The Librating Companions in HD 37124, HD 12661, HD 82943, 47 Uma and GJ 876: Alignment or Antialignment?

We investigated the apsidal motion for the multi-planet systems. In the simulations, we found that the two planets of HD 37124, HD 12661, 47 Uma and HD 82943 separately undergo apsidal alignment or antialignment. But the companions of GJ 876 and $\upsilon$ And are only in apsidal lock about $0^{\circ}$. Moreover, we obtained the criteria with Laplace-Lagrange secular theory to discern whether a pair of planets for a certain system are in libration or circulation.Comment: 13 Pages, 3 figures, 2 tables, Published by ApJ Letters, 591, July 1, 2003 (Figures now included to match the publication

Study on a miniaturized satellite payload for atmospheric temperature measurements

The atmospheric temperature reflects the thermal balance of the atmosphere and is a valuable indicator of climate change. It has been widely recognized that the atmospheric gravity wave activity has a profound effect on the large-scale circulation, thermal and constituent structures in the mesosphere and lower thermosphere (MLT). Temperature distribution in this region is an essential component to identify and quantify gravity waves. Observation from remote sensing instruments on satellite platforms is an effective way to measure the temperature in the MLT region. A miniaturized satellite payload is developed to measure the atmospheric temperature in the MLT region via observing the O2A-band emission. Following a Boltzmann distribution, the relative intensities of the emission lines can be used to derive the temperature profile. Based on the spatial heterodyne spectroscopy, this instrument is capable of resolving individual emission lines in the O2A-band for the spatial and spectral information simultaneously. The monolithic and compact feature of this spectrometer makes it suitable for operating on satellite platforms. In this work, the characterization of the instrument is investigated for the purpose of simultaneously measuring multiple emission lines of the O2A-band. The instrument is explored through a series of experimental methods, providing characteristics of the instrument and evaluation of its performance. In spatial and spectral domain, Level- 0 and Level-1 data processors are developed to convert the raw data to the calibrated spectral radiance for further temperature and gravity wave characterization. Within this framework, the performance of the utilized detector is evaluated along with its radiation tolerance in space environment. In the processor, the detector artifacts are corrected based on the measurements in laboratory or in space. The radiometric response of the instrument is characterized on a pixel-by-pixel basis using a blackbody. An interferogram distortion correction algorithm is developed to correct for the spatial and phase distortion induced by the detector optics. Further, localized phase distortion correction is implemented to correct for the remaining phase error. Unwanted ghost emission lines are removed based on two dimensional Fourier transform. In the spectral domain, the processing steps mainly consist of wavelength calibration and instrument spectral response correction, including filter response correction and modulation efficiency correction. As an in-orbit verification, the AtmoSHINE instrument was successfully deployed in space on 22th of December, 2018. In the first test phase, the functionality and the performance of the instrument in space were verified. The detector dark current measurement in orbit is consistent with the ground-based results. Based on the the calibration procedures and the developed data processing algorithms, the O2A-band emission lines can be successfully resolved. A cross-verification of the AtmoSHINE limb radiance profile with other satellite payload measurements indicates that the radiometric performance of the instrument is within the expectation. The retrieved temperature parameters are studied with respect to different number of samples and different objective functions in the optimization. This work verifies the ability of the instrument to derive the atmospheric temperature in the MLT region and its potential application in gravity wave detections

Negative Regulation of p53 Functions by Daxx and the Involvement of MDM2

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Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation

Unsupervised learning of optical flow, which leverages the supervision from view synthesis, has emerged as a promising alternative to supervised methods. However, the objective of unsupervised learning is likely to be unreliable in challenging scenes. In this work, we present a framework to use more reliable supervision from transformations. It simply twists the general unsupervised learning pipeline by running another forward pass with transformed data from augmentation, along with using transformed predictions of original data as the self-supervision signal. Besides, we further introduce a lightweight network with multiple frames by a highly-shared flow decoder. Our method consistently gets a leap of performance on several benchmarks with the best accuracy among deep unsupervised methods. Also, our method achieves competitive results to recent fully supervised methods while with much fewer parameters.Comment: Accepted to CVPR 2020, https://github.com/lliuz/ARFlo

On optimizing subspaces for face recognition

Abstract We propose a subspace learning algorithm for face recognition by directly optimizing recognition performance scores