为了快速识别市场中的劣质食用油,提出了一种结合激光诱导荧光(laser-induced fluorescence,LIF)技术与偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA)的高品质食用油掺伪鉴别方法。首先利用实验室搭建的LIF...为了快速识别市场中的劣质食用油,提出了一种结合激光诱导荧光(laser-induced fluorescence,LIF)技术与偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA)的高品质食用油掺伪鉴别方法。首先利用实验室搭建的LIF系统采集了橄榄油、芝麻油和花生油及其掺伪样本的荧光光谱数据;然后基于PLS-DA方法分别为橄榄油、芝麻油和花生油构建了掺伪鉴别模型;最后通过预测集对模型性能进行了评估。结果表明,PLS-DA模型能够准确捕捉掺伪样本与真实样本荧光光谱之间的差异性特征,在实验所得数据验证下,达到了100%的分类准确率。该方法可实现对掺伪食用油的高精度鉴别,为食品安全监管提供了科学的鉴别手段。展开更多
数字化教学能力是教育数字化转型时期教师必备的关键能力,深入探究并分析教师数字化教学能力的影响因素,是教育管理者和教师应对技术挑战、提升教学质量、培养创新人才的关键环节。基于此,文章依托统一接受和使用技术(Unified Theory of...数字化教学能力是教育数字化转型时期教师必备的关键能力,深入探究并分析教师数字化教学能力的影响因素,是教育管理者和教师应对技术挑战、提升教学质量、培养创新人才的关键环节。基于此,文章依托统一接受和使用技术(Unified Theory of Acceptance and Use of Technology,UTAUT)模型,采用偏最小二乘结构方程模型(Partial Least Squares Structural Equation Modeling,PLS-SEM)和模糊集定性比较分析(Fuzzy-Set Qualitative Comparative Analysis,fsQCA)方法,对教师数字化教学能力的影响因素及其组合效应进行了实证分析。其中,PLS-SEM分析结果表明,绩效期望、努力期望、社群影响、便利条件和自我效能感对教师数字化教学意愿有显著的正向影响,并进一步正向影响教师的数字化教学能力;教师的自我效能感对数字化教学能力有显著的直接影响,且影响效应最强。而fs QCA分析结果显示,存在四条激发教师数字化教学能力的路径,在这些路径中数字化教学意愿和自我效能感是两个重要的前因变量,这弥补了结构方程模型分析的相对不足。文章通过研究,旨在为教育数字化转型时期教师数字化教学能力的提升提供实证依据。展开更多
水稻类病斑突变体在研究水稻细胞程序性死亡和广谱抗病性中具有重要作用,已报道的水稻类病斑主要发生在叶片上,少量发生在颖壳上。本研究中首次报道了水稻的一种穗叶类病斑突变体pls1(Panicle and leaf spot 1),其从三叶期叶片开始出现...水稻类病斑突变体在研究水稻细胞程序性死亡和广谱抗病性中具有重要作用,已报道的水稻类病斑主要发生在叶片上,少量发生在颖壳上。本研究中首次报道了水稻的一种穗叶类病斑突变体pls1(Panicle and leaf spot 1),其从三叶期叶片开始出现红褐色斑点,随生育进程扩大,并扩展到其他器官。与以往报道的水稻类病斑突变体不同的是,pls1抽穗后稻穗枝梗和颖壳逐渐产生红褐色病斑,成熟期稻穗干枯,严重影响产量,是一种新类型的水稻类病斑。结合图位克隆和全基因组重测序发现pls1突变体产生了173403 bp的大片段缺失,导致7个基因缺失和1个基因启动子缺失。这8个基因中4个编码醇溶蛋白,另外3个在叶片和穗部表达量较低,只有Os12g0268000在叶片和稻穗中较其他器官有较高的表达量,推测PLS1为Os12g0268000,基因功能注释显示其编码色胺5-羟化酶。pls1突变体叶片中活性氧、过氧化氢、超氧阴离子过量积累,抗氧系统相关酶氧化物歧化酶、抗坏血酸过氧化物酶、过氧化氢酶和谷胱甘肽还原酶活性提高,发生细胞程序性死亡和叶绿体降解,降低光合能力。褪黑素在植物耐盐性中起重要作用。进一步的功能分析发现,缺失PLS1会抑制水稻中褪黑素合成相关酶基因OsTDC1、OsTDC3、OsSNAT1、OsASMT1和OsCOMT的表达,进而导致pls1突变体的耐盐性下降。综上,穗叶类病斑突变体pls1是一种新类型的水稻类病斑突变体,将为水稻类病斑研究提供新的种质材料;耐盐性的分析揭示了色胺5-羟化酶的新功能,为研究其在细胞程序性死亡和耐盐性中的机制提供了新视角。展开更多
煤炭灰分值是衡量煤炭质量的关键指标之一,灰分含量和性质对燃烧设备、环境、后续的加工利用都有着极大影响。针对目前煤炭灰分检测方法的滞后性、劳动密集型问题,提出了一种基于XRF光谱的预处理(Preprocessing,PRE)与偏最小二乘法(Part...煤炭灰分值是衡量煤炭质量的关键指标之一,灰分含量和性质对燃烧设备、环境、后续的加工利用都有着极大影响。针对目前煤炭灰分检测方法的滞后性、劳动密集型问题,提出了一种基于XRF光谱的预处理(Preprocessing,PRE)与偏最小二乘法(Partial Least Squares,PLS)相结合的XRF煤炭灰分智能预测算法。通过将XRF技术获取煤炭样品的光谱数据输入PLS主模型初步预测灰分,再将相关校正参数输入补偿优化模型中,最终将两者相加得到预测灰分值。试验结果表明:相对于偏最小二乘法回归、神经网络回归模型,PRE-PLS模型决定系数为0.9951,均方根误差为0.9411,平均绝对误差为0.7332%,表明该模型具备较高的精度,能够胜任现场检测工作,为生产提供可靠指导。展开更多
Urbanization and industrialization have escalated water pollution,threatening ecosystems and human health.Water pollution not only degrades water quality but also poses long-term risks to human health through the food...Urbanization and industrialization have escalated water pollution,threatening ecosystems and human health.Water pollution not only degrades water quality but also poses long-term risks to human health through the food chain.The development of efficient wastewater detection and treatment methods is essential for mitigating this environmental hazard.Carbon dots(CDs),as emerging carbon-based nanomaterials,exhibit properties such as biocompatibility,photoluminescence(PL),water solubility,and strong adsorption,positioning them as promising candidates for environmental monitoring and management.Particularly in wastewater treatment,their optical and electron transfer properties make them ideal for pollutant detection and removal.Despite their potential,comprehensive reviews on CDs'role in wastewater treatment are scarce,often lacking detailed insights into their synthesis,PL mechanisms,and practical applications.This review systematically addresses the synthesis,PL mechanisms,and wastewater treatment applications of CDs,aiming to bridge existing research gaps.It begins with an overview of CDs structure and classification,essential for grasping their properties and uses.The paper then explores the pivotal PL mechanisms of CDs,crucial for their sensing capabilities.Next,comprehensive synthesis strategies are presented,encompassing both top-down and bottom-up strategies such as arc discharge,chemical oxidation,and hydrothermal/solvothermal synthesis.The diversity of these methods highlights the potential for tailored CDs production to suit specific environmental applications.Furthermore,the review systematically discusses the applications of CDs in wastewater treatment,including sensing,inorganic removal,and organic degradation.Finally,it delves into the research prospects and challenges of CDs,proposing future directions to enhance their role in wastewater treatment.展开更多
文摘为了快速识别市场中的劣质食用油,提出了一种结合激光诱导荧光(laser-induced fluorescence,LIF)技术与偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA)的高品质食用油掺伪鉴别方法。首先利用实验室搭建的LIF系统采集了橄榄油、芝麻油和花生油及其掺伪样本的荧光光谱数据;然后基于PLS-DA方法分别为橄榄油、芝麻油和花生油构建了掺伪鉴别模型;最后通过预测集对模型性能进行了评估。结果表明,PLS-DA模型能够准确捕捉掺伪样本与真实样本荧光光谱之间的差异性特征,在实验所得数据验证下,达到了100%的分类准确率。该方法可实现对掺伪食用油的高精度鉴别,为食品安全监管提供了科学的鉴别手段。
文摘数字化教学能力是教育数字化转型时期教师必备的关键能力,深入探究并分析教师数字化教学能力的影响因素,是教育管理者和教师应对技术挑战、提升教学质量、培养创新人才的关键环节。基于此,文章依托统一接受和使用技术(Unified Theory of Acceptance and Use of Technology,UTAUT)模型,采用偏最小二乘结构方程模型(Partial Least Squares Structural Equation Modeling,PLS-SEM)和模糊集定性比较分析(Fuzzy-Set Qualitative Comparative Analysis,fsQCA)方法,对教师数字化教学能力的影响因素及其组合效应进行了实证分析。其中,PLS-SEM分析结果表明,绩效期望、努力期望、社群影响、便利条件和自我效能感对教师数字化教学意愿有显著的正向影响,并进一步正向影响教师的数字化教学能力;教师的自我效能感对数字化教学能力有显著的直接影响,且影响效应最强。而fs QCA分析结果显示,存在四条激发教师数字化教学能力的路径,在这些路径中数字化教学意愿和自我效能感是两个重要的前因变量,这弥补了结构方程模型分析的相对不足。文章通过研究,旨在为教育数字化转型时期教师数字化教学能力的提升提供实证依据。
文摘煤炭灰分值是衡量煤炭质量的关键指标之一,灰分含量和性质对燃烧设备、环境、后续的加工利用都有着极大影响。针对目前煤炭灰分检测方法的滞后性、劳动密集型问题,提出了一种基于XRF光谱的预处理(Preprocessing,PRE)与偏最小二乘法(Partial Least Squares,PLS)相结合的XRF煤炭灰分智能预测算法。通过将XRF技术获取煤炭样品的光谱数据输入PLS主模型初步预测灰分,再将相关校正参数输入补偿优化模型中,最终将两者相加得到预测灰分值。试验结果表明:相对于偏最小二乘法回归、神经网络回归模型,PRE-PLS模型决定系数为0.9951,均方根误差为0.9411,平均绝对误差为0.7332%,表明该模型具备较高的精度,能够胜任现场检测工作,为生产提供可靠指导。
基金supported by the Natural Science Foundation of Hebei Province(No.E2022208046)National Science Foundation of China(No.52004080)+2 种基金Key project of National Natural Science Foundation of China(No.U20A20130)Key research and development project of Hebei Province(No.22373704D)2023 Central Government Guide Local Science and Technology Development Fund Project(No.236Z1812 G)。
文摘Urbanization and industrialization have escalated water pollution,threatening ecosystems and human health.Water pollution not only degrades water quality but also poses long-term risks to human health through the food chain.The development of efficient wastewater detection and treatment methods is essential for mitigating this environmental hazard.Carbon dots(CDs),as emerging carbon-based nanomaterials,exhibit properties such as biocompatibility,photoluminescence(PL),water solubility,and strong adsorption,positioning them as promising candidates for environmental monitoring and management.Particularly in wastewater treatment,their optical and electron transfer properties make them ideal for pollutant detection and removal.Despite their potential,comprehensive reviews on CDs'role in wastewater treatment are scarce,often lacking detailed insights into their synthesis,PL mechanisms,and practical applications.This review systematically addresses the synthesis,PL mechanisms,and wastewater treatment applications of CDs,aiming to bridge existing research gaps.It begins with an overview of CDs structure and classification,essential for grasping their properties and uses.The paper then explores the pivotal PL mechanisms of CDs,crucial for their sensing capabilities.Next,comprehensive synthesis strategies are presented,encompassing both top-down and bottom-up strategies such as arc discharge,chemical oxidation,and hydrothermal/solvothermal synthesis.The diversity of these methods highlights the potential for tailored CDs production to suit specific environmental applications.Furthermore,the review systematically discusses the applications of CDs in wastewater treatment,including sensing,inorganic removal,and organic degradation.Finally,it delves into the research prospects and challenges of CDs,proposing future directions to enhance their role in wastewater treatment.
