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The aeroacoustic characteristics of flying vehicles with pitch-fixed rotors differ from traditional helicopters with pitch-controlled rotor blades. Accurate predictions of rotor noise are still challenging because many uncertainty factors and unsteadinesses exist. This work investigates the aeroacoustic effects of rotational speed deviation, rotation speed fluctuation, blade vibration and blade geometric asymmetry. The analysis is based on the efficient computation of rotor noise under different working conditions. The mean aerodynamic variables are computed using the blade element moment theory, while small-amplitude fluctuations are introduced to account for the unsteadiness and uncertainty factors. It is shown that periodic rotation speed fluctuations and blade vibrations can produce significant extra tones. By contrast, if the fluctuations and vibrations are random, the noise level in a wide frequency range is increased. The intriguing result reminds us of the need to revisit the rotor broadband noise sources commonly attributed to turbulent flows. The influences are observer angle dependent, and the extra noise production is more significant in the upstream and downstream directions. The asymmetric blade geometry can cause extra tonal noise at the harmonics of the blade shaft frequency. The noise features of dual rotors are also investigated. Usually, the noise is sensitive to the initial phase difference and rotation directions due to the interference effect. However, the noise features are vastly altered if there are slight differences in the rotation speeds. Although the influences of some factors on rotor noise were already known, the present study provides a more comprehensive analysis of the problem. The results also highlight the need to consider these practical factors for accurate noise prediction of multi-rotor flying vehicles.
Understanding the statistics of bedload particle motions is of great importance. To model the hop events which are defined as trajectories of particles moving successively from the start to the end of their motions, recently, Wu et al. (Water Resour. Res., vol. 56, 2020, p. e2019WR025116) have successfully performed individual-based simulations according to the Fokker–Planck equation for particle velocities. However, analytical solutions are still not available due to (i) difficulties in treating the velocity-dependent diffusivity, and (ii) a knowledge gap in incorporating the termination of particle motions for the equation. To tackle the above-mentioned challenges, we first specify a Robin boundary condition representing the deposition of particles. Second, for analytical solutions of hop statistics, a variable transformation is devised to deal with the velocity-dependent diffusivity. The original bedload transport problem is thus found to be governed by the classic equation for the solute transport in tube flows with a constant diffusivity after the transformation. Finally, through solving the spatial and temporal moments of the governing equation, we investigate the influence of the deposition rate on three key characteristics of particle hops. Importantly, we have related the deposition rate to the mean travel times and hop distances, enabling a direct determination of this physical parameter based on measured particle motion statistics. The analytical solutions are validated by experimental observations with different bedload particle diameters and transport conditions. Based on the limited experimental datasets, the deposition frequency is shown to decrease as the shear stress increases when the flow rate is not small.
In this work, theoretical modelling, quasi-three-dimensional (quasi-3D) simulations and micromodel experiments are conducted to study spontaneous imbibition with gravity in porous media micromodels. By establishing the force balance governing the spontaneous imbibition process, we develop a theoretical model for predicting the imbibition length against time in a rectangular capillary. The theoretical model is then extended to the prediction of a compact displacement process in a micromodel by using an equivalent width, which is derived by analogising the micromodel to a rectangular capillary. By simulating spontaneous imbibition in a rectangular capillary with various aspect ratios ($\varepsilon$), we show that the application condition of the quasi-3D method is $\varepsilon \leqslant 1/3$. Next, we simulate spontaneous imbibition in micromodels with various geometries and flow conditions. Fingering and compact displacement are identified for varying viscosity ratios and gravitational accelerations. At low (high) viscosity ratio of wetting to non-wetting fluids, an upward (downward) gravity can promote the stability of the wetting front, favouring the transition from fingering to compact displacement. In addition, we find that the depth-oriented interface curvature dominates the capillary effect during the imbibition, and such a mechanism is considered by introducing an equivalent contact angle into the theoretical model. With the help of equivalent width and contact angle, the theoretical model is shown to provide satisfactory prediction of the compact displacement process. Finally, a micromodel experiment is presented to further verify the developed theoretical model and the quasi-3D simulation.
Safety voice helps organizations to identify safety issues timely and is critical to the long-term growth of the organization. Safety voice has become a hot research topic in organizational safety, and different scales have been developed. However, the unique cultural context in China has led to the need to redevelop safety voice measurement tools. In this paper, we developed an initial scale of safety voice for employees in Chinese organizational contexts fusing in-depth interviews and mature scales. The initial scale based on two samples (n1 = 205, n2 = 420) was revised and validated using item analysis, exploratory factor analysis, confirmatory factor analysis, and reliability analysis to finalize the final scale. We finally found that the safety voice scale in Chinese organizational contexts contains two dimensions: promotive safety voice and prohibitive safety voice. The scale developed in this paper is a reliable tool to measure safety voice behavior of Chinese employees.
Surface reactions such as the adsorption and desorption at boundaries are very common for solute dispersion in many applications of chemistry, biology, hydraulics, etc. To study how reversible adsorption affects the transient dispersion, Zhang, Hesse & Wang (J. Fluid Mech., vol. 828, 2017, pp. 733–752) have investigated the temporal evolution of moments using the Laplace transform method. Owing to difficulties introduced by the adsorption–desorption boundary condition, great challenges arise from the inverse Laplace transform: dealing with the singularities by the residue theorem can tremendously increase complexities. This work provides a much simpler analytical method to derive solutions in a more compact form that is valid for the entire range of the reactive transport process. Such a progress demonstrates that the classic framework of separation of variables can be extended and applied to this more general adsorption–desorption condition, based on which higher-order statistics including skewness and kurtosis can be explicitly explored in practice. Also extended is Gill's generalised dispersion model for solute concentration distributions, which can now address the entire transient dispersion characteristics, instead of just applied for the long-time asymptotic reactive process as done previously. Regarding the most classic Taylor dispersion problem, we investigate the influence of the reversible adsorption–desorption on the solute cloud in a tube flow. Not only the transient dispersion characteristics of transverse-average concentration distribution but also those of the bulk, surface and total-average distributions are discussed. We further investigate the influence of initial conditions on the non-uniformity of the transient dispersion over the cross-section.
Based on erosion coupon tests, a sand erosion model for 17-4PH steel was developed. The developed erosion model was validated against the results of compressor erosion tests from a generic rig and from other researchers. A high-fidelity computational fluid dynamics (CFD) model of the test rig was built, a user-defined function was developed to implement the erosion model into the ANSYS CFD software, and the turbulent, two-phase flow-field in multiple reference frames was solved. The simulation results are consistent with the test results from the compressor rig and with experimental findings from other researchers. Specifically, the sand erosion blunts the leading edge, sharpens the trailing edge and increases pressure-surface roughness. The comparisons between the experimental observations and numerical results as well as a quantitative comparison with three other sand erosion models indicate that the developed sand erosion model is adequate for erosion prediction of engine components made of 17-4PH steel.
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).
The rapid and accurate taxonomic identification of fossils is of great significance in paleontology, biostratigraphy, and other fields. However, taxonomic identification is often labor-intensive and tedious, and the requisition of extensive prior knowledge about a taxonomic group also requires long-term training. Moreover, identification results are often inconsistent across researchers and communities. Accordingly, in this study, we used deep learning to support taxonomic identification. We used web crawlers to collect the Fossil Image Dataset (FID) via the Internet, obtaining 415,339 images belonging to 50 fossil clades. Then we trained three powerful convolutional neural networks on a high-performance workstation. The Inception-ResNet-v2 architecture achieved an average accuracy of 0.90 in the test dataset when transfer learning was applied. The clades of microfossils and vertebrate fossils exhibited the highest identification accuracies of 0.95 and 0.90, respectively. In contrast, clades of sponges, bryozoans, and trace fossils with various morphologies or with few samples in the dataset exhibited a performance below 0.80. Visual explanation methods further highlighted the discrepancies among different fossil clades and suggested similarities between the identifications made by machine classifiers and taxonomists. Collecting large paleontological datasets from various sources, such as the literature, digitization of dark data, citizen-science data, and public data from the Internet may further enhance deep learning methods and their adoption. Such developments will also possibly lead to image-based systematic taxonomy to be replaced by machine-aided classification in the future. Pioneering studies can include microfossils and some invertebrate fossils. To contribute to this development, we deployed our model on a server for public access at www.ai-fossil.com.
According to a WHO report, the number of patients with coronavirus disease 2019 (COVID-19) has reached 456,797,217 worldwide as of 15 March, 2022. In Wuhan, China, large teams of health-care personnel were dispatched to respond to the COVID-19 emergency. This study aimed to determine the sociodemographic and psychological predictors of resilience among frontline nurses fighting the current pandemic.
Methods:
A total of 143 nurses were recruited from February 15 to February 20, 2020, to participate in this study. The 10-item Connor-Davidson Resilience Scale and the 21-item Depression Anxiety Stress Scale were used to estimate the participants’ resilience and mental wellbeing.
Results:
Results showed that the nurses displayed a moderate resilience level. Their median depression, anxiety, and stress scores were 1, 2, and 3, respectively, which were negatively correlated with resilience. Female gender, being dispatched to Wuhan, and depression levels were the significant predictors of resilience.
Conclusions:
The results suggest that particular attention should be given to nurses who were dispatched to Wuhan and who exhibited depression symptoms, and appropriate measures should be taken to boost their resilience.
This study is performed to figure out how the presence of diabetes affects the infection, progression and prognosis of 2019 novel coronavirus disease (COVID-19), and the effective therapy that can treat the diabetes-complicated patients with COVID-19. A multicentre study was performed in four hospitals. COVID-19 patients with diabetes mellitus (DM) or hyperglycaemia were compared with those without these conditions and matched by propensity score matching for their clinical progress and outcome. Totally, 2444 confirmed COVID-19 patients were recruited, from whom 336 had DM. Compared to 1344 non-DM patients with age and sex matched, DM-COVID-19 patients had significantly higher rates of intensive care unit entrance (12.43% vs. 6.58%, P = 0.014), kidney failure (9.20% vs. 4.05%, P = 0.027) and mortality (25.00% vs. 18.15%, P < 0.001). Age and sex-stratified comparison revealed increased susceptibility to COVID-19 only from females with DM. For either non-DM or DM group, hyperglycaemia was associated with adverse outcomes, featured by higher rates of severe pneumonia and mortality, in comparison with non-hyperglycaemia. This was accompanied by significantly altered laboratory indicators including lymphocyte and neutrophil percentage, C-reactive protein and urea nitrogen level, all with correlation coefficients >0.35. Both diabetes and hyperglycaemia were independently associated with adverse prognosis of COVID-19, with hazard ratios of 10.41 and 3.58, respectively.
Listeriosis is a rare but serious foodborne disease caused by Listeria monocytogenes. This matched case–control study (1:1 ratio) aimed to identify the risk factors associated with food consumption and food-handling habits for the occurrence of sporadic listeriosis in Beijing, China. Cases were defined as patients from whom Listeria was isolated, in addition to the presence of symptoms, including fever, bacteraemia, sepsis and other clinical manifestations corresponding to listeriosis, which were reported via the Beijing Foodborne Disease Surveillance System. Basic patient information and possible risk factors associated with food consumption and food-handling habits were collected through face-to-face interviews. One hundred and six cases were enrolled from 1 January 2018 to 31 December 2020, including 52 perinatal cases and 54 non-perinatal cases. In the non-perinatal group, the consumption of Chinese cold dishes increased the risk of infection by 3.43-fold (95% confidence interval 1.27–9.25, χ2 = 5.92, P = 0.02). In the perinatal group, the risk of infection reduced by 95.2% when raw and cooked foods were well-separated (χ2 = 5.11, P = 0.02). These findings provide important scientific evidence for preventing infection by L. monocytogenes and improving the dissemination of advice regarding food safety for vulnerable populations.
Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices.
Methods
Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naïve (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations.
Results
VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network.
Conclusions
Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.
Prolonged parturition duration has been widely demonstrated to be a risk factor for incidence of stillbirth. This study evaluated the supply of dietary fibre on the parturition duration, gut microbiota and metabolome using sows as a model. A total of 40 Yorkshire sows were randomly given diet containing normal level of dietary fibre (NDF, 17·5 % dietary fibre) or high level of dietary fibre (HDF, 33·5 % dietary fibre). Faecal microbiota profiled with 16S rRNA amplicon sequencing, SCFA and metabolome in the faeces and plasma around parturition were compared between the dietary groups. Correlation analysis was conducted to further explore the potential associations between specific bacterial taxa and metabolites. Results showed that HDF diet significantly improved the parturition process as presented by the shorter parturition duration. HDF diet increased the abundance of the phyla Bacteroidetes and Synergistetes and multiple genera. Except for butyrate, SCFA levels in the faeces and plasma of sows at parturition were elevated in HDF group. The abundances of fifteen and twelve metabolites in the faeces and plasma, respectively, markedly differ between HDF and NDF sows. These metabolites are involved in energy metabolism and bacterial metabolism. Correlation analysis also showed associations between specific bacteria taxa and metabolites. Collectively, our study indicates that the improvement of parturition duration by high fibre intake in late gestation is associated with gut microbiota, production of SCFA and other metabolites, potentially serving for energy metabolism.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
Aims
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
Method
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
Results
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
Conclusions
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
The aim of this study was to evaluate the association between prenatal and neonatal period exposures and the risk of childhood and adolescent nasopharyngeal carcinoma (NPC). From January 2009 to January 2016, a total of 46 patients with childhood and adolescent NPC (i.e., less than 18 years of age) who were treated at Sun Yat-sen University Cancer Center were screened as cases, and a total of 45 cancer-free patients who were treated at Sun Yat-sen University Zhongshan Ophthalmic Center were selected as controls. The association between maternal exposures during pregnancy and obstetric variables and the risk of childhood and adolescent NPC was evaluated using logistic regression analysis. Univariate analysis revealed that compared to children and adolescents without a family history of cancer, those with a family history of cancer had a significantly higher risk of childhood and adolescent NPC [odds ratios (OR) = 3.15, 95% confidence interval (CI) = 1.02–9.75, P = 0.046], and the maternal use of folic acid and/or multivitamins during pregnancy was associated with a reduced risk of childhood and adolescent NPC in the offspring (OR = 0.07, 95% CI = 0.02–0.25, P < 0.001). After multivariate analysis, only the maternal use of folic acid and/or multivitamins during pregnancy remained statistically significant. These findings suggest that maternal consumption of folic acid and/or multivitamins during pregnancy is associated with a decreased risk of childhood and adolescent NPC in the offspring.
As acute infectious pneumonia, the coronavirus disease-2019 (COVID-19) has created unique challenges for each nation and region. Both India and the United States (US) have experienced a second outbreak, resulting in a severe disease burden. The study aimed to develop optimal models to predict the daily new cases, in order to help to develop public health strategies. The autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models, ARIMA–GRNN hybrid model and exponential smoothing (ES) model were used to fit the daily new cases. The performances were evaluated by minimum mean absolute per cent error (MAPE). The predictive value with ARIMA (3, 1, 3) (1, 1, 1)14 model was closest to the actual value in India, while the ARIMA–GRNN presented a better performance in the US. According to the models, the number of daily new COVID-19 cases in India continued to decrease after 27 May 2021. In conclusion, the ARIMA model presented to be the best-fit model in forecasting daily COVID-19 new cases in India, and the ARIMA–GRNN hybrid model had the best prediction performance in the US. The appropriate model should be selected for different regions in predicting daily new cases. The results can shed light on understanding the trends of the outbreak and giving ideas of the epidemiological stage of these regions.
The aim of the present study was to compare the rate of preterm birth (PTB) and growth from birth to 18 years between twins conceived by in vitro fertilization (IVF) and twins conceived by spontaneous conception (SC) in mainland China. The retrospective cohort study included 1164 twins resulting from IVF and 25,654 twins conceived spontaneously, of which 494 from IVF and 6338 from SC were opposite-sex twins. PTB and low birth weight (LBW), and growth, including length/height and weight, were compared between the two groups at five stages: infancy (0 year), toddler period (1–2 years), preschool (3–5 years), primary or elementary school (6–11 years), and adolescence (10–18 years). Few statistically significant differences were found for LBW and growth between the two groups after adjusting for PTB and other confounders. Twins born by IVF faced an increased risk of PTB compared with those born by SC (adjusted odds ratio [aOR] 8.21, 95% confidence interval [CI] [3.19, 21.13], p < .001 in all twins and aOR 10.12, 95% CI [2.32, 44.04], p = .002 in opposite-sex twins). Twins born by IVF experienced a similar growth at five stages (0–18 years old) when compared with those born by SC. PTB risk, however, is significantly higher for twins conceived by IVF than those conceived by SC.
The present study evaluated effects of dietary supplementation with tryptophan (Trp) on muscle growth, protein synthesis and antioxidant capacity in hybrid catfish Pelteobagrus vachelli♀ × Leiocassis longirostris♂. Fish were fed six different diets containing 2·6 (control), 3·1, 3·7, 4·2, 4·7 and 5·6 g Trp/kg diet for 56 d, respectively. Results showed that dietary Trp significantly (1) improved muscle protein content, fibre density and frequency of fibre diameter; (2) up-regulated the mRNA levels of PCNA, myf5, MyoD1, MyoG, MRF4, IGF-I, IGF-II, IGF-IR, PIK3Ca, TOR, 4EBP1 and S6K1; (3) increased phosphorylation levels of AKT, TOR and S6K1; (4) decreased contents of MDA and PC, and increased activities of CAT, GST, GR, ASA and AHR; (5) up-regulated mRNA levels of CuZnSOD, CAT, GST, GPx, GCLC and Nrf2, and decreased Keap1 mRNA level; (6) increased nuclear Nrf2 protein level and the intranuclear antioxidant response element-binding ability, and reduced Keap1 protein level. These results indicated that dietary Trp improved muscle growth, protein synthesis as well as antioxidant capacity, which might be partly related to myogenic regulatory factors, IGF/PIK3Ca/AKT/TOR and Keap1/Nrf2 signalling pathways. Finally, based on the quadratic regression analysis of muscle protein and MDA contents, the optimal Trp requirements of hybrid catfish (21·82–39·64 g) were estimated to be 3·94 and 3·93 g Trp/kg diet (9·57 and 9·54 g/kg of dietary protein), respectively.
The safe closure of atrial septal defect with deficient posterior-inferior or inferior vena cava rim is a controversial issue. Few studies have been conducted on the closure of atrial septal defect with deficient posterior-inferior or inferior vena cava rim without fluoroscopy. This study evaluated the feasibility and safety of echocardiography-guided transcatheter closure of atrial septal defect with deficient posterior-inferior or inferior vena cava rim.
Methods:
The data of 136 patients who underwent transcatheter atrial septal defect closure without fluoroscopy from March 2017 to March 2020 were retrospectively analysed. The patients were classified into the deficient (n = 45) and sufficient (n = 91) posterior-inferior or inferior vena cava rim groups. Procedure and the follow-up results were compared between the two groups.
Results:
Atrial septal defect indexed diameter and the device indexed diameter in the deficient rim group were both larger than that in the sufficient rim group (22.12 versus 17.38 mm/m2, p < 0.001; 24.77 versus 21.21 mm/m2, p = 0.003, respectively). There was no significant difference in the success rate of occlusion between two groups (97.78% in the deficient rim group versus 98.90% in the sufficient rim group, p = 1.000). During follow-up, the incidence of severe adverse cardiac events was not statistically significant (p = 0.551).
Conclusions:
Atrial septal defect with deficient posterior-inferior or inferior vena cava rim can safely undergo transcatheter closure under echocardiography alone if precisely evaluated with transesophageal or transthoracic echocardiography and the size of the occluder is appropriate. The mid-term results after closure are similar to that for an atrial septal defect with sufficient rim.