Not many bathymetric maps are available for many lakes and reservoirs in developing countries. Usually the bathymetric mapping requires investment in expensive equipment and fieldwork, both of which are not accessible...Not many bathymetric maps are available for many lakes and reservoirs in developing countries. Usually the bathymetric mapping requires investment in expensive equipment and fieldwork, both of which are not accessible in these countries. This work demonstrates the ability to develop bathymetric map of Mosul Lake by using a digital elevation model (DEM). The depths model of the lake was designed through the use of three main stages;a coastline extraction, dataset interpolation and a triangular irregular network model. The normalized difference water index (NDWI) was used for automatic delineation of the lake coastline from satellite images. The ordinary kriging interpolation with a stable model was used to interpolate the water depths dataset. Finally a triangulated irregular network (TIN) model was used to visualize the resulting interpolation model. Calculated values of area and volume of a TIN model during 2011 were compared with values of supposed initial operation of the reservoir. The differences of water volume storage between these stages at 321 m water level was about 0.81 × 109 m3, where the lake lost around 10% of storage value. Also the results of depths lake model show that the change in water storage between March and July 2011 was about 3.08 × 109 m3.展开更多
Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
Spatial computing and augmented reality are advancing rapidly,with the goal of seamlessly blending virtual and physical worlds.However,traditional depth-sensing systems are bulky and energy-intensive,limiting their us...Spatial computing and augmented reality are advancing rapidly,with the goal of seamlessly blending virtual and physical worlds.However,traditional depth-sensing systems are bulky and energy-intensive,limiting their use in wearable devices.To overcome this,recent research by X.Liu et al.presents a compact binocular metalens-based depth perception system that integrates efficient edge detection through an advanced neural network.This system enables accurate,realtime depth mapping even in complex environments,enhancing potential applications in augmented reality,robotics,and autonomous systems.展开更多
Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level st...Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level stemming from the doped rare earth ion or intrinsic defects to the electronic structure of the host,and therefore thermoluminescence measurement becomes a radical technology in studying trap depth,which is one of the significant parameters that determine the properties of persistent luminescence and photostimulated luminescence.However,the results of trap depth obtained by different thermoluminescence methods are quite different so that they are not comparable.Herein,we analyzed different thermoluminescence methods,selected and improved the traditional peak position method of T_(m)/500 to be E=(-0.94Inβ+30.09)kT_(m).Only the experimental heating rate(β)is needed additionally,but the accuracy is improved greatly in most cases.This convenient and accurate method will accelerate the discovery of novel rare earth-doped materials.展开更多
对于复杂天气场景图像模糊、低对比度和颜色失真所导致的深度信息预测不准的问题,以往的研究均以标准场景的深度图作为先验信息来对该类场景进行深度估计。然而,这一方式存在先验信息精度较低等问题。对此,提出一个基于多尺度注意力机...对于复杂天气场景图像模糊、低对比度和颜色失真所导致的深度信息预测不准的问题,以往的研究均以标准场景的深度图作为先验信息来对该类场景进行深度估计。然而,这一方式存在先验信息精度较低等问题。对此,提出一个基于多尺度注意力机制的单目深度估计模型TalentDepth,以实现对复杂天气场景的预测。首先,在编码器中融合多尺度注意力机制,在减少计算成本的同时,保留每个通道的信息,提高特征提取的效率和能力。其次,针对图像深度不清晰的问题,基于几何一致性,提出深度区域细化(Depth Region Refinement,DSR)模块,过滤不准确的像素点,以提高深度信息的可靠性。最后,输入图像翻译模型所生成的复杂样本,并计算相应原始图像上的标准损失来指导模型的自监督训练。在NuScence,KITTI和KITTI-C这3个数据集上,相比于基线模型,所提模型对误差和精度均有优化。展开更多
Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(...Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.展开更多
Satellites in LEO (Low Earth Orbits) are closest to the Earth’s surface, having the smallest coverage area compared to other orbits, depending on altitude and elevation angle, and providing relatively too short visib...Satellites in LEO (Low Earth Orbits) are closest to the Earth’s surface, having the smallest coverage area compared to other orbits, depending on altitude and elevation angle, and providing relatively too short visibility and communication duration, in range of (2 - 15) minutes. Communication duration represents the key performance indicator for LEO satellite communication systems. For longer communication sessions, more satellites must be involved, and the signals must be handed over from one satellite to the next to provide uninterrupted real-time services to the appropriate user or ground station. This leads to the concept and structure of the satellites organized in the constellation. Communication window (visibility window) depends on the designed horizon plane width determined by licensed elevation angle. For the appropriate calculations, a satellite from the Starlink constellation at altitude of 550 km is considered, observed under licensed designed elevations of 40˚ and 25˚. Calculations under two designed elevation levels confirmed the wider horizon and consequently longer communication under the lower elevation.展开更多
BACKGROUND The incidence of acute myocardial infarction(AMI)is rising,with cardiac rupture accounting for approximately 2%of deaths in patients with acute ST-segment elevation myocardial infarction(STEMI).Ventricular ...BACKGROUND The incidence of acute myocardial infarction(AMI)is rising,with cardiac rupture accounting for approximately 2%of deaths in patients with acute ST-segment elevation myocardial infarction(STEMI).Ventricular free wall rupture(FWR)occurs in approximately 2%of AMI patients and is notably rare in patients with non-STEMI.Types of cardiac rupture include left ventricular FWR,ventricular septal rupture,and papillary muscle rupture.The FWR usually leads to acute cardiac tamponade or electromechanical dissociation,where standard resuscitation efforts may not be effective.Ventricular septal rupture and papillary muscle rupture often result in refractory heart failure,with mortality rates over 50%,even with surgical or percutaneous repair options.CASE SUMMARY We present a rare case of an acute non-STEMI patient who suffered sudden FWR causing cardiac tamponade and loss of consciousness immediate before undergoing coronary angiography.Prompt resuscitation and emergency open-heart repair along with coronary artery bypass grafting resulted in successful patient recovery.CONCLUSION This case emphasizes the risks of AMI complications,shares a successful treatment scenario,and discusses measures to prevent such complications.展开更多
Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a signi...Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a significant challenge faced in the field of computer vision.However,existing monocular video depth estimation models tend to produce blurred or inaccurate depth information in regions with object edges and low texture.To address this issue,we propose a monocular depth estimation model architecture guided by semantic segmentation masks,which introduces semantic information into the model to correct the ambiguous depth regions.We have evaluated the proposed method,and experimental results show that our method improves the accuracy of edge depth,demonstrating the effectiveness of our approach.展开更多
Allium stracheyi(Baker)is widely utilized as a culinary herb and is typically encountered in the higher elevations of the Himalayas.Consequently,it is of great significance to compare the ecological adaptability of th...Allium stracheyi(Baker)is widely utilized as a culinary herb and is typically encountered in the higher elevations of the Himalayas.Consequently,it is of great significance to compare the ecological adaptability of this indigenous species to alternative habitats and its introduction into new environments.This research aims to investigate and gain a comprehensive understanding of A.stracheyi,also known as faran,in Uttarakhand region.We aim to examine how this plant adapts morphologically,physiologically,biochemically,and anatomically to varying elevations,specifically at 550,2200,2460,and 3400 m above mean sea level(m AMSL).This plant demonstrated remarkable morphophysiological adjustments across various aspects of its development,encompassing modified growth patterns,alterations in leaf dimensions,leaf count,etc..Moreover,biochemical adaptations have been identified as pivotal in bolstering the plant resilience to the stress associated with higher elevation.Enzymes like superoxide dismutase(SOD)and peroxidase(POD)exhibited significant responsiveness to elevational variations,contributing to the plant's ability to confront the challenges posed by high-elevational conditions.In terms of anatomy,the plant manifested alterations in its leaf and vascular tissues along the elevational gradient.These modifications involve an increased density of stomata and a greater count of vascular bundles,optimizing gas exchange and adaptation to water stress in frequently encountered harsh environmental conditions at higher elevations.Understanding the adaptive mechanisms employed by A.stracheyi provides valuable insights,especially in forecasting how A.stracheyi might respond to global climate change,particularly in regions affected by habitat fragmentation.展开更多
Forests exert significant biogeophysical cooling effects(CE)through processes such as increased evapotranspiration,reduced albedo,and enhanced surface roughness.However,little is known about the extent to which elevat...Forests exert significant biogeophysical cooling effects(CE)through processes such as increased evapotranspiration,reduced albedo,and enhanced surface roughness.However,little is known about the extent to which elevation-induced temperature differences bias the observed CE and how this bias interacts with the underlying biogeophysical mechanisms.In this study,we integrated multisensor remote sensing products and Shuttle Radar Topography Mission(SRTM)elevation data on the Google Earth Engine(GEE)platform,and applied a spatial-temporal window regression approach to quantify and correct the sensitivity of land surface temperature(LST)to elevation for forest pixels across China from 2001 to 2022.First,we found that forest LST exhibited a significant negative relationship with elevation,leading to systematic CE overestimation by 0.61 K during the day and 0.60 K at night compared with altitudecorrected CE values.Second,after correction,the CE showed clear spatial heterogeneity,with stronger daytime cooling in tropical(-0.54 K)and temperate forests(-0.24 K),and warming in cold(+0.11 K)and arid regions(+0.53 K),while most regions experienced nighttime warming.Among forest types,evergreen needleleaf forests(ENF)exhibited the strongest daytime cooling(-0.36 K),whereas deciduous broadleaf(DBF)and open shrublands(OS)tended to warm.Third,mechanism analysis revealed that elevation correction strengthened the correlations of CE with leaf area index(LAI)and evapotranspiration,while maintaining a significant negative correlation with albedo,indicating that both radiative and non-radiative processes jointly shape the unbiased CE.These findings provide a more accurate quantification of forest CE by eliminating elevation-induced bias,which providing a more accurate assessment of the climate mitigation potential of forests,which is crucial for developing more effective forest management and ecological restoration strategies.展开更多
自监督单目深度估计受到了国内外研究人员的广泛关注。现有基于深度学习的自监督单目深度估计方法主要采用编码器-解码器结构。然而,这些方法在编码过程中对输入图像进行下采样操作,导致部分图像信息,尤其是图像的边界信息丢失,进而影...自监督单目深度估计受到了国内外研究人员的广泛关注。现有基于深度学习的自监督单目深度估计方法主要采用编码器-解码器结构。然而,这些方法在编码过程中对输入图像进行下采样操作,导致部分图像信息,尤其是图像的边界信息丢失,进而影响深度图的精度。针对上述问题,提出一种基于拉普拉斯金字塔的自监督单目深度估计方法(Self-supervised Monocular Depth Estimation Based on the Laplace Pyramid,LpDepth)。此方法的核心思想是:首先,使用拉普拉斯残差图丰富编码特征,以弥补在下采样过程中丢失的特征信息;其次,在下采样过程中使用最大池化层突显和放大特征信息,使编码器在特征提取过程中更容易地提取到训练模型所需要的特征信息;最后,使用残差模块解决过拟合问题,提高解码器对特征的利用效率。在KITTI和Make3D等数据集上对所提方法进行了测试,同时将其与现有经典方法进行了比较。实验结果证明了所提方法的有效性。展开更多
Climate warming causes mountainous species to shift their distributions towards higher elevations.How elevation influences growth-climate relationship in mountain regions has been intensively investigated.However,how ...Climate warming causes mountainous species to shift their distributions towards higher elevations.How elevation influences growth-climate relationship in mountain regions has been intensively investigated.However,how microtopography shapes tree growth and its drought resistance along the elevation gradient remains poorly understood.We used a network of Larix principis-rupprechtii tree-ring data comprising 1,918 trees from different age classes and mountain slopes,along an elevation gradient ranging from 970 to 1,869 m,to investigate how slope gradients mediate the growth and drought resilience of larch trees along an elevation gradient in North China.Growing season drought and temperature were the major limiting climatic factors for larch trees across the study region.Larch trees younger than 40 years exhibited a stronger positive correlation between basal area increment(BAI)and elevation on steep slopes(10°-35°)than on flat(0°-5°)or gentle(5°-10°)slopes.At low-elevation steep slopes,the growth of larch trees younger than 40 years showed a stronger correlation with the Palmer drought severity index(PDSI).Both resistance and resilience were found to increase along the elevation gradient on steep slopes for young larch trees but not for old larch trees.No significant differences were observed in the drought recovery ability of larch trees across all age groups at increasing elevation.Our results highlight that drought events may particularly affect the growth of young larch trees on low-elevation steep slopes,with potential repercussions on mortality rates.展开更多
Ice shelves are important passageways for ice sheets flowing into the ocean.Through iceberg calving and basal melting,ice shelves exert considerable influence on the mass balance of the Antarctic Ice Sheet and glacier...Ice shelves are important passageways for ice sheets flowing into the ocean.Through iceberg calving and basal melting,ice shelves exert considerable influence on the mass balance of the Antarctic Ice Sheet and glacier stability.The Ross Ice Shelf(RIS),the largest body of floating ice on Earth,plays an essential role in any changes in the mass balance of the Antarctic Ice Sheet.The long-term elevation change trend of RIS has been calculated with multiple satellite altimetry in previous studies.However,the seasonal variations were less revealed.Based on crossover analysis and indirect observation adjustments,this study proposed a new method for constructing seasonal records for surface elevation changes in the RIS using ICESat laser altimetry data from 2003 to 2009.The results showed that surface elevation changes exhibited seasonal variations with fluctuations over 20 cm,and the seasonal change characteristics were closely related to the temperature.Interannual variations in RIS surface elevation decreased from 2003 to2009 at a rate of 2 cm/yr.From March 2003 to April 2007,the surface elevation decreased at 3.7 cm/yr;however,after April 2007,the surface elevation increased at 5.5 cm/yr.The more recent stages of surface elevation growth have been influenced by reductions in the summer basal melt,which is related to the decreases in ocean heat content.展开更多
Maintaining the s-polarization state of laser beams is important to achieve high modulation depth in a laser-interference-based super-resolution structured illumination microscope(SR-SIM).However,the imperfect optical...Maintaining the s-polarization state of laser beams is important to achieve high modulation depth in a laser-interference-based super-resolution structured illumination microscope(SR-SIM).However,the imperfect optical components can depolarize the laser beams hence degenerating the modulation depth.Here,we first presented a direct measurement method designed to estimate the modulation depth more precisely by shifting illumination patterns with equal phase steps.This measurement method greatly reduces the dependence of modulation depths on the samples,and then developed a polarization optimization method to achieve high modulation depth at all orientations by actively and quantitatively compensating for the additional phase difference using a combination of waveplate and a liquid crystal variable retarder(LCVR).Experimental results demonstrate that our method can achieve illumination patterns with modulation depth higher than 0.94 at three orientations with only one LCVR voltage,which enables isotropic resolution improvement.展开更多
Land subsidence significantly impacts the accuracy of the National Elevation Datum in China.In order to solve this issue,a dynamic and economical way was proposed to update the National Elevation Datum with the assist...Land subsidence significantly impacts the accuracy of the National Elevation Datum in China.In order to solve this issue,a dynamic and economical way was proposed to update the National Elevation Datum with the assistance of InSAR in the North China Plain,which served as the research area.Moreover,the GNSS result was used to correct the InSAR result for the vertical deformation field,which has a relatively unified deformation reference.By integrating the vertical deformation field with the national elevation control point,an analysis and evaluation of changes in the National Elevation Datum were conducted.In addition,a regional remeasurement scheme was formulated to achieve dynamic updates and mainte-nance of the National Elevation Datum on a regional scale.Through data acquisition and processing,we successfully improved reliability within the main subsidence areas for future use.As a result,updating the elevation values utilize a regional update method,and a dynamic and economical technical process to update the National Elevation Datum is shown in the study.展开更多
In the dynamic scene of autonomous vehicles,the depth estimation of monocular cameras often faces the problem of inaccurate edge depth estimation.To solve this problem,we propose an unsupervised monocular depth estima...In the dynamic scene of autonomous vehicles,the depth estimation of monocular cameras often faces the problem of inaccurate edge depth estimation.To solve this problem,we propose an unsupervised monocular depth estimation model based on edge enhancement,which is specifically aimed at the depth perception challenge in dynamic scenes.The model consists of two core networks:a deep prediction network and a motion estimation network,both of which adopt an encoder-decoder architecture.The depth prediction network is based on the U-Net structure of ResNet18,which is responsible for generating the depth map of the scene.The motion estimation network is based on the U-Net structure of Flow-Net,focusing on the motion estimation of dynamic targets.In the decoding stage of the motion estimation network,we innovatively introduce an edge-enhanced decoder,which integrates a convolutional block attention module(CBAM)in the decoding process to enhance the recognition ability of the edge features of moving objects.In addition,we also designed a strip convolution module to improve the model’s capture efficiency of discrete moving targets.To further improve the performance of the model,we propose a novel edge regularization method based on the Laplace operator,which effectively accelerates the convergence process of themodel.Experimental results on the KITTI and Cityscapes datasets show that compared with the current advanced dynamic unsupervised monocular model,the proposed model has a significant improvement in depth estimation accuracy and convergence speed.Specifically,the rootmean square error(RMSE)is reduced by 4.8%compared with the DepthMotion algorithm,while the training convergence speed is increased by 36%,which shows the superior performance of the model in the depth estimation task in dynamic scenes.展开更多
Coal seam water injection in tunnels is an effective technical measure for preventing coal mine rock bursts.This study used the improved split Hopkinson pressure bar(SHPB)to apply three equal static stresses to water-...Coal seam water injection in tunnels is an effective technical measure for preventing coal mine rock bursts.This study used the improved split Hopkinson pressure bar(SHPB)to apply three equal static stresses to water-saturated coal to simulate the initial stress environment of coal at different depths.Then,dynamic mechanical experiments were conducted on the saturated coal at different depths to investigate the effects of water saturation and depth on the coal samples’dynamic mechanical properties.Under uniaxial compression and without lateral compression,the strength of coal samples decreased to varying degrees in the saturated state;under different depth conditions,the dynamic strength of coal in the saturated state decreased compared with that in the natural state.However,compared with that at 0 m,the reduction in the strength of coal under the saturated condition at 200,400,600,and 800 m was significantly reduced.The findings of this study provide a basic theoretical foundation for the prevention and control of dynamic coal mine disasters.展开更多
文摘Not many bathymetric maps are available for many lakes and reservoirs in developing countries. Usually the bathymetric mapping requires investment in expensive equipment and fieldwork, both of which are not accessible in these countries. This work demonstrates the ability to develop bathymetric map of Mosul Lake by using a digital elevation model (DEM). The depths model of the lake was designed through the use of three main stages;a coastline extraction, dataset interpolation and a triangular irregular network model. The normalized difference water index (NDWI) was used for automatic delineation of the lake coastline from satellite images. The ordinary kriging interpolation with a stable model was used to interpolate the water depths dataset. Finally a triangulated irregular network (TIN) model was used to visualize the resulting interpolation model. Calculated values of area and volume of a TIN model during 2011 were compared with values of supposed initial operation of the reservoir. The differences of water volume storage between these stages at 321 m water level was about 0.81 × 109 m3, where the lake lost around 10% of storage value. Also the results of depths lake model show that the change in water storage between March and July 2011 was about 3.08 × 109 m3.
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
基金financially supported by the POSCO-POSTECH-RIST Convergence Research Center program funded by POSCOthe National Research Foundation (NRF) grants (RS-2024-00462912, RS-2024-00416272, RS-2024-00337012, RS-2024-00408446) funded by the Ministry of Science and ICT (MSIT) of the Korean government+2 种基金the Korea Evaluation Institute of Industrial Technology (KEIT) grant (No. 1415185027/20019169, Alchemist project) funded by the Ministry of Trade, Industry and Energy (MOTIE) of the Korean governmentthe Soseon Science fellowship funded by Community Chest of Koreathe NRF PhD fellowship (RS-2023-00275565) funded by the Ministry of Education (MOE) of the Korean government。
文摘Spatial computing and augmented reality are advancing rapidly,with the goal of seamlessly blending virtual and physical worlds.However,traditional depth-sensing systems are bulky and energy-intensive,limiting their use in wearable devices.To overcome this,recent research by X.Liu et al.presents a compact binocular metalens-based depth perception system that integrates efficient edge detection through an advanced neural network.This system enables accurate,realtime depth mapping even in complex environments,enhancing potential applications in augmented reality,robotics,and autonomous systems.
基金Project supported by the National Natural Science Foundation of China(52372134,12274023)the Fundamental Re search Funds for the Central Universities(FRF-EYIT-23-04)。
文摘Rare earth-doped inorganic compounds contribute mostly to the family of persistent luminescent materials due to the versatile energy levels of rare earth ions.One of the key research aims is to match the trap level stemming from the doped rare earth ion or intrinsic defects to the electronic structure of the host,and therefore thermoluminescence measurement becomes a radical technology in studying trap depth,which is one of the significant parameters that determine the properties of persistent luminescence and photostimulated luminescence.However,the results of trap depth obtained by different thermoluminescence methods are quite different so that they are not comparable.Herein,we analyzed different thermoluminescence methods,selected and improved the traditional peak position method of T_(m)/500 to be E=(-0.94Inβ+30.09)kT_(m).Only the experimental heating rate(β)is needed additionally,but the accuracy is improved greatly in most cases.This convenient and accurate method will accelerate the discovery of novel rare earth-doped materials.
文摘对于复杂天气场景图像模糊、低对比度和颜色失真所导致的深度信息预测不准的问题,以往的研究均以标准场景的深度图作为先验信息来对该类场景进行深度估计。然而,这一方式存在先验信息精度较低等问题。对此,提出一个基于多尺度注意力机制的单目深度估计模型TalentDepth,以实现对复杂天气场景的预测。首先,在编码器中融合多尺度注意力机制,在减少计算成本的同时,保留每个通道的信息,提高特征提取的效率和能力。其次,针对图像深度不清晰的问题,基于几何一致性,提出深度区域细化(Depth Region Refinement,DSR)模块,过滤不准确的像素点,以提高深度信息的可靠性。最后,输入图像翻译模型所生成的复杂样本,并计算相应原始图像上的标准损失来指导模型的自监督训练。在NuScence,KITTI和KITTI-C这3个数据集上,相比于基线模型,所提模型对误差和精度均有优化。
基金Supported by the National Key R&D Program of China (No.2023YFC3008100)the National Natural Science Foundation of China (No.U23A2033)
文摘Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model(Grid-DEM),we proposed a“Fusion based on Image Recognition(FIR)”method for multi-sourced depth data fusion,and used it to merge the electronic nautical chart dataset(referred to as Chart2014 in this paper)with the global digital elevation dataset(referred to as Globalbath2002 in this paper).Compared to the traditional fusion of two datasets by direct combination and interpolation,the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014,reduce the calculation difficulty,and be more intuitive,and,the choice of different interpolation methods in FIR and the influence of the“exclusion radius R”parameter were discussed.FIR avoids complex calculations of spatial distances among points from different sources,and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius R,which greatly improved the fusion status of a reliable dataset.The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error,showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China,and factors such as the point density distribution of multiple source data,accuracy,interpolation method,and various terrain conditions should be fully considered when selecting the exclusion radius R.
文摘Satellites in LEO (Low Earth Orbits) are closest to the Earth’s surface, having the smallest coverage area compared to other orbits, depending on altitude and elevation angle, and providing relatively too short visibility and communication duration, in range of (2 - 15) minutes. Communication duration represents the key performance indicator for LEO satellite communication systems. For longer communication sessions, more satellites must be involved, and the signals must be handed over from one satellite to the next to provide uninterrupted real-time services to the appropriate user or ground station. This leads to the concept and structure of the satellites organized in the constellation. Communication window (visibility window) depends on the designed horizon plane width determined by licensed elevation angle. For the appropriate calculations, a satellite from the Starlink constellation at altitude of 550 km is considered, observed under licensed designed elevations of 40˚ and 25˚. Calculations under two designed elevation levels confirmed the wider horizon and consequently longer communication under the lower elevation.
文摘BACKGROUND The incidence of acute myocardial infarction(AMI)is rising,with cardiac rupture accounting for approximately 2%of deaths in patients with acute ST-segment elevation myocardial infarction(STEMI).Ventricular free wall rupture(FWR)occurs in approximately 2%of AMI patients and is notably rare in patients with non-STEMI.Types of cardiac rupture include left ventricular FWR,ventricular septal rupture,and papillary muscle rupture.The FWR usually leads to acute cardiac tamponade or electromechanical dissociation,where standard resuscitation efforts may not be effective.Ventricular septal rupture and papillary muscle rupture often result in refractory heart failure,with mortality rates over 50%,even with surgical or percutaneous repair options.CASE SUMMARY We present a rare case of an acute non-STEMI patient who suffered sudden FWR causing cardiac tamponade and loss of consciousness immediate before undergoing coronary angiography.Prompt resuscitation and emergency open-heart repair along with coronary artery bypass grafting resulted in successful patient recovery.CONCLUSION This case emphasizes the risks of AMI complications,shares a successful treatment scenario,and discusses measures to prevent such complications.
文摘Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a significant challenge faced in the field of computer vision.However,existing monocular video depth estimation models tend to produce blurred or inaccurate depth information in regions with object edges and low texture.To address this issue,we propose a monocular depth estimation model architecture guided by semantic segmentation masks,which introduces semantic information into the model to correct the ambiguous depth regions.We have evaluated the proposed method,and experimental results show that our method improves the accuracy of edge depth,demonstrating the effectiveness of our approach.
基金supported by Uttarakhand Council for Biotechnology(grant number UCB/R&D PROJECT/2022/20 dated 06.05.2022).
文摘Allium stracheyi(Baker)is widely utilized as a culinary herb and is typically encountered in the higher elevations of the Himalayas.Consequently,it is of great significance to compare the ecological adaptability of this indigenous species to alternative habitats and its introduction into new environments.This research aims to investigate and gain a comprehensive understanding of A.stracheyi,also known as faran,in Uttarakhand region.We aim to examine how this plant adapts morphologically,physiologically,biochemically,and anatomically to varying elevations,specifically at 550,2200,2460,and 3400 m above mean sea level(m AMSL).This plant demonstrated remarkable morphophysiological adjustments across various aspects of its development,encompassing modified growth patterns,alterations in leaf dimensions,leaf count,etc..Moreover,biochemical adaptations have been identified as pivotal in bolstering the plant resilience to the stress associated with higher elevation.Enzymes like superoxide dismutase(SOD)and peroxidase(POD)exhibited significant responsiveness to elevational variations,contributing to the plant's ability to confront the challenges posed by high-elevational conditions.In terms of anatomy,the plant manifested alterations in its leaf and vascular tissues along the elevational gradient.These modifications involve an increased density of stomata and a greater count of vascular bundles,optimizing gas exchange and adaptation to water stress in frequently encountered harsh environmental conditions at higher elevations.Understanding the adaptive mechanisms employed by A.stracheyi provides valuable insights,especially in forecasting how A.stracheyi might respond to global climate change,particularly in regions affected by habitat fragmentation.
基金Under the auspices of National Social Sciences Foundation of China(No.21BJY114)。
文摘Forests exert significant biogeophysical cooling effects(CE)through processes such as increased evapotranspiration,reduced albedo,and enhanced surface roughness.However,little is known about the extent to which elevation-induced temperature differences bias the observed CE and how this bias interacts with the underlying biogeophysical mechanisms.In this study,we integrated multisensor remote sensing products and Shuttle Radar Topography Mission(SRTM)elevation data on the Google Earth Engine(GEE)platform,and applied a spatial-temporal window regression approach to quantify and correct the sensitivity of land surface temperature(LST)to elevation for forest pixels across China from 2001 to 2022.First,we found that forest LST exhibited a significant negative relationship with elevation,leading to systematic CE overestimation by 0.61 K during the day and 0.60 K at night compared with altitudecorrected CE values.Second,after correction,the CE showed clear spatial heterogeneity,with stronger daytime cooling in tropical(-0.54 K)and temperate forests(-0.24 K),and warming in cold(+0.11 K)and arid regions(+0.53 K),while most regions experienced nighttime warming.Among forest types,evergreen needleleaf forests(ENF)exhibited the strongest daytime cooling(-0.36 K),whereas deciduous broadleaf(DBF)and open shrublands(OS)tended to warm.Third,mechanism analysis revealed that elevation correction strengthened the correlations of CE with leaf area index(LAI)and evapotranspiration,while maintaining a significant negative correlation with albedo,indicating that both radiative and non-radiative processes jointly shape the unbiased CE.These findings provide a more accurate quantification of forest CE by eliminating elevation-induced bias,which providing a more accurate assessment of the climate mitigation potential of forests,which is crucial for developing more effective forest management and ecological restoration strategies.
文摘自监督单目深度估计受到了国内外研究人员的广泛关注。现有基于深度学习的自监督单目深度估计方法主要采用编码器-解码器结构。然而,这些方法在编码过程中对输入图像进行下采样操作,导致部分图像信息,尤其是图像的边界信息丢失,进而影响深度图的精度。针对上述问题,提出一种基于拉普拉斯金字塔的自监督单目深度估计方法(Self-supervised Monocular Depth Estimation Based on the Laplace Pyramid,LpDepth)。此方法的核心思想是:首先,使用拉普拉斯残差图丰富编码特征,以弥补在下采样过程中丢失的特征信息;其次,在下采样过程中使用最大池化层突显和放大特征信息,使编码器在特征提取过程中更容易地提取到训练模型所需要的特征信息;最后,使用残差模块解决过拟合问题,提高解码器对特征的利用效率。在KITTI和Make3D等数据集上对所提方法进行了测试,同时将其与现有经典方法进行了比较。实验结果证明了所提方法的有效性。
基金funded by the National Natural Science Foundation of China(No.U24A20353)the S&T Program of Hebei(Nos.226Z6801G,C2021204002,and 20210365)+1 种基金the Talent Introduction Program in Hebei Agricultural University(No.YJ201918)supported by the SERI-funded ERC Starting Grant,project MB23.00011.
文摘Climate warming causes mountainous species to shift their distributions towards higher elevations.How elevation influences growth-climate relationship in mountain regions has been intensively investigated.However,how microtopography shapes tree growth and its drought resistance along the elevation gradient remains poorly understood.We used a network of Larix principis-rupprechtii tree-ring data comprising 1,918 trees from different age classes and mountain slopes,along an elevation gradient ranging from 970 to 1,869 m,to investigate how slope gradients mediate the growth and drought resilience of larch trees along an elevation gradient in North China.Growing season drought and temperature were the major limiting climatic factors for larch trees across the study region.Larch trees younger than 40 years exhibited a stronger positive correlation between basal area increment(BAI)and elevation on steep slopes(10°-35°)than on flat(0°-5°)or gentle(5°-10°)slopes.At low-elevation steep slopes,the growth of larch trees younger than 40 years showed a stronger correlation with the Palmer drought severity index(PDSI).Both resistance and resilience were found to increase along the elevation gradient on steep slopes for young larch trees but not for old larch trees.No significant differences were observed in the drought recovery ability of larch trees across all age groups at increasing elevation.Our results highlight that drought events may particularly affect the growth of young larch trees on low-elevation steep slopes,with potential repercussions on mortality rates.
基金supported by the National Key Research and Development Program of China under grant numbers 2023YFC2809103 and 2024YFC2813505the National Natural Science Foundation of China under the grant number 41706216+2 种基金the Fundamental Research Funds for the Central Universities under grant numbers 2042022kf1204,2042022kf1069,2042023gf0012,2042022dx0001the Hubei Provincial Natural Science Foundation of China under grant number 2022CFB081the State Key Laboratory of Geodesy and Earth's Dynamics,Innovation Academy for Precision Measurement Science and Technology under grant number SKLGED2023-2-6。
文摘Ice shelves are important passageways for ice sheets flowing into the ocean.Through iceberg calving and basal melting,ice shelves exert considerable influence on the mass balance of the Antarctic Ice Sheet and glacier stability.The Ross Ice Shelf(RIS),the largest body of floating ice on Earth,plays an essential role in any changes in the mass balance of the Antarctic Ice Sheet.The long-term elevation change trend of RIS has been calculated with multiple satellite altimetry in previous studies.However,the seasonal variations were less revealed.Based on crossover analysis and indirect observation adjustments,this study proposed a new method for constructing seasonal records for surface elevation changes in the RIS using ICESat laser altimetry data from 2003 to 2009.The results showed that surface elevation changes exhibited seasonal variations with fluctuations over 20 cm,and the seasonal change characteristics were closely related to the temperature.Interannual variations in RIS surface elevation decreased from 2003 to2009 at a rate of 2 cm/yr.From March 2003 to April 2007,the surface elevation decreased at 3.7 cm/yr;however,after April 2007,the surface elevation increased at 5.5 cm/yr.The more recent stages of surface elevation growth have been influenced by reductions in the summer basal melt,which is related to the decreases in ocean heat content.
基金supported by the National Natural Science Foundation of China[Grant Nos.62205367 and 62141506]the Suzhou Basic Research Pilot Project[Grant Nos.SSD2023006 and SJC2021013]the National Key Research and Development Program of China[Grant No.2023YFF1205700].
文摘Maintaining the s-polarization state of laser beams is important to achieve high modulation depth in a laser-interference-based super-resolution structured illumination microscope(SR-SIM).However,the imperfect optical components can depolarize the laser beams hence degenerating the modulation depth.Here,we first presented a direct measurement method designed to estimate the modulation depth more precisely by shifting illumination patterns with equal phase steps.This measurement method greatly reduces the dependence of modulation depths on the samples,and then developed a polarization optimization method to achieve high modulation depth at all orientations by actively and quantitatively compensating for the additional phase difference using a combination of waveplate and a liquid crystal variable retarder(LCVR).Experimental results demonstrate that our method can achieve illumination patterns with modulation depth higher than 0.94 at three orientations with only one LCVR voltage,which enables isotropic resolution improvement.
基金supported by the Scientific and Technological Innovation Project of SHASG(SCK2022-01)National Key Research and Development Program of China(2016YFC0803109)。
文摘Land subsidence significantly impacts the accuracy of the National Elevation Datum in China.In order to solve this issue,a dynamic and economical way was proposed to update the National Elevation Datum with the assistance of InSAR in the North China Plain,which served as the research area.Moreover,the GNSS result was used to correct the InSAR result for the vertical deformation field,which has a relatively unified deformation reference.By integrating the vertical deformation field with the national elevation control point,an analysis and evaluation of changes in the National Elevation Datum were conducted.In addition,a regional remeasurement scheme was formulated to achieve dynamic updates and mainte-nance of the National Elevation Datum on a regional scale.Through data acquisition and processing,we successfully improved reliability within the main subsidence areas for future use.As a result,updating the elevation values utilize a regional update method,and a dynamic and economical technical process to update the National Elevation Datum is shown in the study.
基金funded by the Yangtze River Delta Science and Technology Innovation Community Joint Research Project(2023CSJGG1600)the Natural Science Foundation of Anhui Province(2208085MF173)Wuhu“ChiZhu Light”Major Science and Technology Project(2023ZD01,2023ZD03).
文摘In the dynamic scene of autonomous vehicles,the depth estimation of monocular cameras often faces the problem of inaccurate edge depth estimation.To solve this problem,we propose an unsupervised monocular depth estimation model based on edge enhancement,which is specifically aimed at the depth perception challenge in dynamic scenes.The model consists of two core networks:a deep prediction network and a motion estimation network,both of which adopt an encoder-decoder architecture.The depth prediction network is based on the U-Net structure of ResNet18,which is responsible for generating the depth map of the scene.The motion estimation network is based on the U-Net structure of Flow-Net,focusing on the motion estimation of dynamic targets.In the decoding stage of the motion estimation network,we innovatively introduce an edge-enhanced decoder,which integrates a convolutional block attention module(CBAM)in the decoding process to enhance the recognition ability of the edge features of moving objects.In addition,we also designed a strip convolution module to improve the model’s capture efficiency of discrete moving targets.To further improve the performance of the model,we propose a novel edge regularization method based on the Laplace operator,which effectively accelerates the convergence process of themodel.Experimental results on the KITTI and Cityscapes datasets show that compared with the current advanced dynamic unsupervised monocular model,the proposed model has a significant improvement in depth estimation accuracy and convergence speed.Specifically,the rootmean square error(RMSE)is reduced by 4.8%compared with the DepthMotion algorithm,while the training convergence speed is increased by 36%,which shows the superior performance of the model in the depth estimation task in dynamic scenes.
基金Projects(52225403,52074112)supported by the National Natural Science Foundation of ChinaProject(2022CFD009)supported by the Hubei Natural Science Foundation Innovation and Development Joint Fund Key Project,China+2 种基金Project(SDGZK2423)supported by the State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering,ChinaProject(HJZKYBKT2024111)supported by the Xiangyang Federation of Social Sciences“Hanjiang Think Tank”Project,ChinaProject supported by the Hubei Superior and Distinctive Discipline Group of“New Energy Vehicle and Smart Transportation”,China。
文摘Coal seam water injection in tunnels is an effective technical measure for preventing coal mine rock bursts.This study used the improved split Hopkinson pressure bar(SHPB)to apply three equal static stresses to water-saturated coal to simulate the initial stress environment of coal at different depths.Then,dynamic mechanical experiments were conducted on the saturated coal at different depths to investigate the effects of water saturation and depth on the coal samples’dynamic mechanical properties.Under uniaxial compression and without lateral compression,the strength of coal samples decreased to varying degrees in the saturated state;under different depth conditions,the dynamic strength of coal in the saturated state decreased compared with that in the natural state.However,compared with that at 0 m,the reduction in the strength of coal under the saturated condition at 200,400,600,and 800 m was significantly reduced.The findings of this study provide a basic theoretical foundation for the prevention and control of dynamic coal mine disasters.
