Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence

Relationship between sea level change and a single climate indicator has been widely discussed.However,few studies focused on the relationship between monthly mean sea level(MMSL)and several key impact factors,including CO_(2) concentration,sea ice area,and sunspots,on various time scales.In addition,research on the independent relationship between climate factors and sea level on various time scales is lacking,especially when the dependence of climate factors on Nino 3.4 is excluded.Based on this,we use wavelet coherence(WC)and partial wavelet coherence(PWC)to establish a relationship between MMSL and its influencing factors.The WC results show that the influence of climate indices on MMSL has strong regional characteristics.The significant correlation between Southern Hemisphere sea ice area and MMSL is opposite to that between Northern Hemisphere sea ice area and MMSL.The PWC results show that after removing the influence of Nino 3.4,the significant coherent regions of the Pacific Decadal Oscillation(PDO),Dipole Mode Index(DMI),Atlantic Multidecadal Oscillation(AMO),and Southern Oscillation Index(SOI)decrease to varying degrees on different time scales in different regions,demonstrating the influence of Nino 3.4.Our work emphasizes the interrelationship and independent relationship between MMSL and its influencing factors on various time scales and the use of PWC and WC to describe this relationship.The study has an important reference significance for selecting the best predictors of sea level change or climate systems.

Analysis of the Main Factors Influencing Food Production in China Based on Time Series Trend Chart

Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effective irrigation area,the affected area,total machinery power,food production cost index,food production price index,financial funds for supporting agriculture,farmers and countryside),and put them into categories of material input,resources and environment,and policy factors. Using the factor analysis,we carry out the multi-angle analysis of these typical influencing factors one by one through the time series trend chart. It is found that application rate of chemical fertilizer,the growing area of food crops and drought-affected area become the key factors affecting food production. On this basis,we set forth the corresponding recommendations for improving the comprehensive food production capacity.

Factors Influencing Migrant Workers' Urban Labor Patterns: Willing Working Time in Urban Areas as the Mediator

China is witnessing a very complicated economic development environment.Migrant workers'working patterns will directly affect their income level and the realization of many economic and social development goals.This paper collects relevant data from three places:Shanghai,Lanzhou and Chengdu for empirical research whose results show that determinants of migrant worker's willing working time in urban areas mainly include the“income-consumption difference”,“urban-rural consumption difference”and their“urban income and expenditure uncertainty”.These factors directly affect their effective working time in the city,and determine their choice of choosing corresponding work patterns.From the significant differences of these factors,we can see that migrant workers in China is still struggling to solve their material needs under the pressure of livelihood,and less attention is paid to their spiritual needs and the pursuit of quality of life.

Coupling effects of influence factors on probability of corrosion initiation time of reinforced concrete

The coupling model of major influence factors such state affecting the chloride diffusion process in concrete is as environmental relative humidity, load-induced crack and stress discussed. The probability distributions of the critical chloride concentration Cc, the chloride diffusion coefficient D, and the surface chloride concentration Cs were determined based on the collected natural exposure data. And the estimation of probability of corrosion initiation considering the coupling effects of influence factors is presented. It is found that the relative humidity and curing time are the most effective factors affecting the probability of corrosion initiation before and after 10 years of exposure time. At the same exposure time, the influence of load-induced crack and stress state on the probability of corrosion initiation is obvious, in which the effect of crack is the most one

Spatial-temporal Characteristics and Factors Influencing Commuting Activities of Middle-class Residents in Guangzhou City, China

The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.

Electricity Price Influence Factors Analysis Using Stochastic Matrix for Real-Time Electricity Price Forecasting

Real-time electricity price( RTEP) influence factor extraction is essential to forecasting accurate power system electricity prices. At present,new electricity price forecasting models have been studied to improve predictive accuracy,ignoring the extraction and analysis of RTEP influence factors. In this study,a correlation analysis method is proposed based on stochastic matrix theory.Firstly, an augmented matrix is formulated, including RTEP influence factor data and RTEP state data. Secondly, data correlation analysis results are obtained given the statistical characteristics of source data based on stochastic matrix theory.Mean spectral radius( MSR) is used as the measure of correlativity.Finally,the proposed method is evaluated in New England electricity markets and compared with the BP neural network forecasting method. Experimental results show that the extracted index system comprehensively generalizes RTEP influence factors,which play a significant role in improving RTEP forecasting accuracy.

Short-term inbound rail transit passenger flow prediction based on BILSTM model and influence factor analysis

Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.

Impact of Operative and Peri-operative Factors on the Long-term Prognosis of Primary Liver Cancer Patients Undergoing Hepatectomy

This study examined the impact of the operative and peri-operative factors on the long-term prognosis of patients with primary liver cancer undergoing hepatectomy. A total of 222 patients with primary liver cancer who underwent hepatectomy were followed up from January 1986 to December 2010 at Chinese PLA General Hospital. The post-operative complication rate was 14.0% for all cases, 13.7% for hepatocellular carcinoma（HCC）, 10.0% for cholangiocarcinoma. The 1-, 3-, 5- and 10-year overall survival rates in patients with primary liver cancer after resection were 76.6%, 57.6%, 41.4%, and 21.0%. The survival rates were significantly higher in the HCC group than in the cholangiocarcinoma group（P=0.000）, in the non-anatomical resection group than in the anatomical resection group（P=0.005）, in the female group than in the male group（P=0.002）, in patients receiving no blood transfusion than in those who were given intra-operative blood transfusion（P=0.000）, in patients whose intra-operative blood loss was less than 400 m L than in those who intra-operatively lost more than 400 m L（P=0.000）. No significant difference was found in the survival rate between the HBs Ag-positive group and the HBs Ag-negative group（P=0.532）. Our study showed that anatomical resection, blood loss and blood transfusion were predictors of poor survival after hepatectomy for primary liver cancer patients, and concomitant hepatitis B virus infection bore no relation with the post-resection survival.

Optimization of shut-in time based on saturation rebalancing in volume-fractured tight oil reservoirs

Based on imbibition replacement of shut-in well in tight oil reservoirs, this paper expounds the principle of saturation rebalancing during the shut-in process after fracturing, establishes an optimization method for shut-in time after horizontal well volume fracturing with the goal of shortening oil breakthrough time and achieving rapid oil breakthrough, and analyzes the influences of permeability, porosity, fracture half-length and fracturing fluid volume on the shut-in time. The oil and water imbibition displacement in the matrix and fractures occurs during the shut-in process of wells after fracturing. If the shut-in time is too short, the oil-water displacement is not sufficient, and the oil breakthrough time is long after the well is put into production. If the shut-in time is too long, the oil and water displacement is sufficient, but the energy dissipation in the formation near the bottom of the well is severe, and the flowing period is short and the production is low after the well is put into production. A rational shut-in time can help shorten the oil breakthrough time, extend the flowing period and increase the production of the well. The rational shut-in time is influenced by factors such as permeability, porosity, fracture half-length and fracturing fluid volume. The shortest and longest shut-in times are negatively correlated with porosity, permeability, and fracture half-length, and positively correlated with fracturing fluid volume. The pilot test in tight oil horizontal wells in the Songliao Basin, NE China, has confirmed that the proposed optimization method can effectively improve the development effect of horizontal well volume fracturing.

变化环境下渭河流域土壤水储量模拟及影响因素

[目的]随着气候变化和人类活动影响加剧,流域气候和下垫面条件发生改变,为准确模拟土壤水分变化过程并分析其影响因素对于地区的水资源管理和植被建设的重要意义。[方法]以黄土高原地区渭河流域为研究对象,基于ABCD水文模型,采用EFAST法分析模型参数敏感性,构建常参数和时变参数模型,比较不同参数模型的径流深和土壤水储量模拟精度,探讨气候变化和植被恢复对渭河流域土壤水储量变化的影响,明确土壤水储量变化的主导因素。[结果]土壤水层补给地下水的比例参数c最为敏感,地下水储放系数d、流域实际蒸散发量与土壤蓄水量之和的上限参数b次之,表征土壤完全饱和前径流的倾向性参数a最不敏感;与ABCD常参数模型相比,时变参数模型将率定期径流深模拟结果的NSE、KGE、R^(2)分别提高19%,10%,19%,验证期的NSE、KGE、R^(2)分别提高7%,7%,9%,时变参数模型显著改善径流深模拟效果;基于时变参数模型模拟的渭河流域土壤水储量与ERA5-Land 0—100 cm土层土壤水储量的相关关系最强,二者的变化过程基本相同;不同影响因素对渭河流域土壤水储量变化的影响程度由强到弱依次为潜在蒸散发>降水>NDVI。[结论]研究成果为该地区水资源规划和管理、植被建设提供科学依据,也为其他类似地区的土壤水储量研究提供参考。

癌症病人时间感知的研究进展

对癌症病人时间感知的概念、转变特点、影响因素、干预措施等方面进行综述,指出国内关于癌症病人时间感知的研究较少,可借鉴国外相关研究的优点与不足,并进一步探索癌症病人时间感知影响因素,开展纵向前瞻性研究,以探讨其时间感知的纵向变化特征。

碳移除下全球地表气温峰值出现时间的主要影响因子:能量平衡模型研究

碳移除是21世纪末实现巴黎气候协定温度目标的关键手段。在其开展后,全球地表气温将在随后的若干年达峰。目前,耦合模式比较计划第六阶段(CMIP6)开展碳移除试验的数值模式较少,限制了科学界对碳移除下全球地表气温峰值出现时间的理解。本文发现,基于强迫—响应能量框架的两层能量平衡模型能够很好地重现出:1)大气CO_(2)浓度变化对全球地表气温的影响;2)碳移除过程中全球地表气温的峰值出现时间。因此,该模型可作为CMIP6碳移除试验的补充,能够胜任峰值出现时间的影响因子研究。该能量平衡模型的结果显示,在碳移除过程中,不考虑深层海洋的情况下,对全球平均地表气温的峰值出现时间影响最大的因子为平衡气候敏感度,其次为地表热容量;当深层海洋存在时,影响最大的因子为深层海洋热容量,其次为平衡气候敏感度,之后为地表热容量。这些因子主要通过改变碳移除开始时地表净能量收入的大小来影响全球地表气温峰值的出现时间。相比不考虑深层海洋的情况,深层海洋的存在可以略微提前全球温度峰值出现的时间,并使得碳移除后CO_(2)强迫对地表净能量的下降幅度的贡献较大。

多因素影响下的驾驶舱拨动开关反应时研究

针对飞行员操纵驾驶舱拨动开关的反应时问题,通过搭建飞行模拟实验舱,采集飞行员操纵驾驶舱拨动开关的反应时数据,应用多因素方差分析方法,研究在多因素影响下,影响飞行员反应时的因素。结果表明:驾驶舱拨动开关位于飞行员正前方左侧水平斜向下45°的面板,反应时最短;规定正确的操作开关方向为向前为正,相比方向为向后为正,飞行员的操纵反应时更短;高负荷因素下,飞行员反应时更长;有灯光引导条件下可以降低飞行员的反应时;面板位置、负荷处理、灯光引导3种因素主体之间的交互作用对飞行员操纵驾驶舱拨动开关的反应时的影响显著。通过实验研究与数据处理分析,结果客观真实,有助于提升飞行员的飞行安全水平,也为操纵器件设计问题提供了基础实验研究和建议。

页岩气老井重复压裂时机优化方法

基于多孔介质弹性理论、嵌入式离散裂缝模型及有限体积法,考虑页岩气微观渗流机制,建立适用于裂缝性页岩气储集层的渗流-地质力学全耦合模型,并提出了重复压裂时机优化方法,采用四川盆地涪陵页岩气井资料分析了重复压裂时机的影响因素。研究表明:受地层压力衰竭影响,最大水平主应力反转面积占总面积的百分比随时间的延长先增加后减小,且距人工裂缝越近的区域,应力反转面积百分比曲线出现峰值的时间越短,最终归零(恢复到初始状态)的时间也越短。重复压裂的最佳时间受基质渗透率、初始应力差、天然裂缝逼近角的影响:基质渗透率、初始应力差越大,应力反转面积百分比曲线出现峰值、恢复到初始状态的时间越短,采取重复压裂措施的时机越早。天然裂缝逼近角越大,裂缝附近越难发生应力反转、重复压裂最佳时间越早,人工裂缝末端以远区域越易发生应力反转、重复压裂最佳时间越晚。对于基质渗透率很小的储集层,其单井产能递减快,为保证经济性,可采取关井或注气补能等措施恢复应力,提前实施重复压裂。

HIV阳性MSM的社会行为及首次同性性行为到阳性时间的影响因素分析

目的了解艾滋病病毒(HIV)阳性男男性行为者(MSM)的社会行为特征,分析首次同性性行为到阳性时间的影响因素。方法收集2007—2022年绵阳市疾病预防控制中心新确证并实施首次流行病学调查的阳性MSM资料,阳性时间的影响因素分析采用χ^(2)检验和Logistics回归模型。结果共收集有效资料457份,自认性取向成因属先天因素63.95%、后天因素36.05%,首次同性性行为性伴来源互联网60.54%、朋友等39.46%。首次同性性行为年龄平均23.95岁,发生阶段为在校学生44.64%、工作后55.36%。53.75%使用过rush poppers。阳性时间平均5.25年。多因素分析结果,职业学生/商业服务/无业(OR=1.868)、首次同性性行为发生在在校学生阶段(OR=1.555)者阳性时间短的可能更大,婚姻状况在婚及其他(OR=0.566)、固定性伴数≥3人(OR=0.553)、偶遇性伴数≥5人(OR=0.457)者阳性时间短的可能更小。结论阳性MSM多自认其性取向属先天因素,首次同性性行为的性伴来源互联网、发生在工作后和使用新型毒品较为普遍。阳性时间与婚姻状况、首次同性性行为发生阶段及性伴数量相关联。要针对性强化健康教育和行为干预。

下肢静脉曲张术后延续性干预的效果及复发影响因素分析

目的探讨下肢静脉曲张术后延续性干预的效果及复发影响因素。方法选择2020年3月至2022年9月收治的下肢静脉曲张并行手术治疗的患者100例,随机分为观察组和对照组各50例,对照组行常规干预,观察组使用延续性干预,对比2组复发情况、凝血功能及生活质量。根据患者术后12个月是否复发分为复发组42例和未复发组58例,收集2组一般资料,应用多因素Logistic回归分析术后复发的影响因素。结果观察组术后6、9、12个月复发率低于对照组(P<0.05,P<0.01);观察组凝血酶时间、凝血酶原时间及活化部分凝血酶原时间均长于对照组(P<0.05);观察组躯体、心理、角色、社会四个维度评分均高于对照组(P<0.05)。年龄≥60岁、体质量指数、文化程度、静脉曲张年限、凝血功能以及延续性干预均是下肢静脉曲张术后复发的影响因素(P<0.05,P<0.01)。结论年龄、体质量指数、文化程度、静脉曲张年限及凝血功能是下肢静脉曲张术后复发影响因素,术后应用延续性干预能降低复发率,提高患者生活质量。

新入职护士时间管理倾向与临床实践行为的调查研究

目的探讨新入职护士时间管理倾向与临床实践行为的现状、相关性及影响因素。方法于2022年1月选取九江市的市级、县级5家医院的145名新入职护士作为调查对象,采用问卷调查的方式,对护士进行一般人口学特征6项,时间管理倾向量表3个维度及临床实践行为3个维度的调查,比较不同人口学特征护士的时间管理倾向、临床实践行为,采用Pearson检验分析护士时间管理倾向与临床实践行为的相关性,采用多元线性回归分析临床实践行为的影响因素。结果145名护士的时间管理倾向量表总分为(3.74±0.62)分,其中时间价值感、时间监控观、时间效能感得分较高。临床实践行为评分总分为(4.15±0.64)分,其中认知、情感、操作技能得分较高。不同学历、生源地、所在医院级别、是否担任班干部的护士时间管理倾向评分比较,不同学历、生源地、所在医院级别的护士临床实践行为评分比较,差异有统计学意义(P<0.05)。时间管理倾向量表3个维度评分及总分,与临床实践行为3个维度评分及总分呈正相关(P<0.05)。多元线性回归分析显示,护士的学历、生源地、医院级别、时间管理倾向3个维度评分及总分为临床实践行为的影响因素(P<0.05)。结论新入职护士时间管理倾向与临床实践行为处于较高水平,而且呈现正相关,其中生源地、市级医院、时间管理倾向为临床实践行为的影响因素,因此需加强时间管理技巧的培训,提高护士的临床实践行为,研究价值较高。

基于模块化思想的LCC-HVDC改进小信号建模及交互稳定性分析

随着电网换相型高压直流输电(line commutated converter based high voltage direct current, LCC-HVDC)技术的广泛应用,交直流混联电力系统的交互稳定性问题日益突出。首先基于状态空间平均法建立了考虑非线性换相重叠动态过程的LCC换流器传递函数模型。为适应愈加复杂的直流输电系统建模,提出利用模块化思想分别建立LCC-HVDC各子系统小信号模型,并推导了能反映交直流系统和换流器之间电气耦合特性的接口矩阵实现子系统连接,从而模块化建立精确且易于扩展的计及控制链路延时和锁相环输出相位波动的双端LCC-HVDC系统改进小信号模型。最后分析了控制系统参数和控制链路延时对系统小干扰稳定性的影响以及失稳模态的主导因素,揭示了双端LCC-HVDC系统交直流混合谐振机理及送受端交互影响具体过程。研究结果可以为系统参数设计、谐振抑制措施提供理论基础。

乐园游客排队最大接受时长影响因素研究——基于上海迪士尼乐园的实证研究

以ACSI模型为核心,结合ABC态度模型和归因理论等建立了概念模型,旨在探究游客排队最大接受时长的影响因素。将迪士尼乐园作为研究对象,对收集到的220份问卷进行统计分析结果发现,顾客期望维度的四个变量对排队最大接受时长均存在正向影响;游客排队时的感知质量中,游客对于园方排队管理的努力程度的感知以及游乐项目对于游客预期的个性化需求的满足程度对排队最大接受时长有正向影响,而排队的感知时长会对其产生负向影响;排队最大接受时长与顾客的抱怨/不满之间存在负向影响。研究结论为乐园优化游客排队体验,提升游客排队最大接受时长提供了一定的指导。

基于CiteSpace的公交停靠时间影响因素分析

为了降低公交停靠时的延误,以便于合理地进行公交站规划设计。通过利用CiteSpace对公交停靠时间领域文献进行研究。根据得到的图谱对当前的研究热点和以后的研究方向进行总结分析。结果表明,我国对公交停靠时间的研究可分为两个阶段,探索发展和钻研创新阶段,而近期研究热点偏向遗传算法和智能交通方向。精读文献后得出影响公交停靠时间的因素为乘客上下车时间和公交车加减速时间,同时结合站台形式这个特殊的影响因素进行了分类分析,为今后的公交停靠站设计提供参考。