As an important component of the stirling-type pulse tube cryocooler(SPTC),an efficient phase shifter can significantly improve the cooling capacity.Compared to the common phase shifter,the active warm displacer(AWD)h...As an important component of the stirling-type pulse tube cryocooler(SPTC),an efficient phase shifter can significantly improve the cooling capacity.Compared to the common phase shifter,the active warm displacer(AWD)has a wider phase adjustment range and therefore can obtain a better phase relationship easily.Based on a two-stage thermal-coupled SPTC operating in the 20 K range,this paper studied the influence of the swept volume ratio between the compressor and displacer.The research found that the swept volume ratio changes the cooling capacity and efficiency of the cryocooler mainly by changing the phase difference between the pressure wave and the volume flow at the cold end.It was found from the results of the simulation and experiments that there is an optimal displacement of the displacer(Xd)of 2.5 mm and an optimal phase angle of 15°to obtain the highest cooling efficiency while the displacement of the compressor is constant.The cooling capacity at 20 K is 1.3 W while the input electrical power of the second stage compressor is 202 W,which indicates an overall relative Carnot efficiency(rCOP)of 0.055 in terms of input electrical power.In addition,due to the reasonable setting of precooling temperature and capacity,the swept volume ratio and phase at the maximum cooling capacity and maximum efficiency are consistent in this study.The research improves the understanding of phase shifters and has guiding significance for the optimization of the SPTC working below 20 K.展开更多
Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Reg...Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.展开更多
Active landslides pose a significant threat globally,endangering lives and property.Effective monitoring and forecasting of displacements are essential for the timely warnings and mitigation of these events.Interferom...Active landslides pose a significant threat globally,endangering lives and property.Effective monitoring and forecasting of displacements are essential for the timely warnings and mitigation of these events.Interferometric synthetic aperture radar(InSAR)stands out as an efficient and prevalent tool for monitoring landslide deformation and offers new prospects for displacement prediction.However,challenges such as inherent limitation of satellite viewing geometry,long revisit cycles,and limited data volume hinder its application in displacement forecasting,notably for landslides with near-north-south deformation less detectable by InSAR.To address these issues,we propose a novel strategy for predicting three-dimensional(3D)landslide displacement,integrating InSAR and global navigation satellite system(GNSS)measurements with machine learning(ML).This framework first synergizes InSAR line-of-sight(LOS)results with GNSS horizontal data to reconstruct 3D displacement time series.It then employs ML models to capture complex nonlinear relationships between external triggers,landslide evolutionary states,and 3D displacements,thus enabling accurate future deformation predictions.Utilizing four advanced ML algorithms,i.e.random forest(RF),support vector machine(SVM),long short-term memory(LSTM),and gated recurrent unit(GRU),with Bayesian optimization(BO)for hyperparameter tuning,we applied this innovative approach to the north-facing,slow-moving Xinpu landslide in the Three Gorges Reservoir Area(TGRA)of China.Leveraging over 6.5 years of Sentinel-1 satellite data and GNSS measurements,our framework demonstrates satisfactory and robust prediction performance,with an average root mean square deviation(RMSD)of 9.62 mm and a correlation coefficient(CC)of 0.996.This study presents a promising strategy for 3D displacement prediction,illustrating the efficacy of integrating InSAR monitoring with ML forecasting in enhancing landslide early warning capabilities.展开更多
Bedding parallel stepped rock slopes exist widely in nature and are used in slope engineering.They are characterized by complex topography and geological structure and are vulnerable to shattering under strong earthqu...Bedding parallel stepped rock slopes exist widely in nature and are used in slope engineering.They are characterized by complex topography and geological structure and are vulnerable to shattering under strong earthquakes.However,no previous studies have assessed the mechanisms underlying seismic failure in rock slopes.In this study,large-scale shaking table tests and numerical simulations were conducted to delineate the seismic failure mechanism in terms of acceleration,displacement,and earth pressure responses combined with shattering failure phenomena.The results reveal that acceleration response mutations usually occur within weak interlayers owing to their inferior performance,and these mutations may transform into potential sliding surfaces,thereby intensifying the nonlinear seismic response characteristics.Cumulative permanent displacements at the internal corners of the berms can induce quasi-rigid displacements at the external corners,leading to greater permanent displacements at the internal corners.Therefore,the internal corners are identified as the most susceptible parts of the slope.In addition,the concept of baseline offset was utilized to explain the mechanism of earth pressure responses,and the result indicates that residual earth pressures at the internal corners play a dominant role in causing deformation or shattering damage.Four evolutionary deformation phases characterize the processes of seismic responses and shattering failure of the bedding parallel stepped rock slope,i.e.the formation of tensile cracks at the internal corners of the berm,expansion of tensile cracks and bedding surface dislocation,development of vertical tensile cracks at the rear edge,and rock mass slipping leading to slope instability.Overall,this study provides a scientific basis for the seismic design of engineering slopes and offers valuable insights for further studies on preventing seismic disasters in bedding parallel stepped rock slopes.展开更多
Mitigating vortex-induced vibrations(VIV)in flexible risers represents a critical concern in offshore oil and gas production,considering its potential impact on operational safety and efficiency.The accurate predictio...Mitigating vortex-induced vibrations(VIV)in flexible risers represents a critical concern in offshore oil and gas production,considering its potential impact on operational safety and efficiency.The accurate prediction of displacement and position of VIV in flexible risers remains challenging under actual marine conditions.This study presents a data-driven model for riser displacement prediction that corresponds to field conditions.Experimental data analysis reveals that the XGBoost algorithm predicts the maximum displacement and position with superior accuracy compared with Support vector regression(SVR),considering both computational efficiency and precision.Platform displacement in the Y-direction demonstrates a significant positive correlation with both axial depth and maximum displacement magnitude.The fourth point displacement exhibits the highest contribution to model prediction outcomes,showing a positive influence on maximum displacement while negatively affecting the axial depth of maximum displacement.Platform displacement in the X-and Y-directions exhibits competitive effects on both the riser’s maximum displacement and its axial depth.Through the implementation of XGBoost algorithm and SHapley Additive exPlanation(SHAP)analysis,the model effectively estimates the riser’s maximum displacement and its precise location.This data-driven approach achieves predictions using minimal,readily available data points,enhancing its practical field applications and demonstrating clear relevance to academic and professional communities.展开更多
The girder end restraint devices such as bearings and dampers on long span suspension bridge will deteriorate over time.However,it is difficult to achieve the quantitative assessment of the performance of the restrain...The girder end restraint devices such as bearings and dampers on long span suspension bridge will deteriorate over time.However,it is difficult to achieve the quantitative assessment of the performance of the restraint device through existing detection methods in actual inspections,making it difficult to obtain the impact of changes in the performance of the restraint device on the bridge structure.In this paper,a random vehicle load model is firstly established based on the WIM data of Jiangyin Bridge,and the displacement of girder end under the actual traffic flow is simulated by using finite element dynamic time history analysis.On this basis,according to the performance test data of the bearings and dampers,the performance degradation laws of the above two restraint devices are summarized,and the performance degradation process of the two restraint devices and the effects of different restraint parameters on the bridge structure are simulated.The results show that the performance degradation of the damper will significantly reduce the damping force at low speed,resulting in a significant increase in the cumulative displacement of the girder end;in the presence of longitudinal dampers,the increase in the friction coefficient caused by the deterioration of the bearing sliding plate has little effect on the cumulative displacement,but excessive wear of the bearing sliding plate adversely affects the structural dynamic performance.展开更多
Succinylcholine(SC)is a widely used depolarizing muscle relaxant,but improper use can lead to arrhythmias and,in severe cases,pose a life-threatening risk.Additionally,some criminals exploit SC for illicit activities....Succinylcholine(SC)is a widely used depolarizing muscle relaxant,but improper use can lead to arrhythmias and,in severe cases,pose a life-threatening risk.Additionally,some criminals exploit SC for illicit activities.Therefore,rapid SC detection is paramount for clinical practice and public safety.Currently,however,limited methods are available for the rapid detection of SC.A fluorescent indicator displacement assay sensor based on molecular recognition of an amide naphthotube was developed.This sensor enabled the rapid fluorescent detection of SC through competitive binding between SC and methylene blue with the amide naphthotube.The sensor exhibited exceptional sensitivity with a detection limit as low as 1.1μmol/L and a detection range of 1.1~60μmol/L,coupled with outstanding selectivity and robust stability.Furthermore,this sensor accurately determined SC levels in biological samples such as serum.In summary,this research provides a new solution for the rapid and accurate sensing of SC in complex matrices and offers new insights for the swift identification and detection of toxins.展开更多
Two international standards,ISO 18501:2025,Performance rating of positive displacement refrigerant compressor,and ISO 18483:2025,Performance rating of centrifugal refrigerant compressor,were released at an event held ...Two international standards,ISO 18501:2025,Performance rating of positive displacement refrigerant compressor,and ISO 18483:2025,Performance rating of centrifugal refrigerant compressor,were released at an event held by GREE and Hefei General Machinery Research Institute Co.,Ltd.in Zhuhai,South China’s Guangdong province on June 12.展开更多
Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps...Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.展开更多
To tackle the difficulties of the point prediction in quantifying the reliability of landslide displacement prediction,a data-driven combination-interval prediction method(CIPM)based on copula and variational-mode-dec...To tackle the difficulties of the point prediction in quantifying the reliability of landslide displacement prediction,a data-driven combination-interval prediction method(CIPM)based on copula and variational-mode-decomposition associated with kernel-based-extreme-learningmachine optimized by the whale optimization algorithm(VMD-WOA-KELM)is proposed in this paper.Firstly,the displacement is decomposed by VMD to three IMF components and a residual component of different fluctuation characteristics.The key impact factors of each IMF component are selected according to Copula model,and the corresponding WOA-KELM is established to conduct point prediction.Subsequently,the parametric method(PM)and non-parametric method(NPM)are used to estimate the prediction error probability density distribution(PDF)of each component,whose prediction interval(PI)under the 95%confidence level is also obtained.By means of the differential evolution algorithm(DE),a weighted combination model based on the PIs is built to construct the combination-interval(CI).Finally,the CIs of each component are added to generate the total PI.A comparative case study shows that the CIPM performs better in constructing landslide displacement PI with high performance.展开更多
Shape memory alloy(SMA)bars are currently preferred over elastomeric seismic isolators due to the elimination of degradation within effective damping and stiffness factors during the cyclic response of an isolation sy...Shape memory alloy(SMA)bars are currently preferred over elastomeric seismic isolators due to the elimination of degradation within effective damping and stiffness factors during the cyclic response of an isolation system.These bars could also be used to prevent the functionality of the isolator units from failing due to large deformations.This study aims to investigate the performance of a high damping rubber bearing(HDRB)isolator that is combined with two different types of SMA bars,i.e.,Nickel-Titanium(Ni-Ti)and Copper-Aluminum-Beryllium(Cu-Al-Be),subjected to near-fault ground motions that are characterized with forward directivity and fling step effects.To achieve this objective,a self-centering material with flag-shape,force-deformation hysteresis was utilized to simulate the behavior of SMA bars in OpenSees.A single degree of freedom(SDOF)system representing an isolated one-story shear building was developed to conduct nonlinear analysis under selected ground motions.The SMA bars were introduced as an X-shape within the model and were connected diagonally to the top and bottom of the isolator.Results showed that the HDRB system’s hysteretic response under near-fault ground accelerations experiences significant degradation,especially when near-fault motions involve the fling step effect.It was demonstrated that SMA bars effectively reduce large displacement observed in HDRB systems under near-fault earthquakes.Comparing the results of the base-isolated HDRB and SMA-HDRB subjected to selected ground motions demonstrated that maximum displacement was found to be significantly reduced by an average of 79%when SMA bars were used.Incorporating SMA bars with a larger diameter significantly improves the efficiency of SMA HDRB systems,and a reduction in maximum displacements is more pronounced for fling step,near-fault ground motions.展开更多
This research proposes an innovative solution to the inherent challenges faced by landslide displacement prediction models based on data-driven methods,such as the need for extensive historical datasets for training,t...This research proposes an innovative solution to the inherent challenges faced by landslide displacement prediction models based on data-driven methods,such as the need for extensive historical datasets for training,the reliance on manual feature selection,and the difficulty in effectively utilizing landslide historical data.We have developed a dual-channel deep learning prediction model that integrates multimodal decomposition and an attention mechanism to overcome these challenges and improve prediction performance.The proposed methodology follows a three-stage framework:(1)Empirical Mode Decomposition(EMD)effectively segregates cumulative displacement and feature factors;(2)We have developed a Double Exponential Smoothing(DES)ensemble optimized through a Non-dominated Sorting Genetic Algorithm-II(NSGA-II)to enhance trend prediction;while employing a Bidirectional Long Short-Term Memory-Radial Basis Function(BiLSTM-RBF)network enhanced by a hybrid attention mechanism,which facilitates a global-local synergistic approach to hierarchical feature extraction,thereby improving the prediction of periodic displacements;(3)A bidirectional adaptive feature extraction mechanism aligns attention weights with BiLSTM propagation paths through spatial mapping,complemented by an innovative loss function incorporating Prediction Interval(PI)width optimization.In the comparative experiments of the Baishuihe landslide:the RMSE,MAE,and R^(2) indexes of monitoring point ZG118 are improved by 19.8%,35.2%,and 3.2%compared with the optimal baseline model(RBF-MIC);in the monitoring point ZG93,where the amount of data is less,the three indexes are even more improved by 52.1%,32.3%,and 21.8%compared with the optimal baseline model(GRU-None).These results substantiate the model’s capacity to overcome dual constraints of data paucity and feature engineering limitations in geohazard prediction.展开更多
Acoustic communication signals are important for species recognition and mate attraction across numerous taxa.For instance,most of thethousands of species of frogs have a species-specifc advertisement call that female...Acoustic communication signals are important for species recognition and mate attraction across numerous taxa.For instance,most of thethousands of species of frogs have a species-specifc advertisement call that females use to localize and discriminate among potential mates.Thus,the acoustic structure of the advertisement call is critical for reproductive success.The acoustic structure of calls will generally divergeover evolutionary time and can be infuenced by the calls of sympatric species.While many studies have shown the infuence of geographyon contemporary call variation in populations of frogs,no study has compared the acoustic structure of frog calls across many species to askwhether we can detect an infuence of divergence time and overall geographic overlap on the differences in acoustic structure of species-typicalcalls that we observe now.To this end,we compared acoustic features of the calls of 225 species of frogs within 4 families.Furthermore,weused a behavioral assay from 1 species of frog to determine which acoustic features to prioritize in our large-scale analyses.We found evidencethat both phylogeny(time)and geography(place)relate to advertisement call acoustics albeit with large variation in these relationships acrossthe 4 families in the analysis.Overall,these results suggest that,despite the many ecological and evolutionary forces that infuence call structure,the broad forces of time and place can shape aspects of advertisement call acoustics.展开更多
Irradiation experiments on p-Ga N gate high-electron-mobility transistors(HEMTs) were conducted using neutrons at Back-streaming White Neutron(Back-n) facility at the China Spallation Neutron Source(CSNS).Two groups o...Irradiation experiments on p-Ga N gate high-electron-mobility transistors(HEMTs) were conducted using neutrons at Back-streaming White Neutron(Back-n) facility at the China Spallation Neutron Source(CSNS).Two groups of devices were float-biased,while one group was ON-biased.Post-irradiation analysis revealed that the electrical performance of the devices exhibited progressive degradation with increasing Back-n fluence,with the ON-biased group demonstrating the most pronounced deterioration.This degradation was primarily characterized by a negative shift in the threshold voltage,a significant increase in reverse gate leakage current,and a slight reduction in forward gate leakage.Further analysis of the gate leakage current and capacitance-voltage characteristics indicated an elevated concentration of two-dimensional electron gas(2DEG),attributed to donor-type defects introduced within the barrier layer by Back-n irradiation.These defects act as hole traps,converting into fixed positive charges that deepen the quantum-well conduction band,thereby enhancing the 2DEG density.Additionally,through the trap-assisted tunneling mechanism,these defects serve as tunneling centers,increasing the probability of electron tunneling and consequently elevating the reverse gate leakage current.展开更多
Vertical position changes of ground-based Global Navigation Satellite System(GNSS) stations have been used to study regional terrestrial water storage(TWS) changes. However, the feasibility is still unclear in many ar...Vertical position changes of ground-based Global Navigation Satellite System(GNSS) stations have been used to study regional terrestrial water storage(TWS) changes. However, the feasibility is still unclear in many areas due to diverse local effects. This study aims to evaluate the capability of GNSS vertical displacements in monitoring hydrological variations in four climate settings over Chinese mainland. The spatial and temporal variations of hydrological load-induced(HYDL) vertical displacements at 208 GNSS sites during 2011-2020 were analyzed by comparing with Gravity Recovery and Climate Experiment(GRACE)/GRACE Follow-On(GFO) and Global Land Data Assimilation System(GLDAS) derived TWS changes. The results indicate that GNSS vertical positions show different capabilities in capturing seasonal and non-seasonal hydrological dynamics in different climate regions. Among the four climatic settings, the subtropical monsoon climate(SMC) region, with the largest deformation fluctuation(the regional mean root mean square(RMS) is 7.97 mm), has the highest regional mean HYDL-GRACE and HYDL-GLDAS anti-correlation coefficients(CCs) of-0.47 and-0.45 at the seasonal scale, respectively. For the individual GNSS site, the number of the sites with CC <-0.40 between HYDL and GRACE/GLDASderived TWS changes accounts for 55.1% and 55.1%(SMC), 13.0% and 7.4%(temperate monsoon climate, TMC), 6.7% and 13.3%(temperate continental climate, TCC), 32.3% and 38.7%(plateau climate,PC), respectively. For the non-seasonal term, although the proportion with CC <-0.40 in each climate type decreases mainly due to the influence of local geodynamic and human activities, especially in the SMC and PC regions, GNSS site vertical deformations still show good capability in monitoring hydrological extremes. The results provide valuable information for better application of GNSS to hydrology.展开更多
License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation,which lead to pixel displacements.This article introduces a Displacement Region Recognition M...License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation,which lead to pixel displacements.This article introduces a Displacement Region Recognition Method(DR2M)to address such a problem.This method operates on displaced features compared to the training input observed throughout definite time frames.The technique focuses on detecting features that remain relatively stable under haze,using a frame-based analysis to isolate edges minimally affected by visual noise.The edge detection failures are identified using a bilateral neural network through displaced feature training.The training converges bilaterally towards the minimum edges from the maximum region.Thus,the training input and detected edges are used to identify the displacement between observed image frames to extract and differentiate the license plate region from the other vehicle regions.The proposed method maps the similarity feature between the detected and identified vehicle regions.This aids in leveraging the plate recognition precision with a high F1 score.Thus,this technique achieves a 10.27%improvement in identification precision,a 10.57%increase in F1 score,and a 9.73%reduction in false positive rate compared to baseline methods under maximum displacement conditions caused by haze.The technique attains an identification precision of 95.68%,an F1 score of 94.68%,and a false positive rate of 4.32%,indicating robust performance under haze-affected settings.展开更多
Diamond is a promising semiconductor material for future space exploration,owing to its unique atomic and electronic structures.However,diamond materials and related devices still suffer from irradiation damage under ...Diamond is a promising semiconductor material for future space exploration,owing to its unique atomic and electronic structures.However,diamond materials and related devices still suffer from irradiation damage under space irradiation involving high-energy irradiating particles.The study of the generation and evolution of point defects can help understand the irradiation damage mechanisms in diamond.This study systematically investigated the defect dynamics of diamond in 162 crystallographic directions uniformly selected on a spherical surface using molecular dynamics simulations,with primary knock-on atom(PKA)energies up to 20 keV,and temperatures ranging from 300 K to 1800 K.The results reveal that the displacement threshold energy of diamond changes periodically with crystallographic directions,which is related to the shape of potential energy surface along that direction.Additionally,the number of residual defects correlates positively with PKA energy.However,temperature has dual competing effects:while it enhances the probability of atomic displacement,it simultaneously suppresses the probability of defect formation by accelerating defect recombination.The calculation of sparse radial distribution function indicates that the defect distribution shows a certain degree of similarity in the short-range region across different PKA energies.As the PKA energy increases,defect clusters tend to become larger in size and more numerous in quantity.This study systematically investigates the anisotropy of displacement threshold energy and elucidates the relationship between various irradiation conditions and the final states of irradiation-induced defects.展开更多
AIM:To evaluate visual outcomes of pars plana vitrectomy(PPV)combined with tissue plasminogen activator(tPA)-induced clot lysis and pneumatic displacement for submacular hemorrhage(SMH)in a cohort of closed-globe trau...AIM:To evaluate visual outcomes of pars plana vitrectomy(PPV)combined with tissue plasminogen activator(tPA)-induced clot lysis and pneumatic displacement for submacular hemorrhage(SMH)in a cohort of closed-globe trauma patients.METHODS:A retrospective,multicenter interventional case series involving 7 eyes of 7 patients who underwent PPV with subretinal tPA administration for SMH secondary to closed-globe injury were conducted.The primary outcome measure was the change in Snellen visual acuity.RESULTS:The mean age of patients was 32y(range:21-51y),with a mean follow-up duration of 4.6mo(range:1.1-14.9mo).The average best-corrected visual acuity(BCVA)was 20/1020 at baseline and 20/114 at the final visit,respectively(P=0.025).Preoperative BCVA was not a significant predictor of final BCVA(r=0.102,P=0.827).Final BCVA did not differ significantly between patients who underwent PPV within 14d of symptom onset and those who underwent surgery after 14d(P=0.57).All eyes received SF6 or C3F8 gas tamponade.CONCLUSION:Surgical intervention involving tPAmediated clot lysis and pneumatic displacement may yield visual benefits in trauma-induced SMH without underlying retinal vascular disease;however,larger prospective studies are warranted to confirm these findings.展开更多
Africa’s Buildings:Architecture and the Displacement of Cultural Heritage By ITOHAN I.OSAYIMWESE Princeton University Press This book is a groundbreaking history that exposes the systematic looting of Africa’s archi...Africa’s Buildings:Architecture and the Displacement of Cultural Heritage By ITOHAN I.OSAYIMWESE Princeton University Press This book is a groundbreaking history that exposes the systematic looting of Africa’s architectural heritage by Western collectors,museums,and colonial officials.展开更多
Acoustic detection has many applications across science and technology from medicine to imaging and communications.However,most acoustic sensors have a common limitation in that the detection must be near the acoustic...Acoustic detection has many applications across science and technology from medicine to imaging and communications.However,most acoustic sensors have a common limitation in that the detection must be near the acoustic source.Alternatively,laser interferometry with picometer-scale motional displacement detection can rapidly and precisely measure sound-induced minute vibrations on remote surfaces.Here,we demonstrate the feasibility of sound detection up to 100 kHz at remote sites with≈60 m optical path length via laser homodyne interferometry.Based on our ultrastable hertz linewidth laser with 10-15 fractional stability,our laser interferometer achieves 0.5 pm/Hz1/2 displacement sensitivity near 10 kHz,bounded only by laser frequency noise over 10 kHz.Between 140 Hz and 15 kHz,we achieve a homodyne acoustic sensing sensitivity of subnanometer/Pascal across our conversational frequency overtones.The minimal sound pressure detectable over 60 m optical path length is≈2 mPa,with dynamic ranges over 100 dB.With the demonstrated standoff picometric distance metrology,we successfully detected and reconstructed musical scores of normal conversational volumes with high fidelity.The acoustic detection via this precision laser interferometer could be applied to selective area sound sensing for remote acoustic metrology,optomechanical vibrational motion sensing,and ultrasensitive optical microphones at the laser frequency noise limits.展开更多
基金supported by the National Natural Science Foundation of China(No.51806231)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB35000000).
文摘As an important component of the stirling-type pulse tube cryocooler(SPTC),an efficient phase shifter can significantly improve the cooling capacity.Compared to the common phase shifter,the active warm displacer(AWD)has a wider phase adjustment range and therefore can obtain a better phase relationship easily.Based on a two-stage thermal-coupled SPTC operating in the 20 K range,this paper studied the influence of the swept volume ratio between the compressor and displacer.The research found that the swept volume ratio changes the cooling capacity and efficiency of the cryocooler mainly by changing the phase difference between the pressure wave and the volume flow at the cold end.It was found from the results of the simulation and experiments that there is an optimal displacement of the displacer(Xd)of 2.5 mm and an optimal phase angle of 15°to obtain the highest cooling efficiency while the displacement of the compressor is constant.The cooling capacity at 20 K is 1.3 W while the input electrical power of the second stage compressor is 202 W,which indicates an overall relative Carnot efficiency(rCOP)of 0.055 in terms of input electrical power.In addition,due to the reasonable setting of precooling temperature and capacity,the swept volume ratio and phase at the maximum cooling capacity and maximum efficiency are consistent in this study.The research improves the understanding of phase shifters and has guiding significance for the optimization of the SPTC working below 20 K.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd..(Grant No.H20230317)。
文摘Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.
基金jointly supported by the International Research Center of Big Data for Sustainable Development Goals(Grant No.CBAS2022GSP02)the National Natural Science Foundation of China(Grant Nos.42072320 and 42372264).
文摘Active landslides pose a significant threat globally,endangering lives and property.Effective monitoring and forecasting of displacements are essential for the timely warnings and mitigation of these events.Interferometric synthetic aperture radar(InSAR)stands out as an efficient and prevalent tool for monitoring landslide deformation and offers new prospects for displacement prediction.However,challenges such as inherent limitation of satellite viewing geometry,long revisit cycles,and limited data volume hinder its application in displacement forecasting,notably for landslides with near-north-south deformation less detectable by InSAR.To address these issues,we propose a novel strategy for predicting three-dimensional(3D)landslide displacement,integrating InSAR and global navigation satellite system(GNSS)measurements with machine learning(ML).This framework first synergizes InSAR line-of-sight(LOS)results with GNSS horizontal data to reconstruct 3D displacement time series.It then employs ML models to capture complex nonlinear relationships between external triggers,landslide evolutionary states,and 3D displacements,thus enabling accurate future deformation predictions.Utilizing four advanced ML algorithms,i.e.random forest(RF),support vector machine(SVM),long short-term memory(LSTM),and gated recurrent unit(GRU),with Bayesian optimization(BO)for hyperparameter tuning,we applied this innovative approach to the north-facing,slow-moving Xinpu landslide in the Three Gorges Reservoir Area(TGRA)of China.Leveraging over 6.5 years of Sentinel-1 satellite data and GNSS measurements,our framework demonstrates satisfactory and robust prediction performance,with an average root mean square deviation(RMSD)of 9.62 mm and a correlation coefficient(CC)of 0.996.This study presents a promising strategy for 3D displacement prediction,illustrating the efficacy of integrating InSAR monitoring with ML forecasting in enhancing landslide early warning capabilities.
基金supported by the National Natural Science Foundation of China (Grant No.52108361)the Sichuan Science and Technology Program of China (Grant No.2023YFS0436)the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (Grant No.SKLGP2022Z015).
文摘Bedding parallel stepped rock slopes exist widely in nature and are used in slope engineering.They are characterized by complex topography and geological structure and are vulnerable to shattering under strong earthquakes.However,no previous studies have assessed the mechanisms underlying seismic failure in rock slopes.In this study,large-scale shaking table tests and numerical simulations were conducted to delineate the seismic failure mechanism in terms of acceleration,displacement,and earth pressure responses combined with shattering failure phenomena.The results reveal that acceleration response mutations usually occur within weak interlayers owing to their inferior performance,and these mutations may transform into potential sliding surfaces,thereby intensifying the nonlinear seismic response characteristics.Cumulative permanent displacements at the internal corners of the berms can induce quasi-rigid displacements at the external corners,leading to greater permanent displacements at the internal corners.Therefore,the internal corners are identified as the most susceptible parts of the slope.In addition,the concept of baseline offset was utilized to explain the mechanism of earth pressure responses,and the result indicates that residual earth pressures at the internal corners play a dominant role in causing deformation or shattering damage.Four evolutionary deformation phases characterize the processes of seismic responses and shattering failure of the bedding parallel stepped rock slope,i.e.the formation of tensile cracks at the internal corners of the berm,expansion of tensile cracks and bedding surface dislocation,development of vertical tensile cracks at the rear edge,and rock mass slipping leading to slope instability.Overall,this study provides a scientific basis for the seismic design of engineering slopes and offers valuable insights for further studies on preventing seismic disasters in bedding parallel stepped rock slopes.
基金The research work was financially supported by the National Natural Science Foundation of China(Grant Nos.51979238 and 52301338)the Sichuan Science and Technology Program(Grant Nos.2023NSFSC1953 and 2023ZYD0140).
文摘Mitigating vortex-induced vibrations(VIV)in flexible risers represents a critical concern in offshore oil and gas production,considering its potential impact on operational safety and efficiency.The accurate prediction of displacement and position of VIV in flexible risers remains challenging under actual marine conditions.This study presents a data-driven model for riser displacement prediction that corresponds to field conditions.Experimental data analysis reveals that the XGBoost algorithm predicts the maximum displacement and position with superior accuracy compared with Support vector regression(SVR),considering both computational efficiency and precision.Platform displacement in the Y-direction demonstrates a significant positive correlation with both axial depth and maximum displacement magnitude.The fourth point displacement exhibits the highest contribution to model prediction outcomes,showing a positive influence on maximum displacement while negatively affecting the axial depth of maximum displacement.Platform displacement in the X-and Y-directions exhibits competitive effects on both the riser’s maximum displacement and its axial depth.Through the implementation of XGBoost algorithm and SHapley Additive exPlanation(SHAP)analysis,the model effectively estimates the riser’s maximum displacement and its precise location.This data-driven approach achieves predictions using minimal,readily available data points,enhancing its practical field applications and demonstrating clear relevance to academic and professional communities.
基金supported by the National Key Research and Development Program of China(No.2022YFB3706704)the Academician Special Science Research Project of CCCC(No.YSZX-03-2022-01-B).
文摘The girder end restraint devices such as bearings and dampers on long span suspension bridge will deteriorate over time.However,it is difficult to achieve the quantitative assessment of the performance of the restraint device through existing detection methods in actual inspections,making it difficult to obtain the impact of changes in the performance of the restraint device on the bridge structure.In this paper,a random vehicle load model is firstly established based on the WIM data of Jiangyin Bridge,and the displacement of girder end under the actual traffic flow is simulated by using finite element dynamic time history analysis.On this basis,according to the performance test data of the bearings and dampers,the performance degradation laws of the above two restraint devices are summarized,and the performance degradation process of the two restraint devices and the effects of different restraint parameters on the bridge structure are simulated.The results show that the performance degradation of the damper will significantly reduce the damping force at low speed,resulting in a significant increase in the cumulative displacement of the girder end;in the presence of longitudinal dampers,the increase in the friction coefficient caused by the deterioration of the bearing sliding plate has little effect on the cumulative displacement,but excessive wear of the bearing sliding plate adversely affects the structural dynamic performance.
文摘Succinylcholine(SC)is a widely used depolarizing muscle relaxant,but improper use can lead to arrhythmias and,in severe cases,pose a life-threatening risk.Additionally,some criminals exploit SC for illicit activities.Therefore,rapid SC detection is paramount for clinical practice and public safety.Currently,however,limited methods are available for the rapid detection of SC.A fluorescent indicator displacement assay sensor based on molecular recognition of an amide naphthotube was developed.This sensor enabled the rapid fluorescent detection of SC through competitive binding between SC and methylene blue with the amide naphthotube.The sensor exhibited exceptional sensitivity with a detection limit as low as 1.1μmol/L and a detection range of 1.1~60μmol/L,coupled with outstanding selectivity and robust stability.Furthermore,this sensor accurately determined SC levels in biological samples such as serum.In summary,this research provides a new solution for the rapid and accurate sensing of SC in complex matrices and offers new insights for the swift identification and detection of toxins.
文摘Two international standards,ISO 18501:2025,Performance rating of positive displacement refrigerant compressor,and ISO 18483:2025,Performance rating of centrifugal refrigerant compressor,were released at an event held by GREE and Hefei General Machinery Research Institute Co.,Ltd.in Zhuhai,South China’s Guangdong province on June 12.
文摘Imbalanced multiclass datasets pose challenges for machine learning algorithms.They often contain minority classes that are important for accurate predictions.However,when the data is sparsely distributed and overlaps with data points fromother classes,it introduces noise.As a result,existing resamplingmethods may fail to preserve the original data patterns,further disrupting data quality and reducingmodel performance.This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling(NDESO),a hybridmethod that integrates a data displacement strategy with a resampling technique to achieve data balance.It begins by computing the average distance of noisy data points to their neighbors and adjusting their positions toward the center before applying random oversampling.Extensive evaluations compare 14 alternatives on nine classifiers across synthetic and 20 real-world datasetswith varying imbalance ratios.This evaluation was structured into two distinct test groups.First,the effects of k-neighbor variations and distance metrics are evaluated,followed by a comparison of resampled data distributions against alternatives,and finally,determining the most suitable oversampling technique for data balancing.Second,the overall performance of the NDESO algorithm was assessed,focusing on G-mean and statistical significance.The results demonstrate that our method is robust to a wide range of variations in these parameters and the overall performance achieves an average G-mean score of 0.90,which is among the highest.Additionally,it attains the lowest mean rank of 2.88,indicating statistically significant improvements over existing approaches.This advantage underscores its potential for effectively handling data imbalance in practical scenarios.
基金financially supported by the National Natural Science Foundation of China(Nos.42277149,41502299,41372306)the Research Planning of Sichuan Education Department,China(No.16ZB0105)+3 种基金the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project(Nos.SKLGP2016Z007,SKLGP2018Z017,SKLGP2020Z009)Chengdu University of Technology Young and Middle Aged Backbone Program(No.KYGG201720)Sichuan Provincial Science and Technology Department Program(No.19YYJC2087)China Scholarship Council。
文摘To tackle the difficulties of the point prediction in quantifying the reliability of landslide displacement prediction,a data-driven combination-interval prediction method(CIPM)based on copula and variational-mode-decomposition associated with kernel-based-extreme-learningmachine optimized by the whale optimization algorithm(VMD-WOA-KELM)is proposed in this paper.Firstly,the displacement is decomposed by VMD to three IMF components and a residual component of different fluctuation characteristics.The key impact factors of each IMF component are selected according to Copula model,and the corresponding WOA-KELM is established to conduct point prediction.Subsequently,the parametric method(PM)and non-parametric method(NPM)are used to estimate the prediction error probability density distribution(PDF)of each component,whose prediction interval(PI)under the 95%confidence level is also obtained.By means of the differential evolution algorithm(DE),a weighted combination model based on the PIs is built to construct the combination-interval(CI).Finally,the CIs of each component are added to generate the total PI.A comparative case study shows that the CIPM performs better in constructing landslide displacement PI with high performance.
基金Open Access funding enabled and organized by CAUL and its Member Institutions。
文摘Shape memory alloy(SMA)bars are currently preferred over elastomeric seismic isolators due to the elimination of degradation within effective damping and stiffness factors during the cyclic response of an isolation system.These bars could also be used to prevent the functionality of the isolator units from failing due to large deformations.This study aims to investigate the performance of a high damping rubber bearing(HDRB)isolator that is combined with two different types of SMA bars,i.e.,Nickel-Titanium(Ni-Ti)and Copper-Aluminum-Beryllium(Cu-Al-Be),subjected to near-fault ground motions that are characterized with forward directivity and fling step effects.To achieve this objective,a self-centering material with flag-shape,force-deformation hysteresis was utilized to simulate the behavior of SMA bars in OpenSees.A single degree of freedom(SDOF)system representing an isolated one-story shear building was developed to conduct nonlinear analysis under selected ground motions.The SMA bars were introduced as an X-shape within the model and were connected diagonally to the top and bottom of the isolator.Results showed that the HDRB system’s hysteretic response under near-fault ground accelerations experiences significant degradation,especially when near-fault motions involve the fling step effect.It was demonstrated that SMA bars effectively reduce large displacement observed in HDRB systems under near-fault earthquakes.Comparing the results of the base-isolated HDRB and SMA-HDRB subjected to selected ground motions demonstrated that maximum displacement was found to be significantly reduced by an average of 79%when SMA bars were used.Incorporating SMA bars with a larger diameter significantly improves the efficiency of SMA HDRB systems,and a reduction in maximum displacements is more pronounced for fling step,near-fault ground motions.
基金supported in part by the Guizhou Province Science Technology Support Plan([2024]General 007,[2022]General 264,[2023]General 096,[2023]General 412,and[2023]General 409)in part by the National Natural Science Foundation of China(Grant No.61861007)+2 种基金in part by the Guizhou Province Science and Technology Planning Project(ZK[2021]General 303)in part by the Project of GUIYANG HYDROPOWER INVESTIGATION DESIGN&RESEARCH INSTITUTE CHECC(YJ2022-12)in part by the Science and Technology Project of Power Construction Corporation of China,Ltd.(DJ-ZDXM-2022-44).
文摘This research proposes an innovative solution to the inherent challenges faced by landslide displacement prediction models based on data-driven methods,such as the need for extensive historical datasets for training,the reliance on manual feature selection,and the difficulty in effectively utilizing landslide historical data.We have developed a dual-channel deep learning prediction model that integrates multimodal decomposition and an attention mechanism to overcome these challenges and improve prediction performance.The proposed methodology follows a three-stage framework:(1)Empirical Mode Decomposition(EMD)effectively segregates cumulative displacement and feature factors;(2)We have developed a Double Exponential Smoothing(DES)ensemble optimized through a Non-dominated Sorting Genetic Algorithm-II(NSGA-II)to enhance trend prediction;while employing a Bidirectional Long Short-Term Memory-Radial Basis Function(BiLSTM-RBF)network enhanced by a hybrid attention mechanism,which facilitates a global-local synergistic approach to hierarchical feature extraction,thereby improving the prediction of periodic displacements;(3)A bidirectional adaptive feature extraction mechanism aligns attention weights with BiLSTM propagation paths through spatial mapping,complemented by an innovative loss function incorporating Prediction Interval(PI)width optimization.In the comparative experiments of the Baishuihe landslide:the RMSE,MAE,and R^(2) indexes of monitoring point ZG118 are improved by 19.8%,35.2%,and 3.2%compared with the optimal baseline model(RBF-MIC);in the monitoring point ZG93,where the amount of data is less,the three indexes are even more improved by 52.1%,32.3%,and 21.8%compared with the optimal baseline model(GRU-None).These results substantiate the model’s capacity to overcome dual constraints of data paucity and feature engineering limitations in geohazard prediction.
基金funded through a grant from the NationalScience Foundation(IOS-1914646)the SmithsonianInstitute Postdoctoral Fellowship program.
文摘Acoustic communication signals are important for species recognition and mate attraction across numerous taxa.For instance,most of thethousands of species of frogs have a species-specifc advertisement call that females use to localize and discriminate among potential mates.Thus,the acoustic structure of the advertisement call is critical for reproductive success.The acoustic structure of calls will generally divergeover evolutionary time and can be infuenced by the calls of sympatric species.While many studies have shown the infuence of geographyon contemporary call variation in populations of frogs,no study has compared the acoustic structure of frog calls across many species to askwhether we can detect an infuence of divergence time and overall geographic overlap on the differences in acoustic structure of species-typicalcalls that we observe now.To this end,we compared acoustic features of the calls of 225 species of frogs within 4 families.Furthermore,weused a behavioral assay from 1 species of frog to determine which acoustic features to prioritize in our large-scale analyses.We found evidencethat both phylogeny(time)and geography(place)relate to advertisement call acoustics albeit with large variation in these relationships acrossthe 4 families in the analysis.Overall,these results suggest that,despite the many ecological and evolutionary forces that infuence call structure,the broad forces of time and place can shape aspects of advertisement call acoustics.
基金supported by the National Natural Science Foundation of China (Grant Nos.12120101005,U2030104,12175174,11975174,and 12105229)State Key Laboratory Foundation of Laser Interaction with Matter (Grant Nos.SKLLIM1807 and SKLLIM2106)+1 种基金the Postdoctoral Fellowship Program of CPSF (Grant No.GZC20241372)National Key Laboratory of Intense Pulsed Radiation Simulation and Effect (Grant No.NKLIPR2419)。
文摘Irradiation experiments on p-Ga N gate high-electron-mobility transistors(HEMTs) were conducted using neutrons at Back-streaming White Neutron(Back-n) facility at the China Spallation Neutron Source(CSNS).Two groups of devices were float-biased,while one group was ON-biased.Post-irradiation analysis revealed that the electrical performance of the devices exhibited progressive degradation with increasing Back-n fluence,with the ON-biased group demonstrating the most pronounced deterioration.This degradation was primarily characterized by a negative shift in the threshold voltage,a significant increase in reverse gate leakage current,and a slight reduction in forward gate leakage.Further analysis of the gate leakage current and capacitance-voltage characteristics indicated an elevated concentration of two-dimensional electron gas(2DEG),attributed to donor-type defects introduced within the barrier layer by Back-n irradiation.These defects act as hole traps,converting into fixed positive charges that deepen the quantum-well conduction band,thereby enhancing the 2DEG density.Additionally,through the trap-assisted tunneling mechanism,these defects serve as tunneling centers,increasing the probability of electron tunneling and consequently elevating the reverse gate leakage current.
基金supported by National Natural Science Foundation of China(42064002,42004013,42204006)the GuangxiNatural Science Foundation of China(2024GXNSFDA010041)+5 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515010469)Guangxi Key Laboratory of Spatial Information and Geomatics(Grant no.21-238-21-05)the Open Fund of Hubei Luojia Laboratory(230100019,230100020)The GNSS observation data are provided by Crustal Movement Observation Network of China(CMONC)The GRACE/GFO mascon gravimetry data products are provided by NASA Jet Propulsion Laboratory/California Institute of TechnologyThe GLDAS data products are provided by NASA Earthdata.
文摘Vertical position changes of ground-based Global Navigation Satellite System(GNSS) stations have been used to study regional terrestrial water storage(TWS) changes. However, the feasibility is still unclear in many areas due to diverse local effects. This study aims to evaluate the capability of GNSS vertical displacements in monitoring hydrological variations in four climate settings over Chinese mainland. The spatial and temporal variations of hydrological load-induced(HYDL) vertical displacements at 208 GNSS sites during 2011-2020 were analyzed by comparing with Gravity Recovery and Climate Experiment(GRACE)/GRACE Follow-On(GFO) and Global Land Data Assimilation System(GLDAS) derived TWS changes. The results indicate that GNSS vertical positions show different capabilities in capturing seasonal and non-seasonal hydrological dynamics in different climate regions. Among the four climatic settings, the subtropical monsoon climate(SMC) region, with the largest deformation fluctuation(the regional mean root mean square(RMS) is 7.97 mm), has the highest regional mean HYDL-GRACE and HYDL-GLDAS anti-correlation coefficients(CCs) of-0.47 and-0.45 at the seasonal scale, respectively. For the individual GNSS site, the number of the sites with CC <-0.40 between HYDL and GRACE/GLDASderived TWS changes accounts for 55.1% and 55.1%(SMC), 13.0% and 7.4%(temperate monsoon climate, TMC), 6.7% and 13.3%(temperate continental climate, TCC), 32.3% and 38.7%(plateau climate,PC), respectively. For the non-seasonal term, although the proportion with CC <-0.40 in each climate type decreases mainly due to the influence of local geodynamic and human activities, especially in the SMC and PC regions, GNSS site vertical deformations still show good capability in monitoring hydrological extremes. The results provide valuable information for better application of GNSS to hydrology.
基金supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R848)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabiathe Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia for funding this research work through the project number“NBU-FFR-2025-2932-09”.
文摘License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation,which lead to pixel displacements.This article introduces a Displacement Region Recognition Method(DR2M)to address such a problem.This method operates on displaced features compared to the training input observed throughout definite time frames.The technique focuses on detecting features that remain relatively stable under haze,using a frame-based analysis to isolate edges minimally affected by visual noise.The edge detection failures are identified using a bilateral neural network through displaced feature training.The training converges bilaterally towards the minimum edges from the maximum region.Thus,the training input and detected edges are used to identify the displacement between observed image frames to extract and differentiate the license plate region from the other vehicle regions.The proposed method maps the similarity feature between the detected and identified vehicle regions.This aids in leveraging the plate recognition precision with a high F1 score.Thus,this technique achieves a 10.27%improvement in identification precision,a 10.57%increase in F1 score,and a 9.73%reduction in false positive rate compared to baseline methods under maximum displacement conditions caused by haze.The technique attains an identification precision of 95.68%,an F1 score of 94.68%,and a false positive rate of 4.32%,indicating robust performance under haze-affected settings.
基金supported by the Science and Technology Innovation Program of Hunan Province,China(Grant No.2021RC4026)the National Natural Science Foundation of China(Grant Nos.12204538,12104507,and 92365203)Hunan Provincial Science Fund for Distinguished Young Scholars(Grant No.2022JJ10060).
文摘Diamond is a promising semiconductor material for future space exploration,owing to its unique atomic and electronic structures.However,diamond materials and related devices still suffer from irradiation damage under space irradiation involving high-energy irradiating particles.The study of the generation and evolution of point defects can help understand the irradiation damage mechanisms in diamond.This study systematically investigated the defect dynamics of diamond in 162 crystallographic directions uniformly selected on a spherical surface using molecular dynamics simulations,with primary knock-on atom(PKA)energies up to 20 keV,and temperatures ranging from 300 K to 1800 K.The results reveal that the displacement threshold energy of diamond changes periodically with crystallographic directions,which is related to the shape of potential energy surface along that direction.Additionally,the number of residual defects correlates positively with PKA energy.However,temperature has dual competing effects:while it enhances the probability of atomic displacement,it simultaneously suppresses the probability of defect formation by accelerating defect recombination.The calculation of sparse radial distribution function indicates that the defect distribution shows a certain degree of similarity in the short-range region across different PKA energies.As the PKA energy increases,defect clusters tend to become larger in size and more numerous in quantity.This study systematically investigates the anisotropy of displacement threshold energy and elucidates the relationship between various irradiation conditions and the final states of irradiation-induced defects.
基金Supportea by DeNardo Education and Research Foundation GrantJeffrey T.Fort Innovation Fund+3 种基金Siteman Retina Research FundResearch to Prevent Blindness IncGetahun H is supported by Washington University in St.Louis School of Medicine Dean’s Medical Student Research Fellowship for the MD5 Yearlong Research ProgramGetahun H is also a recipient of a Research to Prevent Blindness Medical Student Eye Research Fellowship.
文摘AIM:To evaluate visual outcomes of pars plana vitrectomy(PPV)combined with tissue plasminogen activator(tPA)-induced clot lysis and pneumatic displacement for submacular hemorrhage(SMH)in a cohort of closed-globe trauma patients.METHODS:A retrospective,multicenter interventional case series involving 7 eyes of 7 patients who underwent PPV with subretinal tPA administration for SMH secondary to closed-globe injury were conducted.The primary outcome measure was the change in Snellen visual acuity.RESULTS:The mean age of patients was 32y(range:21-51y),with a mean follow-up duration of 4.6mo(range:1.1-14.9mo).The average best-corrected visual acuity(BCVA)was 20/1020 at baseline and 20/114 at the final visit,respectively(P=0.025).Preoperative BCVA was not a significant predictor of final BCVA(r=0.102,P=0.827).Final BCVA did not differ significantly between patients who underwent PPV within 14d of symptom onset and those who underwent surgery after 14d(P=0.57).All eyes received SF6 or C3F8 gas tamponade.CONCLUSION:Surgical intervention involving tPAmediated clot lysis and pneumatic displacement may yield visual benefits in trauma-induced SMH without underlying retinal vascular disease;however,larger prospective studies are warranted to confirm these findings.
文摘Africa’s Buildings:Architecture and the Displacement of Cultural Heritage By ITOHAN I.OSAYIMWESE Princeton University Press This book is a groundbreaking history that exposes the systematic looting of Africa’s architectural heritage by Western collectors,museums,and colonial officials.
基金supported by the Office of Naval Research(Grant Nos.N00014-16-1-2094 and N00014-24-1-2547)the Lawrence Livermore National Laboratory(Grant No.B622827)the National Science Foundation.Y.-S.J.acknowledges support from KRISS(Grant Nos.25011026 and 25011211).
文摘Acoustic detection has many applications across science and technology from medicine to imaging and communications.However,most acoustic sensors have a common limitation in that the detection must be near the acoustic source.Alternatively,laser interferometry with picometer-scale motional displacement detection can rapidly and precisely measure sound-induced minute vibrations on remote surfaces.Here,we demonstrate the feasibility of sound detection up to 100 kHz at remote sites with≈60 m optical path length via laser homodyne interferometry.Based on our ultrastable hertz linewidth laser with 10-15 fractional stability,our laser interferometer achieves 0.5 pm/Hz1/2 displacement sensitivity near 10 kHz,bounded only by laser frequency noise over 10 kHz.Between 140 Hz and 15 kHz,we achieve a homodyne acoustic sensing sensitivity of subnanometer/Pascal across our conversational frequency overtones.The minimal sound pressure detectable over 60 m optical path length is≈2 mPa,with dynamic ranges over 100 dB.With the demonstrated standoff picometric distance metrology,we successfully detected and reconstructed musical scores of normal conversational volumes with high fidelity.The acoustic detection via this precision laser interferometer could be applied to selective area sound sensing for remote acoustic metrology,optomechanical vibrational motion sensing,and ultrasensitive optical microphones at the laser frequency noise limits.
