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Legislation in Germany and in many other countries states that electronic devices should be protected against fire. In accordance with this, most electronic and electrical products contain substances which are flame retarding, but have harmful environmental implications. Thus, the protection of the environment makes it necessary to eliminate these harmful substances. The described base material consists of silicone filled with alumina. Silicone is a non‐toxic material. The filler increases the thermal conductivity of the material. As a result of its good thermal properties, the material does not need flame retarding substances, but is still able to satisfy the fire protection requirements. The properties of the material itself and the construction allow the building of an excellent, non‐flame retarded and therefore environmentally friendly 3D‐circuit board.

In 2017, the Chinese Super League (CSL), the first professional football division in the People’s Republic of China (PRC), became the highest-spending league in the international players’ transfer market, with a total spending of €377m. Moreover, the government of the PRC is backing the CSL with an ambitious football plan. Therefore, the purpose of this paper is to examine the governance of the CSL by questioning the organisational viability of the league.

In addition to the relevant international literature, this study is based on 14 recent scholarly articles published in Mandarin from 2013 to 2018 to reflect the national academic debate. Moreover, website research on all CSL clubs has been conducted. The institutional analysis follows the integrative change model of Cunningham (2002) complemented by agency and bureaucracy theory.

The CSL still faces substantial governance problems caused by the divergence of goal setting, organisational inefficiencies and compliance issues. The organisational change is notably constrained by internal competitive value commitments and external power dependency.

The institutional findings on the CSL provide a starting point for empirical studies. The approach contributes to the theory of sport governance processes.

The material and insights are informative for decision makers to evaluate the competitiveness of the CSL.

This paper is the first international in-depth analysis of the governance of the CSL using the body of knowledge published in Mandarin.

As a response to the COVID-19 pandemic, both educators and students adapted to course delivery modes no longer centered on in-person interactions. Resiliency and self-regulation are key to success in online contexts, but the rapid transition to remote learning left many students without the necessary support to develop these skills. Much of the existing literature on self-regulation and resiliency focuses on cognitive processes and strategies such as goal orientation, time management, and mindset. However, the added stress and trauma of learning in the context of a global pandemic highlighted the many other factors relevant to students’ development of these skills. Drawing from the literature, the authors explore evidence-informed teaching practices to foster self-regulation and resiliency, highlight the power and privilege of being able to be resilient, advocate for the development of pedagogies of kindness, and emphasize the “how” of implementing techniques to best support students. The authors provide evidence-informed suggestions with the goal of assisting instructors and students during times of high stress, while acknowledging their limitations in addressing structural inequalities highlighted by the COVID-19 pandemic. Nonetheless, the authors argue that evidence-informed techniques and compassionate pedagogies adopted during a period of upheaval remain applicable to future in-person and online pedagogies.

Argues that currently many businesses are looking to reduce the environmental impact of their activities or products but sadly the results are often disappointing. Sustainable development remains elusive. The future clearly demands something different ‐ we need solution focused products that produce an E‐plus effect. These will increasingly dominate future markets and provide the key to a competitive edge. The challenges, and barriers, are, however, likely to be significant ‐ concurrently the environmental lobby is changing tactics, moving from problem/blame campaigning to preventive/solutions campaigning. Campaigners rightly point to the earth bank balance as continually overdrawn and unhealthy, with life support systems threatened and biodiversity declining. No one appears to re‐invest in this global bank balance. Withdrawals are easy, but investing is not so easy. With the E‐plus concept creativity and innovation will require different patterns of thinking from the people that have hitherto used their talent to create existing new products and markets or to survive hard times. Managers need not only promote a climate of innovation and creativity but do so in directions that are fundamentally different. Business talent and enterprise is poised to become a major player as a social force. The talent is out there and some of the new innovative thinking patterns are explained in this article through the description of simple examples from across Europe.

This study aims to propose a learning pattern analysis method which can improve a predictive model’s performance, as well as discover hidden insights into micro-level learning pattern. Analyzing student’s learning patterns can help instructors understand how their course design or activities shape learning behaviors; depict students’ beliefs about learning and their motivation; and predict learning performance by analyzing individual students’ learning patterns. Although time-series analysis is one of the most feasible predictive methods for learning pattern analysis, literature-indicated current approaches cannot provide holistic insights about learning patterns for personalized intervention. This study identified at-risk students by micro-level learning pattern analysis and detected pattern types, especially at-risk patterns that existed in the case study. The connections among students’ learning patterns, corresponding self-regulated learning (SRL) strategies and learning performance were finally revealed.

The method used long short-term memory (LSTM)-encoder to process micro-level behavioral patterns for feature extraction and compression, thus the students’ behavior pattern information were saved into encoded series. The encoded time-series data were then used for pattern analysis and performance prediction. Time series clustering were performed to interpret the unique strength of proposed method.

Successful students showed consistent participation levels and balanced behavioral frequency distributions. The successful students also adjusted learning behaviors to meet with course requirements accordingly. The three at-risk patten types showed the low-engagement (R1) the low-interaction (R2) and the non-persistent characteristics (R3). Successful students showed more complete SRL strategies than failed students. Political Science had higher at-risk chances in all three at-risk types. Computer Science, Earth Science and Economics showed higher chances of having R3 students.

The study identified multiple learning patterns which can lead to the at-risk situation. However, more studies are needed to validate whether the same at-risk types can be found in other educational settings. In addition, this case study found the distributions of at-risk types were vary in different subjects. The relationship between subjects and at-risk types is worth further investigation.

This study found the proposed method can effectively extract micro-level behavioral information to generate better prediction outcomes and depict student’s SRL learning strategies in online learning. The authors confirm that the research in their work is original, and that all the data given in the paper are real and authentic. The study has not been submitted to peer review and not has been accepted for publishing in another journal.