Strategies on Sample Size Determination and Qualitative and Quantitative Traits Integration to Construct Core Collection of Rice (Oryza sativa)

The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions （6.6%） could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits （QT1）, quantitative traits （QT2） and integrated qualitative and quantitative traits （QTT）, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections （225, 200, 175, 150, 125, 100, 75 and 50）. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.

Simulation of sludge－dredging effects in controlling nutrient release of LakeKasumigaura with large－size core samples

Nutrient release from the dredged and undredged sediments in Lake Kasumigaura were simulated under the laboratory control conditions with large-size core samples. It was found that phosphate and ammonia release fluxes are less in aerobic than those in anaerobic. In different simulated dredged depth, the phosphate release showed large divergence in the anaerobic than in the aerobic. There was a larger accumulated release of phosphate and ammonia at actual dredged (St. B) than the undredged (St. A) in anaerobic condition. This showed that the sludge-dredging was effective of controlling phosphorus and nitrogen release. A preliminary assessment is drawn from the experiments that the sludge-dredging work in Tsuchiura Bay of Lake Kasumigaura can reduce about 15. 9% of phospbate and 56. 2% of anunonia release from the sediments respectively.

Sample Size Determination and Statistical Hypothesis Testing for Core Centration in Press Coated Tablets

A novel statistical approach to evaluate the manufacturing quality of press coated tablets in terms of the centering of their core is presented. We also provide a formula to determine the necessary sample size. This approach is applied to real data.

Frequency and Characteristics of Dust Sediments in Core Samples from Hashylan Wetland, Kermanshah, Iran

Dust phenomenon is one of the biggest environmental problems in arid and semiarid regions. In these areas, lakes and wetlands are natural dust traps and core sampling method can be an appropriate way to assess the phenomenon of the dust. Therefore, the purpose of this study is the study of frequency and characteristics of dust sediments in core samples from Hashilan wetlands, Kermanshah. Four intact core samples were taken from different parts of the Hashilan wetland in Kermanshah. Physical, chemical and micromorphological analysis were done. Also clay mineralogy was performed using X-ray analysis (XRD) and shape of particles was photographed by scanning electron microscope (SEM). Considering that four samples had been taken from different parts of the wetland, the quantitative differences in dust amount are likely due to the location of the samples. The results of XRD and thin sections show that the dominant mineralogical composition of dust particles was clay minerals, quartz and calcite. SEM results for core sample 1 revealed that most particles had the size between 2 to 50 mm which ranged from fine silt to coarse silt. Considering the similarities between SEM images for core sample 1 and those from Kermanshah dust measurement station, it could be said that fine rounded particles detected at top 30 cm of core samples had Aeolian origin. These findings were in accordance with the results from dust measurement and weather station of Kermanshah about increased dust activities in the study area over past 10 years.

Engineering behaviour of in situ cored deep cement mixed marine deposits subjected to undrained and drained shearing

The deep cement mixing(DCM)is used to improve the capacity and reduce the settlement of the soft ground by forming cemented clay columns.The investigation on the mechanical behaviour of the DCM samples is limited to either laboratory-prepared samples or in-situ samples under unconfined compression.In this study,a series of drained and undrained triaxial shearing tests was performed on the in-situ cored DCM samples with high cement content to assess their mechanical behaviours.It is found that the drainage condition affects significantly the stiffness,peak and residual strengths of the DCM samples,which is mainly due to the state of excess pore water pressure at different strain levels,i.e.being positive before the peak deviatoric stress and negative after the peak deviatoric stress,in the undrained tests.The slope of the failure envelope changes obviously with the confining pressures,being steeper at lower stress levels and flatter at higher stress levels.The strength parameters,effective cohesion and friction angle obtained from lower stress levels(c′0 andφ′0)are 400 kPa and 58°,respectively,which are deemed to be true for design in most DCM applications where the in-situ stress levels are normally at lower values of 50-200 kPa.Additionally,the computed tomography(CT)scanning system was adopted to visualize the internal structures of DCM samples.It is found that the clay pockets existing inside the DCM samples due to uneven mixing affect markedly their stress-strain behaviour,which is one of the main reasons for the high variability of the DCM samples.

Infiltration characteristics of non-aqueous phase liquids in undisturbed loessal soil cores

The widespread contamination of soils and aquifers by non-aqueous phase liquids （NAPL）, such as crude oil, poses serious environmental and health hazards globally. Understanding the infiltration characteristics of NAPL in soil is crucial in mitigating or remediating soil contamination. The infiltration characteristics of crude and diesel oils into undisturbed loessal soil cores, collected in polymethyl methacrylate cylindrical columns, were investigated under a constant fluid head （3 era） of either crude oil or diesel oil. The infiltration rate of both crude and diesel oils decreased exponentially as wetting depth increased with time. Soil core size and bulk density both had significant effects on NAPL infiltration through the undisturbed soil cores; a smaller core size or a greater bulk density could reduce oil penetration to depth. Compacting soil in areas susceptible to oil spills may be an effective stratage to reduce contamination. The infiltration of NAPL into soil cores was spatially anisotropic and heterogeneous, thus recording the data at four points on the soil core is a good stratage to improve the accuracy of experimental results. Our results revealed that crude and diesel oils, rather than their components, have a practical value for remediation of contaminated loessal soils.

Method of Constructing Core Collection for Malus sieversii in Xinjiang,China Using Molecular Markers

The method for constructing core collection ofMalus sieversii based on molecular marker data was proposed. According to 128 SSR allele of 109 M. sieversii, an allele preferred sampling strategy was used to construct M. sieversii core collection, using the UPGMA （unweighted pair-group average method） cluster method according to Nei ＆ Li, SM, and Jaccard genetic distances, by stepwise clustering, and compared with the random sampling strategy. The number of lost allele and t-test of Nei＇s gene diversity and Shannon＇s information index were used to evaluate the representative core collections. The results showed that compared with the random sampling strategy, allele preferred sampling strategy could construct more representative core collections. SM, difference for construction of M. sieversii core collection. Jaccard, and Nei ＆ Li genetic distances had no significant SRAP （sequence-related amplified polymorphism） data and morphological data showed that allele preferred sampling strategy was a good sampling strategy for constructing core collection of M. sieversii. Allele preferred sampling strategy combined with SM, Jaccard, and Nei ＆ Li genetic distances using stepwise clustering was the suitable method for constructing M. sieversii core collection.

Assessment of different genetic distances in constructing cotton core subset by genotypic values

One hundred and sixty-eight genotypes of cotton from the same growing region were used as a germplasm group to study the validity of different genetic distances in constructing cotton core subset. Mixed linear model approach was employed to unbiasedly predict genotypic values of 20 traits for eliminating the environmental effect. Six commonly used genetic distances(Euclidean,standardized Euclidean,Mahalanobis,city block,cosine and correlation distances) combining four commonly used hierarchical cluster methods(single distance,complete distance,unweighted pair-group average and Ward's methods) were used in the least distance stepwise sampling(LDSS) method for constructing different core subsets. The analyses of variance(ANOVA) of different evaluating parameters showed that the validities of cosine and correlation distances were inferior to those of Euclidean,standardized Euclidean,Mahalanobis and city block distances. Standardized Euclidean distance was slightly more effective than Euclidean,Mahalanobis and city block distances. The principal analysis validated standardized Euclidean distance in the course of constructing practical core subsets. The covariance matrix of accessions might be ill-conditioned when Mahalanobis distance was used to calculate genetic distance at low sampling percentages,which led to bias in small-sized core subset construction. The standardized Euclidean distance is recommended in core subset construction with LDSS method.

高温小井眼大直径岩心旋转井壁取心仪研制及应用

随着油气勘探开发难度增大,特别是海洋油气勘探开发的不断加大,以及深水井、高温井越来越多,地质方面对电缆测井技术所获取的参数要求也越来越高。为了更好地获取小井眼尺寸井壁岩心样本,助力油气田高效探勘开发,通过对取心仪井下仪器关键零部件电子控制短节和机械液压短节的创新设计与模拟分析,研制了适用于高温、高压、小尺寸井眼的大直径旋转井壁取心仪(MRCT-dumpy)。通过功能测试和5口井作业应用表明,大直径旋转井壁取心仪钻头性能及取心电机性能均得到充分验证,其热管理系统满足作业需要,符合设计要求;该取心仪取心功能正常,最高单趟收获岩心43颗,满足小井眼大直径取心作业要求。该仪器的设计与应用可为后期同类技术的发展提供指导。

基于空间插值的不规则海洋地质样品测试分析数据聚类算法研究

海洋地质调查中获取大量海洋沉积物柱状样样品测试分析数据,样品测试分析目的不同导致柱状样数据采样深度不同,由此造成地质取样数据在三维空间上呈现不规则散点状分布。传统聚类算法无法在三维空间上对此类不规则散点数据进行聚类分析。对此,文章设计了一种基于空间插值的不规则地质样品测试分析数据聚类算法,有效地将三维样品测试分析散点数据降为二维数据后进行聚类分析,本算法较好地解决了地质体中试验测试数据的不均衡性问题,为海洋地质大数据分析提供了基础技术方法。

基于机器学习的水泥基灌浆料强度预测方法

针对采用小直径芯样法准确预测水泥基灌浆料抗压强度的问题,使用压力试验机分别对水泥基灌浆料标准尺寸试块和小直径芯样进行抗压强度试验,并基于试验数据,采用支持向量机回归(SVR)和随机森林回归(RFR)对水泥基灌浆料抗压强度进行回归预测。结果表明:标准尺寸试块均呈正反相接的四角锥体破坏形态,而高径比为0.7和1.0的小直径芯样呈正反相接的圆锥体破坏形态,高径比为1.2的小直径芯样呈斜裂缝剪切破坏形态;标准尺寸试块和小直径芯样的抗压强度值均服从正态分布,且无离群值;随着龄期的增长,标准尺寸试块和小直径芯样的抗压强度提高,且具有早期强度较高的特性;直径46 mm芯样的抗压强度较小,且更易受加工精度的影响;在给定的龄期和直径下,高径比为0.7的芯样抗压强度值最大,抗压强度离散程度最小;RFR预测模型对水泥基灌浆料抗压强度的预测效果更优。所提方法可较准确预测水泥基灌浆料抗压强度,为水泥基灌浆料抗压强度的预测研究提供了参考。

基于表型性状构建禾初级核心种质

“禾”是适应贵州黔东南山区峡谷森林中遮荫、泥沼、寒冷、积水等特殊自然生境生长的地方水稻品种。以402份禾种质资源为材料,依据禾颖尖颜色差异将原始种质划分为5组,基于26个表型性状,采用逐步聚类法以6种总体取样规模、4种组内取样比例和2种组内取样方法筛选最佳取样策略,构建禾初级核心种质,并对其进行综合评价。结果表明,10%为最适总体取样规模,组内取样比例法以对数比例法最优,聚类取样法是组内最佳取样方法。在最佳取样策略下,共获得47份禾初级核心种质,占比11.69%,表型保留比例为95.77%。核心种质评价结果表明,构建的核心种质作为原始种质的浓缩能够代表禾原始种质的遗传多样性。

焦虑情绪何时会激发创业努力?一个跨层次双重调节模型

创业者必须投入极大强度的努力,才能带领初创企业度过三年艰难的酝酿期。部分研究指出,情绪是激发创业者持续投入努力的近端驱动力。焦虑作为创业活动中显著存在的日常情绪,关于其在何种情况下能够激发创业努力的研究却略显不足。本文基于社会认知理论,引入核心自我评价和创业身份中心性作为调节变量,探究日常焦虑情绪对创业努力的促进作用。借助体验抽样法,收集了嵌入在44位创业者中的684份有效问卷。跨层回归结果表明,当创业者核心自我评价高时,焦虑情绪积极促进创业努力;当创业者创业身份中心性高时,焦虑情绪积极促进创业努力;当创业者的核心自我评价和创业身份中心性均高时,焦虑情绪最大程度激发创业努力。隔日配对数据结果表明,在核心自我评价和创业认同中心性水平均高的情况下,当日焦虑情绪体验的激励作用可以持续到次日。研究结论不仅丰富了创业情境下焦虑情绪研究,揭开了焦虑与创业努力复杂关系;而且回应了关于情绪能否直接导致行为观点的质疑,丰富了创业努力情感观研究。

化子坪长6储层长岩心CO_(2)驱替实验及数值模拟评价

二氧化碳驱提高石油采收率(CO_(2)-EOR)在我国大部分低渗透、低孔隙度油藏中的应用越来越重要。鉴于国家净零排放目标,在采用二氧化碳驱提高采收率时,二氧化碳封存是另一个重要考虑因素。针对低渗油藏,开展天然岩心长岩心CO_(2)驱替试验,并利用TOGA(TOUGH Oil,Gas,Aqueous)软件建立岩心尺度数值模型开展模型的识别与验证,对模型的有效性及物性参数进行敏感性分析,结果表明,1)根据出口气油比可将二氧化碳驱油与封存划分为未见气(0~100)、极少量气(100~1 000)、气体突破(1 000~10 000)、大量气窜(>10000)四个不同阶段;2)孔隙度、渗透率及非均质性对模拟结果影响较大,在后续实际场地模型中应予以重点关注。研究结果可为实际场地规模模型提供参数依据。

基于表型性状分析构建冀北地区马铃薯核心种质

为合理利用和更好保存马铃薯种质资源,本研究以冀北地区保存的502份马铃薯种质资源为材料,调查了26个表型性状,以不同块茎肉色进行分组,设置简单比例、对数比例、平方根比例和多样性比例4种取样方法,5%、10%、15%、20%、25%和30%共6种取样比例,利用2种遗传距离(欧氏距离和马氏距离)和4种聚类方法(类平均法、最长距离法、最短距离法、离差平方和法),探讨最佳取样策略,抽选核心种质。利用遗传多样性特征值、t检验、评价参数和系统聚类等方法对核心种质的表型性状进行评价,以及利用主成分分析对核心种质进行确认。结果表明,平方根比例法能够使核心种质更具代表性,20%为最佳取样比例,欧氏距离优于马氏距离,最优聚类方法为最短距离法,最终抽提出100份马铃薯核心种质,占全部种质的19.92%;核心种质的评价和主成份分析结果表明100份核心种质消除了大部分遗传冗余,保留了所有样本的遗传多样性,具有良好的代表性。本研究为马铃薯种质资源的有效利用和种质创新提供了重要的理论依据和实践基础。

关于加强我国实物地质资料统筹保管工作的思考

实物地质资料是地质勘探工作形成的宝贵资源,确保重要实物地质资料安全妥善保管是实现其潜在价值有效保存和高效利用的重要保障,而如何改进日益增长的重要岩芯保管需求和有限的库房建设之间的矛盾,是当前我国实物地质资料保管工作面临的重要问题。笔者等系统总结了近年来我国实物地质资料保管工作在制度建设、库房建设等方面取得的重要成果,分析了当前面临的主要问题,研究并提出了我国实物地质资料统筹保管工作的总体布局、机制建立等方面的建议,为提升我国实物地质资料统筹保管能力提供参考。

基于表型性状的酸枣核心种质构建

为更好地保存和研究酸枣种质,提高利用效率,以211份酸枣种质为试材,基于表型性状数据,在25%取样比例下,对所有种质进行逐步系统聚类,从遗传距离方法、取样方法、聚类方法和取样比例4个方面探讨酸枣核心种质的最佳取样策略。根据最佳取样策略和3种分组取样方法进行分组取样,并与不分组取样进行比较。结果表明:基于25%取样比例,采用优先取样法、欧氏距离法和可变类平均法构建核心种质效果最佳;在最佳构建策略下筛选总体取样比例,结果表明最佳总体取样比例为25%;不分组取样构建的核心种质Pcore的方差差异百分率(VD)、变异系数变化率(VR)和极差符合率(CR)高于分组取样构建的核心种质Core-L,构建效果更好;定性描述性状保留比例、t检验、符合率检验、主成分分析和样品三维分布图表明构建的核心种质能够消除遗传冗余,能够代表原始种质。基于表型性状筛选出的最佳构建策略为“欧氏距离+可变类平均法+优先取样法+25%取样比例”,经过补充完善,最终得到58份核心种质,具有较高的代表性。本研究成功构建了能够代表原始酸枣种质表型遗传多样性的核心种质,有助于科学、有效地收集和保存酸枣种质资源,为深入挖掘和利用酸枣种质资源提供了科学依据,同时也为选育酸枣良种奠定基础。

基于ICEEMDAN多尺度熵与NGO-HKELM的转子故障诊断

针对电机转子故障信号非平稳、敏感的故障特征不能有效提取,传统分类器参数智能优化算法存在优化速度慢、调整参数多、易陷入局部最优等问题提出基于ICEEMDAN-MSE-KPCA与NGO-HKELM优化的转子故障诊断方法。首先,采用改进的自适应噪声完全集合经验模态分解(improved complete empirical mode decomposition with adaptive noise,ICEEMDAN)方法对转子振动信号进行分解和重构;计算重构信号的多尺度样本熵(multiscale sample entropy,MSE),形成特征向量,通过核主成分分析(kernel principal component analysis,KPCA)方法对高维的特征向量进行降维;最后,将降维后的特征向量输入北方苍鹰算法(northern goshawk optimization,NGO)优化的混合核极限学习机(hybrid extreme learning machine,HKELM)进行转子故障分类。研究结果表明,基于ICEEMDAN-MSE-KPCA与NGO-HKELM优化的转子故障诊断模型,平均识别准确率可达97.7273%,平均寻优时间为1.0681 s,收敛速度快、准确率高以及分类效果好。

混凝土灌注桩钻芯法芯样抗压强度结果不确定度评定

本文结合工程实例分析了混凝土灌注桩钻芯法芯样抗压强度试验过程中引入的因素,建立了混凝土芯样抗压强度测量不确定的计算模型,计算出不同因素导致的不确定度分量,从而分别计算A类和B类测量不确定度、合成标准不确定度及扩展不确定度。根据不同因素导致的不确定度分量大小,分析出影响不确定度的关键因素,基于此提出提高抗压强度检测结果准确性的方法。

基于保护电路运行状态增强识别的双馈风电场等值建模

网侧故障期间各风电机组保护电路运行状态是影响双馈风电场并网点暂态响应特性的主要因素。针对双馈风电机组保护电路运行状态难以显式数学表征的问题,提出了基于保护电路运行状态增强识别的双馈风电场等值建模方法。首先,根据样本对模型训练过程的影响程度构建了核心样本指数用于提取核心样本,利用生成对抗网络(generative adversarial network, GAN)对核心样本进行学习生成增强。然后,采用增强样本集训练深度信念网络(deep belief network, DBN)构建双馈风电机组保护电路运行状态识别模型。最后,根据识别结果及风速对双馈风电场内机组进行分群,计算各群等值参数最终建立双馈风电场等值模型。通过对比试验以及指标评价,验证了样本增强对模型训练的提升效果以及运用所提方法构建的等值模型的准确性。