An optimization approach for localization refinement of candidate traffic signs

We propose a localisation refinement approach for candidate traffic signs. Previous traffic sign localisation approaches which place a bounding rectangle around the sign do not always give a compact bounding box, making the subsequent classification task more difficult. We formulate localisation as a segmentation problem, and incorporate prior knowledge concerning color and shape of traffic signs. To evaluate the effectiveness of our approach, we use it as an intermediate step between a standard traffic sign localizer and a classifier. Our experiments use the well-known GTSDB benchmark as well as our new CTSDB (Chinese Traffic Sign Detection Benchmark). This newly created benchmark is publicly available, and goes beyond previous benchmark datasets: it has over 5,000 highresolution images containing more than 14,000 traffic signs taken in realistic driving conditions. Experimental results show that our localization approach significantly improves bounding boxes when compared to a standard localizer, thereby allowing a standard traffic sign classifier to generate more accurate classification results

Federated Learning Robust to Byzantine Attacks: Achieving Zero Optimality Gap

In this paper, we propose a robust aggregation method for federated learning (FL) that can effectively tackle malicious Byzantine attacks. At each user, model parameter is firstly updated by multiple steps, which is adjustable over iterations, and then pushed to the aggregation center directly. This decreases the number of interactions between the aggregation center and users, allows each user to set training parameter in a flexible way, and reduces computation burden compared with existing works that need to combine multiple historical model parameters. At the aggregation center, geometric median is leveraged to combine the received model parameters from each user. Rigorous proof shows that zero optimality gap is achieved by our proposed method with linear convergence, as long as the fraction of Byzantine attackers is below half. Numerical results verify the effectiveness of our proposed method

Versatile interactions at interfaces for SPH-based simulations

The realistic capture of various interactions at interfaces is a challenging problem for SPH-based simulation. Previous works have mainly considered a single type of interaction, while real-world phenomena typically exhibit multiple interactions at different interfaces. For instance, when cracking an egg, there are simultaneous interactions between air, egg white, egg yolk, and the shell. To conveniently handle all interactions simultaneously in a single simulation, a versatile approach is critical. In this paper, we present a new approach to the surface tension model based on pairwise interaction forces; its basis is to use a larger number of neighboring particles. Our model is stable, conserves momentum, and furthermore, prevents the particle clustering problem which commonly occurs at the free surface. It can be applied to simultaneous interactions at multiple interfaces (e.g. fluid-solid and fluid-fluid). Our method is versatile, physically plausible and easy-to-implement. We also consider the close connection between droplets and bubbles, and show how to animate bubbles in air as droplets, with the help of a new surface particle detection method. Examples are provided to demonstrate the capabilities and effectiveness of our approach

Circulating microRNA-92a and microRNA-21 as novel minimally invasive biomarkers for primary breast cancer

PURPOSE: MicroRNAs (miRNAs) play an essential role in breast malignant tumor development and progression. The development of clinically validated biomarkers for primary breast cancer (BC) has remained an insurmountable task despite other advances in the field of cancer molecular biology. The objective of this study is to investigate the differential expression of miRNAs and the potential of circulating microRNAs as novel primary breast cancer biomarkers. METHODS: Our analyses were performed on 48 tissue and 100 serum samples of patients with primary BC and a set of 20 control samples of healthy women, respectively. The relative expression of ten candidate miRNAs (miR-106b, miR-125b, miR-17, miR-185, miR-21, miR-558, miR-625, miR-665, miR-92a, and miR-93) from the results of four bioinformatics approaches and literature curation was measured by real-time quantitative reverse transcription PCR (qRT-PCR). RESULTS: The level of miR-92a was significantly lower, while miR-21 was higher, as previous reports, in tissue and serum samples of BC than that of healthy controls (p < 0.001). Logistic regression and receiver operating characteristic curve analyses revealed the significant and independent value (p < 0.001) of the miR-92a and miR-21 expression quantification in serums. Moreover, the comparison with the clinicopathologic data of the BC patients showed that decreased levels of miR-92a and increased levels of miR-21 were associated with tumor size and a positive lymph node status (p < 0.001). CONCLUSIONS: These findings suggest that many miRNAs expressions are altered in BC, whose expression profiling may provide a useful clue for the pathophysiological research. Circulating miR-92a has potential use as novel breast cancer biomarker, which is comparable to miR-21

Association of sleep complaints with all-cause and heart disease mortality among US adults

IntroductionCompared with sleep disorders, no consensus has been reached on whether a subjective complaint of having trouble sleeping is associated with increased all-cause and heart disease mortality risk. Previous studies displayed considerable heterogeneity in population disease characteristics and duration of follow-up. Therefore, the aims of this study were to examine the relationship between sleep complaints and all-cause and heart disease mortality and whether the associations were influenced by follow-up time and population disease characteristics. In addition, we aimed to figure out the influence of the joint effects of sleep duration and sleep complaints on mortality risk.MethodsThe present study utilized data from five cycles of the National Health and Nutrition Examination Survey (NHANES) (2005~2014) linked with the most updated 2019 National Death Index (NDI). Sleep complaints were determined by answers to “Have you ever told a doctor or other health professional that you have trouble sleeping?” and “Have you ever been told by a doctor or other health professional that you have a sleep disorder?”. Those who answered ‘Yes' to either of the aforementioned two questions were considered as having sleep complaints.ResultsA total of 27,952 adult participants were included. During a median follow-up of 9.25 years (interquartile range, 6.75–11.75 years), 3,948 deaths occurred and 984 were attributable to heart disease. A multivariable-adjusted Cox model revealed that sleep complaints were significantly associated with all-cause mortality risk (HR, 1.17; 95% CI, 1.07–1.28). Subgroup analysis revealed that sleep complaints were associated with all-cause (HR, 1.17; 95% CI, 1.05–1.32) and heart disease (HR, 1.24; 95% CI, 1.01–1.53) mortality among the subgroup with cardiovascular disease (CVD) or cancer. In addition, sleep complaints were more strongly associated with short-term mortality than long-term mortality. The joint analysis of sleep duration and sleep complaints showed that sleep complaints mainly increased the mortality risk in those with short (&lt; 6 h/day, sleep complaints HR, 1.40; 95% CI, 1.15–1.69) or recommended (6–8 h/day, sleep complaints HR, 1.15; 95% CI, 1.01–1.31) sleep duration group.DiscussionIn conclusion, sleep complaints were associated with increased mortality risk, indicating a potential public benefit of monitoring and managing sleep complaints in addition to sleep disorders. Of note, persons with a history of CVD or cancer may represent a potentially high-risk group that should be targeted with a more aggressive intervention of sleep problems to prevent premature all-cause and heart disease death