Effects of rotation and gravity on an electro-magneto-thermoelastic medium with diffusion and voids by using the Lord-Shulman and dual-phase-lag models

The effects of rotation and gravity on an electro-magneto-thermoelastic medium with diffusion and voids in a generalized thermoplastic half-space are studied by using the Lord-Shulman (L-S) model and the dual-phase-lag (DPL) model. The analytical solutions for the displacements, stresses, temperature, diffusion concentration, and volume fraction field with different values of the magnetic field, the rotation, the gravity, and the initial stress are obtained and portrayed graphically. The results indicate that the effects of gravity, rotation, voids, diffusion, initial stress, and electromagnetic field are very pronounced on the physical properties of the material.

A Problem of a Semi-Infinite Medium Subjected to Exponential Heating Using a Dual-Phase-Lag Thermoelastic Model

The problem of a semi-infinite medium subjected to thermal shock on its plane boundary is solved in the context of the dual-phase-lag thermoelastic model. The expressions for temperature, displacement and stress are presented. The governing equations are expressed in Laplace transform domain and solved in that domain. The solution of the problem in the physical domain is obtained by using a numerical method for the inversion of the Laplace transforms based on Fourier series expansions. The numerical estimates of the displacement, temperature, stress and strain are obtained for a hypothetical material. The results obtained are presented graphically to show the effect phase-lag of the heat flux and a phase-lag of temperature gradient on displacement, temperature, stress.

Time fractional dual-phase-lag heat conduction equation

We build a fractional dual-phase-lag model and the corresponding bioheat transfer equation, which we use to interpret the experiment results for processed meat that have been explained by applying the hyperbolic conduction. Analytical solutions expressed by H-functions are obtained by using the Laplace and Fourier transforms method. The inverse fractional dual-phase-lag heat conduction problem for the simultaneous estimation of two relaxation times and orders of fractionality is solved by applying the nonlinear least-square method. The estimated model parameters are given. Finally, the measured and the calculated temperatures versus time are compared and discussed. Some numerical examples are also given and discussed.

Monitoring models for base flow effect and daily variation of dam seepage elements considering time lag effect

Affected by external environmental factors and evolution of dam performance, dam seepage behavior shows nonlinear time-varying characteristics. In this study, to predict and evaluate the long-term development trend and short-term fluctuation of the dam seepage behavior, two monitoring models were developed, one for the base flow effect and one for daily variation of dam seepage elements. In the first model, to avoid the influence of the time lag effect on the evaluation of seepage variation with the time effect component of seepage elements, the base values of the seepage element and the reservoir water level were extracted using the wavelet multi-resolution analysis method, and the time effect component was separated by the established base flow effect monitoring model. For the development of the daily variation monitoring model for dam seepage elements, all the previous factors, of which the measured time series prior to the dam seepage element monitoring time may have certain influence on the monitored results, were considered. Those factors that were positively correlated with the analyzed seepage element were initially considered to be the support vector machine(SVM) model input factors, and then the SVM kernel function-based sensitivity analysis was performed to optimize the input factor set and establish the optimized daily variation SVM model. The efficiency and rationality of the two models were verified by case studies of the water level of two piezometric tubes buried under the slope of a concrete gravity dam.Sensitivity analysis of the optimized SVM model shows that the influences of the daily variation of the upstream reservoir water level and rainfall on the daily variation of piezometric tube water level are processes subject to normal distribution.

Time lag characteristics of sap flow in seed-maize and their implications for modeling transpiration in an arid region of Northwest China

Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation（R_s） and vapor pressure deficit of the air（VPD_（air））. Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in R_s and preceded the changes in VPD_（air） both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize＇s sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and R_s in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPD_（air） in comparison with wet soil and also increase the speed by which sap flow adjusts to R_s. However, sap flow lags that were associated with R_s before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements.

An Application of the Modified Shear Lag Model to Study the Influence of Thermal Residual Stresses on the Stiffness and Yield Strength of Short Fiber Reinforced Metal Matrix Composites

The modified shear lag model proposed recently was applied to calculate thermal residual stresses and subsequent stress distributions under tensile and compressive loadings. The expressions for the elastic moduli and the yield strengths under tensile and compressive loadings were derived which take account of thermal residual stresses. The asymmetries in the elastic modulus and the yield strength were interpreted using the derived expressions and the obtained results of the stress calculations. The model predictions have exhibited good agreements with the experimental results and also with the other theoretical predictions

A New Smoothing Approach with Diverse Fixed-lags Based on Target Motion Model

Recently, lots of smoothing techniques have been presented for maneuvering target tracking. Interacting multiple model-probabilistic data association （IMM-PDA） fixed-lag smoothing algorithm provides an efficient solution to track a maneuvering target in a cluttered environment. Whereas, the smoothing lag of each model in a model set is a fixed constant in traditional algorithms. A new approach is developed in this paper. Although this method is still based on IMM-PDA approach to a state augmented system, it adopts different smoothing lag according to diverse degrees of complexity of each model. As a result, the application is more flexible and the computational load is reduced greatly. Some simulations were conducted to track a highly maneuvering target in a cluttered environment using two sensors. The results illustrate the superiority of the proposed algorithm over comparative schemes, both in accuracy of track estimation and the computational load.

A New Modification to Shear Lag Model as Applied to Stiffness and Yield Strength of Short Fiber Reinforced Metal Matrix Composites

A new modification for the shear lag model is given and the expressions for the stiffness and yield Strength of short fiber metal matri×composite are derived. These expressions are then compared with our experimental data in a SiCw/Al-Li T6 composite and the published experimental data on different SiCw/Al T6 composites and also compared with the previous shear lag models and the other theoretical models.

四川地区精细化降水预报融合订正试验及检验

精细化定量降水网格预报是天气预报业务的重点和难点,基于西南区域智能数值网格模式预报系统(Southwest China WRF-based Intelligent Numeric Grid forecast System,SWC-WINGS)1 km×1 km分辨率的小时降水预报,利用时间滞后和概率匹配方法开展融合订正试验,再利用中国气象局多源融合降水系统(CMA Multi-source Precipitation Analysis System,CMPAS)三源融合降水实况格点数据,对2022年7—8月四川地区的小时降水预报融合订正结果进行检验,并在四川盆地西部一次短时强降水天气过程中进行应用,结果表明:(1)时间滞后集合降水预报相较于模式降水预报,存在小量级预报过度,大量级预报过于保守的问题;(2)时间滞后结合概率匹配的降水预报融合订正方法有效提升了各量级降水预报的TS评分,尤其1~2 h预报时效提升显著,小时雨量超过0.1 mm、5 mm、10 mm和20 mm量级的TS评分平均提升率分别为7.2%、17.2%、28.3%和36.3%;(3)一次短时强降水天气过程的应用结果表明,时间滞后结合概率匹配的融合订正方法对模式小时降水预报有较好的改进效果,尤其对大量级降水预报有较强的订正能力。

空间滞后模型在新疆地区HIV/AIDS报告率影响因素生态学研究中的应用

目的应用空间滞后模型分析影响新疆地区人类免疫缺陷病毒(HIV)/艾滋病(AIDS)报告率的社会人口学因素,探讨该模型在AIDS流行病学中的应用价值。方法利用Geoda软件对新疆85个区县2007年—2015年HIV/AIDS报告率与社会人口学因素进行空间回归模型分析。结果多重线性回归(OLS)模型显示回归残差存在空间自相关性(Moran′s I=0.2867,P<0.001),参照拉格朗日乘数(LM)检验,最后选用空间滞后模型(SLM)进行数据分析。SLM中空间滞后项差异具有统计学意义(P<0.001),即HIV/AIDS报告率存在正的空间自相关性。HIV/AIDS报告率与人口数呈正相关,与农业人口比例呈负相关。与传统OLS模型相比,SLM的调整R^(2)上升,对数似然比的绝对值和赤池信息量准则(AIC)值下降,提示拟合效果更好。结论人口多和城镇化比例高的地区HIV/AIDS报告率较高。SLM在AIDS影响因素的生态学研究中有推广价值。

个体化频带滑动窗特征的轻度认知障碍诊断研究

轻度认知障碍(MCI)是老年性痴呆诊断的关键阶段,脑电(EEG)信号特征可以反映MCI患者的认知状态,帮助实现早期诊断。现有研究在EEG特征提取过程中,针对脑电各节律,大多采用固定的时间窗完成分段处理,忽略了不同节律的特征差异,从而影响诊断效果。针对该问题,本文提出了一种新的组合滑动窗优化算法,该算法通过迭代振幅调整傅里叶变换(IAAFT)对零模型的构建方法进行了改进,以此得到评估大脑动态特性指标KPLI,通过对EEG各频段信号采取多种滑动窗组合,并以KPLI指标引导,得到适合不同频段的最佳滑动窗组合。在最佳滑动窗组合基础上,对各频段组合提取相位滞后指数(PLI),进行连续小波变换(CWT)特征,通过ResNet-MLP双通道分类网络实现MCI诊断。结果显示,使用个性化组合频段滑动窗对88名受试者(32名MCI患者,36名阿尔茨海默症患者以及20名正常对照组)实现了诊断分类,得到了82.2%的分类准确率,比固定窗的分类提高了10%(得到了72.2%的分类准确率)。结果表明,基于个体化脑电节律特征组合能够更好提取MCI的特征,提高轻度认知障碍诊断的正确率与特异性,是一种有效的脑电特征提取方法。

川西高原机场对地区旅游业发展影响因素研究

航空运输业与旅游业是促进我国经济发展的重要产业,探究与分析机场对旅游业发展的要素对于促进航空运输业与旅游业的可持续发展和制定科学合理的旅游发展战略具有重要的意义。文章通过构建双对数模型对川西高原机场发展和旅游业发展状况展开研究,估计机场通航后各相关指标对旅游业发展的影响程度,并对部分机场进行滞后分析。结果显示,机场通航后各相关指标对地区旅游业发展的影响程度不同,且都显著促进当地旅游业的发展,同时通过滞后分析发现,各机场不同时期对不同地区旅游业发展的影响差别较大。

数字普惠金融的民生福祉效应:“红利”与“鸿沟”

数字普惠金融比传统金融具有更好的地理穿透性,为增进民生福祉,破解“胡焕庸线魔咒”提供了可能,但较少有文献对此进行系统研究。论文基于中国民生发展指数和数字普惠金融指数,利用空间统计与计量方法,从市级层面系统考察了数字普惠金融的民生福祉效应,并分析了以胡焕庸线为界的区域异质性特征。研究发现:数字普惠金融指数和民生福祉指数具有明显的空间分布异质性特点,呈现“高值向东南集聚、低值向西北集聚”的趋势。数字普惠金融与民生福祉皆存在显著的空间关联性,空间集聚特征明显且呈两极分化格局,胡焕庸线仍是两者的重要空间分界线;高-高集聚主要分布在胡焕庸线东南侧的沿海城市,低-低集聚主要分布在靠近胡焕庸线两侧的城市。数字普惠金融显著增进了民生福祉,发挥出“数字红利”的普惠作用;该作用在胡焕庸线东南侧城市显著高于西北侧城市,但两侧差距在缩小,这说明区域“鸿沟”在缩小,“胡焕庸线魔咒”有望破解。此外,研究还显示数字普惠金融的覆盖广度和使用深度是增进民生福祉的主要驱动力,而且后者的作用大于前者。因此,要加快西部地区数字基础设施与相关技术发展,提升胡焕庸线西北侧城市数字普惠金融的覆盖广度与使用深度,以增进区域民生福祉均衡性和可及性。

城市群集聚效应对高质量发展的影响——以山东半岛城市群为例

城市群的集聚尤其是生产性服务业与人才集聚能够优化产业空间布局与提升城市活力,深入分析生产性服务业和人才的集聚效应并探讨其影响与作用成为山东半岛城市群实现高质量发展的关键。文章以山东半岛城市群17个地级市为样本,构建2011—2018年面板数据,使用莫兰指数计算出山东半岛城市群17个地级市存在正向空间自相关性,再运用AcrGIS软件绘制山东半岛城市群生产性服务业与人才集聚态势演进表,最后通过构建空间滞后模型,分析山东半岛城市群生产性服务业与人才集聚对高质量发展的影响。研究发现:山东半岛城市群的生产性服务业与人才集聚存在负向溢出效应,本地区生产性服务业与人才集聚会抑制周边城市的经济高质量发展,“虹吸效应”大于“溢出效应”。根据研究结果提出的对策建议,可为山东半岛城市群高质量发展提供参考依据。

基于分布滞后非线性模型分析体感温度对乌鲁木齐市高血压住院数的影响

目的探讨体感温度与高血压患者住院数的关联性和滞后效应,并分析不同等级高血压与体感温度之间的影响差异。方法使用2019—2021年乌鲁木齐市10家医院高血压住院患者信息,从乌鲁木齐市气象局和环境监测站获取得到日均气压、环境温度、相对湿度、风速、日照时长、NO2、SO2、CO、O3、PM10、PM2.5数据。采用分布滞后非线性模型探讨体感温度和高血压患者住院数之间的暴露-滞后-效应关系。结果在日均体感温度与每日不同高血压住院数总暴露反应关系中,总高血压住院数、2级高血压住院数、3级高血压住院数与日均体感温度的暴露-反应曲线均呈非线性。极端日均体感低温(P5:-17.2℃)对每日总高血压住院数、3级高血压住院数的累积滞后效应会随着滞后天数的增加逐渐增强,并在累积滞后第14天时累积相对危险度(cumulative relative risk,CRR)达到最高,分别为2.025(95%CI:1.191~3.442)、2.171(95%CI:1.268~3.716)。在极端体感高温(P_(95):25.0℃)下,日均体感温度对每日总高血压住院数、2级高血压住院数和3级高血压住院数有影响,累积滞后影响分别在第2 d、第9 d和第2 d达到最强,CRR分别为0.72(95%CI:0.55~0.94)、0.57(95%CI:0.33~0.99)、0.69(95%CI:0.53~0.91)。结论体感温度与高血压患者住院数存在负效应关系,公共卫生部门可以根据预测的体感温度制定高血压预警,提示高血压易感人群在体感温度变化时注意防范,为降低高血压发病率提供新的防治思路。

降雨量与脑卒中入院的关联性:基于分布滞后非线性模型

背景脑卒中是严重危害人类健康的主要慢性病,降雨量与脑卒中发病的关系尚未明确。目的分析南昌市降雨量与脑卒中入院的关联性,为制定脑卒中综合防治策略和措施提供科学依据。方法收集江西省卫生健康委员会信息中心DRGs管理系统中南昌市2015—2019年脑卒中入院数据及全国城市空气质量实时发布平台大气污染物和南昌市气象基站数据,分析脑卒中入院患者、大气污染物及气象因素的基本特征。采用Spearman秩相关分析探究脑卒中入院例数与大气污染物和气象因素的相关性,利用分布滞后非线性模型分析降雨量与脑卒中入院的关系,并按照性别、年龄(<65岁和≥65岁)进行分层分析,lag代表滞后天数。结果2015—2019年南昌市脑卒中入院患者79523例,其中男性(49072例,61.71%)、年龄≥65岁(48092例,60.48%)的患者所占比例较大,冬(12月~次年2月)、春(3~5月)季脑卒中入院例数分别为20065例(25.23%)、20358例(25.60%)。降雨量与脑卒中入院呈非线性关系,并存在一定的滞后效应。降雨量对脑卒中入院的效应在lag1、lag2的RR值均为1.009,95%CI分别为1.000~1.019、1.001~1.016。分层分析显示:较高降雨量对男性脑卒中入院例数的主要效应为lag6,RR值为1.003;对女性脑卒中入院例数的主要效应为lag1和lag2,RR值分别为1.018(95%CI=1.004~1.031)、1.020(95%CI=1.009~1.031);对65岁以下缺血性脑卒中入院例数的主要效应为lag1(RR=1.016,95%CI=1.003~1.030)、lag2(RR=1.018,95%CI=1.007~1.029)。结论短期暴露于较高降雨量可增加脑卒中入院风险,女性、65岁以下人群对降雨暴露更为敏感,应加强对该人群的防护。

基于剪滞理论的纤维应力分布分析

探讨拉压过程中纤维与基体之间的应力,利用弹性力学基本理论,根据Cox剪滞模型,推导轴向力和剪切力理论数学公式。在推导过程中,将径向力考虑在内,同时纤维与基体间的应力传递过程需要通过剪切应力来实现,最终求解轴向力,对轴向力和剪切力的分布作图并进行详细分析。最终发现径向力存在的情况下,最大剪应力有所降低,降低幅度达5.25%,最大轴向力有所提升,提升幅度达3.76%。同时,在拉伸过程中发现纤维两端出现了最大剪应力,而最大轴向力出现在纤维中心处。

昼夜温差对乌鲁木齐市慢性肾脏病日住院人次影响的时间序列分析

目的探讨昼夜温差(diurnal temperature range,DTR)影响慢性肾脏病(chronic kidney diseases,CKD)日住院人次的影响。方法收集2019年1月1日至2020年12月31日乌鲁木齐市4所三甲医院、4所二甲医院、1所一甲医院CKD日住院人次数据,同期气象及污染物数据来自于乌鲁木齐市主城区的6个国控监测点,采用分布滞后非线性模型,控制星期几效应、假期效应、长期时间趋势及其它因素,分析DTR与CKD日住院人次的关系。结果CKD日住院人次与DTR(滞后0~21 d)的暴露-反应曲线呈“N”形,CKD患者住院风险随DTR的升高呈先上升后下降趋势。低度和高度DTR对CKD患者住院的影响存在一定的滞后效应,中度DTR对住院影响较小;DTR=5℃时,单日效应出现在第3天[RR=1.081,95%CI(1.020,1.145),P<0.05],最大效应出现在第21天[RR=1.090,95%CI(1.014,1.173),P<0.05];高度DTR=14℃(P_(95))时,单日效应出现在第4天[RR=1.086,95%CI(1.007,1.172),P<0.05],最大效应出现在第5天[RR=1.089,95%CI(1.009,1.176),P<0.05],累积滞后均暂未发现有统计学差异。男性和年龄<65岁的CKD患者更易受到DTR的影响,寒冷季节和四季更替时DTR变化对CKD患者住院的影响更大。结论男性与<65岁CKD患者更易受到DTR的影响,在寒冷季节和四季交替DTR变化时更应重点保护易感人群免受DTR的影响。

留守初中生抑郁症状对非自杀性自伤行为影响的纵向研究

目的 评估留守初中生抑郁症状与非自杀性自伤行为变化趋势,探讨二者发展关系及时序效应。方法 通过多阶段分层整群随机抽样,使用儿童抑郁量表(CDS)和青少年非自杀性自伤评定问卷(ANSAQ),对372名留守初中生进行为期1年的3次纵向调查。结果 留守初中生抑郁症状和非自杀性自伤行为呈线性增长。抑郁初始水平正向预测非自杀性自伤初始水平与增长速率(β=0.473,β=0.577;P<0.01),抑郁增长速率正向预测非自杀性自伤增长速率(β=0.806,P<0.001);交叉滞后回归分析显示:Tn抑郁可正向预测Tn+1非自杀性自伤行为(β=0.365,β=0.322;P<0.001),Tn非自杀性自伤行为不能预测Tn+1抑郁(β=0.117,β=0.094;P>0.05)。结论 留守初中生抑郁症状和非自杀性自伤行为随时间不断增长,抑郁症状是非自杀性自伤的前因变量,抑郁症状可预测非自杀性自伤发生。

盐城市气温与居民死亡关联分析:基于分布滞后非线性模型

目的研究温度对盐城市居民死亡的健康效应。方法分别从当地疾控部门、气象局和环境监测中心收集2015—2019年盐城市居民逐日死亡数据(非意外总死亡、呼吸系统疾病和循环系统疾病)、气象和空气污染数据。通过建立分布滞后非线性模型,评价气温与居民死亡关联。结果气温与居民非意外总死亡、呼吸系统疾病死亡和循环系统疾病死亡的关联呈“U”型。极端低温与居民非意外总死亡、呼吸系统疾病死亡和循环系统疾病死亡的关联呈现滞后性,相对危险度(RR)在暴露第3天达到最大,分别为1.03(95%CI:1.02~1.04)、1.06(95%CI:1.04~1.09)和1.02(95%CI:1.00~1.04);极端高温与居民非意外总死亡、呼吸系统疾病死亡和循环系统疾病死亡的关联呈现急性效应,RR在暴露当天健康效应最大,分别为1.19(95%CI:1.14~1.24)、1.20(95%CI:1.10~1.30)和1.25(95%CI:1.17~1.33)。极端低温对非意外总死亡、呼吸系统疾病死亡和循环系统疾病死亡的累计健康效应RR值均在14天后达到最大;极端高温对非意外总死亡、呼吸系统疾病死亡和循环系统疾病死亡的累计健康效应分别在暴露3、7和7天后达到最大。男性死亡风险在极端低温时高于女性,在极端高温时低于女性;≥65岁人群在极端高温时的非意外总死亡和循环系统疾病死亡风险高于<65岁人群。结论非适宜温度会增加盐城市居民的死亡健康风险,且低温滞后效应的持续时间比高温长。