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We summarize recent progress toward the next generation of CTEQ-TEA parton distribution functions, CT25, based on a global NNLO analysis that incorporates a significant sample of newly included LHC data. We present a baseline fit within the forthcoming full CT25 fit, which includes new Drell-Yan, top-pair, and inclusive-jet data at 8 and 13 TeV, and exhibits non-trivial pulls on the high-𝑥 gluon and the flavor structure of the quark sea. In the context of progress toward CT25, we also summarize several recent and ongoing studies of the interplay between phenomenological PDFs and lattice-QCD calculations, simultaneous extractions of 𝛼𝑠 (𝑀𝑍) within the CT framework, and an expanded program of uncertainty quantification that treats parametrization dependence as an explicit source of epistemic uncertainty, among other issues. We also briefly highlight CT efforts to understand the effects of partial implementations of N3LO corrections into PDF fits, which include benchmark calculations for Higgs and vector-boson processes. We comment on the implications of recent improvements to the CT analysis for precision phenomenology at the LHC and future facilities. 

We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on the DT focus on its “eyes,” which is the emerging sensing and perception like object detection and tracking, what really distinguishes the DT from a traditional simulator lies in its “brain,” the prediction and decision making capabilities of extracting patterns and making informed decisions from what has been seen and perceived. In order to add value to urban transportation management, DTs need to be powered by artificial intelligence and complement with low-latency highbandwidth sensing and networking technologies, in other words, cyberphysical systems (CPS). We will first review the DT pipeline enabled by CPS and propose our DT architecture deployed on a real-world testbed in New York City. This paper can be a pointer to help researchers and practitioners identify challenges and opportunities for the development of DTs; a bridge to initiate conversations across disciplines; and a road map to exploiting potentials of DTs for diverse urban transportation applications.