Chandra Observation of a Weak Shock in the Galaxy Cluster A2556

Based on a 21.5 ks \chandra\ observation of A2556, we identify an edge on the surface brightness profile (SBP) at about 160$h_{71}^{-1}$ kpc northeast of the cluster center, and it corresponds to a shock front whose Mach number $\mathcal{M}$ is calculated to be $1.25_{-0.03}^{+0.02}$. No prominent substructure, such as sub-cluster, is found in either optical or X-ray band that can be associated with the edge, suggesting that the conventional super-sonic motion mechanism may not work in this case. As an alternative solution, we propose that the nonlinear steepening of acoustic wave, which is induced by the turbulence of the ICM at the core of the cluster, can be used to explain the origin of the shock front. Although nonlinear steepening weak shock is expected to occur frequently in clusters, why it is rarely observed still remains a question that requires further investigation, including both deeper X-ray observation and extensive theoretical studies.Comment: 15 pages, 4 figures, accepted by Ap

Exploring the Cosmic Reionization Epoch in Frequency Space: An Improved Approach to Remove the Foreground in 21 cm Tomography

Aiming to correctly restore the redshifted 21 cm signals emitted by the neutral hydrogen during the cosmic reionization processes, we re-examine the separation approaches based on the quadratic polynomial fitting technique in frequency space to investigate whether they works satisfactorily with complex foreground, by quantitatively evaluate the quality of restored 21 cm signals in terms of sample statistics. We construct the foreground model to characterize both spatial and spectral substructures of the real sky, and use it to simulate the observed radio spectra. By comparing between different separation approaches through statistical analysis of restored 21 cm spectra and corresponding power spectra, as well as their constraints on the mean halo bias $b$ and average ionization fraction $x_e$ of the reionization processes, at $z=8$ and the noise level of 60 mK we find that, although the complex foreground can be well approximated with quadratic polynomial expansion, a significant part of Mpc-scale components of the 21 cm signals (75% for $\gtrsim 6h^{-1}$ Mpc scales and 34% for $\gtrsim 1h^{-1}$ Mpc scales) is lost because it tends to be mis-identified as part of the foreground when single-narrow-segment separation approach is applied. The best restoration of the 21 cm signals and the tightest determination of $b$ and $x_e$ can be obtained with the three-narrow-segment fitting technique as proposed in this paper. Similar results can be obtained at other redshifts.Comment: 33 pages, 14 figures. Accepted for publication in Ap

How to Identify and Separate Bright Galaxy Clusters from the Low-frequency Radio Sky?

In this work we simulate the $50-200$ MHz radio sky that is constrained in the field of view ($5^{\circ}$ radius) of the 21 Centimeter Array (21CMA), by carrying out Monte-Carlo simulations to model redshifted cosmological reionization signals and strong contaminating foregrounds, including emissions from our Galaxy, galaxy clusters, and extragalactic point sources. As an improvement of previous works, we consider in detail not only random variations of morphological and spectroscopic parameters within the ranges allowed by multi-band observations, but also evolution of radio halos in galaxy clusters, assuming that relativistic electrons are re-accelerated in the ICM in merger events and lose energy via both synchrotron emission and inverse Compton scattering with CMB photons. By introducing a new approach designed on the basis of independent component analysis (ICA) and wavelet detection algorithm, we prove that, with a cumulative observation of one month with the 21CMA array, about $80\%$ of galaxy clusters with central brightness temperatures of $> 10~{\rm K}$ at 65 MHz can be safely identified and separated from the overwhelmingly bright foreground. We find that the morphological and spectroscopic distortions are extremely small as compared to the input simulated clusters, and the reduced $\chi^2$ of brightness temperature profiles and spectra are controlled to be $\lesssim 0.5$ and $\lesssim 1.3$, respectively. These results robustly indicate that in the near future a sample of dozens of bright galaxy clusters will be disentangled from the foreground in 21CMA observations, the study of which will greatly improve our knowledge about cluster merger rates, electron acceleration mechanisms in cluster radio halos, and magnetic field in the ICM.Comment: 35 pages, 10 figures, Accepted for publication in The Astrophysical Journa

A Chandra Study of Temperature Substructures in Intermediate-Redshift Galaxy Clusters

By analyzing the gas temperature maps created from the Chandra archive data, we reveal the prevailing existence of temperature substructures on ~100 kpc scales in the central regions of nine intermediate-redshift (z~0.1) galaxy clusters, which resemble those found in the Virgo and Coma Clusters. Each substructure contains a clump of hot plasma whose temperature is about 2-3 keV higher than the environment, corresponding to an excess thermal energy of ~1E58-1E60 erg per clump. Since if there were no significant non-gravitational heating sources, these substructures would have perished in 1E8-1E9 yrs due to thermal conduction and turbulent flows, whose velocity is found to range from about 200 to 400 km/s, we conclude that the substructures cannot be created and sustained by inhomogeneous radiative cooling. We also eliminate the possibilities that the temperature substructures are caused by supernova explosions, or by the non-thermal X-ray emission due to the inverse-Comptonization of the CMB photons. By calculating the rising time of AGN-induced buoyant bubbles, we speculate that the intermittent AGN outbursts (~ 1E60 erg per burst) may have played a crucial role in the forming of the high temperature substructures. Our results are supported by recent study of McNamara & Nulsen (2007), posing a tight observational constraint on future theoretical and numerical studies.Comment: 31 pages, 7 figures, ApJ accepte

A Joint Chandra and XMM-Newton View of Abell 3158: Massive Off-Centre Cool Gas Clump As A Robust Diagnostic of Merger Stage

By analysing the Chandra and XMM-Newton archived data of the nearby galaxy cluster Abell 3158, which was reported to possess a relatively regular, relaxed morphology in the X-ray band in previous works, we identify a bow edge-shaped discontinuity in the X-ray surface brightness distribution at about $120h_{71}^{-1}$ kpc west of the X-ray peak. This feature is found to be associated with a massive, off-centre cool gas clump, and actually forms the west boundary of the cool clump. We find that the cool gas clump is moving at a subsonic velocity of ~700 km/s toward west on the sky plane. We exclude the possibility that this cool clump was formed by local inhomogeneous radiative cooling in the intra-cluster medium, due to the effectiveness of the thermal conduction on the time-scale of $\sim 0.3$ Gyr. Since no evidence for central AGN activity has been found in Abell 3158, and this cool clump bears many similarities to the off-centre cool gas clumps detected in other merging clusters in terms of their mass, size, location, and thermal properties (e.g. lower temperature and higher abundance as compared with the environment), we speculate that the cool clump in Abell 3158 was caused by a merger event, and is the remnant of the original central cool-core of the main cluster or the infalling sub-cluster. This idea is supported not only by the study of line-of-sight velocity distribution of the cluster member galaxies, but also by the study of gas entropy-temperature correlation. This example shows that the appearance of such massive, off-centre cool gas clumps can be used to diagnose the dynamical state of a cluster, especially when prominent shocks and cold fronts are absent.Comment: Accepted by MNRAS; 12 pages, 6 figure

Advances in Multi-Sensor Data Fusion: Algorithms and Applications

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of “algorithm fusion” methods; (3) Establishment of an automatic quality assessment scheme

Understanding the Potential Influence of WeChat Engagement on Bonding Capital, Bridging Capital, and Electronic Word-of-Mouth Intention

As the most prevalent social media platform in mainland China, WeChat enables interpersonal communication among users and serves as an innovative marketing platform for enterprises to interact with consumers. Although numerous studies have investigated the antecedents of electronic word-of-mouth (e-WOM), WeChat users’ specific behaviors still receive limited academic attention. Drawing from social capital theory and social exchange theory, this article develops a model to systematically explore three differentiated types of WeChat behaviors and their association with users’ social capital and e-WOM intention. The conceptual model is explicitly evaluated by utilizing web-based data gathered from 271 young people. Obtained results demonstrate the path effects indicating that: (1) WeChat use behaviors such as seeking, sharing, and liking can positively influence bonding social capital, while only the impacts of sharing and liking on bridging social capital are significant; (2) bonding and bridging social capital are both significant predictors of e-WOM intention, and bonding social capital is the more influential of the two; (3) bonding social capital partially mediates the effect of seeking on e-WOM intention. These findings are eloquent for researchers and operators to further grasp the increasing importance of WeChat adoption and social capital on young generations’ e-WOM intention in the evolving digital age.publishe

Accounting for Carbon Sink and Its Dominant Influencing Factors in Chinese Ecological Space

Ecological space (ES), including forest ecological space (FES) and grassland ecological space (GES) in this study, is the land with natural attributes and the main functions of providing ecological services, which has a huge potential capacity for carbon sink (CS). The interannual fluctuation of the CS in ES is severe, which is affected by factors such as precipitation and temperature, but it is still controversial which is the dominant factor in affecting the fluctuation process of the CS in ES. To this end, the multi-source remote sensing monitoring data on the fine-grid scale were collected in this study, including the land use and land cover remote sensing monitoring data, the data products of moderate-resolution imaging spectroradiometer (including land surface water index, photosynthetically active radiation, enhanced vegetation index, gross primary productivity), and meteorological data (including precipitation and temperature). By coupling the vegetation photosynthesis model and soil respiration model, the CS in CES from 2010 to 2020 was calculated, and the interannual fluctuation trends and stability of CS in CES were analyzed. Furthermore, the correlation coefficient and partial correlation coefficient equation between the CS of CES with precipitation and temperature were constructed to explore the correlation between interannual fluctuation of CS in CES with meteorological factor, and to determine the dominant position of precipitation and temperature in affecting the fluctuation process of the CS in CES. The research results show that the annual average CS of per unit area in CES was 233.78 gC·m−2·a−1, and the cumulative CS was 11.83 PgC. The GES and FES contributed 6.33 PgC and 5.49 PgC of CS, respectively. From 2010 to 2020, the CS of CES showed an upward trend and was generally in a relatively stable state (the mean value of the coefficient of variation was 0.6248). However, the year with severe fluctuation of was found in this study (from 2013 to 2015), the reason is that the precipitation was too low in 2014, which indicated that climate change, especially the change of precipitation, played a important role in the fluctuation of CS in CES. The results of correlation analysis confirmed the above analysis. The change of CS in CES is highly positively correlated with the change of precipitation (the correlation coefficient is 0.085), and weakly positively correlation with temperature (the correlation coefficient was 0.026). The precipitation is the dominant influencing factor, which has a positive effect on CS in CES. Within a climate environment dominated by precipitation, precipitation and temperature jointly affect the CS in CES. It should be noted that in some regions with variable climate, precipitation and temperature had relatively little impact on CS in CES. Their fluctuations may depend more on the ecosystem’s own ecological services’ regulation ability and their response degree to changes in atmospheric CO2 concentration

Spatial–temporal distribution of global production–living–ecological space during the period 2000–2020

Abstract Global production-living-ecology space closely corresponds with sustainable development’s economic, social and ecological elements. The dataset of global production–living–ecological space in this paper was generated by combining the global land cover obtained using GlobeLand30 and the population density supplied by NASA’s Socioeconomic Data and Applications Center in 2000, 2010, and 2020. The verification was carried out using the random sampling function of ArcGIS software on the basis of Google Earth sample images. The overall accuracy of the global production–living–ecological space data in 2020 was 83.94% and the Kappa coefficient was 0.81. The overall accuracy of the global production–living–ecological space data in 2010 was 87.00% and the Kappa coefficient was 0.84. The overall accuracy of the spatial data in 2000 was 86.06% and the Kappa coefficient was 0.83. The dataset fills a gap in the global production-living-ecology space database and will be an essential reference for assessing the coordinated development of sustainable development goals