Ecological Planting Imperative: Functional Systems,Not Stylized Ecologies

The ability of landscape architectural projects to mitigate the worst effects of climate change will depend upon designed ecological systems. These systems will be built with plants. Despite the recognition of ecology as an essential driver of landscapes, the professionals of landscape architecture too often lack the knowledge and practical skills to create robust vegetative systems. New approaches and tools are required. This article outlines principles and methods for designing biodiverse plant systems for urban sites. Planting methods that increase species richness, functional diversity, and spatial complexity are emphasized as a way of developing more resilient plantings. Selecting species with similar evolutionary adaptions to stress, disturbance, and competition—as well as creating multi-layered compositions of diverse plant morphologies—allows designers to create compatible, long-lived plant mixes. To balance the increased visual complexity of diverse plant mixes, the article explores design techniques to make plantings more appealing to the public. The strategies explored here are based on the projects, experience, and research of Phyto Studio, a Washington, D.C. based studio. The methods build on work described in the author’s book, Planting in a Post-Wild World, an exploration of how to create designed plant communities.     

生态健康旅游袜产品的创意设计与开发

介绍生态健康旅游袜产品的创意设计思路及工艺设计,包括产品定位设计、功能设计、品质设计、外观设计、包装设计。阐述生态健康旅游袜产品的生产工艺流程,包括纤维生产工艺、短流程快速纺纱生产工艺、生态健康旅游袜生产工艺。详细分析生态健康旅游袜产品主体纤维材料的选择,并以生态健康旅途袜产品开发为例,介绍袜品研发过程,并对袜品进行性能测试。总结生态健康旅游袜的产品定位原则、创意设计思想及研发关键技术,对功能性袜品的设计开发具有借鉴意义。     

Evolving accuracy: A genetic algorithm to improve election night forecasts

In this paper, we apply genetic algorithms to the field of electoral studies. Forecasting election results is one of the most exciting and demanding tasks in the area of market research, especially due to the fact that decisions have to be made within seconds on live television. We show that the proposed method outperforms currently applied approaches and thereby provides an argument to tighten the intersection between computer science and social science, especially political science, further. We scrutinize the performance of our algorithm's runtime behavior to evaluate its applicability in the field. Numerical results with real data from a local election in the Austrian province of Styria from 2010 substantiate the applicability of the proposed approach.     

Integrated planning and scheduling under production uncertainties: Bi-level model formulation and hybrid solution method

We propose a novel method for integrating planning and scheduling problems under production uncertainties. The integrated problem is formulated into a bi-level program. The planning problem is solved in the upper level, while the scheduling problems in the planning periods are solved under uncertainties in the lower level. The planning and scheduling problems are linked via service level constraints. To solve the integrated problem, a hybrid method is developed, which iterates between a mixed-integer linear programming solver for the planning problem and an agent-based reactive scheduling method. If the service level constraints are not met, a cutting plane constraint is generated by the agent-based scheduling method and appended to the planning problem which is solved to determine new production quantities. The hybrid method returns an optimality gap for validating the solution quality. The proposed method is demonstrated by two complicated problems which are solved efficiently with small gaps less than 1%.     

Multiobjective optimization and decision-making for DG planning considering benefits between distribution company and DGs owner

Environmental concerns and fossil fuels uncertainties have resulted in promotion of multi-source and multi-type distributed generation (DG). However, the development of DG has brought new challenges to distribution system. This paper proposes a multiobjective optimization and decision-making methodology for determining size and site of multi-source and multi-type DG in distribution networks. The proposed method is based on the combination of analytical method and multi-objective optimization method and set pair of analysis (SPA). The comprehensive analysis of the loss sensitivity factor, voltage profile and reliability gave DG candidate locations. The multi-objective optimization method is based on an already-known but suitably modified Non-Dominated Sorting Genetic Algorithm (NSGA) to solve the constructed formulations, which include maximizing benefits of DG owner and Distribution Companies (DisCo) while meeting some constraints. The objective not only includes costs for DG investment, DG operation and maintenance, purchase of power by DisCo but also involving quantization for improvement of losses, voltage, reliability, etc. SPA, which is a multi-attribute decision analysis, is applied to obtain the synthetic priority of pareto solutions and carry out rank stability analysis. Furthermore, the proposed technique is applied to 37-bus distribution network. The results show that the proposed method is fast, reliable and available to determine size and site of DG as well as balance benefits between DG owner and DisCo.     

Barriers and facilitators to following the dietary guidelines for vegetable intake: Follow-up of an intervention to increase vegetable intake

The Dietary Guidelines for Americans (DGA) stress the importance of a diet high in vegetables; however, intake remains low. Recently, we found that self-identified low vegetable consumers ate the recommended daily amounts of vegetables when they were provided gratis but returned to habitual intake when vegetables were no longer supplied. This follow-up study aimed to identify key barriers and facilitators to vegetable consumption and to assess if barriers and facilitators differ between adults who had been provided vegetables in recommended amounts (N = 18) and those who had acted as controls with no vegetables provided (N = 16) during a randomized, controlled trial. Nominal group technique (NGT) sessions were conducted to identify and prioritize perceived barriers and facilitators to following the DGA for vegetables. Responses from all NGT sessions were aggregated and grouped into major themes. Convenience, availability, cost, and knowledge were core facilitators in both groups, while motivation emerged as a facilitator only in the control group. Time, preference, and cost were core barriers in both groups, while availability emerged as a barrier only in the control group and social support a barrier only in the intervention group. The barriers and facilitators identified by the intervention group and the control group from the primary study differed in relative rankings, suggesting that the experience of consuming provided vegetables influenced the strength of the perceived barriers and facilitators. The multi-factorial nature of the identified barriers and facilitators underscores the importance of addressing individual, social, and environmental factors to increase vegetable consumption.     

国土空间规划下水利基础设施信息管理平台设计

加快建立国土空间规划体系并监督实施是党中央、国务院做出的重大部署,而水利基础设施空间布局对促进各类空间布局与水资源承载能力、防洪安全保障水平相适应,预留水利基础设施建设空间具有重要作用。为有效对接国土空间规划编制工作,结合实际需求,研究并建立水利基础设施空间布局管理的标准、规范和体系,完成水利基础设施空间数据库的设计,并研究离线瓦片存储和Lucene全文检索引擎技术。在.Net框架的Visual Studio集成开发环境中,利用ArcGIS Engine组件开发水利基础设施信息管理平台,实现地图浏览、空间数据管理及数据质检分析功能,为统一水利空间用途管控、规划编制审批、实施监督管理提供数据支撑,也为下一步构建基础设施空间布局一张图管控平台提供坚实的基础与保障。     

Energy,exergy and ecological analysis and multiobjective optimization of the hydrogen-fueled Scimitar engine with fixed nozzle geometry

In this study, an energy, exergy and ecological analysis and multiobjective optimization of the Scimitar engine with fixed core nozzle outlet geometry are carried out at hypersonic cruise conditions. A single-objective optimization is performed first, which revealed that overall efficiency and coefficient of ecological performance are maximized with different optimum nozzle outlet areas, and it propounded the need for a multiobjective optimization. The single objective optimization also showed that decreasing the hydrogen fuel mass flow rate and cruise altitude together with increasing the air mass flow rate and cruise speed improve the performance of the engine. Then, the multiobjective optimization is performed with the utopia point method. It is concluded that for fuel and air mass flow rates of 3.99 kg/s and 178.6 kg/s, respectively, and cruise speed and altitude of Ma = 5.2 and 22 km, respectively, the optimum core nozzle outlet area is 4.00 m², when equal weight factors are used for overall efficiency and coefficient of ecological performance. A comparison with the base scenario results showed that the overall efficiency has increased from 55.1% to 57.3%, and the engine size is reduced from 5.38 m² to 4.00 m² with the multiobjective optimization.     

Multi-objective planning and optimization of microgrid lithium iron phosphate battery energy storage system consider power supply status and CCER transactions

Lithium iron phosphate battery (LIPB) is the key equipment of battery energy storage system (BESS), which plays a major role in promoting the economic and stable operation of microgrid. Based on the advancement of LIPB technology and efficient consumption of renewable energy, two power supply planning strategies and the china certified emission reduction (CCER) model are proposed respectively. Based on it, the multi-objective planning optimization model with economic benefits, environmental benefits and power supply stability as the objective function is established for the first time, and the Newton Weighted Sum Frisch method (NWSFA) solution model is adopted. In the planning process, rain flow counting method is used to research the life of BESS, which improves the accuracy of energy storage annual cost calculation. A park in northern China is taken as a case study to demonstrate the application of this model. The simulation results show that the annual economic operating cost of BESS is decreased by 18.81%, the energy supply reliability is increased by 0.15%, and the optimal electricity price adjustment ratio of the system is 15%.