Selection and Mid-infrared Spectroscopy of Ultraluminous Star-Forming Galaxies at z~2

Starting from a sample of 24 \micron\ sources in the Extended Groth Strip, we use 3.6 to 8 \micron\ color criteria to select ultraluminous infrared galaxies (ULIRGs) at $z\sim2$. Spectroscopy from 20-38 \micron\ of 14 objects verifies their nature and gives their redshifts. Multi-wavelength data for these objects imply stellar masses ${>}10^{11}$ \Msun\ and star formation rates $\ge$410 \Msun yr$^{-1}$. Four objects of this sample observed at 1.6 \micron\ (rest-frame visible) with {\it HST}/WFC3 show diverse morphologies, suggesting that multiple formation processes create ULIRGs. Four of the 14 objects show signs of active galactic nuclei, but the luminosity appears to be dominated by star formation in all cases.Comment: 33 pages, 13 figures, accepted by Ap

Scale-free resilience of real traffic jams

The concept of resilience can be realized in natural and engineering systems, representing the ability of system to adapt and recover from various disturbances. Although resilience is a critical property needed for understanding and managing the risks and collapses of transportation system, an accepted and useful definition of resilience for urban traffic as well as its statistical property under perturbations is still missing. Here we define city traffic resilience based on the spatio-temporal clusters of congestion in real traffic, and find that the resilience follows a scale free distribution in two-dimensional city road networks and one-dimensional highways, with different exponents, but similar exponents in different days and different cities. The traffic resilience is also revealed to have a novel scaling relation between the cluster size of the spatio-temporal jam and its recovery duration, independent of microscopic details. Our findings of universal traffic resilience can provide indication towards better understanding and designing these complex engineering systems under internal and external disturbances. Comment: 6 pages, 4 figure Document type: Articl

Scale-free Resilience of Real Traffic Jams

The concept of resilience can be realized in natural and engineering systems, representing the ability of system to adapt and recover from various disturbances. Although resilience is a critical property needed for understanding and managing the risks and collapses of transportation system, an accepted and useful definition of resilience for urban traffic as well as its statistical property under perturbations is still missing. Here we define city traffic resilience based on the spatio-temporal clusters of congestion in real traffic, and find that the resilience follows a scale free distribution in two-dimensional city road networks and one-dimensional highways, with different exponents, but similar exponents in different days and different cities. The traffic resilience is also revealed to have a novel scaling relation between the cluster size of the spatio-temporal jam and its recovery duration, independent of microscopic details. Our findings of universal traffic resilience can provide indication towards better understanding and designing these complex engineering systems under internal and external disturbances.Comment: 6 pages, 4 figure

CANDELS: Correlations of SEDs and Morphologies with Star-formation Status for Massive Galaxies at z ~ 2

We present a study on Spectral Energy Distributions, Morphologies, and star formation for an IRAC-selected extremely red object sample in the GOODS Chandra Deep Field-South. This work was enabled by new HST/WFC3 near-IR imaging from the CANDELS survey as well as the deepest available X-ray data from Chandra 4 Ms observations. This sample consists of 133 objects with the 3.6um limiting magnitude of [3.6] = 21.5, and is approximately complete for galaxies with M >10^{11}M_sun at 1.5 < z < 2.5. We classify this sample into two types, quiescent and star-forming galaxies, in the observed infrared color-color ([3.6]-[24] vs K-[3.6]) diagram. The further morphological study of this sample show a consistent result with the observed color classification. The classified quiescent galaxies are bulge dominated and star-forming galaxies in the sample have disk or irregular morphologies. Our observed infrared color classification is also consistent with the rest-frame color (U-V vs V-J) classification. We also found that quiescent and star-forming galaxies are well separated in the nonparametric morphology parameter (Gini vs M_{20}) diagram measuring their concentration and clumpiness: quiescent galaxies have Gini coefficient higher than 0.58 and star forming galaxies have Gini coefficient lower that 0.58. We argue that the star formation quenching process must lead to or be accompanied by the increasing galaxy concentration. One prominent morphological feature of this sample is that disks are commonly seen in this massive galaxy sample at 1.5 < z < 2.5: 30% of quiescent galaxies and 70% of star forming galaxies with M >10^{11}M_sun have disks in their rest-frame optical morphologies. The prevalence of these extended, relatively undisturbed disks challenges the merging scenario as the main mode of massive galaxy formation.Comment: 36 pages,16 figures,Accepted by Ap

Analysis of the Characteristics of Climate Change in the Ecologically Vulnerable Area of the Mu Us Dune Field under the Background of Global Warming

The Mu Us dune field is one of China’s four major dune fields, which are ecologically vulnerable areas of northwest semiarid land across Shaanxi, Ningxia, and Inner Mongolia, also very sensitive to the global temperature rise and environmental changes. This paper uses data on the temperature, precipitation, and precipitable water vapor (PWV) in the Mu Us dune field and its surrounding areas to analyze and discuss the time series and spatial distribution characteristics of these three factors in this area. The results of the study show that, in recent years, the trend of temperature increase in the Mu Us dune field has been higher than the average level in China, but this trend has gradually subsided since 2000. The spatial distribution of temperature presents an obvious characteristic of gradual increase from north to south and is affected by latitude, altitude, and topography. The annual cumulative precipitation of the Mu Us dune field is lower than the average level in China. However, in recent years, the rate of the increase in precipitation in this area has been significantly higher than that of the average rate of increase in China. The eastern part of the dune field has the most precipitation, which gradually decreases to the west. The spatial distribution of precipitation is greatly affected by monsoon factors in the region and the distribution of rivers. In the research field, PWV has been rising in recent years, which is greatly related to the increase of vegetation coverage in this region. This demonstrates that the Mu Us dune field has experienced a “warmer and wetter” trend in recent years

An Improved Predicted Model for BDS Ultra-Rapid Satellite Clock Offsets

The satellite clocks used in the BeiDou-2 satellite navigation System (BDS) are Chinese self-developed Rb atomic clocks, and their performances and stabilities are worse than GPS and Galileo satellite clocks. Due to special periodic noises and nonlinear system errors existing in the BDS clock offset series, the GPS ultra-rapid clock model, which uses a simple quadratic polynomial plus one periodic is not suitable for BDS. Therefore, an improved prediction model for BDS satellite clocks is proposed in order to enhance the precision of ultra-rapid predicted clock offsets. First, a basic quadratic polynomial model which is fit for the rubidium (Rb) clock is constructed for BDS. Second, the main cyclic terms are detected and identified by the Fast Fourier Transform (FFT) method according to every satellite clock offset series. The detected results show that most BDS clocks have special cyclic terms which are different from the orbit periods. Therefore, two main cyclic terms are added to absorb the periodic effects. Third, after the quadratic polynomial plus two periodic fitting, some evident nonlinear system errors also exist in the model residual, and the Back Propagation (BP) neural network model is chosen to compensate for these nonlinear system errors. The simulation results show that the performance and precision using the improved model are better than that of China iGMAS ultra-rapid prediction (ISU-P) products and the Deutsches GeoForschungsZentrum GFZ BDS ultra-rapid prediction (GBU-P) products. Comparing to ISU-P products, the average improvements using the proposed model in 3 h, 6 h, 12 h and 24 h are 23.1%, 21.3%, 20.2%, and 19.8%, respectively. Meanwhile the accuracy improvements of the proposed model are 9.9%, 13.9%, 17.3%, and 21.2% compared to GBU-P products. In addition, the kinematic Precise Point Positioning (PPP) example using 8 Multi-GNSS Experiment MGEX stations shows that the precision based on the proposed clock model has improved about 16%, 14%, and 38% in the North (N), East (E) and Height (H) components

Impact of Meteorological Factors on Thermokarst Lake Changes in the Beilu River Basin, Qinghai-Tibet Plateau, China (2000–2016)

Variations in weather conditions have a significant impact on thermokarst lakes, such as the sub-lake permafrost thawing caused by global warming. Based on the analysis of Landsat sensor images by ENVI TM 5.3 software, the present study quantitatively determined the area of the thermokarst lakes and the area of the single selected thermokarst lake in the Beilu River Basin from 2000 to 2016. In an effort to explore the reason for changes in the area of thermokarst lakes, this work used Pearson correlation to analyze the relationship between the area of thermokarst lakes and precipitation, wind speed, average temperature, and relative humidity as obtained from the weather station Wudaoliang. Furthermore, this study used multiple linear regression to comprehensively study the correlation between the meteorological factors and changes in the thermokarst lake area. In this case, the total lake-area changes and the single-area changes exhibited unique patterns. The results showed that the total lake area and the single selected lake area increased year by year. Furthermore, the effects of the four meteorological factors defined above on the total area of typical thermokarst lakes are different from the effects of these factors on the single selected thermokarst lake. While the total area of specific thermokarst lakes exhibited a time lag in their response to the four factors, the surface area of the selected thermokarst lake responded to these factors on time. The dominant meteorological factor contributing to total lake area variations of typical thermokarst lakes is the increasing annual average temperature. The Pearson correlation coefficient between the total area and the annual average temperature is 0.717, suggesting a statistically significant correlation between the two factors. For the selected thermokarst lake, the surface area is related to annual average temperature and wind speed. As a result, wind speed and average temperature could infer the variation law on the thermokarst lake due to the linear fitting equation between area and significant meteorological factors

Precision Space Observation Technique for Geological Hazard Monitoring and Early Warning

Since the 21st century, with the deterioration of the world environment and the intense human activities, geological disasters have been occurred more frequently. Precision space observation technology is an important means for geological disasters monitoring and early warning. In this paper, the characteristics and monitoring methods of common geological disasters are introduced. The technical characteristics and application of InSAR, LiDAR, high resolution remote sensing and GNSS are discussed. The integration of high precision spatial monitoring technology are reviewed and prospected. Finally, the future trends of the geological disaster monitoring and early warning technology are summarized

A regional weighted mean temperature model that takes into account climate differences: taking Shaanxi, China as an example

The weighted mean temperature Tm is a key parameter of the global navigation satellite system (GNSS) inversion of precipitation. Taking the Shaanxi area in China as an example, this paper combines the reanalysis data of the European Weather Forecast Center (ECMWF) with the data of three sounding stations, and establishes a Tm regionalized regression model considering periodicity based on the principle of least squares. The data from three radiosonde stations in Shaanxi Province were used for verification. The results show that the Tm regional model established in this paper taking into account the cycle has an average improvement rate of 16.1% compared with the traditional Bevis model. In addition, in view of the differences in regions with different climate types, this paper establishes a sub-climatic zone Tm model with a piecewise linear form that changes with latitude, and solves the problem of adaptability of the regression model in different climate zones. Compared with sounding data, the Tm model that takes into account the climate difference has an external accuracy (RMS) range of 1.47~2.06 K. Compared with the Bevis model, the average accuracy improvement rate is 44.9%, and the improvement effect is significant; using ECMWF data to select 19 each grid point evaluates the accuracy of the model. The results show that the average RMS is 3.26 K and the maximum RMS is 3.67 K; the average STD is 2.69 K and the maximum STD is 3.19 K

BDS/GPS/Galileo Precise Point Positioning Performance Analysis of Android Smartphones Based on Real-Time Stream Data

Smartphones with the Android operating system can acquire Global Navigation Satellite System (GNSS) raw pseudorange and carrier phase observations, which can provide a new way for the general public to obtain precise position information. However, only postprocessing precise orbit and clock offset products in some older smart devices are applied in current studies. The performances of precise point positioning (PPP) with the smartphone using real-time products and newly smartphones are still unrevealed, which is more valuable for real-time applications. This study investigates the observation data quality and multi-GNSS real-time PPP performance using recent smartphones. Firstly, the observed carrier-to-noise density ratio (C/N0), number of satellites and position dilution of precision (PDOP) of GNSS observations are evaluated. The results demonstrate that the C/N0 received by Huawei Mate40 is better than that of the Huawei P40 for GPS, BDS, QZSS and Galileo systems, while the GLONASS is poorer, and the PDOP of the Huawei P40 is slightly better than that of Mate40. Additionally, a comprehensive analysis of real-time precise orbit and clock offset products performance is conducted. The experiment result expresses that the orbit and clock offset performance of GPS and Galileo is better than that of BDS-3 and GLONASS, and BDS-2 is the worst. Finally, single- and dual-frequency multi-GNSS combined PPP experiments using observations received from smartphones and real-time products are conducted; the results indicate that the real-time static PPP using a smartphone can achieve decimeter-level positioning accuracy, and kinematic PPP can achieve meter-level positioning accuracy after convergence