Hand, foot, and mouth disease (HFMD) shows spatiotemporal heterogeneity in China. A spatiotemporal filtering model was constructed and applied to HFMD data to explore the underlying spatiotemporal structure of the disease and determine the impact of different spatiotemporal weight matrices on the results. HFMD cases and covariate data in East China were collected between 2009 and 2015. The different spatiotemporal weight matrices formed by Rook, K-nearest neighbour (KNN; K = 1), distance, and second-order spatial weight matrices (SO-SWM) with first-order temporal weight matrices in contemporaneous and lagged forms were decomposed, and spatiotemporal filtering model was constructed by selecting eigenvectors according to MC and the AIC. We used MI, standard deviation of the regression coefficients, and five indices (AIC, BIC, DIC, R2, and MSE) to compare the spatiotemporal filtering model with a Bayesian spatiotemporal model. The eigenvectors effectively removed spatial correlation in the model residuals (Moran’s I < 0.2, p > 0.05). The Bayesian spatiotemporal model’s Rook weight matrix outperformed others. The spatiotemporal filtering model with SO-SWM was superior, as shown by lower AIC (92,029.60), BIC (92,681.20), and MSE (418,022.7) values, and higher R2 (0.56) value. All spatiotemporal contemporaneous structures outperformed the lagged structures. Additionally, eigenvector maps from the Rook and SO-SWM closely resembled incidence patterns of HFMD.

In the contemporary maritime industry, characterised by intense competition, reduced visibility due to heavy fog is a primary cause of accidents, significantly impairing maritime operational efficiency. Consequently, investigating foggy weather navigation safety holds crucial practical significance. This paper, through an analysis and synthesis of various aspects of foggy navigation technology, including foggy navigation regulations at different ports, fog warnings, foggy vessel environmental perception and foggy auxiliary navigation systems, explores the key issues concerning vessel navigation during foggy conditions from a scientific perspective. This discussion encompasses the aspects of regulatory frameworks, standardisation, and the development of intelligent and responsive onboard equipment. Finally, the paper offers a glimpse into potential strategies for fog navigation.

Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models are determined by the subjectively assigned scales of the latent variables. Thus, conclusions in existing studies comparing structural equation modeling (SEM) and path analysis with weighted composites (PAWC) on the accuracy and precision of the estimates of the indirect effect in mediation analysis have little validity. Instead of comparing the size on estimates of the indirect effect between SEM and PAWC, this article compares parameter estimates by signal-to-noise ratio (SNR), which does not depend on the metrics of the latent variables once the anchors of the latent variables are determined. Results show that PAWC yields greater SNR than SEM in estimating and testing the indirect effect even when measurement errors exist. In particular, path analysis via factor scores almost always yields greater SNRs than SEM. Mediation analysis with equally weighted composites (EWCs) also more likely yields greater SNRs than SEM. Consequently, PAWC is statistically more efficient and more powerful than SEM in conducting mediation analysis in empirical research. The article also further studies conditions that cause SEM to have smaller SNRs, and results indicate that the advantage of PAWC becomes more obvious when there is a strong relationship between the predictor and the mediator, whereas the size of the prediction error in the mediator adversely affects the performance of the PAWC methodology. Results of a real-data example also support the conclusions.

The paper develops a two-stage robust procedure for structural equation modeling (SEM) and an R package rsem to facilitate the use of the procedure by applied researchers. In the first stage, M-estimates of the saturated mean vector and covariance matrix of all variables are obtained. Those corresponding to the substantive variables are then fitted to the structural model in the second stage. A sandwich-type covariance matrix is used to obtain consistent standard errors (SE) of the structural parameter estimates. Rescaled, adjusted as well as corrected and F-statistics are proposed for overall model evaluation. Using R and EQS, the R package rsem combines the two stages and generates all the test statistics and consistent SEs. Following the robust analysis, multiple model fit indices and standardized solutions are provided in the corresponding output of EQS. An example with open/closed book examination data illustrates the proper use of the package. The method is further applied to the analysis of a data set from the National Longitudinal Survey of Youth 1997 cohort, and results show that the developed procedure not only gives a better endorsement of the substantive models but also yields estimates with uniformly smaller standard errors than the normal-distribution-based maximum likelihood.

This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found. Conditions under which monotonic relationships do not exist are also identified. Such functional relationships allow researchers to better understand the problem when significant factor loading estimates are expected but not obtained, and vice versa. What will affect the likelihood for Heywood cases (negative unique variance estimates) is also explicit through these relationships. Empirical findings in the literature are discussed using the obtained results.

This study demonstrates a kilowatt-level, spectrum-programmable, multi-wavelength fiber laser (MWFL) with wavelength, interval and intensity tunability. The central wavelength tuning range is 1060–1095 nm and the tunable number is controllable from 1 to 5. The wavelength interval can be tuned from 6 to 32 nm and the intensity of each channel can be adjusted independently. Maximum output power up to approximately 1100 W has been achieved by master oscillator power amplifier structures. We also investigate the wavelength evolution experimentally considering the difference of gain competition, which may give a primary reference for kW-level high-power MWFL spectral manipulation. To the best of our knowledge, this is the highest output power ever reported for a programmable MWFL. Benefiting from its high power and flexible spectral manipulability, the proposed MWFL has great potential in versatile applications such as nonlinear frequency conversion and spectroscopy.

The material removal rate (MRR) serves as a crucial indicator in the chemical mechanical polishing (CMP) process of semiconductor wafers. Currently, the mainstream method to ascertain the MRR through offline measurements proves time inefficient and struggles to represent process variability accurately. An efficient MRR prediction model based on stacking ensemble learning that integrates models with disparate architectures was proposed in this study. First, the processing signals collected during wafer polishing, as available in the PHM2016 dataset, were analyzed and preprocessed to extract statistical and neighbor domain features. Subsequently, Pearson correlation coefficient analysis (PCCA) and principal component analysis (PCA) were employed to fuse the extracted features. Ultimately, random forest (RF), light gradient boosting machine (LightGBM), and backpropagation neural network (BPNN) with hyperparameters optimized by the Bayesian Optimization Algorithm were integrated to establish an MRR prediction model based on stacking ensemble learning. The developed model was verified on the PHM2016 benchmark test set, and a Mean Square Error (MSE) of 7.72 and a coefficient of determination (R2) of 95.82% were achieved. This indicates that the stacking ensemble learning based model, integrated with base models of disparate architectures, offers considerable potential for real-time MRR prediction in the CMP process of semiconductor wafers.

Several novel anthropometric indices, including paediatric body adiposity index (BAIp) and triponderal mass index (TMI), have emerged as potential tools for estimating body fat in preschool children. However, their comparative validity and accuracy, particularly when compared with established indicators such as BMI, have not been thoroughly investigated. This cross-sectional study enrolled 2869 preschoolers aged 3–6 years in Wuhan, China. The non-parametric Bland–Altman analysis was employed to evaluate the agreement between BMI, BAIp and TMI with percentage of body fat (PBF), determined by bioelectrical impedance analysis (BIA), serving as the reference measure of adiposity. Additionally, receiver operating characteristic curve analysis was conducted to assess the effectiveness of BMI, BAIp and TMI in screening for obesity. BAIp demonstrated the least bias in estimating PBF, showing discrepancies of 3·64 % (95 % CI 3·40 %, 4·12 %) in boys and 3·95 % (95 % CI 3·79 %, 4·23 %) in girls. Conversely, BMI underestimated PBF by 3·89 % (95 % CI 3·70 %, 4·37 %) in boys and 4·81 % (95 % CI 4·59 %, 5·09 %) in girls, while TMI also underestimated PBF by 5·15 % (95 % CI 4·90 %, 5·52 %) in boys and 5·68 % (95 % CI 5·30 %, 5·91 %) in girls. BAIp exhibited the highest AUC values (AUC = 0·867–0·996) in boys, whereas in girls, there was no statistically significant difference between BMI (AUC = 0·936, 95 % CI 0·921, 0·948) and BAIp (AUC = 0·901, 95 % CI 0·883, 0·916) in girls (P = 0·054). In summary, when considering the identification of obesity, BAIp shows promise as a screening tool for both boys and girls.

Sjögren's syndrome (SS) is a chronic autoimmune disease caused by immune system disorders. The main clinical manifestations of SS are dry mouth and eyes caused by the destruction of exocrine glands, such as the salivary and lacrimal glands, and systemic manifestations, such as interstitial pneumonia, interstitial nephritis and vasculitis. The pathogenesis of this condition is complex. However, this has not been fully elucidated. Treatment mainly consists of glucocorticoids, disease-modifying antirheumatic drugs and biological agents, which can only control inflammation but not repair the tissue. Therefore, identifying methods to regulate immune disorders and repair damaged tissues is imperative. Cell therapy involves the transplantation of autologous or allogeneic normal or bioengineered cells into the body of a patient to replace damaged cells or achieve a stronger immunomodulatory capacity to cure diseases, mainly including stem cell therapy and immune cell therapy. Cell therapy can reduce inflammation, relieve symptoms and promote tissue repair and regeneration of exocrine glands such as the salivary glands. It has broad application prospects and may become a new treatment strategy for patients with SS. However, there are various challenges in cell preparation, culture, storage and transportation. This article reviews the research status and prospects of cell therapies for SS.

We report on an experimental study of turbulent Rayleigh–Bénard convection with asymmetric top and bottom plates. The plates are covered with pyramid-shaped roughness elements whose aspect ratios are $\lambda =1$ or $\lambda =4$. In the low-Rayleigh-number regime ($Ra<1.9\times 10^9$), the heat transport efficiencies in the asymmetric cells, characterized by the Nusselt number, are smaller than those measured in a symmetric $\lambda = 1$ cell and are greater than those for a symmetric $\lambda = 4$ cell, whereas in the high-Rayleigh-number regime ($Ra>1.9\times 10^9$), the Nusselt numbers of the asymmetric cells are, in turn, greater than those for the symmetric cell with $\lambda = 1$ and smaller than those for the symmetric cell with $\lambda = 4$. In addition, the heat transports of individual plates are studied based on the temperature drops across both halves of the cell. In the low-$Ra$ regime, the $\lambda =1$ plate shows higher heat transfer than the $\lambda =4$ plate, while for the high-$Ra$ regime, the $\lambda =4$ plate shows a higher heat transport ability. In both regimes, the individual Nusselt number of the plate with lower heat transfer is insensitive to the topology of the other plate. Besides, it is found that the symmetry of the centre temperature distribution is robust to the symmetry breaking of boundary topographies. For the $Ra$ range explored, a weak temperature inversion is observed in the bulk of asymmetric rough cells. Finally, we remark that the temperature fluctuation at the cell centre and the Reynolds number associated with the large-scale circulation show universal power laws in terms of the flux Rayleigh number as $\sigma _{T_{c}}\sim Ra_F^{0.68}$ and $Re_{LSC}\sim Ra_F^{0.36}$, respectively.

We present a systematic study on the effects of small aspect ratios $\varGamma$ on heat transport in liquid metal convection with a Prandtl number of $Pr=0.029$. The study covers $1/20\le \varGamma \le 1$ experimentally and $1/50\le \varGamma \le 1$ numerically, and a Rayleigh number $Ra$ range of $4\times 10^3 \le Ra \le 7\times 10^{9}$. It is found experimentally that the local effective heat transport scaling exponent $\gamma$ changes with both $Ra$ and $\varGamma$, attaining a $\varGamma$-dependent maximum value before transition-to-turbulence and approaches $\gamma =0.25$ in the turbulence state as $Ra$ increases. Just above the onset of convection, Shishkina (Phys. Rev. Fluids, vol 6, 2021, 090502) derived a length scale $\ell =H/(1+1.49\varGamma ^{-2})^{1/3}$. Our numerical study shows $Ra_{\ell }$, i.e. $Ra$ based on $\ell$, serves as a proper control parameter for heat transport above the onset with $Nu-1=0.018(1+0.34/\varGamma ^2)(Ra/Ra_{c,\varGamma }-1)$. Here $Ra_{c,\varGamma }$ represents the $\varGamma$-dependent critical $Ra$ for the onset of convection and $Nu$ is the Nusselt number. In the turbulent state, for a general scaling law of $Nu-1\sim Ra^\alpha$, we propose a length scale $\ell = H/(1+1.49\varGamma ^{-2})^{1/[3(1-\alpha )]}$. In the case of turbulent liquid metal convection with $\alpha =1/4$, our measurement shows that the heat transport will become weakly dependent on $\varGamma$ with $Ra_{\ell }\equiv Ra/(1+1.49\varGamma ^{-2})^{4/3} \ge 7\times 10^5$. Finally, once the flow becomes time-dependent, the growth rate of $Nu$ with $Ra$ declines compared with the linear growth rate in the convection state. A hysteresis is observed in a $\varGamma =1/3$ cell when the flow becomes time-dependent. Measurements of the large-scale circulation suggest the hysteresis is caused by the system switching from a single-roll-mode to a double-roll-mode in an oscillation state.

In the double-cone ignition scheme of inertial confinement fusion, the head-on collision of two compressed fuel jets from the cone-tips forms an isochoric plasma, which is then heated suddenly by a MeV relativistic electron beam produced by ultra-intense picosecond laser pulses. This fast-heating process was studied experimentally at the Shenguang II upgrade laser facility. By observing temporal-resolved X-ray emission and the spatial-resolved X-ray spectrum, the colliding process and heating process are carefully studied. The colliding plasma was imaged to have dimensions of approximately 86 μm in the implosion direction and approximately 120 μm in the heating direction. By comparing the simulated plasma X-ray spectrum with experimental data, the electron temperature of the heated plasma was found to rapidly increase to 600 ± 50 eV, almost doubling the temperature achieved before the heating laser incidence.

We report a home-built velocity-gradient-tensor-resolved particle image velocimetry (VGTR-PIV) system which spatio-temporally resolves all components of the velocity gradient tensor. This technique is applied to the paradigmatic turbulent Rayleigh–Bénard convection system in a cylindrical cell at three representative positions, i.e. centre, side and bottom regions. The VGTR-PIV system allows us to directly measure, for the first time, the spatio-temporally resolved energy dissipation rate and enstrophy in turbulent thermal convection. In the experiment, the Rayleigh number $Ra$ varied in the range $2 \times 10^8 \leqslant Ra \leqslant 8 \times 10^9$ and the Prandtl number $Pr$ was fixed at $Pr = 4.34$. Compared with the fully resolved energy dissipation rate $\varepsilon$, the pseudo-dissipation provides the best estimate within $3\,\%$, the planar (two-dimensional) surrogate has a larger relative error and the one-dimensional surrogate leads to the largest error. The power-law scalings of the time-averaged energy dissipation rate with the Rayleigh number follow $\langle \varepsilon _c \rangle _t / (\nu ^3 H^{-4}) = 9.86 \times 10^{-6} Ra^{1.54 \pm 0.02}$, $\langle \varepsilon _s \rangle _t / (\nu ^3 H^{-4}) = 9.26 \times 10^{-3} Ra^{1.25 \pm 0.02}$ and $\langle \varepsilon _b \rangle _t / (\nu ^3 H^{-4}) = 2.70 \times 10^{-2} Ra^{1.23 \pm 0.02}$ in the centre, side and bottom regions, respectively where $\nu$ is dynamic viscosity and $H$ is cell height. These scaling relations, along with our earlier measured time-averaged energy dissipation rate at the bottom wall surface $\langle \varepsilon _w \rangle _t / (\nu ^3 H^{-4}) = 9.65 \times 10^{-2} Ra^{1.25 \pm 0.02}$ (J. Fluid Mech., vol. 947, 2022, A15), provide important constraints against which theoretical models may be tested. For the centre and side locations in the convection cell, the probability density functions (p.d.f.s) of the energy dissipation rate and enstrophy both follow a stretched exponential distribution. For the bottom region, the p.d.f.s of dissipation and enstrophy exhibit a stretched exponential distribution outside the viscous boundary layer and an exponential distribution inside the viscous boundary layer. It is also found that extreme events with high dissipation are the most intermittent in the side region, whereas the bottom region is less intermittent than the cell centre.

A laser stripe sensor has two kinds of calibration methods. One is based on the homography model between the laser stripe plane and the image plane, which is called the one-step calibration method. The other is based on the simple triangular method, which is named as the two-step calibration method. However, the geometrical meaning of each element in the one-step calibration method is not clear as that in the two-step calibration method. A novel mathematical derivation is presented to reveal the geometrical meaning of each parameter in the one-step calibration method, and then the comparative study of the one-step calibration method and the two-step calibration method is completed and the intrinsic relationship is derived. What is more, a one-step calibration method is proposed with 7 independent parameters rather than 11 independent parameters. Experiments are conducted to verify the accuracy and robust of the proposed calibration method.

Lipase is an industrial enzyme, the catalytic efficiency of which is restricted by various environmental factors. To improve this efficiency, immobilization technology has been utilized in the past to improve the stability of lipase in harsh conditions. Immobilization technology can be divided into physical methods and chemical methods. Some unsolved problems remain in current immobilization technology. The interaction between enzyme and immobilization support is weak and reversible during physical adsorption, resulting in poor stability of the immobilized enzyme and the contamination of substrate solution by leached enzymes. In chemical methods, enzyme-active sites might be inactivated due to the chemical reactions between enzyme molecules and support, resulting in a decrease in the enzymes’ catalytic activity (Liu et al., 2018a). The objective of the current study was to construct a nanostructured lipase via Mg-amino-clay as a carrier and improve the catalytic activity and stability of lipase by immobilization. Lipase produced by Aspergillus oryzae was immobilized on aminopropyl functionalized magnesium phyllosilicate (a 2:1 trioctahedral talc-like silicate Mg-amino-clay) via a 1-(3-Dimethylaminopropyl)-3-ethyl-carbodiimide hydrochloride (EDC) coupling agent. The physical and chemical properties of the Mg-amino-clay and Mg-amino-clay-based nanostructured biocatalyst (Mg-clay-lipase) were characterized by X-ray diffraction, Fourier-transform infrared spectroscopy, and scanning electron microscopy. Optimal immobilization conditions were determined by taking into account the following variables: amount of initial lipase, EDC concentration, and reaction time. The results revealed that the optimum temperature, pH, and thermal stability of Mg-clay-lipase were greater than equivalent values for free lipase under optimal conditions (described below – Process for Immobilization of Lipase on Mg-amino-clay). The Michaelis-Menten constant (Km) values were 5.25 mM and 7.42 mM while the maximum reaction rates (vmax) were 30.58 mM/(L·min) and 55.87 mM/(L·min) for free lipase and Mg-clay-lipase, respectively. The present study provided a new nanostructured biocatalyst and demonstrated that the enzyme activity and stability of Mg-clay-lipase were superior to those of free lipase due to the mechanism of 'interface activation'.

The clay mineralogy of the Zhada sediments was investigated, using X-ray diffraction and scanning electron microscopy, to obtain a better understanding of climatic change and uplift of the Himalayas in the Zhada region of Tibet. The sediments of Zhada basin in the late Miocene to Pliocene consist of lacustrine and fluvial deposits >800 m thick and can be subdivided into five clay assemblage zones based on their clay-mineral composition. The upward zonation is as follows: (1) smectite-kaolinite; (2) illite-chlorite; (3) chlorite-illite-kaolinite; (4) illite-chlorite; and (5) smectite, illite, and kaolinite. The ratio of chlorite + illite to kaolinite + smectite (Ch+I/K+S) and the Kübler index indicate a warm and humid climate from 9.5 to 8.4 Ma, a cold and dry climate from 8.4 to 7.2 Ma, a warm and seasonal arid climate from 7.2 to 4.5 Ma, a cool and humid climate from 4.5 to 3.6 Ma, and a warm and seasonally humid climate from 3.6 to 3.0 Ma. Intense fluctuations in the Kübler index and in the quantities of evaporite minerals dolomite, aragonite, and gypsum, during the period 7.2–4.5 Ma suggest strong climatic fluctuations between humid and seasonally humid conditions in the Zhada basin. Rapid uplift around the Zhada basin occurred at 8.4 and 3.6 Ma, with sharp subsidence at 7.2 and 4.5 Ma. Evolution of the climate at Zhada showed a different model from that of global climate change, and tectonics-led climate change was the major contributor to climate evolution in the area.

In order to establish a compact all-optical Thomson scattering source, experimental studies were conducted on the 45 TW Ti: sapphire laser facility. By including a steel wafer, mixed gas, and plasma mirror into a double-exit jet, several mechanisms, such as shock-assisted ionization injection, ionization injection, and driving laser reflection, were integrated into one source. So, the source of complexity was remarkably reduced. Electron bunches with central energy fluctuating from 90 to 160 MeV can be produced. Plasma mirrors were used to reflect the driving laser. The scattering of the reflected laser on the electron bunches led to the generation of X-ray photons. Through comparing the X-ray spots under different experimental conditions, it is confirmed that the X-ray photons are generated by Thomson scattering. For further application, the energy spectra and source size of the Thomson scattering source were measured. The unfolded spectrum contains a large amount of low-energy photons besides a peak near 67 keV. Through importing the electron energy spectrum into the Monte Carlo simulation code, the different contributions of the photons with small and large emitting angles can be used to explain the origin of the unfolded spectrum. The maximum photon energy extended to about 500 keV. The total photon production was 107/pulse. The FWHM source size was about 12 μm.