657 research outputs found

    Constraint on intermediate-range gravity from earth-satellite and lunar orbiter measurements, and lunar laser ranging

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    In the experimental tests of gravity, there have been considerable interests in the possibility of intermediate-range gravity. In this paper, we use the earth-satellite measurement of earth gravity, the lunar orbiter measurement of lunar gravity, and lunar laser ranging measurement to constrain the intermediate-range gravity from lambda=1.2*10^{7}m - 3.8*10^{8}m. The limits for this range are alpha=10^{-8}-5*10^{-8}, which improve previous limits by about one order of magnitude in the range lambda=1.2*10^{7}m-3.8*10^{8}m.Comment: 8 pages, International Journal of Modern Physics D, in press (World Scientific, 2005

    G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification

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    Pathological glomerulus classification plays a key role in the diagnosis of nephropathy. As the difference between different subcategories is subtle, doctors often refer to slides from different staining methods to make decisions. However, creating correspondence across various stains is labor-intensive, bringing major difficulties in collecting data and training a vision-based algorithm to assist nephropathy diagnosis. This paper provides an alternative solution for integrating multi-stained visual cues for glomerulus classification. Our approach, named generator-to-classifier (G2C), is a two-stage framework. Given an input image from a specified stain, several generators are first applied to estimate its appearances in other staining methods, and a classifier follows to combine visual cues from different stains for prediction (whether it is pathological, or which type of pathology it has). We optimize these two stages in a joint manner. To provide a reasonable initialization, we pre-train the generators in an unlabeled reference set under an unpaired image-to-image translation task, and then fine-tune them together with the classifier. We conduct experiments on a glomerulus type classification dataset collected by ourselves (there are no publicly available datasets for this purpose). Although joint optimization slightly harms the authenticity of the generated patches, it boosts classification performance, suggesting more effective visual cues are extracted in an automatic way. We also transfer our model to a public dataset for breast cancer classification, and outperform the state-of-the-arts significantly.Comment: Accepted by AAAI 201

    Building Potent Chimeric Antigen Receptor T Cells With CRISPR Genome Editing

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    Chimeric antigen receptor (CAR) T cells have shown great promise in the treatment of hematological and solid malignancies. However, despite the success of this field, there remain some major challenges, including accelerated T cell exhaustion, potential toxicities, and insertional oncogenesis. To overcome these limitations, recent advances in CRISPR technology have enabled targetable interventions of endogenous genes in human CAR T cells. These CRISPR genome editing approaches have unleashed the therapeutic potential of CAR T cell therapy. Here, we summarize the potential benefits, safety concerns, and difficulties in the generation of gene-edited CAR T cells using CRISPR technology

    Emergent O(4) symmetry at the phase transition from plaquette-singlet to antiferromagnetic order in quasi-two-dimensional quantum magnets

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    Recent experiments [J. Guo et al., Phys. Rev. Lett.124,206602 (2020)] on thermodynamic properties of the frustrated layered quantum magnet SrCu2_2(BO3_3)2_2 -- the Shastry-Sutherland material -- have provided strong evidence for a low-temperature phase transition between plaquette-singlet and antiferromagnetic order as a function of pressure. Further motivated by the recently discovered unusual first-order quantum phase transition with an apparent emergent O(4) symmetry of the antiferromagnetic and plaquette-singlet order parameters in a two-dimensional "checkerboard J-Q" quantum spin model [B. Zhao et al., Nat. Phys. 15, 678 (2019)], we here study the same model in the presence of weak inter-layer couplings. Our focus is on the evolution of the emergent symmetry as the system crosses over from two to three dimensions and the phase transition extends from strictly zero temperature in two dimensions up to finite temperature as expected in SrCu2_2(BO3_3)2_2. Using quantum Monte Carlo simulations, we map out the phase boundaries of the plaquette-singlet and antiferromagnetic phases, with particular focus on the triple point where these two order phases meet the paramagnetic phase for given strength of the inter-layer coupling. All transitions are first-order in the neighborhood of the triple points. We show that the emergent O(4) symmetry of the coexistence state breaks down clearly when the interlayer coupling becomes sufficiently large, but for a weak coupling, of the magnitude expected experimentally, the enlarged symmetry can still be observed at the triple point up to significant length scales. Thus, it is likely that the plaquette-singlet to antiferromagnetic transition in SrCu2_2(BO3_3)2_2 exhibits remnants of emergent O(4) symmetry, which should be observable due to additional weakly gapped Goldstone modes.Comment: 14 pages, 8 figure

    Real-time energy management for diesel heavy duty hybrid electric vehicles

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    In this paper, a fuzzy-tuned equivalent consumption minimization strategy (F-ECMS) is proposed as an intelligent real-time energy management solution for a conceptual diesel engine-equipped heavy duty hybrid electric vehicle (HEV). In the HEV, two electric motors/generators are mounted on the turbocharger shaft and engine shaft, respectively, which can improve fuel efficiency by capturing and storing energy from both regenerative braking and otherwise wasted engine exhaust gas. The heavy duty HEV frequently involved in duty cycles characterized by start-stop events, especially in off-road applications, whose dynamics is analyzed in this paper. The on-line optimization problem is formulated as minimizing a cost function in terms of weighted fuel power and electric power. In the cost function, a cost factor is defined for both improving energy transmission efficiency and maintaining the battery energy balance. To deal with the nonexplicit relationship between HEV fuel economy, battery state of charge (SOC), and control variables, the cost factor is fuzzy tuned using expert knowledge and experience. In relation to the fuel economy, the air-fuel ratio is an important factor. An online search for capable optimal variable geometry turbocharger (VGT) vane opening and exhaust gas recirculation (EGR) valve opening is also necessary. Considering the exhaust emissions regulation in diesel engine control, the boundary values of VGT and EGR actuators are identified by offline design-of-experiment tests. An online rolling method is used to implement the multivariable optimization. The proposed method is validated via simulation under two transient driving cycles, with the fuel economy benefits of 4.43% and 6.44% over the nonhybrid mode, respectively. Compared with the telemetry equivalent consumption minimization strategy, the proposed F-ECMS shows better performance in the sustainability of battery SOC under driving conditions with the rapid dynamics often associated with off-road applications
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