Machine learning (ML) models have been developed to identify randomised controlled trials (RCTs) to accelerate systematic reviews (SRs). However, their use has been limited due to concerns about their performance and practical benefits. We developed a high-recall ensemble learning model using Cochrane RCT data to enhance the identification of RCTs for rapid title and abstract screening in SRs and evaluated the model externally with our annotated RCT datasets. Additionally, we assessed the practical impact in terms of labour time savings and recall improvement under two scenarios: ML-assisted double screening (where ML and one reviewer screened all citations in parallel) and ML-assisted stepwise screening (where ML flagged all potential RCTs, and at least two reviewers subsequently filtered the flagged citations). Our model achieved twice the precision compared to the existing SVM model while maintaining a recall of 0.99 in both internal and external tests. In a practical evaluation with ML-assisted double screening, our model led to significant labour time savings (average 45.4%) and improved recall (average 0.998 compared to 0.919 for a single reviewer). In ML-assisted stepwise screening, the model performed similarly to standard manual screening but with average labour time savings of 74.4%. In conclusion, compared with existing methods, the proposed model can reduce workload while maintaining comparable recall when identifying RCTs during the title and abstract screening stages, thereby accelerating SRs. We propose practical recommendations to effectively apply ML-assisted manual screening when conducting SRs, depending on reviewer availability (ML-assisted double screening) or time constraints (ML-assisted stepwise screening).

A recent study published in Oryx proposed that the extinct Javan tiger Panthera tigris sondaica may still survive on the Island of Java, Indonesia, based on mitochondrial DNA analysis of a single hair sample collected from a location where a tiger was reportedly encountered. However, upon reanalysing the genetic data presented in that study, we conclude that there is little support for this claim. The sequences of the putative tiger hair and Javan tiger museum specimens generated are not from tiger cytoplasmic mitochondrial DNA but more likely the nuclear pseudogene copies of mitochondrial DNA. In addition, the number of mismatches between the two Javan tiger sequences is unusually high for homologous sequences that are both from tigers, suggesting potential issues with data reliability. The paper provides insufficient details on quality control measures, making it impossible to rule out the possibility that errors were introduced during the analysis. Consequently, it is inappropriate to use the sequences presented in that study to infer the existence of the Javan tiger.

Let $X=GC$ be a group, where C is a cyclic group and G is either a generalized quaternion group or a dihedral group such that $C\cap G=1$. In this paper, X is characterized and, moreover, a complete classification for $X$ is given, provided that G is a generalized quaternion group and C is core-free.

The associations between obesity and liver diseases are complex and diverse. To explore the causal relationships between obesity and liver diseases, we applied two-sample Mendelian randomisation (MR) and multivariable MR analysis. The data of exposures (BMI and WHRadjBMI) and outcomes (liver diseases and liver function biomarker) were obtained from the open genome-wide association study database. A two-sample MR study revealed that the genetically predicted BMI and WHRadjBMI were associated with non-alcoholic fatty liver disease, liver fibrosis and autoimmune hepatitis. Obesity was not associated with primary biliary cholangitis, liver failure, liver cell carcinoma, viral hepatitis and secondary malignant neoplasm of liver. A higher WHRadjBMI was associated with higher levels of biomarkers of lipid accumulation and metabolic disorders. These findings indicated independent causal roles of obesity in non-alcoholic fatty liver disease, liver fibrosis and impaired liver metabolic function rather than in viral or autoimmune liver disease.

Dual anterior interventricular artery is a rare type of CHD. We reported a fifteen-year-old girl who underwent CT angiography that demonstrated one anterior interventricular artery from aorta and another from pulmonary artery.

In preparation for an experiment with a laser-generated intense proton beam at the Laser Fusion Research Center at Mianyang to investigate the 11B(p,α)2α reaction, we performed a measurement at very low proton energy between 140 keV and 172 keV using the high-voltage platform at the Institute of Modern Physics, Lanzhou. The aim of the experiment was to test the ability to use CR-39 track detectors for cross-section measurements and to remeasure the cross-section of this reaction close to the first resonance using the thick target approach. We obtained the cross-section σ = 45.6 ± 12.5 mb near 156 keV. Our result confirms the feasibility of CR-39 type track detector for nuclear reaction measurement also in low-energy regions.

Many studies have investigated the positivity rate of hepatitis B surface antibody (HBsAb) after hepatitis B vaccine (HepB) immunization. However, the antibody level, assessed monthly or at more frequent intervals after each of the three doses, particularly within the first year after birth, has not been previously reported. To elucidate the level of antibody formation at various times after vaccination, the current study used the available detection data of HBsAb in hospitalized children to analyze the HBsAb level after immunization combined with their vaccination history. Both the positivity rate and geometric mean concentration (GMC) increased sequentially with immunization doses, reaching their peaks earlier after the third dose than after the first two doses, and the rate of HBsAb positivity was able to reach 100% between 11 and 90 days after completing the three doses of HepB. Within one year after receiving the three doses, the antibody positivity rate and GMC were maintained above 90% and 100 mIU/mL, respectively, and subsequently steadily declined, reaching the lowest value in the 9th and 10th years. The current findings reveal, in more detail, the level of antibody formation at different times following each dose of HepB in hospitalized children, particularly in the age group up to one year after vaccination. For the subjects of this study, we prefer to believe that the proportion of HBsAb non-response should be less than 5% after full immunization with HepB, provided that the appropriate time for blood collection is chosen.

We numerically investigated the global linear instability and bifurcations in electro-thermo-convection (ETC) of a dielectric liquid confined in a two-dimensional (2-D) concentric annulus subjected to a strong unipolar injection. Seven kinds of solutions exist in this ETC system due to the complex bifurcations, i.e. saddle-node, subcritical and supercritical Hopf bifurcations. These bifurcation routes constitute at most four solution branches. Global linear instability analysis and energy analysis were conducted to explain the instability mechanism and transition of different solutions and to predict the local instability regions. The linearized lattice Boltzmann method (LLBM) for global linear instability analysis, first proposed by Pérez et al. (Theor. Comput. Fluid Dyn., vol. 31, 2017, pp. 643–664) to analyse incompressible flows, was extended here to solve the whole set of coupled linear equations, including the linear Navier–Stokes equations, the linear energy equation, Poisson's equation and the linear charge conservation equation. A multiscale analysis was also performed to recover the macroscopic linearized Navier–Stokes equations from the four different discrete lattice Boltzmann equations (LBEs). The LLBM was validated by calculating the linear critical value of 2-D natural convection; it has an error of 1.39% compared with the spectral method. Instability with global travelling wave behaviour is a unique behaviour in the annulus configuration electrothermohydrodynamic system, which may be caused by the baroclinity. Finally, the chaotic behaviour was quantitatively analysed through calculation of the fractal dimension and Lyapunov exponent.

The aim of this study is to evaluate the infection risk of aircraft passengers seated within and beyond two rows of the index case(s) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A(H1N1)pdm09 virus, and SARS-CoV-1. PubMed databases were searched for articles containing information on air travel–related transmission of SARS-CoV-2, influenza A(H1N1)pdm09 virus, and SARS-CoV-1 infections. We performed a meta-analysis of inflight infection data. In the eight flights where the attack rate could be calculated, the inflight SARS-CoV-2 attack rates ranged from 2.6% to 16.1%. The risk ratios of infection for passengers seated within and outside the two rows of the index cases were 5.64 (95% confidence interval (CI):1.94–16.40) in SARS-CoV-2 outbreaks, 4.26 (95% CI:1.08–16.81) in the influenza A(H1N1)pdm09 virus outbreaks, and 1.91 (95% CI:0.80–4.55) in SARS-CoV-1 outbreaks. Furthermore, we found no significant difference between the attack rates of SARS-CoV-2 in flights where the passengers were wearing masks and those where they were not (p = 0.22). The spatial distribution of inflight SARS-CoV-2 outbreaks was more similar to that of the influenza A(H1N1)pdm09 virus outbreaks than to that of SARS-CoV-1. Given the high proportion of asymptomatic or pre-symptomatic infection in SARS-CoV-2 transmission, we hypothesised that the proximity transmission, especially short-range airborne route, might play an important role in the inflight SARS-CoV-2 transmission.

In recent years, the extraction of overlapping relations has received great attention in the field of natural language processing (NLP). However, most existing approaches treat relational triples in sentences as isolated, without considering the rich semantic correlations implied in the relational hierarchy. Extracting these overlapping relational triples is challenging, given the overlapping types are various and relatively complex. In addition, these approaches do not highlight the semantic information in the sentence from coarse-grained to fine-grained. In this paper, we propose an end-to-end neural framework based on a decomposition model that incorporates multi-granularity relational features for the extraction of overlapping triples. Our approach employs an attention mechanism that combines relational hierarchy information with multiple granularities and pretrained textual representations, where the relational hierarchies are constructed manually or obtained by unsupervised clustering. We found that the different hierarchy construction strategies have little effect on the final extraction results. Experimental results on two public datasets, NYT and WebNLG, show that our mode substantially outperforms the baseline system in extracting overlapping relational triples, especially for long-tailed relations.

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.

Modal global linear stability analysis of thermal convection is performed with the linearized lattice Boltzmann method (LLBM). The onset of Rayleigh–Bénard convection in rectangular cavities with conducting and adiabatic sidewalls and the instability of two-dimensional (2-D) and three-dimensional (3-D) natural convection in cavities are studied. The method of linearizing the local equilibrium probability distribution function that was first proposed by Pérez et al. (Theor. Comp. Fluid Dyn., vol. 31, 2017, pp. 643–664) is extended to solve the coupled linear Navier–Stokes equations together with the linear energy equation in this work. A multiscale analysis is also performed to recover the macroscopic linear Navier–Stokes equations from the discrete lattice Boltzmann equations for both the single and multiple relaxation time models. The present LLBM is implemented in the framework of the Palabos library. It is validated by calculating the linear critical value of 2-D natural convection that the LLBM with the multiple relaxation time model has an error less than 1 % compared with the spectral method. The instability mechanism of the flow is explained by kinetic energy transfer analysis. It is shown that the buoyancy mechanism and inertial mechanism tend to stabilize the Hopf bifurcation of the 2-D natural convection at Pr < 0.08 and Pr > 1, respectively. For 3-D natural convection, subcritical bifurcation of the Hopf type is found for low-Prandtl-number fluids (Pr < 0.1).

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.

This study was a retrospective multicentre cohort study of patients with coronavirus disease 2019 (COVID-19) diagnosed at 24 hospitals in Jiangsu province, China as of 15 March 2020. The primary outcome was the occurrence of acute respiratory failure during hospital stay. Of 625 patients, 56 (9%) had respiratory failure. Some selected demographic, epidemiologic, clinical and laboratory features as well as radiologic features at admission and treatment during hospitalisation were significantly different in patients with and without respiratory failure. The multivariate logistic analysis indicated that age (in years) (odds ratio [OR], 1.07; 95% confidence interval [CI]: 1.03–1.10; P = 0.0002), respiratory rate (breaths/minute) (OR, 1.23; 95% CI: 1.08–1.40; P = 0.0020), lymphocyte count (109/l) (OR, 0.18; 95% CI: 0.05–0.69; P = 0.0157) and pulmonary opacity score (per 5%) (OR, 1.38; 95% CI: 1.19–1.61; P < 0.0001) at admission were associated with the occurrence of respiratory failure. Older age, increased respiratory rate, decreased lymphocyte count and greater pulmonary opacity score at admission were independent risk factors of respiratory failure in patients with COVID-19. Patients having these risk factors need to be intensively managed during hospitalisation.