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Empirical evidence on how supervisors have perceived the changes and the implications of the COVID-19 pandemic on their supervision is scarce. This paper aims to examine how the changing landscape of doctoral education has affected supervision from the supervisors’ perspective.

This survey addressed change, challenges and impact in supervisory responsibilities due to COVID-19 pandemic. The survey was completed by 561 doctoral supervisors from a large multi-field research-intensive university in Finland.

Results show that supervisors estimated that their supervision had been negatively affected by the pandemic, but to a lesser extent than their doctoral candidates’ progress and well-being. In the changed landscape of supervision, the supervisors grappled with challenges related to recognising doctoral candidates’ need of help. Supervisors’ experiences of the challenges and the impact of changed circumstances varied depending on the field and the position of the supervisor, whether they supervised part- or full-time candidates, and the organisation of supervision.

The slowed-down progression and diminishing well-being of doctoral candidates reported by supervisors is likely to influence supervision in a delayed way. Supervisors may be anticipating some issues with stalled studying and stress, but the question is the extent to which they are prepared to handle these as they emerge in supervision encounters. The fact that the experiences varied across field, position, organisation of supervision and the type of candidates (full or part time) suggests that support provided for supervisors to overcome challenges needs to be tailored and engineered.

This study contributes to the literature on doctoral supervision by exploring the impact of transitioning to online supervision and the rapid changes in doctoral supervision as a consequence of the recent global pandemic.

The COVID-19 pandemic has had its impact on research and researchers, potentially influencing the future of academia. Yet, to the best of the authors’ knowledge, there are no empirical studies on the alignment between supervisors’ and supervisees’ estimates of the impact of COVID-19. This study aims to contribute to bridging this gap by exploring PhD candidates’ and supervisors’ perceptions of the impact of COVID-19 on candidates’ study progress and study well-being, and whether the estimates were related to supervisors’ and supervisees’ well-being.

A total of 768 PhD candidates and 561 doctoral supervisors from a large multifield research-intensive university in Finland participated in this quantitative study. Data were collected with the doctoral experience survey and the supervisory experience survey.

In general, the results show that both supervisors and supervisees recognised the negative impact of the pandemic on candidates’ well-being and progress, and their perceptions were quite well aligned. However, supervisors estimated that the impact had been more detrimental than the supervisees did. The results also show that the supervisors’ perceptions of the negative impact of COVID-19 on candidates’ progress and well-being were related to reduced levels of their own well-being.

Results can be used in developing effective support means for both the supervisors and supervisees to overcome the hardships caused by the COVID-19 pandemic and to avoid long-term negative consequences for the candidates in degree completion, career trajectories and the future of the academy.

In the development processes of a product’s market life cycle, there are three phases of an enterprise’s innovation: new product development, production processes, and product management. In this article, the analyses of benefit and costs, value, and profit to companies are discussed in different stages. New logistics features that appear in an enterprise’s supply chain based on innovative modeling are discussed. Then a logistics model and its technical system based on the classified logistics center are established, which are appropriate for innovative modeling within an agile supply chain. Using the basic theory and techniques of ‘extenics’, the formal conception of innovative modeling-based manufacture in logistics is presented, and the matter-element models are established. Finally, a case study demonstrates the results.

Data has become a factor of production. This occurs when history enters the era of big data, in which technologies such as artificial intelligence, cloud computing and blockchain are used to collect, manipulate, mine and process data. Data is a special product of labor, a sub-derivative of other production factors.

The data factor has a dual attribute: being physical (technical) and social. The social attribute of the data factor can not only materialize the technical attribute but also amplify it. In other words, the data has a multiplication effect on the allocation efficiency of other production factors. The social attribute of the data is brought out via the technical attribute as the medium. From a technical perspective, this medium is strongly adhesive, and after being bonded with other factors of production, it will only lead to a physical reaction and not change the nature of other factors.

However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

Therefore, to get a scientific understanding of the dual attribute and its interaction effects on the data factor, it is necessary to take the following steps. We should promote institutional design that amplifies the positive externality, with a focus on facilitating public data sharing and improving the value of commercial data development. Also, we need to strengthen institutional arrangements that prevent and control the negative externality by emphasizing data supervision based on data types and levels as well as the rule of law.

After the 19th CPC national congress, Chinese Communist Party and the government put forward higher requirements for the development of coastal zones, and it is urgent to establish an integrated coastal zone management system, so as to better guarantee the construction of maritime powers and regional coordinated development. The purpose of this paper is to aim at re-examining and positioning China’s integrated coastal zone management.

This paper sorts out the current situation of coastal zone resources and environment, summarizes prominent problems and clarifies the path of comprehensive management of coastal zone based on the typicality and comprehensiveness of coastal ecosystem.

Coastal zone is a typical area of “life community shared among mountains, rivers, forests, fields, lakes and grass.” However, there are three prominent problems at present, namely, separation between land and sea, separation among industry sectors and separation among administrative jurisdictions. Coastal zone planning and legislation are important measures to realize the comprehensive management of coastal zone.

This paper puts forward some suggestions on the reform of coastal zone management from the perspective of planning and legislation.

The purpose of this paper is to communicate a method to perform simultaneous topology optimization of component and support structures considering typical metal additive manufacturing (AM) restrictions and post-print machining requirements.

An integrated topology optimization is proposed using two density fields: one describing the design and another defining the support layout. Using a simplified AM process model, critical overhang angle restrictions are imposed on the design. Through additional load cases and constraints, sufficient stiffness against subtractive machining loads is enforced. In addition, a way to handle non-design regions in an AM setting is introduced.

The proposed approach is found to be effective in producing printable optimized geometries with adequate stiffness against machining loads. It is shown that post-machining requirements can affect optimal support structure layout.

This study uses a simplified AM process model based on geometrical characteristics. A challenge remains to integrate more detailed physical AM process models to have direct control of stress, distortion and overheating.

The presented method can accelerate and enhance the design of high performance parts for AM. The consideration of post-print aspects is expected to reduce the need for design adjustments after optimization.

The developed method is the first to combine AM printability and machining loads in a single topology optimization process. The formulation is general and can be applied to a wide range of performance and manufacturability requirements.

Currently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.

Driven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.

From the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

To overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

Deployment of deep neural networks on embedded devices is becoming increasingly popular because it can reduce latency and energy consumption for data communication. This paper aims to give out a method for deployment the deep neural networks on a quad-rotor aircraft for further expanding its application scope.

In this paper, a design scheme is proposed to implement the flight mission of the quad-rotor aircraft based on multi-sensor fusion. It integrates attitude acquisition module, global positioning system position acquisition module, optical flow sensor, ultrasonic sensor and Bluetooth communication module, etc. A 32-bit microcontroller is adopted as the main controller for the quad-rotor aircraft. To make the quad-rotor aircraft be more intelligent, the study also proposes a method to deploy the pre-trained deep neural networks model on the microcontroller based on the software packages of the RT-Thread internet of things operating system.

This design provides a simple and efficient design scheme to further integrate artificial intelligence (AI) algorithm for the control system design of quad-rotor aircraft.

This method provides an application example and a design reference for the implementation of AI algorithms on unmanned aerial vehicle or terminal robots.

This article aims to consider teacher's views about intervisitations regarding its application and its usefulness as a community-enhancer. Many educators venture into the world of teaching because they love learning and value learning from their peers (rather than merely from text or administrators); however, teacher reservations or hesitations towards the practice of engaging in intervisitations do exist and can serve as an obstacle.

The findings reported in this study resulted from the analysis of two teacher's perspectives towards classroom intervisitations. The subset of data presented in this study resulted from the surveys and semi-structured interviews that were conducted. Qualitative methodology was used to address the research question as it allows for a greater exploration, description and ideally the emotions of participants/teachers. The coding process consisted of open coding, which then led to axial coding and the elevation of codes to themes.

In this study, teacher buy-in would be enhanced through the protocol feeling more personalized, less-dictated and more flexible in its execution, especially through the support of administrators and district leaders. In addition, teacher mindsets and perceptions also need some reshifting and should be part of the professional development process involving intervisitation roll-outs as any hesitations/limitations/and lack of willingness need to be honed in on and prioritized. Lastly, limiting teachers from an appropriate amount of time to complete such work may also encourage shallow collaboration among teachers instead of in-depth reflexive practice. By prioritizing intervisitations and/or inter-teacher collaboration in the building and allowing teachers to embark on professional development sessions with each other as a means of growing as a teacher and community, all will flourish.

Through examining the narratives of two educators, it was found that teacher willingness to partake in intervisitations is dependent on the school climate, particularly with regards to trust and a yearn-to-learn among inter-school peers and administrators. In addition, providing ample time and educating teachers on the benefits of such practices enhances one's wanting to independently venture into such work.