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  1. Placing and orienting a camera to compose aesthetically meaningful shots of a scene is not only a key objective in real-world photography and cinematography but also for virtual content creation. The framing of a camera often significantly contributes to the story telling in movies, games, and mixed reality applications. Generating single camera poses or even contiguous trajectories either requires a significant amount of manual labor or requires solving highdimensional optimization problems, which can be computationally demanding and error-prone. In this paper, we introduce GAIT, a Deep Reinforcement Learning (DRL) agent, that learns to automatically control a camera to generate a sequence of aesthetically meaningful views for synthetic 3D indoor scenes. To generate sequences of frames with high aesthetic value, GAIT relies on a neural aesthetics estimator, which is trained on a crowed-sourced dataset. Additionally, we introduce regularization techniques for diversity and smoothness to generate visually interesting trajectories for a 3D environment, and to constrain agent acceleration in the reward function to generate a smooth sequence of camera frames. We validated our method by comparing it to baseline algorithms, based on a perceptual user study, and through ablation studies. The source code of our method will be released with the final version of our paper. 
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    Free, publicly-accessible full text available October 1, 2024
  2. Abstract

    The current best upper limit for electron electric dipole moment (EDM), |de| < 1.1 × 10−29e cm (90% confidence), was set by the ACME Collaboration in 2018. The ACME experiment uses a spin-precession measurement in a cold beam of thorium monoxide (ThO) molecules to detectde. An improvement in statistical uncertainty would be possible with more efficient use of molecules from the cryogenic buffer gas beam source. Here, we demonstrate electrostatic focusing of the ThO beam with a hexapole lens. This results in a factor of 16 enhancement in the molecular flux detectable downstream, in a beamline similar to that built for the next generation of ACME. We also demonstrate an upgraded rotational cooling scheme that increases the ground state population by 3.5 times compared to no cooling, consistent with expectations and a factor of 1.4 larger than previously in ACME. When combined with other demonstrated improvements, we project over an order of magnitude improvement in statistical sensitivity for the next generation ACME electron EDM search.

     
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  3. Spatial information understanding is fundamental to visual perception in Metaverse. Beyond the stereoscopic visual cues naturally carried in Metaverse, the human vision system may use other auxiliary information provided by any shadow casting or motion parallax available to perceive the 3D virtual world. However, the combined use of shadows and motion parallax to improve 3D perception have not been fully studied. In particular, when visualizing the combination of volumetric data and associated skeleton models in VR, how to provide the auxiliary visual cues to enhance observers’ perception of the structural information is a key yet underexplored topic. This problem is particularly challenging for visualization of data in biomedical research. In this paper, we focus on immersive analytics in neurobiology where the structural information includes the relative position of objects (nuclei / cell body) in the 3D space and the spatial measurement and connectivity of segments (axons and dendrites) in a model. We present a perceptual experiment designed for understanding the consequence of shadow casting and motion parallax in the neuron structures observation and the feedback and analysis of the experiment are reported and discussed. 
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  4. A concentration-gradient composition is proposed as an effective approach to solve the mechanical degradation and improve the electrochemical cyclability for cathodes of sodium-ion batteries. Concentration-gradient shell NaxNiyMn1-yFe(CN)6·nH2O, in which the Ni content gradually increases from the interior to the particle surface, is synthesized by a facile co-precipitation process. The as-obtained cathode exhibits an improved electrochemical performance compared to homogeneous NaxMnFe(CN)6·nH2O, delivering a high reversible specific capacity of 110 mA h g-1 at 0.2 C and outstanding cycling stability (93% retention after 1000 cycles at 5 C). The improvement of electrochemical performance can be attributed to its robust microstructure that effectively alleviates the electrochemically induced stresses and accumulated damage during sodiation/desodiation and thus prevents the initiation of fracture in the particles upon long term cycling. These findings render a prospective strategy to develop high-performance electrode materials for sodium-ion batteries. 
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  5. Face detection and recognition benchmarks have shifted toward more difficult environments. The challenge presented in this paper addresses the next step in the direction of automatic detection and identification of people from outdoor surveillance cameras. While face detection has shown remarkable success in images collected from the web, surveillance cameras include more diverse occlusions, poses, weather conditions and image blur. Although face verification or closed-set face identification have surpassed human capabilities on some datasets, open-set identification is much more complex as it needs to reject both unknown identities and false accepts from the face detector. We show that unconstrained face detection can approach high detection rates albeit with moderate false accept rates. By contrast, open-set face recognition is currently weak and requires much more attention. 
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  6. Abstract The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org . The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages. 
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    Free, publicly-accessible full text available July 28, 2024