Relationship between Inter Canine Width and Inter Alar Width, Inter Commissural Width, and Inter Canthal Distance: A Pilot Study

The aim of this study was to determine the relationship between inter canine width (ICW) and inter alar width (IAW), inter commissural width (ICoW), and inter canthal distance (ICaD) in Bantu population. Materials and Methods: It was a pilot study included all participants who were aged at least 18 years, without a history of orthodontics treatment from Prosthodontics Department, Faculty of Dental Medicine, University of Kinshasa. The Ethics committee of the National Center of Research for Dental Sciences in DR Congo approved the study protocol (CNRSB 1504.218). The participants medical records were obtained from the interview and dental examination. Nature of the study was explained with participant information sheet, and an informed consent of all participants was obtained. The inclusion criteria were no missing maxillary and mandibular teeth, no diastema, and no anterior restorations, 18 years old before enrollment in the study. The exclusion criteria were inability to meet the above requirements, pregnancy, and refusal to participate in the study. The inter-canine width (ICW), inter alar width (IAW), inter canthal distance (ICaD) and inter-commissural width (ICoW) of each participant were measured with a digital Vernier caliper (Mitutoyo, UK Ltd.,) (0.01 mm) three times and the average value was recorded. The inter canthal distance (ICaD) was measured without applying pressure by bringing the recording parts of the caliper just in contact with the medial angle. The inter alar width (IAW) was marked with a fine marked pencil on the widest outer surface of the alae of the nose on either side or width. Those two points were measured without applying pressure by bringing the recording parts of the caliper just in contact with the outer surface. The participant was told to stop breathing shortly to avoid any change in shape of the nose. The inter-commissural width (ICoW) was determined by measuring the maxillary lip vermilion from commissure to commissure without the application of pressure on the tissue in the relaxed state. The inter-canine width (ICW) was measured indirectly using a dental floss. A dental floss was marked on one end prior to placement in the mouth. Using that point as reference, the dental floss was circumference along the curvature of the anterior dentition such that it passed along the contact point of all the teeth. The distal end of the canine teeth on both sides was then marked on the floss while it was stretched in the patients mouth. Floss was marked on both sides with the marker pencil. The distance between the two proximal contact points was measured and recorded. Data, analysis and validation were performed by the SPSS software (version 22.0, IBM SPSS Statistics, Chicago, IL, USA). Unpaired t-test was used, of Kolmogorov-Smirnov test. Analysis of variance (ANOVA) test was used to test for comparability between socio-demographic characteristics dental measurements. Pearsons correlation coefficients test was calculated to determine the relationship between facial and dental parameters. Significance was set at P 0.01. Results: Of 314 participants enrolled, 202 were included. The age ranged from 18 to 68 years, with a mean age of 40.62 12.99 years. Although the Pearsons correlation coefficients were negative. Ninety-three participants (46%) were men and one hundred and nine (54%) were women. The overall mean age was 40.62 12.99 years. Facial and dental measurements were greater in women than men with significant differences for ICW (p = 0.04). However, no significant difference was seen between men and women for IAW, ICaD and ICoW (p = 0.44, p = 0.23, p = 0.31 respectively). The correlation including Pearsons correlation coefficient and P-values for all participants is not demonstrated. Conclusion: Within the limitations of this study, the results suggest that IAW, ICaD and ICoW cannot be used as a preliminary method for determining the width of the maxillary for anterior teeth for edentulous patients.

Inter-Row Spacing of PV Power Plant

When designing a solar power plant, it is much more important to avoid the shadow on the PV Panels. As the shadow falls on the PV Panels;it significantly reduces the generation of required power as planned and designed. This research paper and case study will help a lot to avoid shadow, especially when selecting inter-row spacing between the strings of solar power plants.

Inter-Fraction Analysis of One Week Hypo-Fractionation of Deep Inspiration Breath Hold (DIBH) Technique for Left Sided Breast Cancer Radiation Treatment

The aim of this study was to investigate the inter-fraction variations, patient comfort and knowledge at Charlotte Maxeke Johannesburg Academic Hospital (CMJAH). The differences in set-up that occurred between treatment sessions for the left sided breast patients were observed and recorded. Measurements of routine set-up variation for 24 patients were performed by matching the cone beam computed tomography (CBCT) and the planning computed tomography (CT). Scans of all five fractions per patient were used to quantify the setup variations with standard deviation (SD) in all the three directions (anterior posterior, left right, and superior inferior). The patients DIBH comfort and knowledge was also evaluated. The average translational errors for the anterior posterior (AP, z), left-right (LR, x), and Superior-inferior (SI, y) directions were 0.40 cm, 0.40 cm, and 0.40 cm, respectively. The translation variation of the three directions showed statistical significance (P < 0.05). On comfort and knowledge investigation, among all participants, 80% moderately agreed that the therapist’s instructions for operating the deep inspiration breath hold (DIBH) technique were easy to understand, and 63.33% indicated that their comfort with the DIBH technique was neutral or average. The inter-fraction variations in patients with left-sided breast cancer were qualitatively analyzed. Significant shifts between CBCT and planning CT images were observed. The daily treatment verification could assist accurate dose delivery.

Adaptive neuro-fuzzy interface system for gap acceptance behavior of right-turning vehicles at partially controlled T-intersections

Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system （ANFIS） to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections （in India, vehicles are driven on the left side of a road）. Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver＇s decision （accepted/rejected）. ANFIS models are developed by using 80 % of the extracted data （total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles） and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.

基于Inter.iamb-Tabu算法的区域滑坡敏感性评价

确定滑坡敏感性概率的空间分布,可为滑坡防治政策制定和土地利用规划提供科学依据。由于成灾环境的空间差异和滑坡机理的复杂性,基于不同逻辑架构(物理模型、理论模型等)的滑坡敏感性评价针对特定孕灾环境,无法提前确定最优数学评价模型,而基于深度学习法的、融合多种模型的混合算法能较好地解决这个问题。本文以山东省淄博市博山区为研究区域,基于单因素Logistic回归法筛选了滑坡致灾因子,通过频率比法对致灾因子进行了分级;对4种基于贝叶斯网络的改进算法(MMHC、MMPC-Tabu、Fast.iamb-Tabu、Inter.iamb-Tabu)进行验证,引入错误指数确定了建模效果最佳的算法;计算了博山区774570个栅格的滑坡敏感性概率,绘制了博山区滑坡敏感性分布图;基于GIS的空间叠加和栅格计算器功能,对比了各模型的滑坡敏感性评价结果。研究结果表明:(1)基于Inter.iamb-Tabu开展博山区滑坡敏感性建模时效果最佳。该模型包含10个节点(9个致灾因子节点和1个结局节点)、14条有向边。研究区域可划分为极高敏感区、高敏感区、中敏感区、低敏感区和极低敏感区,分别占总面积的7.30%(49.80km^(2))、16.50%(112.56km^(2))、26.10%(178.05km^(2))、33.20%(226.49km^(2))和16.90%(115.29km^(2)),分别有67处、22处、7处、2处和1处滑坡位于上述敏感区。(2)MMHC、MMPC-Tabu和Fast.iamb-Tabu模型在训练时易舍弃样本中部分因子的特征信息,以达到模型整体精度最优的目的。研究成果可为山东省淄博市博山区滑坡防治提供理论依据,采用的研究方法同样适用于类似地区。

Training Neuro-Fuzzy by Using Meta-Heuristic Algorithms for MPPT

It is one of the topics that have been studied extensively on maximum power point tracking(MPPT)recently.Traditional or soft computing methods are used for MPPT.Since soft computing approaches are more effective than traditional approaches,studies on MPPT have shifted in this direction.This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT.The meta-heuristic training algorithms used are particle swarm optimization(PSO),harmony search(HS),cuckoo search(CS),artificial bee colony(ABC)algorithm,bee algorithm(BA),differential evolution(DE)and flower pollination algorithm(FPA).The antecedent and conclusion parameters of neuro-fuzzy are determined by these algorithms.The data of a 250 W photovoltaic(PV)is used in the applications.For effective MPPT,different neuro-fuzzy structures,different membership functions and different control parameter values are evaluated in detail.Related training algorithms are compared in terms of solution quality and convergence speed.The strengths and weaknesses of these algorithms are revealed.It is seen that the type and number of membership function,colony size,number of generations affect the solution quality and convergence speed of the training algorithms.As a result,it has been observed that CS and ABC algorithm are more effective than other algorithms in terms of solution quality and convergence in solving the related problem.

Long-term and short-term stability characteristics of receiver inter system bias for BDS3/BDS2

The study of inter-system bias(ISB)is important for multi-system fusion and the performance of different signal compatibility.In this paper,the stability of ISB at the BDS3/BDS2 receiver end is calculated and analyzed for different time spans(DOY 060~090 in 2021)from a total of 31 MGEX and iGMAS stations.We adopted two estimation strategies,random walk and constant approach,using the precision products of orbit and clock bias provided by WUM,the influence of which on ISB was also analyzed.Our results showed that the ISB value varied little within a day,and the mean of daily ISB standard deviation was only 0.037 m when the observation condition was good.The signal reception was continuous,indicating a high ISB stability for one day.If extending the time series to one month,however,the ISB standard deviation calculated by constant approach,in which a constant ISB is estimated on a daily basis was about 0.1 m,and the results of adjacent days were not continuous,with no apparent pattern.Concerning the random walk approach,the obtained ISB time series also had a jump,and the conclusion was the same as that of the constant strategy.Besides,receiver types showed a strong regularity in ISB numerical situation,and the distribution of ISB values corresponding to the same receiver type was relatively close.Therefore,we conclude that the ISB parameters remain stable in the short term(one day)and less stable in the long-term period.It is recommended that the ISB term should be set as a constant estimate every day in BDS3/BDS2 solutions,regardless of receiver type consistency.

An Automatic Threshold Selection Using ALO for Healthcare Duplicate Record Detection with Reciprocal Neuro-Fuzzy Inference System

ESystems based on EHRs(Electronic health records)have been in use for many years and their amplified realizations have been felt recently.They still have been pioneering collections of massive volumes of health data.Duplicate detections involve discovering records referring to the same practical components,indicating tasks,which are generally dependent on several input parameters that experts yield.Record linkage specifies the issue of finding identical records across various data sources.The similarity existing between two records is characterized based on domain-based similarity functions over different features.De-duplication of one dataset or the linkage of multiple data sets has become a highly significant operation in the data processing stages of different data mining programmes.The objective is to match all the records associated with the same entity.Various measures have been in use for representing the quality and complexity about data linkage algorithms,and many other novel metrics have been introduced.An outline of the problem existing in themeasurement of data linkage and de-duplication quality and complexity is presented.This article focuses on the reprocessing of health data that is horizontally divided among data custodians,with the purpose of custodians giving similar features to sets of patients.The first step in this technique is about an automatic selection of training examples with superior quality from the compared record pairs and the second step involves training the reciprocal neuro-fuzzy inference system(RANFIS)classifier.Using the Optimal Threshold classifier,it is presumed that there is information about the original match status for all compared record pairs(i.e.,Ant Lion Optimization),and therefore an optimal threshold can be computed based on the respective RANFIS.Febrl,Clinical Decision(CD),and Cork Open Research Archive(CORA)data repository help analyze the proposed method with evaluated benchmarks with current techniques.

Tricube Weighted Linear Regression and Interquartile for Cloud Infrastructural Resource Optimization

Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.

莱卡公司再度亮相Intertextile,用“新”诠释创新实力

8月30日,中国国际纺织面料及辅料(秋冬)博览会(Intertextile)正式落下帷幕。作为暌违两年的再度回归,The LYCRA Company(以下简称“莱卡公司”)携众多新品强势亮相,重磅推出LYCRA■ ADAPTIV fiber(莱卡■智合智纤)系列新产品。为了满足市场对耐用服装的需求,提供更具尺码包容性、更高舒适度和更强功能的服装。

Data Analytics on Unpredictable Pregnancy Data Records Using Ensemble Neuro-Fuzzy Techniques

The immune system goes through a profound transformation during pregnancy,and certain unexpected maternal complications have been correlated to this transition.The ability to correctly examine,diagnoses,and predict pregnancy-hastened diseases via the available big data is a delicate problem since the range of information continuously increases and is scalable.Many approaches for disease diagnosis/classification have been established with the use of data mining concepts.However,such methods do not provide an appropriate classification/diagnosis model.Furthermore,single learning approaches are used to create the bulk of these systems.Classification issues may be made more accurate by combining predictions from many different techniques.As a result,we used the Ensembling of Neuro-Fuzzy(E-NF)method to perform a high-level classification of medical diseases.E-NF is a layered computational model with self-learning and self-adaptive capabilities to deal with specific problems,such as the handling of imprecise and ambiguous data that may lead to uncertainty concerns that specifically emerge during the classification stage.Preprocessing data,Training phase,Ensemble phase,and Testing phase make up the complete procedure for the suggested task.Data preprocessing includes feature extraction and dimensionality reduction.Besides such processes,the training phase includes the fuzzification process of medical data.Moreover,training of input data was done using four types of NF techniques:Fuzzy Adaptive Learning Control Network(FALCON),Adaptive Network-based Fuzzy Inference System(ANFIS),Self Constructing Neural Fuzzy Inference Network(SONFIN)and/Evolving Fuzzy Neural Network(EFuNN).Later,in the ensemble phase,all the NF methods’predicted outcomes are integrated,and finally,the test results are evaluated in the testing phase.The outcomes indicate that the method could predict impaired glucose tolerance,preeclampsia,gestational hypertensive abnormalities,bacteriuria,and iron deficiency anaemia better than the others.In addition,the model exposed the capability to be utilized as an autonomous learning strategy,specifically in the early stages of pregnancy,examinations,and clinical guidelines for disease interventions.

An Adaptive Neuro-Fuzzy Inference System to Improve Fractional Order Controller Performance

The design and analysis of a fractional order proportional integral deri-vate(FOPID)controller integrated with an adaptive neuro-fuzzy inference system(ANFIS)is proposed in this study.Afirst order plus delay time plant model has been used to validate the ANFIS combined FOPID control scheme.In the pro-posed adaptive control structure,the intelligent ANFIS was designed such that it will dynamically adjust the fractional order factors(λandµ)of the FOPID(also known as PIλDµ)controller to achieve better control performance.When the plant experiences uncertainties like external load disturbances or sudden changes in the input parameters,the stability and robustness of the system can be achieved effec-tively with the proposed control scheme.Also,a modified structure of the FOPID controller has been used in the present system to enhance the dynamic perfor-mance of the controller.An extensive MATLAB software simulation study was made to verify the usefulness of the proposed control scheme.The study has been carried out under different operating conditions such as external disturbances and sudden changes in input parameters.The results obtained using the ANFIS-FOPID control scheme are also compared to the classical fractional order PIλDµand conventional PID control schemes to validate the advantages of the control-lers.The simulation results confirm the effectiveness of the ANFIS combined FOPID controller for the chosen plant model.Also,the proposed control scheme outperformed traditional control methods in various performance metrics such as rise time,settling time and error criteria.

对有关电能计量若干问题的思考

文中基于论证和较全面分析,就不同场景下电能计量所关注的截然不同的问题、更好利用大数据去构建电能表检验新方法、动态电能计量研究面临新挑战、关注超谐波电能计量、不宜将电能计量装置与电能表简单划等号,以及测量准确度不同于测量精度等六个问题,阐述了作者的观点和认识,旨在对开展相关研究,以及更清楚理解相关测量方法及概念等起到促进作用。

热处理对选区激光熔化Al-Mn-Mg-Sc-Zr合金力学性能和腐蚀行为的影响

以Al-4.77Mn-1.37Mg-0.67Sc-0.25Zr(质量分数,%)合金粉末为原料,在激光功率330 W和扫描速率700 mm/s下进行选区激光熔化(Selective laser melting,SLM)形成SLM Al-Mn-Mg-Sc-Zr合金,结合慢应变速率拉伸实验、电化学测试、析氢浸泡实验及显微组织表征手段,分析了(350℃,8 h)热处理对SLM Al-Mn-Mg-Sc-Zr合金力学性能和腐蚀行为的影响。结果表明:SLM Al-Mn-Mg-Sc-Zr合金力学性能优异,抗拉强度、屈服强度和伸长率分别为423 MPa、376 MPa和25.1%。热处理后,SLM Al-Mn-Mg-Sc-Zr合金晶内析出大量针棒状纳米Al_(6)Mn相,抗拉强度和屈服强度分别提升至509 MPa和478 MPa。此外,SLM Al-Mn-Mg-Sc-Zr合金具有良好的耐蚀性能,热处理可以促进SLM Al-Mn-Mg-Sc-Zr合金的钝化,在-0.5 V极化电位时出现钝化台阶,降低SLM Al-Mn-Mg-Sc-Zr合金的电流密度,增加SLM Al-Mn-Mg-Sc-Zr合金的阳极极化率,使SLM Al-Mn-Mg-Sc-Zr合金的平均析氢速率从0.242 mL/(cm^(2)·h)降至0.216 mL/(cm^(2)·h),应力腐蚀敏感因子从3.379%降至0.405%。与此同时,热处理也促进了晶内微米富Si相以及晶界富Mn相和Mg相的析出,增加了SLM Al-Mn-Mg-Sc-Zr合金点蚀形核位置,增大了SLM Al-Mn-Mg-Sc-Zr合金的晶界电化学成分非均匀性,降低了SLM Al-Mn-Mg-Sc-Zr合金的点蚀和晶间腐蚀抗力。

Research progress on inter-monthly winter temperature variation in East Asia and climate prediction

近年来,东亚冬季气温的月际间变化十分显著,冬季不同月份或不同阶段之间极端冷暖事件的转折或交替频发.由于月际间变化常常被季节平均掩盖,东亚冬季气候预测面临众多的挑战.因此,亟需研究东亚冬季气温月际间变化的特征和机理,明确其可预测性和预测来源,进而研制考虑月际变化的东亚冬季气温的有效预测方法和预测模型.本文回顾了过去5年对东亚冬季气温月际间变化的主要特征,物理过程,机制,可预测性和预测的研究进展,同时考虑了多个与气温相联系统的变化,包括冬季风,西伯利亚高压,平流层极涡.本文也进一步讨论了未来的研究前景.

籼粳亚种间育性位点分型及籼粳杂交稻育性位点模式研究

【目的】了解我国籼稻、粳稻材料及籼粳杂交稻组合中亚种间育性位点的分布,建立实现亚种间育性亲和所需遗传位点模式,探索新的籼粳杂交稻组合模式,为亚种间亲和材料改良和籼粳育性亲和分子设计育种打下基础。【方法】通过筛选得到育性位点的籼粳分型标记对我国水稻材料进行育性位点的籼粳分型检测,挑选部分籼稻、粳稻亲本进行杂交并统计分析F1代花粉育性和结实率。【结果】籼稻和粳稻之间在所有育性位点均存在少量相互渗入。由于籼稻育性位点渗入,粳稻可以分为Ⅰ型(所有位点均为粳型)和Ⅱ型(Sc^(i)、Sd^(i)和Se^(i),上标i代表来自籼稻)。S5不亲和时籼粳杂交稻结实率约为50%,亲和时结实率约为80%。Sa、Sb、Sc或Sd单个位点杂合对于花粉育性影响较小,但Se/pf12/RHS12单个位点杂合时显著降低花粉育性。籼粳杂交稻材料检测结果表明其育性位点的基本模式是S5和部分花粉育性位点纯合/亲和。带有S5^(n)的籼稻两系不育系深08S与粳稻Ⅱ型材料的杂交F_(1)代的花粉育性和结实率正常。【结论】S5是控制雌配子育性的核心位点。影响雄配子育性的位点具有累加效应,其中Se可能是不可缺少的重要位点。S5+Se与Sa、Sb、Sc、Sd任意两个纯合位点可能是实现籼粳亚种间育性亲和的基本遗传位点模式。以广亲和两系籼稻不育系为母本,常规粳稻为父本的“籼不粳恢”籼粳杂交模式是一个可行的亚种间组合模式。

部际信用治理合作备忘录:性质、效力与优化

合作备忘录是部际信用合作治理的重要方式。不同于行政规范性文件,合作备忘录既是公法协定中的部际协定,也是一种契约治理形态。合作备忘录遵循契约相对性一般原理,具有相对效力,但这种效力相对性也是相对的。由于科层制特有的权力结构与行政服从义务、不完善的信用立法、对个人利益的保护等,合作备忘录的效力溢出至地方公权力主体和相对人。合作备忘录具有补充信用立法、强化行政协助、促进参与式治理等优势,也存在冲击法律体系、违反法律保留原则、规避监督、缺乏合作保障等不足,因而需从合法性、规范性、民主性等方面加以优化。

家族相似性、符号圈与艺术跨媒介叙事

总体性的“艺术”仅仅是一个相对意义上的统称,一个代表所有具体门类艺术的“家族相似性”概念。洛特曼把总体性的艺术看成一个大的“符号圈”,而这个符号圈中又存在由各门类艺术构成的多个小符号圈。符号圈具有两个基本特征:一是有界性,即符号圈是有边界的,主要关涉内外关系;二是不均衡性,即符号圈区分为“中心”与“外围”,这是符号圈的内部组织规则。这两个特征都给“艺术文本”的跨媒介叙事带来了深刻影响。综合运用“家族相似性”和“符号圈”理论,不仅可以很好地解释艺术与非艺术,以及艺术符号圈中不同艺术门类之间的跨媒介叙事问题,而且可以合理地解释同一种文学、艺术体裁中的“互参”现象。

北京“新三代家庭”育儿模式下的儿童友好型城市规划策略

回溯儿童友好城市的理念起源,借鉴家庭社会学对于当代抚育结构的经典研究见解,认识到建设儿童友好城市不能仅关注儿童个体,而必须以家庭为完整单元,映射到由全龄人群组成的社会生态系统深部。通过面向北京育儿家庭进行大样本问卷调查,提炼当前北京育儿家庭成员之间亲职分配的主流模式,认识到由代际协作育儿纽带联结的“新三代家庭”已经构成了当前北京最典型的家庭育儿模式。这一认知有助于定位超大城市儿童友好政策输出的侧重领域,避免儿童友好城市创建走向千城一面。通过深入挖掘这一典型模式下“双职工中青年”“银发育儿族”“多孩家庭子女”等人群需求,提出6点促进儿童与家人共享城市服务的策略。

年龄视角下家庭结构转变对农村老人代际支持的影响

本文采用“安徽省农村老年人生活福利状况”2001-2018年7期专项追踪调查数据,聚焦年龄效应构建个体增长模型,深入探究年龄视角下家庭结构转变对农村老人代际支持的动态影响。结果表明,代际支持策略随家庭结构而异,同时该策略会因老人年龄调节而有所调整。其中,随年龄调节,“变为独居”老人会为子女提供更多经济支持;“一直二代及以上同住”老人与其子女间情感亲密越差;“变为二代及以上同住”老人逐渐获得更多日常照料;“一直隔代同住”与“变为隔代同住”老人会得到子女更高水平经济支持,并减少照料支持提供。结果揭示了在老龄化与城市化并行推进的背景下,家庭养老在农村的主体地位仍牢固,巩固家庭养老的主体地位对缓解农村社会养老压力意义深远;揭示了社会应重视不同家庭结构老人的群体异质性,提倡老人接受符合其养老期待的差异化社会养老服务;揭示了孝道观念深刻根植于子女内心并不断驱使其改进代际支持策略,通过两代人的不同支持行为,利用各自优势实现需求互补,这对促进家庭代际和谐至关重要。