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This article examines the career development of international football coaches in the context of their transnational migration. Previous research has mainly relied on the normative stages models to explain coaching career development, which has limitations in capturing the complexity and diversity of coach career trajectories, particularly in terms of unique individual experiences and contextual impacts on their career development. Drawing upon the theory of careership, this article seeks to bridge the gap by focusing on how individual coaches navigate their careers according to their horizon for action. Careership theory provides a useful lens through which to examine the interactions between individuals and their contexts, in gaining a more nuanced understanding of how these interactions shape career trajectories. Semi-structured interviews were conducted with eight international coaches who worked in China to gather qualitative data. The results show that the migration of coaches closely intertwined with their career development in a variety of ways, which were manifested in different career horizons for migration within two distinct stages of career development: (1) 'career-consolidation' reflecting the willingness to stabilise and solidify the career pathways, and (2) 'career-reformulation' highlighting the desires or needs to change the current career trajectories. The findings of this article suggest that career development is a multifaceted process encompassing normative, longitudinal steps, individualised approaches, objectives, constraints and unexpected events. Analysing coaches' horizons for action allows researchers and practitioners (e.g. coach educators) to gain a holistic picture of individual and contextual distinctions within the longitudinal stages of coaching career development. [ABSTRACT FROM AUTHOR]

The mining and metallurgical industry is a fundamental sector of China's industry, consisting of various subdivisions such as mining, mineral processing, smelting, etc. Mining and metallurgical equipment are characterized by harsh operating conditions, complex operation and maintenance, high energy consumption, significant pollution, substantial loss, and a high accident rate, resulting in an urgent need to leverage new infrastructure like 5G and the Industrial Internet to provide cloud-based digital and intelligent services for the "deaf, dumb, and dull" equipment in this industry. Therefore, constructing an industrial internet platform for cloud-based mining and metallurgical equipment is one of the crucial means to achieve resource aggregation and optimal allocation, enhance equipment efficiency and safety levels, and is also an inevitable choice for realizing the industry's digital transformation and upgrading. Based on the background and current situation of the construction of the cloud industrial Internet platform on equipment and the needs of the mining and metallurgy industry, the cloud industry Internet platform on mining and metallurgy industry equipment is studied. The construction contents of the device layer, edge layer, IaaS layer, PaaS layer, application layer, and security protection system are provided, respectively. Through constructing the three major functional systems: network, platform, and security, key industrial equipment assets, production and manufacturing systems, management systems, and resource applications have been fully integrated. The specific construction steps and effects of the platform are analyzed through a practical case of a mining and metallurgical enterprise. The proposed construction scheme can meet the needs of constructing a cloud industrial Internet platform for equipment in the mining and metallurgy industry and solve the common problems of cloud industrial equipment in the industry, so as to provide a theoretical and practical reference for mining and metallurgy enterprises to carry out similar platform construction, support fine equipment management, reduce equipment operation and maintenance costs and accident rates, promote the public service ecological construction of cloud industrial equipment solutions, and help the collaborative development of upstream and downstream of the industrial chain. [ABSTRACT FROM AUTHOR]

Addressing the challenge of rehearsing large-scale equipment assembly, particularly for oversized components like wind turbine towers, hubs, nacelles, and blades, which often face quality issues such as substandard workmanship and wide tolerances during on-site assembly, a system has been developed for simulating wind turbine assembly. This system enables digital wind turbine assembly by creating virtual and production process models and employing intelligent database analysis. It resolves the problem of the absence of pre-production for large-scale equipment, meets the batch production needs of the wind turbine manufacturing industry, enhances the safety of wind turbine operations, improves operator assembly skills, and boosts production efficiency. This platform has already been implemented in the wind turbine manufacturing industry, yielding significant economic benefits. [ABSTRACT FROM AUTHOR]

Taking lightweight sandwich plate structures as the main research object, the self-repairing design and implementation method were studied according to the fracture failure forms of the structures. The structural samples were prepared by additive manufacturing technology, and the restoration effect of the repaired structural mechanics properties was compared and analyzed through experimental tests. The results show that the designed sandwich plate self-repairing structure has a good ability to repair cracks, and the stress resistance of the repaired structure is restored to 85.6% of the original structures. [ABSTRACT FROM AUTHOR]

Nine diterpenoid alkaloids were isolated from Aconitum georgei Comber belonging to the genus Aconitum in Ranunculaceae family. Their structures were determinated by using HR-ESI-MS and 1 D/2D NMR spectra as geordine (1), yunaconitine (2), chasmanine (3), crassicauline A (4), forestine (5), pseudaconine (6), 14-acetylalatisamine (7), austroconitine B (8), and talatisamine (9). Among them, compound 1 is a previously undescribed aconitine-type C19-diterpenoid alkaloid, and compounds 3, and 5-9 have not previously been isolated from this species. The results of in vitro experiments indicated that new compound 1 possesses mild anti-inflammatory activity, which inhibited the production of NO in LPS-activated RAW 264.7 cells with an inhibition ratio of 29.75% at 50 μM. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) possess fast-moving abilities and have been used in various tasks in the past decades. However, their performances are still restricted by insufficient endurance and confined environments. Intuitively, combining other locomotion modes with UAVs, such as diving and driving, would be an appropriate idea to improve the robot's adaptability and solve the endurance problem. Recently, the terrestrial/aerial hybrid robots have drawn the researchers' eyes for their outstanding performances, which can deploy flight mode to traverse insurmountable terrains and ground mode to increase endurance and realize detailed searches. Therefore, this paper developed the autonomous quadrotor tilting hybrid robot (AQT-HR) to achieve terrestrial/aerial dual-modal mobility and verified that the robot delivers high energy efficiency. The AQT-HR can achieve flying and driving through a quadrotor tilting mechanism, which can alter one single driving force into different directions. Furthermore, the dynamic models of the hybrid robot's aerial and ground locomotion are derived and introduced into the model-feedforward PID control algorithm for improving the robot's flying stability. Finally, we conducted some mobility tests and experiments about traversing obstacles to demonstrate that the proposed hybrid robot can realize autonomous mode switching and perform a low energy consumption in ground movement mode. [ABSTRACT FROM AUTHOR]

For the instability problem of the wind turbine flexible tower caused by mechanical fatigue and vibration, Back Propagation (BP) neural network is used to establish the tower vibration prediction model to solve the wind turbine tower vibration prediction analysis. To find correlation association factors impacting the flexible tower vibration, the multi-source heterogeneous data from various operating situations of wind turbines are optimized using correlation analysis. A BP neural network-based tower vibration prediction model is created. The findings of a simulation investigation using data from a wind farm’s 2 MW wind turbine with a 120 m flexible tower reveal that the BP neural network has the greatest predictive power for operating situations below the rated wind speed. The root mean square error RMSE decreased by 10.6608; the mean absolute error MAE decreased by 9.1915 compared to the above rated wind speed. It is proved that the BP neural network prediction model has high accuracy in predicting the vibration of the flexible tower for working conditions below the rated wind speed, which can provide accurate data support for the vibration control of the flexible towers. [ABSTRACT FROM AUTHOR]

Nine diterpenoid alkaloids were isolated from Aconitum georgei Comber belonging to the genus Aconitum in Ranunculaceae family. Their structures were determinated by using HR-ESI-MS and 1 D/2D NMR spectra as geordine ( 1 ), yunaconitine ( 2 ), chasmanine ( 3 ), crassicauline A ( 4 ), forestine ( 5 ), pseudaconine ( 6 ), 14-acetylalatisamine ( 7 ), austroconitine B ( 8 ), and talatisamine ( 9 ). Among them, compound 1 is a previously undescribed aconitine-type C 19 -diterpenoid alkaloid, and compounds 3 , and 5 - 9 have not previously been isolated from this species. The results of in vitro experiments indicated that new compound 1 possesses mild anti-inflammatory activity, which inhibited the production of NO in LPS-activated RAW 264.7 cells with an inhibition ratio of 29.75% at 50 μM.