The Insertion of Economic Cybernetics Students on the Romanian Labor Market in the Context of Digital Economy and COVID-19 Pandemic

The purpose of this paper is to provide evidence of the insertion of Romanian students of economic cybernetics on the labor market by connecting business environment expectations with the goals of a competitive digital economy. The research is organized around three hypotheses to address the issues of both non-employed and employed economic cybernetics students. A rank-ordered probit choice model was estimated to compute the probability that a certain skill requires improvement. The empirical results showed that the COVID-19 pandemic stimulated more cybernetics students to get a job in this period. Moreover, these students present the necessary level of digital skills to be employed, but other skills need improvement: skills of analysis and synthesis, adaptability in handling crisis situations and creativity. This research reveals the lack of working experience as the main cause for rejection after an interview and the students’ tendency to overestimate their salary. This study also identified barriers of the insertion on the labor market for these students with digital skills that were not the subject of previous studies. Moreover, the impact of the COVID-19 pandemic on their decision to get a job in this period is assessed and a few recommendations of skills improvements are provided. These results present practical implications for educational policies and the business environment in the context of achieving a competitive European digital economy. The limit of this research is given by the sample representativeness for cybernetics students only for Bucharest, but a future paper will ensure a representative sample at the national level.

Consumer-generated discourse on cannabis as a medicine: Review of techniques (Preprint)

BACKGROUND Medicinal cannabis is increasingly being used for a variety of physical and mental health conditions. Social media and online health platforms provide a valuable real time and cost-effective surveillance resource for individuals who use cannabis for medicinal purposes. This is especially important considering evidence for the optimal use of medicinal cannabis is still emerging. Despite the online marketing of medicinal cannabis to consumers, currently, there is no robust, regulatory framework to measure clinical health benefit or individual experience of adverse events. OBJECTIVE We reviewed research approaches and methodologies of studies that utilize online user-generated text to study the use of cannabis as a medicine. METHODS We conducted the review using PRISMA guidelines, searching Medline, Scopus, Web of Science and Embase databases from their respective inceptions until May 2021. Studies were included if they aimed to understand online user-generated text related to health conditions where cannabis is used as a medicine, or where health was mentioned in general cannabis conversations. RESULTS Thirty-eight articles were included in the review. Of these, Twitter was used three times more than other computer-generated sources including Reddit, online forums, GoFundMe, YouTube, and Google Trends. Analytic methods included sentiment assessment, thematic analysis (manual and automatic), social network analysis, and geographic analysis. CONCLUSIONS This study is the first to systematically review techniques utilized by research on consumer-generated text for understanding cannabis as a medicine. It is increasingly evident that consumer-generated data offers opportunities for a greater understanding of individual behavior, population health outcomes. Yet research using this data has some limitations that include difficulties in establishing sample representativeness, and a lack of methodological best practice. To address these, publicly available de-identified annotated data sources; determination of posts origins (organizations, bots, power users, or ordinary individuals); and more powerful analytical techniques can be employed.

An Encouraging Environment for the Development of Gifted Students within the Knowledge Society

The aim of our paper is to conduct a theoretical and empirical analysis of the relevance of an encouraging environment in the development and progress of gifted students within the modern knowledge society. In order to ensure the highest level of sample representativeness, the research was carried out on a sample of 106 teachers working with specialized classes for talented students, and teachers who had worked with those students at their previous stage of schooling. The study was conducted in schools belonging to the areas of the City of Nis and Kosovska Mitrovica (Republic of Serbia)*, by using the scaling technique. Through factor analysis, the following 5 most prominent features (factors) of an environment that encourages the development of gifted students within the knowledge society were extracted: 1) differentiated curricula, 2) encouraging problem-based learning, 3) integrated approach to learning, 4) encouraging research-based approach to learning, 5) developing logical and creative thinking skills. This research also found that the level of schooling of gifted students significantly determines the differences in teachers’ perceptions of the characteristics of an environment that encourages the development of gifted students, while school location was not a deciding factor.

Investigation of the saturated steam sampling method influence on the sample representativeness in chemical control systems at thermal power plants

The most important requirement for sampling is the sample representativeness, which is achieved by the design and location choice of sample nozzle, as well as the speed mode and the presence of sharp pressure drops in the saturated steam flow. The Ansys CFX software package simulates the sampling processes saturated steam in power units with low, medium and high pressure boilers which are used on operating thermal power plants. The saturated steam was sampled from low-pressure boiler by a single-strip probe with a Venturi nozzle, from the medium-pressure boiler was sampled by tapping a pipe at 90 to the main steam line, and the steam of the high – pressure boiler was sampled by a wellhead probe. In three sampling cases it is found that of saturated steam, the flow in the sample nozzle loses speed and decreases to values unacceptable for the selection of a representative sample-below tear rate of the moisture film from the surface. It is confirmed that in the industrial sampling conditions, the condition of speeds equality in the main steam line and in the sample nozzle is not met, which leads to a violation of the sample representativeness. The paper studies the change in the composition of the sampled saturated vapor sample after the film formation on the sample’s nozzle wall in relation to power units with ammonia dosing. It was found that the sample received by the chemical control analyzers is depleted due to the formation of a film and the ferrum and ammonia concentration in moisture droplets on the inner surface of the sampling line.

Rapid deployment of a community engagement study and educational trial via social media: implementation of the UC-COVID study

Background In response to the COVID-19 pandemic and associated adoption of scarce resource allocation (SRA) policies, we sought to rapidly deploy a novel survey to ascertain community values and preferences for SRA and to test the utility of a brief intervention to improve knowledge of and values alignment with a new SRA policy. Given social distancing and precipitous evolution of the pandemic, Internet-enabled recruitment was deemed the best method to engage a community-based sample. We quantify the efficiency and acceptability of this Internet-based recruitment for engaging a trial cohort and describe the approach used for implementing a health-related trial entirely online using off-the-shelf tools. Methods We recruited 1971 adult participants (≥ 18 years) via engagement with community partners and organizations and outreach through direct and social media messaging. We quantified response rate and participant characteristics of our sample, examine sample representativeness, and evaluate potential non-response bias. Results Recruitment was similarly derived from direct referral from partner organizations and broader social media based outreach, with extremely low study entry from organic (non-invited) search activity. Of social media platforms, Facebook was the highest yield recruitment source. Bot activity was present but minimal and identifiable through meta-data and engagement behavior. Recruited participants differed from broader populations in terms of sex, ethnicity, and education, but had similar prevalence of chronic conditions. Retention was satisfactory, with entrance into the first follow-up survey for 61% of those invited. Conclusions We demonstrate that rapid recruitment into a longitudinal intervention trial via social media is feasible, efficient, and acceptable. Recruitment in conjunction with community partners representing target populations, and with outreach across multiple platforms, is recommended to optimize sample size and diversity. Trial implementation, engagement tracking, and retention are feasible with off-the-shelf tools using preexisting platforms. Trial registration ClinicalTrials.gov NCT04373135. Registered on May 4, 2020

Waste LED Lamp Characterization: A Call for More Consistent and Well-Documented Study

Solid-state lighting has been replacing conventional lighting in the market, raising concerns for implementing an efficient end-of-life management system. Since LED waste streams have not been quite dominant, characterization studies (product-level characteristics, component-wise information, bill of materials, diversity, and differences) are inconsistent and having substantial gaps. This study investigates the end-of-life LED lamp literature, focusing on the bill-of-materials, and reveals that the characterization procedure suffers from a severe lack of sample representativeness. Consequently, characterization results are widely varied and not generalizable. Moreover, most of the studies did not inform and document the detailed sample characteristics, precluding the possibility of identifying reasons for variation. Combining available information from the recent studies, we present a mass distribution at the component level, exemplifying the prospect for meeting EU regulatory limit and the need for more insight at the lamp and component level. To fill the disconnection between lamp level characteristics and component and material content, we propose a characterization protocol that carefully documents lamp, component, and material level information by establishing a lamp-component–material composition nexus. The protocol may help researchers, policymakers, and industrial stakeholders conduct a systematic characterization, analyze complexities and prepare for a sustainable solution.

Rapid Deployment of A Community Engagement Study And Educational Trial Via Social Media: Implementation of The UC-COVID Study

Background: In response to the COVID-19 pandemic and associated adoption of scarce resource allocation (SRA) policies, we sought to rapidly deploy a novel survey to ascertain community values and preferences for SRA, and to test the utility of a brief intervention to improve knowledge of and values alignment with a new SRA policy. Given social distancing and precipitous evolution of the pandemic, Internet enabled recruitment was deemed the best method to engage a community-based sample. We quantify the efficiency and acceptability of this Internet-based recruitment for engaging a trial cohort and describe the approach used for implementing a health-related trial entirely online using off-the-shelf tools.Methods: We recruited 1,971 adult participants (≥18 years) via engagement with community partners and organizations and outreach through direct and social media messaging. We quantified response rate and participant characteristics of our sample, examine sample representativeness, and evaluate potential non-response bias. Results: Recruitment was similarly derived from direct referral from partner organizations and broader social media based outreach, with extremely low study entry from organic (non-invited) search activity. Of social media platforms, Facebook was the highest yield recruitment source. Bot activity was present but minimal and identifiable through meta-data and engagement behavior. Recruited participants differed from broader populations in terms of sex, ethnicity, and education, but had similar prevalence of chronic conditions. Retention was satisfactory, with entrance into the first follow-up survey for 61% of those invited. Conclusions: We demonstrate that rapid recruitment into a longitudinal intervention trial via social media is feasible, efficient, and acceptable. Recruitment in conjunction with community partners representing target populations, and with outreach across multiple platforms, is recommended to optimize sample size and diversity. Trial implementation, engagement tracking, engagement and retention are feasible with off-the-shelf tools using preexisting platforms.Trial Registration: ClinicalTrials.gov registration NCT04373135.