No abstract

According to the estimated data rates, it is predicted that 24 PB raw experimental data will be produced per month from 14 beamlines at the first stage of the High-Energy Photon Source (HEPS) in China, and the volume of experimental data will be even greater with the completion of over 90 beamlines at the second stage in the future. To make sure that the huge amount of data collected at HEPS is accurate, available and accessible, an effective data management system (DMS) is crucial for deploying the IT systems. In this article, a DMS is designed for HEPS which is responsible for automating the organization, transfer, storage, distribution and sharing of the data produced from experiments. First, the general situation of HEPS is introduced. Second, the architecture and data flow of the HEPS DMS are described from the perspective of facility users and IT, and the key techniques implemented in this system are introduced. Finally, the progress and the effect of the DMS deployed as a testbed at beamline 1W1A of the Beijing Synchrotron Radiation Facility are shown.

Daisy (Data Analysis Integrated Software System) has been designed for the analysis and visualisation of X-ray experiments. To address the requirements of the Chinese radiation facilities community, spanning an extensive range from purely algorithmic problems to scientific computing infrastructure, Daisy sets up a cloud-native platform to support on-site data analysis services with fast feedback and interaction. Furthermore, the plug-in based application is convenient to process the expected high throughput data flow in parallel at next-generation facilities such as the High Energy Photon Source (HEPS). The objectives, functionality and architecture of Daisy are described in this article.

CO2 emissions reduction has long been discussed, since the problem is one of the most urgent issues we human beings are faced with in the 21st century. Time-sharing electric vehicles (TSEVs), combining the benefits of cleaner energy and more sufficient utilization, are considered a sustainable future transportation tool, with increasing support from governments around the world. Although numerous studies have been carried out in this domain, few have studied the development process, considering the inverse interrelations, including the policy implementation effects and user choice, in a dynamic way. This research fills the previous academic gap and presents a system dynamics (SD) model incorporating scenario analysis to simulate the effect of introducing time-sharing electric vehicles in changing the user quantities in transportation tools, including public and private sectors, under different levels of government subsidies, thus providing policy implications and ex-ante assessment for the subsidies. The results suggest that it is not the greater the subsidy, the better the effect. Considering that one of the purposes of introducing TSEVs is to reduce private vehicles, there is a threshold for user transfer. It is actually under low subsidy that private internal combustion engine vehicle (ICV) users are most attracted to the TSEVs compared to the medium and high ones. The gap between the simulation results and common sense reminds us that ex-ante assessment and overall planning in the process of industry development are necessary.