Fixed Point Iteration Algorithms for Low-rank Matrix Completion

A lot of applications can be formulated as matrix completion problems. In order to address such problems, a common assumption is that the underlying matrix is (approximately) low-rank. Under certain conditions, the recovery of low-rank matrix can be done via nuclear norm minimization, a convex program. Scalable and fast algorithms are essential as the practical matrix completion tasks always occur on a large scale. Here we study two algorithms and generalize the uni ed framework of xed point iteration algorithm. We derive the convergence results and propose a new algorithm based on the insights. Compared with the baseline algorithms, our proposed method is signi cantly more e cient without loss of precision and acceleration potentiality. ii

Study of Wind Flow Angle and Velocity on Ice Accretion of Transmission Line Composite Insulators

Ice accretion on insulators in cold regions is a serious and inevitable problem for power transmission lines, which may cause over-load and icing flashover accidents and can lead to wide power outage. In this research work, multiphase numerical simulations are carried out to investigate the effect of wind flow angle & velocity on the ice accretion of transmission line composite insulators. To verify the simulation results, lab-based icing tests are carried out in artificial climate chamber of Chongqing University. Results show that the change of wind flow angle has an obvious effect on both accreted ice shape and ice mass of insulators. When wind flow angle changes from 0° to 90° or -90°, the ice mass increases before dropping sharply. Meanwhile, ice mass accretion on insulators with wind flow angle is more sensitive to the change of wind velocity. For V-shape insulator strings, the ice mass increased 47.22% in average compared to ordinary suspension insulators. The findings of this research can provide significant engineering reference for the design of transmission line in icing prone areas

LIGHT: Joint Individual Building Extraction and Height Estimation from Satellite Images through a Unified Multitask Learning Network

Building extraction and height estimation are two important basic tasks in remote sensing image interpretation, which are widely used in urban planning, real-world 3D construction, and other fields. Most of the existing research regards the two tasks as independent studies. Therefore the height information cannot be fully used to improve the accuracy of building extraction and vice versa. In this work, we combine the individuaL buIlding extraction and heiGHt estimation through a unified multiTask learning network (LIGHT) for the first time, which simultaneously outputs a height map, bounding boxes, and a segmentation mask map of buildings. Specifically, LIGHT consists of an instance segmentation branch and a height estimation branch. In particular, so as to effectively unify multi-scale feature branches and alleviate feature spans between branches, we propose a Gated Cross Task Interaction (GCTI) module that can efficiently perform feature interaction between branches. Experiments on the DFC2023 dataset show that our LIGHT can achieve superior performance, and our GCTI module with ResNet101 as the backbone can significantly improve the performance of multitask learning by 2.8% AP50 and 6.5% delta1, respectively

Exploration of the hypoglycemic mechanism of Fuzhuan brick tea based on integrating global metabolomics and network pharmacology analysis

Introduction: Fuzhuan brick tea (FBT) is a worldwide popular beverage which has the appreciable potential in regulating glycometabolism. However, the reports on the hypoglycemic mechanism of FBT remain limited.Methods: In this study, the hypoglycemic effect of FBT was evaluated in a pharmacological experiment based on Kunming mice. Global metabolomics and network pharmacology were combined to discover the potential target metabolites and genes. In addition, the real-time quantitative polymerase chain reaction (RT-qPCR) analysis was performed for verification.Results: Seven potential target metabolites and six potential target genes were screened using the integrated approach. After RT-qPCR analysis, it was found that the mRNA expression of VEGFA, KDR, MAPK14, and PPARA showed significant differences between normal and diabetes mellitus mice, with a retracement after FBT treatment.Conclusion: These results indicated that the hypoglycemic effect of FBT was associated with its anti-inflammatory activities and regulation of lipid metabolism disorders. The exploration of the hypoglycemic mechanism of FBT would be meaningful for its further application and development

Population-Based Sexual Behavior Surveys in China: Liuzhou Compared with Other Prefectural Cities

Sexual behaviors in China are rapidly changing; simultaneously, STI/HIV prevalence is increasing in the general population. To investigate these major shifts, we examined sexual behaviors and self-reported sexually transmitted infections (STI) in one prefectural city in southern China, Liuzhou, and compared it to other prefectural cities throughout China. We used adults age 18-39 from two sets of population-based surveys that paralleled each other in both content and method. The first set was the Liuzhou survey conducted in 2008 (n=398). The second set consisted of two national surveys collected in 2006 and 2010 (n=2186). Liuzhou respondents reported more active social and sexual behaviors than their national counterparts, including more socializing, dancing, drinking excessively, sexual activity among never married men and women, purchasing commercial sex among men, one-night stands among men, multiple sexual partnerships and self-reported STI among both men and women. Women in Liuzhou reported greater sexual risk behavior than their national counterparts, although overall they reported less than their male counterparts; they were also more likely to have had an abortion than women in other prefectural cities. Our findings provide a comprehensive overview of the sexual context of Liuzhou among the general population, which may help explain the greater STI/HIV prevalence in Liuzhou

Multi-Threshold Recurrence Rate Plot: A Novel Methodology for EEG Analysis in Alzheimer’s Disease and Frontotemporal Dementia

This study introduces Multi-Threshold Recurrence Rate Plots (MTRRP), a novel methodology for analyzing dynamic patterns in complex systems, such as those influenced by neurodegenerative diseases in brain activity. MTRRP characterizes how recurrence rates evolve with increasing recurrence thresholds. A key innovation of our approach, Recurrence Complexity, captures structural complexity by integrating local randomness and global structural features through the product of Recurrence Rate Gradient and Recurrence Hurst, both derived from MTRRP. We applied this technique to resting-state EEG data from patients diagnosed with Alzheimer’s Disease (AD), Frontotemporal Dementia (FTD), and age-matched healthy controls. The results revealed significantly higher recurrence complexity in the occipital areas of AD and FTD patients, particularly pronounced in the Alpha and Beta frequency bands. Furthermore, EEG features derived from MTRRP were evaluated using a Support Vector Machine with leave-one-out cross-validation, achieving a classification accuracy of 87.7%. These findings not only underscore the utility of MTRRP in detecting distinct neurophysiological patterns associated with neurodegenerative diseases but also highlight its broader applicability in time series analysis, providing a substantial tool for advancing medical diagnostics and research