Maternal syphilis not only seriously affects the quality of life of pregnant women themselves but also may cause various adverse pregnancy outcomes (APOs). This study aimed to analyse the association between the related factors and APOs in maternal syphilis. 7,030 pregnant women infected with syphilis in Henan Province between January 2016 and December 2022 were selected as participants. Information on their demographic and clinical characteristics, treatment status, and pregnancy outcomes was collected. Multivariate logistic regression models and chi-squared automatic interaction detector (CHAID) decision tree models were used to analyse the factors associated with APOs. The multivariate logistic regression results showed that the syphilis infection history (OR = 1.207, 95% CI, 1.035–1.409), the occurrence of abnormality during pregnancy (OR = 5.001, 95% CI, 4.203–5.951), not receiving standard treatment (OR = 1.370, 95% CI, 1.095–1.716), not receiving any treatment (OR = 1.313, 95% CI, 1.105–1.559), and a titre ≥1:8 at diagnosis (OR = 1.350, 95%CI, 1.079–1.690) and before delivery (OR = 1.985, 95%CI, 1.463–2.694) were risk factors. A total of six influencing factors of APOs in syphilis-infected women were screened using the CHAID decision tree model. Integrated prevention measures such as early screening, scientific eugenics assessment, and standard syphilis treatment are of great significance in reducing the incidence of APOs for pregnant women infected with syphilis.

To comprehensively study the physical properties of inductively coupled plasma (ICP), a finite element method (FEM) simulation model of ICP is developed using the well-established COMSOL software. To benchmark the validation of the FEM model, two key physical parameters, the electron density and the electron temperature of the ICP plasma, are precisely measured by the state-of-the-art laser Thomson scattering diagnostic approach. For low-pressure plasma such as ICP, the local pressure in the generator tube is difficult to measure directly. The local gas pressure in the ICP tube has been calibrated by comparing the experimental and simulation results of the maximum electron density. And on this basis, the electron density and electron temperature of ICP under the same gas pressure and absorbed power have been compared by experiments and simulations. The good agreement between the experimental and simulation data of these two key physical parameters fully verifies the validity of the ICP FEM simulation model. The experimental verification of the ICP FEM simulation model lays a foundation for further study of the distribution of various physical quantities and their variation with pressure and absorption power, which is beneficial for improving the level of ICP-related processes.

In this paper, we propose a modified Kudla–Rapoport conjecture for the Krämer model of unitary Rapoport–Zink space at a ramified prime, which is a precise identity relating intersection numbers of special cycles to derivatives of Hermitian local density polynomials. We also introduce the notion of special difference cycles, which has surprisingly simple description. Combining this with induction formulas of Hermitian local density polynomials, we prove the modified Kudla–Rapoport conjecture when $n=3$. Our conjecture, combining with known results at inert and infinite primes, implies the arithmetic Siegel–Weil formula for all non-singular coefficients when the level structure of the corresponding unitary Shimura variety is defined by a self-dual lattice.

As a major approach for controlling electromagnetic (EM) waves, metamaterials have experienced an abundant and rapid development in the 21st century. They have provided flexible and powerful techniques for controlling EM waves and brought many unique applications that are difficult to realise with natural materials. With increasing demands on dynamic controls of the EM waves, many innovations have been conducted in both three-dimensional metamaterials and two-dimensional metasurfaces, in which the meta-atom has been gradually evolved from passive to active. In 2014, coding and digital mechanisms were initially introduced to the metamaterials, further advancing the appearance of digitally programmable metamaterials. The programmable metamaterials have shown great potentials in not only real-time manipulations of the EM waves, but also direct information processing on the EM wave level. In this article, we present an in-depth review of the programmable EM metamaterials and metasurfaces, focusing on the programmable features including theoretical concepts, implementing methods and applications in EM controls. We first give a short retrospect of traditional metamaterials and metasurfaces, followed by the concepts and detailed discussions of digital coding and field-programmable metamaterials. Then, we introduce space-domain, time-domain and space–time-domain programmable metamaterials and metasurfaces, mainly focusing on their theories, functionalities, experimental implementations, and system-level applications. Finally, we conclude the current advances of the programmable metamaterials and metasurfaces, and give a prospect for the future developments.

A new system for preparing 14C samples was established for a compact accelerator mass spectrometer (GXNU-AMS) at Guangxi Normal University. This sample preparation system consists of three units: a vacuum maintenance unit, a CO2 purification unit, and a CO2 reduction unit, all of which were made of quartz glass. A series of radiocarbon (14C) preparation experiments were conducted to verify the reliability of the system. The recovery rate of graphite obtained was more than 80%. The carbon content in the commercial toner and wood sample was linearly fitted to the CO2 pressure in the measurement unit of the system. The results showed a good linear relationship, indicating that the reliability of the sample preparation system. AMS measurements were conducted on a batch of standard, wood, and dead graphite samples prepared using this system. The results showed that the beam current of 12C- for each sample was more than 40 μA, the carbon contamination introduced during the sample preparation process was ∼ 2 × 10–15, and that the new sample preparation system is compact, low-contamination, and efficient and meets the GXNU-AMS requirements for 14C samples.

Many waterflooding oil fields, injecting water into an oil-bearing reservoir for pressure maintenance, are in their middle to late stages of development. To explore the geological conditions and improve oilfield recovery of the most important well group of the Hu 136 block, located on the border areas of three provinces (Henan, Shandong, and Hebei), Zhongyuan Oilfield, Sinopec, central China, a 14C cross-well tracer monitoring technology was developed and applied in monitoring the development status and recognize the heterogeneity of oil reservoirs. The tracer response in the production well was tracked, and the water drive speed, swept volume of the injection fluid were obtained. Finally, the reservoir heterogeneity characteristics, such as the dilution coefficient, porosity, permeability, and average pore-throat radius, were fitted according to the mathematical model of the heterogeneous multi-layer inter-well theory. The 14C-AMS technique developed in this work is expected to be a potential analytical method for evaluating underground reservoir characteristics and providing crucial scientific guidance for the mid to late oil field recovery process.

Novel navigation applications provide a driving behavior score for each finished trip to promote safe driving, which is mainly based on experts’ domain knowledge. In this paper, with automobile insurance claims data and associated telematics car driving data, we propose a supervised driving risk scoring neural network model. This one-dimensional convolutional neural network takes time series of individual car driving trips as input and returns a risk score in the unit range of (0,1). By incorporating credibility average risk score of each driver, the classical Poisson generalized linear model for automobile insurance claims frequency prediction can be improved significantly. Hence, compared with non-telematics-based insurers, telematics-based insurers can discover more heterogeneity in their portfolio and attract safer drivers with premiums discounts.

This study aimed to evaluate the performance of Cobas human papillomavirus (HPV) test in cervical cancer screening. A total of 3442 women aged ⩾20 years used Cobas HPV and hybrid capture 2 (HC2) tests were included in this study. Women with any positive result were examined by liquid-based cytology (LBC) test. Then subjects with abnormal LBC or positive Cobas HPV16/18 were further checked by colposcopy to observe the visible lesions to perform the pathological examination. Of these 3442 women, 328 cases were Cobas HPV positive, and the positive rate was 9.53% (95% confidence interval (CI) 8.50–10.53). The positive rate of HPV16, HPV18, and other 12 types of high-risk HPV were 1.54% (95% CI 1.12–1.95), 0.55% (95% CI 0.30–0.80), and 7.44% (95% CI 6.56–8.32), respectively. The coincidence rate of Cobas HPV test and HC2 test was 90% (95% CI 89.00–91.00; Kappa = 0.526) in the primary screening. Age had a non-linear relationship with Cobas HPV positive rate (χ2 = 4.240, P = 0.040) and HPV16/18 typing positive rate (χ2 = 6.610, P = 0.010). Compared with the LBC test, the Cobas HPV test had higher sensitivity when detecting patients with high cervical intraepithelial neoplasia (CIN2+ and CIN3+).

The present study evaluated whether fat mass assessment using the triceps skinfold (TSF) thickness provides additional prognostic value to the Global Leadership Initiative on Malnutrition (GLIM) framework in patients with lung cancer (LC). We performed an observational cohort study including 2672 LC patients in China. Comprehensive demographic, disease and nutritional characteristics were collected. Malnutrition was retrospectively defined using the GLIM criteria, and optimal stratification was used to determine the best thresholds for the TSF. The associations of malnutrition and TSF categories with survival were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HR). Malnutrition was identified in 808 (30·2 %) patients, and the best TSF thresholds were 9·5 mm in men and 12 mm in women. Accordingly, 496 (18·6 %) patients were identified as having a low TSF. Patients with concurrent malnutrition and a low TSF had a 54 % (HR = 1·54, 95 % CI = 1·25, 1·88) greater death hazard compared with well-nourished individuals, which was also greater compared with malnourished patients with a normal TSF (HR = 1·23, 95 % CI = 1·06, 1·43) or malnourished patients without TSF assessment (HR = 1·31, 95 % CI = 1·14, 1·50). These associations were concentrated among those patients with adequate muscle mass (as indicated by the calf circumference). Additional fat mass assessment using the TSF enhances the prognostic value of the GLIM criteria. Using the population-derived thresholds for the TSF may provide significant prognostic value when used in combination with the GLIM criteria to guide strategies to optimise the long-term outcomes in patients with LC.

We report a direct numerical simulation (DNS) study of the mean velocity and temperature profiles in turbulent Rayleigh–Bénard convection (RBC) at low Prandtl numbers ($Pr$). The numerical study is conducted in a vertical thin disk with $Pr$ varied in the range $0.17\leq Pr\leq 4.4$ and the Rayleigh number ($Ra$) varied in the range $5\times 10^8\leq Ra \leq 1\times 10^{10}$. By varying $Pr$ from 4.4 to 0.17, we find a sharp change of flow patterns for the large-scale circulation (LSC) from a rigid-body rotation to a near-wall turbulent jet. We numerically examine the mean velocity equation in the bulk region and find that the mean horizontal velocity profile $u(z)$ can be determined by a balance equation between the mean convection and turbulent diffusion with a constant turbulent viscosity $\nu _t$. This balance equation admits a self-similarity jet solution, which fits the DNS data well. In the boundary-layer region, we find that both the mean temperature profile $T(z)$ and $u(z)$ can be determined by a balance equation between the molecular diffusion and turbulent diffusion. Within the viscous boundary layer, both $u(z)$ and $T(z)$ can be solved analytically and the analytical results agree well with the DNS data. Our careful characterisation of the mean velocity and temperature profiles in low-$Pr$ RBC provides a further understanding of the intricate interplay between the LSC, plume emission and boundary-layer dynamics, and pinpoints the physical mechanism for the emergence of a pronounced LSC in low-$Pr$ RBC.

Student's t test is valid for statistical inference under the normality assumption or asymptotically. By contrast, although the bootstrap t test was proposed in 1993, it is seldom adopted in medical research. We aim to demonstrate that the bootstrap t test outperforms Student's t test under normality in data. Using random data samples from normal distributions, we evaluated the testing performance, in terms of true-positive rate (TPR) and false-positive rate and diagnostic abilities, in terms of the area under the curve (AUC), of the bootstrap t test and Student's t test. We explore the AUC of both tests with varying sample size and coefficient of variation. We compare the testing outcomes using the COVID-19 serial interval (SI) data in Shenzhen and Hong Kong, China, for demonstration. With fixed TPR, the bootstrap t test maintained the equivalent accuracy in TPR, but significantly improved the true-negative rate from the Student's t test. With varying TPR, the diagnostic ability of bootstrap t test outperformed or equivalently performed as Student's t test in terms of the AUC. The equivalent performances are possible but rarely occur in practice. We find that the bootstrap t test outperforms by successfully detecting the difference in COVID-19 SI, which is defined as the time interval between consecutive transmission generations, due to sex and non-pharmaceutical interventions against the Student's t test. We demonstrated that the bootstrap t test outperforms Student's t test, and it is recommended to replace Student's t test in medical data analysis regardless of sample size.

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.

Nicotine 3,5-dihydroxybenzoate dihydrate is a nicotine salt and can be used as compositions in tobacco products. X-ray powder diffraction data, unit-cell parameters, and space group for nicotine 3,5-dihydroxybenzoate, C10H15N2⋅C7H5O4⋅2H2O, are reported [a = 8.424(1) Å, b = 13.179(8) Å, c = 8.591(1) Å, α = 90°, β = 102.073(8)°, γ = 90°, unit-cell volume V = 932.765(3) Å3, Z = 2, ρcal = 1.256 g⋅cm−3, and space group P21] at room temperature. All measured lines were indexed and are consistent with the P21 space group.

The clinical characteristics of patients with COVID-19 were analysed to determine the factors influencing the prognosis and virus shedding time to facilitate early detection of disease progression. Logistic regression analysis was used to explore the relationships among prognosis, clinical characteristics and laboratory indexes. The predictive value of this model was assessed with receiver operating characteristic curve analysis, calibration and internal validation. The viral shedding duration was calculated using the Kaplan–Meier method, and the prognostic factors were analysed by univariate log-rank analysis and the Cox proportional hazards model. A retrospective study was carried out with patients with COVID-19 in Tianjin, China. A total of 185 patients were included, 27 (14.59%) of whom were severely ill at the time of discharge and three (1.6%) of whom died. Our findings demonstrate that patients with an advanced age, diabetes, a low PaO2/FiO2 value and delayed treatment should be carefully monitored for disease progression to reduce the incidence of severe disease. Hypoproteinaemia and the fever duration warrant special attention. Timely interventions in symptomatic patients and a time from symptom onset to treatment <4 days can shorten the duration of viral shedding.