Dior“文化挪用”马面裙事件引发民众热议,以“马面裙”为代表的新中式服装走进大众视野。新中式服装实现了传统文化与现代时尚的完美融合,其产业发展在经济、文化等不同维度上均具有重要价值,因而了解民众对新中式服装的情感倾向与关注...Dior“文化挪用”马面裙事件引发民众热议,以“马面裙”为代表的新中式服装走进大众视野。新中式服装实现了传统文化与现代时尚的完美融合,其产业发展在经济、文化等不同维度上均具有重要价值,因而了解民众对新中式服装的情感倾向与关注点,深入分析影响民众关于新中式服装购买意愿的影响因素对新中式服装产业的未来发展及传统文化传承具有深远意义。团队通过网络爬取进行文本分析,为问卷设计提供理论支持。基于描述性统计分析构建消费者画像,综合应用二值Logistic回归与随机森林模型确定影响消费意愿的主要因素,从消费者因素、产品因素和推广途径三个方面明确新中式服装的市场方向,以此提出有价值的结论与建议。结果表明,性别、年龄、学历、收入、地区作用的消费者自身因素是影响新中式服装购买意愿的最主要因素。Dior’s “cultural appropriation” incident involving horse-face skirts has sparked public discussion, and new Chinese-style clothing represented by the horse-face skirts has entered the public eye. This style perfectly blends traditional culture with modern fashion, and its industrial development has important value in different dimensions such as economy and culture. Therefore, understanding the emotional tendencies and concerns of the public towards the new Chinese-style clothing, and conducting a deep analysis of the factors influencing the public’s willingness to purchase such clothing have profound significance for the future development of the new Chinese-style clothing industry and the inheritance of traditional culture. The team conducted text analysis through web crawling to provide theoretical support for questionnaire design. Based on descriptive statistical analysis, a consumer portrait is constructed, and binary logistic regression and random forest models are comprehensively applied to determine the main factors affecting consumers’ willingness. Clarifying the market direction of new Chinese-style clothing from three aspects: consumer factors, product attributes, and promotional channels, in order to provide valuable conclusions and suggestions. The results indicate that consumer factors such as gender, age, education, income, and regional influence are the most significant factors affecting the willingness to purchase new Chinese-style clothing.展开更多
目的基于随机森林模型探讨中青年乳腺癌患者未成年子女养育忧虑现状及其影响因素,为临床干预提供依据。方法采用便利抽样法,选择2023年4月至12月在本市某三级甲等综合医院乳腺外科接受诊疗的275例乳腺癌患者为研究对象。采用自行设计的...目的基于随机森林模型探讨中青年乳腺癌患者未成年子女养育忧虑现状及其影响因素,为临床干预提供依据。方法采用便利抽样法,选择2023年4月至12月在本市某三级甲等综合医院乳腺外科接受诊疗的275例乳腺癌患者为研究对象。采用自行设计的一般资料问卷、中文版养育忧虑问卷(parenting concerns questionnaire,PCQ)、领悟社会支持量表(perceived social support scale,PSSS)、癌症复发担忧量表(concern about recurrence scale,CARS)、简易疾病感知量表(brief illness perception questionnaire,BIPQ)进行调查。基于随机森林模型和最小绝对收缩和选择算法(least absolute shrinkage and selection operator,LASSO)对变量进行重要性排序和变量筛选,将筛选后的变量纳入多元线性回归分析。结果260例患者完成研究。中青年乳腺癌患者养育忧虑得分为(51.1±6.4)分。将随机森林及LASSO回归确定的变量,纳入多元线性回归分析结果显示(并按影响因素重次要排序),疾病感知越高、领悟社会支持越低、癌症复发担忧越大、肿瘤分期Ⅳ期、离异/丧偶、未成年子女个数越多的中青年乳腺癌患者养育的忧虑越严重(均P<0.05),解释总变异的57.0%。结论中青年乳腺癌患者养育忧虑处于中等偏高水平,受多种因素影响,医护人员应针对性制订措施给予干预,以便降低患者养育忧虑水平。展开更多
随着对地观测技术的飞速发展,我们能够以前所未有的精度和频率获取地球表面的各种数据,通过进行更精细的空间分析和时间序列分析,可以揭示地理环境变化的深层次规律。本文旨在建立中国降水量变化趋势及其与海拔、坡度、土地利用之间的...随着对地观测技术的飞速发展,我们能够以前所未有的精度和频率获取地球表面的各种数据,通过进行更精细的空间分析和时间序列分析,可以揭示地理环境变化的深层次规律。本文旨在建立中国降水量变化趋势及其与海拔、坡度、土地利用之间的预测模型。通过对降水量、地形因素和五种主要土地覆盖类型的相关性分析,运用Logistic回归和随机森林模型探讨了这些因素对灾害发生的共同影响机制。此外,采用ARIMA时间序列模型预测了未来2025年到2035年间的降水量和土地利用格局,并结合随机森林模型评估了此期间各地区暴雨灾害风险的空间分布。研究结果揭示了在极端天气条件下最脆弱的地区,为灾害防范和土地规划提供了重要参考。With the rapid advancement of remote sensing technologies, we are now able to obtain various data on the Earth’s surface with unprecedented accuracy and frequency. Through more refined spatial and time series analyses, the underlying patterns of geographical environmental changes can be revealed. This study aims to establish predictive models for the trends in precipitation changes in China and their relationships with elevation, slope, and land use. By analyzing the correlations between precipitation, topographic factors, and five major land cover types, the study employs Logistic regression and Random Forest models to explore the joint impact of these factors on the occurrence of disasters. Additionally, the ARIMA time series model is utilized to forecast precipitation and land use patterns from 2025 to 2035, while the Random Forest model is applied to assess the spatial distribution of rainfall disaster risks during this period. The results of the study highlight the most vulnerable regions under extreme weather conditions, providing valuable insights for disaster prevention and land planning.展开更多
文摘Dior“文化挪用”马面裙事件引发民众热议,以“马面裙”为代表的新中式服装走进大众视野。新中式服装实现了传统文化与现代时尚的完美融合,其产业发展在经济、文化等不同维度上均具有重要价值,因而了解民众对新中式服装的情感倾向与关注点,深入分析影响民众关于新中式服装购买意愿的影响因素对新中式服装产业的未来发展及传统文化传承具有深远意义。团队通过网络爬取进行文本分析,为问卷设计提供理论支持。基于描述性统计分析构建消费者画像,综合应用二值Logistic回归与随机森林模型确定影响消费意愿的主要因素,从消费者因素、产品因素和推广途径三个方面明确新中式服装的市场方向,以此提出有价值的结论与建议。结果表明,性别、年龄、学历、收入、地区作用的消费者自身因素是影响新中式服装购买意愿的最主要因素。Dior’s “cultural appropriation” incident involving horse-face skirts has sparked public discussion, and new Chinese-style clothing represented by the horse-face skirts has entered the public eye. This style perfectly blends traditional culture with modern fashion, and its industrial development has important value in different dimensions such as economy and culture. Therefore, understanding the emotional tendencies and concerns of the public towards the new Chinese-style clothing, and conducting a deep analysis of the factors influencing the public’s willingness to purchase such clothing have profound significance for the future development of the new Chinese-style clothing industry and the inheritance of traditional culture. The team conducted text analysis through web crawling to provide theoretical support for questionnaire design. Based on descriptive statistical analysis, a consumer portrait is constructed, and binary logistic regression and random forest models are comprehensively applied to determine the main factors affecting consumers’ willingness. Clarifying the market direction of new Chinese-style clothing from three aspects: consumer factors, product attributes, and promotional channels, in order to provide valuable conclusions and suggestions. The results indicate that consumer factors such as gender, age, education, income, and regional influence are the most significant factors affecting the willingness to purchase new Chinese-style clothing.
文摘目的基于随机森林模型探讨中青年乳腺癌患者未成年子女养育忧虑现状及其影响因素,为临床干预提供依据。方法采用便利抽样法,选择2023年4月至12月在本市某三级甲等综合医院乳腺外科接受诊疗的275例乳腺癌患者为研究对象。采用自行设计的一般资料问卷、中文版养育忧虑问卷(parenting concerns questionnaire,PCQ)、领悟社会支持量表(perceived social support scale,PSSS)、癌症复发担忧量表(concern about recurrence scale,CARS)、简易疾病感知量表(brief illness perception questionnaire,BIPQ)进行调查。基于随机森林模型和最小绝对收缩和选择算法(least absolute shrinkage and selection operator,LASSO)对变量进行重要性排序和变量筛选,将筛选后的变量纳入多元线性回归分析。结果260例患者完成研究。中青年乳腺癌患者养育忧虑得分为(51.1±6.4)分。将随机森林及LASSO回归确定的变量,纳入多元线性回归分析结果显示(并按影响因素重次要排序),疾病感知越高、领悟社会支持越低、癌症复发担忧越大、肿瘤分期Ⅳ期、离异/丧偶、未成年子女个数越多的中青年乳腺癌患者养育的忧虑越严重(均P<0.05),解释总变异的57.0%。结论中青年乳腺癌患者养育忧虑处于中等偏高水平,受多种因素影响,医护人员应针对性制订措施给予干预,以便降低患者养育忧虑水平。
文摘随着对地观测技术的飞速发展,我们能够以前所未有的精度和频率获取地球表面的各种数据,通过进行更精细的空间分析和时间序列分析,可以揭示地理环境变化的深层次规律。本文旨在建立中国降水量变化趋势及其与海拔、坡度、土地利用之间的预测模型。通过对降水量、地形因素和五种主要土地覆盖类型的相关性分析,运用Logistic回归和随机森林模型探讨了这些因素对灾害发生的共同影响机制。此外,采用ARIMA时间序列模型预测了未来2025年到2035年间的降水量和土地利用格局,并结合随机森林模型评估了此期间各地区暴雨灾害风险的空间分布。研究结果揭示了在极端天气条件下最脆弱的地区,为灾害防范和土地规划提供了重要参考。With the rapid advancement of remote sensing technologies, we are now able to obtain various data on the Earth’s surface with unprecedented accuracy and frequency. Through more refined spatial and time series analyses, the underlying patterns of geographical environmental changes can be revealed. This study aims to establish predictive models for the trends in precipitation changes in China and their relationships with elevation, slope, and land use. By analyzing the correlations between precipitation, topographic factors, and five major land cover types, the study employs Logistic regression and Random Forest models to explore the joint impact of these factors on the occurrence of disasters. Additionally, the ARIMA time series model is utilized to forecast precipitation and land use patterns from 2025 to 2035, while the Random Forest model is applied to assess the spatial distribution of rainfall disaster risks during this period. The results of the study highlight the most vulnerable regions under extreme weather conditions, providing valuable insights for disaster prevention and land planning.
