An iterative data-driven turbulence modeling framework based on Reynolds stress representation

Data-driven turbulence modeling studies have reached such a stage that the fundamental framework is basically settled, but several essential issues remain that strongly affect the performance, including accuracy, smoothness, and generalization capacity. Two problems are studied in the current research: (1) the processing of the Reynolds stress tensor and (2) the coupling method between the machine learning turbulence model and CFD solver. The first determines the form of predicting targets and the resulting physical completeness and interpretability. The second determines the training process and intrinsic relevance between the mean flow features and Reynolds stress. For the Reynolds stress processing issue, we perform the theoretical derivation to extend the relevant tensor arguments of Reynolds stress in addition to the strain rate and rotation rate. Then, the tensor representation theorem is employed to give the complete irreducible invariants and integrity basis. In addition, an adaptive regularization term is employed to enhance the representation performance. For the CFD coupling issue, an iterative coupling data-driven turbulence modeling framework with consistent convergence is proposed. The training data preparation, predicting target selection, and computation platform are illustrated. The framework is then applied to a canonical separated flow for verification. The mean flow results obtained by coupling computation of the trained machine learning model and CFD solver have high consistency with the DNS true values, which proves the validity of the current approach

Regulation mechanisms of disulfidptosis-related genes in ankylosing spondylitis and inflammatory bowel disease

IntroductionDisulfidptosis is a recently identified form of cell death that contributes to maintaining the internal environment balance of an organism. However, the molecular basis of disulfidptosis in ulcerative colitis (UC), ankylosing spondylitis (AS), and Crohn’s disease (CD) has not been thoroughly explored.MethodsFirstly, the differentially expressed genes (DEGs) and disulfidptosis-associated genes (DAGs) were obtained through differential analysis between diseases (AS, CD, and UC) and control groups. After the disulfidptosis score was acquired using the single-sample gene set enrichment analysis (ssGSEA) algorithm, the DE-DAGs were screened by overlapping DAGs and DEGs of the three diseases. Next, the feature genes were selected through a combination of machine learning algorithms, receiver operating characteristic (ROC) curves, and expression analysis. Based on these feature genes, nomograms were created for AS, CD and UC. The co-feature genes were then identified by taking the intersections of the genes featured in all three diseases. Meanwhile, single-gene set enrichment analysis (GSEA) and the TF-mRNA-miRNA network were utilized to investigate the molecular mechanisms of the co-feature genes. To validate the expression differences of the co-feature genes between healthy controls and patients (AS and IBD), RT-PCR was performed. Lastly, mendelian randomization (MR) analysis was utilized to explore the causality between genetic variants of S100A12 with AS, UC and CD.ResultsIn this study, 11 DE-DAGs were obtained. Functional enrichment analysis revealed their involvement in cytokine production and fatty acid biosynthesis. Latterly, AS/CD/UC -feature genes were derived, and they all had decent diagnostic performance. Through evaluation, the performance of the nomogram was decent for three diseases. Then, 2 co-feature genes (S100A12 and LILRA5) were obtained. The GSEA enrichment results indicated that the co-feature genes were mainly enriched in the cytokine-cytokine receptor interaction and drug metabolism cytochrome P450. As shown by functional experiments, there was a correlation between the mRNA expression of S100A12 with AS, UC and CD. Additionally, a causal connection between S100A12 and IBD was detected through MR analysis.DiscussionIn this study, 2 co-feature genes (S100A12 and LILRA5) were screened, and their functions were investigated in AS, CD and UC, providing a basis for further research into diagnosis and treatment

Dual RNA-Seq of Trunk Kidneys Extracted From Channel Catfish Infected With Yersinia ruckeri Reveals Novel Insights Into Host-Pathogen Interactions

Host-pathogen intectarions are complex, involving large dynamic changes in gene expression through the process of infection. These interactions are essential for understanding anti-infective immunity as well as pathogenesis. In this study, the host-pathogen interaction was analyzed using a model of acute infection where channel catfish were infected with Yersinia ruckeri. The infected fish showed signs of body surface hyperemia as well as hyperemia and swelling in the trunk kidney. Double RNA sequencing was performed on trunk kidneys extracted from infected channel catfish and transcriptome data was compared with data from uninfected trunk kidneys. Results revealed that the host-pathogen interaction was dynamically regulated and that the host-pathogen transcriptome fluctuated during infection. More specifically, these data revealed that the expression levels of immune genes involved in Cytokine-cytokine receptor interactions, the NF-kappa B signaling pathway, the JAK-STAT signaling pathway, Toll-like receptor signaling and other immune-related pathways were significantly upregulated. Y. ruckeri mainly promote pathogenesis through the flagellum gene fliC in channel catfish. The weighted gene co-expression network analysis (WGCNA) R package was used to reveal that the infection of catfish is closely related to metabolic pathways. This study contributes to the understanding of the host-pathogen interaction between channel catfish and Y. ruckeri, more specifically how catfish respond to infection through a transcriptional perspective and how this infection leads to enteric red mouth disease (ERM) in these fish

Design and Optimization of Multiple Circumferential Casing Grooves Distribution Considering Sweep and Lean Variations on the Blade Tip

This paper focuses on the design and optimization of the axial distribution of the circumferential groove casing treatment (CGCT). Effects of the axial location of multiple casing grooves on the flow structures are numerically studied. Sweep and lean variations are then introduced to the blade tip, and their influences on the grooves are discussed. The results show that the ability of the CGCT to relieve the blockage varies with the distribution of grooves, and the three-dimensional blading affects the performance of both the blade and the CGCT. Accordingly, a multi-objective optimization combining the CGCT design with the sweep and lean design is conducted. Objectives, including the total pressure ratio and the adiabatic efficiency, are set at the design point; meanwhile, the choking mass flow and the near-stall performance are constrained. The coupling between the CGCT and the blade is improved, which contributes to an optimal design point performance and a sufficient stall margin. The sweep and lean in the tip redistribute the spanwise and chordwise loading, which enhances the ability of the CGCT to improve the blade’s performance. This work shows that the present CGCT-blade integrated optimization is a practical engineering strategy to develop the working capacity and efficiency of a compressor blade while achieving the stall margin extension

on the probability distribution of the carry cells of stream ciphers f-fcsr-h v2 and f-fcsr-h v3

F-FCSR-H v2 is one of the 8 final stream ciphers in the eSTREAM portfolio. However, it was broken by M. Hell and T. Johansson at ASIACRYPT 2008 by exploiting the bias in the carry cells of a Galois FCSR. In order to resist this attack, at SAC 2009 F. Arnault proposed the new stream cipher F-FCSR-H v3 based upon a ring FCSR. M. Hell and T. Johansson only presented experimental results but no theoretical results for the success probability of their powerful attack against F-FCSR-H v2. And so far there are no analytical results of F-FCSR-H v3. This paper discusses the probability distribution of the carry cells of F-FCSR-H v2 and F-FCSR-H v3. We build the probability model for the carry cells of the two stream ciphers and prove that the consecutive output sequence of a single carry cell is a homogeneous Markov chain and the inverse chain is also a homogeneous Markov chain. We also prove that the probability of l consecutive outputs of a single carry cell to be zeros is (1/2)&middot(3/4) l∈-∈1, which is a weakness of the carry cells of F-FCSR-H v2 and F-FCSR-H v3, noticing that (1/2)&middot(3/4) l∈-∈1∈>∈2-∈l for l∈>∈1. FCSR is a finite-state automata, so its distribution is stable. Based on this fact, we construct a system of equations using the law of total probability, and present a theoretical probability of breaking F-FCSR-H v2 by solving the equations. Applying this technique to F-FCSR-H v3, we obtain that the probability of all the 82 carry cells of F-FCSR-H v3 to be zeros at the same clock is at least 2-∈64.29, which is much higher than 2-∈82. This is another weakness of the carry cells of F-FCSR-H v3. Our results provide theoretical support to M.Hell and T.Johansson's cryptanalysis of F-FCSR-H v2 and establish a theoretical foundation for further cryptanalysis of F-FCSR-H v3. © 2012 Springer-Verlag Berlin Heidelberg.F-FCSR-H v2 is one of the 8 final stream ciphers in the eSTREAM portfolio. However, it was broken by M. Hell and T. Johansson at ASIACRYPT 2008 by exploiting the bias in the carry cells of a Galois FCSR. In order to resist this attack, at SAC 2009 F. Arnault proposed the new stream cipher F-FCSR-H v3 based upon a ring FCSR. M. Hell and T. Johansson only presented experimental results but no theoretical results for the success probability of their powerful attack against F-FCSR-H v2. And so far there are no analytical results of F-FCSR-H v3. This paper discusses the probability distribution of the carry cells of F-FCSR-H v2 and F-FCSR-H v3. We build the probability model for the carry cells of the two stream ciphers and prove that the consecutive output sequence of a single carry cell is a homogeneous Markov chain and the inverse chain is also a homogeneous Markov chain. We also prove that the probability of l consecutive outputs of a single carry cell to be zeros is (1/2)&middot(3/4) l∈-∈1, which is a weakness of the carry cells of F-FCSR-H v2 and F-FCSR-H v3, noticing that (1/2)&middot(3/4) l∈-∈1∈>∈2-∈l for l∈>∈1. FCSR is a finite-state automata, so its distribution is stable. Based on this fact, we construct a system of equations using the law of total probability, and present a theoretical probability of breaking F-FCSR-H v2 by solving the equations. Applying this technique to F-FCSR-H v3, we obtain that the probability of all the 82 carry cells of F-FCSR-H v3 to be zeros at the same clock is at least 2-∈64.29, which is much higher than 2-∈82. This is another weakness of the carry cells of F-FCSR-H v3. Our results provide theoretical support to M.Hell and T.Johansson's cryptanalysis of F-FCSR-H v2 and establish a theoretical foundation for further cryptanalysis of F-FCSR-H v3. © 2012 Springer-Verlag Berlin Heidelberg

Explicit Solution for Critical Depth in Closed Conduits Flowing Partly Full

Critical depth is an essential parameter for the design, operation, and maintenance of conduits. Circular, arched, and egg-shaped sections are often used in non-pressure conduits in hydraulic engineering, irrigation, and sewerage works. However, equations governing the critical depth in various sections are complicated implicit transcendental equations. The function model is established for the geometric features of multiple sections using the mathematical transform method and while considering non-dimensional parameters. Then, revised PSO algorithms are implemented in MATLAB, and the right solution’s formula for the critical depths in various non-pressure conduit sections is established through optimization. The error analysis results show that the established formula has broad applicability. The maximum relative errors of the formula for critical depths are less than 0.182%, 0.0629%, and 0.170% in circular, arched, and egg-shaped sections, respectively, which are more accurate than those of existing formulas; the form of the formula proposed in this work is also more compact than that of the existing formulas. The results of this research may be useful in design, operation, and maintenance in conduit engineering

Multi-Robot Formation Control Based on CVT Algorithm and Health Optimization Management

In view of the low formation redundancy in the traditional rigid formation algorithm and its difficulty in dynamically adapting to the external environment, this study considers the use of the CVT (centroidal Voronoi tessellation) algorithm to control multiple robots to form the desired formation. This method significantly increases the complexity of the multi-robot system, its structural redundancy, and its internal carrying capacity. First, we used the CVT algorithm to complete the Voronoi division of the global map, and then changed the centroid position of the Voronoi cell by adjusting the density function. When the algorithm converged, it could ensure that the position of the generated point was the centroid of each Voronoi cell and control the robot to track the position of the generated point to form the desired formation. The use of traditional formations requires less consideration of the impact of the actual environment on the health of robots, the overall mission performance of the formation, and the future reliability. We propose a health optimization management algorithm based on minor changes to the original framework to minimize the health loss of robots and reduce the impact of environmental restrictions on formation sites, thereby improving the robustness of the formation system. Simulation and robot formation experiments proved that the CVT algorithm could control the robots to quickly generate formations, easily switch formations dynamically, and solve the formation maintenance problem in obstacle scenarios. Furthermore, the health optimization management algorithm could maximize the life of unhealthy robots, making the formation more robust when performing tasks in different scenarios