A convective cloud transport model, without chemical processes, is developed by joining a set of concentration conservative equations into a two-dimensional, slab-symmetric and fully elastic numerical cloud model, and...A convective cloud transport model, without chemical processes, is developed by joining a set of concentration conservative equations into a two-dimensional, slab-symmetric and fully elastic numerical cloud model, and a numerical experiment is completed to simulate the vertical transport of ground-borne, inert gaseous pollutant by deepthunderstorm. The simulation shows that deep convective storm can very effectively transport high concentrated pollutant gas from PBL upward to the upper troposphere in 30 to 40 minutes, where the pollutant spreads laterally outward with strong anvil outflow, forming an extensive high concentration area. Meanwhile, relatively low concentration areas are formed in PBL both below and beside the cloud, mainly caused by dynamic pumping effect and sub-cloud downdraft flow. About 80% of the pollutant gas transported to the upper troposphere is from the layer below 1.5 km AGL (above ground level).展开更多
Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a n...Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a novel method for efficient and lightweight 3D building reconstruction from drone imagery using line clouds and sparse point clouds.Our approach eliminates the need to generate dense point clouds,and thus significantly reduces the computational burden by reconstructing 3D models directly from sparse data.We addressed the limitations of line clouds for plane detection and reconstruction by using a new algorithm.This algorithm projects 3D line clouds onto a 2D plane,clusters the projections to identify potential planes,and refines them using sparse point clouds to ensure an accurate and efficient model reconstruction.Extensive qualitative and quantitative experiments demonstrated the effectiveness of our method,demonstrating its superiority over existing techniques in terms of simplicity and efficiency.展开更多
During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and...During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and polarization of which depends on the Sun’s location.If a cloud contains spatially oriented ice particles,then it becomes anisotropic,that is,the coefficients of directional light scattering of such a cloud depend on the Sun’s zenith and azimuth angles.In this work,the possibility of using the effect of anisotropic scattering of solar radiation on the predictive ability of machine learning algorithms in solving the problem of predicting the HLC backscattering phase matrix(BSPM)was evaluated.The hypothesis that solar radiation scattered on HLCs has no effect on the BSPM elements of such clouds determined with a polarization lidar was tested.The operation of two algorithms for predicting the BSPM elements is evaluated.To train the first one,meteorological data were used as input parameters;for the second algorithm,the azi-muthal and zenith angles of the Sun’s position were added to the meteorological parameters.It is shown that there is no significant improvement in the predictive ability of the algorithm.展开更多
Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote s...Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote sensing of MPC properties is still challenging,and there is seldom MPC result inferred from passive spectral observations.This study examines the spectral characteristics of MPCs in the shortwave-infrared(SWIR)channels over the wavelength of 0.4–2.5μm,and evaluates the potential of current operational satellite spectroradiometer channels for MPC retrievals.With optical properties of MPCs based on the assumption of uniform mixing of both ice and liquid water particles,the effects of MPC ice optical thickness fraction(IOTF)and effective radius on associated optical properties are analyzed.As expected,results indicate that the MPC optical properties show features for ice and liquid water clouds,and their spectral variations show noticeable differences from those for homogeneous cases.A radiative transfer method is employed to examine the sensitivity of SWIR channels to given MPC cloud water path(CWP)and IOTF.MPCs have unique signal characteristics in the SWIR spectrum.The 0.87-μm channel is most sensitive to CWP.Meanwhile,the 1.61-and 2.13-μm channels are more sensitive to water-dominated MPCs(IOTF approaching 0),and the 2.25-μm channel is sensitive to both water-dominated and ice-dominated MPCs(IOTF approaching 1).Such spectral differences are potentially possible to be used to infer MPC properties based on radiometer observations,which will be investigated in future studies.展开更多
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
This study numerically investigates the formation of high-velocity molecular clouds(HVMCs)in the Galactic Center(GC)based on the X-ray emission analysis.We employ three-dimensional magnetohydrodynamic simulations to e...This study numerically investigates the formation of high-velocity molecular clouds(HVMCs)in the Galactic Center(GC)based on the X-ray emission analysis.We employ three-dimensional magnetohydrodynamic simulations to explore the propagation and acceleration of HVMCs with starburst-driven winds,considering vertical,horizontal,and no magnetic field scenarios.Our results reveal that the envelope gas(with a typical T~10~8 K and density~10^(-2)cm^(-3))of molecular clouds(MCs)as a result of the shock interaction is responsible for X-ray emission.Additionally,some clear boundary exists between the interstellar medium(ISM),envelope gas and MCs,and the envelope gas protects the MCs in the heated environment of the shock wave.In theory,it is challenging to distinguish between the envelope gas,MCs and ISM in terms of X-ray emission.Our simulations suggest that the envelope gas has a significant impact on the survival and emission characteristics of MCs,providing insights into the complex interactions from the supernova feedback mechanisms in the GC.展开更多
Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected ...Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops.In response,we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds.The proposed method employs voxel filtering to downsample point clouds,constructs a point cloud topology using K-d trees,utilizes principal component analysis to calculate the point cloud normals,and employs the pointwise clustering(PWC)algorithm to extract discontinuities from rock outcrop point clouds.This method provides information on the location and orientation(dip direction and dip angle)of the discontinuities,and the modified whale optimization algorithm(MWOA)is utilized to identify major discontinuity sets and their average orientations.Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy.In particular,the method yields more reasonable extraction results for discontinuities with certain undulations.The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds.展开更多
Mapping and analyzing rock mass discontinuities based on 3D(three-dimensional)point cloud(3DPC)is one of the most important work in the engineering geomechanical survey.To efficiently analyze the distribution of disco...Mapping and analyzing rock mass discontinuities based on 3D(three-dimensional)point cloud(3DPC)is one of the most important work in the engineering geomechanical survey.To efficiently analyze the distribution of discontinuities,a self-developed code termed as the cloud-group-cluster(CGC)method based on MATLAB for mapping and detecting discontinuities based on the 3DPC was introduced.The identification and optimization of discontinuity groups were performed using three key parameters,i.e.K,θ,and f.A sensitivity analysis approach for identifying the optimal key parameters was introduced.The results show that the comprehensive analysis of the main discontinuity groups,mean orientations,and densities could be achieved automatically.The accuracy of the CGC method was validated using tetrahedral and hexahedral models.The 3D point cloud data were divided into three levels(point cloud,group,and cluster)for analysis,and this three-level distribution recognition was applied to natural rock surfaces.The densities and spacing information of the principal discontinuities were automatically detected using the CGC method.Five engineering case studies were conducted to validate the CGC method,showing the applicability in detecting rock discontinuities based on 3DPC model.展开更多
Existing reverse-engineering methods struggle to directly generate editable,parametric CAD models from scanned data.To address this limitation,this paper proposes a reverse-modeling approach that reconstructs parametr...Existing reverse-engineering methods struggle to directly generate editable,parametric CAD models from scanned data.To address this limitation,this paper proposes a reverse-modeling approach that reconstructs parametric CAD models from multi-view RGB-D point clouds.Multi-frame point-cloud registration and fusion are first employed to obtain a complete 3-D point cloud of the target object.A region-growing algorithm that jointly exploits color and geometric information segments the cloud,while RANSAC robustly detects and fits basic geometric primitives.These primitives serve as nodes in a graph whose edge features are inferred by a graph neural network to capture spatial constraints.From the detected primitives and their constraints,a high-accuracy,fully editable parametric CAD model is finally exported.Experiments show an average parameter error of 0.3 mm for key dimensions and an overall geometric reconstruction accuracy of 0.35 mm.The work offers an effective technical route toward automated,intelligent 3-D reverse modeling.展开更多
DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive...DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.展开更多
Climate change is significantly influenced by both clouds and Earth’s surface temperature(EST).While numerous studies have investigated clouds and EST separately,the extent of clouds’impact on EST remains unclear.Ba...Climate change is significantly influenced by both clouds and Earth’s surface temperature(EST).While numerous studies have investigated clouds and EST separately,the extent of clouds’impact on EST remains unclear.Based on the inspiration and limitation of cloud radiative effect(CRE),this study provides a pioneering attempt to propose a novel indicator,cloud radiative effect on surface temperature(CREST),aiming to quantify how clouds affect EST globally while also analyzing the physical mechanism.Using reanalysis and remotely sensed data,a phased machine learning scheme in combination of surface energy balance theory is proposed to estimate EST under all-sky and hypothetical clear-sky conditions in stages,thereby estimating the newly defined CREST by subtracting the hypothetical clear-sky EST from the all-sky EST.The inter-annual experiments reveal the significant spatial heterogeneity in CREST across land,ocean,and ice/snow regions.As a global offset of the heterogeneity,clouds exhibit a net warming effect on global surface temperature on an annual scale(e.g.,0.26 K in 1981),despite their ability to block sunlight.However,the net warming effect has gradually weakened to nearly zero over the past four decades(e.g.,only 0.06 K in 2021),and it’s even possible to transform into a cooling effect,which might be good news for mitigating the global warming.展开更多
Based on data collected during the first U.S. Department of Energy （DOE） Atmospheric Radiation Measurement （ARM） field campaigns at Shouxian, east- ern China in 2008, the effects of clouds and aerosols on the surf...Based on data collected during the first U.S. Department of Energy （DOE） Atmospheric Radiation Measurement （ARM） field campaigns at Shouxian, east- ern China in 2008, the effects of clouds and aerosols on the surface radiation budget during the period Octo- ber-December 2008 were studied. The results revealed that the largest longwave （LW）, shortwave （SW）, and net Aerosol Radiative Effects （AREs） are 12.7, -37.6, and -24.9 W rn-2, indicating that aerosols have LW warming impact, a strong SW cooling effect, and a net cooling ef- fect on the surface radiation budget at Shouxian during the study period 15 October-15 December 2008. The SW cloud radiative forcing （CRF） is -135.1 W m-2, much cooler than ARE （about 3.6 times）, however, the LW CRF is 43.6 W m 2, much warmer than ARE, and resulting in a net CRF of-91.5 W m-2, about 3.7 times of net ARE. These results suggest that the clouds have much stronger LW warming effect and SW cooling effect on the surface radiation budget than AREs. The net surface radiation budget is dominated by SW cooling effect for both ARE and CRE. Furthermore, the precipitatable clouds （PCs） have the largest SW cooling effect and LW warming ef- fect, while optically thin high clouds have the smallest cooling effect and LW warming on the surface radiation budget. Comparing the two selected caseds, CloudSat cloud radar reflectivity agrees very well with the AMF （ARM Mobile Facility） WACR （W-band ARM Cloud Radar） measurements, particularly for cirrus cloud case. These result will provide a ground truth to validate the model simulations in the future.展开更多
Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphys...Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphysical processes such as raindrop evaporation and cloud water accretion in a double-moment six-class cloud microphysics scheme were revised to enhance the simulation of low clouds using the Global-Regional Integrated Forecast System(GRIST)model. The validation of the revised scheme using a single-column version of the GRIST demonstrated a reasonable reduction in liquid water biases. The revised parameterization simulated medium-and low-level cloud fractions that were in better agreement with the observations than the original scheme. Long-term global simulations indicate the mitigation of the originally overestimated low-level cloud fraction and cloud-water mixing ratio in mid-to high-latitude regions,primarily owing to enhanced accretion processes and weakened raindrop evaporation. The reduced low clouds with the revised scheme showed better consistency with satellite observations, particularly at mid-and high-latitudes. Further improvements can be observed in the simulated cloud shortwave radiative forcing and vertical distribution of total cloud cover. Annual precipitation in mid-latitude regions has also improved, particularly over the oceans, with significantly increased large-scale and decreased convective precipitation.展开更多
Word cloud visualization is a compelling graphical representation that visually depicts the frequency of words within a given text or dataset[1].Research on word clouds focuses on two main aspects.The first emphasizes...Word cloud visualization is a compelling graphical representation that visually depicts the frequency of words within a given text or dataset[1].Research on word clouds focuses on two main aspects.The first emphasizes processing words,such as using the latent Dirichlet allocation(LDA)algorithm to uncover topics in the documents[2],while the second involves visual impact through striking word arrangements[3,4].In the realm of extensive biomedical data,effectiveknowledge delivery to biologists is crucial.展开更多
In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task schedul...In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task scheduling is crucial for efficiently handling IoT user requests,thereby improving system performance,cost,and energy consumption across nodes in cloud computing.With the large amount of data and user requests,achieving the optimal solution to the task scheduling problem is challenging,particularly in terms of cost and energy efficiency.In this paper,we develop novel strategies to save energy consumption across nodes in fog computing when users execute tasks through the least-cost paths.Task scheduling is developed using modified artificial ecosystem optimization(AEO),combined with negative swarm operators,Salp Swarm Algorithm(SSA),in order to competitively optimize their capabilities during the exploitation phase of the optimal search process.In addition,the proposed strategy,Enhancement Artificial Ecosystem Optimization Salp Swarm Algorithm(EAEOSSA),attempts to find the most suitable solution.The optimization that combines cost and energy for multi-objective task scheduling optimization problems.The backpack problem is also added to improve both cost and energy in the iFogSim implementation as well.A comparison was made between the proposed strategy and other strategies in terms of time,cost,energy,and productivity.Experimental results showed that the proposed strategy improved energy consumption,cost,and time over other algorithms.Simulation results demonstrate that the proposed algorithm increases the average cost,average energy consumption,and mean service time in most scenarios,with average reductions of up to 21.15%in cost and 25.8%in energy consumption.展开更多
The Pantone Color of the Year 2026,PANTONE 11-4201 Cloud Dancer,has been introduced as a soft,lofty white symbolizing calm and clarity in an increasingly noisy world.This gentle shade invites a sense of peace and spac...The Pantone Color of the Year 2026,PANTONE 11-4201 Cloud Dancer,has been introduced as a soft,lofty white symbolizing calm and clarity in an increasingly noisy world.This gentle shade invites a sense of peace and spaciousness,encouraging focus and creating room for creativity and reflection.Cloud Dancer embodies a desire for simplicity and renewal-a blank canvas that allows our minds to wander and new ideas to take shape.Its expansive presence fosters environments where tranquility meets inspiration,offering visual calm that supports wellbeing and mental lightness.展开更多
Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.Howev...Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.However,traditional approaches frequently rely on single-objective optimization methods which are insufficient for capturing the complexity of such problems.To address this limitation,we introduce MDMOSA(Multi-objective Dwarf Mongoose Optimization with Simulated Annealing),a hybrid that integrates multi-objective optimization for efficient task scheduling in Infrastructure-as-a-Service(IaaS)cloud environments.MDMOSA harmonizes the exploration capabilities of the biologically inspired Dwarf Mongoose Optimization(DMO)with the exploitation strengths of Simulated Annealing(SA),achieving a balanced search process.The algorithm aims to optimize task allocation by reducing makespan and financial cost while improving system resource utilization.We evaluate MDMOSA through extensive simulations using the real-world Google Cloud Jobs(GoCJ)dataset within the CloudSim environment.Comparative analysis against benchmarked algorithms such as SMOACO,MOTSGWO,and MFPAGWO reveals that MDMOSA consistently achieves superior performance in terms of scheduling efficiency,cost-effectiveness,and scalability.These results confirm the potential of MDMOSA as a robust and adaptable solution for resource scheduling in dynamic and heterogeneous cloud computing infrastructures.展开更多
Material phase-transition represents a significant phenomenon and mechanism in the context of hypervelocity protection.This study presents a thorough analysis of the phase-transition phenomena induced by shock pressur...Material phase-transition represents a significant phenomenon and mechanism in the context of hypervelocity protection.This study presents a thorough analysis of the phase-transition phenomena induced by shock pressure as the shock wave propagates initially to the rear of the projectile.The shock wave that induces a phase-transition is commonly referred to as a macroscopic phase-transition wave,whereas the interface that separates the distinct phases is referred to as macroscopic phase-boundary.The contact interface between the spherical projectile and the thin plate,characterized by its curved surface,plays a significant role in the nonlinear propagation and evolution of wave systems.The pressure distribution along the central axis of a spherical projectile is derived in accordance with the linear decay law observed for axial pressure.On this basis,a quadratic function is employed to characterize the trend of changes in wave front pressure,thereby facilitating the establishment of a model for wave front pressure distribution.Using the phase-transition pressure criterion for materials,the wave front phase evolution process is derived,and the macroscopic phase-boundary is determined.Based on the geometric propagation model(GPM)and the pressure distribution of the wave front,a phase geometric propagation model(PGPM)is proposed.The phase distribution of a spherical projectile impacting a thin plate is obtained by theoretical methods.The accuracy of the PGPM is subsequently validated through a comparison of its results with those obtained from numerical simulations.展开更多
E-commerce has transformed Caoxian into a hub of traditional Chinese attire.STEPPING inside Caoxian’s Youai Cloud Warehouse,a livestreaming base dedicated to hanfu(traditional clothing),it feels less like a clothing ...E-commerce has transformed Caoxian into a hub of traditional Chinese attire.STEPPING inside Caoxian’s Youai Cloud Warehouse,a livestreaming base dedicated to hanfu(traditional clothing),it feels less like a clothing warehouse and more like a time capsule.Thousands of intricately embroidered garments line the racks-from elegant horse-face skirts to modernised editions of traditional Chinese clothing.展开更多
基金This Project is supported by the National Natural Science Foundation of China.
文摘A convective cloud transport model, without chemical processes, is developed by joining a set of concentration conservative equations into a two-dimensional, slab-symmetric and fully elastic numerical cloud model, and a numerical experiment is completed to simulate the vertical transport of ground-borne, inert gaseous pollutant by deepthunderstorm. The simulation shows that deep convective storm can very effectively transport high concentrated pollutant gas from PBL upward to the upper troposphere in 30 to 40 minutes, where the pollutant spreads laterally outward with strong anvil outflow, forming an extensive high concentration area. Meanwhile, relatively low concentration areas are formed in PBL both below and beside the cloud, mainly caused by dynamic pumping effect and sub-cloud downdraft flow. About 80% of the pollutant gas transported to the upper troposphere is from the layer below 1.5 km AGL (above ground level).
基金Supported by the Guangdong Major Project of Basic and Applied Basic Research (2023B0303000016)the National Natural Science Foundation of China (U21A20515)。
文摘Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a novel method for efficient and lightweight 3D building reconstruction from drone imagery using line clouds and sparse point clouds.Our approach eliminates the need to generate dense point clouds,and thus significantly reduces the computational burden by reconstructing 3D models directly from sparse data.We addressed the limitations of line clouds for plane detection and reconstruction by using a new algorithm.This algorithm projects 3D line clouds onto a 2D plane,clusters the projections to identify potential planes,and refines them using sparse point clouds to ensure an accurate and efficient model reconstruction.Extensive qualitative and quantitative experiments demonstrated the effectiveness of our method,demonstrating its superiority over existing techniques in terms of simplicity and efficiency.
基金supported by the Government of the Russian Federation grant number 075-15-2025-009 of 28 February 2025 and by the Russian Science Foundation,Grant No.24-72-10127.
文摘During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and polarization of which depends on the Sun’s location.If a cloud contains spatially oriented ice particles,then it becomes anisotropic,that is,the coefficients of directional light scattering of such a cloud depend on the Sun’s zenith and azimuth angles.In this work,the possibility of using the effect of anisotropic scattering of solar radiation on the predictive ability of machine learning algorithms in solving the problem of predicting the HLC backscattering phase matrix(BSPM)was evaluated.The hypothesis that solar radiation scattered on HLCs has no effect on the BSPM elements of such clouds determined with a polarization lidar was tested.The operation of two algorithms for predicting the BSPM elements is evaluated.To train the first one,meteorological data were used as input parameters;for the second algorithm,the azi-muthal and zenith angles of the Sun’s position were added to the meteorological parameters.It is shown that there is no significant improvement in the predictive ability of the algorithm.
基金supported by the National Natural Science Foundation of China[Grant Nos.42205086 and 42122038]。
文摘Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote sensing of MPC properties is still challenging,and there is seldom MPC result inferred from passive spectral observations.This study examines the spectral characteristics of MPCs in the shortwave-infrared(SWIR)channels over the wavelength of 0.4–2.5μm,and evaluates the potential of current operational satellite spectroradiometer channels for MPC retrievals.With optical properties of MPCs based on the assumption of uniform mixing of both ice and liquid water particles,the effects of MPC ice optical thickness fraction(IOTF)and effective radius on associated optical properties are analyzed.As expected,results indicate that the MPC optical properties show features for ice and liquid water clouds,and their spectral variations show noticeable differences from those for homogeneous cases.A radiative transfer method is employed to examine the sensitivity of SWIR channels to given MPC cloud water path(CWP)and IOTF.MPCs have unique signal characteristics in the SWIR spectrum.The 0.87-μm channel is most sensitive to CWP.Meanwhile,the 1.61-and 2.13-μm channels are more sensitive to water-dominated MPCs(IOTF approaching 0),and the 2.25-μm channel is sensitive to both water-dominated and ice-dominated MPCs(IOTF approaching 1).Such spectral differences are potentially possible to be used to infer MPC properties based on radiometer observations,which will be investigated in future studies.
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
文摘Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
基金the cosmology simulation database(CSD)in the National Basic Science Data Center(NBSDC)and its funds the NBSDC-DB-10the support from the National Key Research and Development Program of China(2022YFA1602930)+3 种基金the National Natural Science Foundation of China(NSFC,grant Nos.11825303 and 11861131006)the science research grants from the China Manned Space project with No.CMS-CSST 2021-A03,CMSCSST-2021-A04the Fundamental Research Funds for the Central Universities of China(2262022-00216)the startup funding of Zhejiang University。
文摘This study numerically investigates the formation of high-velocity molecular clouds(HVMCs)in the Galactic Center(GC)based on the X-ray emission analysis.We employ three-dimensional magnetohydrodynamic simulations to explore the propagation and acceleration of HVMCs with starburst-driven winds,considering vertical,horizontal,and no magnetic field scenarios.Our results reveal that the envelope gas(with a typical T~10~8 K and density~10^(-2)cm^(-3))of molecular clouds(MCs)as a result of the shock interaction is responsible for X-ray emission.Additionally,some clear boundary exists between the interstellar medium(ISM),envelope gas and MCs,and the envelope gas protects the MCs in the heated environment of the shock wave.In theory,it is challenging to distinguish between the envelope gas,MCs and ISM in terms of X-ray emission.Our simulations suggest that the envelope gas has a significant impact on the survival and emission characteristics of MCs,providing insights into the complex interactions from the supernova feedback mechanisms in the GC.
基金supported by the National Natural Science Foundation of China(Grant No.42407232)the Sichuan Science and Technology Program(Grant No.2024NSFSC0826).
文摘Recognizing discontinuities within rock masses is a critical aspect of rock engineering.The development of remote sensing technologies has significantly enhanced the quality and quantity of the point clouds collected from rock outcrops.In response,we propose a workflow that balances accuracy and efficiency to extract discontinuities from massive point clouds.The proposed method employs voxel filtering to downsample point clouds,constructs a point cloud topology using K-d trees,utilizes principal component analysis to calculate the point cloud normals,and employs the pointwise clustering(PWC)algorithm to extract discontinuities from rock outcrop point clouds.This method provides information on the location and orientation(dip direction and dip angle)of the discontinuities,and the modified whale optimization algorithm(MWOA)is utilized to identify major discontinuity sets and their average orientations.Performance evaluations based on three real cases demonstrate that the proposed method significantly reduces computational time costs without sacrificing accuracy.In particular,the method yields more reasonable extraction results for discontinuities with certain undulations.The presented approach offers a novel tool for efficiently extracting discontinuities from large-scale point clouds.
基金supported by the National Key Research and Development Program of China(Grant Nos.2023YFC2907400 and 2021YFC2900500)the National Natural Science Foundation of China(Grant No.52074020).
文摘Mapping and analyzing rock mass discontinuities based on 3D(three-dimensional)point cloud(3DPC)is one of the most important work in the engineering geomechanical survey.To efficiently analyze the distribution of discontinuities,a self-developed code termed as the cloud-group-cluster(CGC)method based on MATLAB for mapping and detecting discontinuities based on the 3DPC was introduced.The identification and optimization of discontinuity groups were performed using three key parameters,i.e.K,θ,and f.A sensitivity analysis approach for identifying the optimal key parameters was introduced.The results show that the comprehensive analysis of the main discontinuity groups,mean orientations,and densities could be achieved automatically.The accuracy of the CGC method was validated using tetrahedral and hexahedral models.The 3D point cloud data were divided into three levels(point cloud,group,and cluster)for analysis,and this three-level distribution recognition was applied to natural rock surfaces.The densities and spacing information of the principal discontinuities were automatically detected using the CGC method.Five engineering case studies were conducted to validate the CGC method,showing the applicability in detecting rock discontinuities based on 3DPC model.
文摘Existing reverse-engineering methods struggle to directly generate editable,parametric CAD models from scanned data.To address this limitation,this paper proposes a reverse-modeling approach that reconstructs parametric CAD models from multi-view RGB-D point clouds.Multi-frame point-cloud registration and fusion are first employed to obtain a complete 3-D point cloud of the target object.A region-growing algorithm that jointly exploits color and geometric information segments the cloud,while RANSAC robustly detects and fits basic geometric primitives.These primitives serve as nodes in a graph whose edge features are inferred by a graph neural network to capture spatial constraints.From the detected primitives and their constraints,a high-accuracy,fully editable parametric CAD model is finally exported.Experiments show an average parameter error of 0.3 mm for key dimensions and an overall geometric reconstruction accuracy of 0.35 mm.The work offers an effective technical route toward automated,intelligent 3-D reverse modeling.
基金supported by the National Natural Science Foundation of China (Grant No. 12002044)。
文摘DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.
基金carried out under the co-funding of the National Natural Science Foundation of China(NSFC)project(Grant No.42022008)Zhuhai basic and applied research project(Grant No.ZH22017003200009PWC)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant No.311022003).
文摘Climate change is significantly influenced by both clouds and Earth’s surface temperature(EST).While numerous studies have investigated clouds and EST separately,the extent of clouds’impact on EST remains unclear.Based on the inspiration and limitation of cloud radiative effect(CRE),this study provides a pioneering attempt to propose a novel indicator,cloud radiative effect on surface temperature(CREST),aiming to quantify how clouds affect EST globally while also analyzing the physical mechanism.Using reanalysis and remotely sensed data,a phased machine learning scheme in combination of surface energy balance theory is proposed to estimate EST under all-sky and hypothetical clear-sky conditions in stages,thereby estimating the newly defined CREST by subtracting the hypothetical clear-sky EST from the all-sky EST.The inter-annual experiments reveal the significant spatial heterogeneity in CREST across land,ocean,and ice/snow regions.As a global offset of the heterogeneity,clouds exhibit a net warming effect on global surface temperature on an annual scale(e.g.,0.26 K in 1981),despite their ability to block sunlight.However,the net warming effect has gradually weakened to nearly zero over the past four decades(e.g.,only 0.06 K in 2021),and it’s even possible to transform into a cooling effect,which might be good news for mitigating the global warming.
基金sponsored by the U.S. DOE Office of Energy Research,Office of Health and Environmental Research,Environmental Sciences Divisionthe support of DOE Atmospheric System Research(ASR) project with award number DE-SC0008468 at University of North Dakota+3 种基金funded by the Key Laboratory of Meteorological Disaster of Ministry of Education (KLME)(KLME1206)the National Natural Science Foundation of China(41275043 and 41175035)a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)the National Basic Research Program of China(973 Program,2013CB955800) at Beijing Normal University
文摘Based on data collected during the first U.S. Department of Energy （DOE） Atmospheric Radiation Measurement （ARM） field campaigns at Shouxian, east- ern China in 2008, the effects of clouds and aerosols on the surface radiation budget during the period Octo- ber-December 2008 were studied. The results revealed that the largest longwave （LW）, shortwave （SW）, and net Aerosol Radiative Effects （AREs） are 12.7, -37.6, and -24.9 W rn-2, indicating that aerosols have LW warming impact, a strong SW cooling effect, and a net cooling ef- fect on the surface radiation budget at Shouxian during the study period 15 October-15 December 2008. The SW cloud radiative forcing （CRF） is -135.1 W m-2, much cooler than ARE （about 3.6 times）, however, the LW CRF is 43.6 W m 2, much warmer than ARE, and resulting in a net CRF of-91.5 W m-2, about 3.7 times of net ARE. These results suggest that the clouds have much stronger LW warming effect and SW cooling effect on the surface radiation budget than AREs. The net surface radiation budget is dominated by SW cooling effect for both ARE and CRE. Furthermore, the precipitatable clouds （PCs） have the largest SW cooling effect and LW warming ef- fect, while optically thin high clouds have the smallest cooling effect and LW warming on the surface radiation budget. Comparing the two selected caseds, CloudSat cloud radar reflectivity agrees very well with the AMF （ARM Mobile Facility） WACR （W-band ARM Cloud Radar） measurements, particularly for cirrus cloud case. These result will provide a ground truth to validate the model simulations in the future.
基金National Natural Science Foundation of China(42375153,42105153,42205157)Development of Science and Technology at Chinese Academy of Meteorological Sciences(2023KJ038)。
文摘Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphysical processes such as raindrop evaporation and cloud water accretion in a double-moment six-class cloud microphysics scheme were revised to enhance the simulation of low clouds using the Global-Regional Integrated Forecast System(GRIST)model. The validation of the revised scheme using a single-column version of the GRIST demonstrated a reasonable reduction in liquid water biases. The revised parameterization simulated medium-and low-level cloud fractions that were in better agreement with the observations than the original scheme. Long-term global simulations indicate the mitigation of the originally overestimated low-level cloud fraction and cloud-water mixing ratio in mid-to high-latitude regions,primarily owing to enhanced accretion processes and weakened raindrop evaporation. The reduced low clouds with the revised scheme showed better consistency with satellite observations, particularly at mid-and high-latitudes. Further improvements can be observed in the simulated cloud shortwave radiative forcing and vertical distribution of total cloud cover. Annual precipitation in mid-latitude regions has also improved, particularly over the oceans, with significantly increased large-scale and decreased convective precipitation.
基金supported by the National Key R&D Program of China(2022YFC2704304 and 2021YFF0702000)the National Natural Science Foundation of China(32341020 and 32341021)+1 种基金Hubei Innovation Group Project(2021CFA005)the Research Core Facilities for Life Science(HUST).
文摘Word cloud visualization is a compelling graphical representation that visually depicts the frequency of words within a given text or dataset[1].Research on word clouds focuses on two main aspects.The first emphasizes processing words,such as using the latent Dirichlet allocation(LDA)algorithm to uncover topics in the documents[2],while the second involves visual impact through striking word arrangements[3,4].In the realm of extensive biomedical data,effectiveknowledge delivery to biologists is crucial.
基金supported and funded by theDeanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2503).
文摘In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task scheduling is crucial for efficiently handling IoT user requests,thereby improving system performance,cost,and energy consumption across nodes in cloud computing.With the large amount of data and user requests,achieving the optimal solution to the task scheduling problem is challenging,particularly in terms of cost and energy efficiency.In this paper,we develop novel strategies to save energy consumption across nodes in fog computing when users execute tasks through the least-cost paths.Task scheduling is developed using modified artificial ecosystem optimization(AEO),combined with negative swarm operators,Salp Swarm Algorithm(SSA),in order to competitively optimize their capabilities during the exploitation phase of the optimal search process.In addition,the proposed strategy,Enhancement Artificial Ecosystem Optimization Salp Swarm Algorithm(EAEOSSA),attempts to find the most suitable solution.The optimization that combines cost and energy for multi-objective task scheduling optimization problems.The backpack problem is also added to improve both cost and energy in the iFogSim implementation as well.A comparison was made between the proposed strategy and other strategies in terms of time,cost,energy,and productivity.Experimental results showed that the proposed strategy improved energy consumption,cost,and time over other algorithms.Simulation results demonstrate that the proposed algorithm increases the average cost,average energy consumption,and mean service time in most scenarios,with average reductions of up to 21.15%in cost and 25.8%in energy consumption.
文摘The Pantone Color of the Year 2026,PANTONE 11-4201 Cloud Dancer,has been introduced as a soft,lofty white symbolizing calm and clarity in an increasingly noisy world.This gentle shade invites a sense of peace and spaciousness,encouraging focus and creating room for creativity and reflection.Cloud Dancer embodies a desire for simplicity and renewal-a blank canvas that allows our minds to wander and new ideas to take shape.Its expansive presence fosters environments where tranquility meets inspiration,offering visual calm that supports wellbeing and mental lightness.
文摘Task scheduling in cloud computing is a multi-objective optimization problem,often involving conflicting objectives such as minimizing execution time,reducing operational cost,and maximizing resource utilization.However,traditional approaches frequently rely on single-objective optimization methods which are insufficient for capturing the complexity of such problems.To address this limitation,we introduce MDMOSA(Multi-objective Dwarf Mongoose Optimization with Simulated Annealing),a hybrid that integrates multi-objective optimization for efficient task scheduling in Infrastructure-as-a-Service(IaaS)cloud environments.MDMOSA harmonizes the exploration capabilities of the biologically inspired Dwarf Mongoose Optimization(DMO)with the exploitation strengths of Simulated Annealing(SA),achieving a balanced search process.The algorithm aims to optimize task allocation by reducing makespan and financial cost while improving system resource utilization.We evaluate MDMOSA through extensive simulations using the real-world Google Cloud Jobs(GoCJ)dataset within the CloudSim environment.Comparative analysis against benchmarked algorithms such as SMOACO,MOTSGWO,and MFPAGWO reveals that MDMOSA consistently achieves superior performance in terms of scheduling efficiency,cost-effectiveness,and scalability.These results confirm the potential of MDMOSA as a robust and adaptable solution for resource scheduling in dynamic and heterogeneous cloud computing infrastructures.
基金supported by National Natural Science Foundation of China(Nos.12432018,12372346)the Innovative Research Groups of the National Natural Science Foundation of China(No.12221002)National Natural Science Foundation of China(No.12302493)。
文摘Material phase-transition represents a significant phenomenon and mechanism in the context of hypervelocity protection.This study presents a thorough analysis of the phase-transition phenomena induced by shock pressure as the shock wave propagates initially to the rear of the projectile.The shock wave that induces a phase-transition is commonly referred to as a macroscopic phase-transition wave,whereas the interface that separates the distinct phases is referred to as macroscopic phase-boundary.The contact interface between the spherical projectile and the thin plate,characterized by its curved surface,plays a significant role in the nonlinear propagation and evolution of wave systems.The pressure distribution along the central axis of a spherical projectile is derived in accordance with the linear decay law observed for axial pressure.On this basis,a quadratic function is employed to characterize the trend of changes in wave front pressure,thereby facilitating the establishment of a model for wave front pressure distribution.Using the phase-transition pressure criterion for materials,the wave front phase evolution process is derived,and the macroscopic phase-boundary is determined.Based on the geometric propagation model(GPM)and the pressure distribution of the wave front,a phase geometric propagation model(PGPM)is proposed.The phase distribution of a spherical projectile impacting a thin plate is obtained by theoretical methods.The accuracy of the PGPM is subsequently validated through a comparison of its results with those obtained from numerical simulations.
文摘E-commerce has transformed Caoxian into a hub of traditional Chinese attire.STEPPING inside Caoxian’s Youai Cloud Warehouse,a livestreaming base dedicated to hanfu(traditional clothing),it feels less like a clothing warehouse and more like a time capsule.Thousands of intricately embroidered garments line the racks-from elegant horse-face skirts to modernised editions of traditional Chinese clothing.
