Here we report on simultaneous lidar observations of sporadic Ni(Nis)layers and sporadic Na(Nas)layers in the atmosphere over Yanqing,Beijing(40.42°N,116.02°E)from April 2019 to October 2022.During 343 night...Here we report on simultaneous lidar observations of sporadic Ni(Nis)layers and sporadic Na(Nas)layers in the atmosphere over Yanqing,Beijing(40.42°N,116.02°E)from April 2019 to October 2022.During 343 nights of observation,68 Nis and 56 Nas were observed.The seasonal variation of Nis and Nas was also obtained,with the highest occurrence of Nis being in July(43%)and that of Nas being in June(61%).We found that the seasonal variation of Nis is similar to that of Nas and that both occur more frequently in summer than in winter.In addition,we found 23 events in which Nis and Nas occur simultaneously.The average peak altitude of Nas is approximately 1 km higher than that of Nis,and the peak density ratio of Nas to Nis is approximately 5,which is half the density ratio of the two main layers.Additionally,the strength factor for Nas is smaller than that for Nis.Through data analysis of sporadic E layers(Es),we found that Nis and Nas has a significant correlation with Es.The neutralization rates of Ni^(+)/Na^(+)were calculated according to the dissociative recombination reaction of Ni^(+)/Na^(+)and the WACCM-Ni(Whole Atmosphere Community Climate Model of Ni).The production rates of Ni and Na were estimated to be approximately 1:4.4,which is consistent with the density ratio of Nis to Nas.The results showed that the neutralization reaction of Ni+,Na+,and electrons in Es is the main reason for the formation of the Nis layer and the Nas layer.展开更多
Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with ...Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS （AMSR-E） and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System （IMS）. AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as ＂virtual＂ in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model （DEM） but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method.展开更多
On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau a...On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,marked the largest earthquake in the region in recent years.The Shenzha-Dingjie fault zone,situated at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,is a key tectonic feature in the India-Eurasia collision process,exhibiting both thrust and strike-slip faulting.This study analyzed the disaster characteristics induced by the earthquake using Differential Synthetic Aperture Radar Interferometry(DIn SAR)to process Sentinel-1 satellite data and derive pre-and post-earthquake surface deformation information.Additionally,high-resolution optical remote sensing data,UAV(unmanned aerial vehicle)imagery,and airborne Li DAR(light detection and ranging)data were employed to analyze the spatial distribution of the surface rupture zone,with field investigations validating the findings.Key results include:(1)Field verification confirmed that potential landslide hazard points identified via optical image interpretation did not exhibit secondary landslide activity;(2)D-In SAR revealed the co-seismic surface deformation pattern,providing detailed deformation information for the Dingri region;(3)Integration of Li DAR and optical imagery further refined and validated surface rupture characteristics identified by optical-In SAR,indicating a predominantly north-south rupture zone.Additionally,surface fracture features extending in a near east-west direction were observed on the southeast side of the epicenter,accompanied by some infrastructure damage;(4)Surface fracture was most severe in high-intensity seismic areas near the epicenter,with the maximum surface displacement approximately 28 km from the epicenter.The earthquake-induced surface deformation zone spanned approximately 6 km by 46 km,with deformation concentrated primarily on the western side of the Dingmucuo Fault,where maximum subsidence of 0.65 m was detected.On the eastern side,uplift was dominant,reaching a maximum of 0.75 m.This earthquake poses significant threats to local communities and infrastructure,underscoring the urgent need for continued monitoring in affected areas.The findings highlight the effectiveness of multi-source data fusion(space-air-ground based observation)in seismic disaster assessment,offering a methodological framework for rapid post-earthquake disaster response.providing a valuable scientific foundation for mitigating secondary disasters in the region.展开更多
The characteristics of nonmetallic inclusions formed during steel production have a significant influence on steel performance.In this paper,studies on inclusions using confocal scanning laser microscopy(CSLM)are revi...The characteristics of nonmetallic inclusions formed during steel production have a significant influence on steel performance.In this paper,studies on inclusions using confocal scanning laser microscopy(CSLM)are reviewed and summarized,particularly the col-lision of various inclusions,dissolution of inclusions in liquid slag,and reactions between inclusions and steel.Solid inclusions exhibited a high collision tendency,whereas pure liquid inclusions exhibited minimal collisions because of the small attraction force induced by their<90°contact angle with molten steel.The collision of complex inclusions in molten steel was not included in the scope of this study and should be evaluated in future studies.Higher CaO/Al_(2)O_(3)and CaO/SiO_(2)ratios in liquid slag promoted the dissolution of Al_(2)O_(3)-based in-clusions.The formation of solid phases in the slag should be prevented to improve dissolution of inclusions.To accurately simulate the dissolution of inclusions in liquid slag,in-situ observation of the dissolution of inclusions at the steel-slag interface is necessary.Using a combination of CSLM and scanning electron microscopy-energy dispersive spectroscopy,the composition and morphological evolution of the inclusions during their modification by the dissolved elements in steel were observed and analyzed.Although the in-situ observa-tion of MnS and TiN precipitations has been widely studied,the in-situ observation of the evolution of oxide inclusions in steel during so-lidification and heating processes has rarely been reported.The effects of temperature,heating and cooling rates,and inclusion character-istics on the formation of acicular ferrites(AFs)have been widely studied.At a cooling rate of 3-5 K/s,the order of AF growth rate in-duced by different inclusions,as reported in literature,is Ti-O<Ti-Ca-Zr-Al-O<Mg-O<Ti-Zr-Al-O<Mn-Ti-Al-O<Ti-Al-O<Zr-Ti-Al-O.Further comprehensive experiments are required to investigate the quantitative relationship between the formation of AFs and inclusions.展开更多
The high-temperature dissolution behavior of primary carbides in samples taken from GCr15 continuous-casting bloom was observed in-situ by confocal laser scanning microscopy.Equations were fitted to the dissolution ki...The high-temperature dissolution behavior of primary carbides in samples taken from GCr15 continuous-casting bloom was observed in-situ by confocal laser scanning microscopy.Equations were fitted to the dissolution kinetics of primary carbides during either heating or soaking.Dissolution of carbides proceeded in three stages(fast→slow→faster)as either temperature or holding time was increased.During the heating process and during the first and third stages of the soaking process,the original size of the carbides determined the steepness of the slope,but during the middle(“slow”)stage of the soaking process,the slope remained zero.The initial size of the carbides varied greatly,but their final dissolution temperature fell within the narrow range of 1210-1235℃,and the holding time remained within 50 min.Fractal analysis was used to study the morphological characteristics of small and medium-sized carbides during the dissolution process.According to changes in the fractal dimension before and after soaking,the carbides tended to evolve towards a more regular morphology.展开更多
The Macao satellites differ from their predecessors in their orbits:MSS-1(Macao Science Satellite-1)is in low inclination and the planned MSS-2 will be in highly elliptical orbits.This paper reviews the fundamental ad...The Macao satellites differ from their predecessors in their orbits:MSS-1(Macao Science Satellite-1)is in low inclination and the planned MSS-2 will be in highly elliptical orbits.This paper reviews the fundamental advantages and disadvantages of the different possible magnetic measurements:the component(declination,intensity,etc.)and location(satellite,ground,etc.).When planning a survey the choice of component is the"What?"question;the choice of location the"Where?"question.Results from potential theory inform the choice of measurement and data analysis.For example,knowing the vertical component of magnetic field provides a solution for the full magnetic field everywhere in the potential region.This is the familiar Neumann problem.In reality this ideal dataset is never available.In the past we were restricted to declination data only,then direction only,then total intensity only.There have also been large swathes of Earth's surface with no measurements at all(MSS-1 is restricted to latitudes below).These incomplete datasets throw up new questions for potential theory,questions that have some intriguing answers.When only declination is known uniqueness is provided by horizontal intensity measurements on a single line joining the dip-poles.When only directions are involved uniqueness is provided by a single intensity measurement,at least in principle.Paleomagnetic intensities can help.When only total intensity is known,as was largely the case in the early satellite era,uniqueness is provided by a precise location of the magnetic equator.Holes in the data distribution is a familiar problem in geophysical studies.All magnetic measurements sample,to a greater or lesser extent,the potential field everywhere.There is a trade-off between measurements close to the source,good for small targets and high resolution,and the broader sample of a distant measurement.The sampling of a measurement is given by the appropriate Green's function of the Laplacian,which determines both the resolution and scope of the measurement.For example,radial and horizontal measurements near the Earth's surface give a weighted average of the radial component over a patch of the core surface beneath the measurement site about in radius.The patch is smaller for shallower surfaces,for example from satellite to ground.Holes in the data distribution do not correspond to similar holes at the source surface;the price paid is in resolution of the source.I argue that,in the past,we have been too reluctant to take advantage of incomplete and apparently hopeless datasets.展开更多
To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances...To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.展开更多
Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growin...Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.展开更多
The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-...The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.展开更多
In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and ot...In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.展开更多
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P...Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.展开更多
Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimiz...This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimization effect,etc.,aiming to better provide a certain guideline and reference for relevant researchers.展开更多
BACKGROUND Colonic diverticular bleeding(CDB)is a leading cause of gastrointestinal blee-ding-related hospitalizations in Japan and is increasingly recognized as a signifi-cant burden in the United States.Identifying ...BACKGROUND Colonic diverticular bleeding(CDB)is a leading cause of gastrointestinal blee-ding-related hospitalizations in Japan and is increasingly recognized as a signifi-cant burden in the United States.Identifying the stigmata of a recent hemorrhage(SRH)during colonoscopy enables targeted hemostasis and reduces rebleeding.However,no benchmark exists for an appropriate observation duration,resulting in operator-dependent variation.Short observation periods may lead to missed SRH,whereas unnecessarily prolonged procedures,particularly in older patients,can increase patient burden and limit endoscopy unit availability.METHODS We retrospectively analyzed patients with acute hematochezia who underwent an initial colonoscopy between January 2017 and December 2024 at a Japanese tertiary hospital.The Observation time was measured from scope insertion to SRH detection(excluding therapeutic time)or withdrawal.The primary outcome,the“5%plateau time”,was defined as the point when the proportion of patients newly identified with SRH in each 5-minute interval consistently dropped below 5%.Computed tomography(CT)-based stratified analyses were performed by endoscopists who conducted≥10%of procedures.RESULTS Of the 1039 patients who underwent colonoscopy,845(mean age 77±11 years;64.5%male)were included.Nine board-certified endoscopists performed the procedures.SRH was detected in 286 patients(33.8%),with a median detection time of 19 minutes(interquartile range,12-28 minutes).The overall 5%plateau time was 40 minutes and varied according to the CT findings:40,35,and 30 minutes for no extravasation,right-sided extravasation,and left-sided extravasation,respectively.This time point corresponded to when 80%-90%of SRH cases were detected.De-spite variations in SRH detection rates and observation durations among endoscopists,the 5%plateau time was consistently approximately 40 minutes.CONCLUSION Although it varied according to the CT findings,the overall 5%plateau time was 40 minutes.This offers a practical benchmark for the minimum observation time without SRH detection.展开更多
With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heter...With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.展开更多
Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electron...Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.展开更多
This study explored the observation strategy and effectiveness of synoptic-scale adaptive observations for improving sea fog prediction in coastal regions around the Bohai Sea based on a poorly predicted fog event wit...This study explored the observation strategy and effectiveness of synoptic-scale adaptive observations for improving sea fog prediction in coastal regions around the Bohai Sea based on a poorly predicted fog event with cold-front synoptic pattern(CFSP).An ensemble Kalman filter data assimilation system for the Weather Research and Forecasting model was adopted with ensemble sensitivity analysis(ESA).By comparing observation impacts(estimated from a 40-member ensemble with ESA)among different meteorological observation variables and pressure levels,the temperature at 850 hPa and surface layer(850 hPa-and-surface temperature)was selected as the target observation type.Additionally,the area with large observation impacts for this observation type was predicted in the transition region of the surface low–high system.This area developed southward with the low and moved eastward with the low–high system,which could be explained by the main features of CFSP.Moreover,both experiments assimilating synthetic and real observations showed that assimilating 850 hPa-and-surface temperature observations generally yielded better fog coverage forecasts in areas with greater observation impacts than areas with smaller impacts.However,the effectiveness of adaptive observations was reduced when real observations rather than synthetic observations were assimilated,which is possibly due to factors such as observation and model errors.The main conclusions above were verified by another typical fog event with CFSP characteristics.Results of this study highlight the importance of improved initial conditions in the transition region of the low–high system for improving fog prediction and provide scientific guidance for implementing an observation network for fog forecasting over the Bohai Sea.展开更多
Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from...Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.展开更多
The ice-phase microphysical characteristics of a stratiform cloud system over the Qilian Mountains in northwestern China on 15 September 2022 were analyzed via aircraft data.The stratiform cloud system developed under...The ice-phase microphysical characteristics of a stratiform cloud system over the Qilian Mountains in northwestern China on 15 September 2022 were analyzed via aircraft data.The stratiform cloud system developed under southwesterly flows at 500 hPa and was affected locally by topography.Synoptic features and aircraft observations revealed strengthened cloud development on the leeward slope.The ice particle habits and microphysical processes at heights of 6-8 km were investigated.The cloud system was characterized by extremely low supercooled liquid water content at temperatures between−4℃ and−17℃.The ice particle concentrations ranged predominantly from 10 to 30 L^(−1),corresponding to ice water content ranging from 0.01 to 0.05 g m^(−3).Active ice aggregation was observed at temperatures colder than−10°C.The windward side of the cloud system exhibited weaker development and two distinct cloud layers.Intense orographic uplift on the leeward slope enhanced ice particle aggregation.The clouds on the leeside presented lower ice particle concentrations but larger sizes than those on the windward side.The influence of aggregation on the ice particle size distribution was reflected in two main aspects.One aspect was the bimodal spectra at−16℃,with the first peak at 125μm and subpeak at 400-500μm;the other was the broadened size spectra at−13℃ due to significant aggregation of dendrites.展开更多
Earth-based deep space radar studies celestial bodies by both transmitting and receiving radio waves,whereas radio telescopes only work passively.On the operational level,radar missions use only short observation time...Earth-based deep space radar studies celestial bodies by both transmitting and receiving radio waves,whereas radio telescopes only work passively.On the operational level,radar missions use only short observation times,which leaves a large portion of the time available for astronomical observations.However,the design principles used for radar and radio telescopes differ.Technical challenges are involved in making the instruments required to meet the requirements of these two applications simultaneously.In this study,we have attempted to tune a deep space radar system for use in radio astronomical applications and conducted a successful pulsar observation,thus demonstrating the feasibility of using radar systems,particularly distributed deep space radar,to perform astronomical research.Additionally,given the limited astronomical capacity available within the observed frequency range,this system has the potential to contribute to the long-term monitoring of specific radio sources.This work represents the first successful attempt to use an Earth-based deep space radar system to perform radio astronomy in China.We also discuss the challenges of tuning a built radar system for astronomical observation applications and propose recommendations for the design of future large-scale distributed deep space radar systems with innate astronomical capabilities.展开更多
基金supported by the Specialized Research Fund for State Key Laboratories,Chinese Meridian Project,the Specialized Research Fund for the State Key Laboratory of Solar Activity and Space Weather,postgraduate Education Reform and Quality Improvement Project of Henan Province(Grant No.YJS2024JD32)Natural Science Foundation Project of Henan Province(Grant No.242300420253)National Natural Science Foundation of China for Young Scientists(Grant No.42504156)funding.
文摘Here we report on simultaneous lidar observations of sporadic Ni(Nis)layers and sporadic Na(Nas)layers in the atmosphere over Yanqing,Beijing(40.42°N,116.02°E)from April 2019 to October 2022.During 343 nights of observation,68 Nis and 56 Nas were observed.The seasonal variation of Nis and Nas was also obtained,with the highest occurrence of Nis being in July(43%)and that of Nas being in June(61%).We found that the seasonal variation of Nis is similar to that of Nas and that both occur more frequently in summer than in winter.In addition,we found 23 events in which Nis and Nas occur simultaneously.The average peak altitude of Nas is approximately 1 km higher than that of Nis,and the peak density ratio of Nas to Nis is approximately 5,which is half the density ratio of the two main layers.Additionally,the strength factor for Nas is smaller than that for Nis.Through data analysis of sporadic E layers(Es),we found that Nis and Nas has a significant correlation with Es.The neutralization rates of Ni^(+)/Na^(+)were calculated according to the dissociative recombination reaction of Ni^(+)/Na^(+)and the WACCM-Ni(Whole Atmosphere Community Climate Model of Ni).The production rates of Ni and Na were estimated to be approximately 1:4.4,which is consistent with the density ratio of Nis to Nas.The results showed that the neutralization reaction of Ni+,Na+,and electrons in Es is the main reason for the formation of the Nis layer and the Nas layer.
基金Meteorological Research in the Public Interest,No.GYHY201106014Beijing Nova Program,No.2010B037China Special Fund for the National High Technology Research and Development Program of China(863 Program),No.412230
文摘Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS （AMSR-E） and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System （IMS）. AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as ＂virtual＂ in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model （DEM） but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method.
基金supported by the National Natural Science Foundation of China(No.42477170)the Major Project of the National Natural Science Foundation of China(No.42090054)+1 种基金the Research Fund Program of Hubei Key Laboratory of Resources and Eco-Environment Geology(No.HBREGKFJJ-202411)Innovative Group Project of Natural Science Foundation of Hubei Province(No.2024AFA015)。
文摘On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,marked the largest earthquake in the region in recent years.The Shenzha-Dingjie fault zone,situated at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,is a key tectonic feature in the India-Eurasia collision process,exhibiting both thrust and strike-slip faulting.This study analyzed the disaster characteristics induced by the earthquake using Differential Synthetic Aperture Radar Interferometry(DIn SAR)to process Sentinel-1 satellite data and derive pre-and post-earthquake surface deformation information.Additionally,high-resolution optical remote sensing data,UAV(unmanned aerial vehicle)imagery,and airborne Li DAR(light detection and ranging)data were employed to analyze the spatial distribution of the surface rupture zone,with field investigations validating the findings.Key results include:(1)Field verification confirmed that potential landslide hazard points identified via optical image interpretation did not exhibit secondary landslide activity;(2)D-In SAR revealed the co-seismic surface deformation pattern,providing detailed deformation information for the Dingri region;(3)Integration of Li DAR and optical imagery further refined and validated surface rupture characteristics identified by optical-In SAR,indicating a predominantly north-south rupture zone.Additionally,surface fracture features extending in a near east-west direction were observed on the southeast side of the epicenter,accompanied by some infrastructure damage;(4)Surface fracture was most severe in high-intensity seismic areas near the epicenter,with the maximum surface displacement approximately 28 km from the epicenter.The earthquake-induced surface deformation zone spanned approximately 6 km by 46 km,with deformation concentrated primarily on the western side of the Dingmucuo Fault,where maximum subsidence of 0.65 m was detected.On the eastern side,uplift was dominant,reaching a maximum of 0.75 m.This earthquake poses significant threats to local communities and infrastructure,underscoring the urgent need for continued monitoring in affected areas.The findings highlight the effectiveness of multi-source data fusion(space-air-ground based observation)in seismic disaster assessment,offering a methodological framework for rapid post-earthquake disaster response.providing a valuable scientific foundation for mitigating secondary disasters in the region.
基金supported by the National Key R&D Program(No.2023YFB3709900)the National Nature Science Foundation of China(No.U22A20171)+2 种基金China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202315)the High Steel Center(HSC)at North China University of TechnologyUniversity of Science and Technology Beijing,China.
文摘The characteristics of nonmetallic inclusions formed during steel production have a significant influence on steel performance.In this paper,studies on inclusions using confocal scanning laser microscopy(CSLM)are reviewed and summarized,particularly the col-lision of various inclusions,dissolution of inclusions in liquid slag,and reactions between inclusions and steel.Solid inclusions exhibited a high collision tendency,whereas pure liquid inclusions exhibited minimal collisions because of the small attraction force induced by their<90°contact angle with molten steel.The collision of complex inclusions in molten steel was not included in the scope of this study and should be evaluated in future studies.Higher CaO/Al_(2)O_(3)and CaO/SiO_(2)ratios in liquid slag promoted the dissolution of Al_(2)O_(3)-based in-clusions.The formation of solid phases in the slag should be prevented to improve dissolution of inclusions.To accurately simulate the dissolution of inclusions in liquid slag,in-situ observation of the dissolution of inclusions at the steel-slag interface is necessary.Using a combination of CSLM and scanning electron microscopy-energy dispersive spectroscopy,the composition and morphological evolution of the inclusions during their modification by the dissolved elements in steel were observed and analyzed.Although the in-situ observa-tion of MnS and TiN precipitations has been widely studied,the in-situ observation of the evolution of oxide inclusions in steel during so-lidification and heating processes has rarely been reported.The effects of temperature,heating and cooling rates,and inclusion character-istics on the formation of acicular ferrites(AFs)have been widely studied.At a cooling rate of 3-5 K/s,the order of AF growth rate in-duced by different inclusions,as reported in literature,is Ti-O<Ti-Ca-Zr-Al-O<Mg-O<Ti-Zr-Al-O<Mn-Ti-Al-O<Ti-Al-O<Zr-Ti-Al-O.Further comprehensive experiments are required to investigate the quantitative relationship between the formation of AFs and inclusions.
基金supported by Independent Research Project of State Key Laboratory of Advanced Special Steel,Shanghai Key Laboratory of Advanced Ferrometallurgy,Shanghai University(SKLASS-2023-Z13)the Science and Technology Commission of Shanghai Municipality(No.19DZ2270200)+1 种基金A portion of the work was performed at US National High Magnetic Field Laboratory,which is supported by the National Science Foundation(Cooperative Agreement No.DMR-1157490 and DMR-1644779)the State of Florida.Thanks also to Mary Tyler for editing.
文摘The high-temperature dissolution behavior of primary carbides in samples taken from GCr15 continuous-casting bloom was observed in-situ by confocal laser scanning microscopy.Equations were fitted to the dissolution kinetics of primary carbides during either heating or soaking.Dissolution of carbides proceeded in three stages(fast→slow→faster)as either temperature or holding time was increased.During the heating process and during the first and third stages of the soaking process,the original size of the carbides determined the steepness of the slope,but during the middle(“slow”)stage of the soaking process,the slope remained zero.The initial size of the carbides varied greatly,but their final dissolution temperature fell within the narrow range of 1210-1235℃,and the holding time remained within 50 min.Fractal analysis was used to study the morphological characteristics of small and medium-sized carbides during the dissolution process.According to changes in the fractal dimension before and after soaking,the carbides tended to evolve towards a more regular morphology.
文摘The Macao satellites differ from their predecessors in their orbits:MSS-1(Macao Science Satellite-1)is in low inclination and the planned MSS-2 will be in highly elliptical orbits.This paper reviews the fundamental advantages and disadvantages of the different possible magnetic measurements:the component(declination,intensity,etc.)and location(satellite,ground,etc.).When planning a survey the choice of component is the"What?"question;the choice of location the"Where?"question.Results from potential theory inform the choice of measurement and data analysis.For example,knowing the vertical component of magnetic field provides a solution for the full magnetic field everywhere in the potential region.This is the familiar Neumann problem.In reality this ideal dataset is never available.In the past we were restricted to declination data only,then direction only,then total intensity only.There have also been large swathes of Earth's surface with no measurements at all(MSS-1 is restricted to latitudes below).These incomplete datasets throw up new questions for potential theory,questions that have some intriguing answers.When only declination is known uniqueness is provided by horizontal intensity measurements on a single line joining the dip-poles.When only directions are involved uniqueness is provided by a single intensity measurement,at least in principle.Paleomagnetic intensities can help.When only total intensity is known,as was largely the case in the early satellite era,uniqueness is provided by a precise location of the magnetic equator.Holes in the data distribution is a familiar problem in geophysical studies.All magnetic measurements sample,to a greater or lesser extent,the potential field everywhere.There is a trade-off between measurements close to the source,good for small targets and high resolution,and the broader sample of a distant measurement.The sampling of a measurement is given by the appropriate Green's function of the Laplacian,which determines both the resolution and scope of the measurement.For example,radial and horizontal measurements near the Earth's surface give a weighted average of the radial component over a patch of the core surface beneath the measurement site about in radius.The patch is smaller for shallower surfaces,for example from satellite to ground.Holes in the data distribution do not correspond to similar holes at the source surface;the price paid is in resolution of the source.I argue that,in the past,we have been too reluctant to take advantage of incomplete and apparently hopeless datasets.
基金supported by the National Key R&D Program of China(No.2023YFB2603602)the National Natural Science Foundation of China(Nos.52222810 and 52178383).
文摘To elucidate the fracturing mechanism of deep hard rock under complex disturbance environments,this study investigates the dynamic failure behavior of pre-damaged granite subjected to multi-source dynamic disturbances.Blasting vibration monitoring was conducted in a deep-buried drill-and-blast tunnel to characterize in-situ dynamic loading conditions.Subsequently,true triaxial compression tests incorporating multi-source disturbances were performed using a self-developed wide-low-frequency true triaxial system to simulate disturbance accumulation and damage evolution in granite.The results demonstrate that combined dynamic disturbances and unloading damage significantly accelerate strength degradation and trigger shear-slip failure along preferentially oriented blast-induced fractures,with strength reductions up to 16.7%.Layered failure was observed on the free surface of pre-damaged granite under biaxial loading,indicating a disturbance-induced fracture localization mechanism.Time-stress-fracture-energy coupling fields were constructed to reveal the spatiotemporal characteristics of fracture evolution.Critical precursor frequency bands(105-150,185-225,and 300-325 kHz)were identified,which serve as diagnostic signatures of impending failure.A dynamic instability mechanism driven by multi-source disturbance superposition and pre-damage evolution was established.Furthermore,a grouting-based wave-absorption control strategy was proposed to mitigate deep dynamic disasters by attenuating disturbance amplitude and reducing excitation frequency.
基金supported by the National Natural Science Foundation of China(No.62101587)the National Funded Postdoctoral Researcher Program of China(No.GZC20233578)。
文摘Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.
基金supported by the National Natural Science Foundation of China(21663032 and 22061041)the Open Sharing Platform for Scientific and Technological Resources of Shaanxi Province(2021PT-004)the National Innovation and Entrepreneurship Training Program for College Students of China(S202110719044)。
文摘The SiO_(2) inverse opal photonic crystals(PC)with a three-dimensional macroporous structure were fabricated by the sacrificial template method,followed by infiltration of a pyrene derivative,1-(pyren-8-yl)but-3-en-1-amine(PEA),to achieve a formaldehyde(FA)-sensitive and fluorescence-enhanced sensing film.Utilizing the specific Aza-Cope rearrangement reaction of allylamine of PEA and FA to generate a strong fluorescent product emitted at approximately 480 nm,we chose a PC whose blue band edge of stopband overlapped with the fluorescence emission wavelength.In virtue of the fluorescence enhancement property derived from slow photon effect of PC,FA was detected highly selectively and sensitively.The limit of detection(LoD)was calculated to be 1.38 nmol/L.Furthermore,the fast detection of FA(within 1 min)is realized due to the interconnected three-dimensional macroporous structure of the inverse opal PC and its high specific surface area.The prepared sensing film can be used for the detection of FA in air,aquatic products and living cells.The very close FA content in indoor air to the result from FA detector,the recovery rate of 101.5%for detecting FA in aquatic products and fast fluorescence imaging in 2 min for living cells demonstrate the reliability and accuracy of our method in practical applications.
基金supported by National Natural Science Foundation of China(12174350)Science and Technology Project of State Grid Henan Electric Power Company(5217Q0240008).
文摘In the heterogeneous power internet of things(IoT)environment,data signals are acquired to support different business systems to realize advanced intelligent applications,with massive,multi-source,heterogeneous and other characteristics.Reliable perception of information and efficient transmission of energy in multi-source heterogeneous environments are crucial issues.Compressive sensing(CS),as an effective method of signal compression and transmission,can accurately recover the original signal only by very few sampling.In this paper,we study a new method of multi-source heterogeneous data signal reconstruction of power IoT based on compressive sensing technology.Based on the traditional compressive sensing technology to directly recover multi-source heterogeneous signals,we fully use the interference subspace information to design the measurement matrix,which directly and effectively eliminates the interference while making the measurement.The measure matrix is optimized by minimizing the average cross-coherence of the matrix,and the reconstruction performance of the new method is further improved.Finally,the effectiveness of the new method with different parameter settings under different multi-source heterogeneous data signal cases is verified by using orthogonal matching pursuit(OMP)and sparsity adaptive matching pursuit(SAMP)for considering the actual environment with prior information utilization of signal sparsity and no prior information utilization of signal sparsity.
基金supported by Natural Science Foundation of China(Nos.62303126,62362008,author Z.Z,https://www.nsfc.gov.cn/,accessed on 20 December 2024)Major Scientific and Technological Special Project of Guizhou Province([2024]014)+2 种基金Guizhou Provincial Science and Technology Projects(No.ZK[2022]General149) ,author Z.Z,https://kjt.guizhou.gov.cn/,accessed on 20 December 2024)The Open Project of the Key Laboratory of Computing Power Network and Information Security,Ministry of Education under Grant 2023ZD037,author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2024B25),author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024).
文摘Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
文摘This paper deeply discusses the causes of gear howling noise,the identification and analysis of multi-source excitation,the transmission path of dynamic noise,simulation and experimental research,case analysis,optimization effect,etc.,aiming to better provide a certain guideline and reference for relevant researchers.
文摘BACKGROUND Colonic diverticular bleeding(CDB)is a leading cause of gastrointestinal blee-ding-related hospitalizations in Japan and is increasingly recognized as a signifi-cant burden in the United States.Identifying the stigmata of a recent hemorrhage(SRH)during colonoscopy enables targeted hemostasis and reduces rebleeding.However,no benchmark exists for an appropriate observation duration,resulting in operator-dependent variation.Short observation periods may lead to missed SRH,whereas unnecessarily prolonged procedures,particularly in older patients,can increase patient burden and limit endoscopy unit availability.METHODS We retrospectively analyzed patients with acute hematochezia who underwent an initial colonoscopy between January 2017 and December 2024 at a Japanese tertiary hospital.The Observation time was measured from scope insertion to SRH detection(excluding therapeutic time)or withdrawal.The primary outcome,the“5%plateau time”,was defined as the point when the proportion of patients newly identified with SRH in each 5-minute interval consistently dropped below 5%.Computed tomography(CT)-based stratified analyses were performed by endoscopists who conducted≥10%of procedures.RESULTS Of the 1039 patients who underwent colonoscopy,845(mean age 77±11 years;64.5%male)were included.Nine board-certified endoscopists performed the procedures.SRH was detected in 286 patients(33.8%),with a median detection time of 19 minutes(interquartile range,12-28 minutes).The overall 5%plateau time was 40 minutes and varied according to the CT findings:40,35,and 30 minutes for no extravasation,right-sided extravasation,and left-sided extravasation,respectively.This time point corresponded to when 80%-90%of SRH cases were detected.De-spite variations in SRH detection rates and observation durations among endoscopists,the 5%plateau time was consistently approximately 40 minutes.CONCLUSION Although it varied according to the CT findings,the overall 5%plateau time was 40 minutes.This offers a practical benchmark for the minimum observation time without SRH detection.
文摘With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.
基金Under the auspices of the Key Program of National Natural Science Foundation of China(No.42030409)。
文摘Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.
基金supported by the National Natural Science Foundation of China(Grant No.41705081)the Shandong Natural Science Foundation Project(Grant No.ZR2019ZD12)the Laoshan Laboratory(Grant No.LSKJ202202203).
文摘This study explored the observation strategy and effectiveness of synoptic-scale adaptive observations for improving sea fog prediction in coastal regions around the Bohai Sea based on a poorly predicted fog event with cold-front synoptic pattern(CFSP).An ensemble Kalman filter data assimilation system for the Weather Research and Forecasting model was adopted with ensemble sensitivity analysis(ESA).By comparing observation impacts(estimated from a 40-member ensemble with ESA)among different meteorological observation variables and pressure levels,the temperature at 850 hPa and surface layer(850 hPa-and-surface temperature)was selected as the target observation type.Additionally,the area with large observation impacts for this observation type was predicted in the transition region of the surface low–high system.This area developed southward with the low and moved eastward with the low–high system,which could be explained by the main features of CFSP.Moreover,both experiments assimilating synthetic and real observations showed that assimilating 850 hPa-and-surface temperature observations generally yielded better fog coverage forecasts in areas with greater observation impacts than areas with smaller impacts.However,the effectiveness of adaptive observations was reduced when real observations rather than synthetic observations were assimilated,which is possibly due to factors such as observation and model errors.The main conclusions above were verified by another typical fog event with CFSP characteristics.Results of this study highlight the importance of improved initial conditions in the transition region of the low–high system for improving fog prediction and provide scientific guidance for implementing an observation network for fog forecasting over the Bohai Sea.
基金Sponsored by Beijing Youth Innovation Talent Support Program for Urban Greening and Landscaping——The 2024 Special Project for Promoting High-Quality Development of Beijing’s Landscaping through Scientific and Technological Innovation(KJCXQT202410).
文摘Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.
基金supported by the National Natural Science Foundation of China(Grant Nos.42475100 and 42405091)supported by the CMA Key Innovation Team(Grant No.CMA2022ZD10)+1 种基金the CMA Weather Modification Centre Innovation Team(Grant No.WMC2023IT02)the National Key R&D Program of China(Grant No.2019YFC1510305).
文摘The ice-phase microphysical characteristics of a stratiform cloud system over the Qilian Mountains in northwestern China on 15 September 2022 were analyzed via aircraft data.The stratiform cloud system developed under southwesterly flows at 500 hPa and was affected locally by topography.Synoptic features and aircraft observations revealed strengthened cloud development on the leeward slope.The ice particle habits and microphysical processes at heights of 6-8 km were investigated.The cloud system was characterized by extremely low supercooled liquid water content at temperatures between−4℃ and−17℃.The ice particle concentrations ranged predominantly from 10 to 30 L^(−1),corresponding to ice water content ranging from 0.01 to 0.05 g m^(−3).Active ice aggregation was observed at temperatures colder than−10°C.The windward side of the cloud system exhibited weaker development and two distinct cloud layers.Intense orographic uplift on the leeward slope enhanced ice particle aggregation.The clouds on the leeside presented lower ice particle concentrations but larger sizes than those on the windward side.The influence of aggregation on the ice particle size distribution was reflected in two main aspects.One aspect was the bimodal spectra at−16℃,with the first peak at 125μm and subpeak at 400-500μm;the other was the broadened size spectra at−13℃ due to significant aggregation of dendrites.
基金supported by the China Postdoctoral Science Foundation(2024M754113)the Chongqing Postdoctoral Innovative Fund(CQBX202419)the Natural Science Foundation of Chongqing(CSTB2023NSCOMSX0629).
文摘Earth-based deep space radar studies celestial bodies by both transmitting and receiving radio waves,whereas radio telescopes only work passively.On the operational level,radar missions use only short observation times,which leaves a large portion of the time available for astronomical observations.However,the design principles used for radar and radio telescopes differ.Technical challenges are involved in making the instruments required to meet the requirements of these two applications simultaneously.In this study,we have attempted to tune a deep space radar system for use in radio astronomical applications and conducted a successful pulsar observation,thus demonstrating the feasibility of using radar systems,particularly distributed deep space radar,to perform astronomical research.Additionally,given the limited astronomical capacity available within the observed frequency range,this system has the potential to contribute to the long-term monitoring of specific radio sources.This work represents the first successful attempt to use an Earth-based deep space radar system to perform radio astronomy in China.We also discuss the challenges of tuning a built radar system for astronomical observation applications and propose recommendations for the design of future large-scale distributed deep space radar systems with innate astronomical capabilities.
