A two‐step simulation approach combining large eddy simulation (LES) for turbulent flame and multidimensional/multivariate population balance Monte Carlo (PBMC) for nanoparticle dynamics is proposed ...to explore the detailed flame fields and particle dynamics of zirconia nanoparticles in a flame spray pyrolysis (FSP) reactor. The turbulent combustion of gas and spray are simulated by the nonlinear LES‐partially stirred reactor model. Thereafter, the differentially weighted PBMC is applied for the first time to describe the spatially resolved formation and growth of nanoparticles using the flame fields derived from LES as an input. An efficient submodel for particle spatial transport in multidimensional grids is adopted and tested to account for the effect of thermophoresis, convective and diffusion of the nanoparticles. This methodology is successfully applied to an FSP case, demonstrating a reliable level of fidelity when compared to experiments and other model. Simulation results are discussed, in particular the flame fields and the size, morphology, as well as polydisperse primary particle and aggregates size distribution.
Describing spatiotemporal evolution and characteristics of dispersed systems using the population balance equation (PBE), examples including sectional and moment methods are fraught with numerous ...issues. Hence, this study develops an accurate method by combining computational fluid dynamics and population balance‐Monte Carlo method (CFD‐PBMC) with a moderate computational cost. An efficient sub‐model for particle migration was proposed to simulate the convection and diffusion processes of particulate flows. A graphics processing unit (GPU)‐based parallel computation was performed to accelerate the high‐dimensional CFD‐PBMC. Several classical cases with analytical or benchmark solutions were simulated, and a comprehensive comparison was made using the classical weighted random walk method. Good agreements were obtained, except in the case of radial migration, the reasons for which are explained in detail. The measured speedups on the GPU showed a factor of ~450 for pure migration and ~50 for the CFD‐PBMC method when compared with a standard high‐performance computer.
Beryllium is widely used in the manufacturing of precision instruments because of its high thermal and mechanical properties. However, because beryllium is expensive, and processing it generally uses ...subtractive manufacturing methods, the cost is high, the utilization rate of cutting the materials is low, and the processing is difficult. Additionally, it is extremely prone to cracking, brittle fracturing, and fracturing during the machining process. In this paper, a new method for manufacturing beryllium laser additives under a pressure atmosphere is proposed. Via the single-point and single-pass laser melting of beryllium materials in an inert gas (Ar) pressure atmosphere, the results of the experiments conducted in the pressure range of 1 to 30 bar indicated the following: (1) beryllium can absorb the laser and form a molten pool, and the contour area of the upper surface of the molten pool is approximately 80% of that of 304 stainless steel under the same energy input; (2) severe oxidation occurs on and near the molten pool surface under low pressure, and oxidation is eliminated when the pressure is increased; (3) as ambient pressure increases, the surface profile of the molten pool gradually exhibits an irregular shape, and the cracks on the surface of beryllium change from “divergent” to “shrinkage”, which can eliminate cracking. At higher pressures, the “small hole” phenomenon in the molten pool disappears, forming a wide and shallow molten pool shape that is more conducive to stable deposition. The experimental results indicate that the laser-additive manufacturing of beryllium in a pressure atmosphere is a meaningful developmental direction for beryllium processing in the future.
To solve the problems of texture lacking and resolution coarseness in the detection of dim and small drone targets in infrared images, we propose a novel RetinaNet with an asymmetric attention fusion ...mechanism for dim and small drone detection. First, we propose a super-resolution texture-enhancement network as an effective solution for the lack of texture-related information on small infrared targets. The network generates super-resolution images and enhances the texture features of the targets. Second, considering the inadequacy of feature pyramids in the feature fusion stage, we use an asymmetric attention fusion mechanism to constitute an asymmetric attention fusion pyramid network for cross-layer feature fusion in a bidirectional manner; it achieves high-quality semantic and location detail information interaction between scale features. Third, a global average pooling layer is employed to capture global spatial-sensitive information, thus effectively identifying features and achieving classification. Experiments were conducted by using a publicly available infrared image dim-small drone target detection dataset; the results show that the proposed method achieves an AP of 95.43% and a recall of 80.6%, which is a significant improvement over the current mainstream target detection algorithms.
Summary
Panicle architecture is a key determinant of grain yield in cereals, but the mechanisms governing panicle morphogenesis and organ development remain elusive. Here, we have identified a ...quantitative trait locus (qPA1) associated with panicle architecture using chromosome segment substitution lines from parents Nipponbare and 9311. The panicle length, branch number and grain number of Nipponbare were significantly higher than CSSL‐9. Through map‐based cloning and complementation tests, we confirmed that qPA1 was identical to SD1 (Semi Dwarf1), which encodes a gibberellin 20‐oxidase enzyme participating in gibberellic acid (GA) biosynthesis. Transcript analysis revealed that SD1 was widely expressed during early panicle development. Analysis of sd1/osga20ox2 and gnp1/ osga20ox1 single and double mutants revealed that the two paralogous enzymes have non‐redundant functions during panicle development, likely due to differences in spatiotemporal expression; GNP1 expression under control of the SD1 promoter could rescue the sd1 phenotype. The DELLA protein SLR1, a component of the GA signalling pathway, accumulated more highly in sd1 plants. We have demonstrated that SLR1 physically interacts with the meristem identity class I KNOTTED1‐LIKE HOMEOBOX (KNOX) protein OSH1 to repress OSH1‐mediated activation of downstream genes related to panicle development, providing a mechanistic link between gibberellin and panicle architecture morphogenesis.
A new hydrolysable tannin, ethyl castavaloninate (
1
), was isolated from the seeds of
Quercus wutaishanica,
along with nine known compounds, γ-tocopherol (
2
), ethyl brevifolincarboxylate (
3
), ...brevifolin (
4
), (–)-7,7′-dioxodihydroguaiaretic acid (
5
), (–)-pinoresinol (
6
), (–)-dihydrodehydrodiconiferyl alcohol (
7
), (+)-isolariciresinol (
8
), decarboxylated ellagic acid (
9
), and ellagic acid 4-O-xylopyranoside (
10
). The structure of
1
was determined by spectroscopic methods, including NMR, HR-ESI-MS, and IR spectra. This is the first report of compounds
2–10
from the genus
Quercus.
Nonlinear minimization, as a subcase of nonlinear optimization, is an important issue in the research of various intelligent systems. Recently, Zhang et al. developed the continuous-time and ...discrete-time forms of Zhang dynamics (ZD) for time-varying nonlinear minimization. Based on this previous work, another two discrete-time ZD (DTZD) algorithms are proposed and investigated in this paper. Specifically, the resultant DTZD algorithms are developed for time-varying nonlinear minimization by utilizing two different types of Taylor-type difference rules. Theoretically, each steady-state residual error in the DTZD algorithm changes in an
O
(
τ
3
) manner with
τ
being the sampling gap. Comparative numerical results are presented to further substantiate the efficacy and superiority of the proposed DTZD algorithms for time-varying nonlinear minimization.
Abstract
In the adhesive assembly of precision inertial instruments, it is easy for the center of mass to shift due to creep in the adhesive structure, resulting in a reduction in the accuracy of the ...instrument. In the presence of ambient temperature variations, these center of mass shifts can change further, causing variations in the accuracy of the instrument, that is, the accuracy stability problem. This paper investigates this accuracy stability problem. Firstly, numerical simulation modeling of an adhesive structure with assembly errors is carried out, then the center of mass displacement of the structure due to creep of the adhesive structure under different temperature loads is analyzed, and finally, experimental verification of the simulation results is carried out by developing a structural creep experimental device to verify the validity of the simulation results. This thesis provides a theoretical reference for the stability control of the accuracy of adhesive structures with assembly errors.
The effects of ambient pressure on single-pulse laser processing of austenite stainless steel were investigated in this study. The ambient pressure environments were created by Ar gas and ranged from ...0.001 bar to 45 bar. It is observed that the ejection and expansion of the metal vapor are severe under a low pressure and gradually become limited with the increase of ambient pressure. Numerous oxides remain on the molten-pool surface under a low pressure, and a shiny solidified molten-pool surface without oxides can be obtained when the pressure is higher than 10 bar. Furthermore, the ripples induced by the ejection of the metal vapor were detected on the solidified molten-pool surface, and it significantly reduced with the increase in ambient pressure. Larger aspect ratios of molten pools were obtained under higher pressures, and a tendency wherein the primary dendrite arm spacing and grain size decrease with the increase of ambient pressure was observed. When the ambient pressure changed from 0.001 bar to 45 bar, the aspect ratio increased by approximately 12%, the dendrite arm spacing decreased approximately 12% and 4% on the side and center positions, respectively, and the grain size decreased approximately 37%.
Non-cryopreservation temperature exposure (NCE) is a vital preanalytical factor for assessing plasma quality. NCE can introduce undesirable errors in clinical diagnosis or when developing biomarkers ...of diseases. Biomarkers that can effectively indicate the changes in sample quality caused by long-term NCE (0–several days) are limited. Low-molecular-weight (LMW) peptides in the plasma are modulated by endogenous proteases. These protease activities are significantly correlated with NCE temperatures and duration, indicating a potential link of these protease reactions with the preanalytical quality of plasma samples. In this study, two groups of plasma samples were aged at room temperature (RT, 57 samples) and 4 °C (69 samples) for different durations (0, 1, 2, 5, and 10 days), and LMW peptidomics were analyzed through nanopore-assisted matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The analysis revealed 10 peptides that consistently exhibited time-dependent changes, which were used to develop multiple-variable models for predicting the changes in sample quality resulting from extended NCE. These biomarker models exhibited outstanding performance in distinguishing poor-quality samples aged at both RT and 4 °C. To validate the findings, tests on samples from validation sets were conducted by analysts who were blinded to the detailed conditions, which revealed a high specificity (94.3–96.9%) and sensitivity (90.5–99.3%). These results indicate the potential of these peptides as novel biomarkers of quality control.
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