The study addresses the challenge of medical image segmentation with extremely limited labeled data, known as barely-supervised learning. The authors identify a key issue in current semi-supervised methods, which is the low precision of foreground classes in pseudo labels. To tackle this, they introduce a novel method called Compete-to-Win (ComWin), which generates higher quality pseudo labels by comparing confidence maps from different networks and selecting the most confident predictions. They also present an enhanced version, ComWin+, which includes a boundary-aware enhancement module for better accuracy near boundaries. The proposed methods outperform existing solutions on three public medical image datasets, focusing on cardiac structure, pancreas, and colon tumor segmentation. The source code for ComWin has been made available on GitHub.

The study investigates how second language (L2) reading proficiency affects the reliance on phonological and orthographic information in word recognition among Chinese collegiate students learning English as a foreign language. The research finds that higher proficiency learners are sensitive to both phonological and orthographic information, while lower proficiency learners rely more on orthographic information. The study suggests that L2 reading proficiency can lead to a restructuring of word recognition processes, with implications for language instruction and the development of reading skills.

The study explores the enhancement of stability and photovoltaic performance in perovskite solar cells through the use of a 5-ammonium acid additive. The research, conducted by a team of scientists, presents significant advancements in the field of solar energy and material science, highlighting the potential for improved efficiency and durability in photovoltaic technology.

The article discusses a study on the relationship between PD-L1 expression and various clinicopathologic characteristics in patients with liver metastasis of colon cancer. The study involved 72 patients and utilized 18F-FDG PET/CT scans to assess PD-L1 expression. The findings indicate that PD-L1 expression is not significantly related to age, sex, or the number of liver metastases but is significantly correlated with tumor size, differentiation, and patient survival. Additionally, the study found that SUVmax, a parameter from PET imaging, is positively correlated with PD-L1 expression and can be used to predict it. The study also explored the correlation between immune cell infiltration, cancer-associated fibroblasts (CAF) distribution, and PD-L1 expression and SUVmax. It was found that the number of infiltrating cytotoxic T cells is significantly correlated with both SUVmax and PD-L1 expression. Multivariate analysis confirmed that SUVmax and tumor differentiation are independent risk factors for PD-L1 expression. The study contributes to understanding the prognostic value of PD-L1 levels in liver metastases and the efficacy of anti-PD1/PD-L1 therapy.

The article discusses a study on the impact of the updated Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2023 guidelines on the treatment of COPD in China. The study is a multi-center prospective cohort study conducted in northeast China, including 986 diagnosed COPD patients, with 617 completing follow-up. The study found that only half of the patients used COPD-specific medications, with LABA+ICS being the most common therapy. The transition from GOLD 2017 to GOLD 2023 guidelines would result in a significant decrease in the adoption of preferred-line maintenance therapy in China. The study highlights the issue of patients discontinuing maintenance medication during stable phases, a problem seen globally. The findings suggest that the prescription of ICS-containing regimens is widespread and requires attention. The study concludes that further research is needed to assess the impact of the new guidelines on Chinese COPD patients.

The study evaluates the utility of satellite-based precipitation estimates from IMERG-E and forecasted precipitation from NASA's GEOS-FP in real-time hydrological monitoring and forecasting using the DRIVE model. The IMERG Final Run precipitation estimates and corresponding hydrological simulations serve as references. The study finds that IMERG-E has a dominant error source in hit bias, while GEOS-FP shows more false precipitation. The GEOS-FP-driven model performs comparably to the IMERG-E-driven model on the first day, suggesting GEOS-FP can compensate for IMERG-E's time latency in nowcasting. For forecasts with longer lead times, biases tend to cancel out, with initial hydrological conditions contributing to forecast accuracy in most regions, except the tropics where GEOS-FP is more accurate. The study highlights the potential benefits of combining IMERG-E and GEOS-FP for hydrological nowcasts and forecasts.

The article discusses the faculty recruitment process, breaking it down into two decision-making processes: graduates choosing their employers and universities selecting candidates. It highlights the mutual influence in the selection process, where doctoral graduates prefer employment at higher-ranked universities due to the prestige and resources available, while also being conservative in their applications to avoid rejection from institutions far above their alma mater's ranking. The article suggests that the ranking difference between a graduate's employment institution and their alma mater follows a normal distribution. It also notes that universities prioritize candidates from more prestigious institutions, reinforcing the central role of these universities in academia. The selection preferences of both graduates and universities are quantified using probability density functions.

The article discusses the structural and mechanical properties of SF-GMA hydrogels, which are synthesized by methacrylate substitution of silk fibroin (SF) primary amines. Fourier Transform Infrared Spectroscopy (FTIR) and proton nuclear magnetic resonance (H-NMR) spectroscopy were used to analyze the secondary structure and confirm the successful synthesis of the SF-GMA hydrogel. The study found that directional freezing and photo-crosslinking can prevent the transformation from random coil to β-sheet structures, which typically enhances the toughness of SF materials. The mechanical properties of the hydrogels were tested, revealing that directional freezing improves the toughness and strength of the SF-GMA hydrogels without affecting their elongation at break. The article provides detailed insights into the potential of SF-GMA hydrogels for applications in tissue engineering due to their enhanced mechanical properties.

The article presents a comprehensive bibliometric analysis of artificial intelligence (AI) applications in macular edema (ME) research from 2011 to 2022. It identifies the United States as having the highest influence in ME research based on the H-index, with China and the United States being the closest collaborators. The Medical University of Vienna emerged as the most influential institution in this field. The review categorizes reference clusters into ten topics, including retinal Optical Coherence Tomography (OCT) fluid detection and deep learning (DL) architectures. The study utilized databases like the Web of Science Core Collection and bibliometric platforms such as bibliometrix-BiblioShiny, VOSviewer, and CiteSpace for analysis. The research highlights the shift in ME research towards automatic detection and the identification of diabetic macular edema (DME) as a recent research hotspot. The article also acknowledges limitations, such as potential publication bias due to the time frame of the studies included.

The article discusses the compressive responses of different types of specimens: lattices, hybrid PU-foam-filled lattices, and PU foams. It highlights the three stages of compression - elasticity, stress plateau, and densification. The study finds that PU foam enters the stress plateau after a very short elastic stage and begins densification at around 9 mm of compression. The BCC lattice specimens are stiffer than the hybrid ones before the elastic limit, while the hyperbolic lattice specimens are less stiff than those filled with PU foam. The article suggests that PU foam hybridization softens the BCC lattice but stiffens the hyperbolic lattice, attributing this to different deformation mechanisms. High-speed camera observations are used to explore these mechanisms further. The article also notes that the stress plateau stage's steady-state value is almost equal to the peak force of the linear elastic stage, except for the primitive BCC lattice. Finally, it is observed that PU foam hybridization accelerates the entry into the densification stage, particularly for the BCC lattice.