Stature estimation using foot dimensions via 3D scanning in Taiwanese male adults

In forensic identification, the use of foot dimensions to predict stature is a requisite. For Taiwanese male stature prediction, available information about stature estimation using foot dimensions is still lacking. Therefore, the primary purpose of this study was to establish Taiwanese adult male stature prediction models for various foot dimensions. A total of 2,072 male 3D foot models were collected and the subjects' ages ranged from 18 to 59 years old. Thirteen foot dimensions for each foot were utilized in this study. Bilateral differences were tested using paired t-tests. Stature predictions based on different foot dimensions were conducted using simple linear and stepwise regression methods. The results showed significant bilateral differences in the majority of the selected foot dimensions (p < 0.001). Foot length had the highest positive correlation with stature in the right and left foot. Using length-related dimensions generated better prediction accuracy (0.356 < R² < 0.533, 4.193 < SEE < 4.928), whereas the worst accuracy was observed with angle-related dimensions (0.001 < R² < 0.023; 6.072 < SEE < 6.137) when employing a single foot dimension to estimate Taiwanese male stature. Stepwise regression analysis results indicated that the coefficient of determination was improved to 0.590 and 0.593 by applying five and six foot parameters to predict stature, respectively. The findings of the present study suggest that these stature estimation equations can be applied to predict Taiwanese male stature in the forensic science field.     

基于角膜图像的人体死亡时间推断模型初探

目的尸体角膜随死后时间延长发生的形态学变化是规律性较好的指标,常用来判断死亡时间(postmortem interval,PMI)。本文尝试用机器视觉代替人的肉眼主观判断,收集尸体样本以建立通过人体角膜图像推断PMI的模型。方法收集实际案例建立包含505例人体死后角膜图像的数据库,PMI范围为0.24h(约死后14min)至492h(约死后20.5d),大致分为三类(依次为:0~<6h、6~<20h、20h及以上)或二类(0~<15h、15h及以上);使用由华盛顿大学陈天奇博士提出的Xgboost模型分别进行二分类与三分类分析;使用多种卷积神经网络模型分别进行分类和回归学习,并通过比较最终选择了由微软研究院提出的ResNet模型进行分析。结果Xgboost在三分类时预测准确率依次为71.8%、40.7%、65.7%,二分类时为90%、48.5%。ResNet分类模型中,精准率、召回率在三分类时分别依次为:81%、75%,30%、50%,61%、71%,二分类时为:70%、92%,76%、38%。ResNet回归模型中,比较整个模型的预测结果,0~6h内的预测值与真实值较为接近,均值误差为0.5616,均方误差为0.5873,6h之后开始出现较大误差。结论分类和回归模型都在0~6h之内得到了很好的结果,说明在此时间段内,角膜图像噪声较低,可预测性强。     

Desire for Smart Growth: A Survey of Residential Preferences in the Salt Lake Region of Utah

As an alternative to sprawling development, smart growth combines proximity to work, proximity to shopping and other destinations, neighborhood housing mix, shared and paid parking, complete street designs, and proximity to public transit. This article uses a stated-choice experiment to determine residents' attitudes toward these various aspects of smart growth in the Salt Lake region of Utah. Utah is a conservative state, where attitudes toward auto-oriented suburbia may be more positive than in other parts of the United States. So, one might wonder whether changing national attitudes toward smart growth, documented in several surveys, apply to residents of the Salt Lake region. In this stated-choice experiment, respondents were asked to choose between pairs of housing scenarios with different attributes and different prices. Mixed logit (random parameters logit) was used to relate individuals' choices to attributes, prices, and sociodemographic characteristics of respondents. The results show that, generally, respondents have positive attitudes toward most aspects of smart growth but still express preferences for single-family neighborhoods with free parking in their own driveways or garages. Different life cycle cohorts have different preferences. Proximity to work is more important for childless young adults. Young families with children place higher value on living in a neighborhood with only single-family homes and transit access. Retired empty nesters favor a mix of housing types over single-family housing on one-acre-plus lots. The results suggest that while residents of the Salt Lake region like suburban neighborhoods with primarily single-family houses, they would also like to have improved accessibility to amenities in the suburbs.     

Residential Segregation,Housing Submarkets,and Spatial Analysis: St. Louis and Cincinnati as a Case Study

This article considers how spatial analysis of housing submarkets can advance research into residential segregation. While an emphasis on housing submarkets has been proposed as a new construct for modeling housing prices, its use in analyzing residential segregation has been limited. Recent advances in spatial analysis and geographic information systems present new opportunities for researchers to exploit the potential of housing submarkets as constructs that offer a more precise way to examine residential segregation. The article synthesizes literature related to residential segregation and housing submarkets and demonstrates how to delineate housing submarkets using publicly available data. It examines the spatial distribution of housing submarkets and how the socially disadvantaged are represented across housing submarkets in St. Louis, Missouri, and Cincinnati, Ohio, to conclude that St. Louis's housing market is more polarized and racially segregated than Cincinnati's. Spatial analysis of housing submarkets, in conjunction with archival analysis, provides a promising avenue for identifying residential segregation as a multidimensional phenomenon, and a means to explore local processes of urban inequality.     

The faces of death: regional differentiation in cause-specific mortality in the past

In mortality research, much attention has been paid to the strong geographical differentials in mortality levels and in modern mortality decline, as the analysis of this geographical differentiation might hold the key to explaining the determinants of mortality change. The use of historical cause-specific mortality data has proved a challenging, although very insightful, means to this end. The four contributions to this special issue focus on cause-specific mortality in the past, both to reassess older data using new insights and to challenge existing insights by using new data and methods. These papers, of which earlier versions were presented during the thirty-eighth Social Science History Association (SSHA) Meeting in Chicago, 21–24 November 2013, explore mortality at different stages of the life course, ranging from early infancy to old age. Moreover, each paper revolves around a different group of causes of death. Although the papers are in many ways rather different, together they demonstrate how different data, theoretical frameworks and methodologies can push the boundaries of research into the trends and determinants of historical mortality patterns.     

Air Campaign Duration and the Interaction of Air and Ground Forces

This article explores the role that ground troops play in aerial campaigns. Specifically, it intends to explain how ground troops affect the duration of aerial bombing campaigns. It distinguishes between the effect of ground troops on the duration of aerial campaigns that are selective and on those that are more general and less discriminate (using newly coded data on aerial strategies). The effect of ground troops may vary depending on how air power is being used. Ground troops may increase the duration of aerial campaigns in cases in which selective strategies are used during the aerial bombing campaign. In these cases, states lose the possibility of quick, “clean” victories once ground troops are introduced. In the cases of the less-discriminate bombing campaigns, the effect of ground troops is the opposite: They shorten the duration of the bombing campaign, possibly through the increased effectiveness of a combined arms approach.     

CLOSE‐UPS AND THE SCALE OF ECOLOGY: LAND USES AND THE GEOGRAPHY OF SOCIAL CONTEXT AND CRIME

Whereas one line of recent neighborhood research has placed an emphasis on zooming into smaller units of analysis such as street blocks, another line of research has suggested that even the meso‐area of neighborhoods is too narrow and that the area surrounding the neighborhood is also important. Thus, there is a need to examine the scale at which the social ecology impacts crime. We use data from seven cities from around the year 2000 to test our research questions using multilevel negative binomial regression models (N = 73,010 blocks and 8,231 block groups). Our results suggest that although many neighborhood factors seem to operate on the microscale of blocks, others seem to have a much broader impact. In addition, we find that racially and ethnically homogenous blocks within heterogeneous block groups have the most crime. Our findings also show the strongest results for a multitude of land‐use measures and that these measures sharpen some of the associations from social characteristics. Thus, we find that accounting for multiple scales simultaneously is important in ecological studies of crime.     

The Accuracy of Handheld Pre‐Arrest Breath Test Instruments as a Predictor of the Evidential Breath Alcohol Test Results

Drunk driving is a serious threat to public safety. All available and appropriate tools for curbing this threat should be employed to their full extent. The handheld pre‐arrest breath test instrument (PBT) is one tool for identifying the alcohol‐impaired driver and enforcing drunk driving legislation. A set of data was evaluated (n = 1779) where the PBT instrument was employed in drunk driving arrests to develop a multivariate predictive model. When maintained and operated by trained personnel, the PBT provides a reasonable estimate of the evidential test result within the relevant forensic range (95% prediction interval:  ± 0.003 g/210 L). ROC analysis shows that a multivariate model for PBT prediction of the evidentiary alcohol concentration above versus below the legal limit of 0.08 g/210 L has excellent performance with an AUC of 0.96. These results would be of value in evidential hearings seeking to admit the PBT results in drunk driving trials.     

Covenant of Mayors: Reasons for Being an Environmentally and Energy Friendly Municipality

The Covenant of Mayors (CM) is the mainstream European movement involving local authorities who voluntarily commit to increase energy efficiency and the use of renewable energy sources within their territories with the aim of reducing CO₂ emissions and meet the European Union objectives by 2020. One country that has a greater number of signatories of this agreement is Spain. This article analyzes which factors influence the decision of Spanish local authorities to join the ever‐growing movement. An empirical model is formulated to describe the behavior of Spanish local governments, this being a binary choice model which is a function of various political, economic, and technical factors. Among the prominent factors that influence this decision are population, availability of renewable energy, fiscal and environmental stress, citizens’ political preference, the contagion effect of neighboring municipalities, the existence of covenant coordinators, and finally, economic motivations.     

论网络集群事件多维生成模型的构建

根据网络集群事件的基本要素,可构建以现实社会和网络空间为外部环境,以参与者、信息传播活动和事件发展进程为维度的网络集群事件生成模型。参与者在网络集群事件中经历由个体体验、到群体围观、到形成共同信念、到淡化与转移等心理、行为变化过程。网络集群事件信息传播活动可分为“碎片化”传播、扩散化传播、聚集化传播和衰减化传播等阶段。网络集群事件存在由散点引爆、热点聚集、群体极化到事件终结的过程。现实社会和网络空间以及两者的融合、互动,则构成了网络集群事件的社会空间。