The rapidly developing rural tourism industry in China has deeply influenced the livelihoods of rural households. This study compares the impact of rural tourism development in poor areas on the farmers' livelihoo...The rapidly developing rural tourism industry in China has deeply influenced the livelihoods of rural households. This study compares the impact of rural tourism development in poor areas on the farmers' livelihoods, based on the Sustainable Livelihoods Framework proposed by the United Kingdom's Department for International Development. Gougezhuang, a tourist village, and Jiaojiekou, a non-tourist village, both located in Yesanpo Tourism District in the state-level povertystricken Laishui County, Hebei Province, were selected as case studies. The livelihood models of the two villages show great differentiation after 20 years of tourism development. Gougezhuang Village has been driven by the tourism industry and farmers are employed locally, enjoying a relatively higher-income life, with a developmental livelihood model. In contrast, farmers in Jiaojiekou Village earn their living mainly by leaving home to work in the city. They have a low income, with a survival livelihood model, supported by part-time business. Considering that the two villages are adjacent and have similar development backgrounds, the analysis results indicate that rural tourism has an apparent locationspecific effect on poverty alleviation and socioeconomic development, but the development ofrural tourism is limited regarding large-scale poverty alleviation efforts in poor areas. To implement a propoor-tourism strategy and achieve sustainable development, it is necessary to implement comprehensive management measures to change the local conditions of rural settlements and make full use of the spillover effect of tourist consumption.展开更多
根据实验数据,分析,数理推理证明,选用二种存活模型,三种不同的目标函数进行拟合计算比较,得出了较好的存活模型S=EXP(-AD-BD^2)和目标函数Q=sum from i=1 to n[S(D_i,B)-S_i/SE_i]~2。拟合结果表明,用这一存活模型和目标函数进行拟合...根据实验数据,分析,数理推理证明,选用二种存活模型,三种不同的目标函数进行拟合计算比较,得出了较好的存活模型S=EXP(-AD-BD^2)和目标函数Q=sum from i=1 to n[S(D_i,B)-S_i/SE_i]~2。拟合结果表明,用这一存活模型和目标函数进行拟合能获得与实验值配合得好的结果。这种存活模型和目标函数不仅适用于种子实验数据的拟合,而且对其它生物体的实验数据的拟合也有一定适用性。本文还讨论了存活率值及其标准偏差的变化对拟合曲线的影响。展开更多
Tuberculosis is one of the leading causes of morbidity and mortality globally. Although different strategies have been designed and implemented to combat it, it has continuously increased in the past five years, resul...Tuberculosis is one of the leading causes of morbidity and mortality globally. Although different strategies have been designed and implemented to combat it, it has continuously increased in the past five years, resulting in 10 million new cases and 1.6 million deaths. This study aims to estimate survival and predictors among tuberculosis patients on treatment in selected health centers in Addis Ababa, Ethiopia. The study employed a retrospective cohort design where data were collected by reviewing medical records of tuberculosis patients who were registered from May 2016 to May 2017 on treatment in 20 selected health centers in Addis Ababa. Independent predictors were identified, and the strength of association between dependent and independent predictors was determined using the Weibull regression model. Before computing Weibull regression analysis, Cox proportional assumption, model diagnosis, and fitness were checked. The hazard ratio was calculated to indicate the strength of association. Of 371 TB patients, about 136 (36.7%) died during the treatment period. Most TB deaths occurred during the intensive phase, and the overall estimated median survival time was 157 days. In the multivariable Weibull model, age (HR = 0.98), baseline weight (HR = 0.96, P = 0.03), tuberculosis treatment phase (continuation phase, HR = 0.48), and tuberculosis type (pulmonary negative TB, HR = 19.92) were found to be independent predictors of time to death of tuberculosis patients. Finally, the study concluded that the survival time to death of the patients is high. The health care providers should give special attention and follow up for pulmonary negative and underweight TB patients.展开更多
基金supported by the National Natural Science Foundation of China (Grant no. 41671151)the National Social Science Foundation of China (Grant no. 17BGL123)+1 种基金the Key Project of China National Tourism Administration Research Foundation (Grant no. 16TAAK004)the Tourism Young Expert Training Program of China National Tourism Administration (TYETP201527)
文摘The rapidly developing rural tourism industry in China has deeply influenced the livelihoods of rural households. This study compares the impact of rural tourism development in poor areas on the farmers' livelihoods, based on the Sustainable Livelihoods Framework proposed by the United Kingdom's Department for International Development. Gougezhuang, a tourist village, and Jiaojiekou, a non-tourist village, both located in Yesanpo Tourism District in the state-level povertystricken Laishui County, Hebei Province, were selected as case studies. The livelihood models of the two villages show great differentiation after 20 years of tourism development. Gougezhuang Village has been driven by the tourism industry and farmers are employed locally, enjoying a relatively higher-income life, with a developmental livelihood model. In contrast, farmers in Jiaojiekou Village earn their living mainly by leaving home to work in the city. They have a low income, with a survival livelihood model, supported by part-time business. Considering that the two villages are adjacent and have similar development backgrounds, the analysis results indicate that rural tourism has an apparent locationspecific effect on poverty alleviation and socioeconomic development, but the development ofrural tourism is limited regarding large-scale poverty alleviation efforts in poor areas. To implement a propoor-tourism strategy and achieve sustainable development, it is necessary to implement comprehensive management measures to change the local conditions of rural settlements and make full use of the spillover effect of tourist consumption.
文摘根据实验数据,分析,数理推理证明,选用二种存活模型,三种不同的目标函数进行拟合计算比较,得出了较好的存活模型S=EXP(-AD-BD^2)和目标函数Q=sum from i=1 to n[S(D_i,B)-S_i/SE_i]~2。拟合结果表明,用这一存活模型和目标函数进行拟合能获得与实验值配合得好的结果。这种存活模型和目标函数不仅适用于种子实验数据的拟合,而且对其它生物体的实验数据的拟合也有一定适用性。本文还讨论了存活率值及其标准偏差的变化对拟合曲线的影响。
文摘Tuberculosis is one of the leading causes of morbidity and mortality globally. Although different strategies have been designed and implemented to combat it, it has continuously increased in the past five years, resulting in 10 million new cases and 1.6 million deaths. This study aims to estimate survival and predictors among tuberculosis patients on treatment in selected health centers in Addis Ababa, Ethiopia. The study employed a retrospective cohort design where data were collected by reviewing medical records of tuberculosis patients who were registered from May 2016 to May 2017 on treatment in 20 selected health centers in Addis Ababa. Independent predictors were identified, and the strength of association between dependent and independent predictors was determined using the Weibull regression model. Before computing Weibull regression analysis, Cox proportional assumption, model diagnosis, and fitness were checked. The hazard ratio was calculated to indicate the strength of association. Of 371 TB patients, about 136 (36.7%) died during the treatment period. Most TB deaths occurred during the intensive phase, and the overall estimated median survival time was 157 days. In the multivariable Weibull model, age (HR = 0.98), baseline weight (HR = 0.96, P = 0.03), tuberculosis treatment phase (continuation phase, HR = 0.48), and tuberculosis type (pulmonary negative TB, HR = 19.92) were found to be independent predictors of time to death of tuberculosis patients. Finally, the study concluded that the survival time to death of the patients is high. The health care providers should give special attention and follow up for pulmonary negative and underweight TB patients.
