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Based on the conservation laws of energy and mass, and taking into account the effect of chemical reaction between liquid titanium and zirconia ceramic mold on the concentration field and the temperature field, a comprehensive mathematical model for numerical simulation of heat and mass transfer has been established to study the interfacial reaction between liquid Ti and ZrO2 ceramic mold. With the proposed model, numerical simulations were preformed to investigate the effects of pouring temperature and holding time on the oxygen concentrations and reactive layer thickness in metal. The results showed that both the oxygen concentration and the thickness of reactive layer in metal increase with the increase of the holding time and the pouring temperature. The development of reactive layer thickness with time consists of three stages: inoculation (0-1 s), linear increase (1-5 s) and parabolic increase (after 5 s).

In this research, the effects of centrifugal radius and mould rotation speed on microstructure in centrifugal-cast Al-Cu alloy have been investigated. The results show that, with increase of the centrifugal radius or mould rotation speed, the grain size of centrifugal-cast Al-Cu alloy decreases gradually, while the content of white phases containing the Al2Cu precipitated from α-phase, divorced eutectic and regular eutectic microstructure increases, leading to higher Cu macrosegregation. The variation level of microstructure in centrifugal-cast Al-Cu alloy at 600 rpm of mould rotation speed is greater than that at 300 rpm.

Abstract: A study on the interaction between TiAl alloy and zirconia was carried out in argon atmosphere. The micrographic observations of the cross-section perpendicular to the interface were obtained using a scanning electron microscope with a dedicated energy dispersive spectrometer (SEM/EDS). The results showed that firstly TiAl alloy spreads on the ceramic surface, and then infiltrates into the pores between ceramic particles accompanied by a chemical reaction. The whole ceramic mold is broken into tiny blocks. A multiple fission reaction mechanism was developed to explain the interaction between TiAl alloy and zirconia.

Background: Epidemiological and observational studies have indicated an association between Sjögren's syndrome (SS) and Parkinson's disease (PD). However, consistent conclusions have not been reached due to various limitations. In order to determine whether SS and PD are causally related, we conducted a Mendelian randomization study (MR) with two samples. Methods: Data for SS derived from the FinnGen consortium's R9 release (2495 cases and 365 533 controls). Moreover, data for PD were acquired from the publicly available GWAS of European ancestry, which involved 33 674 cases and 449 056 controls. The inverse variance weighted, along with four other effective methodologies, were employed to comprehensively infer the causal relationships between SS and PD. To assess the estimation's robustness, a number of sensitivity studies were performed. To determine the probability of reverse causality, we performed a reverse MR analysis. Results: There was no evidence of a significant causal effect of SS on PD risks based on the MR [odds ratio (OR) = 1.03; 95% confidence interval (CI) = 0.95–1.11; p =.45]. Similarly, no evidence supported the causal effects of PD on SS (OR = 0.92; 95% CI = 0.81–1.04; p =.20). These findings held up under rigorous sensitivity analysis. Conclusions: MR bidirectional analysis did not reveal any cause‐and‐effect relationship between SS and PD, or vice versa. Further study of the mechanisms that may underlie the probable causal association between SS and PD is needed. [ABSTRACT FROM AUTHOR]

Objectives: Fibromyalgia (FM) is a chronic pain disorder that takes a severe physical and psychological toll on patients and severely reduces their quality of life. In recent years, an increasing number of studies have used functional magnetic resonance imaging (fMRI) to investigate its pathogenesis. However, a recent summary analysis of functional connectivity in patients with FM is lacking., Methods: We searched bibliographic databases, including PubMed, Web of Science (from inception until September 1st, 2022). Two separate researchers assessed the bias and quality of the studies. In order to further explain the core mechanism for FM, the abnormal brain function of FM was investigated by Activation Likelihood Estimation (ALE) analysis., Results: Twenty-six FM publications (1,056 subjects) were eligible to be included in an ALE analysis. We found that the anterior cingulate (ACC) and insula (Ins) were abnormally active in patients with FM. In particular, the peak coordinates of (8,46,4) and (-46, -4,10) correspond to brain regions that were less active than healthy individuals. Furthermore, the Z-values were 4.46 and 4.97, while the p-values were 4.06 and 3.38. Surprisingly, we found that the degree of pain was negatively correlated with the activation of Ins (SDM-Z = -2.714)., Conclusions: This study demonstrates abnormal brain activation which could lead to increased sensitivity of pain in patients with FM. The study sheds light on the central mechanisms of FM and provides the basis for further research.

Background: The extra-articular lesions of rheumatoid arthritis (RA) are reported to involve multiple organs and systems throughout the body, including the heart, kidneys, liver, and lungs. This study assessed the potential causal relationship between RA and the risk of chronic kidney diseases (CKDs) using the Mendelian randomization (MR) analysis., Method: Independent genetic instruments related to RA and CKD or CKD subtypes at the genome-wide significant level were chosen from the publicly shared summary-level data of genome-wide association studies (GWAS). Then, we obtained some single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs), which are associated with RA in individuals of European origin, and had genome-wide statistical significance (p5 × 10 -8 ). The inverse-variance weighted (IVW) method was the main analysis method in MR analysis. The other methods, such as weighted median, MR-Egger, simple mode, and weighted mode were used as supplementary sensitivity analyses. Furthermore, the levels of pleiotropy and heterogeneity were assessed using Cochran's Q test and leave-one-out analysis. Furthermore, the relevant datasets were obtained from the Open GWAS database., Results: Using the IVW method, the main method in MR analysis, the results showed that genetically determined RA was associated with higher risks of CKD [odds ratio (OR): 1.22, 95% confidence interval (CI) 1.13-1.31; p  < 0.001], glomerulonephritis (OR: 1.23, 95% CI 1.15-1.31; p < 0.000), amyloidosis (OR = 1.43, 95% CI 1.10-1.88, p  < 0.001), and renal failure (OR = 1.18, 95% CI 1.00-1.38, p  < 0.001). Then, using multiple MR methods, it was confirmed that the associations persisted in sensitivity analyses, and no pleiotropy was detected., Conclusion: The findings revealed a causal relationship between RA and CKD, including glomerulonephritis, amyloidosis, and renal failure. Therefore, RA patients should pay more attention to monitoring their kidney function, thus providing the opportunity for earlier intervention and lower the risk of progression to CKDs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Jiang, Chen, Liu, Qi, Wang, Li, Jiang, Zhang, Huang, Mao and Ying.)

We present a data-driven and interpretable approach for reducing the dimensionality of chaotic systems using spectral submanifolds (SSMs). Emanating from fixed points or periodic orbits, these SSMs are low-dimensional inertial manifolds containing the chaotic attractor of the underlying high-dimensional system. The reduced dynamics on the SSMs turn out to predict chaotic dynamics accurately over a few Lyapunov times and also reproduce long-term statistical features, such as the largest Lyapunov exponents and probability distributions, of the chaotic attractor. We illustrate this methodology on numerical data sets including delay-embedded Lorenz and Rössler attractors, a nine-dimensional Lorenz model, a periodically forced Duffing oscillator chain, and the Kuramoto-Sivashinsky equation. We also demonstrate the predictive power of our approach by constructing an SSM-reduced model from unforced trajectories of a buckling beam and then predicting its periodically forced chaotic response without using data from the forced beam., (© 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).)