Investigation of the Effect of Stress on Oxygen Diffusion in Pure Titanium Using a Phase-Field Model

Diffusion plays a vital role during the fabrication of many materials. It is a well-known fact that stress can influence diffusion behavior. In order to optimize material processing techniques, a quantitative evaluation of the effect of stress on diffusion is essentially required. By analyzing the free energy change in a Ti-O system during diffusion, a phase-field model was developed to address this issue. Using this model, the diffusion of oxygen atoms in pure titanium under different stress states was investigated. It was observed that the true equilibrium concentration of oxygen was proportional to its hydrostatic pressure. Tensile stress can increase the oxygen concentration. This raise in concentration decreased with temperature. However, the promotion of diffusion can be attained in deeper regions at a higher temperature. On the contrary, compressive stress inhibited the diffusion of oxygen in pure titanium. Under a certain compressive stress, the decrease in the oxygen concentration at the surface layer was more significant at a lower temperature, while a decrease could be observed at a deeper distance from the surface at a higher temperature. A thermodynamic explanation of the effect of stress on diffusion was given based on the proposed phase-field model.

In Situ Fabrication of SnO2 Nanowalls for Robust Acetylene Sensing at Low Temperature

Acetylene (C2 H2 ) monitoring in real time and online is essential for erasing transformer risks and guaranteeing normal equipment operation and operator safety. This study examines the direct fabrication of ultrathin SnO2 nanowalls on Ag-Pd substrates using a simple solvothermal method that doesn't demand the use of any additional motivators or templates. The thickness and shape of the nanowalls can be controlled by varying the cetyl trimethyl ammonium bromide (CTAB) concentration in the solvent. As observed, the gas sensor (SnO2 -3) fabricated by 2.4 g CTAB exhibits superior gas-sensing features. This is primarily due to the hollow structure constructed by the arrangement of nanowalls, which delivers not only enough gas diffusion pathways but also enough reaction sites during the gas sensing processes. The findings suggest that low-cost SnO2 nanowalls created using a straightforward procedure could be taken into consideration as prospective candidates for use in industrial C2 H2 sensing applications.

Correlation between essential and toxic elements in maternal blood during early pregnancy and atrial septal defects/ventricular septal defects/patent ductus arteriosus in offspring

BACKGROUND

Congenital heart defects (CHDs) are the most common congenital malformation in the world. Recent studies have found that essential and toxic trace element levels may play a crucial role in the risk of neonatal malformation. However, the relationships between element levels in early pregnancy and CHD risk among humans remain unclear. This study investigates the association between maternal essential element (copper [Cu], zinc [Zn], calcium [Ca], manganese [Mg] and iron [Fe]) and toxic element (lead [Pb] and cadmium [Cd]) levels during early pregnancy and CHDs.

METHODS

A hospital-based case-control study was conducted, including 181 cases and 218 controls. Eligible participants underwent antenatal examination during gestational weeks 11-14 and trace element levels were detected by the atomic absorption method. Multi-variable logistic regression was used to examine the associations between the level of maternal trace elements and CHD risks.

RESULTS

Higher levels of Ca in early pregnancy were associated with lower risk of ASD/VSD risks. Moreover, higher Fe, Pb, and Cd levels in the first trimester were associated with higher risks of all CHD and the subtypes risks, and the tests for trend were significant (all p < .05). The restricted cubic spline analysis showed that there was a nonlinear inverted u-shaped dose-response relationship between levels of Zn, Pb, and Cd in the first trimester and risk of CHDs (non-linearity test p < .05).

CONCLUSIONS

A moderate increase in Zn and Ca levels and a decrease in Pb and Cd levels during early pregnancy are needed to reduce the incidence of CHDs in the Chinese population.

The novel HLA-C*14:02:01:33 allele identified by Pacific Biosciences HiFi sequencing in a Chinese individual

HLA-C*14:02:01:33 differs from HLA-C*14:02:01:01 by one nucleotide substitution in intron 2.

Enantioselective Total Synthesis of (-)-Cephalotanin B

Cephalotaxus diterpenoids are attractive natural products with intriguing molecular frameworks and promising biological features. As a structurally unusual member, (-)-cephalotanin B possesses an extraordinarily congested heptacyclic skeleton, three lactone units, and nine consecutive stereocenters. Herein, we report an enantioselective total synthesis of (-)-cephalotanin B based on a divergent asymmetric Michael addition reaction, a novel Pauson-Khand/deacyloxylation process discovered in the development of a second-generation stereoselective Pauson-Khand reaction protocol, and an epoxide-opening/elimination/dual-lactonization cascade to construct the challenging propeller-shaped A-B-C ring system as key transformations.

Electric Bus Pedal Misapplication Detection Based on Phase Space Reconstruction Method

Due to the environmental protection of electric buses, they are gradually replacing traditional fuel buses. Several previous studies have found that accidents related to electric vehicles are linked to Unintended Acceleration (UA), which is mostly caused by the driver pressing the wrong pedal. Therefore, this study proposed a Model for Detecting Pedal Misapplication in Electric Buses (MDPMEB). In this work, natural driving experiments for urban electric buses and pedal misapplication simulation experiments were carried out in a closed field; furthermore, a phase space reconstruction method was introduced, based on chaos theory, to map sequence data to a high-dimensional space in order to produce normal braking and pedal misapplication image datasets. Based on these findings, a modified Swin Transformer network was built. To prevent the model from overfitting when considering small sample data and to improve the generalization ability of the model, it was pre-trained using a publicly available dataset; moreover, the weights of the prior knowledge model were loaded into the model for training. The proposed model was also compared to machine learning and Convolutional Neural Networks (CNN) algorithms. This study showed that this model was able to detect normal braking and pedal misapplication behavior accurately and quickly, and the accuracy rate on the test dataset is 97.58%, which is 9.17% and 4.5% higher than the machine learning algorithm and CNN algorithm, respectively.

Molecular characterizations of genes in chloroplast genomes of the genus Arachis L. (Fabaceae) based on the codon usage divergence

Studies on the molecular characteristics of chloroplast genome are generally important for clarifying the evolutionary processes of plant species. The base composition, the effective number of codons, the relative synonymous codon usage, the codon bias index, and their correlation coefficients of a total of 41 genes in 21 chloroplast genomes of the genus Arachis were investigated to further perform the correspondence and clustering analyses, revealing significantly higher variations in genomes of wild species than those of the cultivated taxa. The codon usage patterns of all 41 genes in the genus Arachis were AT-rich, suggesting that the natural selection was the main factor affecting the evolutionary history of these genomes. Five genes (i.e., ndhC, petD, atpF, rpl14, and rps11) and five genes (i.e., atpE, psbD, psaB, ycf2, and rps12) showed higher and lower base usage divergences, respectively. This study provided novel insights into our understanding of the molecular evolution of chloroplast genomes in the genus Arachis.