The marital and fertility sentiment orientation of Chinese women and its influencing factors - An analysis based on natural language processing.

Background: With the evolution of China's social structure and values, there has been a shift in attitudes towards marriage and fertility, with an increasing number of women holding diverse perspectives on these matters. In order to better comprehend the fundamental reasons behind these attitude changes and to provide a basis for targeted policymaking, this study employs natural language processing techniques to analyze the discourse of Chinese women.

Methods: The study focused on analyzing 3,200 comments from Weibo, concentrating on six prominent topics linked to women's marriage and fertility.

Information Cocoons on Short Video Platforms and Its Influence on Depression Among the Elderly: A Moderated Mediation Model.

Background: As the elderly increasingly engage with new media, particularly short video platforms, concerns are arising about the formation of "information cocoons" that limit exposure to diverse perspectives. While the impact of these cocoons on society has been investigated, their effects on the mental well-being of the elderly remain understudied. Given the prevalence of depression among the elderly, it is crucial to understand the potential link between information cocoons and depression among older adults.

An innovative coupling technique for integrating oil spill prediction model with finite volume method-based ocean model.

Marine oil spill pollution have increased recent years, threatening the safety of the marine environment. This paper proposes a coupling technique: Fast Mapping & Addressing(FMA) that integrates the oil spill model with oceanographic model. The FMA technique is based on hash function and spatial quadtree algorithm to achieve efficient addressing from an unstructured to a structured grid.

Research on sunken & submerged oil detection and its behavior process under the action of breaking waves based on YOLO v4 algorithm.

Marine oil spill pollution is one of the most serious marine pollution issues. Aiming at the problems of low accuracy and slow speed in the process of detecting the behavior of sunken and submerged oil by traditional methods, a technology of sunken & submerged oil tracking based on YOLO v4 (YOLO refers to 'you look only once') algorithm is proposed in this paper. The image data used in this study are pictures of real oil pollution moving under breaking waves, and they are collected in the laboratory.

Prediction of Yangtze River streamflow based on deep learning neural network with El Niño-Southern Oscillation.

Accurate long-term streamflow and flood forecasting have always been an important research direction in hydrology research. Nowadays, climate change, floods, and other anomalies occurring more and more frequently and bringing great losses to society. The prediction of streamflow, especially flood prediction, is important for disaster prevention.

Early Prediction of the 2019 Novel Coronavirus Outbreak in the Mainland China Based on Simple Mathematical Model.

The 2019 novel coronavirus (2019-nCoV) outbreak has been treated as a Public Health Emergency of International Concern by the World Health Organization. This work made an early prediction of the 2019-nCoV outbreak in China based on a simple mathematical model and limited epidemiological data. Combing characteristics of the historical epidemic, we found part of the released data is unreasonable.