Combined finite element and multi-body dynamics analysis of effects of hydraulic cylinder movement on ploughshare of horizontally reversible plough

Abstract: Hydraulic Cylinder (HC), one of the key components of Horizontally Reversible Plough (HRP), takes the responsibilities for the commuting soiltillage of HRP. The dynamic behaviors of HC surely affectthe tilling performances of HRP. Based on our previously related work, this paper further addresses the effects of HC movements during tillage on ploughshare, especially at share-point, of HRP. For HC, uniform motion was considered in this study. A combined finite element and multi-body dynamics analysis (MDA) was implemented to assess both tillage kinematics and kinetics of the ploughshare. These numerical predictions were primarily involved in five different HC movement velocities and two actual HRP tilling scenarios, respectively, where loading data due to the HC movements were obtained from an MDA and applied to load a finite element modal of the ploughshare. Our results show that the importance of performing MDA as a preliminary step FEA to obtain an insight into the actual stress and strain variations at the share-point. Our findings demonstrate that the different movements of HC have no adverse effects on the service life of the ploughshare though they result in the maximum stress and strain at the sharepoint during HRP tillage

Numerical investigation of scale effect of various injection diameters on interaction in cold kerosene-fueled supersonic flow

Abstract: The incident shock wave generally has a strong effect on the transversal injection field in cold kerosene-fueled supersonic flow, possibly due to its affecting the interaction between incoming flow and fuel through various operation conditions. This study is to address scale effect of various injection diameters on the interaction between incident shock wave and transversal cavity injection in a cold kerosene-fueled scramjet combustor. The injection diameters are separately specified as from 0.5 to 1.5mm in 0.5mm increments when other performance parameters, including the injection angle, velocity and pressure drop are all constant. A combined three dimensional Couple Level Set & Volume of Fluids (CLSVOF) approach with an improved K-H & R-T model is used to characterize penetration height, span expansion area, angle of shock wave and sauter mean diameter (SMD) distribution of the kerosene droplets with/without considering evaporation. Our results show that the injection orifice surely has a great scale effect on the transversal injection field in cold kerosene-fueled supersonic flows. Our findings show that the penetration depth, span angle and span expansion area of the transverse cavity jet are increased with the injection diameter, and that the kerosene droplets are more prone to breakup and atomization at the outlet of the combustor for the orifice diameter of 1.5mm. The calculation predictions are compared against the reported experimental measurements and literatures with good qualitative agreement. The simulation results obtained in this study can provide the evidences for better understanding the underlying mechanism of kerosene atomization in cold supersonic flow and scramjet design improvement

Effects of spray angle variation on mixing in a cold supersonic combustor with kerosene fuel

Abstract: Effective fuel injection and mixing is of particular importance for scramjet engines to be operated reliably because the fuel must be injected into high-speed crossflow and mixed with the supersonic air at an extremely short time-scale. This study numerically characterizes an injection jet under different spray angles in a cold kerosene-fueled supersonic flow and thus assesses the effects of the spray angle on the mixing between incident shock wave and transverse cavity injection. A detailed computational fluid dynamics model is developed in accordance with the real scramjet combustor. Next, the spray angles are designated as 45º, 90º, and 135º respectively with the other constant operational conditions (such as the injection diameter, velocity and pressure). Next, a combination of a three dimensional Couple Level Set & Volume of Fluids with an improved Kelvin-Helmholtz & Rayleigh-Taylor model is used to investigate the interaction between kerosene and supersonic air. The numerical predictions are focused on penetration depth, span expansion area, angle of shock wave and sauter mean diameter distribution of the kerosene droplets with or without evaporation. Finally, validation has been implemented by comparing the calculated to the measured in literature with good qualitative agreement. Results show that no matter whether the evaporation is considered, the penetration depth, span-wise angle and expansion area of the kerosene droplets are all increased with the spray angle, and most especially, that the size of the kerosene droplets is surely reduced with the spray angle increase. These calculations are beneficial to better understand the underlying atomization mechanism in the cold kerosene-fueled supersonic flow and hence provide insights into scramjet design improvement

Effects of injection pressure variation on mixing in a cold supersonic combustor with kerosene fuel

Abstract: Spray jet in cold kerosene-fueled supersonic flow has been characterized under different injection pressures to assess the effects of the pressure variation on the mixing between incident shock wave and transverse cavity injection. Based on the real scramjet combustor, a detailed computational fluid dynamics model is developed. The injection pressures are specified as 0.5, 1.0, 2.0, 3.0 and 4.0 MPa, respectively, with the other constant operation parameters (such as the injection diameter, angle and velocity). A three dimensional Couple Level Set & Volume of Fluids approach incorporating an improved Kelvin-Helmholtz & Rayleigh-Taylor model is used to investigate the interaction between kerosene and supersonic air. The numerical simulations primarily concentrate on penetration depth, span expansion area, angle of shock wave and sauter mean diameter distribution of the kerosene droplets with/without evaporation. Validation has been implemented by comparing the calculated against the measured in literature with good qualitative agreement. Results show that the penetration depth, span-wise angle and expansion area of the transverse cavity jet are all increased with the injection pressure. However, when the injection pressure is further increased, the value in either penetration depth or expansion area increases appreciably. This study demonstrates the feasibility and effectiveness of the combination of Couple Level Set & Volume of Fluids approach and an improved Kelvin-Helmholtz & Rayleigh-Taylor model, in turn providing insights into scramjet design improvement

The Minimum Variation Timescales of X-ray bursts from SGR J1935+2154

The minimum variation timescale (MVT) of soft gamma-ray repeaters can be an important probe to estimate the emission region in pulsar-like models, as well as the Lorentz factor and radius of the possible relativistic jet in gamma-ray burst (GRB)-like models, thus revealing their progenitors and physical mechanisms. In this work, we systematically study the MVTs of hundreds of X-ray bursts (XRBs) from SGR J1935+2154 observed by {\it Insight}-HXMT, GECAM and Fermi/GBM from July 2014 to Jan 2022 through the Bayesian Block algorithm. We find that the MVTs peak at $\sim$ 2 ms, corresponding to a light travel time size of about 600 km, which supports the magnetospheric origin in pulsar-like models. The shock radius and the Lorentz factor of the jet are also constrained in GRB-like models. Interestingly, the MVT of the XRB associated with FRB 200428 is $\sim$ 70 ms, which is longer than that of most bursts and implies its special radiation mechanism. Besides, the median of MVTs is 7 ms, shorter than the median MVTs of 40 ms and 480 ms for short GRBs or long GRBs, respectively. However, the MVT is independent of duration, similar to GRBs. Finally, we investigate the energy dependence of MVT and suggest that there is a marginal evidence for a power-law relationship like GRBs but the rate of variation is at least about an order of magnitude smaller. These features may provide an approach to identify bursts with a magnetar origin.Comment: accepted for publication in ApJ

A longitudinal resource for population neuroscience of school-age children and adolescents in China

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013–2022), the first ten-year stage of the lifespan CCNP (2013–2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0–17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the “Chinese Data-sharing Warehouse for In-vivo Imaging Brain” in the Chinese Color Nest Project (CCNP) – Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust

An accurate green fruits detection method based on optimized YOLOX-m

Fruit detection and recognition has an important impact on fruit and vegetable harvesting, yield prediction and growth information monitoring in the automation process of modern agriculture, and the actual complex environment of orchards poses some challenges for accurate fruit detection. In order to achieve accurate detection of green fruits in complex orchard environments, this paper proposes an accurate object detection method for green fruits based on optimized YOLOX_m. First, the model extracts features from the input image using the CSPDarkNet backbone network to obtain three effective feature layers at different scales. Then, these effective feature layers are fed into the feature fusion pyramid network for enhanced feature extraction, which combines feature information from different scales, and in this process, the Atrous spatial pyramid pooling (ASPP) module is used to increase the receptive field and enhance the network’s ability to obtain multi-scale contextual information. Finally, the fused features are fed into the head prediction network for classification prediction and regression prediction. In addition, Varifocal loss is used to mitigate the negative impact of unbalanced distribution of positive and negative samples to obtain higher precision. The experimental results show that the model in this paper has improved on both apple and persimmon datasets, with the average precision (AP) reaching 64.3% and 74.7%, respectively. Compared with other models commonly used for detection, the model approach in this study has a higher average precision and has improved in other performance metrics, which can provide a reference for the detection of other fruits and vegetables

Development and validation of a novel chemiluminescent immunoassay for diagnosing primary aldosteronism

Purpose: To compare the diagnostic accuracy of plasma aldosterone concentration (PAC), plasma renin activity (PRA) and aldosterone-to-renin ratio (ARR) in primary aldosteronism (PA) using radioimmunoassay (RIA) and chemiluminescence immunoassay (CLIA) methods. Methods: Both RIA and CLIA were used to analyze the PAC, PRA and ARR with subjects in standing or supine position, before and after a saline infusion test (SIT). The correlation between RIA and CLIA was measured by regression analysis. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic accuracy by RIA and CLIA. Results: A positive correlation was found between PAC and PRA after SIT using RIA and CLIA (0.1745 and 0.3085, respectively). A positive correlation was found between the PAC and PRA in standing and supine position using RIA and CLIA (0.3979 vs 0.2399 and 0.1885 vs 0.4032, respectively). There was no obvious difference in AUCs of PAC, PRA, and ARR between RIA and CLIA (PAC: 0.91 vs. 0.89; PRA: 0.88 vs. 0.87; ARR: 0.93 vs. 0.92). In standing posture, the AUCs of PAC, PRA and ARR using RIA were 0.63, 0.72 and 0.78, respectively, and the results of CLIA were 0.65, 0.75 and 0.82, respectively. In supine posture, the AUC of PAC, PRA and ARR using RIA was 0.65, 0.68 and 0.71, respectively, and the results of CLIA were 0.68, 0.70 and 0.79, respectively. Conclusion: Chemiluminescent assay is reliable for diagnosis of PA when compared with radioimmunoassay

A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4

Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s) on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s) and the site(s) of modification. The newly established model was applied to predict the metabolic site(s) of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s) of CYP3A4 on steroids with high predictive accuracy