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Pressure fluctuations play an essential role in the transport of turbulent kinetic energy and vibrational loading. This study focuses on examining the effect of wall cooling on pressure fluctuations in compressible turbulent boundary layers by high-fidelity direct numerical simulations. Pressure fluctuations result from the vorticity mode and the acoustic mode that are both closely dependent on compressibility. To demonstrate the effects of wall cooling at various compressibility intensities, three free-stream Mach numbers are investigated, i.e. $M_\infty =0.5$, 2.0 and 8.0, with real gas effects being absent for $M_\infty =8.0$ due to a low enthalpy inflow. Overall, opposite effects of wall cooling on pressure fluctuations are found between the subsonic/supersonic cases and the hypersonic case. Specifically, the pressure fluctuations normalized by wall shear stress $p^\prime _{rms}/\tau _w$ are suppressed in the subsonic and supersonic cases, while enhanced in the hypersonic case near the wall. Importantly, travelling-wave-like alternating positive and negative structures (APNS), which greatly contribute to pressure fluctuations, are identified within the viscous sublayer and buffer layer in the hypersonic cases. Furthermore, generating mechanisms of pressure fluctuations are explored by extending the decomposition based on the fluctuating pressure equation to compressible turbulent boundary layers. Pressure fluctuations are decomposed into five components, in which rapid pressure, slow pressure and compressible pressure are dominant. The suppression of pressure fluctuations in the subsonic and supersonic cases is due to both rapid pressure and slow pressure being suppressed by wall cooling. In contrast, wall cooling strengthens compressible pressure for all Mach numbers, especially in the hypersonic case, resulting in increased wall pressure fluctuations. Compressible pressure plays a leading role in the hypersonic case, mainly due to the APNS. Essentially, the main effects of wall cooling can be interpreted by the suppression of the vorticity mode and the enhancement of the acoustic mode.
Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a severe and life-threatening complication, characterised by multi-organ failure and high short-term mortality. However, there is limited information on the impact of various comorbidities on HBV-ACLF in a large population. This study aimed to investigate the relationship between comorbidities, complications and mortality. In this retrospective observational study, we identified 2166 cases of HBV-ACLF hospitalised from January 2010 to March 2018. Demographic data from the patients, medical history, treatment, laboratory indices, comorbidities and complications were collected. The mortality rate in our study group was 47.37%. Type 2 diabetes mellitus was the most common comorbidity, followed by alcoholic liver disease. Spontaneous bacterial peritonitis, pneumonia and hepatic encephalopathy (HE) were common in these patients. Diabetes mellitus and hyperthyroidism are risk factors for death within 90 days, together with gastrointestinal bleeding and HE at admission, HE and hepatorenal syndrome during hospitalisation. Knowledge of risk factors can help identify HBV-ACLF patients with a poor prognosis for HBV-ACLF with comorbidities and complications.
We report a generation of energetic protons by the interaction of a high-energy electron driving beam with an underdense plasma slab. After an interaction period of approximately 4000 fs, a proton beam with maximum energy greater than 250 MeV can be achieved by applying a driving beam with energy 1.0 GeV to a 200 $\mathrm {\mu }$m plasma slab. Our two-dimensional particle-in-cell simulations also show that the proton acceleration process can be divided into two stages. In the first stage, a strong positive longitudinal electric field appears near the rear boundary of the plasma slab after the driving beam has passed through it. This acceleration process is similar to the target normal sheath acceleration scheme by the interaction between intense pulsed laser with overdense plasma targets. In the second stage, the accelerated protons experience a long-range acceleration process with a two-stream instability between the high-energy driving beam and the proton beam. Further analyses show that this accelerated proton beam is equipped with the property of good collimation and high energy. This scheme presents a new way for proton or ion acceleration on some special occasions.
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.
Robotic systems are usually controlled to repetitively perform specific actions for manufacturing tasks. The traditional control methods are domain-dependent and model-dependent with cost of much human efforts. They cannot meet the new requirements of generality and flexibility in many areas such as intelligent manufacturing and customized production. This paper develops a general model-free approach to enable robots to perform multi-step object sorting tasks through deep reinforcement learning. Taking projected heightmap images from different time steps as input without extra high-level image analysis and understanding, critic models are designed to produce a pixel-wise Q value map for each type of action. It is a new trial to apply pixel-wise Q value-based critic networks to solve multi-step sorting tasks that involve many types of actions and complex action constraints. The experimental validations on simulated and realistic object sorting tasks demonstrate the effectiveness of the proposed approach. Qualitative results (videos), code for simulated and realistic experiments, and pre-trained models are available at https://github.com/JiatongBao/DRLSorting
OBJECTIVES/GOALS: Diffusion basis spectrum imaging (DBSI) allows for detailed evaluation of white matter microstructural changes present in cervical spondylotic myelopathy (CSM). Our goal is to utilize multidimensional clinical and quantitative imaging data to characterize disease severity and predict long-term outcomes in CSM patients undergoing surgery. METHODS/STUDY POPULATION: A single-center prospective cohort study enrolled fifty CSM patients who underwent surgical decompression and twenty healthy controls from 2018-2021. All patients underwent diffusion tensor imaging (DTI), DBSI, and complete clinical evaluations at baseline and 2-years follow-up. Primary outcome measures were the modified Japanese Orthopedic Association score (mild [mJOA 15-17], moderate [mJOA 12-14], severe [mJOA 0-11]) and SF-36 Physical and Mental Component Summaries (PCS and MCS). At 2-years follow-up, improvement was assessed via established MCID thresholds. A supervised machine learning classification model was used to predict treatment outcomes. The highest-performing algorithm was a linear support vector machine. Leave-one-out cross-validation was utilized to test model performance. RESULTS/ANTICIPATED RESULTS: A total of 70 patients – 20 controls, 25 mild, and 25 moderate/severe CSM patients – were enrolled. Baseline clinical and DTI/DBSI measures were significantly different between groups. DBSI Axial and Radial Diffusivity were significantly correlated with baseline mJOA and mJOA recovery, respectively (r=-0.33, p<0.01; r=-0.36, p=0.02). When predicting baseline disease severity (mJOA classification), DTI metrics alone performed with 38.7% accuracy (AUC: 72.2), compared to 95.2% accuracy (AUC: 98.9) with DBSI metrics alone. When predicting improvement after surgery (change in mJOA), clinical variables alone performed with 33.3% accuracy (AUC: 0.40). When combining DTI or DBSI parameters with key clinical covariates, model accuracy improved to 66.7% (AUC: 0.65) and 88.1% (AUC: 0.95) accuracy, respectively. DISCUSSION/SIGNIFICANCE: DBSI metrics correlate with baseline disease severity and outcome measures at 2-years follow-up. Our results suggest that DBSI may serve as a valid non-invasive imaging biomarker for CSM disease severity and potential for postoperative improvement.
One major challenge for a continuum model to describe nanoscale confined fluid flows is the lack of a boundary condition that can capture molecular-scale slip behaviours. In this work, we propose a molecular-kinetic boundary condition to model the fluid–surface and fluid–fluid molecular interactions using the Lennard–Jones type potentials, and add a mean-field force to the momentum equation. This new boundary condition is then applied to investigate the nanoscale Couette and Poiseuille flows using the generalised hydrodynamic model developed by Guo et al. (Phys. Fluids, volume 18, issue 6, 2006a, 067107). The accuracy of our model is validated by molecular dynamics simulations and other models for a broad range of parameters including density, shear rate, wettability and channel width. Our simulation results reveal some unexpected and unintuitive slip behaviours at the nanoscale, including the epitaxial layering structure of fluids and the slip length minimum. The slip length minimum, which is analogous to the Knudsen minimum, can be explained by competing fluid–solid and fluid–fluid molecular interactions as density varies. A new scaling law is proposed for the slip length to account for not only the competing effect between the fluid–solid and fluid–fluid molecular interactions, but also many other physical mechanisms including the competition between the fluid internal potential energy and kinetic energy, and the confinement effect. While the slip length is nearly constant at the low shear rates, it increases rapidly at the high shear rates due to friction reduction. These molecular-scale slip behaviours are caused by energy corrugations at the fluid–solid interface where strong fluid–solid and fluid–fluid molecular interactions interplay.
For the safety problems caused by the limited landing space of the deck during the arresting process of the carrier-based aircraft, a dynamic model of the carrier-based aircraft’s landing and arresting is built. Based on the batch simulation method, the lateral dynamics safety envelope of the aircraft during the arresting was defined, and the dynamic response of the key points in the envelope during the arresting process was investigated. Subsequently, the influence of engine thrust and aircraft quality on the arresting safety envelope was studied based on reasonable safety evaluation indicators, and the safety status envelope of the deck arresting was given. Then, the particular Hamilton-Jacobi partial differential equation is used to obtain the lateral dynamics safety envelope of the carrier-based aircraft in the process of landing and arresting by backward inversion. Results indicate that engine thrust and landing quality have little effect on the yaw angle in the arresting safety boundary during the arresting. Additionally, with the engine thrust and landing quality increase, the maximum safe off-centre distance gradually decreases, and the safety boundary decreases accordingly. During the phase of landing glide, the engine thrust and quality have little effect on the maximum safe eccentric distance. When the engine thrust is increased by 40%, the maximum safe yaw angle is reduced from 0.3°, and the safety boundary is reduced by 4.2%. When the aircraftquality increases by 40%, the maximum safe yaw angle is reduced by 0.4°, and the safety boundary is reduced by 2.8%. The findings of this paper can provide framework for the research on theaircraft-to-carrier dynamic matching characteristics of the carrier-based system, and is of great significance to the research on improving the safety of the carrier-based aircraft landing arresting.
Evidence of couples’ BMI and its influence on birth weight is limited and contradictory. Therefore, this study aims to assess the association between couple’s preconception BMI and the risk of small for gestational age (SGA)/large for gestational age (LGA) infant, among over 4·7 million couples in a retrospective cohort study based on the National Free Pre-pregnancy Checkups Project (NFPCP) between December 1, 2013 and November 30, 2016 in China. Among the live births, 256,718 (5·44%) SGA events and 506,495 (10·73%) LGA events were documented, respectively. After adjusting for confounders, underweight men had significantly higher risk [OR 1·17 95%CI (1·15-1·19)] of SGA infants compared with men with normal BMI, while a significant and increased risk of LGA infants was obtained for overweight and obese men [OR 1·08 (95% CI: 1·06-1·09); OR 1·19 (95%CI 1·17-1·20)] respectively. The restricted cubic spline (RCS) result revealed a non-linearly decreasing dose-response relationship of paternal BMI (less than 22·64) with SGA. Meanwhile, a non-linearly increasing dose-response relationship of paternal BMI (more than 22·92) with LGA infants was observed. Moreover, similar results about the association between maternal preconception BMI and SGA/LGA infants were obtained. Abnormal preconception BMIs in either women or men were associated with increased risk of SGA/LGA infants, respectively. Overall, couple’s abnormal weight before pregnancy may be an important preventable risk factor for SGA/LGA infants.
Subthreshold depression could be a significant precursor to and a risk factor for major depression. However, reliable estimates of the prevalence and its contribution to developing major depression under different terminologies depicting subthreshold depression have to be established.
Methods
By searching PubMed and Web of Science using predefined inclusion criteria, we included 1 129 969 individuals from 113 studies conducted. The prevalence estimates were calculated using the random effect model. The incidence risk ratio (IRR) was estimated by measuring the ratio of individuals with subthreshold depression who developed major depression compared to that of non-depressed individuals from 19 studies (88, 882 individuals).
Results
No significant difference in the prevalence among the different terminologies depicting subthreshold depression (Q = 1.96, p = 0.5801) was found. By pooling the prevalence estimates of subthreshold depression in 113 studies, we obtained a summary prevalence of 11.02% [95% confidence interval (CI) 9.78–12.33%]. The youth group had the highest prevalence (14.17%, 95% CI 8.82–20.55%), followed by the elderly group (12.95%, 95% CI 11.41-14.58%) and the adult group (8.92%, 95% CI 7.51–10.45%). Further analysis of 19 studies' incidence rates showed individuals with subthreshold depression had an increased risk of developing major depression (IRR = 2.95, 95% CI 2.33–3.73), and the term minor depression showed the highest IRR compared with other terms (IRR = 3.97, 95% CI 3.17–4.96).
Conclusions
Depression could be a spectrum disorder, with subthreshold depression being a significant precursor to and a risk factor for major depression. Proactive management of subthreshold depression could be effective for managing the increasing prevalence of major depression.
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.
Long-term care given to disabled older adults takes many forms, with each impacting life satisfaction through different ways. Drawing data from the 2011–2018 China Health and Retirement Longitudinal Survey, this article explores the effects of various care types on life satisfaction, with a particular focus on disabled older persons. Estimates derived from a fixed effects model with propensity score matching show that compared with formal care, informal care has significant positive effects on life satisfaction for disabled older adults. In addition, informal care has its greatest positive effect on life satisfaction on those who are mildly disabled, men and rural residents compared to their counterparts, while formal care addresses the needs of individuals with severe disability. We find that the main channels of effect occur through reduced loneliness and unhappiness, increased participation in social activities and improved physical health. This work contributes to the existing literature by demonstrating how various care types affect life satisfaction in China where filial piety, the central pillar of the Confucian ethics, is one of the common shared values among residents. These findings highlight the benefits derived from policies that promote and support the provision of informal care for older individuals. Moreover, there is a pressing need to buttress the formal care provision as a supplement to support severely disabled older adults in China.
This research communication aims to characterize the prevalence, molecular characterization and antimicrobial resistance profiling of Streptococcus agalactiae isolated from clinical mastitis in China. A total of 140 Strep. agalactiae isolates were identified from 12 out of 201 farms in 6 provinces, overall herd prevalence was 18.6% and the MLST analysis showed clonal complexes (CC) 103 and CC 67 were present in these herds with CC 103 predominant, accounting for 97.9%. Isolates were mostly sensitive to the tested antimicrobials: penicillin, ceftiofur, amoxi/clav, cefquinome, and vancomycin (100%), followed by cefalexin (97.9%), oxacillin (96.4%), enrofloxacin (95.7%), erythromycin (89.3%), and clindamycin (88.6%). Only 19.3 and 0.7% of isolates were sensitive to tetracycline and daptomycin, respectively, and sequence type (ST) 103 was most resistant to antimicrobials. In conclusion, CC 103 was the predominant subgroup of bovine mastitis Strep. agalactiae in China, and most antimicrobials apart from tetracycline and daptomycin were effective.
In order to assist patients with lower limb disabilities in normal walking, a new trajectory learning scheme of limb exoskeleton robot based on dynamic movement primitives (DMP) combined with reinforcement learning (RL) was proposed. The developed exoskeleton robot has six degrees of freedom (DOFs). The hip and knee of each artificial leg can provide two electric-powered DOFs for flexion/extension. And two passive-installed DOFs of the ankle were used to achieve the motion of inversion/eversion and plantarflexion/dorsiflexion. The five-point segmented gait planning strategy is proposed to generate gait trajectories. The gait Zero Moment Point stability margin is used as a parameter to construct a stability criteria to ensure the stability of human-exoskeleton system. Based on the segmented gait trajectory planning formation strategy, the multiple-DMP sequences were proposed to model the generation trajectories. Meanwhile, in order to eliminate the effect of uncertainties in joint space, the RL was adopted to learn the trajectories. The experiment demonstrated that the proposed scheme can effectively remove interferences and uncertainties.
Efficient and high-precision identification of dynamic parameters is the basis of model-based robot control. Firstly, this paper designed the structure and control system of the developed lower extremity exoskeleton robot. The dynamics modeling of the exoskeleton robot is performed. The minimum parameter set of the identified parameters is determined. The dynamic model is linearized based on the parallel axis theory. Based on the beetle antennae search algorithm (BAS) and particle swarm optimization (PSO), the beetle swarm optimization algorithm (BSO) was designed and applied to the identification of dynamic parameters. The update rule of each particle originates from BAS, and there is an individual’s judgment on the environment space in each iteration. This method does not rely on the historical best solution in the PSO and the current global optimal solution of the individual particle, thereby reducing the number of iterations and improving the search speed and accuracy. Four groups of test functions with different characteristics were used to verify the performance of the proposed algorithm. Experimental results show that the BSO algorithm has a good balance between exploration and exploitation capabilities to promote the beetle to move to the global optimum. Besides, the test was carried out on the exoskeleton dynamics model. This method can obtain independent dynamic parameters and achieve ideal identification accuracy. The prediction result of torque based on the identification method is in good agreement with the ideal torque of the robot control.
Noncompressible torso hemorrhage (NCTH) is a major challenge in prehospital bleeding control and is associated with high mortality. This study was performed to estimate medical knowledge and the perceived barriers to information acquisition among health-care workers (HCWs) regarding NCTH in China.
Methods:
A self-administered and validated questionnaire was distributed among 11 WeChat groups consisting of HCWs engaged in trauma, emergency, and disaster rescue.
Results:
A total of 575 HCWs participated in this study. In the knowledge section, the majority (87.1%) denied that successful hemostasis could be obtained by external compression. Regarding attitudes, the vast majority of HCWs exhibited positive attitudes toward the important role of NCTH in reducing prehospital preventable death (90.4%) and enthusiasm for continuous learning (99.7%). For practice, fewer than half of HCWs (45.7%) had heard of NCTH beforehand, only a minority (14.3%) confirmed they had attended relevant continuing education, and 16.3% HCWs had no access to updated medical information. The most predominant barrier to information acquisition was the lack of continuing training (79.8%).
Conclusions:
Knowledge and practice deficiencies do exist among HCWs. Obstacles to update medical information warrant further attention. Furthermore, education program redesign is also needed.