Learning with Noisy Labels Incorporating Fairness and Privacy Concerns

In the era of big data, the volume of data is growing at a tremendous rate as data has been generated from multifarious sources, but without reasonable supervision. Consequently, the generated data are primarily imperfect, such as inaccurate, biased, and even invading privacy. However, modern machine learning systems heavily rely on the quality of data. Noisy labels (inaccurate data) can be easily memorized by deep neural networks and thereby leads to overfitting and poor generalization problems; biased data guide models to give unfair predictions toward certain groups; privacy-invasion data are inherently harmful to the machine learning community. To deal with noisy labels, we propose two solutions to this problem from diverse perspectives. The first one from a noise reduction perspective transforms data points with noisy class labels to data pairs with noisy similarity labels. The second one from a curriculum learning perspective designs a curriculum selecting training data based on their dynamics over the course of training to learn the clean classifier and the transition matrix simultaneously. We provide general frameworks for learning fair classifiers with noisy labels. For statistical fairness notions, we rewrite the classification risk and the fairness metric in terms of noisy data and thereby build robust classifiers. For the causality-based fairness notion, we exploit the internal causal structure of data to model the label noise and counterfactual fairness simultaneously; we propose a denoised and unbiased estimator for the classification risk with respect to the accurately labeled data by employing the noisy data with indirect supervision and then learn the optimal model under the empirical risk minimization framework

Understanding the Habitual Pattern of Concomitant Consumption of Herbs to Alleviate the Symptoms of Ulcerative Colitis by Comparative Proteome Analysis

Anchang decoction is an empirical prescription for the treatment of ulcerative colitis in China. In order to better understand its therapeutic function, large efforts have been made to identify its chemical constituents and to unravel the efficacy of its principal constituents. However, the molecular mechanism of its combinations is still unclear. Proteomics application has yielded some positive results in drug development and the identification of potential drug targets, suggesting the potential of this analytical approach to explore the action of molecular mechanisms of herbal formula by robustly addressing dynamic proteome changes. Label-free quantification and parallel reaction monitoring were used to identify differentially expressed proteins in the colon tissue of ulcerative colitis rats, fed with Anchang decoction and mesalazine, respectively. In this study, a total of 1,182 proteins were identified. From GO and KEGG analyses, the proteins of cytoskeleton and cytochrome P450 changed significantly with the occurrence of ulcerative colitis. In the meantime, antigen binding proteins and antioxidant-related proteins turned out to have drastic fluctuations with mesalazine and Anchang decoction. It has also been confirmed that KRT8, MYH11, FLNA, and LMNA are all related to the formation of ulcerative colitis based on parallel reaction monitoring analysis. The increase in FGG in the ulcerative colitis rat model is due to mesalazine, whereas that in KRT8 is due to Anchang decoction. The results from this study provide insights for the mechanism of action of Anchang decoction, which turns out to be an efficient technical pipeline for understanding worldwide medicinal herbs

Prevalence of non-alcoholic fatty liver disease and its relation to hypoadiponectinaemia in the middle-aged and elderly Chinese population

Introduction: Hypoadiponectinaemia is an important risk factor for non-alcoholic fatty liver disease (NAFLD). However, little is known about its role in the Chinese population. This study sought to assess the prevalence of NAFLD and its association with hypoadiponectinaemia in middle-aged and elderly Chinese. Material and methods: We conducted a population-based cross-sectional study in an urban Shanghai sample of 2201 participants age 50 years to 83 years (973 men, 1228 women). Hepatic ultrasonographic examination was performed for all participants. Serum adiponectin concentrations were measured by ELISA methods. Results: The prevalence of NAFLD was 19.8% (16.0% in men, 22.8% in women). Serum adiponectin levels were significantly higher in female than in male subjects (p < 0.001). Serum adiponectin levels were significantly lower in NAFLD subjects than those in control subjects (p < 0.001). The prevalence of NAFLD progressively increased with declining adiponectin levels (p(for) (trend) < 0.001). The participants in the lowest adiponectin quartile had a significantly increased risk for acquiring NAFLD (OR = 2.31, 95% CI 1.72-3.15) after adjustment for potential confounders. Conclusions: Population-based screening suggests that NAFLD is highly prevalent in middle-aged and elderly people in Shanghai, particularly among women. Serum adiponectin level is negatively associated with NAFLD independently of potential cofounders, indicating that hypoadiponectinaemia may contribute to the development of NAFLD

Concept Design of the “Guanlan” Science Mission: China’s Novel Contribution to Space Oceanography

Among the various challenges that spaceborne radar observations of the ocean face, the following two issues are probably of a higher priority: inadequate dynamic resolution, and ineffective vertical penetration. It is therefore the vision of the National Laboratory for Marine Science and Technology of China that two highly anticipated breakthroughs in the coming decade are likely to be associated with radar interferometry and ocean lidar (OL) technology, which are expected to make a substantial contribution to a submesoscale-resolving and depth-resolving observation of the ocean. As an expanded follow-up of SWOT and an oceanic counterpart of CALIPSO, the planned “Guanlan” science mission comprises a dual-frequency (Ku and Ka) interferometric altimetry (IA), and a near-nadir pointing OL. Such an unprecedented combination of sensor systems has at least three prominent advantages. (i) The dual-frequency IA ensures a wider swath and a shorter repeat cycle which leads to a significantly improved temporal and spatial resolution up to days and kilometers. (ii) The first spaceborne active OL ensures a deeper penetration depth and an all-time detection which leads to a layered characterization of the optical properties of the subsurface ocean, while also serving as a near-nadir altimeter measuring vertical velocities associated with the divergence, and convergence of geostrophic eddy motions in the mixed layer. (iii) The simultaneous functioning of the IA/OL system allows for an enhanced correction of the contamination effects of the atmosphere and the air-sea interface, which in turn considerably reduces the error budgets of the two sensors. As a result, the integrated IA/OL payload is expected to resolve the ocean variability at submeso and sub-week scales with a centimeter-level accuracy, while also partially revealing marine life systems and ecosystems with a 10-m vertical interval in the euphotic layer, moving a significant step forward toward a “transparent ocean” down to the vicinity of the thermocline, both dynamically and bio-optically

Inter-comparison of wind measurements in the atmospheric boundary layer with Aeolus and a ground-based coherent Doppler lidar network over China

After the successful launch of Aeolus which is the first spaceborne wind lidar developed by the European Space Agency (ESA) on 22 August 2018, we deployed several ground-based coherent Doppler wind lidars (CDLs) to verify the wind observations from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations over China, the Rayleigh-clear and Mie-cloudy horizontal-line-of-sight (HLOS) wind velocities from Aeolus in the atmospheric boundary layer are compared with that from CDLs

Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations

Background There are seven human-adaptation lineages of Mycobacterium tuberculosis (Mtb). Tuberculosis (TB) dissemination is strongly influenced by human movements and host genetics. The detailed lineage distribution evolution of Mtb in Zhejiang Province is unknown. We aim to determine how different sub-lineages are transmitted and distributed within China and Zhejiang Province. Methods We analysed whole-genome sequencing data for a worldwide collection of 1154 isolates and a provincial collection of 1296 isolates, constructed the best-scoring maximum likelihood phylogenetic tree. Bayesian evolutionary analysis was used to calculate the latest common ancestor of lineages 2 and 4. The antigenic diversity of human T cell epitopes was evaluated by calculating the pairwise dN/dS ratios. Results Of the Zhejiang isolates, 964 (74.38%) belonged to lineage 2 and 332 (25.62%) belonged to lineage 4. The distributions of the sub-lineages varied across the geographic regions of Zhejiang Province. L2.2 is the most ancient sub-lineage in Zhejiang, first appearing approximately 6897 years ago (95% highest posterior density interval (HDI): 6513–7298). L4.4 is the most modern sub-lineage, first appearing approximately 2217 years ago (95% HDI: 1864–2581). The dN/dS ratios showed that the epitope and non-epitope regions of lineage 2 strains were significantly (P < 0.001) more conserved than those of lineage 4. Conclusions An increase in the frequency of lineage 4 may reflect its successful transmission over the last 20 years. The recent common ancestors of the sub-lineages and their transmission routes are relevant to the entry of humans into China and Zhejiang Province. Diversity in T cell epitopes may prevent Mycobacterium tuberculosis from being recognized by the immune system