Optical switch with an ultralow DC drift based on thin-film lithium tantalate.

We present an electro-optic (EO) switch with ultralow DC drift on a thin-film lithium tantalate (TFLT) platform, even with SiO2 cladding and without post-annealing processes. The flat Vπ and EO responses have been measured across various driving frequencies, input optical powers, and temperatures. Stable optical switching is achievable in the low-frequency range. The experiment also demonstrated superior long-term stability (up to 2 h) compared to thin-film lithium niobate optical switches under similar on-chip optical power conditions (around -8 dBm).

Research on a Three-Way Decision-Making Approach, Based on Non-Additive Measurement and Prospect Theory, and Its Application in Aviation Equipment Risk Analysis.

Due to the information non-independence of attributes, combined with a complex and changeable environment, the analysis of risks faces great difficulties. In view of this problem, this paper proposes a new three-way decision-making (3WD) method, combined with prospect theory and a non-additive measure, to cope with multi-source and incomplete risk information systems. Prospect theory improves the loss function of the original 3WD model, and the combination of non-additive measurement and probability measurement provides a new perspective to understand the meaning of decision-making, which could measure the relative degree by considering expert knowledge and objective data. The theoretical basis and framework of this model are illustrated, and this model is applied to a real in-service aviation equipment structures risk evaluation problem involving multiple incomplete risk information sources. When the simulation analysis is carried out, the results show that the availability of this method is verified. This method can also evaluate and rank key risk factors in equipment structures, which provides a reliable basis for decisions in aviation safety management.

DCENet-based low-light image enhancement improved by spiking encoding and convLSTM.

The direct utilization of low-light images hinders downstream visual tasks. Traditional low-light image enhancement (LLIE) methods, such as Retinex-based networks, require image pairs. A spiking-coding methodology called intensity-to-latency has been used to gradually acquire the structural characteristics of an image. convLSTM has been used to connect the features. This study introduces a simplified DCENet to achieve unsupervised LLIE as well as the spiking coding mode of a spiking neural network. It also applies the comprehensive coding features of convLSTM to improve the subjective and objective effects of LLIE. In the ablation experiment for the proposed structure, the convLSTM structure was replaced by a convolutional neural network, and the classical CBAM attention was introduced for comparison. Five objective evaluation metrics were compared with nine LLIE methods that currently exhibit strong comprehensive performance, with PSNR, SSIM, MSE, UQI, and VIFP exceeding the second place at 4.4% (0.8%), 3.9% (17.2%), 0% (15%), 0.1% (0.2%), and 4.3% (0.9%) on the LOL and SCIE datasets. Further experiments of the user study in five non-reference datasets were conducted to subjectively evaluate the effects depicted in the images. These experiments verified the remarkable performance of the proposed method.

Relationship between polymorphisms in homologous recombination repair genes RAD51 G172T、XRCC2 & XRCC3 and risk of breast cancer: A meta-analysis.

Background: Genetic variability in DNA double-strand break repair genes such as RAD51 gene and its paralogs XRCC2、XRCC3 may contribute to the occurrence and progression of breast cancer. To obtain a complete evaluation of the above association, we performed a meta-analysis of published studies. Methods: Electronic databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, were comprehensively searched from inception to September 2022. The Newcastle-Ottawa Scale (NOS) checklist was used to assess all included non-randomized studies. Odds ratios (OR) with 95% confidence intervals (CI) were calculated by STATA 16.0 to assess the strength of the association between single nucleotide polymorphisms (SNPs) in these genes and breast cancer risk. Subsequently, the heterogeneity between studies, sensitivity, and publication bias were performed. We downloaded data from The Cancer Genome Atlas (TCGA) and used univariate and multivariate Cox proportional hazard regression (CPH) models to validate the prognostic value of these related genes in the R software. Results: The combined results showed that there was a significant correlation between the G172T polymorphism and the susceptibility to breast cancer in the homozygote model (OR= 1.841, 95% CI=1.06-3.21, P=0.03). Furthermore, ethnic analysis showed that SNP was associated with the risk of breast cancer in Arab populations in homozygous models (OR=3.52, 95% CI=1.13-11.0, P= 0.003). For the XRCC2 R188H polymorphism, no significant association was observed. Regarding polymorphism in XRCC3 T241M, a significantly increased cancer risk was only observed in the allelic genetic model (OR=1.05, 95% CI= 1.00-1.11, P=0.04). Conclusions: In conclusion, this meta-analysis suggests that Rad51 G172T polymorphism is likely associated with an increased risk of breast cancer, significantly in the Arab population. The relationship between the XRCC2 R188H polymorphism and breast cancer was not obvious. And T241M in XRCC3 may be associated with breast cancer risk, especially in the Asian population.