The Blursday Database: Individuals’ Temporalities in Covid Times

The Covid-19 pandemic and associated lockdowns triggered worldwide changes in the daily routines of human experience. The Blursday database provides measures of subjective time and related processes from more than 2,800 participants (over 9 countries) tested on 14 questionnaires and 15 behavioral tasks during the Covid-19 pandemic. The easy-to-process database and all data collection tools are made fully accessible to researchers interested in studying the effects of social isolation on temporal information processing, time perspective, decision-making, sleep, metacognition, attention, memory, self-perception, and mindfulness. Blursday also includes vital quantitative statistics such as sleep patterns, personality traits, psychological well-being, and lockdown indices. Herein, we exemplify the use of the database with novel quantitative insights on the effects of lockdown (stringency, mobility) and subjective confinement on time perception (duration, passage of time, temporal distances). We show that new discoveries are possible as illustrated by an inter-individual central tendency effect in retrospective duration estimation.

Experience in using phyto-structures for tertiary treatment of urban wastewater

This paper considers the experimental biocenosis development for tertiary wastewater treatment with respect to the climate features of South of Russia. The plant species with advantaged biotechnical characteristics that acceptable for steppe environment are described. The growing season productivity of the highest aquatic vegetation for the phyto-structures first year exploitation is determined. The quantitative statistics for indicative microorganism populations is calculated. The data obtained allows to measure the ecological effectiveness of wastewater treating phyto-system and to develop a cheap and recyclable biocenosis for the inhabited localities with temperate continental climate.

The Development and Application of Machine Learning in Atmospheric Environment Studies

Machine learning (ML) plays an important role in atmospheric environment prediction, having been widely applied in atmospheric science with significant progress in algorithms and hardware. In this paper, we present a brief overview of the development of ML models as well as their application to atmospheric environment studies. ML model performance is then compared based on the main air pollutants (i.e., PM2.5, O3, and NO2) and model type. Moreover, we identify the key driving variables for ML models in predicting particulate matter (PM) pollutants by quantitative statistics. Additionally, a case study for wet nitrogen deposition estimation is carried out based on ML models. Finally, the prospects of ML for atmospheric prediction are discussed.

Consequence of Covid-19 lockdown on household food security: Voices from Hoima City, Uganda

Purpose: To investigate the consequence covid-19 lockdown on food security among a cohort of peri-urban households in Hoima city. Research methodology: A descriptive survey was employed targeting 186 respondents. Data were collected using a researcher-designed self-administered questionnaire and analysed using quantitative statistics. Specifically, chi-square was employed to establish whether the hypothesis held sway; also, regression analysis was employed with a view of forecasting the degree of change in household food security due to covid-19 lockdown. Results: The period of lockdown announced and implemented by the government had a positive consequence on food security. Nonetheless, the economic hardships overturned the successes otherwise achieved as a number of households sold off much of the food so as acquire other household items. Recommendations: While the government is credited for instituting a lockdown as a means to reduce the spread of covid-19 virus, it is recommended that city authorities are encouraged to boost urban farming by distributing agri-inputs to households in the peri-urban seeing that their daily incomes are already constrained. Contribution: The findings of this study may be useful to city authorities in Uganda in evolving a guide on integration of food security as a cross-cutting issue in the overall strategic disaster management plan. This article makes an input to the budding field of understanding by underlining inroads that can generate more sustainable urban community livelihoods through food security.

The study of local beef market structure in Jakarta, Indonesia

This study was implemented to determine benefit distribution from the value chain and analyze Jakarta’s local beef market’s price determination processes. The research method was a survey, and a purposive sampling technique was used to select key informants. A structured questionnaire was designed to collect the data supplemented with focus group discussion. Data were analyzed using descriptive quantitative statistics. The descriptive statistics revealed a market structure based on the elements to have many consumers and suppliers with ex-imported cattle (98 percent) and local cattle from East Nusa Tenggara and East Java (2 percent) fulfilled the demand in a year. Middlemen in the supply chain have more significant benefits than producers (feedlots and farmers) and consumers. The implication of the study is developing a business model for modern retail or butchering-based meat shops that increases the added value of local meat and benchmarking of a long beef chain efficiency at post-cutting (downstream). The development of a modern retail business model is expected to drive the shifting system sales of beef from a commodity to a product basis.

Unprofessional conduct by nurses: A document analysis of disciplinary decisions

Background: A small minority of nurses are investigated when they fail to meet the required professional standards. Unprofessional conduct does not just affect the nurse but also patients, colleagues and managers. However, it has not been clearly defined. Objective: The objective was to identify unprofessional conduct by registered nurses by examining disciplinary decisions by a national regulator. Design: A retrospective document analysis. Data and research context: Disciplinary decisions delivered to 204 registered nurses by the Finnish national regulatory authority from 2007 to 2016. The data were analysed with quantitative statistics. Ethical consideration: The study received permission from the Finnish National Supervisory Authority for Welfare and Health and used confidential documents that were supplied on the basis of complete anonymity and confidentiality. Findings: The mean age of the registered nurses who were disciplined was 44 years and 81% were female. Two-thirds had worked for their employer for 5 years or less, 53% had two or more employers and 18% had a criminal history. All the decisions included a primary reason for why the nurses were investigated, but there were also 479 coexisting reasons. In most cases, unprofessional conduct was connected to substance abuse (96%). In addition, stealing of medicine, a decreased ability to work and neglect of nursing guidelines were reported. Discussion: We found that the nurses were investigated for unprofessional conduct for complex combinations of primary and coexisting reasons. Our study highlighted that more attention needs to be paid to the key markers for unprofessional conduct. Conclusion: Unprofessional conduct is a complex phenomenon that is connected to nurses’ individual and working backgrounds and has an impact on their work performance. More research is needed to identify how nursing communities can detect, manage and limit the serious effects and consequences of unprofessional conduct.

Improving Environmental Care Characters Through E-Modules Based on Local Wisdom Mangrove Ecotourism

Teachers are less able to develop electronic modules that can improve student character. Electronic modules should be designed with materials that take advantage of the environment around students so that learning activities seem more real. This research was conducted to analyze the relationship between caring for the environment, integrated with an electronic module based on local wisdom of mangrove ecotourism. This type of research is quantitative associative. The sample in this study amounted to 22 people, using a sampling technique called purposive sampling. The data collection instrument used was a questionnaire. Data analysis used descriptive qualitative and quantitative statistics. The results in this study are that the environmental care character possessed by students has a good category, seen from the environmental care character indicator after using an electronic module based on local wisdom, strengthened by the correlation results obtained by 0.885 and produces a very good relationship, wherein using the electronic module has a close relationship with the character of caring for the environment. Therefore, both students and teachers need to implement electronic modules based on local wisdom that can be used to instil environmental care characters in students.

The Development Status of Decommissioning Technology of Nuclear Facilities: An Insight From Patents

The decommissioning technology of nuclear facilities has been one of the most important research directions of nuclear industry for several decades, and further enhancements are being carried out in the world. The global published patents about the decommissioning technology of nuclear facilities are investigated in this work. The technology forecasting and the development strategy of the decommissioning technology of nuclear facilities was provided from the view of patents, based on the nations, the technology field, the trend in the number of patents applications. This work will contribute to understanding the advanced developments of the decommissioning technology of nuclear facilities by a new perspective. Through quantitative statistics and content analysis, the understanding of relevant industries and technology development trend of personnel in the industry is promoted from the perspective of open patent data, a complex of technology, law and economy. Through the technology and economy behind the patent data to ensure its reliability and authenticity, this paper puts forward suggestions and prospects for the practitioners in the field of nuclear facilities decommissioning from the aspects of how to combine the research and analysis of patent situation with the development of the industry.

Teacher’s Perception of Self-Directed Learning and EFL Students’ Learning Autonomy during COVID-19 Pandemic

The COVID-19 pandemic has forced academic institutions in Indonesia to implement online learning. As a result, teachers must prepare online learning strategies that can build students’ independent learning. This study aims to analyze teacher perceptions of independent learning, assigned activities in online learning, and independent learning components in activities. This study uses an embedded mixed-method approach. The methods used to collect data are observation, interviews, and questionnaires. The instruments used to collect data are self-rated questionnaires, observation tables, and classification tables. The technique used in analyzing the data is descriptive qualitative and quantitative statistics. The results of this study indicate that teachers feel they have knowledge about and in implementing Independent Learning. The teacher carries out the learning process in three parts: pre-activity, initial activity, and post-activity. However, there are only three components of Self-Directed Learning that are included in the action. In its activities, self-directed learning is when the teacher provides material, individual assignments, and assistance when needed. However, independent learning is no longer a reflection on post-activity because there is no feedback. Therefore, more effective and exciting learning activities are required.

Teacher’s Ability in Preparing Lesson Plans for English as a Foreign Language During the Pandemic in the Senior High School

There are still many students who do not follow online learning well. Students who are not focused on online learning. In addition, there are still many teachers who find it challenging to design appropriate learning for students. This will have an impact on learning activities that cannot run optimally, especially in English subjects. The negative impact of this is that the ability of students will decrease. This study aims to analyze the teacher's ability to prepare EFL lesson plans through Google Classroom, the teacher's obstacles in compiling EFL lesson plans through Google Classroom, and students' obstacles in learning English as a foreign language (EFL) through Google Classroom. The method used in this study is a mixed-method. The method used to collect data is observation, interviews, and questionnaires. The instrument used to collect data is a questionnaire. Before data collection, the three instruments were validated and tested empirically. The technique used to analyze the data is descriptive qualitative and quantitative statistics. The results showed that the ability of teachers to prepare EFL lesson plans through Google Classroom was still lacking. In addition, EFL students also encounter obstacles in learning English as a foreign language (EFL) through Google Classroom.