化学教学内容情感性艺术处理的策略

化学教学内容是教学系统的基本要素之一。对教学内容作情感性艺术处理,显示了教师高超的化学教学艺术。其艺术策略分为:一是巧妙组织教学内容来调节学生的学习心向,包括心理匹配策略、超出预期策略;二是有效地利用教学内容中的情感资源来陶冶学生的情操,包括展示情感策略、发掘情感策略、诱发情感策略、赋予情感策略。     

游客情感计算的文本大数据挖掘方法比较研究

旅游文本大数据以其方便、快捷和低门槛的特点为游客情感计算提供了极大便利,已经成为旅游大数据的主要来源之一。基于大数据理论和情感理论,以文本大数据为数据源,在全面梳理国内外情感计算相关成果的基础上,利用人工智能中的逻辑/算法编程方法、机器学习方法、深度学习方法对旅游文本大数据进行挖掘,探索最佳的基于文本大数据的游客情感计算方法。研究发现：（1）基于情感词典的游客情感计算模型,其核心是构建情感词典和设计情感计算规则,方法简单,容易实现,适用语料范围广。（2）机器学习,用统计学方法抽取文本中的特征项,具有非线性特征,可靠性较线性特征的情感词典方法高。（3）基于深度学习技术的游客情感计算,效果良好,准确率在85%以上。训练多领域的文本语料易于移植,实用性强,且泛化能力好,较适合大数据时代游客情感计算研究。     

Development and validation of a reversed‐phase HPLC method for licarbazepine monitoring in serum of patients under oxcarbazepine treatment

Licarbazepine is the pharmacologically active metabolite of oxcarbazepine, a drug indicated for the treatment of partial seizures and bipolar disorders. Several HPLC methods have been developed thus far but there is lack of control for interferences from antipsychotic drugs. The aim of the present study was to develop a simple, low‐cost and reliable HPLC‐UV method for the determination of licarbazepine in human serum in the presence of co‐administered antiepileptic, antipsychotic and commonly prescribed drugs. Sample preparation consisted of a single protein precipitation step with methanol. Separation lasted ~9 min on a reversed‐phase C₁₈ column using a mobile phase composed of 50 mm sodium‐dihydrogen‐phosphate‐monohydrate/acetonitrile (70:30, v/v) delivered isocratically at 0.9 mL/min and 30°C. Wavelength was 210 nm and calibration curve was linear with r ² 0.998 over the range 0.2–50.0 μg/mL. Coefficient of variation was <5.03% and bias <−4.92%. Recovery ranged from 99.49 to 104.52% and the limit of detection was 0.0182 μg/mL. No interferences from the matrix or from antiepileptic, antipsychotic and commonly prescribed drugs were observed. The method was applied to serum samples of patients under oxcarbazepine treatment and proved to be a useful tool for the therapeutic drug monitoring of licarbazepine during monotherapy or adjunctive treatment of seizures or affective disorders.     

新生代员工情感承诺与短工行为的实证研究——以工作满意度为中介变量

研究情感承诺对新生代员工短工行为的影响,引入工作满意度为中介变量,通过问卷调查的形式,收集了不同类型企业的调研数据,并运用结构方程模型对收集到的数据进行实证分析,来验证提出的研究假设.研究结果表明:情感承诺不仅能够减少新生代员工短工行为的出现,而且两者之间的关系是通过工作满意度的完全中介作用得到实现.最后确定研究结论,并对如何减少新生代员工的短工行为提出相应的对策建议.     

组织性别构成多样性对员工组织承诺影响的实证分析

本文采用组织承诺的三维度概念模型探讨组织性别多样性对组织承诺的影响,研究认为员工工作级别中的性别多样性对其组织承诺(情感承诺、连续承诺)有显著的负影响,而上一级性别多样性只对其情感承诺有显著的正影响,并对此结果进行了深入讨论。     

Measurement of students’ mathematics motivation and self-concept at institutions of higher education: evidence of reliability and validity

ABSTRACT

The study aims at proposing a quantitative instrument tailored to measure the level of mathematics motivation and self-concept of students in mathematics courses at academic institutions of higher education. The significance of this study stems from its endeavour to measure mathematics motivation and self-concept of students in courses of mathematics at academic institutions of higher education which ultimately contributes to the success of students, academic institutions and societies. A quantitative research methodology has been employed in this study in which a 55-item survey instrument has been tailored and piloted. The results of factor analysis indicate that the instrument’s items loaded into mathematics motivational factors and mathematics self-concept factors. The cumulative percentage explained by mathematics motivational factors is 55.3% and the cumulative percentage explained by mathematics self-concept factors is 53.2%. The factors of mathematics motivation and mathematics self-concept explain the majority of variance in the dataset. The findings of validity and reliability tests show that 35 items measure mathematics motivation through four subscales which include importance and necessity of mathematics; perception of success in mathematics; enjoyment of mathematics; and expectations of future career and income. The other 20 items measure mathematics self-concept through two subscales which include cognitive mathematics self-concept and affective mathematics self-concept.     

游客情感计算的文本大数据挖掘方法比较研究

旅游文本大数据以其方便、快捷和低门槛的特点为游客情感计算提供了极大便利,已经成为旅游大数据的主要来源之一。基于大数据理论和情感理论,以文本大数据为数据源,在全面梳理国内外情感计算相关成果的基础上,利用人工智能中的逻辑/算法编程方法、机器学习方法、深度学习方法对旅游文本大数据进行挖掘,探索最佳的基于文本大数据的游客情感计算方法。研究发现：（1）基于情感词典的游客情感计算模型,其核心是构建情感词典和设计情感计算规则,方法简单,容易实现,适用语料范围广。（2）机器学习,用统计学方法抽取文本中的特征项,具有非线性特征,可靠性较线性特征的情感词典方法高。（3）基于深度学习技术的游客情感计算,效果良好,准确率在85%以上。训练多领域的文本语料易于移植,实用性强,且泛化能力好,较适合大数据时代游客情感计算研究。     

乡村民宿经营者情感劳动价值评估研究

情感劳动是乡村民宿经营中重要的无形资产,有效评估其价值对民宿以及乡村具有重要意义。基于情感劳动价值的抽象性,尝试运用层次分析法建立乡村民宿经营者情感劳动价值评估体系,并以贵州省肇兴侗寨为案例地,应用模糊综合评价法围绕乡村民宿经营者、顾客、村民对情感劳动价值进行评估,用实证的方式考查该评估体系在民宿型乡村地区中的实用性和可行性。结果表明,情感劳动能够产生显著的顾客价值与经营者价值,尤其是极显著的乡村价值,推动民宿经营者积极开展情感劳动,引导民宿业更好地助力乡村振兴。     

不同信任环境下在线知识社区知识系统演化研究

信任作为在线知识社区中的社会影响因素,对社区中的成员进行沟通学习、知识共享有着重要的作用。不同的在线知识社区有着不同的信任环境,而信任环境的不同会影响社区中用户的学习模式和观点传播。基于此,本文提出了基于信任与Deffaunt的组合观点影响模型。信任模型主要将社区中的信任分为认知信任和情感信任,通过调节参数结构,对应不同信任环境中信任的动态演化过程。Deffaunt模型作为基本观点影响模型,模拟了不同信任环境下的在线知识社区的知识观点的演化过程。实验结果发现,信任环境的高低决定了社区中的观点是否收敛,并且社区中的群体理性人占比和信任程度都能影响观点的收敛速度。