Cost/Benefit Assessment of a Smart Distribution System With Intelligent Electric Vehicle Charging

In the near future, with more distributed generators connected and new demands arising from the electrification of heat and transport in the distribution networks, infrastructure will become ever more stressed. However, building costly new circuits to accommodate generation and demand growth is time-consuming and environmentally unfriendly. Therefore, active network management (ANM) has been promoted in many countries, aiming to relieve network pressure. Previous research in ANM was focused on distribution areas with significant renewable penetration, where ANM reduced network pressure through significantly enhanced generation curtailment strategies rather than adopting traditional asset investment. This paper proposes the use of electric vehicles (EVs) as responsive demand to complement network stress relief that was purely based on generation curtailment. It is achieved by allowing EVs to absorb excessive renewable generation when they cause network pressure, and it thus can provide additional measures to generation curtailment strategies. The approach is illustrated on a practical extra-high voltage distribution system. The analyses clearly demonstrate the combined management of demand and generation is superior to previous sole generation management. The combined management strategy can achieve 7.9% improvement in utilization of renewable energy, and subsequently increase the net investment profit by £566 k

Microfiber Coupler Based Biosensor Incorporating a Layer of Gold Nanoparticles with Improved Sensitivity

We studied the effect of a star-shaped gold nanoparticles layer coated on the surface of the microfiber coupler (MFC) on the sensitivity of the embedded MFC biosensor. It is shown that deposition of the layer of star-shaped gold nanoparticles on the MFC sensor surface results in a significantly increased spectral shift (on average 3.05 nm shift compared to a 1.08 nm shift per layer of electrolyte for the sample without the nanoparticles layer). In addition, introducing the nanoparticle layer results in the decrease of the transmission power; measurement of the changes in transmission also could be used as a means for the sensor interrogation

M2-Encoder: Advancing Bilingual Image-Text Understanding by Large-scale Efficient Pretraining

Vision-language foundation models like CLIP have revolutionized the field of artificial intelligence. Nevertheless, VLM models supporting multi-language, e.g., in both Chinese and English, have lagged due to the relative scarcity of large-scale pretraining datasets. Toward this end, we introduce a comprehensive bilingual (Chinese-English) dataset BM-6B with over 6 billion image-text pairs, aimed at enhancing multimodal foundation models to well understand images in both languages. To handle such a scale of dataset, we propose a novel grouped aggregation approach for image-text contrastive loss computation, which reduces the communication overhead and GPU memory demands significantly, facilitating a 60% increase in training speed. We pretrain a series of bilingual image-text foundation models with an enhanced fine-grained understanding ability on BM-6B, the resulting models, dubbed as $M^2$-Encoders (pronounced "M-Square"), set new benchmarks in both languages for multimodal retrieval and classification tasks. Notably, Our largest $M^2$-Encoder-10B model has achieved top-1 accuracies of 88.5% on ImageNet and 80.7% on ImageNet-CN under a zero-shot classification setting, surpassing previously reported SoTA methods by 2.2% and 21.1%, respectively. The $M^2$-Encoder series represents one of the most comprehensive bilingual image-text foundation models to date, so we are making it available to the research community for further exploration and development

Study on the efficiency evolution trend of coordinated development of the human–earth system in minority areas of Yunnan, China

IntroductionImproving the development efficiency of human–earth systems is a practical requirement for achieving high-quality regional development.MethodsThe article designs a data envelopment analysis (DEA) model under the constraints of coordinated development degree from the perspective of the interaction of natural, economic and social systems to evaluate the development efficiency of human–earth systems and uses GA-BP neural network model for the prediction of the development efficiency of the human–earth system of each geographical unit from 2018 to 2025 based on the panel data of the 8 ethnic autonomous prefectures in Yunnan Province form 1995 to 2017.ResultsThe study found that from 1995 to 2017, the coordination degree and the coordinated development degree of the human–earth system in Yunnan minority areas were on the rise, but mainly manifested in the coordination of low development degree, and the average comprehensive efficiency value of input and output showed a downward trend. The prediction results for 2018–2025 showed that the human–earth system in Yunnan minority areas will be at a low efficient coordinated development level, and the coordinated development degree will show a downward trend. The development degree of natural subsystems in many ethnic minority areas showed negative growth and was negatively correlated with the development degree of economic and social subsystems. In 2025, except Honghe and Banna, the other six regions will be inefficient regions. Among these six inefficient regions, only Wenshan has input redundancy in the natural subsystem, but the phenomenon of input redundancy in the economic subsystem and insufficient output in the natural subsystem is common, indicating that industrial pollution has been controlled to a certain extent in most regions, but the economic investment mode and resource recycling efficiency need to be optimized and improved.DiscussionOur results could enrich the content of human–earth system characteristics in typical regions, and also provide theoretical support for regional coordinated development in China

Cost/Benefit Assessment of a Smart Distribution System With Intelligent Electric Vehicle Charging

In the near future, with more distributed generators connected and new demands arising from the electrification of heat and transport in the distribution networks, infrastructure will become ever more stressed. However, building costly new circuits to accommodate generation and demand growth is time-consuming and environmentally unfriendly. Therefore, active network management (ANM) has been promoted in many countries, aiming to relieve network pressure. Previous research in ANM was focused on distribution areas with significant renewable penetration, where ANM reduced network pressure through significantly enhanced generation curtailment strategies rather than adopting traditional asset investment. This paper proposes the use of electric vehicles (EVs) as responsive demand to complement network stress relief that was purely based on generation curtailment. It is achieved by allowing EVs to absorb excessive renewable generation when they cause network pressure, and it thus can provide additional measures to generation curtailment strategies. The approach is illustrated on a practical extra-high voltage distribution system. The analyses clearly demonstrate the combined management of demand and generation is superior to previous sole generation management. The combined management strategy can achieve 7.9% improvement in utilization of renewable energy, and subsequently increase the net investment profit by £566 k

High-Speed X-Ray Transmission and Numerical Study of Melt Flows inside the Molten Pool during Laser Welding of Aluminum Alloy

By using the X-ray transmission imaging system, melt flows inside a molten pool were studied during laser welding of aluminum alloy at different welding speeds. Then, the correlation between temperature gradients along the direction of weld penetration and melt flows in the rear part of a molten pool was analyzed by using a three-dimensional numerical method. And the presented model was verified by experimental results. The corresponding investigation was carried out to further study the correlation between temperature gradient and melt flow behavior of the molten pool in the plate heated by preheating temperature. The results indicated that, in the rear part of the molten pool, the maximum flow velocity was located at the bottom of the molten pool. The melt metal in the rear molten pool caused by different welding speeds had significantly different flow trends. As the welding speed increased, the absorbed intensity on the keyhole front wall also increased as well as the recoil pressure that could maintain the keyhole opened. Consequently, the increase of the welding speed was more beneficial to improving the stability of the molten pool

The Akebia Genus as a Novel Forest Crop: A Review of Its Genetic Resources, Nutritional Components, Biosynthesis, and Biological Studies

The genus Akebia belongs to the Lardizabalaceae family and comprises five species that are primarily distributed in East Asia. Plants of the Akebia genus comprise deciduous and semi-evergreen perennial twining vines that have been used in Chinese herbal medicine for at least 2000 years. The plants of this genus have the potential to form a novel forest crop with high nutritional and economic value because their fruit has a delicious sweet taste and rich nutrient components. In this study, we organized, analyzed, and evaluated the available published scientific literature on the botanical, ecological, and phytochemical characteristics of Akebia plants. Based on these studies, we briefly introduced botanical and ecological characteristics and focused on reviewing the development and utilization of wild genetic resources in the genus Akebia. We further explored the genus' rich nutritional components, such as triterpenes, flavonoids, polyphenols, polysaccharides, and fatty acids, and their potential use in food and health improvement applications. In addition, several papers describing advances in biotechnological research focusing on micropropagation, nutrient biosynthesis, and fruit ripeness were also included. This review provides comprehensive knowledge of the Akebia genus as a new forest crop for food and fruit utilization, and we also discuss future breeding and research prospects