有砟轨道路基翻浆冒泥模型试验系统的研发与应用

为研究既有线有砟轨道路基的翻浆冒泥机理，自主研发了一套能够模拟循环荷载–湿化耦合作用的模型试验系统。模型试样直径500 mm，由厚度分别为350 mm的路基土和200 mm的道砟组成，整个试样在高强度透明有机玻璃模型筒中制备完成。模型试验系统配备有监测荷载、位移、体积含水率和孔隙水压力的4种传感器，并通过高清相机对颗粒迁移过程进行图像捕捉。基于所研发的试验系统，针对辛泰铁路典型翻浆冒泥病害路段土样，开展翻浆冒泥模型试验。试验结果表明：动孔隙水压力是导致翻浆冒泥病害产生的关键因素。随着体积含水率的增加，动孔隙水压力引起的颗粒迁移量逐渐增加；在饱和状态下，会引起大量颗粒迁移，翻浆冒泥现象显著。试验结束时，道砟污染指数达到25%，在实际工程中已严重影响铁路的正常运营，有必要对污染道砟进行换填。     

A comparison of shear stress estimation methods for a single geobag on a rough bed

There are several methods for estimating bed shear stress in the literature, but comprehensive comparisons among them are limited and under specific conditions. This study compared these methods first on a bare smooth bed, and then for a single geobag on a rough bed in the interest of determining the stability of geobags used in riverbank protection structures. The geobag was filled with cement or sand and tested under different open channel flow conditions. The turbulent kinetic energy method appeared to best represent the local bed shear stress on the geobag when using the newly calibrated proportionality constants. The Reynolds stress method via extrapolation was relatively unaffected by changes to the geobags shape and measurement locations, suggesting this method inadequately represents the local bed shear stress. The Patel method and the universal law of the wall method failed to represent local bed shear stress in the rough bed cases due to instrument limitations and the breakdown of the law of the wall. This study highlights the impact of different methods on the bed shear stress estimation.     

α径迹法用于分辨高浓铀和Pu微粒的方法研究

擦拭样品微粒分析技术是核保障环境样品分析的一种主要手段，从大量灰尘颗粒中识别并定位含高浓铀（HEU）或含Pu微粒是微粒分析首先需要解决的问题。本文以HEU和Pu微粒为研究对象，建立了用于微粒α径迹测量的样品制备方法，采用CR-39固体径迹探测器为α径迹探测器，测量了不同蚀刻时间2种微粒产生的α径迹星的径迹参数。结果表明：可通过测量径迹短轴与曲率直径并作图来分辨HEU和Pu微粒，该方法对于蚀刻时间大于10 h的微粒径迹星，均能明显分辨，对于径迹非常密集的径迹星，也能准确分辨。     

A values–beliefs–attitude model of local food consumption: An empirical study in China and Denmark

Consumers’ and policy makers’ interest in local foods is growing. Accordingly, researchers are also increasingly paying attention to the consumption of local foods. Studies have identified preference for local foods as an emergent consumer ideology called “locavorism”, but they have not yet addressed its antecedents or put it into a theoretical context. In addition, extant research provides several insights into local food buying behaviour in developed economies (e.g., USA, UK, Germany, or Italy); however, studies simultaneously conducted in developed and emerging economies are lacking. To address these research gaps, this study develops a conceptual framework with proposed relationships among values, beliefs (locavorism and fresh start mindset), and attitudes towards and intentions to purchase local foods in China and Denmark. We conducted an online survey in China and Denmark that evaluated our constructs with pre-developed multiple-item measures. Using structural equation modelling to test the integrated model, we find that values and long-term orientation are antecedents of consumer beliefs but the influences of values on consumer beliefs differ between collectivistic-dominated China and individualistic-dominated Denmark. Specifically, collectivistic values are significantly and positively related to locavorism in both countries, while individualistic values are strongly linked to locavorism only in Denmark; collectivistic values have no effects on fresh start mindset for the two samples, but individualistic values are significantly and positively related to a fresh start mindset in Denmark. In addition, consumer beliefs are significantly and positively associated with attitudes towards and intentions to buy local foods. Local food marketers can use our findings to target their communications more effectively.     

融入局部几何特征的流形谱聚类图像分割

为了改善谱聚类图像分割的精准性和时效性,文中提出融入局部几何特征的流形谱聚类图像分割算法.首先,考虑图像数据的流形结构,在数据点的K近邻域内执行局部PCA,得到数据间本征维数的关系.然后,引入流形学习中的局部线性重构技术,通过混合线性分析器得到数据间局部切空间的相似性,结合二者构造含有局部几何特征的相似性矩阵.再利用Nystr m技术逼近待分割图像的特征向量,对构造的k个主特征向量执行谱聚类.最后,在Berkeley数据集上的对比实验验证文中算法的准确性和时效性优势.     

A comparison of manual handling risks in different domestic waste collection systems using three separate evaluation methods

Arising out of the challenge for Local Authorities (LAs) to operate sustainable systems of work, is to avoid the creation of ill-health including the most significant causes of physical absence, musculoskeletal disorders (MSDs).The study's aim was to compare the reliability of the manual handling element of the Health and Safety Executives (HSEs) risk comparator tool for different domestic waste collection methods with self-reported pain via body-mapping and MSD ill health absence rates. Participatory body-mapping exercises were carried out in five LAs with one LA resurveyed, six months after the move from 35 and 50 L containers to a wheeled bin recycling service.The lowest levels of self-reported pain were for services designed with 240l wheeled bins excluding glass; the highest levels were for services that included 100l of garden waste sacks and recycling boxes. Industry data supports previous laboratory studies showing wheeled bins to be associated with less MSD outcomes than boxes, baskets and sacks.Triangulation of data established a statistically significant correlation of 0.85 (Pearson) between average pain-count (APC) and the mean MSD absence rates, with a strong correlation of 0.77 (Spearman) between APC and risk rating. The correlation is moderate, 0.49 (Spearman) between MSD absence and risk rating, reflecting possible intervening variables and a low participation rate by LAs.The contribution of this study is to improve the design of sustainable waste collection strategies to minimise MSD associated absence. In the absence of reliable absence data, body mapping should be used as a proxy method of assessing MSD risk.     

加权信息熵与增强局部二值模式结合的人脸识别

针对人脸识别因光照、姿态、表情、遮挡及噪声等多种因素的影响而导致的识别率不高的问题，提出一种加权信息熵（IEw）与自适应阈值环形局部二值模式（ATRLBP）算子相结合的人脸识别方法（IE （w） ATR-LBP）。首先，从原始人脸图像分块提取信息熵，得到每个子块的IEw；然后，利用ATRLBP算子分别对每个人脸子块提取特征从而得到概率直方图；最后，将各个块的IEw与概率直方图相乘，再串联成为原始人脸图像最后的特征直方图，并利用支持向量机（SVM）对人脸进行识别。在AR人脸库的表情、光照、遮挡A和遮挡B四个数据集上，IE （w） ATR-LBP方法分别取得了98.37%、94.17%、98.20%和99.34%的识别率。在ORL人脸库上，IE （w） ATR-LBP方法的最大识别率为99.85%；而且在ORL人脸库5次不同训练样本的实验中，与无噪声时相比，加入高斯和椒盐噪声后的平均识别率分别下降了14.04和2.95个百分点。实验结果表明，IE （w） ATR-LBP方法能够有效提高人脸在受光照、姿态、遮挡等影响时的识别率，尤其是存在表情变化及脉冲类噪声干扰时的识别率。     

A brief review of dynamic mechanical metamaterials for mechanical energy manipulation

In the past decades, many mechanical metamaterials with uncommon static properties have been reported. On the other hand, mechanical metamaterials possessing extraordinary dynamic performance, also referred to as acoustic/elastic metamaterials, have gained more and more attractions. Examples include acoustic cloaking metamaterials that can generate an invisible region for acoustic waves, zero-stiffness metamaterials that can isolate vibrating mechanical energy, origami-based metamaterials that can realize the directional transmission of elastic waves and so on. To better understand the mechanisms adopted in dynamic mechanical metamaterials and present a general view about the existing works, we have reviewed some representative works and categorized them based on the ways of how these mechanical metamaterials manipulate the interactions between matters and mechanical energy. To distinguish the different categories of the dynamic mechanical metamaterials, we use a pair of binary numbers to measure the changing states of the magnitude and direction of the energy flow, respectively. A summary of some research works with associated reference numbers is presented in this paper with emphasis on the operating frequency, working bandwidth, and characteristic size of the element.     

Patterns in environmental priorities revealed through government open data portals

The ways in which environmental priorities are framed are varied and influenced by political forces. One technological advance--the proliferation of government open data portals (ODPs)--has the potential to improve governance through facilitating access to data. Yet it is also known that the data hosted on ODPs may simply reflect the goals and interests of multiple levels of political power. In this article, I use traditional statistical correlation and regression techniques along with newer natural language processing and machine learning algorithms to analyze the corpus of datasets hosted on government ODPs (total: 49,066) to extract patterns that relate scales of governance and political liberalism/conservatism to the priorities and meaning attached to environmental issues. I find that state-level and municipal-level ODPs host different categories of environmental datasets, with municipal-level ODPs generally hosting more datasets pertaining to services and amenities and state-level ODPs hosting more datasets pertaining to resource protection and extraction. Stronger trends were observed for the influences of political conservatism/liberalism among state-level ODPs than for municipal-level ODPs.