A Restricted SIR Model with Vaccination Effect for the Epidemic Outbreaks Concerning COVID-19

This paper presents a restricted SIRmathematicalmodel to analyze the evolution of a contagious infectious disease outbreak(COVID-19)using available data.The new model focuses on two main concepts:first,it can present multiple waves of the disease,and second,it analyzes how far an infection can be eradicated with the help of vaccination.The stability analysis of the equilibrium points for the suggested model is initially investigated by identifying the matching equilibrium points and examining their stability.The basic reproduction number is calculated,and the positivity of the solutions is established.Numerical simulations are performed to determine if it is multipeak and evaluate vaccination’s effects.In addition,the proposed model is compared to the literature already published and the effectiveness of vaccination has been recorded.

WOMBAT—A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML)

WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from http：//agbu. une.edu.au/-kmeyer/wombat.html

Generalization properties of restricted Boltzmann machine for short-range order

A biased sampling algorithm for the restricted Boltzmann machine(RBM) is proposed, which allows generating configurations with a conserved quantity. To validate the method, a study of the short-range order in binary alloys with positive and negative exchange interactions is carried out. The network is trained on the data collected by Monte–Carlo simulations for a simple Ising-like binary alloy model and used to calculate the Warren–Cowley short-range order parameter and other thermodynamic properties. We demonstrate that the proposed method allows us not only to correctly reproduce the order parameters for the alloy concentration at which the network was trained, but can also predict them for any other concentrations.

Intelligent architecture modeling for multilevel fluvial reservoirs based on architecture interface and elements

At present,the architecture modeling method of fluvial reservoirs are still developing.Traditional methods usually use grids to characterize architecture interbeds within the reservoir.Due to the thin thickness of this type of the interlayers,the number of the model grids must be greatly expanded.The number of grids in the tens of millions often makes an expensive computation;however,upscaling the model will generate a misleading model.The above confusion is the major reason that restricts the largescale industrialization of fluvial reservoir architecture models in oilfield development and production.Therefore,this paper explores an intelligent architecture modeling method for multilevel fluvial reservoirs based on architecture interface and element.Based on the superpositional relationship of different architectural elements within the fluvial reservoir,this method uses a combination of multilevel interface constraints and non-uniform grid techniques to build a high-resolution 3D geological model for reservoir architecture.Through the grid upscaling technology of heterogeneous architecture elements,different upscaling densities are given to the lateral-accretion bedding and lateral-accretion bodies to simplify the model gridding.This new method greatly reduces the number of model grids while ensuring the accuracy of lateral-accretion bedding models,laying a foundation for large-scale numerical simulation of the subsequent industrialization of the architecture model.This method has been validated in A layer of X oilfield with meandering fluvial channel sands as reservoirs and B layer of Y oilfield with braided river sands as reservoirs.The simulation results show that it has a higher accuracy of production history matching and remaining oil distribution forecast of the targeted sand body.The numerical simulation results show that in the actual development process of oilfield,the injected water will not displace oil in a uniform diffusive manner as traditionally assumed,but in a more complex pattern with oil in upper part of sand body being left behind as residual oil due to the influences of different levels of architecture interfaces.This investigation is important to guiding reservoir evaluation,remaining oil analysis,profile control and potential tapping and well pattern adjustment.

A Molecular Thermodynamic Model for Restricted Swelling Behaviors of Thermo-sensitive Hydrogel

A molecular thermodynamic model was developed for describing the restricted swelling behavior of a thermosensitive hydrogel confined in a limited space. The Gibbs free energy includes two contributions, the contribution of mixing of polymer and solvent calculated by using the lattice model of random polymer solution, and the contribution due to the elasticity of polymer network. This model can accurately describe the swelling behavior of restricted hydrogels under uniaxial and biaxial constraints by using two model parameters. One is the interaction energy parameter between polymer network and solvent, and the other is the size parameter depending on the degree of cross-linking. The calculated results show that the swelling ratio reduces significantly and the phase transition temperature decreases slightly as the restricted degree increases, which agree well with the experimental data.

On Diagnostics in Stochastic Restricted Linear Regression Models

The aim of this paper is to propose some diagnostic methods in stochastic restricted linear regression models. A review of stochastic restricted linear regression models is given. For the model, this paper studies the method and application of the diagnostic mostly. Firstly, review the estimators of this model. Secondly, show that the case deletion model is equivalent to the mean shift outlier model for diagnostic purpose. Then, some diagnostic statistics are given. At last, example is given to illustrate our results.

Surface structures of equilibrium restricted curvature model on two fractal substrates

With the aim to probe the effects of the microscopic details of fractal substrates on the scaling of discrete growth models, the surface structures of the equilibrium restricted curvature （ERC） model on Sierpinski arrowhead and crab sub- strates are analyzed by means of Monte Carlo simulations. These two fractal substrates have the same fractal dimension dr, but possess different dynamic exponents of random walk Zrw. The results show that the surface structure of the ERC model on fractal substrates are related to not only the fractal dimension df, but also to the microscopic structures of the substrates expressed by the dynamic exponent of random walk Zrw- The ERC model growing on the two substrates follows the well-known Family-Vicsek scaling law and satisfies the scaling relations 2a ~ df ~ z ~ 2Zrw. In addition, the values of the scaline exponents are in ~ood a^reement with the analytical orediction of the fractional Mullins-Herring equation.

Gas-Fluid and Fluid-Solid Phase Instability for Restricted Primitive Model

By considering the fluctuation of grand potential f~ around equilibrium with respect to small one-particle density fluctuations δpα（r→）, the phase instability of restricted primitive model （RPM） of ionic systems is investigated. We use the integral equation theory to calculate the direct correlation functions in the reference hypernetted chain approximation and obtain the spinodai line of RPM. Our anaiysis explicitly indicates that the gas-fluid phase instability is induced by k = 0 fluctuation mode, while the fluid-solid phase instability is related to k ≠ 0 fluctuation modes. The spinodai line is qualitatively consistent with the result of computer simulations by others.

Green's function Monte Carlo method combined with restricted Boltzmann machine approach to the frustrated J_(1)–J_(2)Heisenberg model

Restricted Boltzmann machine(RBM)has been proposed as a powerful variational ansatz to represent the ground state of a given quantum many-body system.On the other hand,as a shallow neural network,it is found that the RBM is still hardly able to capture the characteristics of systems with large sizes or complicated interactions.In order to find a way out of the dilemma,here,we propose to adopt the Green's function Monte Carlo(GFMC)method for which the RBM is used as a guiding wave function.To demonstrate the implementation and effectiveness of the proposal,we have applied the proposal to study the frustrated J_(1)-J_(2)Heisenberg model on a square lattice,which is considered as a typical model with sign problem for quantum Monte Carlo simulations.The calculation results demonstrate that the GFMC method can significantly further reduce the relative error of the ground-state energy on the basis of the RBM variational results.This encourages to combine the GFMC method with other neural networks like convolutional neural networks for dealing with more models with sign problem in the future.

Model identification with BPNN on restrictive ecological factors of SRB for sulfate-reduction

The model of back-propagation neural network (BPNN) was presented to demonstrate the effect of restrictive ecological factors, COD/SO 4 2- ratio, pH value, alkalinity (ALK) and SO 4 2- loading rate (Ns), on sulfate reduction of Sulfate Reducing Bacteria (SRB) in an acidogenic sulfate reducing reactor supplied with molasses as sole organic carbon source and sodium sulfate as electron acceptor. The compare of experimental results and computer simulation was also discussed. It was shown that the method of BPNN had a powerful ability to analyze the ecological characteristic of acidogenic sulfate reducing ecosystem quantitatively.

Model and algorithm of optimizing alternate traffic restriction scheme in urban traffic network

An optimization model and its solution algorithm for alternate traffic restriction(ATR) schemes were introduced in terms of both the restriction districts and the proportion of restricted automobiles. A bi-level programming model was proposed to model the ATR scheme optimization problem by aiming at consumer surplus maximization and overload flow minimization at the upper-level model. At the lower-level model, elastic demand, mode choice and multi-class user equilibrium assignment were synthetically optimized. A genetic algorithm involving prolonging codes was constructed, demonstrating high computing efficiency in that it dynamically includes newly-appearing overload links in the codes so as to reduce the subsequent searching range. Moreover,practical processing approaches were suggested, which may improve the operability of the model-based solutions.

Modelling the Violation of Restrictions Pertaining to Deforestation in a Given Land Right

This paper develops a model that could be used to visualize and predict the violation of restrictions in a given forest. The violation of restriction in this case is assumed to be the difference in areal extent between two forest cover scenes with time;termed “deforestation”. It analyses the relationship in forest cover changes overtime in Ganye Forest Reserve and Glide Cross Country Farm in Adamawa state, Nigeria. Cadastral maps of the forest reserve and farmland were used as the base maps, while the satellite images served as the spatio-temporal data. Landsat ETM+ images of 2003, 2008 and 2013 were used to identify, determine and estimate the violation of restrictions. The result shows that the violation of restrictions could be reliably determined for both the forest reserve and farmland and forecast made in order to predict future occurrence. It also revealed a continuous deforestation in the forest reserve, while in the farmland regeneration of forest stock was noticed. This information is very vital for forest management, planning and decision making in a viable land administration domain.

Admissibility of Linear Estimators in the Growth Curve Model with Respect to Inequality Restriction

For the growth curve model with respect to inequality restriction： Y = XBZ ＋ε,ε（0, σ2V I）, trNB ≥0, this paper gives some necessary and sufficient conditions for the linear estimator of KBL to be admissible in the class of homogeneous linear estimators LH and nonhomogeneous linear estimators LI, respectively, under the quadratic loss function tr（d（Y） - KBL）＇（d（Y） - KBL）.

欧盟对中国反倾销的贸易限制效应研究——基于2010—2022年月度贸易数据

本文将欧洲联盟2010—2022年间对我国发起的反倾销案件进行完整梳理,首先选取我国遭受欧盟反倾销的典型涉案产品,详细阐述欧洲联盟进口量和进口额在反倾销前后的变动趋势。其次,使用2010—2022年间欧洲联盟与我国的HS6位码月度贸易数据构建动态面板模型,采用差分广义矩估计,确定以季度为研究周期,更为合理地动态考察欧洲联盟对我国反倾销的贸易限制效应,并区分反倾销节点异质性和产品异质性。最后,采用反事实估计法量化欧洲联盟对我国反倾销典型涉案产品的贸易限制比例。研究结果表明,欧洲联盟对我国反倾销典型涉案产品存在贸易限制效应,立案调查的贸易限制效应通常不存在滞后,而肯定性终裁的贸易限制效应往往存在滞后。本文对我国出口企业如何预警欧洲联盟发起的反倾销具有实际意义,也有助于重点出口行业合理调整生产,避免欧洲联盟对我国反倾销带来的损失。若贸易数据可以细分反倾销涉案产品的HS8位码,则能进一步将产品创新可能带来的影响纳入考察。

家庭旅游决策行为的影响因素与机制研究——基于CEM模型

文章运用问卷调查法,以约束-影响-缓解模型为理论框架,将家庭旅游决策者作为研究对象,探究旅游动机、旅游限制、协商策略与家庭旅游意愿之间的影响关系。通过研究发现:在家庭旅游决策过程中,(1)旅游动机(个人动机、家庭动机)和协商策略(行为策略、认知策略)均对家庭旅游意愿有正向影响,而旅游限制(家人内在限制和家庭限制)对家庭旅游意愿有负向影响;(2)旅游动机(个人动机、家庭动机)和旅游限制(个人内在限制、结构限制)均对协商策略有显著的正向影响;(3)协商策略在旅游限制(个人内在限制和结构限制)和旅游动机(个人动机和家庭动机)对家庭旅游意愿的影响关系中均起到中介作用;(4)通过家庭旅游类型与家庭生命周期交叉分析可知,组织爸妈游的家庭主要处于家庭生命周期中的无巢期,伴侣游主要处于筑巢期,其次是空巢期,亲子游主要处于满巢期,三代同游主要处于满巢期。文章不仅有助于丰富家庭旅游的理论研究,同时可为政府部门和相关企业在家庭旅游市场精准营销上提供实践启示。

基于PRECEDE模式的居民减盐行为影响因素的混合方法研究

背景中国居民高血压患病率高而控制率低,大量流行病学研究表明减少膳食盐的摄入有助于降低血压水平,因此探索居民减盐行为的影响因素对于居民自身的健康管理及减轻社会负担意义重大。目的基于PRECEDE模式,探索山东居民减盐行为的倾向因素、强化因素和促成因素,为后续减盐工作提供科学建议。方法运用混合研究方法,采用目的抽样法,先后于2016年和2018年采访居民共计114名,访谈提纲主要包含对控盐的态度、在控盐过程中遇到的困难以及获得的帮助等。定量数据来源于2016年山东省减盐防控高血压项目终末调查鲁东、鲁中南地区的问卷数据,从数据库中选取与高血压相关调查内容,共纳入研究样本6697份。结果多分类Logistic回归结果显示,在控制其他变量影响下,性别、职业、文化程度对减盐行为依从性有影响(P<0.05)。在控制个人一般情况的影响下,个人口味、减盐知识及对低盐饮食的态度对减盐行为依从性有影响(P<0.05)。医生的干预能强化居民减盐行为。通过医务人员的健康教育,不仅能增强高血压患者的减盐行为与意识,还能加强家人的督促,提升家人的减盐行为与意识,进而达到促进居民减盐的目的。家人在日常生活中的督促能强化居民控盐行为。山东省减盐行动制定了项目推进政策、餐饮业政策、食品业政策以及减盐健康教育政策,打造了浓厚的减盐大环境。低盐产品中对居民影响较大的是限盐勺,低盐食品及低钠盐的可及性相对较低影响了其控盐作用。大众媒体宣传是居民获得减盐信息的主要途径,目前作用较为明显的大众传播方式包括电视和在公共场所的宣传。结论对低盐饮食的态度及知识水平因素是影响居民减盐行为的倾向因素;医生的劝诫和家人的提醒能帮助居民开始减盐,也能强化居民减盐行为,属于强化因素;减盐相关政策、大众传播为居民减盐创造了社会氛围,减盐相关产品则提供了现实条件,属于促成因素。

多国粮食限制出口背景下中国食物安全潜在风险与策略——基于大食物观视角

近年来,全球公共卫生事件和地缘冲突事件频发。面对重大突发事件的冲击,许多国家为保障本国粮食安全限制对外出口,这将对中国食物进口造成不利影响。文章对多国粮食限制出口前后中国食物进口变动进行分析,并用时间序列ARIMAX模型分析中国食物大类、谷物类、畜肉类和水产品类安全水平的主要影响因素,设定的主要因素有国际各类食物贸易动荡程度和中国食物受害风险,分析出当前中国食物安全水平主要受蛋白质类食物供给的影响,多国粮食限制出口对中国谷物类食物和水产品类食物供给影响不大,对畜肉类食物长期供给的影响需警惕。最后,本文基于多国粮食限制出口前后中国食物进口变动分析和实证结果提出未来在大食物观视角下保障中国食物安全的政策建议。

乌江限制性航道船舶快速性预报研究

文中以乌江航道为例,针对当前推广应用的千吨级绿色高能效标准船型,基于乌江标准船型的船模阻力与自航试验,测试了不同水深状态下阻力及自航性能参数.采用傅汝德换算法估算实船阻力及有效功率,分析各工况下有效功率与航速的对应规律,为标准船型选定合适的主机功率.结合船舶能源应用现状制定不同动力方案,计算并比较各方案对应的碳排放与必要运费率,最终推荐柴油-天然气双燃料动力模式.

孕期血清铁蛋白动态变化及其与分娩结局的相关性

目的分析孕期血清铁蛋白(SF)水平的动态变化,探讨不同孕周SF水平与分娩结局的相关关系。方法选取2021年1月至2023年8月期间,在安徽医科大学第一附属医院东城院区规律产检且连续3次SF检测的孕妇665名作为研究对象。分析孕期SF的动态变化,用线性回归模型和限制性立方样条分析不同孕周SF与分娩结局间的相关性,并构建SF动态变化与分娩结局的群组轨迹模型。结果随着孕周增加,SF水平下降,铁缺乏率增加。线性相关性分析显示孕8~16周、孕16~24周SF与分娩结局相关性无统计学意义(P>0.05);孕24-32周SF水平与新生儿身长(β:−0.009,95%CI:−0.015~−0.003)、新生儿体质量(β:−3.331,95%CI:−5.201~−1.461)及分娩孕周(β:−0.013,95%CI:−0.019~−0.008)呈负相关。限制性立方样条曲线拟合显示,孕8~16周SF、孕16~24周SF与分娩结局相关性无统计学意义(P整体>0.05),孕24~32周SF与分娩孕周和新生儿身长呈线性剂量-反应关系(P整体<0.05,P非线性>0.05),与新生儿体质量呈非线性相关关系(P整体<0.05,P非线性<0.05)。群组轨迹模型显示,SF浓度下降较快组早产率高于SF浓度下降中等组和较慢组(P<0.01),SF不同变化轨迹类型与新生儿体重相关性无统计学意义。结论孕24~32周SF水平升高与分娩孕周、新生儿身长和体质量相关,孕期SF持续下降与早产发生风险增加有关。

子痫前期并发胎儿生长受限的风险预测列线图模型构建与验证

目的探讨子痫前期并发胎儿生长受限(FGR)的影响因素,并依此建立列线图预测模型。方法回顾性分析郑州人民医院2018年12月至2022年12月收治的168例子痫前期患者的临床资料,按照2∶1的比例将其分为建模组(112例)和验证组(56例),并根据是否并发FGR将建模组分为并发组(49例)和未并发组(63例)。采用多因素logistic回归分析法分析子痫前期并发FGR的影响因素,并采用R3.4.3软件包绘制列线图模型,采用Bootstrap法进行内部验证;绘制受试者工作特征(ROC)曲线对列线图预测子痫前期并发FGR的效能进行分析,采用决策曲线分析法(DCA)验证模型的临床净获益率。结果并发组发病孕周<34周、羊水过少、收缩压≥160 mmHg、胎儿脐动脉收缩压与舒张压比值(S/D)升高、24 h尿蛋白定量≥2.0 g占比以及血红蛋白(HB)、谷草转氨酸(AST)、血尿酸(UA)、尿素氮(BUN)、肌酐、D-二聚体(D-D)水平高于未并发组(P<0.05),白蛋白、凝血酶原时间(PT)水平低于未并发组(P<0.05);经logistic回归分析可知,发病孕周<34周、羊水过少、S/D比值升高、24 h尿蛋白定量≥2.0 g、BUN和D-D水平升高是子痫前期并发FGR的危险因素(P<0.05),白蛋白是其保护因素(P<0.05)。依据以上影响因素构建子痫前期并发FGR的列线图模型,经Bootstrap法进行内部验证,其一致性指数为0.825,校正曲线和标准曲线拟合度较好;ROC曲线结果显示,建模组列线图预测子痫前期并发FGR的曲线下面积(AUC)、灵敏度、特异度分别为0.862、83.67%、87.30%;验证组列线图预测子痫前期并发FGR的AUC、灵敏度、特异度分别为0.830、80.77%、83.33%;DCA提示列线图模型进行风险评估可获得满意的净收益。结论发病孕周<34周、羊水过少、S/D比值升高、24 h尿蛋白定量≥2.0 g、BUN和D-D水平升高均是子痫前期并发FGR的危险因素,白蛋白是其保护因素,且基于此构建的列线图模型临床应用价值较高,可为临床筛选子痫前期并发FGR高危患者提供参考。