A Solving Algorithm for Nonlinear Bilevel Programing Problems Based on Human Evolutionary Model

An algorithm based on the human evolutionary model is proposed for solving nonlinear bilevel programing problems. In view of the hierarchical structure of this problem, the algorithm is designed through feeding back the optimal solution of the lower-level problem to the upper-level. Based on the quality of individuals at each iteration, this proposed algorithm can independently change the population size to achieve the balance between global and local searching ability during the progress of evolution, which can perform an exhaustive search in the whole landscape through creating an individual by using the tabu search method. Finally, we test four typical bilevel programing problems by using the proposed algorithm to verify its feasibility. The experimental results indicate the proposed algorithm can not only solve bilevel programing problems but also get the global optimal solution

An Analysis on Barriers to Biomass and Bioenergy Development in Rural China Using Intuitionistic Fuzzy Cognitive Map

Biomass is viewed as one of the critical renewable energies and it widely exists in nature. Developing bioenergy has been promoted as a viable mean of dealing with environment issues that are related to the utilization of fossil fuel. However, due to many obstacles, the biomass and bioenergy technology has not won widespread support in developing countries, like China, with vast land area, particularly in rural area. Furthermore, most existing researches just focused on the description of the influence factors, along with the solution to the technical problems, while many social factors are overlooked. In fact, the process of developing biomass is indeed complicated due to the need for consensus and active participation of the various stakeholders, such as the government, the industry, and the local residents. Therefore, while integrating the intuitionistic fuzzy logic and fuzzy cognitive map, this study constructs an intuitionistic fuzzy cognitive map (IFCM) that is in line with experts’ suggestions and the current literature to investigate how to promote the development of biomass through enhancing public acceptance. We conduct several simulations from the perspective of different stakeholders, according to the IFCM. The analysis results reveal the influence mechanism in the system and illustrate the effect of various factors that are stressed by every stakeholder. The research design also provides a reference for future studies

How can fuel cell vehicles bring a bright future for this dragon? Answer by multi-criteria decision making analysis

Fuel Cell Vehicles (FCVs) has been introduced to the market around the world in recent years. As the largest automobile market of the world, China is also one of the potential FCVs market. However, a series of factors and barriers influence the willingness of China's customers to accept FCVs. By using Fishbone Diagram, field survey and workshop discussions, this paper proposes a group of factors that may affect customers' preferences on FCVs. Furthermore, Fuzzy AHP and Pareto Analysis are employed to prioritize these factors, and identify the critical ones. The results indicate that fuel availability, vehicle performance, and economic costs are the most important dimensions in affecting customers' attitude towards FCVs. More specifically, vehicle reliability and safety, purchasing cost, industry development, vehicle model and space contribute the most significance in customers' purchase decision. According to the results, some policy implications are proposed from the prospective of improving and demonstrating vehicle performance, government leading facility construction and operation, and costs reductions. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved

Cobalt phosphide nanowires as efficient near-infrared light-driven antibacterial agents with high stability and cytocompatibility

Rapid emergence of antibiotic-resistant bacteria has brought huge threat to global healthcare systems. Alternative strategies are urgently needed to fight against these superbugs. In this study, we synthesized a series of cobalt phosphide nanoarchitectures and characterized their physicochemical properties as well as their antibacterial activities. We found that all nanomaterials showed an impressive photothermal property as indicated by their strong near-infrared (NIR) absorption capacity. In particular, 1D-CoP nanowires exhibited the optimal photothermal efficiency due to their higher aspect ratio. Under NIR light illumination, the temperature of the 1D-CoP nanowires suspension was increased by 45.4 °C within 20 min. In contrast, the temperatures of 2D-CoP nanoplates and 3D-CoP nanocubes were increased by 25.5 °C and 26.9 °C, respectively. The growth of planktonic bacteria can be effectively inhibited by 99% within 30 min under NIR irradiation with the presence of 1D-CoP nanowires in suspension. In comparison, up to 60% of the bacteria could be killed when treated with 2D-CoP nanoplates and 3D-CoP nanocubes. Moreover, all nanomaterials displayed high cytocompatibility. This work emphasizes that the anisotropy plays an important role in governing the photothermal properties of NIR-driven materials. Furthermore, the application of CoP nanowires is a promising strategy to treat antibiotic-resistant bacteria

Critical Mineral Security in China: An Evaluation Based on Hybrid MCDM Methods

With economic globalization, the supply-and-demand gap of China’s minerals is becoming increasingly sharp, and the degree of dependence on imports is climbing, which poses a severe threat to the resource security for the country. From the perspectives of system and sustainable development, this paper develops a conceptual framework of mineral security, which is composed of five dimensions: availability, accessibility, technology and efficiency, sociability and governance, and environmental sustainability. Based on this framework, it constructs the evaluating metrics for measuring mineral security. Moreover, it employs the hybrid multiple criteria decision-making methods of Fuzzy analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) to assess the security performance for China’s several critical minerals, namely iron, copper, aluminum, lead, zinc, and nickel, with respect to the period of 2001 to 2015. The result indicates that the critical minerals of China were at a low to moderate level of security. Iron, copper, and nickel were in an unsecure situation for their short supply in China, and showed a downswing trend. On the other hand, as the preponderant minerals, lead and zinc were at a relatively secure position and uprising; however, they were exhausting their superiority for the huge and rapid-growth economic demand. Aluminum, as a mineral that China seriously depends on for imports, also demonstrated an upward trend due to the successful management of diversity of importing sources

Recent intensified erosion and massive sediment deposition in Tibetan Plateau rivers

Abstract Recent climate change has caused an increase in warming-driven erosion and sediment transport processes on the Tibetan Plateau (TP). Yet a lack of measurements hinders our understanding of basin-scale sediment dynamics and associated spatiotemporal changes. Here, using satellite-based estimates of suspended sediment, we reconstruct the quantitative history and patterns of erosion and sediment transport in major headwater basins from 1986 to 2021. Out of 13 warming-affected headwater regions, 63% of the rivers have experienced significant increases in sediment flux. Despite such intensified erosion, we find that 30% of the total suspended sediment flux has been temporarily deposited within rivers. Our findings reveal a pronounced spatiotemporal heterogeneity within and across basins. The recurrent fluctuations in erosion-deposition patterns within river channels not only result in the underestimation of erosion magnitude but also drive continuous transformations in valley morphology, thereby endangering local ecosystems, landscape stability, and infrastructure project safety

LeafNet : a tool for segmenting and quantifying stomata and pavement cells

Stomata play important roles in gas and water exchange in leaves. The morphological features of stomata and pavement cells are highly plastic and are regulated during development. However, it is very laborious and time-consuming to collect accurate quantitative data from the leaf surface by manual phenotyping. Here, we introduce LeafNet, a tool that automatically localizes stomata, segments pavement cells (to prepare them for quantification), and reports multiple morphological parameters for a variety of leaf epidermal images, especially bright-field microscopy images. LeafNet employs a hierarchical strategy to identify stomata using a deep convolutional network and then segments pavement cells on stomata-masked images using a region merging method. LeafNet achieved promising performance on test images for quantifying different phenotypes of individual stomata and pavement cells compared with six currently available tools, including StomataCounter, Cellpose, PlantSeg, and PaCeQuant. LeafNet shows great flexibility, and we improved its ability to analyze bright-field images from a broad range of species as well as confocal images using transfer learning. Large-scale images of leaves can be efficiently processed in batch mode and interactively inspected with a graphic user interface or a web server (https://leafnet.whu.edu.cn/). The functionalities of LeafNet could easily be extended and will enhance the efficiency and productivity of leaf phenotyping for many plant biologists