SP-YOLO: A Real-Time and Efficient Multi-Scale Model for Pest Detection in Sugar Beet Fields.

Beet crops are highly vulnerable to pest infestations throughout their growth cycle, which significantly affects crop development and yield. Timely and accurate pest identification is crucial for implementing effective control measures. Current pest detection tasks face two primary challenges: first, pests frequently blend into their environment due to similar colors, making it difficult to capture distinguishing features in the field; second, pest images exhibit scale variations under different viewing angles, lighting conditions, and distances, which complicates the detection process.

The impact of negative emotions and relationship quality on consumers' repurchase intention: An empirical study based on service recovery in China's online travel agencies.

Service failures of online travel agencies (OTAs) occur frequently, which makes the OTA business operation model face huge risks. However, the current academic circles still pay insufficient attention to OTA service recovery. This study obtained research data through scenario experiment method, and analyzed data through SPSS25.