Decomposition of Changes in Earnings Inequality in China: A Distributional Approach

Using the nationwide household data, this study examines the changes in the Chinese urban income distributions from 1987 to 1996 and from 1996 to 2004, and investigates the causes of these changes. The Oaxaca-Blinder decomposition method is applied to decomposing the mean earnings increases, and the Firpo-Fortin-Lemieux method based upon a recentered influence function is used to decompose the changes in the income distribution and the inequality measures such as the variance and the 10-90 ratio. The decomposition results show that the wage structure effects such as the widened gender pay gap, the increasing return to college education, and the widened gap in the return to different industries, ownership, and regions, have contributed to most of the overall increases in income inequality. During the different time periods, 1987-1996 and 1996-2004, the impacts of these factors vary at the different points (e.g. the lower half or upper half) of distribution.Earnings inequality; Unconditional Quantile Regressions; Earnings distribution; Decomposition

Decomposition of Changes in Earnings Inequality in China: A Distributional Approach

Using the nationwide household data, this study examines the changes in the Chinese urban income distributions from 1987 to 1996 and from 1996 to 2004, and investigates the causes of these changes. The Oaxaca-Blinder decomposition method is applied to decomposing the mean earnings increases, and the Firpo-Fortin-Lemieux method based upon a recentered influence function is used to decompose the changes in the income distribution and the inequality measures such as the variance and the 10-90 ratio. The decomposition results show that the wage structure effects such as the widened gender pay gap, the increasing return to college education, and the widened gap in the return to different industries, ownership, and regions, have contributed to most of the overall increases in income inequality. During the different time periods, 1987-1996 and 1996-2004, the impacts of these factors vary at the different points (e.g. the lower half or upper half) of distribution

Decomposition of Changes in Earnings Inequality in China: A Distributional Approach

Using the nationwide household data, this study examines the changes in the Chinese urban income distributions from 1987 to 1996 and from 1996 to 2004, and investigates the causes of these changes. The Oaxaca-Blinder decomposition method is applied to decomposing the mean earnings increases, and the Firpo-Fortin-Lemieux method based upon a recentered influence function is used to decompose the changes in the income distribution and the inequality measures such as the variance and the 10-90 ratio. The decomposition results show that the wage structure effects such as the widened gender pay gap, the increasing return to college education, and the widened gap in the return to different industries, ownership, and regions, have contributed to most of the overall increases in income inequality. During the different time periods, 1987-1996 and 1996-2004, the impacts of these factors vary at the different points (e.g. the lower half or upper half) of distribution

Effect of rs1344706 in the ZNF804A gene on the brain network.

ZNF804A rs1344706 (A/C) was the first SNP that reached genome-wide significance for schizophrenia. Recent studies have linked rs1344706 to functional connectivity among specific brain regions. However, no study thus far has examined the role of this SNP in the entire functional connectome. In this study, we used degree centrality to test the role of rs1344706 in the whole-brain voxel-wise functional connectome during the resting state. 52 schizophrenia patients and 128 healthy controls were included in the final analysis. In our whole-brain analysis, we found a significant interaction effect of genotype × diagnosis at the precuneus (PCU) (cluster size = 52 voxels, peak voxel MNI coordinates: x = 9, y = - 69, z = 63, F = 32.57, FWE corrected P < 0.001). When we subdivided the degree centrality network according to anatomical distance, the whole-brain analysis also found a significant interaction effect of genotype × diagnosis at the PCU with the same peak in the short-range degree centrality network (cluster size = 72 voxels, F = 37.29, FWE corrected P < 0.001). No significant result was found in the long-range degree centrality network. Our results elucidated the contribution of rs1344706 to functional connectivity within the brain network, and may have important implications for our understanding of this risk gene's role in functional dysconnectivity in schizophrenia

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity.

BackgroundGenetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.MethodsIn this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N = 30) or the active control group (N = 30). Both groups were trained for 20 sessions during 4 weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N = 101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.ResultsIn the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p = .030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p = .025).ConclusionsThis study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training

The Photoperiod-Insensitive Allele Ppd-D1a Promotes Earlier Flowering in Rht12 Dwarf Plants of Bread Wheat

The gibberellin-responsive dwarfing gene Rht12 can significantly reduce plant height without changing seedling vigor and substantially increase ear fertility in bread wheat (Triticum aestivum. L). However, Rht12 delays heading date and anthesis date, hindering the use of Rht12 in wheat improvement. To promote early flowering of the Rht12 dwarf plants, the photoperiod-insensitive allele Ppd-D1a was introduced through a cross between Jinmai47 (Ppd-D1a) and Karcagi (Rht12). The results showed that Ppd-D1a can rescue the delaying effect of Rht12 on flowering time and promote earlier flowering by 9.0 days (163.2°Cd) in the Rht12 dwarf plants by shortening the late reproduction phase. Plant height was reduced by Rht12 (43.2%) and Ppd-D1a (10.9%), achieving dwarf plants with higher lodging resistance. Ear fertility, like the grain number per spike, was significantly increased by Rht12 (21.3%), while it was reduced by Ppd-D1a (6.5%). However, thousand kernel weight was significantly reduced by Rht12 (12.9%) but significantly increased by Ppd-D1a (16.9%). Finally, plant yield was increased by 16.4 and 8.2%, and harvest index was increased by 24.9 and 15.4% in the Rht12 dwarf lines and tall lines with Ppd-D1a, respectively. Clearly, there was an additive interaction between Rht12 and Ppd-D1 and the introduction of Ppd-D1a advanced the flowering time and improved the yield traits of Rht12 dwarf plants, suggesting that the combination of Rht12 and Ppd-D1a would be conducive to the successful use of Rht12 in wheat breeding programs

Comparative genomics reveals insights into avian genome evolution and adaptation

Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve