Multigrain/polydispersity has a significant impact on turbidity current (TC). Despite the fact that several researches have looked into this effect, the impact of the fluid–particle interactions is not fully understood. Motivated by this, we employ the Eulerian–Lagrangian computational fluid dynamics–discrete element method model to investigate the dynamics of the bidisperse lock-exchange TC. Results show that, because the coarse particles will settle faster and stop moving forward, the two phases of bidisperse transport and fine component transport can be distinguished in the evolution of the bidisperse TC. During the bidisperse transport stage, the upper interface of each component is primarily determined by their own settling and transport characteristics and does not strongly depend on the relative fine particle volume fraction $\phi _F$. Fine particles are primarily responsible for the vortical structures near the upper interface of the TC head, and the increase of $\phi _F$ promotes their streamwise development. In comparison, fragmented vortical coherent structures are closely related to the presence of coarse particles, which can be seen in the lower layers. Bidisperse segregation alters the collision process between dispersed phases, which differs from monodisperse TC. The collisions and segregation-induced flow establish interconnections between the two dispersed phases. In the latter stage, the transport of fine particles is inhibited by both the lift force and the contact force produced by the collision with the deposited materials. As $\phi _F$ rises, the negative contact force weakens, and its change is essentially balanced by the rise in negative lift force.

This paper focuses on the wave inverse cascade instability analysis with self-regulating feedback control for a fixed external potential field and a highly localized finite-amplitude initial pulse. The wave inverse cascade instability analysis is carried out by solving the corresponding two-dimensional generalized nonlinear Schrödinger equation. The wave field firstly suffers from the modulation instability, followed by collapse into turbulence containing the shortest-wavelength modes in the system. This is followed by inverse cascade of the shortest wavelength modes back to the longer-wavelength ones, until a statistical stationary turbulent state is reached. It is found that the inverse cascade is limited to the shorter-wavelength modes with the wavenumber $\left |k\right |\geq 100$. This shows that the viscous damping $p_i$ acts like a control switch to the inverse cascade, and the feedback control can also regulate the intensity of the inverse cascade mode.

Spatiotemporal mode-locking creates great opportunity for pulse energy scaling and nonlinear optics research in fiber. Until now, spatiotemporal mode-locking has only been realized in normal-dispersion dissipative soliton and similariton fiber lasers. In this paper, we demonstrated the first experimental realization of a spatiotemporally mode-locked soliton laser in mid-infrared fluoride fiber with anomalous dispersion. The mode-locked fluoride fiber oscillator directly generated a record pulse energy of 16.1 nJ and peak power of 74.6 kW at 2.8 μm wavelength. This work extends the spatiotemporal mode-locking to soliton fiber lasers and should have a wide interest for the laser community.

Over the years, numerous observational studies have substantiated that various dietary choices have opposing effects on CVD. However, the causal effect has not yet been established. Thus, we conducted a Mendelian randomisation (MR) analysis to reveal the causal impact of dietary habits on CVD. Genetic variants strongly associated with 20 dietary habits were selected from publicly available genome-wide association studies conducted on the UK Biobank cohort (n 449 210). Summary-level data on CVD were obtained from different consortia (n 159 836–977 323). The inverse-variance weighted method (IVW) was the primary outcome, while MR-Egger, weighted median and MR Pleiotropy RESidual Sum and Outlier were used to assess heterogeneity and pleiotropy. We found compelling evidence of a protective causal effect of genetic predisposition towards cheese consumption on myocardial infarction (IVW OR = 0·67; 95 % CI = 0·544, 0·826; P = 1·784 × 10−4) and heart failure (IVW OR = 0·646; 95 % CI = 0·513, 0·814; P = 2·135 × 10−4). Poultry intake was found to be a detrimental factor for hypertension (IVW OR = 4·306; 95 % CI = 2·158, 8·589; P = 3·416 × 10−5), while dried fruit intake was protective against hypertension (IVW OR = 0·473; 95 % CI = 0·348, 0·642; P = 1·683 × 10−6). Importantly, no evidence of pleiotropy was detected. MR estimates provide robust evidence for a causal relationship between genetic predisposition to 20 dietary habits and CVD risk, suggesting that well-planned diets may help prevent and reduce the risk of CVD.

Path-following control of wheeled mobile robots has been a crucial research topic in robotic control theory and applications. In path-following control with obstacles, the path-following control and collision avoidance goals might be conflicting, making it challenging to obtain near-optimal solutions for path-following control and obstacle avoidance with low tracking error and input energy consumption. To address this problem, we propose a potential field-based dual heuristic programming (P-DHP) algorithm with an actor–critic (AC) structure for path-following control of mobile robots with obstacle avoidance. In the proposed P-DHP, the path-following control and collision avoidance problems are decoupled into two ones to resolve the control conflict. Firstly, a neural network-based AC is constructed to approximate the near-optimal path-following control policy in a no-obstacle environment. Then, with the trained path-following control policy fixed, a potential field-based control policy structure is constructed by another AC network to generate opposite control forces as the robot moves toward the obstacle, which can guarantee the robot’s control safety and reduce the tracking error and input energy consumption in obstacle avoidance. The simulated and experimental results show that P-DHP can realize near-optimal path-following control with the satisfaction of safety constraints and outperforms state-of-the-art approaches in control performance.

The turbidity current (TC), a ubiquitous fluid–particle coupled phenomenon in the natural environment and engineering, can transport over long distances on an inclined terrain due to the suspension mechanism. A large-eddy simulation and discrete element method coupled model is employed to simulate the particle-laden gravity currents over the inclined slope in order to investigate the auto-suspension mechanism from a Lagrangian perspective. The particle Reynolds number in our TC simulation is $0.01\sim 0.1$ and the slope angle is $1/20 \sim 1/5$. The influences of initial particle concentration and terrain slope on the particle flow regimes, particle movement patterns, fluid–particle interactions, energy budget and auto-suspension index are explored. The results indicate that the auto-suspension particles predominantly appear near the current head and their number increases and then decreases during the current evolution, which is positively correlated with the coherent structures around the head. When the turbidity current propagates downstream, the average particle Reynolds number of the auto-suspension particles remains basically unchanged, and is higher than that of other transported particles. The average particle Reynolds number of the transported particles exhibits a negative correlation with the Reynolds number of the current. Furthermore, the increase in particle concentration will enhance the particle velocity, which allows the turbidity current to advance faster and improves the perpendicular support, thereby increasing the turbidity current auto-suspension capacity. Increasing slope angle will result in a slightly larger front velocity, while the effect of that on the total force is insignificant.

In strong-field physics experiments with ultraintense lasers, a single-shot cross-correlator (SSCC) is essential for fast optimization of the pulse contrast and meaningful comparison with theory for each pulse shot. To simultaneously characterize an ultrashort pulse and its long pedestal, the SSCC device must have both a high resolution and a large temporal window. However, the resolution and window in all kinds of single-shot measurement contradict each other in principle. Here we propose and demonstrate a novel SSCC device with two separate measurement channels: channel-1 for the large-window pedestal measurement has a moderate resolution but a large window, while channel-2 for the ultrashort pulse measurement has a small window but a high resolution; this allows the accurate characterization of the pulse contrast in a single shot. A two-channel SSCC device with a 200-fs resolution and 114-ps window has been developed and tested for its application in ultraintense lasers at 800 nm.

Bloodstream fungal infections have a high mortality rate. There is little data about the long-term mortality rate of fungaemia.This study aimed to explore the mortality of fungaemia and the influencing factors associated with death. In total, 204 intensive care unit (ICU) patients with fungaemia from Multi-parameter Intelligent Monitoring in Intensive Care-III (MIMIC-III) Database were studied. Age, gender, major underlying diseases, data about vital signs and blood test results were analysed to identify the predictors of the mortality and prognosis of fungaemia in ICU patients. Cox regression models were constructed, together with Kaplan−Meier survival curves. The 30-day, 1-year, 2-year, 3-year and 4-year mortality rates were 41.2%, 62.3%, 68.1%, 72.5% and 75%, respectively. Age (P ＜ 0.001, OR = 1.530; P ＜ 0.001, OR = 1.485)，serum bilirubin (P = 0.016, OR = 2.125；P = 0.001, OR = 1.748) and international normalised ratio (INR) (P = 0.001, OR = 2.642; P ＜ 0.001 OR = 2.065) were predictors of both the 30-day and 4-year mortality rates. Renal failure (P = 0.009, OR = 1.643) performed good in prediction of the 4-year mortality. The mortality of fungaemia is high. Age，the serum bilirubin and INR are good predictors of the 30-day and 4-year mortality rates of fungaemia. Renal failure has good performance in predicting the long-term mortality.

Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

A new developed spatially targeted mollusciciding technology for snail control was utilised in a research site. This study aims to analyse whether this technology can achieve rational effectiveness compared with the routine method. Snail density was monitored every spring and autumn from 2010 to 2017 at the research site and routine mollusciciding for snail control was then performed. After snail density monitoring in spring 2018, spatially targeted mollusciciding technology was adopted. Log-linear regression and nonlinear regression models were used for snail density prediction in autumn 2018 and the predicted value was compared with the actual snail density in autumn 2018 to verify the effectiveness of the spatially targeted mollusciciding. Monitoring results showed that overall snail density in the research site decreased from 2010 to 2018. The monitored snail density in autumn 2018 was 0.014/0.1 m2. Predicted by the log-linear regression model, the snail density in autumn 2018 would be 0.028 (95% CI 0.11–0.072)/0.1 m2. Predicted by the nonlinear regression model, the snail density growth in autumn 2018 in contrast to spring 2018 would be 79.79% (95% CI 54.81%–104.77%) and the actual value was 55.56%. Therefore, the effectiveness of the first application of spatially targeted mollusciciding was acceptable. However, the validation of its sustainable effectiveness still needs a replicated study comparing areas where targeted and untargeted methods are applied simultaneously and both snail abundance and human infection are monitored.

Parakmeria omeiensis is a Critically Endangered tree species in the family Magnoliaceae, endemic to south-west China. The tree is functionally dioecious, but little is known about the species’ status in the wild. We investigated the range, population size, age structure, habitat characteristics and threats to P. omeiensis. We located a total of 74 individuals in two populations on the steep slopes of Mount Emei, Sichuan province, growing under the canopy of evergreen broadleaved forest in well-drained gravel soil. A male-biased sex ratio, lack of effective pollinating insects, and habitat destruction result in low seed set and poor seedling survival in the wild. We have adopted an integrated conservation approach, including strengthening in situ conservation, cultivation of saplings, ex situ conservation and reintroduction, to protect this species. The successful conservation of P. omeiensis has important implications for the conservation of the genus Parakmeria and the family Magnoliaceae.

For the guarantee of the long-distance transport of the bunches of China Initiative Accelerator Driven System (CIADS), a new scheme is proposed that extra magnetic field is used in the accelerator-target coupling section before the windowless target to minimize the self-modulation (SM) mechanism. Particle-in-cell simulations are carried out to study the influence of the solenoidal magnetic field on the self-modulation mechanism when long proton bunches move in the background plasmas. The long proton bunches used in the simulations are similar to these in the linear accelerator of CIADS. It is found that the presence of the solenoidal magnetic field will significantly inhibit the self-modulation process. For the strong magnetic field, the longitudinal separation and transverse focusing of the long bunches disappear. We attribute these phenomena to the reason that the strong solenoidal magnetic field restricts the transverse movement of plasma electrons. Thus, there are not enough electrons around the bunch to compensate the space charge effect. Moreover, without transverse current, the longitudinal pinched effect disappears, and the long bunch can not be separated into small pulses anymore.

The quality of the polymer raw material used in plastic processing methods is an important characteristic because it is one of the main factors in producing quality products. Therefore, the characterization of polymeric pellets in the polymer processing industry is very important to avoid using inferior materials. In general, differences in the interiors of polymeric pellets reflect differences in their densities. In this study, a high-sensitivity magnetic levitation method was used to characterize the polymeric pellets in four different occasions. The device used has a high sensitivity that can distinguish minute differences as small as of 0.0041 g/cm3 in density between different samples. In addition, the method can obtain a sample's density without knowing the weight and volume of the sample. This method can be used to characterize materials by testing only a single pellet, which is very useful for polymeric pellet characterization.

In recent years, outbreaks of hand–foot–mouth disease (HFMD) in China, Singapore and other Western Pacific Region, involving millions of children, have become a big threat to public health. This study aimed to quantitatively assess all qualified studies and identify the risk factors for HFMD death. A systematic search of the databases PubMed, Medline, Embase and the Cochrane Library was performed. Study heterogeneity and publication bias were estimated. Seven case–control studies involving 1641 participants (634 died and 1007 survived) were included in the meta-analysis. Human enterovirus 71 infection, male, age ⩽3 years, vomiting, cyanosis, convulsion, duration of fever ⩾3 days, atypical rashes and abdominal distention were not significantly related to HFMD death (P ⩽ 0.05). Lethargy (odds ratio (OR) = 6.62; 95% CI 3.61–12.14; I2 = 0%; P < 0.0001), pneumonoedema/pneumorrhagia (OR = 4.09; 95% CI 2.44–6.87; I2 = 0%; P < 0.0001), seizures (OR = 6.85; 95% CI 2.37–19.74; I2 = 0%; P = 0.0004), dyspnoea (OR = 8.24; 95% CI 2.05–33.19; I2 = 83%; P = 0.003) and coma (OR = 3.76; 95% CI 1.85–7.67; I2 = 0%; P = 0.0003) were significantly associated with HFMD death, which were risk factors for HFMD death.