This paper focuses on analyzing data collected in situations where investigators use multiple discrete indicators as surrogates, for example, a set of questionnaires. A very flexible latent class model is used for analysis. We propose a Bayesian framework to perform the joint estimation of the number of latent classes and model parameters. The proposed approach applies the reversible jump Markov chain Monte Carlo to analyze finite mixtures of multivariate multinomial distributions. In the paper, we also develop a procedure for the unique labeling of the classes. We have carried out a detailed sensitivity analysis for various hyperparameter specifications, which leads us to make standard default recommendations for the choice of priors. The usefulness of the proposed method is demonstrated through computer simulations and a study on subtypes of schizophrenia using the Positive and Negative Syndrome Scale (PANSS).

In this study, mean velocity and temperature profiles for turbulent vertical convection (VC) confined in an infinite channel are investigated theoretically. The analysis starts from the governing equations of the thermal flow, with Reynolds shear stress and turbulent heat flux closed by the mixing length theory. Employing a three-sublayer description of the mean fields, the mean velocity and temperature profiles are found to be linear laws near the channel wall (viscosity-dominated sublayer), and they follow power laws close to the channel centre (turbulence-dominated sublayer). The characteristic scales of velocity, temperature and length in the present profiles arise naturally from the system normalisation, rather than from scaling analyses, thus ensuring a sound mathematical description. The derived profiles are verified fully via various literature data available in the classical regime; further, they are compared with the reported profiles, and the results indicate that the present profiles are the only ones with the ability to interpret data accurately from different sources, demonstrating much better versatility. Meanwhile, we provide analytical arguments showing that in the ultimate regime, the mean profiles in VC may remain in power laws, rather than the log laws inferred by analogy with Rayleigh–Bénard convection (RBC) systems. The power profiles recognised in this study are induced by the effect of buoyancy, which is in parallel with the mean flow in VC and contributes to the streamwise momentum transport, whereas in RBC systems, buoyancy is perpendicular to the mean flow, and does not influence the streamwise momentum transport, resulting in log profiles, being similar to the case of wall shear flows.

Turbulent flows above a solid surface are characterised by a hydrodynamic roughness that represents, for the far velocity field, the typical length scale at which momentum mixing occurs close to the surface. Here, we are theoretically interested in the hydrodynamic roughness induced by a two-dimensional modulated surface, the elevation profile of which is decomposed in Fourier modes. We describe the flow for a sinusoidal mode of given wavelength and amplitude with Reynolds-averaged Navier–Stokes equations closed by means of a mixing-length approach that takes into account a possible surface geometrical roughness as well as the presence of a viscous sublayer. It also incorporates spatial transient effects at the laminar–turbulent transition. Performing a weekly nonlinear expansion in the bedform aspect ratio, we predict the effective hydrodynamic roughness when the surface wavelength is varied and we show that it presents a non-monotonic behaviour at the laminar–turbulent transition when the surface is hydrodynamically smooth. Further, with a self-consistent looped calculation, we are able to recover the smooth–rough transition of a flat surface, for which the hydrodynamic roughness changes from a regime where it is dominated by the viscous length to another one where it scales with the surface corrugation. We finally apply the results to natural patterns resulting from hydrodynamic instabilities such as those associated with dissolution or sediment transport. We discuss in particular the aspect ratio selection of dissolution bedforms and roughness hierarchy in superimposed ripples and dunes.

In this study, a novel kinematic calibration method is proposed to improve the absolute positioning accuracy of 6R robot. This method can achieve indirect compensation of the 25 parameters of modified Denavit–Hartenberg (MDH). The procedures of the method are threefold. Firstly, the 25-parameter errors model of MDH is initially established. However, only the errors of 10 parameters can be directly compensated in the 25-parameter errors model, since the inverse kinematics algorithm has to meet Pieper criterion. Subsequently, a calibration method is proposed to improve accuracy of the absolute position, which uses the Newton–Raphson method to transform the 25-parameter errors into 10-parameter errors (namely T-10 parameter model). Finally, the errors corresponding to 10 parameters in the T-10 parameters model are identified through the least square method. The calibration performances of T-10 parameters model are comprehensively validated by experimentation on two ER6B-C60 robots and one RS010N robot. After kinematic calibration, the average absolute positioning accuracy of the three robots can be improved by about 90%. The results indicate that the proposed calibration method can achieve more precise absolute positioning accuracy and has a wider range of universality.

Underwater archaeology is of great significance for historical and cultural transmission and preservation of underwater heritage, but it is also a challenging task. Underwater heritage is located in an environment with high sediment content, objects are mostly buried, and the water is turbid, resulting in some of the features of objects missing or blurred, making it difficult to accurately identify and understand the semantics of various objects in the scene. To tackle these issues, this paper proposes a global enhancement network (GENet) underwater scene parsing method. We introduce adaptive dilated convolution by adding an extra regression layer, which can automatically deduce adaptive dilated coefficients according to the different scene objects. In addition, considering the easy confusion in the process of fuzzy feature classification, an enhancement classification network is proposed to increase the difference between various types of probabilities by reducing the loss function. We verified the validity of the proposed model by conducting numerous experiments on the Underwater Shipwreck Scenes (USS) dataset. We achieve state-of-the-art performance compared to the current state-of-the-art algorithm under three different conditions: conventional, relic semi-buried, and turbidified water quality. The experimental results show that the proposed algorithm performs best in different situations. To verify the generalizability of the proposed algorithm, we conducted comparative experiments on the current publicly available Cityscapes, ADE20K, and the underwater dataset SUIM. The experimental results show that this paper achieves good performance on the public dataset, indicating that the proposed algorithm is generalizable.

Objectives: Central-line–associated bloodstream infection (CLABSI) has been the leading cause of healthcare-associated infections (HAIs) in the intensive care unit (ICU) setting. Previous studies have shown that a care bundle is effective in reducing CLABSI rates; however, the data on long-term sustainability and cost savings of bundled care are limited. Methods: From January 2011 to December 2020, a prospective surveillance was performed to monitor CLABSI at a university hospital in northern Taiwan. To reduce the CLABSI rate, a hospital-wide bundled care program for CLABSI prevention was implemented in 2013. We evaluated the long-term effect of the care bundle on CLABSI incidence and length of stay in the ICU. Results: During the study period, the overall CLABSI incidence decreased from 8.22 per 1,000 catheter days before the care bundle was implemented to 6.33 per 1,000 catheter days in 2020 (P for trend <.01). The most common pathogens causing CLABSI were gut organisms (1,420 of 2,363, 60.1%), followed by environmental organisms (734 of 2,363, 31.1%) and skin organisms (177 of 2,363, 7.5%). The decreasing trend was statistically significant in the incidence of CLABSI caused by skin organisms (P for trend < .01), but not in the incidence of CLABSI caused by environmental organisms (P for trend = .86) or gut organisms (P for trend = .06). In the multivariable analysis, implementation of this care bundle was independently associated with a decrease in the CLABSI rate (RR, 0.77; 95% CI, 0.66–0.88). Compared with patients without CLABSI, patients with CLABSI had a longer average ICU length of stay (27 vs 17 days). Conclusions: A sustainable reduction in the incidence of CLABSI caused by common commensals could be achieved through a cost-saving bundled care program.

This paper revisits the melting process of phase change materials (PCMs) enclosed in a horizontally placed rectangular cavity, with isothermal and adiabatic conditions subjected to the vertical and horizontal walls, respectively. First, numerical simulations based on an improved lattice Boltzmann method are conducted to illustrate and to inform the theoretical modelling. It is shown that, compared with the traditional two-stage conduction–convection melting description, it is more reasonable to include a third stage in terms of the heat transfer behaviour. During the third stage, the remnant solid PCM is located in the corner formed by the cold and bottom walls of the cavity, and an increasing part of the input energy will be transferred directly out of the cavity without compensating for the melting latent heat, thus inducing a continuously decreasing melting rate until the end of the melting process. Then theoretical predictions are derived piecewise for the melted liquid fraction during the entire melting process, and the corresponding transitions between two successive stages are also discussed. The results are validated successfully via the available experimental and numerical data in the literature, and could guide the design and operation of latent heat storage systems.

This study aimed to describe the clinical manifestations of adenovirus infections and identify potential risk factors for co-infection with chlamydia, viruses and bacteria in hospitalised children from Hangzhou, China. From January to December 2019, the characteristics of hospitalised children infected with adenovirus at Hangzhou Children's Hospital and Zhejiang Xiaoshan Hospital were collected. The clinical factors related to co-infection with chlamydia, viruses and bacteria were assessed using multivariate logistic regression analyses. A total of 5989 children were infected with adenovirus, of which 573 were hospitalised for adenovirus infection. The severity of adenovirus respiratory infection was categorised as follows: mild (bronchiolitis, 73.6%), moderate (bronchopneumonia, 17.6%) or severe (pneumonia, 8.8%). Of the 573 children who were hospitalised, 280 presented with co-infection of chlamydia, viruses or bacteria, while the remaining 293 had only adenovirus infection. Multivariate stepwise logistic regression analyses indicated that elevated ferritin was associated with an increased risk of chlamydia co-infection (odds ratio (OR) 6.50; 95% confidence interval (CI) 1.56–27.11; P = 0.010). However, increased white blood cell (WBC) count was associated with a reduced risk of viral co-infection (OR 0.84; 95% CI 0.75–0.95; P = 0.006). The study indicated that co-infection with chlamydia could be affected by elevated ferritin levels. WBC levels could affect viral co-infection in hospitalised children infected with adenovirus.

Athetis lepigone Möschler (Lepidoptera, Noctuidae) is a common maize pest in Europe and Asia. However, there is no long-term effective management strategy is available yet to suppress its population. Adults rely heavily on olfactory cues to locate their optimal host plants and oviposition sites. Pheromone-binding proteins (PBPs) are believed to be responsible for recognizing and transporting different odorant molecules to interact with receptor membrane proteins. In this study, the ligand-binding specificities of two AlepPBPs (AlepPBP2 and AlepPBP3) for sex pheromone components and host plant (maize) volatiles were measured by fluorescence ligand-binding assay. The results demonstrated that AlepPBP2 had a high affinity with two pheromones [(Z)-7-dodecenyl acetate, Ki = 1.11 ± 0.1 μM, (Z)-9-tetradecenyl acetate, Ki = 1.32 ± 0.15 μM] and ten plant volatiles, including (-)-limonene, α-pinene, myrcene, linalool, benzaldehyde, nonanal, 2-hexanone, 3-hexanone, 2-heptanone and 6-methyl-5-hepten-2-one. In contrast, we found that none of these chemicals could bind to AlepPBP3. Our results clearly show no significant differences in the functional characterization of the binding properties between AlepPBP2 and AlepPBP3 to sex pheromones and host plant volatiles. Furthermore, molecular docking was employed for further detail on some crucial amino acid residues involved in the ligand-binding of AlepPBP2. These findings will provide valuable information about the potential protein binding sites necessary for protein-ligand interactions which appear as attractive targets for the development of novel technologies and management strategies for insect pests.

Studies have suggested an association between metabolic and cerebrocardiovascular diseases and major depressive disorder (MDD). However, the risk of metabolic and cerebrocardiovascular diseases in the unaffected siblings of patients with MDD remains uncertain. Using the Taiwan National Health Insurance Research Database, 22,438 unaffected siblings of patients with MDD and 89,752 age-/sex-matched controls were selected and followed up from 1996 to the end of 2011. Individuals who developed metabolic and cerebrocardiovascular diseases during the follow-up period were identified. Compared with the controls, the unaffected siblings of patients with MDD had a higher prevalence of metabolic diseases, such as hypertension (5.0% vs. 4.5%, p = 0.007), dyslipidemia (5.6% vs. 4.8%, p < 0.001), and obesity (1.7% vs. 1.5%, p = 0.028), and cerebrocardiovascular diseases, such as ischemic stroke (0.6% vs. 0.4%, p < 0.005) and ischemic heart disease (2.1% vs. 1.7%, p < 0.001). Logistic regression analyses revealed that the unaffected siblings of patients with MDD were more likely to develop hypertension, dyslipidemia, ischemic stroke, and ischemic heart diseases during the follow-up period than the controls. Our study revealed a familial coaggregation between MDD and metabolic and cerebrocardiovascular diseases. Additional studies are required to investigate the shared pathophysiology of MDD and metabolic and cerebrocardiovascular diseases.

We apply the first-principles calculations to investigate the structure, mechanical, and thermodynamic properties of WB12 and TiB12 under high pressure (0–100 GPa). The calculated results show that WB12 and TiB12 are thermodynamically stable at the 0 GPa or high pressure. WB12 is more thermodynamically stable than TiB12. In particular, the calculated Vickers hardness of WB12 and TiB12 at the ground state is 29.9 GPa and 43.2 GPa, respectively, indicating that TiB12 is a potential superhard material. With increasing pressure, the calculated elastic modulus of WB12 and TiB12 increases gradually. The calculated electronic structure shows that the high Vickers hardness and elastic properties of WB12 and TiB12 derive from the 3D network B–B covalent bonds. In addition, the calculated Debye temperature at the ground state is 927 K for WB12 and 1339 K for TiB12, respectively. With increasing pressure, the calculated Debye temperature of WB12 and TiB12 increases gradually. Our work shows that TiB12 not only exhibits high hardness but also shows better thermodynamic properties in comparison with WB12.