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Creators/Authors contains: "Jeni, L."

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  1. Light Field Networks, the re-formulations of radiance fields to oriented rays, are magnitudes faster than their coordinate network counterparts, and provide higher fidelity with respect to representing 3D structures from 2D observations. They would be well suited for generic scene representation and manipulation, but suffer from one problem: they are limited to holistic and static scenes. In this paper, we propose the Dynamic Light Field Network (DyLiN) method that can handle non-rigid deformations, including topological changes. We learn a deformation field from input rays to canonical rays, and lift them into a higher dimensional space to handle discontinuities. We further introduce CoDyLiN, which augments DyLiN with controllable attribute inputs. We train both models via knowledge distillation from pretrained dynamic radiance fields. We evaluated DyLiN using both synthetic and real world datasets that include various non-rigid deformations. DyLiN qualitatively outperformed and quantitatively matched state-of-the-art methods in terms of visual fidelity, while being 25 - 71x computationally faster. We also tested CoDyLiN on attribute annotated data and it surpassed its teacher model. Project page: https://dylin2023.github.io. 
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    Free, publicly-accessible full text available June 1, 2024
  2. We investigated whether a growth mindset intervention could be leveraged to promote performance and interest in computer science, through what mechanisms it might do so, and whether effects were stronger for women than for men. In particular, we explored whether the growth mindset intervention improved academic performance and career interest by increasing intrinsic value. We developed and tested a scalable, online, 4-session growth mindset intervention at 7 universities, across 16 introductory computer science classes ( N = 491). The intervention did not have a significant total effect on academic performance, although it indirectly improved grades via value. Additionally, the intervention, relative to the control, improved interest in the field and value also mediated this effect. Counter to expectations, the intervention worked equally well for women and men. Theoretical and practical applications are discussed.

     
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  3. Abstract

    Azanone (HNO) is a reactive nitrogen species with pronounced biological activity and high therapeutic potential for cardiovascular dysfunction. A critical barrier to understanding the biology of HNO and furthering clinical development is the quantification and real‐time monitoring of its delivery in living systems. Herein, we describe the design and synthesis of the first chemiluminescent probe for HNO,HNOCL‐1, which can detect HNO generated from concentrations of Angeli's salt as low as 138 nmwith high selectivity based on the reaction with a phosphine group to form a self‐cleavable azaylide intermediate. We have capitalized on this high sensitivity to develop a generalizable kinetics‐based approach, which provides real‐time quantitative measurements of HNO concentration at the picomolar level.HNOCL‐1can monitor dynamics of HNO delivery in living cells and tissues, demonstrating the versatility of this method for tracking HNO in living systems.

     
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  4. Abstract

    Azanone (HNO) is a reactive nitrogen species with pronounced biological activity and high therapeutic potential for cardiovascular dysfunction. A critical barrier to understanding the biology of HNO and furthering clinical development is the quantification and real‐time monitoring of its delivery in living systems. Herein, we describe the design and synthesis of the first chemiluminescent probe for HNO,HNOCL‐1, which can detect HNO generated from concentrations of Angeli's salt as low as 138 nmwith high selectivity based on the reaction with a phosphine group to form a self‐cleavable azaylide intermediate. We have capitalized on this high sensitivity to develop a generalizable kinetics‐based approach, which provides real‐time quantitative measurements of HNO concentration at the picomolar level.HNOCL‐1can monitor dynamics of HNO delivery in living cells and tissues, demonstrating the versatility of this method for tracking HNO in living systems.

     
    more » « less