Aboveground biomass stocks of species-rich natural forests in southern China are influenced by stand structural attributes,species richness and precipitation

Forests,the largest terrestrial carbon sinks,play an important role in carbon sequestration and climate change mitigation.Although forest attributes and environmental factors have been shown to impact aboveground biomass,their influence on biomass stocks in species-rich forests in southern China,a biodiversity hotspot,has rarely been investigated.In this study,we characterized the effects of environmental factors,forest structure,and species diversity on aboveground biomass stocks of 30 plots(1 ha each) in natural forests located within seven nature reserves distributed across subtropical and marginal tropical zones in Guangxi,China.Our results indicate that forest aboveground biomass stocks in this region are lower than those in mature tropical and subtropical forests in other regions.Furthermore,we found that aboveground biomass was positively correlated with stand age,mean annual precipitation,elevation,structural attributes and species richness,although not with species evenness.When we compared stands with the same basal area,we found that aboveground biomass stock was higher in communities with a higher coefficient of variation of diameter at breast height.These findings highlight the importance of maintaining forest structural diversity and species richness to promote aboveground biomass accumulation and reveal the potential impacts of precipitation changes resulting from climate warming on the ecosystem services of subtropical and northern tropical forests in China.Notably,many natural forests in southern China are not fully stocked.Therefore,their continued growth will increase their carbon storage over time.

Correction of seismic attribute-based smallstructure prediction errors using GPR data-a case study of the Shuguang Coal Mine,Shanxi

Small structures in coal mine working face is one of the main hidden dangers of safe and effi cient production in coal mine.Currently,seismic exploration is often used as the main method for detecting such structures.However,limited by the accuracy of seismic data processing and interpretation,the interpreted location of small structures is often deviated.Ground-penetrating radar(GPR)can detect small structures accurately,but the exploration depth is shallow.The combination of the two methods can improve the exploration accuracy of small structures in coal mine.Aiming at the 1226#working face of Shuguang coal mine,we propose a method of seismic-attributes based small-structure prediction error correction using GPR data.First,we extract the coherence,curvature,and dip attributes from seismic data,that are sensitive to small structures,then by considering factors such as the eff ective detection range of GPR and detection environment,we select two structures from the prediction results of seismic attributes for GPR detection.Finally,based on the relationship between the positions of small structures predicted by the two methods,we use statistical methods to determine the overall off set distance and azimuth of the small structures in the entire study area and use the results as a standard for correcting each structure position.The results show that the GPR data can be used to correct the horizontal position errors of small structures predicted by seismic attribute analysis.The accuracy of the prediction results is greatly improved,with the error controlled within 5 m and reduced by more than 80%.Therefore,the feasibility of the method proposed in this study is verified.

Structural attributes,evolution and petroleum geological significances of the Tongnan negative structure in the central Sichuan Basin,SW China

The Tongnan secondary negative structure in central Sichuan Basin has controls and influences on the structural framework and petroleum geological conditions in the Gaoshiti-Moxi area.To clarify the controls and influences,the deformation characteristics,structural attributes and evolution process of the Tongnan negative structure were investigated through a series of qualitative and quantitative methods such as balanced profile restoration,area-depth-strain(ADS)analysis,and structural geometric forward numerical simulation,after comprehensive structural interpretation of high-precision 3D seismic data.The results are obtained in three aspects.First,above and below the P/AnP(Permian/pre-Permian)unconformity,the Tongnan negative structure demonstrates vertical differential structural deformation.It experiences two stages of structural stacking and reworking:extensional depression(from the Sinian Dengying Formation to the Permian),and compressional syncline deformation(after the Jurassic).The multi-phase trishear deformation of the preexisting deep normal faults dominated the extensional depression.The primary depression episodes occurred in the periods from the end of Late Proterozoic to the deposition of the 1st–2nd members of the Dengying Formation,and from the deposition of Lower Cambrian Longwangmiao Formation–Middle–Upper Cambrian until the Ordovician.Second,the multi-stage evolution process of the Tongnan negative structure controlled the oil and gas migration and adjustment and present-day differential gas and water distribution between the Tongnan negative structure and the Gaoshiti and Moxi-Longnüsi structural highs.Third,the Ordovician,which is limitedly distributed in the Tongnan negative structure and is truncated by the P/AnP unconformity on the top,has basic geological conditions for the formation of weathering karst carbonate reservoirs.It is a new petroleum target deserving attention.

Spatial distribution pattern of Picea schrenkiana population in the Middle Tianshan Mountains and the relationship with topographic attributes

The spatial distribution of plant populations is an important feature of population structure and it de- termines the population＇s ecological preferences, biological characteristics and relationships with environmental factors. The point pattern analysis method was adopted to study the distribution pattern of Picea schrenkiana indi- viduals of different size classes and the correlations between two size classes as well as the impact of topog- raphical attributes on the population distribution. With increasing diameter at breast height, the plant density of the P. schrenkiana population showed a declining trend. Old trees showed a random distribution at a small spatial scale （0-12 m）, whereas saplings, small trees and big trees all had an aggregated distribution at all scales. With the increase of tree age, the scales at which maximal aggregation occurred gradually increased and the aggregation strength decreased. At a small scale （0-16 m）, all size classes showed a negative correlation and the larger the difference between tree size, the more significant the negative correlation. The number of medium, big and old trees had a significantly positive correlation with elevations, whereas the number of saplings and small trees was not significantly correlated with elevations. The numbers of saplings, small and medium trees showed a significant positive correlation with slope gradient, whereas the number of big trees was not significantly correlated, and the number of old trees was negatively correlated with gradient. With the exception of old trees, saplings, small, me- dium and big trees showed negative correlations with convexity index. The study provides a theoretical basis for the conservation, rehabilitation and sustainable management of forest ecosystems in the Tianshan Mountains.

Choosing meaningful structure data for improving web search

In order to improve the quality of web search,a new query expansion method by choosing meaningful structure data from a domain database is proposed.It categories attributes into three different classes,named as concept attribute,context attribute and meaningless attribute,according to their semantic features which are document frequency features and distinguishing capability features.It also defines the semantic relevance between two attributes when they have correlations in the database.Then it proposes trie-bitmap structure and pair pointer tables to implement efficient algorithms for discovering attribute semantic feature and detecting their semantic relevances.By using semantic attributes and their semantic relevances,expansion words can be generated and embedded into a vector space model with interpolation parameters.The experiments use an IMDB movie database and real texts collections to evaluate the proposed method by comparing its performance with a classical vector space model.The results show that the proposed method can improve text search efficiently and also improve both semantic features and semantic relevances with good separation capabilities.

Study of formation boundary and dip attribute extraction based on edge detection technology

In the seismic profile interpretation process,as the seismic data are big and the small geological features are difficult to identify,improvement of the efficiency is needed. In this study,structure tensor method in computer image edge detection processing is applied into the 2D seismic profile. Coherent attribute is used to extract formation edge. At the same time,extracting the eigenvalues and eigenvectors to calculate the seismic geometric properties which include dip and apparent dip,automatic identification is achieved. Testing the Gaussian kernel function with synthetic models and comparing the coherent attribute and dip attribute extraction results before and after,the conclusion that Gaussian filter can remove the random noise is obtained.

Structure complexity is the primary driver of functional diversity in the temperate forests of northeastern China

Background:Assessing functional diversity to identify its spatial patterns and drivers is an important step towards understanding the adaptive capacity of ecosystems to environmental change. However, until now, these mechanisms were poorly understood in the temperate forests of northeastern China, which prevented the development of new management methods aimed at increasing functional trait diversity and thus ecological resilience.Methods:In this study, we mapped functional diversity distributions using a Kriging Interpolation Method. A specific random forest model approach was adopted to test the importance ranking of 18 variables in explaining the spatial variation of functional diversity. Three piecewise structural equation models (pSEMs) with forest types as random effects were constructed for testing the direct effects of climate, and the indirect effects of stand structure on functional diversity across the large study region. Specific causal relationships in each forest type were also examined using 15 linear structural equation models.Results:Although environmental filtering by climate is important, stand structure explains most of the functional variation of the forest ecosystems in northeastern China. Our study thus only partially supports the stressdominance hypothesis. Several abundant species determine most of the functional diversity, which supports the mass ratio hypothesis.Conclusions:Our results suggest that forest management aimed at increasing structural complexity can contribute to increased functional diversity, especially regarding the mixing of coniferous and broad-leaved tree species.

Moderate Interpretation with Attribute Analysis and 3d Visualization for Deeper Prospects of Balkassar Field, Central Potwar, Upper Indus Basin, Pakistan

Balkassar is an old field with considerable remaining potential. The 2d, 3d seismic and earlier vintages show that Balkassar is composed of two folds that impart heart shaped geometry. It appears likely the early Eocene age Bhadrar formation may provide commercial production with lower water cuts from the eastern lobe (yet untapped) of the structure that may have at least 30 million barrels of unrecovered oil. Horizontal drilling may have promise as an optimum technique for recovery of oil from Paleogene reservoirs. Encouraging oil indications have also been recorded from the early Permian age tobra formation from Balkassar oxy-1 that was not tested by Oxy. Tobra sandstone reservoir can have a matrix porosity approaching 8%. When fractured recoveries from it can be relatively better than the Paleogene reservoirs. The 2D and 3D seismic acquisition has confirmed that the eastern lobe (yet untapped) of the Balkassar field is structurally higher and steeper than the Western lobe which has thus far produced over 30 million barrels. The Eastern lobe thus offers good potential for recovery of oil from the Bhadrar reservoir. The entire field is likely to have potential for recovery of oil from the early Eocene aged Tobra formation. 2-d and 3-D Seismic data interpretation, attribute analysis and visualization for deeper prospect carried in Balksasar field. Tobra and Khewra formation studied for deeper potential drilling. Time contour and depth contour map shows potential for deeper prospects. Also attribute analysis and 3d visualization show good results for deeper potential of Tobra and Khewar formations. Seismic amplitude, Reflection strength, Apparent polarity attribute are visualized and interpreted to find the potential for Tobra and Khewra formation. 3-D visualization also showed positive results for Tobra and Khewra formations.

How Users Perceive Infrastructure Development Affects Their Transport Mode Choice

Transport infrastructure development and perception vary across and within countries, influencing mode choice among road users. This study explores how road users perceive the development of infrastructure modes, service attributes, embedded safety levels, and commuting modes. Additionally, the research examines whether participants’ environmental backgrounds impact their mode choice patterns. The study gathered responses from 1169 participants residing in two regions of Amman, Jordan, each with distinct infrastructure development and population densities. Participants completed a standardized questionnaire, and several statistical techniques were employed for analysis. The findings revealed that facilities’ infrastructure attributes, development, and safety were assessed using three indices. Both participant groups perceived these indices differently on average. Residents of low population density areas with relatively developed infrastructure showed more consistent assessments, irrespective of their most frequently used mode of transportation, tending towards lower scores. Interestingly, subjective ratings of infrastructure development were higher (4.96) than attribute-based ratings (4.32). Despite their generally low-quality perception, public transportation services received the highest appraisal (4.9). Conversely, pedestrian infrastructure complementing public transport received the lowest assessment (4.57), only slightly higher than street environments (4.59). The study found weak associations between subjective service characteristics ratings. Traveler and trip characteristics influenced mode choice and trips more than infrastructure perception. In conclusion, the study suggests that policies should be developed to encourage green transportation, ensure social equality and safety. In addition, the study contributes to understanding perceptions about transport infrastructure, modes of transportation, and the factors that influence sustainable and equitable transportation systems.

数据知识产权登记:商业秘密模式抑或数据库模式

数据知识产权登记试点实践的背后隐含着商业秘密模式和数据库模式的理论分歧。数据的商业秘密保护存在影响数据访问、阻碍数据流通利用的负面效应,不值得在制度上予以强化激励。与其通过商业秘密模式寻求数据与知识产权的关联,不如转向数据库模式。我国数据知识产权登记实践中普遍存在“数据结构”要求,与欧盟的数据库概念具有相通之处。“数据结构”可以体现数据集合的智力成果属性。在大数据时代,数据知识产权保护具有超越传统的数据库保护的内涵。相比欧盟“限缩保护范围—权能宽泛模糊”的数据库特殊权利范式,我国可以选择“扩张保护范围—限缩权利内容”的对应范式,从而适应数字时代数据财产保护的新需求,打造数据库保护的中国升级版。

认知诊断评估中Q矩阵理论及应用

Q矩阵是认知心理学与心理计量学结合的重要载体,Q矩阵在认知诊断中发挥着十分重要的作用。Q矩阵理论和应用研究近年来取得了重要进展。众多研究者从结构化到非结构化、属性二值到多值、简单到复杂模型、独立到一般结构、0-1到多级评分方面不断深入和拓展Q矩阵理论。Q矩阵理论也广泛应用于测验构念效度评价、计算机化自适应测验选题策略设计、Q矩阵学习和标定、认知诊断测验组卷等。与模型无关的Q矩阵理论和适合特定认知诊断模型下Q矩阵理论,以及最新Q矩阵理论的应用都值得深入研究。

知识状态集合准确界定的意义

教育认知诊断基于被试的作答反应估计其知识状态从而进行分类.尽管给定属性及其层级关系,其知识状态集合是唯一的,但对此并未形成共识.如有的软件包认为同一属性层级关系可对应2种不同的知识状态集合;有的研究仅仅给出属性及其层级关系的知识状态集合的真子集.针对这些情况,该文从理论上和应用上进行了分析,并给出修正的建议.

基于属性的概念化:制度本体研究的必要性与路径

制度本体的研究现状与制度之于人类生活的重要性并不相称,制度研究有必要返回本体,明确存在。解读制度理论的制度理解并指出它所引发的本体认知困惑,确立了制度本体研究的必要性。本体在于内涵,内涵首要是本质,有抱负的研究者都试图给出事物的本质性定义,但此定义往往可欲难求。一个可行的操作化步骤是,确定本体的属性。制度学界普遍接受的“制度即结构”可以明确为“制度即要素结构”,并可解构为要素之制、载体之制与结构之制。确定本体属性、要素化属性并将其概念化,应是可行的本体研究策略或路径。由此获得的概念语言暨制度本体词汇有助于校准本体描述,同时可作为中介术语沟通制度研究,推动制度知识的共享与交流。

历史主义视角下情报学的学科起源、结构与属性

文章从历史主义视角出发,基于文献述评分析了情报学的学科起源、学科边界、焦点研究问题与核心组成部分,将情报学(Information Science)定义为“在不断发展的技术环境中研究信息的管理、分析、处理、增长、关联、传播,以及个人、组织进行信息获取、共享、开发、利用以满足个性化需求的学科”,其核心组成部分包括图书馆信息学、信息计量学、信息学与社会信息学、情报研究与情报工程;分析了情报学的三大学科起源:欧洲的文献信息学派、苏联的科学交流学派、美国的信息科学学派;提出情报学是一门受信息技术驱动并广泛服务于经济社会发展的交叉学科、基础学科和应用学科,其核心目标是“解决人类信息处理能力的局限与信息无限增长之间的矛盾”,并提出相比于“信息资源管理”,信息科学是更加合适的一级学科名称。

大庆SN油田东部过渡带油水边界综合确定

为确定大庆SN油田东部过渡带油水界面,综合钻井、测井、地震资料,结合岩心含油产状分析和老井油水层二次解释,基于双相介质理论的叠后属性油气检测以及基于叠前地震波形指示反演的流体识别等技术,探讨构造油气藏外扩区油水边界的综合确定方法。研究区油水边界具有以下特征:岩心含油产状为油斑以上;测井解释外推为油层或油水同层;叠后属性低高频能量比大于0.85;叠前反演预测含水饱和度小于75%。因此,以“井点定深度、地震定边界、动态来验证”为原则,从“点—线—面—空”,经过综合分析,确定最终油水边界位置。研究成果有效指导了研究区外扩评价部署,对同类型构造油田油水边界研究具有参考意义。

属性偏序形式结构的数学形式化

属性偏序形式结构,作为一种基于人类认知原理和粒计算思想的知识发现和知识表示新理论,目前已有广泛的应用,但其理论基础缺乏抽象化数学化,这势必影响该理论的系统发展。针对上述问题,研究了属性偏序形式结构的数学形式化描述问题。首先,基于粒计算的思想提出了知识表示的形式化框架。在此基础上,通过定义对象集合的覆盖和最简覆盖,给出属性偏序形式结构的粒和粒群的概念,进而通过对粒衍生出粒群的充要条件的讨论,给出了属性偏序形式结构中的知识结构,从而完成属性偏序形式结构的数学形式化描述。最后,通过具体实例展示了利用数学形式化描述构造属性偏序形式结构的过程,并揭示了该过程所体现的人类认知规律。

一种基于属性相似性和分布结构连通性的聚类算法

聚类分析针对不同的数据特点采用不同的相似性度量,现实世界中数据分布复杂,存在分布无规律、密度不均匀等现象,单独考虑实例属性相似性或分布结构连通性会影响聚类效果。为此,提出了一种基于属性相似性和分布结构连通性的聚类算法(A Clustering Algorithm Based on Attribute Similarity and Distributed Structure Connectivity, ASDSC)。首先,利用待聚类数据集中的所有数据实例构建完全无向图,定义了一种兼顾属性相似和分布结构连通的新颖相似性度量方式,用于计算节点相似性,并构造邻接矩阵更新边的权重;其次,借助邻接矩阵执行递增步长的随机游走,依据顶点的连通中心性来识别簇中心并给定簇编号,同时获取其他顶点的连通性;然后,利用连通性计算顶点间的依赖关系,并据此进行簇编号的传播,直至完成聚类。最后,为了验证该方法的聚类性能,在16个合成数据集和10个真实数据集上与5种先进聚类算法进行了对比实验,ASDSC算法取得了优异性能。

基于属性偏序原理的老年2型糖尿病患者脉象特征研究

目的将300例老年2型糖尿病患者作为研究对象,探讨老年2型糖尿病的核心病机,并为临床治疗提供依据。方法利用舌面脉信息采集体质辨识系统采集患者脉象,运用燕山大学的数据挖掘技术,构建属性偏序结构图进行分析和研究。结果300例老年2型糖尿病患者脉象以虚脉、弦脉、结脉为主,且三者常相兼出现,构成脉虚弦、脉结虚、脉结弦等复合脉象。结论老年2型糖尿病患者脉象以虚脉、弦脉、结脉为主,符合肝肾不足、多虚多瘀的病理特点,临床治疗中应兼顾肝肾,并根据脉象弦结的不同程度辅以活血化瘀之品。

融合网络结构与节点属性的关系预测深度学习方法研究

关系预测是网络科学领域的一个重要研究问题。传统基于相似性的启发式方法难以完成大规模或稀疏网络的关系预测任务,虽然近来兴起的基于深度学习的方法可以解决这一问题,但大多数工作主要通过网络结构信息嵌入表示向量的相似性实现关系预测。许多实证研究表明网络关系的形成会受到节点属性的影响,同时相似性也不是关系形成的唯一准则。本文提出了融合网络结构与节点属性进行关系预测的DDLP模型。该模型借助早期融合的方式获取网络结构信息和节点属性信息的嵌入表示,进而通过节点特征向量与连边信息的有监督学习实现关系预测。现实网络中的实验结果表明,DDLP模型可以有效捕捉网络中的连边规律,特别是融合节点属性后,其预测性能(精确率、召回率和F 1值)明显优于比对模型。本研究不仅为关系预测的相关工作提出了一个深度学习模型框架,也为诸如系统推荐的现实应用奠定方法基础。

What diameter?What height?Influence of measures of average tree size on area-based allometric volume relationships

Volume is an important attribute used in many forest management decisions.Data from 83 fixed-area plots located in central New Brunswick,Canada,are used to examine how different measures of stand-level diameter and height influence volume prediction using a stand-level variant of Honer's(1967)volume equation.When density was included in the models(Volume=f(Diameter,Height,Density))choice of diameter measure was more important than choice of height measure.When density was not included(Volume=f(Diameter,Height)),the opposite was true.For models with density included,moment-based estimators of stand diameter and height performed better than all other measures.For models without density,largest tree estimators of stand diameter and height performed better than other measures.The overall best equation used quadratic mean diameter,Lorey's height,and density(root mean square error=5.26 m^3·ha^(-1);1.9%relative error).The best equation without density used mean diameter of the largest trees needed to calculate a stand density index of 400 and the mean height of the tallest 400 trees per ha(root mean square error=32.08 m^(3)·ha^(-1);11.8%relative error).The results of this study have some important implications for height subsampling and LiDAR-derived forest inventory analyses.