目的科学评价芙蓉李果实成熟期间的营养品质,建立色度值表观特征与营养品质的关系。方法以福建省主栽品种芙蓉李为研究对象,对其成熟期间果糖、葡萄糖、蔗糖、苹果酸、奎尼酸、琥珀酸、柠檬酸、富马酸、矢车菊素-3-芸香糖苷、矢车菊素-3...目的科学评价芙蓉李果实成熟期间的营养品质,建立色度值表观特征与营养品质的关系。方法以福建省主栽品种芙蓉李为研究对象,对其成熟期间果糖、葡萄糖、蔗糖、苹果酸、奎尼酸、琥珀酸、柠檬酸、富马酸、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷、多酚、黄酮、类胡萝卜素等13个品质指标进行分析和综合评价。结果芙蓉李成熟期间,各品质指标的含量变化存在显著差异(P<0.05),综合运用相关分析、因子分析、绝对因子分析-多元线性回归(absolute principal component scores-multiple linear regression,APCS-MLR)分析筛选可反映芙蓉李综合品质的主要指标。因子分析提取出3个主因子,贡献率分别为52.677%、23.468%、11.649%,累计贡献率为87.794%。综合APCS-MLR等数理统计分析,主因子1主要对果糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷贡献较大,贡献率分别为53.00%、73.85%、55.54%;主因子2主要对蔗糖、富马酸、果糖、柠檬酸的贡献率较大,分别为28.26%、18.70%、16.14%、15.59%;主因子3主要对多酚(29.13%)和黄酮(28.28%)有较大贡献率;选取3个主因子总贡献率高于60%的果糖、葡萄糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷作为综合品质评价的主要指标。分别对已筛选出的4个主要评价指标与色度值进行多元线性逐步回归分析,建立4个主要指标与色度值的表观预测模型,各模型均具有较好的拟合度,预测值与实测值的均方根误差较小;进一步验证结果表明,通过色度值对4个指标的预测具有较高的可靠性和准确性。结论本研究筛选出的主要指标及预测模型可更加简单、便捷地评价芙蓉李果实成熟期间的综合品质。展开更多
In basketball, each player’s skill level is the key to a team’s success or failure, the skill level is affected by many personal and environmental factors. A physics-informed AI statistics has become extremely impor...In basketball, each player’s skill level is the key to a team’s success or failure, the skill level is affected by many personal and environmental factors. A physics-informed AI statistics has become extremely important. In this article, a complex non-linear process is considered by taking into account the average points per game of each player, playing time, shooting percentage, and others. This physics-informed statistics is to construct a multiple linear regression model with physics-informed neural networks. Based on the official data provided by the American Basketball League, and combined with specific methods of R program analysis, the regression model affecting the player’s average points per game is verified, and the key factors affecting the player’s average points per game are finally elucidated. The paper provides a novel window for coaches to make meaningful in-game adjustments to team members.展开更多
We present a methodology for constructing a short-term event risk score in heart failure patients from an ensemble predictor, using bootstrap samples, two different classification rules, logistic regression and linear...We present a methodology for constructing a short-term event risk score in heart failure patients from an ensemble predictor, using bootstrap samples, two different classification rules, logistic regression and linear discriminant analysis for mixed data, continuous or categorical, and random selection of explanatory variables to build individual predictors. We define a measure of the importance of each variable in the score and an event risk measure by an odds-ratio. Moreover, we establish a property of linear discriminant analysis for mixed data. This methodology is applied to EPHESUS trial patients on whom biological, clinical and medical history variables were measured.展开更多
文摘目的科学评价芙蓉李果实成熟期间的营养品质,建立色度值表观特征与营养品质的关系。方法以福建省主栽品种芙蓉李为研究对象,对其成熟期间果糖、葡萄糖、蔗糖、苹果酸、奎尼酸、琥珀酸、柠檬酸、富马酸、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷、多酚、黄酮、类胡萝卜素等13个品质指标进行分析和综合评价。结果芙蓉李成熟期间,各品质指标的含量变化存在显著差异(P<0.05),综合运用相关分析、因子分析、绝对因子分析-多元线性回归(absolute principal component scores-multiple linear regression,APCS-MLR)分析筛选可反映芙蓉李综合品质的主要指标。因子分析提取出3个主因子,贡献率分别为52.677%、23.468%、11.649%,累计贡献率为87.794%。综合APCS-MLR等数理统计分析,主因子1主要对果糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷贡献较大,贡献率分别为53.00%、73.85%、55.54%;主因子2主要对蔗糖、富马酸、果糖、柠檬酸的贡献率较大,分别为28.26%、18.70%、16.14%、15.59%;主因子3主要对多酚(29.13%)和黄酮(28.28%)有较大贡献率;选取3个主因子总贡献率高于60%的果糖、葡萄糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷作为综合品质评价的主要指标。分别对已筛选出的4个主要评价指标与色度值进行多元线性逐步回归分析,建立4个主要指标与色度值的表观预测模型,各模型均具有较好的拟合度,预测值与实测值的均方根误差较小;进一步验证结果表明,通过色度值对4个指标的预测具有较高的可靠性和准确性。结论本研究筛选出的主要指标及预测模型可更加简单、便捷地评价芙蓉李果实成熟期间的综合品质。
文摘In basketball, each player’s skill level is the key to a team’s success or failure, the skill level is affected by many personal and environmental factors. A physics-informed AI statistics has become extremely important. In this article, a complex non-linear process is considered by taking into account the average points per game of each player, playing time, shooting percentage, and others. This physics-informed statistics is to construct a multiple linear regression model with physics-informed neural networks. Based on the official data provided by the American Basketball League, and combined with specific methods of R program analysis, the regression model affecting the player’s average points per game is verified, and the key factors affecting the player’s average points per game are finally elucidated. The paper provides a novel window for coaches to make meaningful in-game adjustments to team members.
文摘We present a methodology for constructing a short-term event risk score in heart failure patients from an ensemble predictor, using bootstrap samples, two different classification rules, logistic regression and linear discriminant analysis for mixed data, continuous or categorical, and random selection of explanatory variables to build individual predictors. We define a measure of the importance of each variable in the score and an event risk measure by an odds-ratio. Moreover, we establish a property of linear discriminant analysis for mixed data. This methodology is applied to EPHESUS trial patients on whom biological, clinical and medical history variables were measured.
