浅析大学物理微积分思想与矢量思想

本文探讨了微积分思想和矢量思想在大学物理教学中的应用,致力于总结出一个可靠的应用模式用于提高大学物理教学的质量。     

农业绿色发展的内涵与评价研究

[目的]推进农业绿色发展是农业发展观的一场深刻革命,关键在体制机制创新,建立一套适用于全国不同地区农业绿色发展评价的指标体系与评价办法,从而增强各地农业绿色发展责任意识,为推进农业绿色发展提供方向指导和决策参考。[方法]通过对国内外相关研究的梳理分析,对新时代我国农业绿色发展的内涵进行界定,进一步明确农业绿色发展的评价思路。[结果]在此基础上,构建包括4个一级指标、19个二级指标的农业绿色发展定量评价体系与由6个一级指标、15个二级指标构成的农业绿色发展定性评价指标体系,提出了归一化法和标准化系数法等评价方法。[结论]政府要加快建立完善农业绿色发展组织体系、领导干部农业生态资源离任审计以及农业绿色发展考核奖惩制度等制度体系,进一步强化农业生态资源数据采集与统计体系建设,加快更新农业资源环境统计条目,为农业绿色发展评价提供数据支撑。     

Exploring the use of content analysis methodology in consumer research

Content analysis is a viable way to thematise consumer experiences. The purpose of this review study is to examine the use of content analysis in consumer research (1977–2017). The authors explore how content analysis has been used. The reviewed studies address consumer experiences. The results show that qualitative content analysis is not used as a method in its own right; it is more often applied as a supplement to quantitative testing. There is also a lack of rigorous reporting of methodologies in many studies. The systematic review provides four propositions, content analysis studies: 1) vary in execution and reporting; 2) have a tendency towards methodological vagueness; 3) do not apply content analysis as a sole method; 4) are versatile. The study can also serve as point of departure for novice researchers wishing to engage with content analysis research. We suggest that further research is needed to explore the use of qualitative methodologies in consumer research.     

Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

This paper contributes to the nascent literature on nowcasting and forecasting GDP in emerging market economies using big data methods. This is done by analyzing the usefulness of various dimension-reduction, machine learning and shrinkage methods, including sparse principal component analysis (SPCA), the elastic net, the least absolute shrinkage operator, and least angle regression when constructing predictions using latent global macroeconomic and financial factors (diffusion indexes) in a dynamic factor model (DFM). We also utilize a judgmental dimension-reduction method called the Bloomberg Relevance Index (BRI), which is an index that assigns a measure of importance to each variable in a dataset depending on the variable’s usage by market participants. Our empirical analysis shows that, when specified using dimension-reduction methods (particularly BRI and SPCA), DFMs yield superior predictions relative to both benchmark linear econometric models and simple DFMs. Moreover, global financial and macroeconomic (business cycle) diffusion indexes constructed using targeted predictors are found to be important in four of the five emerging market economies that we study (Brazil, Mexico, South Africa, and Turkey). These findings point to the importance of spillover effects across emerging market economies, and underscore the significance of characterizing such linkages parsimoniously when utilizing high-dimensional global datasets.     

All of work? All of life? Reconceptualising work‐life balance for the 21st century

This paper argues that the study of work‐life balance to date has, in the main, adopted a restricted conception of both “work” and “life”, which does not take account of recent developments in life worlds, working arrangements and employment relationships. “Life” has hitherto been viewed as largely comprising caring activities for dependent children, whereas “work” has been premised largely on a traditional model of work, characterised by full‐time, permanent employment with one employer and a conventional understanding of what work involves. This means that extant research and theory only provides a partial view of the work‐life needs and experiences of the workforce. In the paper, we propose extending conceptions of both work and life to incorporate different life worlds and social groups and different working arrangements and employment relationships.     

高职院校环境监测实践教学改革探索

本文分析了高职院校环境监测实践教学中存在的问题,从实践参与教学模式、实践教学方法及考核、评价方式等方面进行了一系列的探索和尝试。     

‘I didn't feel like I was alone anymore’: evaluating self‐organised employee coping practices conducted via Facebook

The long‐term fracturing of the labour movement has led to increased attention to employee coping practices under new management practices and labour processes. However, the literature caters little for the recent rise of employees taking to social networking sites (SNSs), such as Facebook, to find ways to cope with the pressures of contemporary employment. To explore the self‐organised coping qualities of SNSs, interviews were conducted with front line workers, employed by a large anti‐trade union US retailer, who contribute to a self‐organised Facebook group set up as a place for fellow employees to deal with collective employment‐related problems. The main findings suggest employee self‐organised Facebook groups represent an important development and extension to the coping practices available to individual and groups of employees. The main implication of the findings is that Facebook groups appear to strengthen and widen the options for employee resilience in an age of continuing trade union retreat.     

A comparison of programming languages in macroeconomics

We solve the stochastic neoclassical growth model, the workhorse of modern macroeconomics, using C++14, Fortran 2008, Java, Julia, Python, Matlab, Mathematica, and R. We implement the same algorithm, value function iteration, in each of the languages. We report the execution times of the codes in a Mac and in a Windows computer and briefly comment on the strengths and weaknesses of each language.     

Repeated moral hazard and recursive Lagrangeans

This paper shows how to solve dynamic agency models by extending recursive Lagrangean techniques à la Marcet and Marimon (2011) to problems with hidden actions. The method has many advantages with respect to the promised utilities approach (Abreu et al., 1990): it is a significant improvement in terms of simplicity, tractability and computational speed. Solutions can be easily computed for hidden actions models with several endogenous state variables and several agents, while the promised utilities approach becomes extremely difficult and computationally intensive even with just one state variable or two agents.