Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,i...Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,is an important ecological barrier area in the temperate arid zone.The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve.In the present study,we assessed the spatiotemporal variations of four ecosystem services(including net primary productivity(NPP),water yield,soil conservation,and habitat quality)in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.In addition,the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis,and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector.During the study period,NPP and soil conservation values in the reserve increased by 48.20%and 25.56%,respectively;conversely,water yield decreased by 16.56%,and there was no significant change in habitat quality.Spatially,both NPP and habitat quality values were higher in the northern part and lower in the southern part,whereas water yield showed an opposite trend.Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation,and exhibited a trade-off relationship with water yield.Water yield and habitat quality also had a trade-off relationship.NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index(NDVI),respectively,while water yield and soil conservation were more affected by digital elevation model(DEM).Therefore,attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management.The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.展开更多
1.Objective In the past decade,a group of medium to giant lead-zinc deposits,represented by Huoshaoyun,Sachakou,and Yuanbaoling,have been discovered in the Aksai Chin region of Karakoram,Xinjiang.They are all located ...1.Objective In the past decade,a group of medium to giant lead-zinc deposits,represented by Huoshaoyun,Sachakou,and Yuanbaoling,have been discovered in the Aksai Chin region of Karakoram,Xinjiang.They are all located in the Mesozoic carbonate and clastic rock formations.The Sachakou leadzinc mining area is adjacent to the northwest of the Huoshaoyun lead-zinc mining area and is in the same stratigraphic layer as Huoshaoyun.Although many scholars have been arguing about the type and age of Huoshaoyun lead-zinc mineralization,few scholars have paid attention to the classification of the ore-bearing strata in the area.The stratigraphy of the Lower Permian Shenxianwan Group to the Upper Cretaceous Tielongtan Group is exposed in the Sachakou area of Karakorum,Xinjiang,however,the Late Permian-Early Triassic stratigraphy is missing(Fig.1a).Due to the harsh natural conditions in the area and the low level of work,the stratigraphic delineation is not exhaustive,and the regional lithology is dominated by carbonates and clastic rocks,which makes it difficult to identify the age of the regional lithology and causes problems for the exploration and research of lead-zinc in the area.展开更多
A checklist of the macrolichens (foliose, fruticose & squamulose) of Barluk Mountain National Nature Reserve located in northwestern China is presented. It was derived from 47 inventories of preserved and undevelo...A checklist of the macrolichens (foliose, fruticose & squamulose) of Barluk Mountain National Nature Reserve located in northwestern China is presented. It was derived from 47 inventories of preserved and undeveloped areas which yielded more than 670 collections containing 102 taxa (99 species, 1 subspecies, 2 varieties). Eight species were found that were new to Xinjiang, China. Twenty-eight species and 2 varieties were found on rock, 31 species on bark of deciduous and coniferous trees, 26 species on soil and 14 species and 1 subspecies over mosses. Foliose lichens were dominant with 76 species, followed by 16 species of squamulose lichens and 7 species of fruticose lichens.展开更多
In this paper,the performance of the classic snowmelt runoff model(SRM)is evaluated in a daily discharge simulation with two different melt models,the empirical temperature-index melt model and the energy-based radiat...In this paper,the performance of the classic snowmelt runoff model(SRM)is evaluated in a daily discharge simulation with two different melt models,the empirical temperature-index melt model and the energy-based radiation melt model,through a case study from the data-sparse mountainous watershed of the Urumqi River basin in Xinjiang Uyghur Autonomous Region of China.The classic SRM,which uses the empirical temperature-index method,and a radiation-based SRM,incorporating shortwave solar radiation and snow albedo,were developed to simulate daily runoff for the spring and summer snowmelt seasons from 2005 to 2012,respectively.Daily meteorological and hydrological data were collected from three stations located in the watershed.Snow cover area(SCA)was extracted from satellite images.Solar radiation inputs were estimated based on a digital elevation model(DEM).The results showed that the overall accuracy of the classic SRM and radiation-based SRM for simulating snowmeltdischarge was relatively high.The classic SRM outperformed the radiation-based SRM due to the robust performance of the temperature-index model in the watershed snowmelt computation.No significant improvement was achieved by employing solar radiation and snow albedo in the snowmelt runoff simulation due to the inclusion of solar radiation as a temperature-dependent energy source and the local pattern of snowmelt behavior throughout the melting season.Our results suggest that the classic SRM simulates daily runoff with favorable accuracy and that the performance of the radiation-based SRM needs to be further improved by more ground-measured data for snowmelt energy input.展开更多
Surface albedo is a quantitative indicator for land surface processes and climate modeling,and plays an important role in surface radiation balance and climate change.In this study,by means of the MCD43A3 surface albe...Surface albedo is a quantitative indicator for land surface processes and climate modeling,and plays an important role in surface radiation balance and climate change.In this study,by means of the MCD43A3 surface albedo product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS),we analyzed the spatiotemporal variation,persistence status,land cover type differences,and annual and seasonal differences of surface albedo,as well as the relationship between surface albedo and various influencing factors(including Normalized Difference Snow Index(NDSI),precipitation,Normalized Difference Vegetation Index(NDVI),land surface temperature,soil moisture,air temperature,and digital elevation model(DEM))in the north of Xinjiang Uygur Autonomous Region(northern Xinjiang)of Northwest China from 2010 to 2020 based on the unary linear regression,Hurst index,and Pearson's correlation coefficient analyses.Combined with the random forest(RF)model and geographical detector(Geodetector),the importance of the above-mentioned influencing factors as well as their interactions on surface albedo were quantitatively evaluated.The results showed that the seasonal average surface albedo in northern Xinjiang was the highest in winter and the lowest in summer.The annual average surface albedo from 2010 to 2020 was high in the west and north and low in the east and south,showing a weak decreasing trend and a small and stable overall variation.Land cover types had a significant impact on the variation of surface albedo.The annual average surface albedo in most regions of northern Xinjiang was positively correlated with NDSI and precipitation,and negatively correlated with NDVI,land surface temperature,soil moisture,and air temperature.In addition,the correlations between surface albedo and various influencing factors showed significant differences for different land cover types and in different seasons.To be specific,NDSI had the largest influence on surface albedo,followed by precipitation,land surface temperature,and soil moisture;whereas NDVI,air temperature,and DEM showed relatively weak influences.However,the interactions of any two influencing factors on surface albedo were enhanced,especially the interaction of air temperature and DEM.NDVI showed a nonlinear enhancement of influence on surface albedo when interacted with land surface temperature or precipitation,with an explanatory power greater than 92.00%.This study has a guiding significance in correctly understanding the land-atmosphere interactions in northern Xinjiang and improving the regional land-surface process simulation and climate prediction.展开更多
Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the curr...Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.展开更多
Ex situ characterization techniques in molecular beam epitaxy(MBE)have inherent limitations,such as being prone to sample contamination and unstable surfaces during sample transfer from the MBE chamber.In recent years...Ex situ characterization techniques in molecular beam epitaxy(MBE)have inherent limitations,such as being prone to sample contamination and unstable surfaces during sample transfer from the MBE chamber.In recent years,the need for improved accuracy and reliability in measurement has driven the increasing adoption of in situ characterization techniques.These techniques,such as reflection high-energy electron diffraction,scanning tunneling microscopy,and X-ray photoelectron spectroscopy,allow direct observation of film growth processes in real time without exposing the sample to air,hence offering insights into the growth mechanisms of epitaxial films with controlled properties.By combining multiple in situ characterization techniques with MBE,researchers can better understand film growth processes,realizing novel materials with customized properties and extensive applications.This review aims to overview the benefits and achievements of in situ characterization techniques in MBE and their applications for material science research.In addition,through further analysis of these techniques regarding their challenges and potential solutions,particularly highlighting the assistance of machine learning to correlate in situ characterization with other material information,we hope to provide a guideline for future efforts in the development of novel monitoring and control schemes for MBE growth processes with improved material properties.展开更多
The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China,exhibiting typical mountain-oasis-desert distribution characteristics.In recent decades,cl...The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China,exhibiting typical mountain-oasis-desert distribution characteristics.In recent decades,climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems.However,the trade-offs and synergies between ecosystem services(ESs)have not been thoroughly examined.This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs.Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)and Revised Wind Erosion Equation(RWEQ)using land use/land cover(LULC),climate,vegetation,soil,and hydrological data,we quantified the spatiotemporal changes in the five principal ESs(carbon storage,water yield,food production,wind and sand prevention,and habitat quality)of the watershed from 1995 to 2020.Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs.The findings reveal that water yield,carbon storage,and habitat quality exhibited relatively high levels in the upstream,while food production and wind and sand prevention dominated the midstream and downstream,respectively.Furthermore,carbon storage,food production,wind and sand prevention,and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020.Specifically,carbon storage,wind and sand prevention,and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream.Food production in the midstream showed a continuously increasing trend during the study period.Trade-off relationships were identified between water yield and wind and sand prevention,water yield and carbon storage,food production and water yield,and habitat quality and wind and sand prevention.Prominent temporal and spatial synergistic relationships were observed between different ESs,notably between carbon storage and habitat quality,carbon storage and food production,food production and wind and sand prevention,and food production and habitat quality.Water resources emerged as a decisive factor for the sustainable development of the basin,thus highlighting the intricate trade-offs and synergies between water yield and the other four services,particularly the relationship with food production,which warrants further attention.This research is of great significance for the protection and sustainable development of river basins in arid areas.展开更多
Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating a...Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final(IMERG-F)precipitation product,as well as hydrological simulations in the Ebinur Lake Basin,further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region.The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas,and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.展开更多
In this paper,we introduce the weighted multilinear p-adic Hardy operator and weighted multilinear p-adic Ces`aro operator,we also obtain the boundedness of these two operators on the product of p-adic Herz spaces and...In this paper,we introduce the weighted multilinear p-adic Hardy operator and weighted multilinear p-adic Ces`aro operator,we also obtain the boundedness of these two operators on the product of p-adic Herz spaces and p-adic Morrey-Herz spaces,the corresponding operator norms are also established in each case.Moreover,the boundedness of commutators of these two operators with symbols in central bounded mean oscillation spaces and Lipschitz spaces on p-adic Morrey-Herz spaces are also given.展开更多
Ice and snow tourism in China has grown significantly since the country successfully hosted the Beijing Winter Olympics.Climatic conditions profoundly impact the development of ice and snow tourism;however,most studie...Ice and snow tourism in China has grown significantly since the country successfully hosted the Beijing Winter Olympics.Climatic conditions profoundly impact the development of ice and snow tourism;however,most studies have focused on constructing different climate suitability indicators for ice and snow tourism to evaluate individual regions,lacking horizontal comparative studies across multiple regions.This study aims to enrich the connotation of climate suitability for ice and snow sports,establish an evaluation model based on snowfall amount,temperature,and wind speed,and use daily meteorological data from 1991 to 2021 to horizontally compare the climate suitability for ice and snow sports in major ski tourism destinations in China.This study boasts four major findings:1)the average ice and snow sports climate index of each region decreases over time,and the overall suitability of the climate for ice and snow sports is reducing;2)northern Xinjiang exhibits the most evident regional differentiation from‘very suitable’to‘generally suitable’;3)the spatial zoning of climate suitability for ice and snow sports exhibits heterogeneity,as northern Xinjiang is divided into two‘suitable and above’zones with rotating empirical orthogonal function(REOF).Correspondingly,the four provinces of Hebei,Heilongjiang,Jilin,and Liaoning are divided into three‘generally suitable and above’zones;4)snowfall amount is the main factor affecting the climate suitability of ice and snow sports in the major ski tourist destinations in China.展开更多
Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurr...Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.展开更多
Zr-based amorphous alloys have attracted extensive attention because of their large glassy formation ability, wide supercooled liquid region, high elasticity, and unique mechanical strength induced by their icosahedra...Zr-based amorphous alloys have attracted extensive attention because of their large glassy formation ability, wide supercooled liquid region, high elasticity, and unique mechanical strength induced by their icosahedral local structures.To determine the microstructures of Zr–Cu clusters, the stable and metastable geometry of Zr_(n)Cu(n=2–12) clusters are screened out via the CALYPSO method using machine-learning potentials, and then the electronic structures are investigated using density functional theory. The results show that the Zr_(n)Cu(n ≥ 3) clusters possess three-dimensional geometries, Zr_(n)Cu(n≥9) possess cage-like geometries, and the Zr_(12)Cu cluster has icosahedral geometry. The binding energy per atom gradually gets enlarged with the increase in the size of the clusters, and Zr_(n)Cu(n=5,7,9,12) have relatively better stability than their neighbors. The magnetic moment of most Zr_(n)Cu clusters is just 1μB, and the main components of the highest occupied molecular orbitals(HOMOs) in the Zr_(12)Cu cluster come from the Zr-d state. There are hardly any localized two-center bonds, and there are about 20 σ-type delocalized three-center bonds.展开更多
With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(...With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.展开更多
Nova outbursts are the results of thermonuclear runaways,which occur when sufficient material accretes on the surfaces of white dwarfs(WDs).Using the MESA code,we construct a detailed grid for carbon-oxygen and oxygen...Nova outbursts are the results of thermonuclear runaways,which occur when sufficient material accretes on the surfaces of white dwarfs(WDs).Using the MESA code,we construct a detailed grid for carbon-oxygen and oxygen-neon-magnesium novae.By employing population synthesis methods,we conduct a statistical analysis of the distribution of novae in the Milky Way.In our models,on average,a typical nova system may undergo about8000 eruptions and the Galactic nova rate is~130 yr^(-1).The C,N,and O elements in nova ejecta are strongly affected by the mixing degree between WD core and accreted material.Our results show that the average value of^(12)C/^(13)C in nova ejecta is about an order of magnitude lower than that on the surface of a red giant,that for^(16)O/^(17)O is about 5 times lower,and that for^(14)N/^(15)N is about 1.5 times lower.The annual yields of^(13)C,^(15)N,and^(17)O from nova ejection are larger than those from AGB stars.This indicates that compared to a red giant,nova eruptions are a more important source of the odd-numbered nuclear elements of^(13)C,^(15)N,and^(17)O in the Galactic interstellar medium.展开更多
The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightwei...The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightweight YOLOv8-based obstacle detection algorithm optimized for UAV obstacle avoidance.The algorithm enhances the detection capability for small and irregular obstacles by removing the P5 feature layer and introducing deformable convolution v2(DCNv2)to optimize the cross stage partial bottleneck with 2 convolutions and fusion(C2f)module.Additionally,it reduces the model’s parameter count and computational load by constructing the unite ghost and depth-wise separable convolution(UGDConv)series of lightweight convolutions and a lightweight detection head.Based on this,we designed a visual obstacle avoidance algorithm that can improve the obstacle avoidance performance of UAVs in different environments.In particular,we propose an adaptive distance detection algorithm based on obstacle attributes to solve the ranging problem for multiple types and irregular obstacles to further enhance the UAV’s obstacle avoidance capability.To verify the effectiveness of the algorithm,the UAV obstacle detection(UAD)dataset was created.The experimental results show that UAD-YOLOv8 improves mAP50 by 3.4%and reduces GFLOPs by 34.5%compared to YOLOv8n while reducing the number of parameters by 77.4%and the model size by 73%.These improvements significantly enhance the UAV’s obstacle avoidance performance in complex environments,demonstrating its wide range of applications.展开更多
We analyze the frequencies of three known roAp stars,TIC 96315731,TIC 72392575,and TIC 318007796,using the light curves from the Transiting Exoplanet Survey Satellite.For TIC 96315731,the rotational and pulsational fr...We analyze the frequencies of three known roAp stars,TIC 96315731,TIC 72392575,and TIC 318007796,using the light curves from the Transiting Exoplanet Survey Satellite.For TIC 96315731,the rotational and pulsational frequencies are 0.1498360 day^(-1)and 165.2609 day^(-1),respectively.In the case of TIC 72392575,the rotational frequency is 0.25551 day^(-1).We detect a quintuplet of pulsation frequencies with a center frequency of135.9233 day^(-1),along with two signals within the second pair of rotational sidelobes of the quintuplet separated by the rotation frequency.These two signals may correspond to the frequencies of a dipole mode.In TIC318007796,the rotational and pulsational frequencies are 0.2475021 day^(-1),192.73995 day^(-1),and196.33065 day^(-1),respectively.Based on the oblique pulsator model,we calculate the rotation inclination(i)and magnetic obliquity angle(b)for the stars,which provide the geometry of the pulsation modes.Combining the phases of the frequency quintuplets,the pulsation amplitude and phase modulation curves,and the results of spherical harmonic decomposition,we conclude that the pulsation modes of frequency quintuplets in TIC96315731,TIC 72392575,and TIC 318007796 correspond to distorted dipole mode,distorted quadrupole mode,and distorted dipole mode,respectively.展开更多
A t-container Ct(u,v)is a set of t internally disjoint paths between two distinct vertices u and v in a graph G,i.e.,Ct(u,v)={P_(1),P_(2),···,Pt}.Moreover,if V(P_(1))∪V(P_(2))∪···∪V(Pt...A t-container Ct(u,v)is a set of t internally disjoint paths between two distinct vertices u and v in a graph G,i.e.,Ct(u,v)={P_(1),P_(2),···,Pt}.Moreover,if V(P_(1))∪V(P_(2))∪···∪V(Pt)=V(G)then Ct(u,v)is called a spanning t-container,denoted by C_(t)^(sc)(u,v).The length of C_(t)^(sc)(u,v)={P_(1),P_(2),···,Pt}is l(C_(t)^(sc)(u,v))=max{l(P_(i))|1≤i≤t}.A graph G is spanning t-connected if there exists a spanning t-container between any two distinct vertices u and v in G.Assume that u and v are two distinct vertices in a spanning t-connected graph G.Let D_(t)^(sc)(u,v)be the collection of all C_(t)^(sc)(u,v)’s.Define the spanning t-wide distance between u and v in G,d_(t)^(sc)(u,v)=min{l(C_(t)^(sc)(u,v))|C_(t)^(sc)(u,v)∈D_(t)^(sc)(u,v)},and the spanning t-wide diameter of G,D_(t)^(sc)(G)=max{d_(t)^(sc)(u,v)|u,v∈V(G)}.In particular,the spanning wide diameter of G is D_(κ)^(sc)(G),whereκis the connectivity of G.In the paper we provide the upper and lower bounds of the spanning wide diameter of a graph,and show that the bounds are best possible.We also determine the exact values of wide diameters of some well known graphs including Harary graphs and generalized Petersen graphs et al..展开更多
Active surface technique is one of the key technologies to ensure the reflector accuracy of the millimeter/submillimeter wave large reflector antenna.The antenna is complex,large-scale,and high-precision equipment,and...Active surface technique is one of the key technologies to ensure the reflector accuracy of the millimeter/submillimeter wave large reflector antenna.The antenna is complex,large-scale,and high-precision equipment,and its active surfaces are affected by various factors that are difficult to comprehensively deal with.In this paper,based on the advantage of the deep learning method that can be improved through data learning,we propose the active adjustment value analysis method of large reflector antenna based on deep learning.This method constructs a neural network model for antenna active adjustment analysis in view of the fact that a large reflector antenna consists of multiple panels spliced together.Based on the constraint that a single actuator has to support multiple panels(usually 4),an autonomously learned neural network emphasis layer module is designed to enhance the adaptability of the active adjustment neural network model.The classical 8-meter antenna is used as a case study,the actuators have a mean adjustment error of 0.00252 mm,and the corresponding antenna surface error is0.00523 mm.This active adjustment result shows the effectiveness of the method in this paper.展开更多
Let G be a connected graph of order n and m_(RD)^(L)_(G)I denote the number of reciprocal distance Laplacian eigenvaluesof G in an interval I.For a given interval I,we mainly present several bounds on m_(RD)^(L)_(G)I ...Let G be a connected graph of order n and m_(RD)^(L)_(G)I denote the number of reciprocal distance Laplacian eigenvaluesof G in an interval I.For a given interval I,we mainly present several bounds on m_(RD)^(L)_(G)I in terms of various structuralparameters of the graph G,including vertex-connectivity,independence number and pendant vertices.展开更多
基金This research was funded by the Key Laboratory for Sustainable Development of Xinjiang's Historical and Cultural Tourism,Xinjiang University,China(LY2022-06)the Tianchi Talent Project.
文摘Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,is an important ecological barrier area in the temperate arid zone.The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve.In the present study,we assessed the spatiotemporal variations of four ecosystem services(including net primary productivity(NPP),water yield,soil conservation,and habitat quality)in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.In addition,the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis,and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector.During the study period,NPP and soil conservation values in the reserve increased by 48.20%and 25.56%,respectively;conversely,water yield decreased by 16.56%,and there was no significant change in habitat quality.Spatially,both NPP and habitat quality values were higher in the northern part and lower in the southern part,whereas water yield showed an opposite trend.Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation,and exhibited a trade-off relationship with water yield.Water yield and habitat quality also had a trade-off relationship.NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index(NDVI),respectively,while water yield and soil conservation were more affected by digital elevation model(DEM).Therefore,attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management.The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.
基金Supported by the Second Tibetan Plateau Scientific Expedition and Research(2021QZKK0303)the Natural Science Basic Research Program of Shaanxi(2020JQ-440 and 2021JQ-327)+1 种基金the Major Science and Technology Project of Xinjiang Uygur Autonomous Region(2021A03001-2)the projects of the China Geological Survey(DD20230333 and DD20230048).
文摘1.Objective In the past decade,a group of medium to giant lead-zinc deposits,represented by Huoshaoyun,Sachakou,and Yuanbaoling,have been discovered in the Aksai Chin region of Karakoram,Xinjiang.They are all located in the Mesozoic carbonate and clastic rock formations.The Sachakou leadzinc mining area is adjacent to the northwest of the Huoshaoyun lead-zinc mining area and is in the same stratigraphic layer as Huoshaoyun.Although many scholars have been arguing about the type and age of Huoshaoyun lead-zinc mineralization,few scholars have paid attention to the classification of the ore-bearing strata in the area.The stratigraphy of the Lower Permian Shenxianwan Group to the Upper Cretaceous Tielongtan Group is exposed in the Sachakou area of Karakorum,Xinjiang,however,the Late Permian-Early Triassic stratigraphy is missing(Fig.1a).Due to the harsh natural conditions in the area and the low level of work,the stratigraphic delineation is not exhaustive,and the regional lithology is dominated by carbonates and clastic rocks,which makes it difficult to identify the age of the regional lithology and causes problems for the exploration and research of lead-zinc in the area.
文摘A checklist of the macrolichens (foliose, fruticose & squamulose) of Barluk Mountain National Nature Reserve located in northwestern China is presented. It was derived from 47 inventories of preserved and undeveloped areas which yielded more than 670 collections containing 102 taxa (99 species, 1 subspecies, 2 varieties). Eight species were found that were new to Xinjiang, China. Twenty-eight species and 2 varieties were found on rock, 31 species on bark of deciduous and coniferous trees, 26 species on soil and 14 species and 1 subspecies over mosses. Foliose lichens were dominant with 76 species, followed by 16 species of squamulose lichens and 7 species of fruticose lichens.
基金funded by the National Natural Science Foundation of China (41771470, 51069017 and 41261090)
文摘In this paper,the performance of the classic snowmelt runoff model(SRM)is evaluated in a daily discharge simulation with two different melt models,the empirical temperature-index melt model and the energy-based radiation melt model,through a case study from the data-sparse mountainous watershed of the Urumqi River basin in Xinjiang Uyghur Autonomous Region of China.The classic SRM,which uses the empirical temperature-index method,and a radiation-based SRM,incorporating shortwave solar radiation and snow albedo,were developed to simulate daily runoff for the spring and summer snowmelt seasons from 2005 to 2012,respectively.Daily meteorological and hydrological data were collected from three stations located in the watershed.Snow cover area(SCA)was extracted from satellite images.Solar radiation inputs were estimated based on a digital elevation model(DEM).The results showed that the overall accuracy of the classic SRM and radiation-based SRM for simulating snowmeltdischarge was relatively high.The classic SRM outperformed the radiation-based SRM due to the robust performance of the temperature-index model in the watershed snowmelt computation.No significant improvement was achieved by employing solar radiation and snow albedo in the snowmelt runoff simulation due to the inclusion of solar radiation as a temperature-dependent energy source and the local pattern of snowmelt behavior throughout the melting season.Our results suggest that the classic SRM simulates daily runoff with favorable accuracy and that the performance of the radiation-based SRM needs to be further improved by more ground-measured data for snowmelt energy input.
基金This research was supported by the National Key Research and Development Program of China(2019YFC1510505)the Xinjiang University PhD Start-up Fund(BS210226)the National College Student Research Training Plan of China(202210755004).
文摘Surface albedo is a quantitative indicator for land surface processes and climate modeling,and plays an important role in surface radiation balance and climate change.In this study,by means of the MCD43A3 surface albedo product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS),we analyzed the spatiotemporal variation,persistence status,land cover type differences,and annual and seasonal differences of surface albedo,as well as the relationship between surface albedo and various influencing factors(including Normalized Difference Snow Index(NDSI),precipitation,Normalized Difference Vegetation Index(NDVI),land surface temperature,soil moisture,air temperature,and digital elevation model(DEM))in the north of Xinjiang Uygur Autonomous Region(northern Xinjiang)of Northwest China from 2010 to 2020 based on the unary linear regression,Hurst index,and Pearson's correlation coefficient analyses.Combined with the random forest(RF)model and geographical detector(Geodetector),the importance of the above-mentioned influencing factors as well as their interactions on surface albedo were quantitatively evaluated.The results showed that the seasonal average surface albedo in northern Xinjiang was the highest in winter and the lowest in summer.The annual average surface albedo from 2010 to 2020 was high in the west and north and low in the east and south,showing a weak decreasing trend and a small and stable overall variation.Land cover types had a significant impact on the variation of surface albedo.The annual average surface albedo in most regions of northern Xinjiang was positively correlated with NDSI and precipitation,and negatively correlated with NDVI,land surface temperature,soil moisture,and air temperature.In addition,the correlations between surface albedo and various influencing factors showed significant differences for different land cover types and in different seasons.To be specific,NDSI had the largest influence on surface albedo,followed by precipitation,land surface temperature,and soil moisture;whereas NDVI,air temperature,and DEM showed relatively weak influences.However,the interactions of any two influencing factors on surface albedo were enhanced,especially the interaction of air temperature and DEM.NDVI showed a nonlinear enhancement of influence on surface albedo when interacted with land surface temperature or precipitation,with an explanatory power greater than 92.00%.This study has a guiding significance in correctly understanding the land-atmosphere interactions in northern Xinjiang and improving the regional land-surface process simulation and climate prediction.
基金supported by Ministry of Science and Technology of China (Grant No. 2018YFA0606501)National Natural Science Foundation of China (Grant No. 42075037)+1 种基金Key Laboratory Open Research Program of Xinjiang Science and Technology Department (Grant No. 2022D04009)the National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility” (EarthLab)。
文摘Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.
基金supported by the National Key R&D Program of China(Grant No.2021YFB2206503)National Natural Science Foundation of China(Grant No.62274159)+1 种基金CAS Project for Young Scientists in Basic Research(Grant No.YSBR-056)the“Strategic Priority Research Program”of the Chinese Academy of Sciences(Grant No.XDB43010102).
文摘Ex situ characterization techniques in molecular beam epitaxy(MBE)have inherent limitations,such as being prone to sample contamination and unstable surfaces during sample transfer from the MBE chamber.In recent years,the need for improved accuracy and reliability in measurement has driven the increasing adoption of in situ characterization techniques.These techniques,such as reflection high-energy electron diffraction,scanning tunneling microscopy,and X-ray photoelectron spectroscopy,allow direct observation of film growth processes in real time without exposing the sample to air,hence offering insights into the growth mechanisms of epitaxial films with controlled properties.By combining multiple in situ characterization techniques with MBE,researchers can better understand film growth processes,realizing novel materials with customized properties and extensive applications.This review aims to overview the benefits and achievements of in situ characterization techniques in MBE and their applications for material science research.In addition,through further analysis of these techniques regarding their challenges and potential solutions,particularly highlighting the assistance of machine learning to correlate in situ characterization with other material information,we hope to provide a guideline for future efforts in the development of novel monitoring and control schemes for MBE growth processes with improved material properties.
基金financially supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01C77)the PhD Programs Foundation of Xinjiang University(BS202105).
文摘The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China,exhibiting typical mountain-oasis-desert distribution characteristics.In recent decades,climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems.However,the trade-offs and synergies between ecosystem services(ESs)have not been thoroughly examined.This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs.Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)and Revised Wind Erosion Equation(RWEQ)using land use/land cover(LULC),climate,vegetation,soil,and hydrological data,we quantified the spatiotemporal changes in the five principal ESs(carbon storage,water yield,food production,wind and sand prevention,and habitat quality)of the watershed from 1995 to 2020.Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs.The findings reveal that water yield,carbon storage,and habitat quality exhibited relatively high levels in the upstream,while food production and wind and sand prevention dominated the midstream and downstream,respectively.Furthermore,carbon storage,food production,wind and sand prevention,and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020.Specifically,carbon storage,wind and sand prevention,and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream.Food production in the midstream showed a continuously increasing trend during the study period.Trade-off relationships were identified between water yield and wind and sand prevention,water yield and carbon storage,food production and water yield,and habitat quality and wind and sand prevention.Prominent temporal and spatial synergistic relationships were observed between different ESs,notably between carbon storage and habitat quality,carbon storage and food production,food production and wind and sand prevention,and food production and habitat quality.Water resources emerged as a decisive factor for the sustainable development of the basin,thus highlighting the intricate trade-offs and synergies between water yield and the other four services,particularly the relationship with food production,which warrants further attention.This research is of great significance for the protection and sustainable development of river basins in arid areas.
基金supported by The Technology Innovation Team(Tianshan Innovation Team),Innovative Team for Efficient Utilization of Water Resources in Arid Regions(2022TSYCTD0001)the National Natural Science Foundation of China(42171269)the Xinjiang Academician Workstation Cooperative Research Project(2020.B-001).
文摘Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final(IMERG-F)precipitation product,as well as hydrological simulations in the Ebinur Lake Basin,further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region.The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas,and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.
文摘In this paper,we introduce the weighted multilinear p-adic Hardy operator and weighted multilinear p-adic Ces`aro operator,we also obtain the boundedness of these two operators on the product of p-adic Herz spaces and p-adic Morrey-Herz spaces,the corresponding operator norms are also established in each case.Moreover,the boundedness of commutators of these two operators with symbols in central bounded mean oscillation spaces and Lipschitz spaces on p-adic Morrey-Herz spaces are also given.
基金Under the auspices of the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01C372)National Natural Science Foundation of China(No.42261041)+1 种基金Major Key Programs of Philosophy and Social Sciences in Xinjiang University(No.22APY016)Xinjiang Uygur Autonomous Region Federation of Social Sciences Project Key Project(No.2023ZJFLW10)。
文摘Ice and snow tourism in China has grown significantly since the country successfully hosted the Beijing Winter Olympics.Climatic conditions profoundly impact the development of ice and snow tourism;however,most studies have focused on constructing different climate suitability indicators for ice and snow tourism to evaluate individual regions,lacking horizontal comparative studies across multiple regions.This study aims to enrich the connotation of climate suitability for ice and snow sports,establish an evaluation model based on snowfall amount,temperature,and wind speed,and use daily meteorological data from 1991 to 2021 to horizontally compare the climate suitability for ice and snow sports in major ski tourism destinations in China.This study boasts four major findings:1)the average ice and snow sports climate index of each region decreases over time,and the overall suitability of the climate for ice and snow sports is reducing;2)northern Xinjiang exhibits the most evident regional differentiation from‘very suitable’to‘generally suitable’;3)the spatial zoning of climate suitability for ice and snow sports exhibits heterogeneity,as northern Xinjiang is divided into two‘suitable and above’zones with rotating empirical orthogonal function(REOF).Correspondingly,the four provinces of Hebei,Heilongjiang,Jilin,and Liaoning are divided into three‘generally suitable and above’zones;4)snowfall amount is the main factor affecting the climate suitability of ice and snow sports in the major ski tourist destinations in China.
基金the National Natural Science Founda-tion of China(62062062)hosted by Gulila Altenbek.
文摘Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.11864040,11964037,and 11664038)。
文摘Zr-based amorphous alloys have attracted extensive attention because of their large glassy formation ability, wide supercooled liquid region, high elasticity, and unique mechanical strength induced by their icosahedral local structures.To determine the microstructures of Zr–Cu clusters, the stable and metastable geometry of Zr_(n)Cu(n=2–12) clusters are screened out via the CALYPSO method using machine-learning potentials, and then the electronic structures are investigated using density functional theory. The results show that the Zr_(n)Cu(n ≥ 3) clusters possess three-dimensional geometries, Zr_(n)Cu(n≥9) possess cage-like geometries, and the Zr_(12)Cu cluster has icosahedral geometry. The binding energy per atom gradually gets enlarged with the increase in the size of the clusters, and Zr_(n)Cu(n=5,7,9,12) have relatively better stability than their neighbors. The magnetic moment of most Zr_(n)Cu clusters is just 1μB, and the main components of the highest occupied molecular orbitals(HOMOs) in the Zr_(12)Cu cluster come from the Zr-d state. There are hardly any localized two-center bonds, and there are about 20 σ-type delocalized three-center bonds.
基金supported by Tianshan Talent Training Project-Xinjiang Science and Technology Innovation Team Program(2023TSYCTD).
文摘With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.
文摘Nova outbursts are the results of thermonuclear runaways,which occur when sufficient material accretes on the surfaces of white dwarfs(WDs).Using the MESA code,we construct a detailed grid for carbon-oxygen and oxygen-neon-magnesium novae.By employing population synthesis methods,we conduct a statistical analysis of the distribution of novae in the Milky Way.In our models,on average,a typical nova system may undergo about8000 eruptions and the Galactic nova rate is~130 yr^(-1).The C,N,and O elements in nova ejecta are strongly affected by the mixing degree between WD core and accreted material.Our results show that the average value of^(12)C/^(13)C in nova ejecta is about an order of magnitude lower than that on the surface of a red giant,that for^(16)O/^(17)O is about 5 times lower,and that for^(14)N/^(15)N is about 1.5 times lower.The annual yields of^(13)C,^(15)N,and^(17)O from nova ejection are larger than those from AGB stars.This indicates that compared to a red giant,nova eruptions are a more important source of the odd-numbered nuclear elements of^(13)C,^(15)N,and^(17)O in the Galactic interstellar medium.
基金supported by Xinjiang Uygur Autonomous Region Metrology and Testing Institute Project(Grant No.XJRIMT2022-5)Tianshan Talent Training Project-Xinjiang Science and Technology Innovation Team Program(2023TSYCTD0012).
文摘The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightweight YOLOv8-based obstacle detection algorithm optimized for UAV obstacle avoidance.The algorithm enhances the detection capability for small and irregular obstacles by removing the P5 feature layer and introducing deformable convolution v2(DCNv2)to optimize the cross stage partial bottleneck with 2 convolutions and fusion(C2f)module.Additionally,it reduces the model’s parameter count and computational load by constructing the unite ghost and depth-wise separable convolution(UGDConv)series of lightweight convolutions and a lightweight detection head.Based on this,we designed a visual obstacle avoidance algorithm that can improve the obstacle avoidance performance of UAVs in different environments.In particular,we propose an adaptive distance detection algorithm based on obstacle attributes to solve the ranging problem for multiple types and irregular obstacles to further enhance the UAV’s obstacle avoidance capability.To verify the effectiveness of the algorithm,the UAV obstacle detection(UAD)dataset was created.The experimental results show that UAD-YOLOv8 improves mAP50 by 3.4%and reduces GFLOPs by 34.5%compared to YOLOv8n while reducing the number of parameters by 77.4%and the model size by 73%.These improvements significantly enhance the UAV’s obstacle avoidance performance in complex environments,demonstrating its wide range of applications.
基金Funding for the TESS mission is provided by the NASA Explorer Programsupport of the National Natural Science Foundation of China(NSFC,grant Nos.U2031204,12373038,12163005,and 12288102)+1 种基金the science research grants from the China Manned Space Project with No.CMSCSST-2021-A10the Natural Science Foundation of Xinjiang Nos.2022D01D85 and 2022TSYCLJ0006。
文摘We analyze the frequencies of three known roAp stars,TIC 96315731,TIC 72392575,and TIC 318007796,using the light curves from the Transiting Exoplanet Survey Satellite.For TIC 96315731,the rotational and pulsational frequencies are 0.1498360 day^(-1)and 165.2609 day^(-1),respectively.In the case of TIC 72392575,the rotational frequency is 0.25551 day^(-1).We detect a quintuplet of pulsation frequencies with a center frequency of135.9233 day^(-1),along with two signals within the second pair of rotational sidelobes of the quintuplet separated by the rotation frequency.These two signals may correspond to the frequencies of a dipole mode.In TIC318007796,the rotational and pulsational frequencies are 0.2475021 day^(-1),192.73995 day^(-1),and196.33065 day^(-1),respectively.Based on the oblique pulsator model,we calculate the rotation inclination(i)and magnetic obliquity angle(b)for the stars,which provide the geometry of the pulsation modes.Combining the phases of the frequency quintuplets,the pulsation amplitude and phase modulation curves,and the results of spherical harmonic decomposition,we conclude that the pulsation modes of frequency quintuplets in TIC96315731,TIC 72392575,and TIC 318007796 correspond to distorted dipole mode,distorted quadrupole mode,and distorted dipole mode,respectively.
基金supported by the National Natural Science Foundation of the People's Republic of China“On disjoint path covers of graphs and related problems”(12261085)Natural Science Foundation of Xinjiang Uygur Autonomous Region of China“On spanning wide diameter and spanning cycle ability of interconnection networks”(2021D01C116)。
文摘A t-container Ct(u,v)is a set of t internally disjoint paths between two distinct vertices u and v in a graph G,i.e.,Ct(u,v)={P_(1),P_(2),···,Pt}.Moreover,if V(P_(1))∪V(P_(2))∪···∪V(Pt)=V(G)then Ct(u,v)is called a spanning t-container,denoted by C_(t)^(sc)(u,v).The length of C_(t)^(sc)(u,v)={P_(1),P_(2),···,Pt}is l(C_(t)^(sc)(u,v))=max{l(P_(i))|1≤i≤t}.A graph G is spanning t-connected if there exists a spanning t-container between any two distinct vertices u and v in G.Assume that u and v are two distinct vertices in a spanning t-connected graph G.Let D_(t)^(sc)(u,v)be the collection of all C_(t)^(sc)(u,v)’s.Define the spanning t-wide distance between u and v in G,d_(t)^(sc)(u,v)=min{l(C_(t)^(sc)(u,v))|C_(t)^(sc)(u,v)∈D_(t)^(sc)(u,v)},and the spanning t-wide diameter of G,D_(t)^(sc)(G)=max{d_(t)^(sc)(u,v)|u,v∈V(G)}.In particular,the spanning wide diameter of G is D_(κ)^(sc)(G),whereκis the connectivity of G.In the paper we provide the upper and lower bounds of the spanning wide diameter of a graph,and show that the bounds are best possible.We also determine the exact values of wide diameters of some well known graphs including Harary graphs and generalized Petersen graphs et al..
基金supported by the National Key R&D Program of China No.2021YFC220350the National Natural Science Foundation of China Nos.12303094&52165053+2 种基金the Natural Science Foundation of Xinjiang Uygur Autonomous Region Nos.2022D01C683the China Postdoctoral Science Foundation Nos.2023T160549&2021M702751in part by Guangdong Basic and Applied Basic Research Foundation Nos.2020A1515111043&2023A1515010703。
文摘Active surface technique is one of the key technologies to ensure the reflector accuracy of the millimeter/submillimeter wave large reflector antenna.The antenna is complex,large-scale,and high-precision equipment,and its active surfaces are affected by various factors that are difficult to comprehensively deal with.In this paper,based on the advantage of the deep learning method that can be improved through data learning,we propose the active adjustment value analysis method of large reflector antenna based on deep learning.This method constructs a neural network model for antenna active adjustment analysis in view of the fact that a large reflector antenna consists of multiple panels spliced together.Based on the constraint that a single actuator has to support multiple panels(usually 4),an autonomously learned neural network emphasis layer module is designed to enhance the adaptability of the active adjustment neural network model.The classical 8-meter antenna is used as a case study,the actuators have a mean adjustment error of 0.00252 mm,and the corresponding antenna surface error is0.00523 mm.This active adjustment result shows the effectiveness of the method in this paper.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region of China“Graph problems of topological parameters based on the spectra of graph matrices”(2021D01C069)the National Natural Science Foundation of the People's Republic of China“The investigation of spectral properties of graph operations and their related problems”(12161085)。
文摘Let G be a connected graph of order n and m_(RD)^(L)_(G)I denote the number of reciprocal distance Laplacian eigenvaluesof G in an interval I.For a given interval I,we mainly present several bounds on m_(RD)^(L)_(G)I in terms of various structuralparameters of the graph G,including vertex-connectivity,independence number and pendant vertices.
