Teacher-Students Knowledge Distillation for Siamese Trackers

In recent years, Siamese network based trackers have significantly advanced the state-of-the-art in real-time tracking. However, state-of-the-art Siamese trackers suffer from high memory cost which restricts their applicability in mobile applications having strict constraints on memory budget. To address this issue, we propose a novel distilled Siamese tracking framework to learn small, fast yet accurate trackers (students), which capture critical knowledge from large Siamese trackers (teachers) by a teacher-students knowledge distillation model. This model is intuitively inspired by a one-teacher vs multi-students learning mechanism, which is the most usual teaching method in the school. In particular, it contains a single teacher-student distillation model and a student-student knowledge sharing mechanism. The first one is designed by a tracking-specific distillation strategy to transfer knowledge from the teacher to students. The later is utilized for mutual learning between students to enable an in-depth knowledge understanding. To the best of our knowledge, we are the first to investigate knowledge distillation for Siamese trackers and propose a distilled Siamese tracking framework. We demonstrate the generality and effectiveness of our framework by conducting a theoretical analysis and extensive empirical evaluations on several popular Siamese trackers. The results on five tracking benchmarks clearly show that the proposed distilled trackers achieve compression rates up to 18$\times$ and frame-rates of $265$ FPS with speedups of 3$\times$, while obtaining similar or even slightly improved tracking accuracy

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

The Effects of Lead Exposure on Serum Uric Acid and Hyperuricemia in Chinese Adults: A Cross-Sectional Study

The aim of this study was to assess the correlation between blood lead levels and both serum uric acid and hyperuricemia in adult residents living within an area of China with lead pollution.  We conducted a cross-sectional analysis of 2120 subjects (1180 of whom were male) between the ages of 20 and 75 years who had undergone health examinations at the Centers for Disease Control and Prevention (CDC) in a lead-polluted area of China between June 2013 and September 2014. Blood lead was positively correlated with serum uric acid in both males (r = 0.095, p = 0.001) and females (r = 0.134, p < 0.001). Multivariate linear regression analysis demonstrated that for males, blood lead (p = 0.006), age (p = 0.001), current smoking (p = 0.012), education (p = 0.001), triglycerides (TG) (p < 0.001), and serum creatinine (p < 0.001) were independently associated with serum uric acid. For females, blood lead (p < 0.001), body mass index (BMI) (p = 0.009), and TG (p < 0.001) were independently associated with serum uric acid. After multiple adjustments, blood lead was significantly associated with a higher prevalence of hyperuricemia when female subjects were categorized into quartiles (for the highest quartile vs. the lowest quartile, odds ratio (OR) = 2.190; 95% confidence interval (CI): 1.106–4.338; p = 0.025); however, no such association was observed for male subjects. Continuous lead exposure has an independent impact on serum uric acid for both males and females, although this impact is more pronounced for females than for males. Lead exposure is significantly associated with hyperuricemia for females but not for males

Do Future Limitation Perspective in Cancer Patients Predict Fear of Cancer Recurrence, Mental Distress, and the Ventromedial Prefrontal Cortex Activity?

Life-threatening diseases (e.g., cancer) affect people’s future time perspective (FTP) and affect their mental health. When one’s lifetime is perceived as running out, the individual possesses a future limitation perspective (FLP), which is one of factors in FTP. In this study, we explored the structural relationship between FLP, fear of cancer recurrence (FCR), mental health status (MHS), and brain activity in patients with cancer. Cancer patients were divided into two groups using the FTP scale and Feelings About Life Scale: a strong FLP group (S-FLP) and a weak FLP group (W-FLP). For these groups, we measured cancer patients’ MHS using the Symptom Checklist (SCL-90) and FCR using the Cancer Acceptance Scale; brain activity was measured using resting-state functional magnetic resonance imaging (rs-fMRI). Behavioral results showed that the S-FLP group had higher mental symptoms and FCR scores than did the W-FLP group. Neuroimaging results revealed that spontaneous brain activity in the ventromedial prefrontal cortex (vmPFC) was stronger in the W-FLP group than in the S-FLP group. Moreover, brain activity in the vmPFC negatively correlated with FLP, FCR, and SCL-90 scores only in the S-FLP group, and the model constructed further indicated that FCR and SCL-90 scores fully mediated the relationship between FLP and vmPFC activities. These findings suggested that a strong FLP might lead to mental disorders and greater FCR, which might change the spontaneous activity of the vmPFC in cancer patients

Proceedings of the 9th AIMS International Conference (Orlando, FL, USA), DCDS Supplement 2013

Topics: Analysis, applied analysis, differential equations and dynamical systems, in the broadest sense. Applications to real-world problems, including chemical, economical, engineering, physical, environmental, and life sciences, in the forms of modeling and computations