Early and regular hysteroscopy in patients with IUA undergoing hysteroscopic adhesion separation is effective in restoring uterine cavity morphology, preventing re-adhesion and improving menstruation.

Diseases pose significant threats to crop production, leading to substantial yield reductions and jeopardizing global food security. Timely and accurate detection of crop diseases is essential for ensuring sustainable agricultural development and effective crop management. While deep learning-based computer vision techniques have emerged as powerful tools for crop disease recognition, these methods are heavily reliant on large datasets, which are often difficult to obtain in practical agricultural settings. This c…

Cold stress severely limits the growth and productivity of common bean ( Phaseolus vulgaris L.) seedlings, particularly during early development. Exogenous application of acetylsalicylic acid (ASA) has proven to be an effective strategy for enhancing cold tolerance. This study investigates the usefulness of exogenous ASA in enhancing cold tolerance in common bean seedlings exposed to cold stress of 5°C for 12 and 24 hours, along with a control (0h). ASA treatments (1 mM and 2 mM) significantly improved critical ph…

Rural road networks are vital for rural development, yet narrow alleys and occluded segments remain underrepresented in digital maps due to irregular morphology, spectral ambiguity, and limited model generalization. Traditional segmentation models struggle to balance local detail preservation and long-range dependency modeling, prioritizing either local features or global context alone. Hypothesizing that integrating hierarchical local features and global context will mitigate these limitations, this study aims to…

Generalized Category Discovery (GCD) aims to classify both known and novel categories using partially labeled data that contains only known classes. Despite achieving strong performance on existing benchmarks, current textual GCD methods lack sufficient validation in realistic settings. We introduce Event-Centric GCD (EC-GCD), characterized by long, complex narratives and highly imbalanced class distributions, posing two main challenges: (1) divergent clustering versus classification groupings caused by subjective…