Insular biodiversity has aroused the curiosity of biologists in assessing ecological and evolutionary hypotheses concerning their mainland counterparts.Comparisons of particular life history traits between island and ...Insular biodiversity has aroused the curiosity of biologists in assessing ecological and evolutionary hypotheses concerning their mainland counterparts.Comparisons of particular life history traits between island and mainland populations have provided a broader view of phenotypic and behavioral plasticity at both intraspecific and interspecific levels(Meiri 2007).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
This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the pred...This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.展开更多
The Cloud Top Heavenly Palace,a majestic palace complex built with snow in the Changbai Mountains scenic area in Jilin Province,was officially illuminated and opened to the public on December 26,2025.This impressive i...The Cloud Top Heavenly Palace,a majestic palace complex built with snow in the Changbai Mountains scenic area in Jilin Province,was officially illuminated and opened to the public on December 26,2025.This impressive installation,with a main building measuring 20 meters high and 60 meters wide,faithfully recreates a classic scene from the best-selling Grave Robbers'Chronicles web novel series by Xu Lei,better known by his pseudonym Nanpai Sanshu.展开更多
As the European debt crisis deepens, the world economy has yet to find its footing despite signs of growth and renewed confidence. While the developed world faces the
This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and und...This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and underlying mechanisms.The results show that,during the developing winter of EP El Niño,significant SSR reductions occur in southwestern China and the east coast of southern China due to a strong,zonally extended Northwest Pacific anticyclone that transports moisture from the tropical Northwest Pacific and North Indian Ocean,while the northeast of southern China experiences a weak increase in SSR.In contrast,during the developing winter of CP El Niño,SSR decreases in the east of southern China with a significant decrease in the lower basin of the Yangtze River but an increase in the west of southern China with a remarkable increase in eastern Yunnan.The pronounced east-west dipole pattern in SSR anomalies is driven by a meridionally elongated Northwest Pacific anticyclone,which enhances northward moisture transport to the east of southern China while leaving western areas drier.Further research reveals that distinct moisture anomalies during the developing winter of EP and CP events result in divergent SSR distributions across southern China,primarily through modulating the total cloud cover.These findings highlight the critical need to differentiate between El Niño types when predicting medium and long-term variability of radiation in southern China.展开更多
Small and medium-sized enterprises in Zhejiang Province face serious headwinds In Wenzhou of Zhejiang Province,the boomtown of China’s private economy,three renowned manufacturers—Jiangnan Leather,Portman Coffee and
Harnessing solar power is essential for addressing the dual challenges of global warming and the depletion of traditional energy sources.However,the fluctuations and intermittency of photovoltaic(PV)power pose challen...Harnessing solar power is essential for addressing the dual challenges of global warming and the depletion of traditional energy sources.However,the fluctuations and intermittency of photovoltaic(PV)power pose challenges for its extensive incorporation into power grids.Thus,enhancing the precision of PV power prediction is particularly important.Although existing studies have made progress in short-term prediction,issues persist,particularly in the underutilization of temporal features and the neglect of correlations between satellite cloud images and PV power data.These factors hinder improvements in PV power prediction performance.To overcome these challenges,this paper proposes a novel PV power prediction method based on multi-stage temporal feature learning.First,the improved LSTMand SA-ConvLSTMare employed to extract the temporal feature of PV power and the spatial-temporal feature of satellite cloud images,respectively.Subsequently,a novel hybrid attention mechanism is proposed to identify the interplay between the two modalities,enhancing the capacity to focus on the most relevant features.Finally,theTransformermodel is applied to further capture the short-termtemporal patterns and long-term dependencies within multi-modal feature information.The paper also compares the proposed method with various competitive methods.The experimental results demonstrate that the proposed method outperforms the competitive methods in terms of accuracy and reliability in short-term PV power prediction.展开更多
Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmenta...Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.展开更多
The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achievi...The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.展开更多
Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
The characteristics of summertime raindrop size distribution(DSD) and associated relations in the semi-arid region over the Inner Mongolian Plateau(IMP) were investigated,utilizing five-year continuous observations by...The characteristics of summertime raindrop size distribution(DSD) and associated relations in the semi-arid region over the Inner Mongolian Plateau(IMP) were investigated,utilizing five-year continuous observations by a PARSIVEL2disdrometer in East Ujimqin County(EUC),China.It is found that only 7.94% of the 15 664 one-min precipitation samples meet classification criteria as convective rain(CR),but its contribution to the total rainfall amount is 63.87%.Notably,40.72% of the rainfall comes from large-sized raindrops(D> 3 mm),despite the fact that large-sized raindrops account for only 1.73% of the CR total number concentration.Further results show that the mean value of mass-weighted mean diameters(Dm) is larger(2.43 mm) and generalized intercepts(lgN_(W)) is lower(3.19) in CR,aligning with a "continentallike" cluster,which is mainly influenced by the joint impact of in-cloud ice-based processes and the below-cloud environmental background.Also,the empirical relationships of shape-slope(μ-Λ),radar reflectivity-rain rate(Z-R),and rainfall kinetic energy(KE_(time)-Rand KE_(time)-Z) are localized.To quantitatively analyze the impact of DSD parameters on kinetic energy estimation,power-law KE_(time)-R and KE_(time)-Z relationships are derived based on the normalized gamma distribution.N_(W)takes precedence over μ in affecting variabilities of multiplicative coefficients,especially for KE_(time)-R relationship where the multiplicative coefficient is proportional to N_(W)^(-0.287).It should be noted that although the proportion of CR occurring throughout the summer is small,raindrops with lower N_(W) and larger Dmwill generate higher KE_(time),which will bring a higher potential risk of soil erosion in semi-arid regions over IMP.展开更多
基金We are deeply thankful to Neftali Camacho(LACM),Addison Wynn(NMNH),Esther Langan(NMNH),Christina K.Sami(NMNH),David A.Kizirian(AMNH),and Lauren Vonnahme(AMNH)for logistic support to visiting each museum.Shai Meiri and anonymous reviewers provided insightful suggestions that improved the manuscript,and Louis W.Porras also improves the English of the manuscript.Finally,we thank Jose Gonzalez and Ismael Huerta for help in preparing the figure.
文摘Insular biodiversity has aroused the curiosity of biologists in assessing ecological and evolutionary hypotheses concerning their mainland counterparts.Comparisons of particular life history traits between island and mainland populations have provided a broader view of phenotypic and behavioral plasticity at both intraspecific and interspecific levels(Meiri 2007).
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.
基金supported by the National Key R&D Program of China[grant number 2023YFC3008004]。
文摘This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.
文摘The Cloud Top Heavenly Palace,a majestic palace complex built with snow in the Changbai Mountains scenic area in Jilin Province,was officially illuminated and opened to the public on December 26,2025.This impressive installation,with a main building measuring 20 meters high and 60 meters wide,faithfully recreates a classic scene from the best-selling Grave Robbers'Chronicles web novel series by Xu Lei,better known by his pseudonym Nanpai Sanshu.
文摘As the European debt crisis deepens, the world economy has yet to find its footing despite signs of growth and renewed confidence. While the developed world faces the
基金funded by a Project from China Southern Power Grid Company Ltd.(Nos.ZBKJXM20232481 and ZBKJXM20232482)。
文摘This study investigates the distinct impacts of eastern Pacific(EP)and central Pacific(CP)El Niño events on winter shortwave solar radiation(SSR)in southern China,revealing different spatial distributions and underlying mechanisms.The results show that,during the developing winter of EP El Niño,significant SSR reductions occur in southwestern China and the east coast of southern China due to a strong,zonally extended Northwest Pacific anticyclone that transports moisture from the tropical Northwest Pacific and North Indian Ocean,while the northeast of southern China experiences a weak increase in SSR.In contrast,during the developing winter of CP El Niño,SSR decreases in the east of southern China with a significant decrease in the lower basin of the Yangtze River but an increase in the west of southern China with a remarkable increase in eastern Yunnan.The pronounced east-west dipole pattern in SSR anomalies is driven by a meridionally elongated Northwest Pacific anticyclone,which enhances northward moisture transport to the east of southern China while leaving western areas drier.Further research reveals that distinct moisture anomalies during the developing winter of EP and CP events result in divergent SSR distributions across southern China,primarily through modulating the total cloud cover.These findings highlight the critical need to differentiate between El Niño types when predicting medium and long-term variability of radiation in southern China.
文摘Small and medium-sized enterprises in Zhejiang Province face serious headwinds In Wenzhou of Zhejiang Province,the boomtown of China’s private economy,three renowned manufacturers—Jiangnan Leather,Portman Coffee and
基金supported by the Science and Technology Project of Jiangsu Coastal Power Infrastructure Intelligent Engineering Research Center“Photovoltaic Power Prediction System Driven by Deep Learning and Multi-Source Data Fusion”(F2024-5044).
文摘Harnessing solar power is essential for addressing the dual challenges of global warming and the depletion of traditional energy sources.However,the fluctuations and intermittency of photovoltaic(PV)power pose challenges for its extensive incorporation into power grids.Thus,enhancing the precision of PV power prediction is particularly important.Although existing studies have made progress in short-term prediction,issues persist,particularly in the underutilization of temporal features and the neglect of correlations between satellite cloud images and PV power data.These factors hinder improvements in PV power prediction performance.To overcome these challenges,this paper proposes a novel PV power prediction method based on multi-stage temporal feature learning.First,the improved LSTMand SA-ConvLSTMare employed to extract the temporal feature of PV power and the spatial-temporal feature of satellite cloud images,respectively.Subsequently,a novel hybrid attention mechanism is proposed to identify the interplay between the two modalities,enhancing the capacity to focus on the most relevant features.Finally,theTransformermodel is applied to further capture the short-termtemporal patterns and long-term dependencies within multi-modal feature information.The paper also compares the proposed method with various competitive methods.The experimental results demonstrate that the proposed method outperforms the competitive methods in terms of accuracy and reliability in short-term PV power prediction.
基金Postgraduate Innovation Top notch Talent Training Project of Hunan Province,Grant/Award Number:CX20220045Scientific Research Project of National University of Defense Technology,Grant/Award Number:22-ZZCX-07+2 种基金New Era Education Quality Project of Anhui Province,Grant/Award Number:2023cxcysj194National Natural Science Foundation of China,Grant/Award Numbers:62201597,62205372,1210456foundation of Hefei Comprehensive National Science Center,Grant/Award Number:KY23C502。
文摘Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.
文摘The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
基金supported by the National Natural Science Foundation of China(Grant Nos.42325503,42075063,42075066,and 42021004)the Hubei Provincial Natural Science Foundation and the Meteorological Innovation and Development Project of China(Grant No.2023AFD096)the Beijige Foundation of NJIAS(Grant No.BJG202304).
文摘The characteristics of summertime raindrop size distribution(DSD) and associated relations in the semi-arid region over the Inner Mongolian Plateau(IMP) were investigated,utilizing five-year continuous observations by a PARSIVEL2disdrometer in East Ujimqin County(EUC),China.It is found that only 7.94% of the 15 664 one-min precipitation samples meet classification criteria as convective rain(CR),but its contribution to the total rainfall amount is 63.87%.Notably,40.72% of the rainfall comes from large-sized raindrops(D> 3 mm),despite the fact that large-sized raindrops account for only 1.73% of the CR total number concentration.Further results show that the mean value of mass-weighted mean diameters(Dm) is larger(2.43 mm) and generalized intercepts(lgN_(W)) is lower(3.19) in CR,aligning with a "continentallike" cluster,which is mainly influenced by the joint impact of in-cloud ice-based processes and the below-cloud environmental background.Also,the empirical relationships of shape-slope(μ-Λ),radar reflectivity-rain rate(Z-R),and rainfall kinetic energy(KE_(time)-Rand KE_(time)-Z) are localized.To quantitatively analyze the impact of DSD parameters on kinetic energy estimation,power-law KE_(time)-R and KE_(time)-Z relationships are derived based on the normalized gamma distribution.N_(W)takes precedence over μ in affecting variabilities of multiplicative coefficients,especially for KE_(time)-R relationship where the multiplicative coefficient is proportional to N_(W)^(-0.287).It should be noted that although the proportion of CR occurring throughout the summer is small,raindrops with lower N_(W) and larger Dmwill generate higher KE_(time),which will bring a higher potential risk of soil erosion in semi-arid regions over IMP.
