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The Non-Clinical Tomography Users Research Network (NoCTURN) was established in 2022 to advance Findability, Accessibility, Interoperability, and Reuse (FAIR) and Open Science (OS) practices in the computed tomographic (CT) imaging community. CT specialists utilize a shared pipeline to create digital representations of real-world objects for research, education, and outreach, and we face a shared set of challenges and limitations imposed by siloing of current workflows, best practices, and expertise. Mirroring the U.S. National Science Foundation’s “10 Big Ideas” of Convergence Research (2016), and in consideration of the White House Office of Science and Technology Policy's Nelson Memorandum (2020), NoCTURN is leveraging input from a broad community of more than 100 CT educators, researchers, curators, and industry stakeholders to propose improvements to data handling, management, and sharing that cut across scientific disciplines and extend beyond. Our primary goal is to develop practical recommendations and tools that link today's CT data to tomorrow's CT discoveries. NoCTURN is working toward this goal by providing a platform to: 1) engage the international scientific CT community via participant recruitment from imaging facilities, academic departments and museums, and data repositories across the globe; 2) stimulate improvements for CT imaging and data management standards that focus on FAIR and OS principles; and 3) work directly with private companies that manufacture the hardware and software used in CT imaging, visualization, and analysis to find common ground in documentation and interoperability that better reflects the OS standards championed by federal funding agencies. The planned deliverables from this three-year grant include a ‘Rosetta Stone’ for CT terminology, an interactive world map of CT facilities, a guide to CT repositories, and ‘Good, Better, Best’ guidelines for metadata and long-term data management. We aim to reduce the barriers to entry that isolate individuals and research labs, and we anticipate that developing community standards and improving methodological reporting will enable long-term, systemic changes necessary to aid those at all levels of experience in furthering their access to and use of CT imaging. 

Digital publishing platforms and internet resources enable openness of access to scientific findings and data at scales never before realized. Unfortunately, researchers sometimes embrace lock-in systems for data generation and analysis out of necessity because meaningful alternatives do not exist. Scientific advances still take place when this occurs, but they become fragmented with discordant quality control, interoperability, reproducibility, and democratization of access. To maximize the value of these—often—publicly funded resources, disciplines are turning to FAIR Guiding Principles for data stewardship. FAIR (Findability, Accessibility, Interoperability, and Reuse) promotes the added value of widespread data sharing that is transparent, equitable, and inclusive. Here we present NoCTURN, an NSF-funded FAIR Open Science Research Coordination Network for computed tomography users. NoCTURN (the Non-clinical Computed Tomography Users Research Network) aims to address the fragmentation of tomography toolkits stemming from proprietary software, non-uniform metadata formats, and repeatability limits. In this presentation, we outline how we will achieve this aim together by 1) developing a community committed to information sharing; 2) coordinating data analysis, storage, and reporting requirements; 3) highlighting underrepresented voices in the field; 4) developing community standards inclusive of industry, research, education, and outreach stake-holders; and 5) modeling FAIR open science strategies for our colleagues and students. NoCTURN is recruiting undergraduates through established investigators from X-ray-, neutron-, and synchrotron-beam computed tomography communities—and we want to hear from you. 

Recent new constructions of rate-1 OT [Döttling, Garg, Ishai, Malavolta, Mour, and Ostrovsky, CRYPTO 2019] have brought this primitive under the spotlight and the techniques have led to new feasibility results for private-information retrieval, and homomorphic encryption for branching programs. The receiver communication of this construction consists of a quadratic (in the sender's input size) number of group elements for a single instance of rate-1 OT. Recently [Garg, Hajiabadi, Ostrovsky, TCC 2020] improved the receiver communication to a linear number of group elements for a single string-OT. However, most applications of rate-1 OT require executing it multiple times, resulting in large communication costs for the receiver. In this work, we introduce a new technique for amortizing the cost of multiple rate-1 OTs. Specifically, based on standard pairing assumptions, we obtain a two-message rate-1 OT protocol for which the amortized cost per string-OT is asymptotically reduced to only four group elements. Our results lead to significant communication improvements in PSI and PIR, special cases of SFE for branching programs. - PIR: We obtain a rate-1 PIR scheme with client communication cost of $$O(\lambda\cdot\log N)$$ group elements for security parameter $$\lambda$$ and database size $$N$$. Notably, after a one-time setup (or one PIR instance), any following PIR instance only requires communication cost $$O(\log N)$$ number of group elements. - PSI with unbalanced inputs: We apply our techniques to private set intersection with unbalanced set sizes (where the receiver has a smaller set) and achieve receiver communication of $$O((m+\lambda) \log N)$$ group elements where $m, N$ are the sizes of the receiver and sender sets, respectively. Similarly, after a one-time setup (or one PSI instance), any following PSI instance only requires communication cost $$O(m \cdot \log N)$$ number of group elements. All previous sublinear-communication non-FHE based PSI protocols for the above unbalanced setting were also based on rate-1 OT, but incurred at least $$O(\lambda^2 m \log N)$$ group elements.