Learning with Noisy Labels Using Collaborative Sample Selection and Contrastive Semi-Supervised Learning

Learning with noisy labels (LNL) has been extensively studied, with existing approaches typically following a framework that alternates between clean sample selection and semi-supervised learning (SSL). However, this approach has a limitation: the clean set selected by the Deep Neural Network (DNN) classifier, trained through self-training, inevitably contains noisy samples. This mixture of clean and noisy samples leads to misguidance in DNN training during SSL, resulting in impaired generalization performance due to confirmation bias caused by error accumulation in sample selection. To address this issue, we propose a method called Collaborative Sample Selection (CSS), which leverages the large-scale pre-trained model CLIP. CSS aims to remove the mixed noisy samples from the identified clean set. We achieve this by training a 2-Dimensional Gaussian Mixture Model (2D-GMM) that combines the probabilities from CLIP with the predictions from the DNN classifier. To further enhance the adaptation of CLIP to LNL, we introduce a co-training mechanism with a contrastive loss in semi-supervised learning. This allows us to jointly train the prompt of CLIP and the DNN classifier, resulting in improved feature representation, boosted classification performance of DNNs, and reciprocal benefits to our Collaborative Sample Selection. By incorporating auxiliary information from CLIP and utilizing prompt fine-tuning, we effectively eliminate noisy samples from the clean set and mitigate confirmation bias during training. Experimental results on multiple benchmark datasets demonstrate the effectiveness of our proposed method in comparison with the state-of-the-art approaches

Causal effects of specific gut microbiota on musculoskeletal diseases: a bidirectional two-sample Mendelian randomization study

BackgroundRecent observational studies and clinical trials demonstrated an association between gut microbiota and musculoskeletal (MSK) diseases. Nonetheless, whether the gut microbiota composition has a causal effect on the risk of MSK diseases remains unclear.MethodsBased on large-scale genome-wide association studies (GWAS), we performed a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between gut microbiota and six MSK diseases, namely osteoporosis (OP), fracture, sarcopenia, low back pain (LBP), rheumatoid arthritis (RA), and ankylosing spondylitis (AS). Instrumental variables for 211 gut microbiota taxa were obtained from the largest available GWAS meta-analysis (n = 18,340) conducted by the MiBioGen consortium. And the summary-level data for six MSK diseases were derived from published GWAS. The inverse-variance weighted (IVW) method was conducted as a primary analysis to estimate the causal effect, and the robustness of the results was tested via sensitivity analyses using multiple methods. The Bonferroni-corrected test was used to determine the strength of the causal relationship between gut microbiota and various MSK diseases. Finally, a reverse MR analysis was applied to evaluate reverse causality.ResultsAccording to the IVW method, we found 57 suggestive causal relationships and 3 significant causal relationships between gut microbiota and MSK diseases. Among them, Genus Bifidobacterium (β: 0.035, 95% CI: 0.013–0.058, p = 0.0002) was associated with increased left handgrip strength, Genus Oxalobacter (OR: 1.151, 95% CI: 1.065–1.245, p = 0.0003) was correlated with an increased risk of LBP, and Family Oxalobacteraceae (OR: 0.792, 95% CI: 0.698–0.899, p = 0.0003) was linked with a decreased risk of RA. Subsequently, sensitivity analyses revealed no heterogeneity, directional pleiotropy, or outliers for the causal effect of specific gut microbiota on MSK diseases (p > 0.05). Reverse MR analysis showed fracture may result in a higher abundance of Family Bacteroidales (p = 0.030) and sarcopenia may lead to a higher abundance of Genus Sellimonas (p = 0.032).ConclusionGenetic evidence suggested a causal relationship between specific bacteria taxa and six MSK diseases, which highlights the association of the “gut-bone/muscle” axis. Further exploration of the potential microbiota-related mechanisms of bone and muscle metabolism might provide novel insights into the prevention and treatment of MSK diseases

Realization of Self-Rotating Droplets Based on Liquid Metal

Owing to their fascinating characteristics, liquid metals (LMs) have attracted increasing attention from the scientific community, and are a potential material for various applications. A novel phenomenon is reported in which an acid droplet spontaneously rotates on the surface of an LM. The experimental results show that this phenomenon originates from the collective motion of bubbles generated by the chemical reactions between the droplet and the LM. The angular velocity of the droplet rotation is on the order of 10(1) rad s(-1), which is much higher than that driven by other mechanisms. Under different conditions, the period of the droplet differs, and it increases with the pH and radius of the acid droplet. The theoretical results indicate the dominant factors and the characterized angular velocity, which agree well with the experimental data. This phenomenon demonstrate that the general particles can also induce special spatial-temporal patterns, and opens up a new field for the application of LMs

Spontaneous Motion and Rotation of Acid Droplets on the Surface of a Liquid Metal

Self-propulsion of droplets is of great significance in many fields. The spontaneous horizontal motion and self-jumping of droplets have been well realized in various ways. However, there is still a lack of an effective method to enable a droplet to rotate spontaneously and steadily. In this paper, by employing an acid droplet and a liquid metal, the spontaneous and steady rotation of droplets is achieved. For an acid droplet, it may spontaneously move when it is deposited on the surface of the liquid metal. By adjusting experimental parameters to the proper range, the self-rotation of droplet happens. This phenomenon originates from the fluctuation of the droplet boundary and the collective movement of bubbles that are generated by the chemical reactions between the acid droplet and liquid metal. This rotation has a simpler implementation method and more steady rotation state. Its angular velocity is much higher than that driven by other mechanisms. Moreover, the movements of acid droplets on the liquid metal are classified according to experimental conditions. The internal flow fields, the movements and distribution of bubbles, and the fluctuation of the droplet boundary are also explored and discussed. The theoretical model describing the rotational droplet is given. Our work may deepen the understanding of the physical system transition affected by chemical reactions and provide a new way for the design of potential applications, e.g., micro- and nanodevices

Ultrafine Mn3O4 nanowires synthesized by colloidal method as electrode materials for supercapacitors with a wide voltage range

Manganese oxide is considered an ideal pseudo-capacitive electrode material for supercapacitors due to its low cost, environmental friendliness and large theoretical capacity. However, it is difficult to obtain manganese electrodes with a high specific capacitance and a large voltage range. In this study, ultrafine Mn3O4 nanowires with an average diameter of 4.0 nm were synthesized using a colloidal method. They have a large specific surface area of 175.1 m2 g−1, and can provide numerous active sites to enhance their specific capacitances. They also show a large pore volume of 0.7960 cm3 g−1, which can provide essential channels for ion transport during charging and discharging processes. The supercapacitor electrode made of these ultrafine Mn3O4 nanowires exhibits a predominant surface capacitive behavior during charge/discharge processes, and achieves a large specific capacitance of 433.1 F g−1 at a current density of 0.5 A g−1 with a very wide voltage range from -0.5 to 1.1 V in 1 M Na2SO4 electrolyte. An asymmetric supercapacitor (ASC) was assembled using a cathode electrode made of these ultrafine Mn3O4 nanowires and an active carbon (AC) anode electrode, and a high energy density of 26.68 Wh kg−1 at a power density of 442 W kg−1 was achieved. The ASC showed a good cycling stability, and its capacitance value was still maintained at 75.8% after 64,000 charge/discharge cycles

Hierarchically nanostructured Zn0.76C0.24S@Co(OH)2 for high-performance hybrid supercapacitor

It is a great challenge to achieve both high specific capacity and high energy density of supercapacitors by designing and constructing hybrid electrode materials through a simple but effective process. In this paper, we proposed a hierarchically nanostructured hybrid material combining Zn0.76Co0.24S (ZCS) nanoparticles and Co(OH)2 (CH) nanosheets using a two-step hydrothermal synthesis strategy. Synergistic effects between ZCS nanoparticles and CH nanosheets result in efficient ion transports during the charge-discharge process, thus achieving a good electrochemical performance of the supercapacitor. The synthesized ZCS@CH hybrid exhibits a high specific capacity of 1152.0 C g-1 at a current density of 0.5 A g-1 in 2 M KOH electrolyte. Its capacity retention rate is maintained at ∼ 70.0% when the current density is changed from 1 A g-1 to 10 A g-1. A hybrid supercapacitor (HSC) assembled from ZCS@CH as the cathode and active carbon (AC) as the anode displays a capacitance of 155.7 F g-1 at 0.5 A g-1, with a remarkable cycling stability of 91.3% after 12,000cycles. Meanwhile, this HSC shows a high energy density of 62.5 Wh kg-1 at a power density of 425.0 W kg-1, proving that the developed ZCS@CH is a promising electrode material for energy storage applications

BESS frequency regulation strategy on the constraints of planned energy arbitrage using chance-constrained programming

Battery energy storage systems (BESS) are regarded as a multi-functional power system participator, participating in the energy arbitrage strategy (EAS), the frequency regulation strategy (FRS) and so on. However, the existing BESS mainly make profit from the EAS instead of the FRS in many countries such as China. Because there is no appropriate control strategy for BESS, when the developing ancillary services market cannot price the contribution of BESS in FRS. Meanwhile, BESS do have redundant power and capacity, if only the EAS is applied. Therefore, it is significant that BESS are involved in the FRS, that the EAS has the priority in BESS utilization. In this paper, a frequency regulation strategy for the user-side BESS is proposed, on the constraints of the planned energy arbitrage. Specifically, the chance-constrained programming is applied to solve the randomness of frequency regulation requirement, ensuring the BESS profit from the EAS. Also, the exiting BESS are fully used with extra profit from FRS. At last, the promising results prove the advantages of the proposed FRS

Data_Sheet_2_Causal effects of specific gut microbiota on musculoskeletal diseases: a bidirectional two-sample Mendelian randomization study.xlsx

BackgroundRecent observational studies and clinical trials demonstrated an association between gut microbiota and musculoskeletal (MSK) diseases. Nonetheless, whether the gut microbiota composition has a causal effect on the risk of MSK diseases remains unclear.MethodsBased on large-scale genome-wide association studies (GWAS), we performed a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between gut microbiota and six MSK diseases, namely osteoporosis (OP), fracture, sarcopenia, low back pain (LBP), rheumatoid arthritis (RA), and ankylosing spondylitis (AS). Instrumental variables for 211 gut microbiota taxa were obtained from the largest available GWAS meta-analysis (n = 18,340) conducted by the MiBioGen consortium. And the summary-level data for six MSK diseases were derived from published GWAS. The inverse-variance weighted (IVW) method was conducted as a primary analysis to estimate the causal effect, and the robustness of the results was tested via sensitivity analyses using multiple methods. The Bonferroni-corrected test was used to determine the strength of the causal relationship between gut microbiota and various MSK diseases. Finally, a reverse MR analysis was applied to evaluate reverse causality.ResultsAccording to the IVW method, we found 57 suggestive causal relationships and 3 significant causal relationships between gut microbiota and MSK diseases. Among them, Genus Bifidobacterium (β: 0.035, 95% CI: 0.013–0.058, p = 0.0002) was associated with increased left handgrip strength, Genus Oxalobacter (OR: 1.151, 95% CI: 1.065–1.245, p = 0.0003) was correlated with an increased risk of LBP, and Family Oxalobacteraceae (OR: 0.792, 95% CI: 0.698–0.899, p = 0.0003) was linked with a decreased risk of RA. Subsequently, sensitivity analyses revealed no heterogeneity, directional pleiotropy, or outliers for the causal effect of specific gut microbiota on MSK diseases (p > 0.05). Reverse MR analysis showed fracture may result in a higher abundance of Family Bacteroidales (p = 0.030) and sarcopenia may lead to a higher abundance of Genus Sellimonas (p = 0.032).ConclusionGenetic evidence suggested a causal relationship between specific bacteria taxa and six MSK diseases, which highlights the association of the “gut-bone/muscle” axis. Further exploration of the potential microbiota-related mechanisms of bone and muscle metabolism might provide novel insights into the prevention and treatment of MSK diseases.</p