The VLA Sky Survey (VLASS) is a comprehensive radio survey covering the sky visible to the VLA, conducted in three epochs with a focus on imaging galaxies, detecting transient events, exploring Faraday tomography, and uncovering hidden phenomena in the universe. The survey employs innovative strateg

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This collection delves into the complex interplay between technology and society, contrasting the deterministic view with the idea of reciprocal shaping. It examines various epochs from pre-modernity to the information age, highlighting how technology has influenced cultural shifts and modernity its

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The RCRL group at the University of Texas at Austin specializes in research on carbonate reservoirs at various scales, from nanopores to basin architecture. They focus on developing predictive relationships and tools for reservoir characterization based on subsurface datasets and outcrop analogs. Th

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The document discusses a proposal for IEEE 802.11-23/1984r1 TGbi focusing on coordinated MAC rotation, EDP epochs, anonymity sets, and group epochs. It introduces concepts like individual and mass rotations, anonymity set size, and hiding in the crowd examples. The coordination for group epochs and

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Trigger discussion on differences between group and individual epochs in IEEE 802.11 standards. Group epochs involve simultaneous transitions of MAC parameters by all or selected STAs based on AP trigger, while individual epochs allow each STA to independently change its parameters. Key points inclu

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Explore the key epochs of the Cenozoic Era, including Eocene, Oligocene, Miocene, Pliocene, and Pleistocene, each characterized by distinct geological and biological changes over millions of years. Follow the evolution of Earth's climate, flora, and fauna through captivating images representing each

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This proposal by Stephen Rodriguez from Cisco suggests partitioning time into epochs based on network trust levels to determine when clients should change their MAC addresses dynamically. The idea involves rotating MAC addresses at specified intervals depending on the trust level of the network conn

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In the context of training recurrent networks, Epochwise Back Propagation Through Time involves dividing the data set into independent epochs, each representing a specific temporal pattern of interest. The start time of each epoch, denoted by 'no', is crucial for capturing the sequential dependencie

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