The relationship between centrality and land use patterns: Empirical evidence from five Chinese metropolises

The relationship between location and land use patterns is one of the classic theoretical issues in urban studies. Classic models based on the monocentricity hypothesis have limitations in the interpretation of modern urban structure. China has experienced institutional transformation in recent decades, and the interaction of national government policy, market forces and the natural environment has influenced urban planning in Chinese metropolises, resulting in urban structures with special characteristics. This paper examines the distribution of location and land use intensity, and tested the Alonso model by the relationship between them in five Chinese metropolises using Point of Interest data, space syntax methodology, the grid weighted statistical method and the Geographically Weighted Regression (GWR) model. Universal patterns about the scaling relation between intensity of land use types and the centrality of location are revealed. The elasticity of land use types to location, from high to low sensitivity, is commercial, residential then industrial land in most of the five metropolises studied. The sensitivity sequence of land use studied suggests that the hypothetical model based on the classical Alonso model can explain the spatial structure of modern metropolises in China to some extent, especially for the commercial land. But the order of sensitivity of residential land and industrial land to location does not conform to the model. The spatial heterogeneity in land use intensity and centrality were explored and the factors embedded were discussed. It can be found that the relation between centrality and land use intensity conforms to power law. In most of the metropolises studied, when the scaling relation between land use intensity and centrality is super linear, the sequence of the frequency value from high to low are commercial, residential and industrial land; when the scaling relation is sublinear, the sequence of the frequency value is industrial, residential and commercial land.     

Residual learning rates in lead-acid batteries: Effects on emerging technologies

The low price of lead-acid, the most popular battery, is often used in setting cost targets for emerging energy storage technologies. Future cost reductions in lead acid batteries could increase investment and time scales needed for emerging storage technologies to reach cost-parity. In this paper the first documented model of cost reductions for lead-acid batteries is developed. Regression to a standard experience curve using 1989–2012 data yield a poor fit, with R² values of 0.17 for small batteries and 0.05 for larger systems. To address this problem, battery costs are separated into material and residual costs, and experience curves developed for residual costs. Depending on the year, residual costs account for 41–86% of total battery cost. Using running-time averages to address volatility in material costs, a 4-year time average experience curve for residual costs yield much higher R², 0.78 for small and 0.74 for large lead-acid batteries. The learning rate for residual costs in lead-acid batteries is 20%, a discovery with policy implications. Neglecting to consider cost reductions in lead-acid batteries could result in failure of energy storage start-ups and public policy programs. Generalizing this result, learning in incumbent technologies must be understood to assess the potential of emerging ones.     

A graph-based semi-supervised approach to classification learning in digital geographies

As the distinction between online and physical spaces rapidly degrades, social media have now become an integral component of how many people's everyday experiences are mediated. As such, increasing interest has emerged in exploring how the content shared through those online platforms comes to contribute to the collaborative creation of places in physical space at the urban scale. Exploring digital geographies of social media data using methods such as qualitative coding (i.e., content labelling) is a flexible but complex task, commonly limited to small samples due to its impracticality over large datasets. In this paper, we propose a new tool for studies in digital geographies, bridging qualitative and quantitative approaches, able to learn a set of arbitrary labels (qualitative codes) on a small, manually-created sample and apply the same labels on a larger set. We introduce a semi-supervised, deep neural network approach to classify geo-located social media posts based on their textual and image content, as well as geographical and temporal aspects. Our innovative approach is rooted in our understanding of social media posts as augmentations of the time-space configurations that places are, and it comprises a stacked multi-modal autoencoder neural network to create joint representations of text and images, and a spatio-temporal graph convolution neural network for semi-supervised classification. The results presented in this paper show that our approach performs the classification of social media content with higher accuracy than traditional machine learning models as well as two state-of-art deep learning frameworks.     

Comparative study on economic contribution rate of education of China and foreign countries based on soft computing method

Economic contribution rate of education (ECRE) is the key factor of education economics. This article selected China, South Korea, United States and other countries for a total of 15 samples, and put the data of the same period under the framework of soft computing, to simulate the production chain of “education–potential human capital–actual human capital–economic growth”. The basic idea is: Firstly, 15 countries are softly categorized according to the level of science and technology (S&T) progress. Secondly, potential human capital and actual human capital establish the internal correlation (fuzzy mapping) in the same classification, and we conceptualize actual human capital as one production factor, joined with the other two production factors, fixed asset and land, to set up the fuzzy mapping to economic growth., and then calculate economic contribution rate of education of China and foreign by two fuzzy mapping of them. Thirdly, this paper analyzes the present state and differences in the development of education between China and foreign according to different ECRE, and offers proposals for promoting the education in China.     

基于DedeCMS的视频点播模块实现与比较

对视频点播方法进行研究和探讨,将DedeCMS为基础的视频模块与流媒体服务、FTP服务的视频点播形式进行对比。     

土工格栅加筋包边填砂路堤模型试验研究

为探究包边填砂路堤荷载作用下的极限承载力特性、破坏形态规律及加筋性状,设计了土工格栅加筋包边填砂路堤结构,改装美国GCTS公司的USTX-2000动静三轴加载装置进行加载,通过改变加筋层数、筋材布置长度及包边土厚度对土工格栅包边填砂路堤进行一系列试验。对不同工况下包边填砂路堤的极限承载力、封层及坡面法向累积变形、位移变化进行研究。试验结果表明:土工格栅加筋和增加包边土厚度可以显著提高包边填砂路堤的极限承载力,并能减小封层中、封层右及坡顶、坡中的法向累积变形;无筋路堤的滑动面在路堤内呈折线状且并未通过坡脚侵入地基,在坡顶的黏土和砂芯交界处产生最大位移;土工格栅加筋及增加包边土厚度可以使滑动面向路堤内部迁移但形态不变,且最大位移处向路堤内部迁移。     

应对长江口咸潮入侵的临界流量经验模型研究

1994年以来,长江口咸潮入侵严重威胁当地供水安全,随着长江上游水库群陆续建成,有关部门提出了通过上游水库群压咸调度保障长江口地区供水安全的方案。为明确压咸调度的目标流量(即临界流量),基于统计分析的方法,采用多元回归分析和主成分分析方法,选取实测站点数据建立了盐度-潮差-入海流量的相关关系统计模型,研究了咸潮发生的机理;通过模型分析多次咸潮入侵数据,确定临界流量为一个变化值,潮差290～335 cm下的临界流量在9 390～21 633 m³/s之间。研究表明,当长江口咸潮入侵时,单独依靠长江上游水库调度压咸所需的流量大,响应时间长,压咸效果不明显。因此,实际压咸调度应通过流域整体调度与本地蓄淡避咸水库共同作用应对咸潮入侵。     

北京某区域分布式能源规划环境效益及环境问题分析

为满足电力负荷增长的需求,需调整能源结构,提高其他能源发电量所占的比例。因此,除了核电、风电等其他能源电站外,分布式能源应运而生。结合北京某区域分布式能源电站的规划项目,对分布式能源电站可能产生的环境污染问题进行阐述,综合分析其所具有的环境效益,最终提出治理方案,为在北京建设分布式能源电站提供了有价值的参考。     

A User‐Centric Evaluation Procedure for the Design of Child‐Resistant Medicine Bottles

Recently, people have begun to realize the importance of child‐resistant (CR) medicine packaging. However, most manufacturers and designers have not been able to effectively provide prevention strategies or design criteria to protect consumers. This research proposes a systematic approach to analyze CR packaging design problems and experiments to evaluate the identified design parameters and to generate the most suitable CR medicine packaging design. The design of a CR packaging bottle is used as an example to help explain the development procedure. During the development procedure, user trials, questionnaires, and children's anthropometric data on bottle opening and hand operations are analyzed. Five design parameters, specifically the cap diameter, cap height, bottle height, bottle diameter, and torsion, are identified and used to perform a Taguchi orthogonal array experimental analysis. A computer‐aided design system is also built to help generate the most suitable design alternatives. The results should assist designers in determining the most important CR design parameters and their most suitable combinations for bottle and related CR medicine packaging design.