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Open Educational Resources (OER) have been researched for a long time in the open education field. Researchers are now shifting their focus from resources to practices for delivering open education, an area called Open Educational Practices (OEP). However, there is little information in the related literature regarding the design of an OEP-based course or the impact of these types of courses. Therefore, this study designs a new OEP-based course at a public university for teaching family education during the COVID-19 pandemic. It also investigates its impact on learning motivation and teachers’ perceptions. In this context, a practical pilot experiment using both qualitative and quantitative methods was conducted. Specifically, 36 learners participated in this experiment. The obtained findings highlight: (1) an innovative design framework for OEP-based courses that teachers can refer to in their contexts; (2) that learners had a high motivation level in terms of knowledge achievements, individual connection and engagement when taking the OEP-based course; and (3) several advantages and challenges of the OEP-based course from the teacher’s and learners’ perspectives. For instance, the teacher reported the fear of losing control over the learning process when applying OEP. The findings of this paper can help researchers and educators in adopting OEP in higher education especially in times of crises, as well as increase the sustainability of OEP, hence contributing to open education development.

Chinese medicinal herbs (CMHs) have been used for thousands of years because of their significant properties regarding the prevention and treatment of diseases, such as COVID-19. There is an increasingly diminishing supply of wild medicinal resources, and the demand is greater than the supply. Ecological balance and the conservation of natural Chinese medicinal herbs are serious issues in sustainable development, which requires the minimum requirements to be met without compromising the resources of future generations, especially with respect to the maintenance of production and consumption as well as the quality control of CMHs. Hong Kong is an urban business city, busy with work and the fast pace of life. The sustainable development of CMHs is difficult in a huge population situated in an area with very scarce land coverage. The conservation of CMHs in urban horticulture is extremely neglected because people lack living space; for example, Aquilaria Sinensis (the incense tree), also called “pak muk heung” in Cantonese, was an indigenous species that was illegally logged in the past. This led to detrimental effects on the population density and genetic diversity of the species. There is no doubt that Hong Kong is required to set up a management model in community facilities for these emerging modern social configurations, such as building a Chinese herbal garden for the conservation and promotion of a healthy urban environment and giving people a chance to gain more information on CMHs. The current study employed problem analysis and strategic decisions for the sustainable development of 62 kinds of CMHs in a Chinese herbal garden, which converged with some medicinal itineraries of Lingnan herbal medications, and implemented a theoretical framework of management models for ten secondary schools, e.g., the Aroma garden of the L’Occitane at the Technological and Higher Education Institute of Hong Kong (THEi) Tsing Yi campus and Land from the Far East Consortium International Limited in Sai Kung Pak Kong. In the present original article, we would like to establish a sustainable management model for Chinese herbal gardens in an urban city. The sustainable development model for the Chinese herbal gardens is based on five major aspects: (1) land resources, (2) manpower planning, (3) economy, (4) education or training, and (5) ecosystem (cultivation). These are the essential factors of management and are implemented in our Chinese herbal gardens. We aim to find a suitable management model for Chinese herbal gardens and to promote it in other urban cities.

AbstractPersonal greenhouse gas (PGHG) emissions were crucial for achieving carbon peak and neutrality targets. The accounting methodology and driving forces identification of PGHG emissions were helpful for the quantification and the reduction of the PGHG emissions. In this study, the methodology of PGHG emissions was developed from resource obtaining to waste disposal, and the variations of Shanghainese PGHG emissions from 2010 to 2020 were evaluated, with the driving forces analysis based on Logarithmic Mean Divisia Index (LMDI) model. It showed that the emissions decreased from 3796.05 (2010) to 3046.87 kg carbon dioxides (CO2) (2014) and then increased to 3411.35 kg CO2 (2018). The emissions from consumptions accounted for around 62.1% of the total emissions, and that from waste disposal were around 3.1%, which were neglected in most previous studies. The PGHG emissions decreased by around 0.53 kg CO2 (2019) and 405.86 kg CO2 (2020) compared to 2018 and 2019, respectively, which were mainly affected by the waste forced source separation policy and the COVID-19 pandemic. The income level and consumption GHG intensity were two key factors influencing the contractively of GHG emissions from consumption, with the contributing rate of 169.3% and − 188.1%, respectively. Energy consumption was the main factor contributing to the growth of the direct GHG emissions (296.4%), and the energy GHG emission factor was the main factor in suppressing it (− 92.2%). Green consumption, low carbon lifestyles, green levy programs, and energy structure optimization were suggested to reduce the PGHG emissions.

Plastic pollution is recognized as one of the most urgent global environmental concerns. China is the top producer and consumer of plastics and creates the most plastic waste globally. To evaluate policy options to control plastic pollution in China, we first reviewed the relevant policies and action plans in place. Then, we examined plastic-material flows and changes at the national level based on officially published data to evaluate the current situation and efficacy of policies at the macro-level. Results showed that 2016, the start of the 13th Five-Year Plan, was a pivotal year in the history of China’s plastic policies tackling plastic issues nationally and internationally. Since 2016, the growth trend in the production and consumption of plastic products has slowed and the recycling rate has risen, surpassing 30% in 2021. To further tackle plastic pollution, key suggestions with important policy implications were provided, covering better integration of policies, the combined management of vertical–horizontal governance, tracking-system implementation, the introduction of a quality-certification system, the development of behaviour-based consumer-oriented solutions, the promotion of stakeholder collaboration, and the need for appropriate post-COVID-19 policies.

Coronavirus is a fatal disease that affects mammals and birds. Usually, this virus spreads in humans through aerial precipitation of any fluid secreted from the infected entity's body part. This type of virus is fatal than other unpremeditated viruses. Meanwhile, another class of coronavirus was developed in December 2019, named Novel Coronavirus (2019-nCoV), first seen in Wuhan, China. From January 23, 2020, the number of affected individuals from this virus rapidly increased in Wuhan and other countries. This research proposes a system for classifying and analyzing the predictions obtained from symptoms of this virus. The proposed system aims to determine those attributes that help in the early detection of Coronavirus Disease (COVID-19) using the Adaptive Neuro-Fuzzy Inference System (ANFIS). This work computes the accuracy of different machine learning classifiers and selects the best classifier for COVID-19 detection based on comparative analysis. ANFIS is used to model and control ill-defined and uncertain systems to predict this globally spread disease's risk factor. COVID-19 dataset is classified using Support Vector Machine (SVM) because it achieved the highest accuracy of 100% among all classifiers. Furthermore, the ANFIS model is implemented on this classified dataset, which results in an 80% risk prediction for COVID-19.

The main goal of this study is to evaluate the impact of restrictive measures introduced in connection with COVID-19 on consumption in renewable energy markets. The study will be based on the hypothesis that similar changes in human behavior can be expected in the future with the further spread of COVID-19 and/or the introduction of additional quarantine measures around the world. The analysis also yielded additional results. The strongest reductions in energy generation occurred in countries with a high percentage (more than 80%) of urban population (Brazil, USA, the United Kingdom and Germany). This study uses two models created with the Keras Long Short-Term Memory (Keras LSTM) Model, and 76 and 10 parameters are involved. This article suggests that various restrictive strategies reduced the sustainable demand for renewable energy and led to a drop in economic growth, slowing the growth of COVID-19 infections in 2020. It is unknown to what extent the observed slowdown in the spread from March 2020 to September 2020 due to the policy’s impact and not the interaction between the virus and the external environment. All renewable energy producers decreased the volume of renewable energy market supply in 2020 (except China).

This study aims to develop and test a methodological approach to assess the system of food quality and safety in the COVID-19 pandemic. To achieve the study objectives, a multi-country research project was implemented with 425 enterprises from Russia, Azerbaijan, Ukraine, and Belarus. The application of the developed methodological approach resulted in comparable assessments of the various criteria of the food safety and quality assurance system in supply chains. This makes it possible to implement continuous monitoring of the state of the food safety and quality assurance system in the enterprises. In addition, the study identified critical weaknesses in the safety system, including a very low level of assessment by enterprises of the impact of WHO advisory protocols. This greatly increases the risks associated with food safety in the COVID-19 pandemic. Urgent action is required to increase the confidence of food supply chain actors in WHO recommendations and national food safety and quality protocols. The conducted assessments showed that a significant proportion of enterprises did not implement a food safety system. One out of five of the respondents claimed to have implemented safety systems at an enterprise in accordance with the standards recognized by the Global Food Safety Initiative. Only 2% declared the introduction of HACCP at an enterprise, which is logical given the high mistrust of WHO recommendations. The proposed approach can be used in the real sector of the economy to monitor the food safety and quality assurance system in the supply chain at the regional, sectoral and national levels.

This paper contributes to the study of regional economic resilience by analyzing the characteristics and mechanisms of resilience under different shock situations. The paper focuses on the resistance dimension of resilience and analyzes the mechanisms of influence from structural and agency-based factors. Our findings reflect that the regional economic resilience characteristics of resource-based cities in China in response to the 2008 financial crisis and the COVID-19 pandemic vary significantly. We find that the economic resilience has positive spatial autocorrelation characteristics. The regions with strong ability to deal with the shocks can promote resistance in the surrounding regions through their spatial spillover effect. Both structural and agency-based factors play significant roles in regional economic resilience under different shock situations, but the direction of the effect varies significantly. The agency-based factors have a more important role in regional economic resilience. The findings suggest that the nature of different shock situations deserves greater attention in the analysis of regional economic resilience. The mechanisms of structural and agency-based factors may change under different shock situations, and the spatial correlation characteristics of regional economic resilience and the spatial spillover effects should be taken into consideration.