We report here the first hundred-watt continuous wave fiber gas laser in H2-filled hollow-core photonic crystal fiber (PCF) by stimulated Raman scattering. The pump source is a homemade narrow-linewidth fiber oscillator with a 3 dB linewidth of 0.15 nm at the maximum output power of 380 W. To efficiently and stably couple several-hundred-watt pump power into the hollow core and seal the gas, a hollow-core fiber end-cap is fabricated and used at the input end. A maximum power of 110 W at 1153 nm is obtained in a 5 m long hollow-core PCF filled with 36 bar H2, and the conversion efficiency of the first Stokes power is around 48.9%. This work paves the way for high-power fiber gas Raman lasers.

The spatial structure and time evolution of tornado-like vortices in a three-dimensional cavity are studied by topological analysis and numerical simulation. The topology theory of the unsteady vortex in the rectangular coordinate system (Zhang, Zhang & Shu, J. Fluid Mech., vol. 639, 2009, pp. 343–372) is generalized to the curvilinear coordinate system. Two functions $\lambda (q_1,t)$ and $q(q_1,t)$ are obtained to determine the topology structure of the sectional streamline pattern in the cross-section perpendicular to the vortex axis and the meridional plane, respectively. The spiral direction of the sectional streamlines in the cross-section perpendicular to the vortex axis depends on the sign of $\lambda (q_1,t)$. The types of critical points in the meridional plane depend on the sign of $q(q_1,t)$. The relation between the critical points of the streamline pattern in the meridional plane and that in the cross-section perpendicular to the vortex axis is set up. The flow in a three-dimensional rectangular cavity is numerically simulated by solving the three-dimensional Navier–Stokes equations using high-order numerical methods. The spatial structures and the time evolutions of the tornado-like vortices in the cavity are analysed with our topology theory. Both the bubble type and spiral type of vortex breakdown are observed. They have a close relationship with the vortex structure in the cross-section perpendicular to the vortex axis. The bubble-type breakdown has a conical core and the core is non-axisymmetric in the sense of topology. A criterion for the bubble type and the spiral type based on the spatial structure characteristic of the two breakdown types is provided.

Instrument delivery is critical part in vascular intervention surgery. Due to the soft-body structure of instruments, the relationship between manipulation commands and instrument motion is non-linear, making instrument delivery challenging and time-consuming. Reinforcement learning has the potential to learn manipulation skills and automate instrument delivery with enhanced success rates and reduced workload of physicians. However, due to the sample inefficiency when using high-dimensional images, existing reinforcement learning algorithms are limited on realistic vascular robotic systems. To alleviate this problem, this paper proposes discrete soft actor-critic with auto-encoder (DSAC-AE) that augments SAC-discrete with an auxiliary reconstruction task. The algorithm is applied with distributed sample collection and parameter update in a robot-assisted preclinical environment. Experimental results indicate that guidewire delivery can be automatically implemented after 50k sampling steps in less than 15 h, demonstrating the proposed algorithm has the great potential to learn manipulation skill for vascular robotic systems.

In the United States, cardiovascular disease is the leading cause of death and the rate of maternal mortality remains among the highest of any industrialized nation. Maternal cardiometabolic health throughout gestation and postpartum is representative of placental health and physiology. Both proper placental functionality and placental microRNA expression are essential to successful pregnancy outcomes, and both are highly sensitive to genetic and environmental sources of variation. Placental pathologies, such as preeclampsia, are associated with maternal cardiovascular health but may also contribute to the developmental programming of chronic disease in offspring. However, the role of more subtle alterations to placental function and microRNA expression in this developmental programming remains poorly understood. We performed small RNA sequencing to investigate microRNA in placentae from the Rhode Island Child Health Study (n = 230). MicroRNA counts were modeled on maternal family history of cardiovascular disease using negative binomial generalized linear models. MicroRNAs were considered to be differentially expressed at a false discovery rate (FDR) less than 0.10. Parallel mRNA sequencing data and bioinformatic target prediction software were then used to identify potential mRNA targets of differentially expressed microRNAs. Nine differentially expressed microRNAs were identified (FDR < 0.1). Bioinformatic target prediction revealed 66 potential mRNA targets of these microRNAs, many of which are implicated in TGFβ signaling pathway but also in pathways involving cellular metabolism and immunomodulation. A robust association exists between familial cardiovascular disease and placental microRNA expression which may be implicated in both placental insufficiencies and the developmental programming of chronic disease.

To improve Antarctic sea-ice simulations and estimations, an ensemble-based Data Assimilation System for the Southern Ocean (DASSO) was developed based on a regional sea ice–ocean coupled model, which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. To validate the performance of DASSO, experiments were conducted from 15 April to 14 October 2016. Generally, assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. Besides considering uncertainties in the operational atmospheric forcing data, a covariance inflation procedure in data assimilation further improves the simulation of Antarctic sea ice, especially SIT. The results demonstrate the effectiveness of assimilating sea-ice observations in reconstructing the state of Antarctic sea ice, but also highlight the necessity of more reasonable error estimation for the background as well as the observation.

We report an experimental study of the Prandtl-number effects in quasi-two-dimensional (quasi-2-D) Rayleigh–Bénard convection. The experiments were conducted in four rectangular convection cells over the Prandtl-number range of $11.7 \leqslant Pr \leqslant 650.7$ and over the Rayleigh-number range of $6.0\times 10^8 \leqslant Ra \leqslant 3.0\times 10^{10}$. Flow visualization reveals that, as $Pr$ increases from 11.7 to 145.7, thermal plumes pass through the central region much less frequently and their self-organized large-scale motion is more confined along the periphery of the convection cell. The large-scale flow is found to break down for higher $Pr$, resulting in a regime transition in the Reynolds number $Re$. For the $Pr$ range with a large-scale flow of system size, the $Re$ number, Nusselt number $Nu$ and local temperature fluctuations were investigated systematically. It is found that $Re$ scales as $Re \sim Ra^{0.58}Pr^{-0.82}$ in the present geometry, which suggests that it is in line with the behaviour in the 2-D configuration. On the other hand, the measured $Nu(Ra, Pr)$ relation $Nu \sim Ra^{0.289}Pr^{-0.02}$ tends to be compatible with the finding in a three-dimensional (3-D) system. For the temperature fluctuations in the cell centre and near the sidewall, they exhibit distinct $Ra$-dependent scalings that could not be accounted for with existing theories, but their $Pr$ dependences for $Pr \lesssim 50$ are in agreement with the predictions by Grossmann & Lohse (Phys. Fluids, vol. 16, 2004, pp. 4462–4472). These results enrich our understanding of quasi-2-D thermal convection, and its similarities and differences compared to 2-D and 3-D systems.

The dependence of fishbone cycle on energetic particle intensity has been investigated in EAST low-magnetic-shear plasmas. It is observed that the fishbone mode growth rate, saturation amplitude as well as fishbone cycle frequency clearly increase with increasing neutral beam injection (NBI) power. Moreover, enhanced electron density and temperature perturbations as well as energetic particle loss were observed with greater injected NBI power. Simulation results using M3D-K code show that as the NBI power increases, the resonant frequency and the energy of the resonant particles become higher, and the saturation amplitude of the mode also changes, due to the non-perturbative energetic particle contribution. The relationship between the calculated energetic particle pressure ratio and fishbone cycle frequency is obtained as ${f_{\textrm{FC}}} = 2.2{(1000{\beta _{\textrm{ep,calc}}} - 0.1)^{5.9 \pm 0.5}}$. Results consistent with the experimental observations have been achieved based on a predator–prey model.

The surface spectral albedo was measured over coastal landfast sea ice in Prydz Bay (off Zhongshan Station), East Antarctica from 5 October to 26 November of 2016. The mean albedo decreased from late-spring to early-summer, mainly responding to the change in surface conditions from dry (phase I) to wet (phase II). The evolution of the albedo was strongly influenced by the surface conditions, with alternation of frequent snowfall events and katabatic wind that induce snow blowing at the surface. The two phases and day-to-day albedo variability were more pronounced in the near-infrared albedo wavelengths than in the visible ones, as the near-infrared photons are more sensitive to snow metamorphism, and to changes in the uppermost millimeters and water content of the surface. The albedo diurnal cycle during clear sky conditions was asymmetric with respect to noon, decreasing from morning to evening over full and patchy snow cover, and decreasing more rapidly in the morning over bare ice. We conclude that snow and ice metamorphism and surface melting dominated over the solar elevation angle dependency in shaping the albedo evolution. However, we realize that more detailed surface observations are needed to clarify and quantify the role of the various surface processes.

The ablation and acceleration of diamond-like high-density carbon foils irradiated by thermal X-ray radiations are investigated with radiation hydrodynamics simulations. The time-dependent front of the ablation wave is given numerically for radiation temperatures in the range of 100–300 eV. The mass ablation rates and ablation pressures can be derived or implied from the coordinates of ablation fronts, which agree well with reported experiment results of high-density carbon with radiation temperatures Trad in the range of 160–260 eV. It is also found that the $T_{{\rm rad}}^3$ scaling law for ablation rates does not apply to Trad above 260 eV. The trajectories of targets and hydrodynamic efficiencies for different target thicknesses can be derived from the coordinates of ablation fronts using a rocket model and the results agree well with simulations. The peak hydrodynamic efficiencies of the acceleration process are investigated for different foil thicknesses and radiation temperatures. Higher radiation temperatures and target thicknesses result in higher hydrodynamic efficiencies. The simulation results are useful for the design of fusion capsules.

A number of vision-based methods for detecting laser-induced defects on optical components have been implemented to replace the time-consuming manual inspection. While deep-learning-based methods have achieved state-of-the-art performances in many visual recognition tasks, their success often hinges on the availability of a large number of labeled training sets. In this paper, we propose a surface defect detection method based on image segmentation with a U-shaped convolutional network (U-Net). The designed network was trained on paired sets of online and offline images of optics from a large laser facility. We show in our experimental evaluation that our approach can accurately locate laser-induced defects on the optics in real time. The main advantage of the proposed method is that the network can be trained end to end on small samples, without the requirement for manual labeling or manual feature extraction. The approach can be applied to the daily inspection and maintenance of optical components in large laser facilities.

Whiting 1 is a faint and young globular cluster embedded in the Sag dSph. It has similar distance, metalicity and radial velocity with the trailing stream of the Sag. Due to these special properties, Whiting 1 was suggested to be associated with the trailing stream of Sag. However, its origin is still unclear and further investigation of its relation with Sgr dSph is needed. In this work, we use DECaLS data to search the tidal tail of Whiting 1, with the aim of looking for spatial connection between Whiting 1 and Sgr dSph. With Matched Filter method, we detected a tidal tail around the main body of Whiting 1. This tail extends to at least 0.5 degree and aligns with the mean orbit direction of Sgr dSph. This tail is newly detected and it provides additional evidence of the association between Whiting 1 and Sgr trailing stream.

LAMOST has obtained a large number of spectra for K-giant stars whose metallicities are well measured and released in DR5. Combining with the distances, radial velocities and proper motions provided by Gaia DR2, the full position and velocity information has been obtained. Using the Bayesian method we have constrained the rotational velocity of the halo and thick disk components in the local volume within 4 kpc from the Sun. The values of the rotational velocity are and for the halo and disk respectively, with the velocity of LSR assumed to be 232 km s−1. The dispersions of the rotational velocity are and for the two components. What’s more, another hot retrogradely rotating component is discovered.

We have collected 2330 Cepheids to establish an intuitive 3D map of the Milky Way’s disk. As regards the warp amplitude, the Cepheid disk agrees well with the gas disk for radii up to 15 kpc. However, the mean line of nodes (LON) of the Cepheid disk deviates from the Galactic Center–Sun direction by 17.5±1.0°. This is a new and different result compared with previous results. The LON is not stable at any given radius, but it twists. The twisted pattern suggests that the formation of the Milky Way’s warp is dominated by the massive inner disk. The kinematic warp defined by the Cepheids is also in concordance with the spatial warp. In the 2020 era, the anticipated increasing number of new Cepheids will provide a key opportunity to view our Milky Way’s disk as a whole, and we expect that our knowledge of the disk’s main structural features will be much improved.

Kevlar (polyparaphenylene terephthalamide) and PBDT (poly(2,2′-disulfonyl-4,4′-benzidine terephthalamide))-derivatives have very similar chemical structures with aromatic rings. In this study, thermal conductivities of their single chains were calculated using molecular dynamics simulations. Chain rotation was found to be the key to reducing the thermal conductivity. By introducing a new chain rotation factor (CRF), we can easily quantify chain rotation level of single-chain polymers. We demonstrated that thermal conductivity decreases as the CRF increases. We performed further calculations on phonon properties and unveiled that the small thermal conductivity led by large chain rotation can be attributed to reduced phonon group velocities and shortened phonon mean free paths. Insights obtained in this study can be used for tuning thermal conductivity of various polymers and facilitating their various applications including thermal energy conversion and management.

Orthogonal frequency division multiplex (OFDM) system is a special cognitive radio system that is widely used in military and civilian applications. As a crucial aspect of spectrum monitoring and electronic countermeasures reconnaissance, it is important to identify the OFDM signal. An identification method based on fractal box dimension and pseudo-inverse spectrum (PIS) has been proposed in this paper for the recognition problem of OFDM signal under multipath channel. Firstly, by theoretically analyzing the fractal box dimension of OFDM signal and single carrier (SC) signal, it can be concluded that the fractal box dimension of OFDM signal and SC signal has obvious differences. Thus, the fractal box dimension of the two types of signal is used to discriminate OFDM signal and SC signal. Then, the PIS of an OFDM signal is constructed according to the characteristics of the OFDM signal. Through theoretical analysis and the experimental simulation, it illustrates that the classification feature could be extracted by detecting the periodical peak of the PIS of OFDM signal and used for identifying OFDM signal in the Gaussian noise. Simulation results demonstrate that the proposed algorithm has better performance than the conventional algorithm based on autocorrelation.