1,550 research outputs found

    A Sample of Quasars with Strong Nitrogen Emission Lines from the Sloan Digital Sky Survey

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    We report on 293 quasars with strong NIV] lambda 1486 or NIII] lambda 1750 emission lines (rest-frame equivalent width > 3 \AA) at 1.7 < z < 4.0 selected from the Sloan Digital Sky Survey (SDSS) Fifth Data Release. These nitrogen-rich (N-rich) objects comprise ~1.1% of the SDSS quasars. The comparison between the N-rich quasars and other quasars shows that the two quasar subsets share many common properties. We also confirm previous results that N-rich quasars have much stronger Lya and NV lambda 1240 emission lines. Strong nitrogen emission in all ionization states indicates high overall nitrogen abundances in these objects. We find evidence that the nitrogen abundance is closely related to quasar radio properties. The radio-loud fraction in the NIII]-rich quasars is 26% and in the NIV]-rich quasars is 69%, significantly higher than ~8% measured in other quasars with similar redshift and luminosity. Therefore, the high nitrogen abundance in N-rich quasars could be an indicator of a special quasar evolution stage, in which the radio activity is also strong.Comment: 8 pages, 4 figures; accepted by ApJ (ApJ June 10, 2008, v680 n1 issue

    CD147 promotes melanoma cell growth via SOX4-mediated glycolytic metabolism

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    Purpose: To determine the functional roles of cluster of differentiation 147 (CD147) in glycolysis in melanoma cells.Methods: CD147 expression in melanoma tissue and adjacent normal tissue was determined using quantitative real time polymrase chain reaction (qRT-PCR) and immunohistochemistry. Cell Counting Kit-8 (CCK-8) and colony formation assays were used to evaluate cell viability and colony formation, respectively. The role of CD147 in glycolysis in melanoma cells was investigated by determining glucose uptake, production of lactate, and cellular level of ATP.Results: CD147 was enhanced more in melanoma tissue than that in the adjacent normal tissue (p &lt; 0.001). CD147 overexpression promoted the viability and colony formation of melanoma cells. On the other hand, CD147 silencing decreased the viability and colony formation of melanoma cells. Glucose uptake, production of lactate, and cellular level of ATP were upregulated in melanoma cells by CD147 overexpression and downregulated by shRNA-mediated depletion of CD147. CD147 increased expression of C-X-C motif chemokine ligand 1 (CXCL1) to activate the sex-determining region Y-related high-mobility group box 4 (SOX4) pathway. Knockdown of CXCL1 attenuated the positive regulatory effect of CD147 on SOX4. Besides, overexpression of SOX4 reversed the suppressive effects of CD147 silencing on melanoma cell viability, colony formation, and glycolysis.Conclusion: CD147 contributes to melanoma cell growth via upregulation of SOX-mediated glycolysis, thus providing a therapeutic avenue for the management of melanoma. Keywords: Cluster of differentiation 147, CD147, Sex-determining region Y-related high-mobility group box 4, Melanoma, Cell growth, Glycolysi

    Automatic Target Recognition Strategy for Synthetic Aperture Radar Images Based on Combined Discrimination Trees

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    A strategy is introduced for achieving high accuracy in synthetic aperture radar (SAR) automatic target recognition (ATR) tasks. Initially, a novel pose rectification process and an image normalization process are sequentially introduced to produce images with less variations prior to the feature processing stage. Then, feature sets that have a wealth of texture and edge information are extracted with the utilization of wavelet coefficients, where more effective and compact feature sets are acquired by reducing the redundancy and dimensionality of the extracted feature set. Finally, a group of discrimination trees are learned and combined into a final classifier in the framework of Real-AdaBoost. The proposed method is evaluated with the public release database for moving and stationary target acquisition and recognition (MSTAR). Several comparative studies are conducted to evaluate the effectiveness of the proposed algorithm. Experimental results show the distinctive superiority of the proposed method under both standard operating conditions (SOCs) and extended operating conditions (EOCs). Moreover, our additional tests suggest that good recognition accuracy can be achieved even with limited number of training images as long as these are captured with appropriately incremental sample step in target poses

    Research on Cooperative Innovation Behavior of Industrial Cluster Based on Subject Adaptability

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    From the perspective of the interactive cooperation among subjects, this paper portrays the process of cooperative innovation in industrial cluster, in order to capture the correlated equilibrium relationship among them. Through the utilization of two key tools, evolutionary stable strategy and replicator dynamics equations, this paper considers the cost and gains of cooperative innovation and the amount of government support as well as other factors to build and analyze a classic evolutionary game model. On this basis, the subject’s own adaptability is introduced, which is regarded as the system noise in the stochastic evolutionary game model so as to analyze the impact of adaptability on the game strategy selection. The results show that, in the first place, without considering subjects’ adaptability, their cooperation in industrial clusters depends on the cost and gains of innovative cooperation, the amount of government support, and some conditions that can promote cooperation, namely, game steady state. In the second place after the introduction of subjects’ adaptability, it will affect both game theory selection process and time, which means that the process becomes more complex, presents the nonlinear characteristics, and helps them to make faster decisions in their favor, but the final steady state remains unchanged

    Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object Detection

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    The dominant multi-camera 3D detection paradigm is based on explicit 3D feature construction, which requires complicated indexing of local image-view features via 3D-to-2D projection. Other methods implicitly introduce geometric positional encoding and perform global attention (e.g., PETR) to build the relationship between image tokens and 3D objects. The 3D-to-2D perspective inconsistency and global attention lead to a weak correlation between foreground tokens and queries, resulting in slow convergence. We propose Focal-PETR with instance-guided supervision and spatial alignment module to adaptively focus object queries on discriminative foreground regions. Focal-PETR additionally introduces a down-sampling strategy to reduce the consumption of global attention. Due to the highly parallelized implementation and down-sampling strategy, our model, without depth supervision, achieves leading performance on the large-scale nuScenes benchmark and a superior speed of 30 FPS on a single RTX3090 GPU. Extensive experiments show that our method outperforms PETR while consuming 3x fewer training hours. The code will be made publicly available.Comment: Tech Repor
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