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This report may be regarded as a follow up to the previous ICFA Standing Committee on Inter-regional Connectivity (SCIC) Monitoring working group’s Network reports dating back to 1997. The current report updates the January 2015 report. As noted, PingER activities will not be covered in the same depth as earlier reports because of a lack of funding for this effort. We will be including some new areas related to network monitoring in HEP including updates and status on the perfSONAR efforts globally as well as the WLCG Network and Transfer Metrics Working Group activities.

この論文は国立情報学研究所の電子図書館事業により電子化されました。, ポスターセッション

A molecular dynamics (MD) simulation, which includes all degrees of freedom of atomic motion, has been performed for liquid tetrachloromethane (CCl4) over the wide temperature range from 261.26 (near melting point) to 557.43 K (near critical temperature). The translational diffusion coefficient D of the molecular center-of-mass and first and second rank reorientational correlation times 〓1R(l = 1, 2) of the unit vector along the C-C1 axes are simulated at four temperatures. The simulated activation energies Ea values for both D and 〓2R are in better agreement with the experimental ones than our previous simulated ones, and it has been found that our simulation model is reasonable and well reproduced in the real liquid CCl4.

We describe a Magnetic Resonance Imaging (MRI) dataset from individuals from the African nation of Nigeria. The dataset contains pseudonymized structural MRI (T1w, T2w, FLAIR) data of clinical quality. Dataset contains data from 36 images from healthy control subjects, 32 images from individuals diagnosed with age-related dementia and 20 from individuals with Parkinson's disease. There is currently a paucity of data from the African continent. Given the potential for Africa to contribute to the global neuroscience community, this first MRI dataset represents both an opportunity and benchmark for future studies to share data from the African continent., Competing Interests: Competing Interests The authors declare no competing interests.

Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research., Competing Interests: Competing interests. The authors declare no competing financial interests.