection window times,and limited GPS positioning accuracy.To address these issues,this paper proposes a deep learning-based method for detecting and locating stator surface damage.This study establishes a maglev track stator surface image dataset,trains different object detection models,and compares their performance.Ultimately,YOLO and ByteTrack object tracking algorithms were chosen as the basic framework and enhanced to achieve automatic identification of high-speed maglev track stator surface damage images and track and count stator surface localization feature images.By matching the identified damaged images with their corresponding stator segment and beam segment sequence numbers,the location of the damage is pinpointed to the corresponding stator segment,enabling rapid and accurate identification and localization of complex damage to the maglev track stator surface.
基金supports of the National Natural Science Foundation of China(NSFC)(52021004,52394202)key project of the Joint Fund for Innovation and Development of Chongqing Natural Science Foundation(CSTB2022NSCQ-LZX0013)+1 种基金the National Natural Science Foundation of China(NSFC)(52301232,and 52476056)the Natural Science Foundation of Chongqing Province(2024NSCQ-MSX1109).
文摘Controllable synthesis of ultrathin metallene nanosheets and rational design of their spatial arrangement in favor of electrochemical catalysis are critical for their renewable energy applications.Here,a biomimetic design of“Trunk-Branch-Leaf”strategy is proposed to prepare the ultrathin edge-riched Zn-ene“leaves”with a thickness of~2.5 nm,adjacent Zn-ene cross-linked with each other,which are supported by copper nanoneedle“branches”on copper mesh“trunks,”named as Zn-ene/Cu-CM.The resulting superstructure enables the formation of an interconnected network and multiple channels,which can be used as an electrocatalytic CO_(2) reduction reaction(CO_(2)RR)electrode to allow a fast charge and mass transfer as well as a large electrolyte reservoir.By virtue of the distinctive structure,the obtained Zn-ene/Cu-CM electrode exhibits excellent selectivity and activity toward CO production with a maximum Faradaic efficiency of 91.3%and incredible partial current density up to 40 mA cm^(−2),outperforming most of the state-of-the-art Zn-based electrodes for CO_(2) reduction.The phenolphthalein color probe combined with in situ attenuated total reflection-infrared spectroscopy uncovered the formation of the localized pseudo-alkaline microenvironment at the interface of the Zn-ene/Cu-CM electrode.Theoretical calculations confirmed that the localized pH as the origin is responsible for the adsorption of CO_(2) at the interface and the generation of *COOH and *CO intermediates.This study offers valuable insights into developing efficient electrodes through synergistic regulation of reaction microenvironments and active sites,thereby facilitating the electrolysis of practical CO_(2) conversion.
基金Supported by National Natural Science Foundation of China,No.82303672Zhejiang Provincial Health Commission and Zhejiang Provincial Administration of Traditional Chinese Medicine through the Targeted Project for Medical and Health Research,No.2025ZL017and China Primary Health Care Foundation,No.ZLMY20240311001ZJ.
文摘BACKGROUND The liver represents a common site of distant metastasis in patients with esophageal cancer(EC).Conventional chemotherapy(CMT)presents limited efficacy for EC,and EC patients with liver metastases typically experience a poor prognosis,highlighting an urgent need to explore novel treatment approaches.This study evaluated the overall efficacy and safety of CMT vs CMT combined with immune checkpoint inhibitors(ICIs)in the treatment of EC patients with liver metastases.Furthermore,prognostic factors influencing outcomes in this patient population were identified.AIM To evaluate the efficacy and safety of first-line chemoimmunotherapy for EC patients with liver metastases and to analyze prognostic factors.METHODS This retrospective study included 126 EC patients with liver metastases at Zhejiang Cancer Hospital between 2014 and 2024.Patients receiving CMT were compared with those receiving CMT+ICI.Analyzed variables included clinicopathological features,treatment history,characteristics of metastasis,systemic and local treatments,overall survival(OS),and treatment-related adverse events(TRAEs).Prognostic factors were evaluated using univariate and multivariate Cox proportional-hazards regression models.Finally,efficacy outcomes and TRAE profiles were compared between the two groups.RESULTS A significant difference in median OS was identified between the two groups(10.8 months in the CMT group vs 20.8 months in the CMT+ICI group,P=0.004).The CMT+ICI group also demonstrated a significantly longer median progression-free survival of 11.7 months(P<0.001).Patients receiving combination therapy exhibited significantly improved systemic objective response rate and disease control rate.Multivariate analysis identified key factors significantly influencing OS in EC patients with liver metastases:Karnofsky Performance Status score≥70,receipt of local therapy for liver metastases,and the number of cycles of CMT and immunotherapy received.Furthermore,the incidence of TRAEs did not significantly differ between the CMT+ICI and CMT groups.CONCLUSION For EC patients with liver metastases,the combination of CMT and ICIs demonstrates significantly superior efficacy compared with CMT alone,while maintaining manageable TRAEs.
