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This study provides evidence of the influence of perceived threat of COVID-19 on psychological well-being, mediated by negative emotions. In addition, our results confirmed moderating effects of the use of work and non-work technology. Individuals who used technology to a larger extent, experienced more negative emotions when they perceived a higher threat of COVID-19. This study contributes to a better understanding of the factors underlying the negative impact of the COVID-19 pandemic on our mental health and stresses the importance of adopting a mindful technology use 

We present a new chemical mechanism for Hg(0)/ Hg(I) / Hg(II) atmospheric cycling, including recent laboratory and computational data, and implement it in the GEOS-Chem global atmospheric chemistry model for comparison to observations. Our mechanism includes the oxidation of Hg(0) by Br atoms and OH radicals, with subsequent oxidation of Hg(I) by ozone and radicals, re-speciation of gaseous Hg(II) in aerosols and cloud droplets, and speciated Hg(II) photolysis in the gas and aqueous phases. The tropospheric Hg lifetime against deposition in the model is 5.5 months, consistent with observational constraints. The model reproduces the observed global surface Hg(0) concentrations and Hg(II) wet deposition fluxes. Br and OH make comparable contributions to global net oxidation of Hg(0) to Hg(II). Ozone is the principal Hg(I) oxidant, enabling the efficient oxidation of Hg(0) to Hg(II) by OH. BrHgOH and Hg(OH)2 are the initial Hg(II) products of Hg0 oxidation, re-speciate in aerosols and clouds to organic and inorganic complexes, and volatilize to photostable forms. Reduction of Hg(II) to Hg(0) takes place largely through photolysis of aqueous Hg(II)-organic complexes. 71% of model Hg(II) deposition is to the oceans. Major mechanism uncertainties for atmospheric Hg chemistry modeling include the concentrations of Br atoms, the stability and reactions of Hg(I), and the speciation of Hg(II) in aerosols and clouds with implications for photoreduction. 

In this theory paper, we set out to consider, as a matter of methodological interest, the use of quantitative measures of inter-coder reliability (e.g., percentage agreement, correlation, Cohen’s Kappa, etc.) as necessary and/or sufficient correlates for quality within qualitative research in engineering education. It is well known that the phrase qualitative research represents a diverse body of scholarship conducted across a range of epistemological viewpoints and methodologies. Given this diversity, we concur with those who state that it is ill advised to propose recipes or stipulate requirements for achieving qualitative research validity and reliability. Yet, as qualitative researchers ourselves, we repeatedly find the need to communicate the validity and reliability—or quality—of our work to different stakeholders, including funding agencies and the public. One method for demonstrating quality, which is increasingly used in qualitative research in engineering education, is the practice of reporting quantitative measures of agreement between two or more people who code the same qualitative dataset. In this theory paper, we address this common practice in two ways. First, we identify instances in which inter-coder reliability measures may not be appropriate or adequate for establishing quality in qualitative research. We query research that suggests that the numerical measure itself is the goal of qualitative analysis, rather than the depth and texture of the interpretations that are revealed. Second, we identify complexities or methodological questions that may arise during the process of establishing inter-coder reliability, which are not often addressed in empirical publications. To achieve this purposes, in this paper we will ground our work in a review of qualitative articles, published in the Journal of Engineering Education, that have employed inter-rater or inter-coder reliability as evidence of research validity. In our review, we will examine the disparate measures and scores (from 40% agreement to 97% agreement) used as evidence of quality, as well as the theoretical perspectives within which these measures have been employed. Then, using our own comparative case study research as an example, we will highlight the questions and the challenges that we faced as we worked to meet rigorous standards of evidence in our qualitative coding analysis, We will explain the processes we undertook and the challenges we faced as we assigned codes to a large qualitative data set approached from a post positivist perspective. We will situate these coding processes within the larger methodological literature and, in light of contrasting literature, we will describe the principled decisions we made while coding our own data. We will use this review of qualitative research and our own qualitative research experiences to elucidate inconsistencies and unarticulated issues related to evidence for qualitative validity as a means to generate further discussion regarding quality in qualitative coding processes. 

Despite efforts to diversify the engineering workforce, the field remains dominated by White, male engineers. Research shows that underrepresented groups, including women and minorities, are less likely to identify and engage with scientific texts and literacy practices. Often, children of minority groups and/or working-class families do not receive the same kinds of exposure to science, technology, engineering, and mathematics (STEM) knowledge and practices as those from majority groups. Consequently, these children are less likely to engage in school subjects that provide pathways to engineering careers. Therefore, to mitigate the lack of diversity in engineering, new approaches able to broadly support engineering literacy are needed. One promising approach is disciplinary literacy instruction (DLI). DLI is a method for teaching students how advanced practitioners in a given field generate, interpret, and evaluate discipline-specific texts. DLI helps teachers provide access to to high quality, discipline-specific content to all students, regardless of race, ethnicity, gender, or socio-economic status, Therefore, DLI has potential to reduce literacy-based barriers that discourage underrepresented students from pursuing engineering careers. While models of DLI have been developed and implemented in history, science, and mathematics, little is known about DLI in engineering. The purpose of this research is to identify the authentic texts, practices, and evaluative frameworks employed by professional engineers to inform a model of DLI in engineering. While critiques of this approach may suggest that a DLI model will reflect the literacy practices of majority engineering groups, (i.e., White male engineers), we argue that a DLI model can directly empower diverse K-16 students to become engineers by instructing them in the normed knowledge and practices of engineering. This paper presents a comparative case study conducted to investigate the literacy practices of electrical and mechanical engineers. We scaffolded our research using situated learning theory and rhetorical genre studies and considered the engineering profession as a community of practice. We generated multiple types of data with four participants (i.e., two electrical and two mechanical engineers). Specifically, we generated qualitative data, including written field notes of engineer observations, interview transcripts, think-aloud protocols, and engineer logs of literacy practices. We used constant comparative analysis (CCA) coding techniques to examine how electrical and mechanical engineers read, wrote, and evaluated texts to identify the frameworks that guide their literacy practices. We then conducted within-group and cross-group constant comparative analyses (CCA) to compare and contrast the literacy practices specific to each sub-discipline Findings suggest that there are two types of engineering literacy practices: those that resonate across both mechanical and electrical engineering disciplines and those that are specific to each discipline. For example, both electrical and mechanical engineers used test procedures to review and assess steps taken to evaluate electrical or mechanical system performance. In contrast, engineers from the two sub-disciplines used different forms of representation when depicting components and arrangements of engineering systems. While practices that are common across sub-disciplines will inform a model of DLI in engineering for K-12 settings, discipline-specific practices can be used to develop and/or improve undergraduate engineering curricula.