Hillslope soil water flowpaths and the dynamics of roadside soil cation pools influenced by road deicers

Over the past 60 years, road deicers (i.e. road salt) have been applied to roadways in high latitudes to improve road conditions in winter weather. However, the dissolution of road deicers in highway runoff creates waters with high concentrations of sodium, which can mobilize soil metals via soil cation‐exchange reactions. While several studies have detailed the interactions of road salt‐rich solutions and surface and ground waters, less attention has been given to how local hydrologic flowpaths can impact the delivery of these solutions to near‐road soils. Between 2013 and 2014, soil water samples were collected from a roadside transect of lysimeter nests in Pittsburgh, Pennsylvania (USA). Soil water samples were analysed for metal concentrations and resulting data used to examine cation dynamics. While patterns in soil water calcium and magnesium concentrations follow patterns in soil water sodium concentrations, additional processes influence patterns in soil water potassium concentrations. Specifically, we observe the highest calcium and magnesium concentrations in the deepest lysimeters, suggesting divalent cations are mobilized to, and potentially accumulate in, deeper soil horizons. In contrast, soil water potassium concentrations do not follow this pattern. Additionally, in all examined elements (Ca, Mg, K, Na, and Cl), the timing of concentration peaks appears be influenced by a combination of both distance from the roadside and sampling depth. These relationships not only suggest that multiple soil water flowpaths interact with our study transect but also confirm that road salt plumes persist and migrate following the road salting season. Characterizing the interactions of sodium‐rich solutions and roadside soil cation pools clarifies our understanding of metal dynamics in the roadside environment. A deeper understanding of these processes is necessary to effectively restore and manage watersheds as high total dissolved solid solutions (e.g. road deicing melt, unconventional natural gas brines, and marginal irrigation water) continue to influence hydrological systems. Copyright © 2016 John Wiley & Sons, Ltd.     

提高多层前馈网络推广能力的权值控制算法

研究了多层前馈网络的“过拟合”现象,针对网络拟合效果好,而推广能力差的问题,提出了与BP算法相结合的、以权值修正量小于某一给定的较小值为收敛标准的权值控制算法.在紫坪埔水库工程洪水预报的神经网络模型中的应用表明,该方法具有提高多层前馈网络推广能力的作用.     

Many roads to Paris: Explaining urban climate action in 885 European cities

Research on urban climate action has identified a broad range of potential factors explaining why and how local governments decide to tackle climate change. However, empirical evidence linking such factors in order to explain actual urban climate action has so far been mixed. To address this roadblock, our paper relies on a novel approach, postulating that different configurations of factors may lead to the same outcome (“equifinality”), through a qualitative comparative analysis (QCA). It is based on an available data set of local climate mitigation plans in 885 European cities. We find that urban climate action is systematically associated with four qualitatively different configurations of factors, each with its own consistent narrative (“networker cities”, “green cities”, “lighthouse cities”, “fundraising cities”). Crucially, some factors play a positive role in some configurations, a negative in others, and no role in further configurations (e.g., whether a city is located in a country with supportive national climate policies). This confirms that there is no single explanation for urban climate action. Achieving greater robustness in empirical research about urban climate action may thus require a shift, both conceptual and methodological, to the interactions between factors, allowing for different explanations in different contexts.     

Implementing a knowledge system: Lessons from the global stewardship of climate services

Knowledge systems are mechanisms that can drive climate adaptation through the pursuits of enhancing resource sharing, collaboration, and learning, while at the same time helping to develop trust and credibility among individuals and intuitions. While these goals are widely discussed, less is known about the activities and strategies that knowledge systems undertake to achieve these goals. We analyze the Global Framework of Climate Services (GFCS) as a knowledge system organized around the translation of weather and climate information for decision-making. The GFCS brings together the World Meteorological Organization, national meteorological and hydrological services, and some of the world’s largest multilateral scientific, humanitarian, and development organizations. Our analysis draws on key informant interviews, focus groups conducted in African countries, and an online survey of GFCS participants. We describe the main activities pursued by the GFCS that shaped the vision of climate services, built capacity in national climate adaptation, and created connections among diverse actors and organizations worldwide. We show how these activities generated tensions about the purpose of the GFCS and how influence among the knowledge system was distributed. Based on our results, we illustrate new ways to conceptualize the strategies of knowledge systems, which we describe as (1) theorizing the norms of practice and mechanisms of change, (2) legitimizing actors, and (3) managing knowledge. These strategies identify pathways for, and pitfalls to, a knowledge system’s pursuit of its goals, providing guidance to managers of knowledge systems and an analytical framework to evaluate their impacts.     

Chinese and multilateral development finance in the power sector

Public developmental institutions are pivotal in shaping the contours of the electricity sector of the developing world and its associated greenhouse gas emissions pathways. However, we have a fragmented and incomplete picture of the evolution of their investments over time and space. This is particularly the case for the recent rise of various Chinese Developmental Institutions (CDIs) for which infrastructure investment estimates range in the trillions under China’s Belt and Road Initiative (BRI) and for which data is mostly not publicly disclosed. We address this gap in two ways: first, we compile and analyze a novel dataset that draws on commercial data tracking, publicly available datasets, and more than 1,000 supporting documents to match financial transactions by the main CDIs and traditional Multilateral Development Banks (MDBs) to power plant projects worldwide. This allows us to conduct a quantitative, comparative analysis of the role of CDIs and MDBs to understand the relative size, technology, and country focus of such investments in the period 1999–2020. Second, we complement the quantitative dataset with 39 expert interviews to shed light on the drivers behind the Chinese investments, with a particular focus on coal projects. The analysis shows that CDIs have rapidly emerged as the largest public finance provider for the electricity sector in the developing world. We also find that, in contrast with the increasingly green BRI rhetoric, the technology portfolio of CDI investments in power plants is still heavily dominated by coal plants. Over time, however, CDIs have increasingly supported more efficient coal plants and increased the share of their portfolio supporting non-hydro renewables and supported a growing number of projects jointly with MDBs. Steering China’s bilateral coal finance flows through international efforts into a more sustainable direction to meet climate goals will require careful consideration of a set of drivers and enablers of the involvement of CDIs and recipient countries in coal projects, which we discuss, as well as of the role of other finance providers, including traditional MDBs.     

Incorporation of neural network-like processors for GPS navigation

The solution for the receivers position and clock bias using four or more GPS pseudorange measurements involves nonlinear quadratic equations. One of the popular techniques for linearizing the equations and solving them is the least squares (LS) scheme based on an iterative gradient approach. For real-time applications when the solution is to be obtained within a time of the order of 100 ns, a computer often cannot comply with the desired computation time, or high-end computers are too expensive. In this paper various ordinary differential equation formulation schemes, and corresponding circuits of neuron-like analog processors, will be described and several tested in order to ascertain their suitability for GPS navigation processing purposes. The circuits of simple neuron-like analog processors are employed essentially for on-line inversion of matrices, which is usually required for determining LS solutions, as well as dilution of precision (DOP) calculation in standard GPS receivers. Data from single epoch and kinematic positioning experiments will be simulated to validate the effectiveness of the proposed scheme. The properties and performance of the proposed scheme will be assessed and compared to those of the conventional method of matrix inversion.     

基于八向链码的矩的快速计算及2—D目标识别

提出一种直接基于八向链码的矩的快速计算方法，给出了与多边形近似法矩的计算及形状识别时间比较，最后使用不变性矩和人工神经网络完成2—D形状识别。实验结果表明，本文所提出的方法具有更高的计算和识别速度。     

Damage identification in a ship’s structure using neural networks

Visual inspection of large and complex structures such as a ship is difficult and costly due to problems of accessibility. In this paper, a neural network technique is developed for identifying the damage occurrence in the side shell of a ship’s structure. The side shell is modeled as a stiffened plate. The input to the network is the autocorrelation function of the vibration response of the structure. The response was obtained using a finite element model of the structure. The output is a single function , which was formed by adding together the damping and a part of the restoring forces. The function is used to identify not only the damage occurrence in the model but also its extent and location. The results show that the method presented in this work is successful in identifying the occurrence of damage. The detection of the extent and location of damage is promising, however, more work has to be done in this area.