Subjects: Library Science,Information Science >> Utilization of Information submitted time 2024-04-01
Abstract: Purpose/significance By utilizing the Data Citation Index (DCI) database, this article explores the reuse features and influencing factors of scientific data in the field of high-energy physics. These findings serve as a point of reference and support, facilitating the promotion of data sharing and citation standardization in China. Moreover, these contribute to the augmentation of both value and influence of scientific data. Method/process This article adopt statistical regression methods to analyze the basic and citation features of the DCI database. For the reuse features and influencing factors, the analysis includes three dimensions: scientific data attribute features, reuse features, and correlation between attribute and reuse features. Result/conclusion The research findings reveal that the publication volume of scientific data in the field of high-energy physics is exhibiting an increasing trend. However, the proportion of missing data fields is relatively high. The reuse of high-energy physics scientific data is significantly influenced by publication modes and disciplinary categories. These result in the extremely uneven distribution of citation frequency. High-level scientific data are more likely to be reused. Moreover, the standardization of scientific data sharing and citation needs further enhancement. Finally, we propose an optimization and improvement path for high-energy physics science data reuse based on this findings.
Peer Review Status:Awaiting Review
Subjects: Nuclear Science and Technology >> Nuclear Materials and Techniques submitted time 2024-03-25
Abstract: Background : Uranium dioxide (UO2) has been broadly employed as nuclear fuel in nuclear reactors. The poor thermal conductivity of UO2, however, reduces the safety of the reactor due to possible sharp temperature gradients. Graphene oxide (GO) is a kind of promising additive to improve the thermal conductivity of UO2 for its excellent thermal performance. Purpose : This work aimed at achieving uniform distribution of GO in UO2 pellets, effectively controlling the doping amounts, and finally enhancing the thermal conductivity of UO2 pellets. Methods : GO-doped UO2 powders with different doping amounts were prepared by solid-liquid mixing method and ammonium diuranate (ADU) co-precipitation method. After selecting the optimized powdering process, the UO2-GO composite fuel pellets were prepared by spark plasma sintering (SPS). The properties of the UO2-GO composite fuel pellets, such as density, grain size, physical phase, thermal conductivity, etc., were examined and compared with that of the conventional pure UO2 pellets. Results : The results showed that the density of UO2-GO pellets could reach up to 97.6% T.D. The thermal conductivity of UO2-GO pellets with 1.5 wt. % doped GO was 85.9% higher than that of conventional UO2 pellets at 1000 ℃. The grain size of the UO2-GO pellets was uniform, and the GO was homogeneously distributed at the grain boundary to form a bridging thermal conduction network. Conclusions : The thermal conductivity of the UO2 pellets was successfully improved through GO doping.
Peer Review Status:Awaiting Review
Subjects: Library Science,Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract: [Purpose/Significance] By studying the characteristics and laws of knowledge diffusion of scientific datasets, this paper explores the practical role of scientific datasets in the development of discipline fields, so as to provide references for scientific and technological evaluation and management policy-making of scientific datasets. [Method/Process] Taking the datasets of GEO database and the full-text data of reused dataset in PubMed Central Database as the analysis objects, this paper analyzed the knowledge diffusion characteristics of scientific datasets by using content analysis method combined with knowledge diffusion indicators such as diffusion breadth, diffusion intensity and diffusion speed. [Result/Conclusion] The results show that the breadth and intensity of knowledge diffusion of scientific datasets are increasing day by day. Reusing data can accelerate the speed of knowledge diffusion, and China’s position in the field of global scientific data is improving.
Subjects: Library Science,Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract: [Purpose/Significance] This paper analyzes the use characteristics of scientific datasets from the perspective of quantitative analysis and content analysis, quantitatively evaluates the impact of scientific datasets on discipine development, and provides references for scientific data management services and policy research.[Method/Process] Methods of text mining and bibliometric were used to analyze the full-text literature in PubMed Central, this study comprehensively investigated the use of scientific datasets from 7 aspects such as time distribution and use intensity, and on this basis, evaluated the actual impact of scientific datasets on discipline development.[Result/Conclusion] The research results show that the influence of scientific datasets on scientific research in the biomedical field is increasing with each passing day. Data publishing and high-level journals promote the opening and sharing of scientific datasets. The use of scientific datasets is concentrated in the second half of the paper and there are few formal references. The corresponding standards and specifications need to be further strengthened.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-05-18 Cooperative journals: 《计算机应用研究》
Abstract: As Software Defined Network (SDN) is increasingly widely used in various scenarios, a new challenge for SDN to support dynamic requirements of various applications begin to emerge. Digital Twin (DT) can enhance the capabilities of SDN in aspects of real-time analysis, deduction, and network control, and consequently satisfy the dynamic requirements of various applications. Whereas, current DT constructing schemes for SDN usually suffer from the challenges of strict delay constraint, heavy computing overhead, and low cooperating efficiency. To address the above issue, this paper proposes a novel Variable Granularity-Digital Twin (VGDT) according to the application requirement and available computing resource. Based on the distribution characteristic of the computing resource in the network, VGDT builds a cooperatively optimizing model to ensure the delay and effectiveness of the DT for SDN. Then, this paper proposes a hybrid coding genetic algorithm to solve this model, which can achieve the best granularity and the DT placement policy. The simulation results show the performance of VGDT. Compared with current DT, VGDT has higher integrity and validity of digital twin model under limited computing resource.
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc. submitted time 2017-03-23
Abstract:摘要: 目的 介绍“中国彩巢计划:成长在中国(Chinese Color Nest Project – CCNP: Growing Up in China 2013-2022)”大型学龄儿童青少年脑与行为生长曲线项目。 方法 在全国范围内分期分步地开展毕生发展各年龄段的心理行为与脑影像样本积累,未来十年 CCNP 将基于加速纵向实验设计方法,建立中国人脑毕生发展的常模轨线。 结果 作为“彩巢”计划的脑发育项目,devCCNP 已经完成对重庆北碚区 192 名健康儿童青少年(6-18 岁)的 5 年追踪。 结论 devCCNP就实验设计、样本采集策略、数据获取和存储、初步结果和数据共享等方面都说明本计划具备长期实施的可行性。
Peer Review Status:Awaiting Review