A comparative assessment of local municipal food policy integration in the Netherlands

ABSTRACT

Local governments around the world increasingly engage in food governance, aiming to address food system challenges such as obesity, food waste, or food insecurity. However, the extent to which municipalities have actually integrated food across their policies remains unknown. This study addresses this question by conducting a medium-n systematic content analysis of local food policy outputs of 31 Dutch municipalities. Policy outputs were coded for the food goals and instruments adopted by local governments. Our analysis shows that most municipalities integrate food to a limited extent only, predominantly addressing health and local food production or consumption. Furthermore, municipalities seem hesitant to use coercive instruments and predominantly employ informative and organizational instruments. Nonetheless, a small number of municipalities have developed more holistic approaches to address food challenges. These cities may prove to be a leading group in the development of system-based approaches in Dutch local food policy.     

Understanding the impact of High Speed Railway on urban innovation performance from the perspective of agglomeration externalities and network externalities

Transportation infrastructure and innovation play an important role in promoting regional economic growth. However, previous studies have mainly focused on the economic agglomeration by increased accessibility, but ignored the important on inter-city economic linkages and the network externalities it generated. Based on the externality perspective, this paper uses the propensity score matching model (PSM-DID) and spatial econometric model to analyze the heterogeneous impact of HSR opening on urban innovation performance and compare the differential effects of agglomeration externalities and network externalities on knowledge spillovers. The empirical results suggest the following: (1) The opening of HSR significantly improves urban innovation performance, but there is significant spatial heterogeneity. (2) The opening of HSR not only promotes the agglomeration of production factors to cities, but also strengthens inter-city economic connections, thus improving urban innovation performance through agglomeration externalities and network externalities. However, compared to agglomeration externalities, network externalities have a superior strength of impact on urban innovation performance. (3) From the dynamic effect perspective, the opening of HSR has a hysteresis effect on urban innovation of 2–3 years, and differences exist between cities.     

Soft sensing of water depth in combined sewers using LSTM neural networks with missing observations

Information and communication technologies combined with in-situ sensors are increasingly being used in the management of urban drainage systems. The large amount of data collected in these systems can be used to train a data-driven soft sensor, which can supplement the physical sensor. Artificial Neural Networks have long been used for time series forecasting given their ability to recognize patterns in the data. Long Short-Term Memory (LSTM) neural networks are equipped with memory gates to help them learn time dependencies in a data series and have been proven to outperform other type of networks in predicting water levels in urban drainage systems. When used for soft sensing, neural networks typically receive antecedent observations as input, as these are good predictors of the current value. However, the antecedent observations may be missing due to transmission errors or deemed anomalous due to errors that are not easily explained. This study quantifies and compares the predictive accuracy of LSTM networks in scenarios of limited or missing antecedent observations. We applied these scenarios to an 11-month observation series from a combined sewer overflow chamber in Copenhagen, Denmark. We observed that i) LSTM predictions generally displayed large variability across training runs, which may be reduced by improving the selection of hyperparameters (non-trainable parameters); ii) when the most recent observations were known, adding information on the past did not improve the prediction accuracy; iii) when gaps were introduced in the antecedent water depth observations, LSTM networks were capable of compensating for the missing information with the other available input features (time of the day and rainfall intensity); iv) LSTM networks trained without antecedent water depth observations yielded larger prediction errors, but still comparable with other scenarios and captured both dry and wet weather behaviors. Therefore, we concluded that LSTM neural network may be trained to act as soft sensors in urban drainage systems even when observations from the physical sensors are missing.     

基于村落宅图的分类及量化研究——以徽州传统村落群为例

本文以江西省婺源县沱川乡理坑、浙源乡虹关以及思口镇西冲的3次村落测绘作为研究的起点,逐步拓展至对12份徽州传统村落宗族图谱中的村落宅图进行分类及量化研究。通过对村落宅图的研究来还原徽州传统村落群的空间形态,探究其背后的地缘影响、血缘纽带和社会维系,归纳总结出9种村落群的基本构成要素及其所占比率,揭示村落群的空间构成和形态要素。希望在此基础上推演村落群形态的历史演变过程,还原与诠释村落群背后隐藏的内在秩序。     

Predicting pollutant removal in constructed wetlands using artificial neural networks(ANNs)

Growth in urban population,urbanisation,and economic development has increased the demand for water,especially in water-scarce regions.Therefore,sustainable approaches to water management are needed to cope with the effects of the urbanisation on the water environment.This study aimed to design novel configurations of tidal-flow vertical subsurface flow constructed wetlands(VFCWs) for treating urban stormwater.A series of laboratory experiments were conducted with semi-synthetic influent stormwater to examine the effects of the design and operation variables on the performance of the VFCWs and to identify optimal design and operational strategies,as well as maintenance requirements.The results show that the VFCWs can significantly reduce pollutants in urban stormwater,and that pollutant removal was related to specific VFCW designs.Models based on the artificial neural network(ANN) method were built using inputs derived from data exploratory techniques,such as analysis of variance(ANOVA) and principal component analysis(PCA).It was found that PCA reduced the dimensionality of input variables obtained from different experimental design conditions.The results show a satisfactory generalisation for predicting nitrogen and phosphorus removal with fewer variable inputs,indicating that monitoring costs and time can be reduced.     

中国城市天然气消费驱动因素分析

为推动我国能源革命,培育天然气成为主体能源之一,有必要进一步研究我国天然气消费量的发展趋势,探寻影响天然气消费量的驱动因素。为此,采用迪氏对数指标分解法,构建城市天然气消费量分解模型,将驱动因素分解为空间扩张、管网密度、人口密度、人口城镇化、居民天然气气化率、能源消费弹性、天然气替代、经济增长和管道规模等9个效应,并定量分析各效应对我国城市天然气消费量变动的贡献率。研究结果表明:(1)各省天然气消费量驱动因素存在着较大的差异;(2)管道密度效应、管网规模效应、经济增长效应、居民天然气气化率效应、空间扩张效应、能源消费弹性效应能显著推动城市天然气消费量的增长,而人口密度和人口城镇化效应的影响则并不显著。进而根据分效应贡献率和市场特征,将中国30个省区市天然气市场划分为成熟型、培育型、经济发展型和资源约束型等4种类型,并分析了各类型市场天然气消费的核心驱动因素,以期为因地制宜开展天然气产业规划和政策制定提供决策依据。     

文人画对陶瓷绘画创作的影响

陶瓷绘画最早可以追溯到彩陶时期,陶瓷与绘画相互交融发展。至今,文人画的审美精神和文化内涵一直影响着当代陶瓷绘画,在画面的表现形式和内在精神上都极具中国传统文化的艺术精神。     

Impact of Lake Michigan water level rise on complex bidirectional flow in the Chicago Area Waterway System (CAWS)

In the past decade, continuously rising water levels in Lake Michigan have been threatening lakefront areas, especially in metropolitan regions like the Greater Chicago area. This provides the motivation to analyze the impact that high lake levels have on the Chicago Area Waterway System (CAWS). As the only primary free connection between the CAWS and Lake Michigan, the Calumet Area waterway subsystem plays a key and unique role. In this work, a numerical model covering the Calumet subsystem and having Lake Michigan as a boundary condition, is set up, calibrated, and validated using limited field observations. It is found that the Calumet subsystem has become bidirectional, where both discharge and flow directions are controlled by lake levels. When lake levels are below −0.15 m (-0.5 ft, Chicago City Datum, CCD), the discharge in the Grand Calumet River is around zero, with water flowing along its east branch towards Indiana. When lake levels are above +0.46 m (+1.5 ft, CCD), the flow reverses direction and drains west into Illinois. In 2020, the mean lake-level was at +1.07 m (+3.5 ft, CCD), and the base discharge in the Grand Calumet River was approximately 8.5 m³/s (300 ft³/s). The higher Lake Michigan’s level is, the larger the discharge would be into Illinois. Potential impact of this extra discharge on Lake Michigan Diversion Accounting (LMDA) of the State of Illinois and flood management in the Chicago Sanitary and Ship Canal (CSSC), is analyzed; while the nature of the bidirectional flows is characterized with the intent of shedding light on this complex phenomenon.     

充气膜承冰壳结构形态设计及其建造实践

充气膜承冰壳结构是通过对充气 膜喷溅液体材料，待其凝结成型后撤除充气 膜形成的冰壳结构，该技术始于20世纪40年 代的充气膜承薄壳混凝土结构。文章通过比 对混凝土薄壳和冰壳的差异性，梳理充气膜 承薄壳结构的发展主线，对其形态设计方法 进行总结。结合“2017哈尔滨国际冰雪建造 节”相关建造实践，从施工方案的拟定与实 践、施工材料的选择与工艺以及施工工法的 对比与分析三方面对充气膜承冰壳结构形态 设计与建造实践进行总结与备忘，并对其后 期维护相关条件与技术进行讨论。     

Study of traffic characteristics based on internet web real-time traffic conditions by image identification technology

With the rapid development of Internet, it is increasingly convenient to obtain real-time traffic condition information, which has greatly stimulated the improvement of urban traffic guidance. Traffic conditions are generally divided into four grades in the existing network platform, which are expressed in different colours. The understanding of traffic condition is still at the level of abstract senses. Therefore, it is difficult to grasp the characteristics of urban traffic. To this end, a new idea is proposed in this paper, and the new idea is to study the urban traffic characteristics based on real-time traffic condition information extraction with image identification technology. With this method, we can not only quantify the abstract traffic condition information, but also solve the loss of traffic condition information. In addition, an instance is analysed in this paper, it shows that it can provide references for urban traffic organization management very well.