Channel-Wise Contrastive Learning for Learning with Noisy Labels

In real-world datasets, noisy labels are pervasive. The challenge of learning with noisy labels (LNL) is to train a classifier that discerns the actual classes from given instances. For this, the model must identify features indicative of the authentic labels. While research indicates that genuine label information is embedded in the learned features of even inaccurately labeled data, it's often intertwined with noise, complicating its direct application. Addressing this, we introduce channel-wise contrastive learning (CWCL). This method distinguishes authentic label information from noise by undertaking contrastive learning across diverse channels. Unlike conventional instance-wise contrastive learning (IWCL), CWCL tends to yield more nuanced and resilient features aligned with the authentic labels. Our strategy is twofold: firstly, using CWCL to extract pertinent features to identify cleanly labeled samples, and secondly, progressively fine-tuning using these samples. Evaluations on several benchmark datasets validate our method's superiority over existing approaches

Broken Symmetry in Ideal Chern Bands

Recent observations of the fractional anomalous quantum Hall effect in moir\'e materials have reignited the interest in fractional Chern insulators (FCIs). The chiral limit in which analytic Landau level-like single-particle states form an "ideal" Chern band and local interactions lead to Laughlin-like FCIs at $1/3$ filling, has been very useful for understanding these systems by relating them to the lowest Landau level. We show, however, that, even in the idealized chiral limit, a fluctuating quantum geometry is associated with strongly broken symmetries and a phenomenology very different from that of Landau levels. In particular, particle-hole symmetry is strongly violated and e.g. at $2/3$ filling an emergent interaction driven Fermi liquid state with no Landau level counterpart is energetically favoured. In fact, even the exact Laughlin-like zero modes at $1/3$ filling have a non-uniform density tracking the underlying quantum geometry. Moreover, by switching to a Coulomb interaction, the ideal Chern band features charge density wave states with no lowest Landau level counterpart.Comment: 5 pages + 4 figures, comments are welcome

RNA-binding protein with serine-rich domain 1 regulates microsatellite instability of uterine corpus endometrial adenocarcinoma

OBJECTIVE: To determine the role of RNA-binding protein with serine-rich domain 1 (RNPS1) in uterine corpus endometrial carcinoma (UCEC), the role of RNPS1 knockdown in UCEC development in vitro and in vivo, and the relationship between RNPS1 and mismatch repair (MMR) in UCEC. METHODS: We predicted the potential function of RNPS1 using bioinformatics systems. The expression of RNPS1 in tissues and cell lines was analyzed by western blotting and immunohistochemistry. The expression of RNPS1 in MMR was assessed using bioinformatics and western blotting. The proliferation and apoptosis of UCEC cells were assessed under RNPS1 knockdown conditions, and RNPS1 regulation in MMR was detected by suppressing Notch signaling. Associations between RNPS1 and gene mutations in UCEC and prognosis were analyzed. RESULTS: The RNPS1 level was higher in UCEC tumors than in normal tissues and tumors or RL952 cells. Prognostic outcomes were worse when UCEC showed abundant RNPS1 expression. Lentiviral RNPS1 knockdown weakened tumor cell proliferation and suppressed biomarker expression, reduced the tumor volume, promoted apoptosis in vitro and in vivo, and inhibited UCEC development. Increased MutS homolog 2 (MSH2) and MutS homolog 6 (MSH6) levels in MMR after RNPS1 knockdown were reversed by inhibiting Notch signaling. Furthermore, RNPS1 was associated with mutations in NAA11, C2orf57, NUPR1, and other genes involved in UCEC prognosis. CONCLUSION: RNPS1 may regulate the expression levels of MSH2 and MSH6 in MMR, enhancing the proliferation, development, and prognosis of UCEC through a Notch signaling pathway in UCEC. Our study offers a new method and strategy for delaying UCEC development through modulating MMR

Analyzing the Distribution and Trends of Research in Double Top-University Construction in China: A Knowledge Mapping Analysis of CSSCI Literature

This research study, titled "Analysis of Double Top-University Construction in Domestic Academia: A CSSCI Literature Review (2016-2019) Using CiteSpace," provides an analysis of relevant literature on Double Top-University construction in China. The study utilizes the CiteSpace visual tool to examine the distribution characteristics of Double Top-University Construction in China. It is found that The authors, institutions, journals, and focus themes related to Double Top-University construction were remain the key component of research in recent years. Challenges and potential problems exist in the development of China's "double first class" initiative, necessitating greater scholarly attention. Specifically, efforts are required to strengthen the connection between academic research and policy implementation, conduct further research on international experiences and emerging issues, and improve interdisciplinary collaboration among related fields. Given the interdisciplinary nature and complexity of this initiative, effective coordination and integration across disciplines are essential to meet long-term strategic objectives. The findings of the analysis provide valuable insights that can guide and enrich future investigations towards the construction of Double Top-Universities

Soundscape Evaluation Outside a Taoist Temple: A Case Study of Laojundong Temple in Chongqing, China

The unique architectural form and religious background of Taoist buildings can lead to a special acoustic environment, but there is a lack of research on the soundscape evaluation of Taoist buildings. Laojundong Taoist Temple was selected as the research site. The psychological and physiological responses of Taoist priests and ordinary people, and strategies for soundscape renovation were investigated by conducting field measurements, interviews, soundwalks, and audio–visual experiments. There was significant negative linear regression between the LAeq,5min and soundscape comfort (p < 0.01). The visual landscape comfort of ordinary people was notably correlated with landscape diversity (p < 0.01), whereas their soundscape comfort was markedly correlated with the degree of natural soundscape and audio–visual harmony (p < 0.01). The soundscape evaluation by Taoist priests was affected by their belief, activity types, social factors, and spatial positions. With the increasing proportion of the natural elements in the visual landscape in the temple, the acoustic comfort of Taoist priests and ordinary people significantly increased with the addition of bird sounds (p < 0.01). However, with the increasing proportion of Taoist scenes, Taoist music only significantly improved the acoustic comfort and heart rate of ordinary people (p < 0.01)

Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels

In recent years, research on learning with noisy labels has focused on devising novel algorithms that can achieve robustness to noisy training labels while generalizing to clean data. These algorithms often incorporate sophisticated techniques, such as noise modeling, label correction, and co-training. In this study, we demonstrate that a simple baseline using cross-entropy loss, combined with widely used regularization strategies like learning rate decay, model weights average, and data augmentations, can outperform state-of-the-art methods. Our findings suggest that employing a combination of regularization strategies can be more effective than intricate algorithms in tackling the challenges of learning with noisy labels. While some of these regularization strategies have been utilized in previous noisy label learning research, their full potential has not been thoroughly explored. Our results encourage a reevaluation of benchmarks for learning with noisy labels and prompt reconsideration of the role of specialized learning algorithms designed for training with noisy labels

The HeII Lyman alpha forest and the thermal state of the IGM

Recent analyses of the intergalactic UV background by means of the HeII Lyman alpha forest assume that HeII and HI absorption features have the same line widths. We omit this assumption to investigate possible effects of thermal line broadening on the inferred HeII/HI ratio eta and to explore the potential of intergalactic HeII observations to constrain the thermal state of the IGM. Deriving a simple relation between the column density and the temperature of an absorber we develop a procedure to fit the parameters of a power law temperature-density relation and eta simultaneously. In an alternative approach the temperature of an absorber, eta, and the redshift scale of eta variations are estimated simultaneously. Tests with artificial data show that well-constrained results can be obtained only if the signal-to-noise ratio in the HeII forest is S/N > 20. Thus, it is impossible to give an estimate of the temperature-density relation with the HeII data available at present (S/N ~5). However, we find that only 45% of the lines in our sample favor turbulent line widths. Furthermore, the inferred eta values are on average about 0.05 dex larger if a thermal component is taken into account, and their distribution is 46% narrower in comparison to a purely turbulent fit. Therefore, variations of eta on a 10% level may be related to the presence of thermal line broadening. The apparent correlation between the strength of the HI absorption and the eta value, which has been found in former studies, essentially disappears if thermal broadening is taken into account. In the redshift range 2.58 < z < 2.74 towards the quasars HE2347-4342 and HS1700+6416 we obtain eta ~ 100. (abridged)Comment: accepted for publication by A&A, 11 pages, 13 figure