Geochemical characteristics and genetic model of dolomite reservoirs in the eastern margin of the Pre-Caspian Basin

The widespread Carboniferous KT-I dolomite in the eastern margin of the Pre-Caspian Basin is an important hydrocarbon reservoir. The dolomite lithology is dominated by crystalline dolomite. The δ18O values range from -6.71‰ to 2.45‰, and average 0.063‰, obviously larger than -2.5‰, indicating low-temperature dolomite of evaporation origin. Stable strontium isotope ratios （87Sr/86Sr） range from 0.70829 to 0.70875 and average 0.708365, very consistent with 87Sr/86Sr ratios in Carboniferous seawater. Chemical analysis of Ca and Mg elements shows that the dolomite has 9.1 mole% excess Ca or even higher before stabilization. The degree of order of dolomite is medium–slightly poor, varying in a range of 0.336-0.504 and averaging 0.417. It suggests that the dolomite formed under near-surface conditions. There are two models for the origin of the Carboniferous KT-I dolomite reservoir. These are 1） the evaporation concentration – weathering crust model and 2） the shoal facies – seepage reflux model. The former is mainly developed in restricted platforms – evaporate platforms of restricted marine deposition environments with a representation of dolomite associated with gypsum and mudstone. The latter mainly formed in platform edge shoals and intra-platform shoals and is controlled by dolomitization due to high salinity sea water influx from adjacent restricted sea or evaporate platform.

Zero Truncated Bivariate Poisson Model: Marginal-Conditional Modeling Approach with an Application to Traffic Accident Data

A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model with estimation procedure and tests for goodness-of-fit and under (or over) dispersion are shown and applied to road safety data. Two correlated outcome variables considered in this study are number of cars involved in an accident and number of casualties for given number of cars.

Causal inference with marginal structural modeling for longitudinal data in laparoscopic surgery: A technical note

Causal inference prevails in the field of laparoscopic surgery.Once the causality between an intervention and outcome is established,the intervention can be applied to a target population to improve clinical outcomes.In many clinical scenarios,interventions are applied longitudinally in response to patients’conditions.Such longitudinal data comprise static variables,such as age,gender,and comorbidities;and dynamic variables,such as the treatment regime,laboratory variables,and vital signs.Some dynamic variables can act as both the confounder and mediator for the effect of an intervention on the outcome;in such cases,simple adjustment with a conventional regression model will bias the effect sizes.To address this,numerous statistical methods are being developed for causal inference;these include,but are not limited to,the structural marginal Cox regression model,dynamic treatment regime,and Cox regression model with time-varying covariates.This technical note provides a gentle introduction to such models and illustrates their use with an example in the field of laparoscopic surgery.

Marginalized cubature Kalman filtering algorithm based on linear/nonlinear mixed-Gaussian model

Aiming at improving the estimation accuracy and real-time of nonlinear system with linear Gaussian sub-structure,a novel marginalized cubature Kalman filter is proposed in Bayesian estimation framework. Firstly,the marginalized technique is adopted to model the target system dynamics with nonlinear state and linear state separately,and the two parts are estimated by cubature Kalman filter and standard Kalman filter respectively. Therefore,the linear part avoids the generation and propagation process of cubature points. Accordingly,the computational complexity is reduced.Meanwhile,the accuracy of state estimation is improved by taking the difference of nonlinear state estimation as the measurement of linear state. Furthermore,the computational complexity of marginalized cubature Kalman filter is discussed by calculating the number of floating-point operation. Finally,simulation experiments and analysis show that the proposed algorithm can improve the performance of filtering precision and real-time effectively in target tracking system.

Numerical modeling of the development of southeastern Red Sea continental margin

The Red Sea continental margin （RSCM） corresponds to a wide hinge zone between Red Sea and Arabian plate. This margin has been studied through geological and geophysical observations primarily in regard to the evolution of Red Sea rift. This margin is characterized by occurrence of thin sediments, significant onshore uplift, tectonic subsidence of the offshore sedimentary basin, active faulting and seismicity. Studies indicate that sedimentary sequences of the margin are deformed by faults and folds resulting from at least two phases of extension and a phase of uplift. During the two phases of extension due to regional plate stress the sequence was cut by set of extensional faults. While during the phase of uplift the sequence was deformed by folding and faulting. The present paper aims to clear the structural development of RSCM during these tectonic episodes, taken as particular tectonic event, by two-dimensional finite element modeling on plane strain condition. Elastic theology is assumed for the oceanic, continental and transitional crust along with syntectonic deposits. Stress field, shear stress and fault distribution suggests that mantle plume weakened the crust following rifting due to regional stress and developed the margin. These results are well consistent with those from present seismicity, active faulting and neotectonic studies.

Modeling Water Quality Impacts of Growing Corn, Switchgrass, and <i>Miscanthus</i>on Marginal Soils

The goal of the study was to model water quality impacts of growing perennial grasses on marginal soils. The GLEAMS-NAPRA and RUSLE models were used to simulate long-term surface runoff, percolation, erosion, total phosphorus (TP), and nitrate (NO3-N) losses associated with the production of corn-based bioenergy systems (i.e. conventional tillage corn and corn grain plus stover removal), switchgrass and Miscanthus on three marginal quality soils and one good quality soil in Indiana. Simulations showed that switchgrass and Miscanthus had no effect on annual runoff, but decreased percolation by at least 17%. Results also suggested a potential for reduction in erosion for Miscanthus across the soil types examined when compared to corn-based bioenergy production. The production of switchgrass and Miscanthus did not have significant effects on the simulated TP and NO3-N losses in runoff compared to corn production systems. Nitrates leached from fertilized Miscanthus production were approximately 90% lower than NO3-N leached from the production of fertilized switchgrass and corn systems. Additional studies are needed to better understand the hydrology, erosion and nutrient responses of Miscanthus and switchgrass production to meet bioenergy demands.

Marginal Conceptual Predictive Statistic for Mixed Model Selection

We focus on the development of model selection criteria in linear mixed models. In particular, we propose the model selection criteria following the Mallows’ Conceptual Predictive Statistic (Cp) [1] [2] in linear mixed models. When correlation exists between the observations in data, the normal Gauss discrepancy in univariate case is not appropriate to measure the distance between the true model and a candidate model. Instead, we define a marginal Gauss discrepancy which takes the correlation into account in the mixed models. The model selection criterion, marginal Cp, called MCp, serves as an asymptotically unbiased estimator of the expected marginal Gauss discrepancy. An improvement of MCp, called IMCp, is then derived and proved to be a more accurate estimator of the expected marginal Gauss discrepancy than MCp. The performance of the proposed criteria is investigated in a simulation study. The simulation results show that in small samples, the proposed criteria outperform the Akaike Information Criteria (AIC) [3] [4] and Bayesian Information Criterion (BIC) [5] in selecting the correct model;in large samples, their performance is competitive. Further, the proposed criteria perform significantly better for highly correlated response data than for weakly correlated data.

恒定市场份额三层次两极均化模型及其应用——我国对“一带一路”沿线国家农产品出口增长的驱动因素及其贡献率分析

恒定市场份额(CMS)三层次两极均化模型将微观层面的商品价格、数量、种类,中观层面的国别、产业结构,与宏观层面的市场份额和需求规模有机结合起来,系统刻画出口波动的直接因素。基于该模型,本文从总体、动态、区域、产业4个维度逐层解析2002—2021年我国对“一带一路”沿线国家农产品出口增长的驱动因素及其贡献率。结果表明,进口需求效应占据主导地位,需求数量和价格水平增长均有显著贡献,虽然出口竞争力效应总体表现不佳,但是品类竞争力和质量竞争力均小幅改善。“一带一路”倡议提出后,出口竞争力效应显著增长,特别是数量竞争力效应大幅改善。研究还表明,上述效应在不同产业和区域既存在共性特征,也具有一定程度差异性。相对于CMS两层次分解框架,CMS三层次两极均化模型的研究内容更加丰富,经济学含义更加清晰,政策启示更加明确,具有更广泛的应用价值。

Gravity Modeling for the Rifted Crust at the Arabian Shield Margin – Further Insight into Red Sea Spreading

A large variation in elevation and gravity anomaly prevails from the Red Sea coast to the interior of the Arabian Shield (AS) across the Asir Igneous Province (AIP);The Asir Mountain (AM) is developed on AIP. Here the elevation varies from 45 - 2700 m, corresponding changes in F.A. are from –30 to + 220 mgal and B.A. from +22 to –175 mgal. Regression relationships between elevation and gravity anomalies demonstrate significant changes in trend at about 400 m threshold of elevation across the pediment west of AM, at about 45 km inland of the shoreline, flanking the Hizaz-Asir Escarpment (HAE). Gravity anomaly variation along a traverse taken across HAE and AIP is interpreted here in terms of anomalous masses in crust as well as due to deeper crustal configuration. 2D gravity interpretation is, in part, constrained by surface geology, available geologic cross-sections for crust, interpretations from the IRIS Deep-Seismic Refraction Line, and to a lesser extent by the available gross results from shear-wave splitting and receiver function analysis. The gravity model provides probable solutions for the first time on geometric configuration and geophysical identification: a) for the seaward margin of the mid-Tertiary Mafic Crust (TMC) below sediment cover of the Asir pediment that coincides with the 400 m threshold elevation. This signifies an anomalous uplift at the rifting phase. Moho below TMC extends from 10 - 22 km depth across HAE and west margin of AIP, b). Thinned continental crust below the Asir margin whose upper layer coincides with a seismic reflector is at about 22 km depth, c). Rift-margin characteristic detachment fault associated with basaltic flows on top surface of TMC at its inner margin, d). Two geologically mapped low-angle normal faults dipping to the east developed between the basic rocks intruding the AIP and e). felsic pluton farther east within AS. Large scale igneous activity followed by intense deformation affecting AIP clearly owes their origin to the rifting architecture of the AS at the Red Sea extensional margin.

An accurate analytical I-V model for sub-90-nm MOSFETs and its application to read static noise margin modeling

We propose an accurate model to describe the I-V characteristics of a sub-90-nm metal-oxide-semiconductor field-effect transistor(MOSFET) in the linear and saturation regions for fast analytical calculation of the current.The model is based on the BSIM3v3 model.Instead of using constant threshold voltage and early voltage,as is assumed in the BSIM3v3 model,we define these voltages as functions of the gate-source voltage.The accuracy of the model is verified by comparison with HSPICE for the 90-,65-,45-,and 32-nm CMOS technologies.The model shows better accuracy than the nth-power and BSIM3v3 models.Then,we use the proposed I-V model to calculate the read static noise margin(SNM) of nano-scale conventional 6T static random-access memory(SRAM) cells with high accuracy.We calculate the read SNM by approximating the inverter transfer voltage characteristic of the cell in the regions where vertices of the maximum square of the butterfly curves are placed.The results for the SNM are also in excellent agreement with those of the HSPICE simulation for 90-,65-,45-,and 32-nm technologies.Verification in the presence of process variations and negative bias temperature instability(NBTI) shows that the model can accurately predict the minimum supply voltage required for a target yield.

基于Ordered Probit模型的人车冲突安全影响因素研究

为探究和定量分析人车冲突严重程度的影响因素,通过采集3个信号交叉口的人车冲突视频数据,利用T-Analyst标定人车轨迹并计算冲突指标(PET),采用85%位累计频率曲线法划分人车冲突等级;从人、车、路及环境特征中选取10个因素作为变量,构建Ordered Probit模型,以确立人车冲突严重程度的显著影响因素,并通过边际效应定量分析不同显著因素的影响程度。研究结果表明:行人闯红灯情况、年龄、行人交通量、人行道占用情况、人行道起点终点、车辆速度变化及车流量是人车冲突严重程度的显著因素,相较于各自参考量,行人闯红灯、车辆加速通过冲突点、人行道起点及老年人造成严重冲突的概率分别增加8.2%,5.9%,5.1%,4.4%;相较于低流量的交通流,较高流量的车流和行人交通流使得严重冲突的概率分别增加3.7%,2.5%,但人行道占用使得严重冲突的概率下降6.8%。研究结果可为信号交叉口行人过街交通安全设施的设计和实施提供理论依据。

基于电气转矩法的VSC-HVDC系统直流电压振荡稳定性评估

文章采用电气转矩法分析了VSC-HVDC系统的直流电压振荡稳定性。首先,基于电压源型换流器的平均值模型,分别研究了基于功率控制的换流器及基于电压控制的换流器的动态响应特征以得到适用于电气转矩法的并网换流器模型。基于提出的评估模型,建立了双端VSC-HVDC系统的Phillips-Heffron模型并推导出系统的阻尼系数和同步系数。经典电气转矩法指出:电力系统稳定性与系统阻尼系数高度相关。因此,基于电气转矩法推导出的稳定条件揭示了系统直流电压振荡失稳机理,量化了直流网络动态及换流器控制动态对直流电压振荡稳定性的影响。当由基于电压控制的换流器及直流网络提供的正阻尼无法抵消由基于功率控制的换流器产生的负阻尼时,系统直流电压振荡稳定性将无法得到保证。此外,合理设置电压控制器的比例增益能够使系统获得足够的稳定裕度。最后,通过仿真验证了电气转矩法在分析VSC-HVDC系统直流电压振荡稳定性问题时的可行性及所得稳定条件的正确性。

关于当前商业银行盈利模式的调查——以衢州市为例

近年来在各项政策的推动下,贷款利率持续下行,利差1逐步收窄,信贷市场呈现“以价换量”的竞争格局,商业银行以利差为主要利润来源的盈利模式面临较大的挑战。本文通过分析近年来存贷利差的演变和均衡利差的界定得到,当前信贷市场竞争已较为充分,商业银行总体利差接近合理水平。未来在支持实体经济发展的同时,推动融资成本稳中有降的路径应重点从降低商业银行负债端利率和强化成本控制两方面出发。

新疆萨热克杂砾岩型铜矿地质特征、成矿模型与找矿模型

新疆萨热克杂砾岩型铜矿产于塔里木盆地西缘,本文从成矿地质体、成矿构造与成矿结构面、矿石组构、铜矿石中主-微量元素和流体包裹体在垂向和水平方向上的变化等方面进行了研究,结果表明:该类型铜矿的成矿地质体为上侏罗统库孜贡苏组上段(J_(3)k^(2))杂砾岩;成矿构造为北东向的复式向斜和北东向的切层断裂;成矿结构面为下白垩统克孜勒苏群第一岩性段(K_(1)kz^(1))底部褐红色粉砂质泥岩与上侏罗统库孜贡苏组上段(J_(3)k^(2))杂砾岩,矿体上盘褐红色粉砂质泥岩为盆地成矿流体的封闭岩相层。杂砾岩铜矿石中碎裂岩化发育,砾石成分主要为泥岩,铁质碳酸盐岩,石英细砂岩,泥质细砂岩,基性火山岩、千枚状泥质板岩、石英砂岩、石英岩、硅质板岩等,分选性较差,粒径一般为0.3~5 cm,个别达到7 cm以上,磨圆中等,多呈次圆状,后期受构造作用发生碎裂化呈可拼接状砾石。胶结物为方解石、白云石、辉铜矿和少量次生石英及沥青等。石英和方解石包裹体研究结果表明:成矿流体为中—低温、中—高盐度,均一温度和盐度具有弱的正相关性,均一温度和气液比呈明显的正相关性,盐度和气液比呈弱的负相关性。在盆地流体的演化过程中,流体具有温度从高到低,盐度从低到高的演化趋势,表现为石英比方解石和白云石结晶要早一些;包裹体中的气相成分主要有N_(2)、CO_(2)、CH_(4)和H_(2)O,从2685中段到2790中段,气相成分具有从CO_(2)、N_(2)、CH_(4)组合向N_(2)、CH_(4)、H_(2)O组合的演变趋势,表明从下部到上部流体的还原性具有逐步减弱的趋势。在上述研究的基础上建立了本区杂砾岩型铜矿的成矿模型,通过不同比例尺物化探勘查方法的有效性分析建立了该类型铜矿的综合找矿模型,可为在该地区开展同类型矿产勘查提供帮助。

基于逆投影变换的纱筒纱线余量检测算法

纱筒纱线余量检测是纺织行业自动化生产过程中的重要一环,针对目前纱线余量检测算法检测精度低的问题,提出一种基于三点逆投影变换模型的纱筒纱线余量检测技术。根据实际生产过程中相机与纱筒的位置关系,建立三点逆投影变换模型进行初步矫正。为得到更好的图像矫正结果,设置补偿矩阵并根据内外筒位置信息优化变换矩阵,最后将逆投影变换后的图像按照改进的椭圆坐标变换模型展开为矩形,根据余量计算准则计算得到纱筒纱线余量。在自主搭建的检测平台上进行实验,结果表明,本文算法检测精度在5 mm以内,基本满足实际生产要求,可为纺织产业自动化生产提供依据。

西非北部被动陆缘盆地油气地质特征与勘探方向

西非北部盆地勘探程度较低,但资源潜力巨大。基于板块构造理论,通过结合地震与地质方法的综合研究,分析了西非北部主要地质时期的原型盆地,对比了各盆地的结构特征及其沉积充填差异性,解剖已发现油气藏,建立成藏模式,指出下一步勘探方向。研究发现:西非北部被动陆缘盆地群经历了前寒武纪—二叠纪前裂陷、三叠纪—早侏罗世裂陷和中侏罗世至今的陆缘3个演化阶段,形成了断陷型、断坳型和坳陷型3个被动陆缘盆地亚类。断陷型盆地形成单源-构造型成藏模式,勘探目标以裂谷层系的构造成藏组合为主;断坳型盆地可形成双源-双组合型成藏模式,大陆架上的缓坡带以裂谷层系构造圈闭为主,在台地边缘应寻找礁体和内幕岩溶,陡坡带上部的主要勘探目标应为规模较大的滑动-滑塌形成的斜坡扇,下部应关注成熟烃源岩层系内扇体所形成的上白垩统和下白垩统砂岩构造-岩性圈闭;坳陷型盆地以坳陷层系烃源岩为主,主要勘探对象为陡坡下部的浊积砂岩及台地缓坡三角洲砂体,台地边缘礁滩体、台地碳酸盐岩风化壳岩溶和断裂带岩溶也是值得重视的勘探方向。研究可为勘探程度低、资料获取难的被动陆缘深水油气勘探选区评价提供借鉴。

考虑水风光联合发电效益最大的水电站水库优化调度

为了经济合理地充分发挥水电站水库的调节能力,促进风光资源的高效消纳,基于微观经济学生产产品时存在的边际产量递减规律,以水电站水库调节能力为可变要素,将风光资源消纳视为“固定要素”的充分发挥,建立了水风光联合发电效益最大模型,可求解得到促进风光资源经济消纳的水电站水库优化调度方案。算例分析结果表明:在入库流量、负荷需求以及水库运行状态等因素一定的条件下,模型可充分反映水电站水库参与风光出力调节时对风光资源的消纳和水风光联合发电效益的贡献,给出了不同情景下水电站水库参与风光出力调节的优化调度方案,对于在保障电力系统安全的前提下充分发挥水电站水库的调节能力和提升水风光联合发电效益具有一定的参考价值。

基于冲击的涡扇发动机退化建模与下发预测

为解决多性能参数模型无法描述不同起飞推力下发动机性能退化的问题,利用单性能参数结合极端冲击模型描述起飞时发动机全功率运转对热端部件的热冲击影响,利用线性退化模型描述发动机自然退化过程,建立发动机性能可靠度退化模型。利用V2500发动机全寿命EGTM数据,结合最大似然估计给出性能可靠度表达式与模型参数,最后利用机队中同型V2500发动机非完整EGTM数据验证模型,预测下发时间,结果表明此模型预测下发时间和实际下发时间的误差小于3%,证明了模型的有效性。

边缘结构模型在医学研究中的应用现状及对护理研究的启示

对边缘结构模型的概念、统计思想、模型特点以及在医学研究中的应用现状进行综述,为护理研究中处理时依性混杂因素并对纵向数据进行因果推断提供思路。

基于集合效用边际贡献学习的可解释薪酬预测算法

知识技能对薪酬影响作用视为一种多变量影响下高维元素集合的效用建模问题.深度神经网络为解决复杂问题提供了新的机遇,但针对知识导向的细粒度薪酬预测问题,仍缺乏能够对复杂变量影响下的集合效用进行准确、可解释建模的神经网络结构.为此,提出一种基于边际贡献的增量式集合效用网络(marginal contribution-based incremental set utility network,MCISUN)来拟合元素加入时的效用增量,从而灵活且可解释地建模集合效用.区别于以往基于池化层的排列不变性建模算法,MCISUN构建顺序敏感的中间结果,利用集合的排列不变性实现数据增强,有效提升模型数据效率及泛化性.最后,大规模真实薪酬数据上的实验结果表明所提模型在基于技能的薪酬预测任务上比最先进的(state-of-the-art,SOTA)模型效果提升超过30%.同时,定性实验证明模型能够为技能设置合理的贡献值且发现技能间的关联.