Structural geology practice and learning,from the perspective of cognitive science

Spatial ability is required by practitioners and students of structural geology and so, considering spatial skills in the context of cognitive science has the potential to improve structural geology teaching and practice. Spatial thinking skills may be organized using three dichotomies, which can be linked to structural geology practice. First, a distinction is made between separating (attending to part of a whole) and combining (linking together aspects of the whole). While everyone has a basic ability to separate and combine, experts attend to differences guided by experiences of rock properties in context. Second, a distinction is made between seeing the relations among multiple objects as separate items or the relations within a single object with multiple parts. Experts can flexibly consider relations among or between objects to optimally reason about different types of spatial problems. Third, a distinction is made between reasoning about stationary and moving objects. Experts recognize static configurations that encode a movement history, and create mental models of the processes that led to the static state. The observations and inferences made by a geologist leading a field trip are compared with the corresponding observations and inferences made by a cognitive psychologist interested in spatial learning. The presented framework provides a vocabulary for discussing spatial skills both within and between the fields of structural geology and cognitive psychology.     

An SVM-based machine learning method for the separation of alteration zones in Sungun porphyry copper deposit

Sungun porphyry copper deposit is in East Azarbaijan province, NW of Iran. There exist four hypogene alteration types in Sungun: potassic, propylitic, potassic–phyllic, and phyllic. Copper mineralization is essentially associated more with the potassic and less with the phyllic alterations and their separation is, therefore, quite important. This research has tried to separate these two alteration zones in Sungun porphyry copper deposit using the Support Vector Machine (SVM) method based on the fluid inclusion data, and seven variables including homogenization temperatures, salinity, pressure, depth, density and the Cu grade have been measured and calculated for each separate sample. To apply this method, use is made of the radial basis function (RBF) as the kernel function. The best values for λ and C (the most important SVM parameters) that perform well in the training and test data are 0.0001 and 1, respectively. If these values for λ and C are applied, the phyllic and potassic alteration zones in the training and test data will be separated with an accuracy of about 95% and 100%, respectively. This method can help geochemists in separating the alteration zones because classifying and separating samples microscopically is not only very hard, but also quite time and money consuming.     

From “cartoneros” to “recolectores urbanos”. The changing rhetoric and urban waste management policies in neoliberal Buenos Aires

This study contributes to the existent literature on neoliberal urban governance examining the process-based character of this formation. I maintain that neoliberal governance is a fluid and evolving formation which is continuously being constructed and reconstructed beneath a rhetorical veneer of inevitable emergence and permanence. In this context, this work examines the interconnections between neoliberal urban ascendancy, changing rhetoric and urban waste management policies, and waste pickers (cartoneros), in a case study setting, Buenos Aires. Since 2002, the neoliberal urban governance in Buenos Aires (its institutions, programs and policies) has mobilized different rhetoric and policies to negotiate the waste pickers’ “disturbing” and “dirty” presence in the streets. In that process, the waste pickers, originally marginalized and stigmatized by the neoliberal discourse, have been regulated and disciplined into legal and “well behaved” workers. I would argue that, regulating this activity does not entail giving the waste pickers an opportunity to become central actors in the future of urban waste management in the city. Rather, it is compatible with the logic of the local neoliberal urban projects, focused on disciplining the city’s physical and social landscape as new opportunities for growth and development continue to emerge.     

Planning and development regulation amid rapid urban growth: Explaining divergent trajectories in Africa

Why are urban plans, land use regulations and construction codes implemented effectively in some African states but not others? This constitutes an increasingly urgent development concern with major implications for the environment and the urban poor. Rather than being explained by economic factors, bureaucratic capacity or the nature of the urban policies and regulations in place, this paper argues that divergent outcomes are largely rooted in differing political bargaining environments. Comparing Uganda and Rwanda, it presents an empirical study that analyses contrasting planning and regulation trajectories in contexts of similarly low levels of socioeconomic development and soaring rates of urban growth. It argues that the divergent outcomes can be explained in relation to the political resources and incentives confronted by governing elites, which in Rwanda impel state actors to implement plans and regulations while in Uganda incentivize overriding them in the interests of political or economic gain. In highlighting political bargaining contexts and how these change over time, the paper illustrates the critical importance of historically informed city-level political economy analysis for understanding divergent urban development outcomes.     

Predicted ultimate capacity of laterally loaded piles in clay using support vector machine

The determination of ultimate capacity of laterally loaded pile in clay is a key parameter for designing the laterally loaded pile. The available methods for determination of ultimate resistance of pile in clay are not reliable. This study investigates the potential of a support vector machine (SVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. The SVM, which is firmly based on statistical learning theory, uses a regression technique by introducing an ?-insensitive loss function. A sensitivity analysis has been carried out to determine the relative importance of the factors affecting ultimate capacity. The results show that SVM has the potential to be a practical tool for prediction of the ultimate capacity of pile in clay.     

上海旧里保护改造模式与产权处置路径

保护性改造里弄,维护建筑历史和城市文脉是当前城市更新思潮的主流,但改造过程将面临土地制度的诸多约束。本文以静安别墅、田子坊、建业里、179街坊、思南公馆等五个较具代表性的改造案例分析入手,结合产权变动与建筑改造解构与组合,提出里弄的保护改造四种模式,并分析不同模式下土地产权处置差别化方式、路径和土地利益分配形式,为城市日居住保护改造实施提供理论和实践借鉴。     

BOOK REVIEWS

Book Reviews in are this Article Northern Waters . Clive Archer and David Scivener , EDS. Principles of Geographical Information Systems for Land Resources Assessment . P. A. Burrough . The Great Lakes: An Environmental Atlas and Resource Book. Environment Canada , United States Environmental Protection Agency , Brock University , AND Northwestern University . Uneven Development in Southern Europe: Studies of Accumulation, Class, Migration and the State. Rays Hudson AND Jim Lewis , EDS. Hazards: Technology and Fairness. Robert W. Kates and Alvin M. Weinberg . The Price of War. Urbanization in Vietnam 1954–85. Nigel Thrift and Dean Forbes . Population Structures and Models: Developments in Spatial Demography. Robert Woods and Philip Rees , EDS. Evaluating Earthquake Hazards in the Los Angeles Region-An Earth-Science Perspective. J. I. Ziony , ed .     

兰州银滩湿地区域生态经济价值评估

通过分析人工湿地的生态系统服务功能,阐述了黄河湿地生物多样性保护与水文调控生态功能区的重要性,计算了兰州银滩湿地的固碳释氧、空气质量调节、水源涵养和科研文化四项核心生态经济价值。结果表明：银滩湿地核心生态经济价值理论值为1 623.7万元,其中固碳释氧和科研文化价值实现率较高,分别为324.88万元和11.53万元。但现状水分供给、生态结构方面尚存在不合理之处,通过合理配置树草种构成,优化引水渠道等措施,该湿地将发挥更大的生态经济效益。     

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs¹³⁷ activity given the measurements taken in the region of Briansk following the Chernobyl accident.