Modelling home advantage for individual teams in UEFA Champions League football

Background:Home advantage(HA) is well documented in a wide range of team sports including association football(soccer).Although much attention has been paid to differences in the overall magnitude of HA between football competitions and across time,few studies have investigated HA at the team level.Methods:A novel method of estimating HA for individual teams,based solely on home performance,was used to compare HA between the highest performing teams and countries in the Union of European Football Associations(UEFA) Champions League over a 10-year period(2003/2004 to 2012/2013).Away disadvantage(AD) was also estimated based on each team's performance away from home.Poisson regression analysis was used to estimate covariate adjusted HA and AD in terms of the percentage of goals scored at home(HA) and conceded away from home(AD).Results:When controlling for differences in team ability,HA did not vary significantly between the 13 selected teams.There was evidence(p < 0.1),however,of between-team variation in AD,ranging from 45%(away advantage) to 68%(away disadvantage).When teams were grouped into the 11 selected countries,both HA and AD varied significantly(p < 0.02) between countries:HA ranged from 52% for Turkish teams to 70%for English teams,while AD ranged from 52%(France) to 67%(Turkey).Conclusion:Differences in style of play and tactical approaches to home and away matches may explain some of the variation in HA and AD between teams from different countries.

A succession and silviculture model for the broad-leaved Korean pine forests of Changbai Mountain Area

A succession and silviculture model (ZELIG.CBA) for broad-leaved Korean pine forest of Changbai Moutain Area was developed based on the framework of ZELIG model and characteristics of Broad-leaved Korean pine forests of Changbai area. ZELIG.CBA model consists four sub-models: growth model simulating annual increment of individual tree in forest, regeneration model simulating annual establishment of different tree species, mortality model simulating annual agerelated and stress-related morality; and silviculture model simulating the forest response to different silviculture scenario. The validation of the ZELIG.CBA showed that the accuracy of the model for the forest growth was more than 95%. The succession from clear cutting site simulating showed that the ZELIG.CBA model was stable for long term simulation. And selective cutting experiment showed that the optimal scenario for broad-leaved Korean pine forests was removal volume 30% combining with 30a rotation.

Acceptance Process Model of Patients’ Life with Terminally Ill in Home Hospice and Development of a Narrative Approach for Nurses

The prime aim of this study was to find a psychological process model of patients with terminally ill in home hospice investigating the contents of a narrative, and the secondary aim was to create a narrative approach program for nurses. Ten patients narrated their thinking or feelings along with some prepared questions in two sessions. Patients’ narrative data were categorized by a qualitative analysis and 34 categories were chosen. They perceived good points in home hospice like “Being able to spend time freely”, “Close relationships with care staffs and strong confidence”, though they perceived trouble points like “Suffering from putting burden on the people around me” or “Worries about economic problems”. They perceived psychological changes through illness like “Having peace of mind and becoming kind” “Desire for a natural death”. Moreover they perceived their life like “Acceptance of one’s life including illness” “My life lived with satisfaction”. They regarded as important things such as “Spending life time usefully” “Feelings of my family members and of those around me”, and as hopes “Hope to leave my living proof” “Living left time to the fullest”. From these categories, we propose an acceptance model of patients’ life and a narrative program for nurses.

Seasonal Prediction of Tropical Cyclones and Storms over the Southwestern Indian Ocean Region Using the Generalized Linear Models

Tropical cyclones (TCs) and storms (TSs) are among the devastating events in the world and southwestern Indian Ocean (SWIO) in particular. The seasonal forecasting TCs and TSs for December to March (DJFM) and November to May (NM) over SWIO were conducted. Dynamic parameters including vertical wind shear, mean zonal steering wind and vorticity at 850 mb were derived from NOAA (NCEP-NCAR) reanalysis 1 wind fields. Thermodynamic parameters including monthly and daily mean Sea Surface Temperature (SST), Outgoing Longwave Radiation (OLR) and equatorial Standard Oscillation Index (SOI) were used. Three types of Poison regression models (i.e. dynamic, thermodynamic and combined models) were developed and validated using the Leave One Out Cross Validation (LOOCV). Moreover, 2 × 2 square matrix contingency tables for model verification were used. The results revealed that, the observed and cross validated DJFM and NM TCs and TSs strongly correlated with each other (p ≤ 0.02) for all model types, with correlations (r) ranging from 0.62 - 0.86 for TCs and 0.52 - 0.87 for TSs, indicating great association between these variables. Assessment of the model skill for all model types of DJFM and NM TCs and TSs frequency revealed high skill scores ranging from 38% - 70% for TCs and 26% - 72% for TSs frequency, respectively. Moreover, results indicated that the dynamic and combined models had higher skill scores than the thermodynamic models. The DJFM and NM selected predictors explained the TCs and TSs variability by the range of 0.45 - 0.65 and 0.37 - 0.66, respectively. However, verification analysis revealed that all models were adequate for predicting the seasonal TCs and TSs, with high bias values ranging from 0.85 - 0.94. Conclusively, the study calls for more studies in TCs and TSs frequency and strengths for enhancing the performance of the March to May (MAM) and December to October (OND) seasonal rainfalls in the East African (EA) and Tanzania in particular.

Research of Home Information Technology Adoption Model

The Information Technology at Home has caught the attention of various industries such as IT,Home Appliances,Communication,and Real Estate.Based on the information technology acceptance theories and family consumption behaviors theories,this study summarized and analyzed four key belief variables i.e.Perceived Value,Perceived Risk,Perceived Cost and Perceived Ease of Use,which influence the acceptance of home information technology.The study also summaries three groups of external variables.They are social,industrial,and family influence factors.The social influence factors include Subjective Norm;the industry factors include the Unification of Home Information Technological Standards,the Perfection of Home Information Industry Value Chain,and the Competitiveness of Home Information Industry;and the family factors include Family Income,Family Life Cycle and Family Educational Level.The study discusses the relationship among these external variables and cognitive variables.The study provides Home Information Technology Acceptance Model based on the Technology Acceptance Model and the characteristics of home information technology consumption.

基于KJ-KANO模型的亲子家居文创产品设计研究

以亲子用户群体需求为设计导向,综合使用KJ-KANO模型对亲子家居文创产品进行研究与设计,打破亲子沟通障碍的桎梏,营造和谐有爱的亲子氛围。首先运用KJ法获取亲子对于家居文创产品的相关需求,梳理出需求清单;其次运用KANO模型甄别亲子需求的属性以及对需求进行优先级排序。在此基础上,进行亲子家居文创产品设计实践。通过综合运用KJ-KANO模型精准获取用户需求,从而避免设计人员的主观臆断,为设计实践提供合理的设计要素,从而提升亲子群体对于家居文创产品的满意度和幸福体验指数。

基于RGB模型的草莓叶片光合作用指标估测

为了研究基于图像红(R)、绿(G)、蓝(B)颜色参数和叶片SPAD值预测光合作用指标的可行性,以草莓叶片为试验材料,构建多元线性回归模型和反向传播(BP)神经网络模型,对叶片蒸腾速率、气孔导度、净光合速率、胞间CO_(2)浓度进行估测,并对其精度进行评价和验证。结果表明,基于BP神经网络模型,使用图像RGB颜色参数和SPAD值对叶片蒸腾速率进行预测的效果较好,其次是气孔导度。BP神经网络模型的估测精度高于多元线性回归模型,蒸腾速率、气孔导度、净光合速率和胞间CO_(2)浓度的模型预测准确率分别达到91.5%、83.3%、74.4%和71.5%。BP神经网络的蒸腾速率模型、气孔导度模型的决定系数(R2)分别为0.9222、0.8423,均方根误差(RMSE)分别为0.0002、0.0259,平均绝对误差(MAE)分别为0.0001、0.0006。由结果可知,通过数码相机采集图像,并构建RGB模型,可简易快速估测草莓叶片蒸腾速率、气孔导度,能用于生产中草莓光合指标的估测。

我国居家社区养老服务设施利用状况分析与建设措施优化

党的十九大以来,各级政府投入大量资源用于提高居家社区养老服务设施覆盖率。目前,已建成的设施利用状况不容乐观。本文在界定居家社区养老服务、机构、设施内涵及相互关系的基础上,参考安德森模型,构建了居家社区养老服务设施利用分析框架。通过对17个社区调查资料的描述性统计,发现已建成的居家社区养老服务设施尚未得到有效利用。运用二元Logistic回归分析,得出设施利用状况堪忧的主要原因:设施建设不符应老年人的多样化需要;老年人广义支付能力不足约束对设施的利用;设施供给结构不能激发老年人的支付意愿。建议进一步规范居家社区养老相关术语,更加明确居家养老的社区责任边界,充分发挥市场满足多样化养老需求的作用。

基于可调场景语义标注范围的家庭室内语义地图构建

针对家庭室内环境语义地图建图速度较慢和在门口场景语义标注易出现错误等问题,提出一种基于可调场景语义标注范围的家庭室内语义地图构建方法。首先根据YOLOv5s识别的物体大小赋予相应的场景置信度,基于该场景置信度设置阈值使得语义标注范围限制在机器人当前所在区域,确保场景切换时语义标注范围不会立即改变。然后基于人工势场虚拟力“引力斥力”原理,实现语义标注范围的扩大或缩小。最后结合阈值和动态语义标注范围,避免在门口场景中出现语义标注错误。实验结果表明:与Places205-VGG16神经网络建立家庭室内语义地图相比,所提方法平均效率和平均精准率分别提升了11.0%和7.8%,在家庭室内环境中具有一定的优越性。

“关怀-照护”理论、老年照护体系和照护型社会

本文讨论了关于老年照护的三个关键性问题,这三个问题分别对应“照护”的理论背景、现实需要和未来发展。其一,“关怀-照护”理论,是一个围绕英文名词“Care”演绎而成的理论体系,涉及关怀伦理学、照护人类学等,本文用一个三角形图示来阐明以这个理论为基础的老年照护体系中的功能耦合和互动;其二,以上述理论为基础,本文认为居家照护既是中国老年人的刚性需要,也是整个老年照护体系的基础;其三,本文从人工智能的发展及其对未来社会的影响来讨论老年照护体系和居家照护如何适应这一发展趋势,同时对老年照护体系的发展前景提出了较为详细的政策创意和方案设计。

远程办公背景下工作不可预测性对工作与家庭冲突的影响——一个有调节的中介模型

远程办公已成为数字化工作实践的常态,ICT技术使用过程中和工作与家庭生活相关的负面影响越来越受到信息系统领域学者们的重视。本研究运用工作家庭资源理论模型,探究员工在远程办公情境下适应数字技术以及体验工作形式和工作方式转变的过程中感知到的新型工作压力,并阐释其损害员工家庭领域繁荣的具体路径。问卷调查结果表明,远程办公情境下的工作不可预测性导致员工心理弹性的应对资源减少,造成了工作与家庭冲突,而自尊可以有效地帮助员工缓解工作压力和恢复个人资源。实证结果为远程办公如何影响员工的工作体验以及工作与家庭关系提供了新的见解和启示。

基于卡诺模型的城市居民居家社区养老服务需求分析

《“十四五”国家老龄事业发展和养老服务体系规划》明确了“十四五”期间养老服务体系建设目标。准确了解居家社区养老人员服务需求,可以更精准地实现规划目标。首先设计城市居民居家社区养老服务需求指标体系和卡诺问卷,以江门市10个社区居家养老人员为调查对象,收集有效问卷249份。其次运用卡诺模型对问卷数据进行需求属性频数统计、Better-Worse矩阵分析、需求指标敏感性分析,得到魅力属性、期望属性、必备属性和无差异属性分类结果。最后提出总体需求改善策略和针对4类需求属性的需求改善策略,以及4类需求属性和各需求属性中需求指标的优先改善次序。

“互联网+养老”实施背景下济南市虚拟养老院建设的需求及对策

为明确“互联网+养老”背景下济南市社区居民虚拟养老院的服务需求现状,为虚拟养老院的建设提供对策建议,基于Kano模型理论,通过问卷调查法对城市社区老年人进行调查,采用满意度排序与分析形成虚拟养老需求的优先级模型,最后提出针对性的建议,对城市社区虚拟养老院的发展与建设有积极的意义。

以银发经济推进农村互助养老发展的政策支持研究——以J省X市颐养之家为例

我国首部“银发经济”政策文件出台,为农村互助养老模式提供了“有为政府”与“有效市场”相结合的实践场域。通过对具有全国性影响的J省X市颐养之家的典型案例分析发现,当前农村互助养老模式的主要政策目标是为有需要的农村留守、独居及困难老年人提供基本生活保障的兜底型养老。在银发经济“产品化-商品化-产业化”阶段性发展的大趋势下,农村互助养老还可以是普惠式养老,更应该是高质量的积极养老。针对农村互助养老模式在政策执行中分配基础、分配内容、输送策略、筹资机制等方面存在的不足,建议将发挥有效市场作用与有为政府作用更好结合,进一步完善优化政策支持,纳入“一老一小”,扩展受益对象;引进商品化竞争机制,丰富服务供给;推动多主体跨部门合作,形成网状输送;划定红线并链接资源,发展团结经济,着力推动农村互助养老高质量发展。

一种BIM家居场景模型纹理真实性还原方法

针对现有的BIM建模软件与建模方法制作出的模型纹理材质过于单一且真实感不足,不能很好地满足不同用户的实际需求等问题,本文提出了一种BIM家居场景模型纹理真实性还原方法。首先,根据家居场景中常见家具种类建立图像数据集;其次,采用神经网络算法获取到图像的纹理特征信息,得到相似的真实家具图像,并通过最小框图裁剪并合成对应的BIM家居场景中不同家具模型的材质贴图;最后反馈到建模软件实现BIM家居场景模型纹理真实性的还原。实验结果表明,经本文方法处理后的BIM家居场景模型能够较为真实的还原现实场景。

应用地基激光雷达三维点云数据构建长白落叶松树干削度方程

使用地基激光雷达(TLS)三维点云数据提取的落叶松干形数据,构建树干削度方程,为落叶松干形精准预测提供依据。以吉林省一面山林场和杨木林林场落叶松人工林为研究对象,获取71株落叶松点云信息,并提取树干干形数据。选择简单、可变指数、三角函数和分段函数等9个基础削度方程进行比较,利用分位数回归和广义加性模型方法构建削度方程。结果表明:在9个基础削度方程中,Bi(2000)削度方程的拟合效果最好,多重共线性指标条件数也小于100;Bi(2000)基础削度方程构建的分位数回归模型,在9个分位点(τ=0.1、0.2、0.3、0.4、0.5、0.6、0.7、0.8、0.9)处均能收敛,其中在τ=0.5的分位点处的拟合效果最好,略优于非线性回归的拟合结果。在以相对直径为因变量,以相对高的平方根、胸径的平方和树高为自变量的广义加性削度方程中,6种光滑样条函数(三次回归样条函数(CR)、B-样条函数(BS)、薄板回归样条函数(TP)、P-样条函数(PS)、Duchon样条函数(DS)和高斯过程平滑样条函数(GP))的拟合效果相差不大,但广义加性削度方程使用(DS+CR)光滑样条函数比一种光滑样条函数的拟合效果好(相对误差4.407、均方根误差1.158、确定系数0.966),广义加性削度方程的各检验统计量均优于基础削度方程和分位数回归削度方程,且在树干相对高度10%~80%,广义加性削度方程也表现最优(相对误差4.534、均方根误差1.191、确定系数0.964)。因此,(DS+CR)组合光滑样条函数的广义加性削度方程预测精度最高,可用于该区域的落叶松干形预测。

基于SFIC模型的养老事业与养老产业协同发展路径研究

养老事业与养老产业同属于养老服务体系的组成部分,充分发挥其作用重在二者协同发展,即二者相互协作实现养老服务的充分供给且达到二者共同发展的双赢效果。通过创新性地将SFIC模型用于养老服务体系发展分析,构建养老事业与养老产业协同发展分析框架,从星光老年之家、公建民营养老机构、政府购买养老服务、长期护理保险制度试点四个案例比较剖析养老事业与养老产业协同的起始条件、助成性领导、制度设计、合作程序,提出改善养老事业与养老产业协同发展的起始条件、发挥助成性领导对养老事业与养老产业协同发展的创造性作用、优化养老事业与养老产业协同发展的制度设计、在养老事业与养老产业协同发展中实现良性合作四个养老事业与养老产业协同发展的路径。

基于PMC指数模型的农民工返乡创业政策量化评价

农民工返乡创业对于推进乡村振兴,实现共同富裕具有重要意义。结合农民工返乡创业政策文本特点以及文本高频词,采用PMC指数模型,构建包括10个一级指标、38个二级指标的农民工返乡创业政策评价指标体系,对农民工返乡创业政策进行量化评价,并绘制PMC曲线图。研究发现,农民工返乡创业政策样本总体得分优秀,设计较为科学合理,其中2份为完美政策,7份为优秀政策,1份为可接受政策,但政策时效、激励措施还有待完善。

初烤烟叶主脉与叶片的吸附等温线及其热力学性质研究

为探究初烤烟叶主脉与叶片在吸湿过程中所表现出的水分吸附特性,测定初烤烟叶主脉与叶片在环境温度20、25、30、35、40℃以及环境相对湿度50%、60%、70%、80%、90%下的吸湿情况,绘制初烤烟叶主脉与叶片的吸附等温线,采用5种常用的农产品吸附等温线模型对试验数据进行拟合,并在此基础上探究初烤烟叶主脉与叶片的热力学性质。结果表明,初烤烟叶主脉与叶片的吸附等温线属于Ⅲ型等温线,在环境相对湿度相同的条件下,初烤烟叶主脉与叶片的平衡含水率随环境温度的升高而降低。MHAE模型是描述初烤烟叶主脉与叶片吸附等温线的最佳模型,决定系数(R^(2))为0.99877~0.99905,平均相对百分率误差(MRE)为1.45515%~2.94968%。热力学性质研究结果表明,在平衡含水率发生变化时,初烤烟叶主脉与叶片的净等量吸附热(Q_(st))与微分吸附熵(ΔS)有相似的变化趋势,均随平衡含水率的升高而下降,且两者与温度之间都没有明显关系。在初烤烟叶主脉与叶片的水分吸附过程中,熵-焓补偿理论也同样存在并适用,并且水分吸附过程是自发的由焓所驱动的反应。综上,初烤烟叶主脉与叶片在水分吸附过程中的热力学性质较为相似,MHAE模型适合用来描述初烤烟叶主脉与叶片在温度20~40℃的吸附等温线。

农作物生长的胁迫因素光谱甄别模型研究

玉米作为中国重要的粮食产物之一,其生长期间的健康检测一直是农业生产的重要问题。以受不同因素影响下生长的玉米叶片为研究对象,采用ASD光谱仪进行叶片光谱采集;对原始光谱数据进行导数(derivative,D)处理,针对经过求导后光谱部分数据无限趋向0的现象,引入压缩感知(compressed sensing,CS)方法,并采用迭代重加权最小二乘(iterative re-weighted least squares,IRLS)数据重建的方法对光谱数据进行恢复;然后选取竞争性自适应重加权算法(competitive adapative reweighted sampling,CARS),结合不同试验下的影响因素作为标签提取光谱特征;最后通过多层感知机分类模型(multi-layer perceptron,MLP),以达到判别生长状态不佳的农作物所受影响因素的目的。本次试验生成的D-CS-CARS-MLP模型的精度相较于传统模型精度有所提高,可以高达99%以上,可以看出该模型可以针对农作物生长状态不佳所受的影响因素进行判别。经过验证,D-CS-CARS-MLP模型具有较好的稳定性和精度,为植被健康生长监测提供了新的思路与方法。