Age of first exposure (AoFE) is an important factor that influences the quality of L2 acquisition. This study aims to investigate the AoFE effect on the contextual learning of L2 novel words at the neural level, as measured by the N400 component from event-related potentials (ERPs). Eighty-eight participants were recruited for the experiment of L2 pseudoword learning, which includes a learning session and a testing session. The participants’ EEG data were recorded from the testing session, and the N400 effect was derived from target words that were either congruous or incongruous with the context. The linear mixed model and multiple regression model revealed a positive AoFE effect on the N400 effect in discourses that were designed for testing retrieval of episodic and semantic memory even after accounting for the variance contributed by several confounding factors. In addition to AoFE, the effects of total L2 exposure, L2 proficiency and personality on the L2 novel word learning performance indicated by the N400 effect were also confirmed in the statistical results.

In this work, we experimentally investigate the dependence of the stimulated Raman scattering (SRS) effect on the seed linewidth of a high-power nanosecond superfluorescent fiber source (ns-SFS). The results reveal that the SRS in the ns-SFS amplifier is significantly influenced by the full width at half maximum (FWHM) of the ns-SFS seed, and there is an optimal FWHM linewidth of 2 nm to achieve the lowest SRS in our case. The first-order SRS power ratio increases rapidly when the seed’s linewidth deviates from the optimal FWHM linewidth. By power scaling the ns-SFS seed with the optimal FWHM linewidth, a narrowband all-fiberized ns-SFS amplifier is achieved with a maximum average power of 602 W, pulse energy of 24.1 mJ and corresponding peak power of 422.5 kW. This is the highest average power and pulse energy achieved for all-fiberized ns-SFS amplifiers to the best of our knowledge.

Achieving an all-fiber ultra-fast system with above kW average power and mJ pulse energy is extremely challenging. This paper demonstrated a picosecond monolithic master oscillator power amplifier system at a 25 MHz repetition frequency with an average power of approximately 1.2 kW, a pulse energy of approximately 48 μJ and a peak power of approximately 0.45 MW. The nonlinear effects were suppressed by adopting a dispersion stretched seed pulse (with a narrow linewidth of 0.052 nm) and a multi-mode master amplifier with an extra-large mode area; then an ultimate narrow bandwidth of 1.32 nm and a moderately broadened pulse of approximately 107 ps were achieved. Meanwhile, the great spatio-temporal stability was verified experimentally, and no sign of transverse mode instability appeared even at the maximum output power. The system has shown great power and energy capability with a sacrificed beam propagation product of 5.28 mm$\cdot$mrad. In addition, further scaling of the peak power and pulse energy can be achieved by employing a lower repetition and a conventional compressor.

This study deploys RTK-GNSS in 2012, TLS in 2015 and UAV in 2018 to monitor the changes of Urumqi Glacier No. 1 (UG1), eastern Tien Shan, and analyzes the feasibility of three technologies in monitoring the mountain glaciers. DEM differencing shows that UG1 has experienced a pronounced thinning and mass loss for the period of 2012–18. The glacier surface elevation change of −0.83 ± 0.57 m w.e. a−1 has been recorded for 2012–15, whereas the changes of glacier tongue surface elevation in 2015–18 and 2012–18 were −2.03 ± 0.95 and −1.34 ± 0.88 m w.e. a−1, respectively. The glacier area shrunk by 0.07 ± 0.07 × 10−3 km2 and the terminus retreat rate was 6.28 ± 0.83 m a−1 during 2012–18. The good agreement between the glaciological and geodetic specific mass-balances is promising, showing the combination of the three technologies is suitable to monitor glacier mass change. We recommend application of the three technologies to assess each other in different locations of the glacier, e.g. RTK-GNSS base stations, ground control points, glacier tongue and terminus, in order to avoid the inherent limitations of each technology and to provide reliable data for the future studies of mountain glacier changes in western China.

This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 March 2020 in Wuhan is reported. The data of symptoms, comorbidity, demographic, vital sign, CT scans results and laboratory test results on admission were collected. Machine-learning methods (Random Forest and XGboost) were used to rank clinical features for mortality risk. Multivariate logistic regression models were applied to identify clinical features with statistical significance. The predictors of mortality were lactate dehydrogenase (LDH), C-reactive protein (CRP) and age based on 500 bootstrapped samples. A multivariate logistic regression model was formed to predict mortality 292 in-sample patients with area under the receiver operating characteristics (AUROC) of 0.9521, which was better than CURB-65 (AUROC of 0.8501) and the machine-learning-based model (AUROC of 0.4530). An out-sample data set of 13 patients was further tested to show our model (AUROC of 0.6061) was also better than CURB-65 (AUROC of 0.4608) and the machine-learning-based model (AUROC of 0.2292). LDH, CRP and age can be used to identify severe patients with COVID-19 on hospital admission.

Sui SG, Wu MX, King ME, Zhang Y, Ling L, Xu JM, Weng XC, Duan L, Shan BC, Li LJ. Abnormal grey matter in victims of rape with PTSD in Mainland China: a voxel-based morphometry study.

A support vector machine (SVM) method is applied to select K giant stars directly from the spectral features of LAMOST spectra. The performance of the algorithm is assessed using the MILES library. It shows that the completeness of the K giant stars is 87% with only about 6% dwarf contamination. This allows us to select 18,013 K giant stars at |b|>20° and 38,108 at |b|<20° from LAMOST pilot survey data.

We use 63,774 F/G dwarf stars from the LAMOST pilot survey to explore the velocity distribution in the solar neighborhood. The intrinsic UV distribution is reconstructed with a 20-Gaussian model using extreme deconvolution. We find at least two arcs, one extending from (−106, −3) to (94, −27) km/s and the other from (29, −9) to (78, −51) km/s. The arcs are qualitatively consistent with numerical simulations of the resonance induced by the Galactic bar and can be used to constrain its dynamical properties.

There is increasing evidence to show that 2-cell stage mouse blastomeres have differing developmental properties. Additionally, it has been suggested that such a difference might be due to their distribution of mRNA and/or protein asymmetry. However, to date, the exact genes that are involved in the orientation and order of blastomere division are not known. In this study, some differentially expressed transcripts were identified. Axin1, cell division cycle 25 homolog C (Cdc25c) and cyclin-dependent inhibitor 2D (Cdkn2d) were selected for validation by real-time polymerase chain reaction (PCR) based on published data. Our real-time PCR results demonstrated that Axin1, Cdc25c and Cdkn2d genes had different levels of expression among blastomeres of the mouse 2-cell embryo i.e. the level of Axin1 mRNA was significantly higher in one blastomere when compared with the other blastomeres of the 2-cell embryo (p < 0.05). The variation in Cdc25c (p < 0.05) and Cdkn2d (p < 0.01) mRNA expression followed a similar trend to that of Axin1. In addition, the highest levels of expression of these three genes were detected in the same blastomere in the 2-cell embryo. We confirmed that there was an asymmetrical distribution pattern for Axin1, Cdc25c and Cdkn2d transcripts in 2-cell embryos. In conclusion, this study demonstrated clearly that there is embryonic asymmetry at the 2-cell stage and that these differentially expressed genes may result in differentiation in expression in embryo development.

The effects of specific components in culture medium on embryo physiology have been extensively investigated to optimize in vitro culture systems; however, little attention has been paid to antibiotics, the reagents used most commonly in culture systems to prevent contamination. To investigate the potential effects of routine use of antibiotics on cultured embryos, mouse zygotes were cultured with or without antibiotics. In both groups, the developmental rate and cell number of blastocysts appear to be normal. The proportion of embryos with blastomere fragmentation increased slightly when embryos were cultured with antibiotics. In contrast, the presence of antibiotics in the embryo culture system significantly disturbs expression of zygotically activated genes, damages chromatin integrity and increases apoptosis of cultured embryos. These results provide evidence that, when cultured with antibiotics, embryos with normal appearance may possess intrinsic physiological and genetic abnormalities. We demonstrate that the adverse effects of antibiotics on mammalian embryos are more severe than we previously presumed and that antibiotics are not essential for sterility of embryo culture system therefore abolishing antibiotic supplementation during embryo culture.