Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

适于GlobalAllomeTree国际数据平台的标准化中国主要树种树高-胸径方程研建

GlobalAllomeTree作为共享异速方程的国际网络平台,逐渐受到全球高度关注。当前,为促进该项国际合作,针对当前该平台缺乏中国主要树种生长异速方程的现状,系统性更新标准化中国主要树种树高-胸径方程。由于树冠和下部灌木及草丛遮挡,树高相对于胸径测量具有一定的难度,因此需要使用数学工具进行计算。选取了36个树种为材料构建树高-胸径关系方程,以全国主要树种的二元材积模型、各地区一元材积表为基础材料,以取样径阶为1 cm间隔所生成1692组树高-胸径数据作为建立方程样本,1238组外业调查数据为验证样本。建模结果表明:36个主要树种的1692组树高-胸径数据建立的全国通用性树高-胸径方程拟合相关系数(R2)为0.801,方程拟合结果较好,说明可以通过测定胸径,带入树高(H,m)-胸径(D,cm)方程(H=aDb)预估树高;对36个主要树种的树高-胸径方程进行拟合,决定系数R2值均大于0.916,平均误差(ME)、平均绝对误差(MAE)和均方根误差(RMSE)相对较小,方程整体精度较高,可广泛推广;将外业采集的1238组树高-胸径数据,根据36个主要树种树高-胸径方程拟合公式及参数估计值a、b进行方程精度验证,方程预测的平均相对误差为16.86%,在误差允许范围内,并且模型形式规范,可为GlobalAllomeTree平台用户提供科学参考。

Parkland trees on smallholder farms ameliorate soil physical-chemical properties in the semi-arid area of Tigray,Ethiopia

Proposed agroforestry options should begin with the species that farmers are most familiar with,which would be the native multipurpose trees that have evolved under smallholder farms and socioeconomic conditions.The African birch(Anogeissus leiocarpa(DC.)Guill.&Perr.)and pink jacaranda(Stereospermum kunthianum Cham.)trees are the dominant species in the agroforestry parkland system in the drylands of Tigray,Ethiopia.Smallholder farmers highly value these trees for their multifunctional uses including timber,firewood,charcoal,medicine,etc.These trees also could improve soil fertility.However,the amount of soil physical and chemical properties enhanced by the two species must be determined to maintain the sustainable conservation of the species in the parklands and to scale up to similar agroecological systems.Hence,we selected twelve isolated trees,six from each species that had similar dendrometric characteristics and were growing in similar environmental conditions.We divided the canopy cover of each tree into three radial distances:mid-canopy,canopy edge,and canopy gap(control).At each distance,we took soil samples from three different depths.We collected 216 soil samples(half disturbed and the other half undisturbed)from each canopy position and soil depth.Bulk density(BD),soil moisture content(SMC),soil organic carbon(SOC),total nitrogen(TN),available phosphorus(AP),available potassium(AK),p H,electrical conductivity(EC),and cation exchange capacity(CEC)were analysed.Results revealed that soil physical and chemical properties significantly improved except for soil texture and EC under both species,CEC under A.leiocarpus,and soil p H under S.kunthianum,all the studied soils were improved under both species canopy as compared with canopy gap.SMC,TN,AP,and AK under canopy of these trees were respectively 24.1%,11.1%,55.0%,and 9.3% higher than those soils under control.The two parkland agroforestry species significantly enhanced soil fertility near the canopy of topsoil through improving soil physical and chemical properties.These two species were recommended in the drylands with similar agro-ecological systems.

Aging Mongolian pine plantations face high risks of drought-induced growth decline:evidence from both individual tree and forest stand measurements

Discerning vulnerability differences among different aged trees to drought-driven growth decline or to mortality is critical to implement age-specific countermeasures for forest management in water-limited areas.An important species for afforestation in dry environments of northern China,Mongolian pine(Pinus sylvestris var.mongolica Litv.)has recently exhibited growth decline and dieback on many sites,particularly pronounced in old-growth plantations.However,changes in response to drought stress by this species with age as well as the underlying mechanisms are poorly understood.In this study,tree-ring data and remotely sensed vegetation data were combined to investigate variations in growth at individual tree and stand scales for young(9-13 years)and aging(35-52 years)plantations of Mongolian pine in a water-limited area of northern China.A recent decline in tree-ring width in the older plantation also had lower values in satellited-derived normalized difference vegetation indices and normalized difference water indices relative to the younger plantations.In addition,all measured growth-related metrics were strongly correlated with the self-calibrating Palmer drought severity index during the growing season in the older plantation.Sensitivity of growth to drought of the older plantation might be attributed to more severe hydraulic limitations,as reflected by their lower sapwood-and leaf-specific hydraulic conductivities.Our study presents a comprehensive view on changes of growth with age by integrating multiple methods and provides an explanation from the perspective of plant hydraulics for growth decline with age.The results indicate that old-growth Mongolian pine plantations in water-limited environments may face increased growth declines under the context of climate warming and drying.

Tree mycorrhizal associations determine how biodiversity,large trees,and environmental factors drive aboveground carbon stock in temperate forests

Biodiversity,large trees,and environmental conditions such as climate and soil have important effects on forest carbon stocks.However,recent studies in temperate forests suggest that the relative importance of these factors depends on tree mycorrhizal associations,whereby large-tree effects may be driven by ectomycorrhizal(EM)trees,diversity effects may be driven by arbuscular mycorrhizal(AM)trees,and environment effects may depend on differential climate and soil preferences of AM and EM trees.To test this hypothesis,we used forest-inventory data consisting of over 80,000 trees from 631 temperate-forest plots(30 m×30 m)across Northeast China to examine how biodiversity(species diversity and ecological uniqueness),large trees(top 1%of tree diameters),and environmental factors(climate and soil nutrients)differently regulate aboveground carbon stocks of AM trees,EM trees,and AM and EM trees combined(i.e.total aboveground carbon stock).We found that large trees had a positive effect on both AM and EM tree carbon stocks.However,biodiversity and environmental factors had opposite effects on AM vs.EM tree carbon stocks.Specifically,the two components of biodiversity had positive effects on AM tree carbon stocks,but negative effects on EM tree carbon stocks.Environmental heterogeneity(mean annual temperature and soil nutrients)also exhibited contrasting effects on AM and EM tree carbon stocks.Consequently,for the total carbon stock,the positive large-tree effect far surpasses the diversity and environment effect.This is mainly because when integrating AM and EM tree carbon stock into total carbon stock,the opposite diversity-effect(also environment-effect)on AM vs.EM tree carbon stock counteracts each other while the consistent positive large-tree effect on AM and EM tree carbon stock is amplified.In summary,this study emphasized a mycorrhizal viewpoint to better understand the determinants of overarching aboveground carbon profile across regional forests.

N-fixing tree species promote the chemical stability of soil organic carbon in subtropical plantations through increasing the relative contribution of plant-derived lipids

Biodiversity experiments have shown that soil organic carbon(SOC)is not only a function of plant diversity,but is also closely related to the nitrogen(N)-fixing plants.However,the effect of N-fixing trees on SOC chemical stability is still little known,especially with the compounding effects of tree species diversity.An experimental field manipulation was established in subtropical plantations of southern China to explore the impacts of tree species richness(i.e.,one,two,four and six tree species)and with/without N-fixing trees on SOC chemical stability,as indicated by the ratio of easily oxidized organic carbon to SOC(EOC/SOC).Plant-derived C components in terms of hydrolysable plant lipids and lignin phenols were isolated from soils for evaluating their relative contributions to SOC chemical stability.The results showed that N-fixing tree species rather than tree species richness had a significant effect on EOC/SOC.Hydrolysable plant lipids and lignin phenols were negatively correlated with EOC/SOC,while hydrolysable plant lipids contributed more to EOC/SOC than lignin phenols,especially in the occurrence of N-fixing trees.The presence of N-fixing tree species led to an increase in soil N availability and a decrease in fungal abundance,promoting the selective retention of certain key components of hydrolysable plant lipids,thus enhancing SOC chemical stability.These findings underpin the crucial role of N-fixing trees in shaping SOC chemical stability,and therefore,preferential selection of N-fixing tree species in mixed plantations is an appropriate silvicultural strategy to improve SOC chemical stability in subtropical plantations.

Improved Data Stream Clustering Method: Incorporating KD-Tree for Typicality and Eccentricity-Based Approach

Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm.The original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior knowledge.While the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further data.This work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat Tree.Upon arrival,this ensures that new data points interact solely with clusters in very close proximity.This significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some extent.We apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA algorithm.The results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research.

基于自动终止准则改进的kd-tree粒子近邻搜索研究

对于大规模运动模拟问题而言,近邻点的搜索效率将对整体的运算效率产生显著影响。本文基于关联性分析建立kd-tree的最大深度dmax与粒子总数N的自适应关系式,提出了kd-tree自动终止准则,即ATC-kd-tree,同时还考虑了叶子节点大小阈值n_(0)对近邻搜索效率的影响。试验表明,ATC-kd-tree具有更高的近邻搜索效率,相较于不使用自动终止准则的kd-tree搜索效率最高提升46%,且适用性更强,可求解不同N值的近邻搜索问题,解决了粒子总数N发生改变时需要再次率定最大深度dmax的问题。同时,本文还提出了网格搜索法组合坐标下降法的两步参数优化算法GSCD法。通过2维阿米巴虫形状的参数优化试验发现,GSCD法可更为快速地率定ATC-kd-tree的可变参数,其优化效率比网格搜索法最高提升了205%,相较于改进网格搜索法最高提升了90%。研究结果表明,ATC-kd-tree和GSCD法不仅提高了近邻搜索的效率,也为复杂运动中近邻粒子搜索问题提供了一种更为高效的解决方案,能够显著降低计算资源的消耗,进一步提升模拟的精度和效率。

Tree species identity and interaction determine vertical forest structure in young planted forests measured by terrestrial laser scanning

Vertical forest structure is closely linked to multiple ecosystem characteristics,such as biodiversity,habitat,and productivity.Mixing tree species in planted forests has the potential to create diverse vertical forest structures due to the different physiological and morphological traits of the composing tree species.However,the relative importance of species richness,species identity and species interactions for the variation in vertical forest structure remains unclear,mainly because traditional forest inventories do not observe vertical stand structure in detail.Terrestrial laser scanning(TLS),however,allows to study vertical forest structure in an unprecedented way.Therefore,we used TLS single scan data from 126 plots across three experimental planted forests of a largescale tree diversity experiment in Belgium to study the drivers of vertical forest structure.These plots were 9–11years old young pure and mixed forests,characterized by four levels of tree species richness ranging from monocultures to four-species mixtures,across twenty composition levels.We generated vertical plant profiles from the TLS data and derived six stand structural variables.Linear mixed models were used to test the effect of species richness on structural variables.Employing a hierarchical diversity interaction modelling framework,we further assessed species identity effect and various species interaction effects on the six stand structural variables.Our results showed that species richness did not significantly influence most of the stand structure variables,except for canopy height and foliage height diversity.Species identity on the other hand exhibited a significant impact on vertical forest structure across all sites.Species interaction effects were observed to be site-dependent due to varying site conditions and species pools,and rapidly growing tree species tend to dominate these interactions.Overall,our results highlighted the importance of considering both species identity and interaction effects in choosing suitable species combinations for forest management practices aimed at enhancing vertical forest structure.

Tree allometry responses to competition and complementarity in mixed-species plantations of Betula alnoides

Tree allometry plays a crucial role in tree survival,stability,and timber quantity and quality of mixed-species plantations.However,the responses of tree allometry to resource utilisation within the framework of interspecific competition and complementarity remain poorly understood.Taking into consideration strong-and weakspace competition(SC and WC),as well as N_(2)-fixing and non-N_(2)-fixing tree species(FN and nFN),a mixedspecies planting trial was conducted for Betula alnoides,a pioneer tree species,which was separately mixed with Acacia melanoxylon(SC+FN),Erythrophleum fordii(WC+FN),Eucalyptus cloeziana(SC+nFN)and Pinus kesiya var.langbianensis(WC+nFN)in southern China.Six years after planting,tree growth,total nitrogen(N)and carbon(C)contents,and the natural abundances of^(15)N and^(13)C in the leaves were measured for each species,and the mycorrhizal colonisation rates of B.alnoides were investigated under each treatment.Allometric variations and their relationships with space competition and nutrient-related factors were analyzed.The results showed a consistent effect of space competition on the height-diameter relationship of B.alnoides in mixtures with FN or nFN.The tree height growth of B.alnoides was significantly promoted under high space competition,and growth in diameter at breast height(DBH),tree height and crown size were all expedited in mixtures with FN.The symbiotic relationship between ectomycorrhizal fungi and B.alnoides was significantly influenced by both space competition and N_(2) fixation by the accompanying tree species,whereas such significant effects were absent for arbuscular mycorrhizal fungi.Furthermore,high space competition significantly decreased the water use efficiency(WUE)of B.alnoides,and its N use efficiency(NUE)was much lower in the FN mixtures.Structural equation modeling further demonstrated that the stem allometry of B.alnoides was affected by its NUE and WUE via changes in its height growth,and crown allometry was influenced by the mycorrhizal symbiotic relationship.Our findings provide new insights into the mechanisms driving tree allometric responses to above-and belowground resource competition and complementarity in mixed-species plantations,which are instructive for the establishment of mixed-species plantations.

Insights from i-Tree Eco-efficiency Assessment Management of Urban Trees in Oxford,UK

In the era of stock development following the acceleration of urbanization,the revitalization of urban green space has assumed an increasingly significant role.Consequently,the management of urban trees has emerged as a critical focus of urban governance,contributing to the enhancement of livability in human settlements.This study offers a comprehensive analysis of the urban tree management system in Oxford,UK,identifying that its primary objective is to optimize and maintain a harmonious balance between human activities and the natural environment through the implementation of high-quality planting practices.The system emphasizes enhanced management practices and establishes a robust framework for the development of targeted policies and management regulations,utilizing i-Tree eco-efficiency assessment and real-time feedback mechanisms.China’s urban tree management is in its nascent stages,and there is an urgent need for the development of urban green space.By adopting the refined management assessment methodologies employed for urban trees in Oxford,UK,it is possible to enhance the ecological value of urban trees,which represent a significant green resource within cities,and contribute to the creation of more livable urban spaces.

基于FP-tree的新能源汽车产业国际竞争力影响因素关联挖掘算法

为充分挖掘新能源汽车产业国际竞争力影响因素、探究价值增长点,提出了基于FP-tree的影响因素关联挖掘算法。通过构建国际竞争力各指标影响因素的关联规则,分析任意事务数据集中的关联数据,利用最小支持度参数minsup按照从上到下的方式搜索,确定最长的频繁项目集,采用FP-tree关联频繁项目集,设定分支关联性挖掘标准,实现了新能源汽车产业国际竞争力影响因素的挖掘。测试结果表明,设计算法的最小支持度和数据关联挖掘时间较短,置信度分析具有较高的稳定性。

Rising utilization of stable isotopes in tree rings for climate change and forest ecology

Analyses of stable isotopes(C,O,H)in tree rings are increasingly important cross-disciplinary programs.The rapid development in this field documented in an increasing number of publications requires a comprehensive review.This study includes a bibliometric analysis-based review to better understand research trends in tree ring stable isotope research.Overall,1475 publications were selected from the Web of Science Core Collection for 1974-2023.The findings are that:(1)numbers of annual publications and citations increased since 1974.From 1974 to 1980,there were around two relevant publications per year.However,from 2020 to 2022,this rose sharply to 109 publications per year.Likewise,average article citations were less than four per year before 1990,but were around four per article per year after 2000;(2)the major subjects using tree ring stable isotopes include forestry,geosciences,and environmental sciences,contributing to 42.5%of the total during 1974-2023;(3)the top three most productive institutions are the Chinese Academy of Sciences(423),the Swiss Federal Institute for Forest,Snow and Landscape Research(227),and the University of Arizona(204).These achievements result from strong collaborations;(4)review papers,for example,(Dawson et al.,Annu Rev Ecol Syst 33:507-559,2002)and(McCarroll and Loader,Quat Sci Rev 23:771-801,2004),are among the most cited,with more than 1000 citations;(5)tree ring stable isotope studies mainly focus on climatology and ecology,with atmospheric CO_(2) one of the most popular topics.Since 2010,precipitation and drought have received increasing attention.Based on this analysis,the research stages,key findings,debated issues,limitations and direc-tions for future research are summarized.This study serves as an important attempt to understand the progress on the use of stable isotopes in tree rings,providing scientific guid-ance for young researchers in this field.

Comprehensive analyses of the proteome and ubiquitome revealed mechanism of high temperature accelerating petal abscission in tree peony

Tree peony(Paeonia suffruticosa Andrews)is a well-known ornamental plant with high economic value,but the short fluorescence is a key obstacle to its ornamental value and industry development.High temperature accelerates flower senescence and abscission,but the associated mechanisms are poorly understood.In this study,the tandem mass tag(TMT)proteome and label-free quantitative ubiquitome from tree peony cut flowers treated with 20℃for 0 h(RT0),20℃or 28℃for 60 h(RT60 or HT60)were examined based on morphological observation,respectively.Totally,6970 proteins and 1545 lysine ubiquitinated(Kub)sites in 844 proteins were identified.Hydrophilic residues(such as glutamate and aspartate)neighboring the Kub sites were in preference,and 36.01%of the Kub sites were located on the protein surface.The differentially expressed proteins(DEPs)and Kub-DEPs in HT60 vs RT60 were mainly enriched in ribosomal protein,protein biosynthesis,secondary metabolites biosynthesis,flavonoid metabolism,carbohydrate catabolism,and auxin biosynthesis and signaling revealed by GO and KEGG analysis,accompanying the increase of endogenous abscisic acid(ABA)accumulation and decrease of endogenous indoleacetic acid(IAA)level.Additionally,the expression patterns of six enzymes(SAMS,ACO,YUC,CHS,ANS and PFK)putatively with Kub modifications were analyzed by proteome and real-time quantitative RT-PCR.The cell-free degradation assays showed PsSAMS and PsACO proteins could be degraded via the 26 S proteasome system in tree peony flowers.Finally,a working model was proposed for the acceleration of flower senescence and abscission by high temperature.In summary,all results contributed to understanding the mechanism of flower senescence induced by high temperature and prolonging fluorescence in tree peony.

No effect of invasive tree species on aboveground biomass increments of oaks and pines in temperate forests

Prunus serotina and Robinia pseudoacacia are the most widespread invasive trees in Central Europe.In addition,according to climate models,decreased growth of many economically and ecologically important native trees will likely be observed in the future.We aimed to assess the impact of these two neophytes,which differ in the biomass range and nitrogen-fixing abilities observed in Central European conditions,on the relative aboveground biomass increments of native oaks Qucrcus robur and Q.petraea and Scots pine Pinus sylvestris.We aimed to increase our understanding of the relationship between facilitation and competition between woody alien species and overstory native trees.We established 72 circular plots(0.05 ha)in two different forest habitat types and stands varying in age in western Poland.We chose plots with different abundances of the studied neophytes to determine how effects scaled along the quantitative invasion gradient.Furthermore,we collected growth cores of the studied native species,and we calculated aboveground biomass increments at the tree and stand levels.Then,we used generalized linear mixed-effects models to assess the impact of invasive species abundances on relative aboveground biomass increments of native tree species.We did not find a biologically or statistically significant impact of invasive R.pseudoacacia or P.serotina on the relative aboveground,biomass increments of native oaks and pines along the quantitative gradient of invader biomass or on the proportion of total stand biomass accounted for by invaders.The neophytes did not act as native tree growth stimulators but also did not compete with them for resources,which would escalate the negative impact of climate change on pines and oaks.The neophytes should not significantly modify the carbon sequestration capacity of the native species.Our work combines elements of the per capita effect of invasion with research on mixed forest management.

Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method

Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.

Remaining Useful Life Prediction Method for Multi-Component System Considering Maintenance:Subsea Christmas Tree System as A Case Study

Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.

Identification of novel mammalian viruses in tree shrews(Tupaia belangeri chinensis)

The Chinese tree shrew(Tupaia belangeri chinensis),a member of the mammalian order Scandentia,exhibits considerable similarities with primates,including humans,in aspects of its nervous,immune,and metabolic systems.These similarities have established the tree shrew as a promising experimental model for biomedical research on cancer,infectious diseases,metabolic disorders,and mental health conditions.Herein,we used metatranscriptomic sequencing to analyze plasma,as well as oral and anal swab samples,from 105 healthy asymptomatic tree shrews to identify the presence of potential zoonotic viruses.In total,eight mammalian viruses with complete genomes were identified,belonging to six viral families,including Flaviviridae,Hepeviridae,Parvovirinae,Picornaviridae,Sedoreoviridae,and Spinareoviridae.Notably,the presence of rotavirus was recorded in tree shrews for the first time.Three viruses-hepacivirus 1,parvovirus,and picornavirus-exhibited low genetic similarity(<70%)with previously reported viruses at the whole-genome scale,indicating novelty.Conversely,three other viruses-hepacivirus 2,hepatovirus A and hepevirus-exhibited high similarity(>94%)to known viral strains.Phylogenetic analyses also revealed that the rotavirus and mammalian orthoreovirus identified in this study may be novel reassortants.These findings provide insights into the diverse viral spectrum present in captive Chinese tree shrews,highlighting the necessity for further research into their potential for crossspecies transmission.

基于LSM-Tree的分布式数据库异步融合机制研究与实现

信息技术的不断发展,使得分布式数据库成为研究热点。由于NoSQL架构的分布式数据库对SQL支持有限且在事务处理及一致性方面存在缺陷,基于LSM-Tree的NewSQL数据库逐渐成为应用的主流,例如TiDB、OceanBase等。分布式LSM-Tree的存储架构将数据分为基线数据与增量数据,通过合并操作将不同分区的增量数据与基线数据不断融合,并存储在磁盘,从而减少内存压力。但合并会占用大量系统资源,严重影响系统可用性。因此提出了一种基于LSM-Tree架构的异步融合机制,通过细分合并流程,将数据融合异步化,有效地缩短了单次数据合并的时间。实验表明,提出的异步融合机制可显著缩短数据合并时间,提高系统在高频写入场景下的鲁棒性和可用性。

基于深度哈希与VP-Tree的快速图像检索方法

针对高维特征图像检索中的精度和速度挑战,提出了一种结合深度哈希技术和VP-Tree索引的快速图像检索方法.该方法首先设计了一个轻量级的深度卷积编码网络,并在网络中引入了卷积块注意力模块和空间金字塔池化技术,以增强特征提取能力;然后通过该网络模型将图像数据集中每幅图像的高维特征转化为二进制哈希编码,并与其对应的图像编号组成一个哈希表;接着使用所有图像的哈希编码来构建一个VP-Tree,在执行图像检索时将使用待查询图像的哈希编码从VP-Tree中快速找到与其距离最近的节点;最后根据这些节点的哈希值从哈希表中取出对应的结果图像.实验结果表明,所提方法在保持高检索精度的同时显著提升了检索速度(在MNIST、FASHION-MNIST和CIFAR-10上的检索速度分别提高了24.17、8.61和4.01倍).