The sustainable use of renewable resources has become an important issue worldwide in the move towards a less fossil-fuel-intensive future.Mainstream method for fulfilling this aim is to increase the share of renewabl...The sustainable use of renewable resources has become an important issue worldwide in the move towards a less fossil-fuel-intensive future.Mainstream method for fulfilling this aim is to increase the share of renewable energy and materials to substitute fossil fuels and to become fully independent from fossil fuels over the long-term.However, the environmental sustainability of this endeavor has been questioned.In addition,economic and social sustainability issues are also much debated topics in this particular context.Forest resources are often thought to contribute partially to achieving a so-called ＂carbon-neutral society＂.In this review, we discuss sustainability issues of using forest biomass.We present several sustainability indicators for ecological,economic and social dimensions and discuss the issues in applying them in sustainability impact assessments（SIAs）.We also present a number of tools and methods previously used in conducting SIAs.We approach our study from the perspective of the Finnish forestry; in addition, various aspects regarding the application of SIAs in a broader context are also presented.One of the key conclusions of the study is that although sufficient data are available to measure many indicators accurately, the impacts may be very difficult to assess（e.g.impact of greenhouse gases on biodiversity） for conducting a holistic SIA.Furthermore, some indicators, such as ＂biodiversity＂, are difficult to quantify in the first place.Therefore, a mix of different methods, such as Multi-criteria Assessment, Life-cycle Assessment or Cost-Benefit Analysis, as well as different approaches（e.g.thresholds and strong/weak sustainability） are needed in aggregating the results of the impacts.SIAs are important in supporting and improving the acceptability of decision-making, but a certain degree of uncertainty will always have to be tolerated.展开更多
Objective:This paper aims to address the clinical challenge of predicting the outcomes of stroke patients and proposes a comprehensive model called RGX to help clinicians adopt more personalized treatment plans.Impact...Objective:This paper aims to address the clinical challenge of predicting the outcomes of stroke patients and proposes a comprehensive model called RGX to help clinicians adopt more personalized treatment plans.Impact Statement:The comprehensive model is first proposed and applied to clinical datasets with missing data.The introduction of the Shapley additive explanations(SHAP)model to explain the impact of patient indicators on prognosis improves the accuracy of stroke patient mortality prediction.Introduction:At present,the prediction of stroke treatment outcomes faces many challenges,including the lack of models to quantify which clinical variables are closely related to patient survival.Methods:We developed a series of machine learning models to systematically predict the mortality of stroke patients.Additionally,by introducing the SHAP model,we revealed the contribution of risk factors to the prediction results.The performance of the models was evaluated using multiple metrics,including the area under the curve,accuracy,and specificity,to comprehensively measure the effectiveness and stability of the models.Results:The RGX model achieved an accuracy of 92.18%on the complete dataset,an improvement of 11.38%compared to that of the most advanced state-of-the-art model.Most importantly,the RGX model maintained excellent predictive ability even when faced with a dataset containing a large number of missing values,achieving an accuracy of 84.62%.Conclusion:In summary,the RGX ensemble model not only provides clinicians with a highly accurate predictive tool but also promotes the understanding of stroke patient survival prediction,laying a solid foundation for the development of precision medicine.展开更多
As an important component of city evolution, urban land redevelopment has an impact on transportation system. The current traffic impact analysis （TIA） is lack of a comprehensive component for non-motorized transpor...As an important component of city evolution, urban land redevelopment has an impact on transportation system. The current traffic impact analysis （TIA） is lack of a comprehensive component for non-motorized transportation under redevelopment. For a better guidance of land redevelopment and non-motorized transportation planning, it is necessary to evaluate the negative impact of redevelopment on non-motorized traffic in the TIA. In this paper, an evaluation framework for the impact analysis is built up. We organized the pro- cedures and components of impact evaluation, and proposed the corresponding qualitative and quantitative evaluation indicators for non-motorized traffic under redevelopment. Level of service （LOS） and its criterion are employed for external impact evaluation, and level of safety, convenience, independence, and comfort which are four aspects of quality of service （QOS） are proposed to analyze the internal impact. The framework is applied to a redevelopment study in Shanghai, China. The case study results indicate that the rede- velopment from a residential area to a mixed commercial area has a significant impact on non-motorized traffic. The potential negative impact from both external and internal traffic can be minimized by reasonable improvements in the internal land use design.展开更多
基金supported by the research project“Sustainable,climate-neutral and resource-efficient forest-based bioeconomy”funded by the Strategic Research Council at the Academy of Finland(Council(Decision No.293380)
文摘The sustainable use of renewable resources has become an important issue worldwide in the move towards a less fossil-fuel-intensive future.Mainstream method for fulfilling this aim is to increase the share of renewable energy and materials to substitute fossil fuels and to become fully independent from fossil fuels over the long-term.However, the environmental sustainability of this endeavor has been questioned.In addition,economic and social sustainability issues are also much debated topics in this particular context.Forest resources are often thought to contribute partially to achieving a so-called ＂carbon-neutral society＂.In this review, we discuss sustainability issues of using forest biomass.We present several sustainability indicators for ecological,economic and social dimensions and discuss the issues in applying them in sustainability impact assessments（SIAs）.We also present a number of tools and methods previously used in conducting SIAs.We approach our study from the perspective of the Finnish forestry; in addition, various aspects regarding the application of SIAs in a broader context are also presented.One of the key conclusions of the study is that although sufficient data are available to measure many indicators accurately, the impacts may be very difficult to assess（e.g.impact of greenhouse gases on biodiversity） for conducting a holistic SIA.Furthermore, some indicators, such as ＂biodiversity＂, are difficult to quantify in the first place.Therefore, a mix of different methods, such as Multi-criteria Assessment, Life-cycle Assessment or Cost-Benefit Analysis, as well as different approaches（e.g.thresholds and strong/weak sustainability） are needed in aggregating the results of the impacts.SIAs are important in supporting and improving the acceptability of decision-making, but a certain degree of uncertainty will always have to be tolerated.
基金supported by the Beijing Municipal Natural Science Foundation(7244510).
文摘Objective:This paper aims to address the clinical challenge of predicting the outcomes of stroke patients and proposes a comprehensive model called RGX to help clinicians adopt more personalized treatment plans.Impact Statement:The comprehensive model is first proposed and applied to clinical datasets with missing data.The introduction of the Shapley additive explanations(SHAP)model to explain the impact of patient indicators on prognosis improves the accuracy of stroke patient mortality prediction.Introduction:At present,the prediction of stroke treatment outcomes faces many challenges,including the lack of models to quantify which clinical variables are closely related to patient survival.Methods:We developed a series of machine learning models to systematically predict the mortality of stroke patients.Additionally,by introducing the SHAP model,we revealed the contribution of risk factors to the prediction results.The performance of the models was evaluated using multiple metrics,including the area under the curve,accuracy,and specificity,to comprehensively measure the effectiveness and stability of the models.Results:The RGX model achieved an accuracy of 92.18%on the complete dataset,an improvement of 11.38%compared to that of the most advanced state-of-the-art model.Most importantly,the RGX model maintained excellent predictive ability even when faced with a dataset containing a large number of missing values,achieving an accuracy of 84.62%.Conclusion:In summary,the RGX ensemble model not only provides clinicians with a highly accurate predictive tool but also promotes the understanding of stroke patient survival prediction,laying a solid foundation for the development of precision medicine.
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education(No. 200802470030)
文摘As an important component of city evolution, urban land redevelopment has an impact on transportation system. The current traffic impact analysis （TIA） is lack of a comprehensive component for non-motorized transportation under redevelopment. For a better guidance of land redevelopment and non-motorized transportation planning, it is necessary to evaluate the negative impact of redevelopment on non-motorized traffic in the TIA. In this paper, an evaluation framework for the impact analysis is built up. We organized the pro- cedures and components of impact evaluation, and proposed the corresponding qualitative and quantitative evaluation indicators for non-motorized traffic under redevelopment. Level of service （LOS） and its criterion are employed for external impact evaluation, and level of safety, convenience, independence, and comfort which are four aspects of quality of service （QOS） are proposed to analyze the internal impact. The framework is applied to a redevelopment study in Shanghai, China. The case study results indicate that the rede- velopment from a residential area to a mixed commercial area has a significant impact on non-motorized traffic. The potential negative impact from both external and internal traffic can be minimized by reasonable improvements in the internal land use design.
