During the investigation of parasitic pathogens of Mytilus coruscus, infection of a Perkinsus-like protozoan parasite was detected by alternative Ray's Fluid Thioglycolate Medium (ARFTM). The diameter of hypnospores or prezoosporangia was 8–27 (15.6 ± 4.0, n = 111) μm. The prevalence of the Perkinsus-like species in M. coruscus was 25 and 12.5% using ARFTM and PCR, respectively. The ITS1-5.8S-ITS2 fragments amplified by PCR assay had 100% homology to that of P. beihaiensis, suggesting that the protozoan parasite was P. beihaisensis and M. coruscus was its new host in East China Sea (ECS). Histological analysis showed the presence of trophozoites of P. beihaiensis in gill, mantle and visceral mass, and the schizonts only found in visceral mass. Perkinsus beihaiensis infection led to inflammatory reaction of hemocyte and the destruction of digestive tubules in visceral mass, which had negative effect on health of the farmed M. coruscus and it deserves more attention.

This study applies a comprehensive bioecological perspective to address a significant gap in the childhood adversity literature by employing latent profile analysis to examine the impact of diverse combinations of early childhood adversities and protective factors on adolescent psychosocial and behavioral outcomes. Drawing from the United Kingdom’s Millennium Cohort Study (N = 19,444), we identified eight unique profiles of early childhood adversity and protective factors. These profiles provide a nuanced understanding of adversity combinations and allow for differentiation between groups with similar profiles. Latent profile membership was a significant predictor of all adolescent outcome variables, indicating that profiles differed significantly from one another on psychosocial and behavioral outcomes (Wald values ranged from 10.10–623.22; p < .001). Some findings support the cumulative risk model, indicating that exposure to multiple early adversities increases the likelihood of adverse outcomes. However, we also found that specific adversities, such as parental psychopathology, parental alcohol use, and neighborhood deprivation, uniquely impact adolescent outcomes. This study highlights the necessity for tailored interventions and policies to support children with distinct early life experiences, emphasizing the importance of addressing both cumulative and specific adversities at multiple levels to prevent psychosocial and behavioral problems in adolescence.

Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near-atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and three-dimensional (3D) classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other using deep learning. TomoNet’s hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNet’s potential for broad applications to various cryoET projects targeting high-resolution in situ structures.

The status of the genera Euparagonimus Chen, 1963 and Pagumogonimus Chen, 1963 relative to Paragonimus Braun, 1899 was investigated using DNA sequences from the mitochondrial cytochrome c oxidase subunit I (CO1) gene (partial) and the nuclear ribosomal DNA second internal transcribed spacer (ITS2). In the phylogenetic trees constructed, the genus Pagumogonimus is clearly not monophyletic and therefore not a natural taxon. Indeed, the type species of Pagumogonimus,P. skrjabini from China, is very closely related to Paragonimus miyazakii from Japan. The status of Euparagonimus is less obvious. Euparagonimus cenocopiosus lies distant from other lungflukes included in the analysis. It can be placed as sister to Paragonimus in some analyses and falls within the genus in others. A recently published morphological study placed E. cenocopiosus within the genus Paragonimus and probably this is where it should remain.

Samples of Na-saturated, Upton montmorillonite were prepared with different contents of water (H2O or D2O) by: (1) adsorption of water from the vapor phase at a specific value of p/p°, the relative humidity, (2) adsorption of water from the vapor phase at p/p° = 1.0 followed by desorption of the water into the vapor phase at a specific p/p° < 1.0, and (3) adsorption of water from the liquid phase followed by desorption of the water into the vapor phase at a specific p/p° < 1.0. Water adsorbed initially from the vapor phase was called V-adsorbed water, and water adsorbed initially from the liquid phase was called L-adsorbed water. The water contents of these samples were determined by gravimetric analysis, the c-axis spacings by X-ray powder diffraction, the O-D stretching frequencies by IR spectroscopy, and the heats of immersion by differential microcalorimetry. No difference was found between V-adsorbed and L-adsorbed water; however, if the final water content was established by adsorption, the system was in a different state than if the final water content was established by desorption. In particular, hysteresis was observed in the following properties: the relative humidity of the adsorbed water, the O-D stretching frequency in this water, and the degree of order in the stacking of the clay layers. The only property that did not exhibit hysteresis was the heat of immersion. Apparently, hysteresis occurred because the orderliness of the system was not reversible, and, thus, any property that depended on orderliness was hysteretic.

The reactivity of basal surfaces, steps and edges of muscovite was studied by imaging surface precipitates of PbCl2 using atomic force microscopy (AFM). We reacted PbCl2 solution with freshly cleaved muscovite surfaces and found that PbCl2 precipitates were formed on the basal surfaces, steps and edges. It was observed that PbCl2 precipitated preferentially along the steps compared to the basal surfaces and that PbCl2 precipitates at multiple-layer edges were needle-shaped and oriented in different directions. One of the muscovite samples we cleaved had muscovite fragments sitting on the freshly cleaved surfaces. These fragments resulted from previously formed cracks. Thus, we were able to compare the reactivity of the weathered surfaces with that of freshly cleaved surfaces. It was found that PbCl2 was not precipitated along the edges of previously cracked muscovite fragments. These results clearly demonstrated that the edges of freshly cleaved muscovite are the most reactive surface sites, whereas the edges of weathered muscovite are not as reactive. We believe that the surface reactivity of the edges of freshly cleaved muscovite is likely due to terminal or Al-OH1/2− groups on these crystalline surfaces, which favor adsorption of Pb2+ ions and the subsequent nucleation and precipitation reactions. We also investigated the effect of drying rate on the morphology of the surface precipitates. Fast drying resulted in a nearly complete covered surface with a leaflike morphology, whereas slow drying resulted in more isolated surface clusters.

Transient electromagnetic field plays very important roles in the evolution of high-energy-density matter or laser plasma. Now, a new design is proposed in this paper to diagnose the transient magnetic field, using relativistic electron bunch as a probe based on high-energy electron radiography. And based on this scheme, the continuous distribution of magnetic strength field can be snapshotted. For 1 mm thick quadrupole magnet model measured by 50 MeV probe electron beams, the simulation result indicates that this diagnosis has spatial resolution better than 4 microns and high measurement accuracy for strong magnetic strength and high magnetic gradient field no matter whether the magnetic interaction is focusing or defocusing for the range from -510 T∗ μm to 510 T∗ μm.

The prevalence of workaholism has negative consequences on human health. Lack of sleep, a well-known problem among adults in modern society, is often attributed to overwork as a result of workaholism. Yet there is a lack of empirical research examining how and when workaholism will lead to sleep problems. To answer this question and to examine the longitudinal effect of workaholism on sleep in China, we investigate the mediating role of perceived evening responsibilities of work and the moderating effect of work autonomy. Two hundred and five Chinese working adults (58.0% female) voluntarily completed the online questionnaires at Time 1 (T1) and Time 2 (T2; 1-month later). Results showed that workaholism at T1 had a significant and positive correlation with sleep problem at T2. Further analysis suggested that perceived evening responsibilities of work fully mediated the relationship between workaholism and sleep problem. Work autonomy was shown to buffer the positive effect of workaholism on perceived evening responsibilities of work and attenuate the indirect effect of workaholism on sleep problem. While workers should be made aware of the negative impact of workaholism on sleep, organizations should also consider interventions to enhance employees’ autonomy and control of their work.

A multi-agent deep reinforcement learning (DRL)-based model is presented in this study to reconstruct flow fields from noisy data. A combination of reinforcement learning with pixel-wise rewards, physical constraints represented by the momentum equation and the pressure Poisson equation, and the known boundary conditions is used to build a physics-constrained deep reinforcement learning (PCDRL) model that can be trained without the target training data. In the PCDRL model, each agent corresponds to a point in the flow field and learns an optimal strategy for choosing pre-defined actions. The proposed model is efficient considering the visualisation of the action map and the interpretation of the model operation. The performance of the model is tested by using direct numerical simulation-based synthetic noisy data and experimental data obtained by particle image velocimetry. Qualitative and quantitative results show that the model can reconstruct the flow fields and reproduce the statistics and the spectral content with commendable accuracy. Furthermore, the dominant coherent structures of the flow fields can be recovered by the flow fields obtained from the model when they are analysed using proper orthogonal decomposition and dynamic mode decomposition. This study demonstrates that the combination of DRL-based models and the known physics of the flow fields can potentially help solve complex flow reconstruction problems, which can result in a remarkable reduction in the experimental and computational costs.

Competition among the two-plasmon decay (TPD) of backscattered light of stimulated Raman scattering (SRS), filamentation of the electron-plasma wave (EPW) and forward side SRS is investigated by two-dimensional particle-in-cell simulations. Our previous work [K. Q. Pan et al., Nucl. Fusion 58, 096035 (2018)] showed that in a plasma with the density near 1/10 of the critical density, the backscattered light would excite the TPD, which results in suppression of the backward SRS. However, this work further shows that when the laser intensity is so high ($>{10}^{16}$ W/cm2) that the backward SRS cannot be totally suppressed, filamentation of the EPW and forward side SRS will be excited. Then the TPD of the backscattered light only occurs in the early stage and is suppressed in the latter stage. Electron distribution functions further show that trapped-particle-modulation instability should be responsible for filamentation of the EPW. This research can promote the understanding of hot-electron generation and SRS saturation in inertial confinement fusion experiments.

Machine vision has been extensively researched in the field of unmanned aerial vehicles (UAV) recently. However, the ability of Sense and Avoid (SAA) largely limited by environmental visibility, which brings hazards to flight safety in low illumination or nighttime conditions. In order to solve this critical problem, an approach of image enhancement is proposed in this paper to improve image qualities in low illumination conditions. Considering the complementarity of visible and infrared images, a visible and infrared image fusion method based on convolutional sparse representation (CSR) is a promising solution to improve the SAA ability of UAVs. Firstly, the source image is decomposed into a texture layer and structure layer since infrared images are good at characterising structural information, and visible images have richer texture information. Both the structure and the texture layers are transformed into the sparse convolutional domain through the CSR mechanism, and then CSR coefficient mapping are fused via activity level assessment. Finally, the image is synthesised through the reconstruction results of the fusion texture and structure layers. In the experimental simulation section, a series of visible and infrared registered images including aerial targets are adopted to evaluate the proposed algorithm. Experimental results demonstrates that the proposed method increases image qualities in low illumination conditions effectively and can enhance the object details, which has better performance than traditional methods.

The target backsheath field acceleration mechanism is one of the main mechanisms of laser-driven proton acceleration (LDPA) and strongly depends on the comprehensive performance of the ultrashort ultra-intense lasers used as the driving sources. The successful use of the SG-II Peta-watt (SG-II PW) laser facility for LDPA and its applications in radiographic diagnoses have been manifested by the good performance of the SG-II PW facility. Recently, the SG-II PW laser facility has undergone extensive maintenance and a comprehensive technical upgrade in terms of the seed source, laser contrast and terminal focus. LDPA experiments were performed using the maintained SG-II PW laser beam, and the highest cutoff energy of the proton beam was obviously increased. Accordingly, a double-film target structure was used, and the maximum cutoff energy of the proton beam was up to 70 MeV. These results demonstrate that the comprehensive performance of the SG-II PW laser facility was improved significantly.

The control of a wing-in-ground craft (WIG) usually allows for many needs, like cruising, speed, survival and stealth. Various degrees of emphasis on these requirements result in different trajectories, but there has not been a way of integrating and quantifying them yet. Moreover, most previous studies on other vehicles’ multi-objective trajectory is planned globally, lacking for local planning. For the multi-objective trajectory planning of WIGs, this paper proposes a multi-objective function in a polynomial form, in which each item represents an independent requirement and is adjusted by a linear or exponential weight. It uses the magnitude of weights to demonstrate how much attention is paid relatively to the corresponding demand. Trajectories of a virtual WIG model above the wave trough terrain are planned using reward shaping based on the introduced multi-objective function and deep reinforcement learning (DRL). Two conditions are considered globally and locally: a single scheme of weights is assigned to the whole environment, and two different schemes of weights are assigned to the two parts of the environment. Effectiveness of the multi-object reward function is analysed from the local and global perspectives. The reward function provides WIGs with a universal framework for adjusting the magnitude of weights, to meet different degrees of requirements on cruising, speed, stealth and survival, and helps WIGs guide an expected trajectory in engineering.

The paper addresses the six-degree-of-freedom coupled control problem for spacecraft formation flying subject to actuator saturation and input quantisation whilst considering limited communication resources. Firstly, a novel event-triggered distributed observer without continuous communications is presented to recover the information of the virtual leader. Remarkably, by embedding a hyperbolic tangent function-based nonlinear term into the triggering condition, the event-based observer realises a more reasonable trigger threshold. Subsequently, an adding-a-power-integrator-based fixed-time control algorithm is proposed for the follower spacecraft. Further, the control scheme ingeniously compensates for the actuator saturation and the input quantisation problems without embedding auxiliary systems. Finally, numerical simulations are carried out to highlight the advantages of the theoretical results.

The Hall–Vinen–Bekharevich–Khalatnikov (HVBK) model is widely used to numerically study quantum turbulence in superfluid helium. Based on the two-fluid model of Tisza and Landau, the HVBK model describes the normal (viscous) and superfluid (inviscid) components of the flow using two Navier–Stokes type of equations, coupled through a mutual friction force term. We derive transport equations for the third-order moments for each component of velocity involving the fourth-order moments, which are classical probes for internal intermittency at any scale, and revealing the probability of rare and strong fluctuations. Budget equations are assessed through direct numerical simulations of the HVBK flow. We simulate a forced homogeneous isotropic turbulent flow with Reynolds number of the normal fluid (based on Taylor's microscale) close to 100. Values from 0.1 to 10 are considered for the ratio between the normal and superfluid densities. For these flows, an inertial range is not discernible and the restricted scaling range approach is used to take into account the finite Reynolds number (FRN) effect. We analyse the importance of each term in budget equations and emphasize their role in energy exchange between normal and superfluid components. Some interesting features are observed: (i) transport and pressure-related terms are dominant, similarly to single-fluid turbulence; and (ii) the mathematical signature of the FRN effect is weak despite the low value of the Reynolds number. The flatness of the velocity derivatives is finally studied through the transport equations and their limit for very small scales, and it is shown to gradually increase for lower and lower temperatures, for both normal fluid and superfluid. This similarity highlights the strong locking of the two fluids. The flatness factors are also found in reasonable agreement with classical turbulence.

We study how derivatives (with nonlinear payoffs) affect the underlying asset’s liquidity. In a rational expectations equilibrium, informed investors expect low conditional volatility and sell derivatives to the others. These derivative trades affect different investors’ utility differently, possibly amplifying liquidity risk. As investors delta hedge their derivative positions, price impact in the underlying drops, suggesting improved liquidity, because informed trading is diluted. In contrast, effects on price reversal are ambiguous, depending on investors’ relative delta hedging sensitivity (i.e., the gamma of the derivatives). The model cautions of potential disconnections between illiquidity measures and liquidity risk premium due to derivatives trading.