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The purpose of this paper is to improve the corrosion resistance of the 6061-Al alloy as the battery pack material for electric vehicles, and the nano-SiC/MAO composite coating was prepared.

The corrosion resistance of coatings was evaluated by the global electrochemical test, and the local electrochemical impedance spectroscopy (LEIS) was used to study the local corrosion mechanism. The laser confocal microscope, scanning electron microscope and X-ray diffractometer (XRD) were used to characterise coatings.

Results showed that the impedance of nano-SiC/MAO coating was 1–2 times higher than MAO coating, and the main corrosion product was Al(OH)₃. LEIS results showed that the impedance of the nano-SiC/MAO coating was two times higher than the MAO coating. The defective SiC/Micro-arc oxidation coating still had high corrosion resistance compared to the MAO coating.

The physical model of the local corrosion mechanism for SiC/MAO composite coating in “cavity-fracture collapse” mode was proposed.

Coal is a critical global energy source, and fluctuations in its price significantly impact related enterprises' profitability. This study aims to develop a robust model for predicting the coal price index to enhance coal purchase strategies for coal-consuming enterprises and provide crucial information for global carbon emission reduction.

The proposed coal price forecasting system combines data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. It addresses the challenge of merging low-resolution and high-resolution data by adaptively combining both types of data and filling in missing gaps through interpolation for internal missing data and self-supervision for initiate/terminal missing data. The system employs self-supervised learning to complete the filling of complex missing data.

The ensemble model, which combines long short-term memory, XGBoost and support vector regression, demonstrated the best prediction performance among the tested models. It exhibited superior accuracy and stability across multiple indices in two datasets, namely the Bohai-Rim steam-coal price index and coal daily settlement price.

The proposed coal price forecasting system stands out as it integrates data decomposition, semi-supervised feature engineering, ensemble learning and deep learning. Moreover, the system pioneers the use of self-supervised learning for filling in complex missing data, contributing to its originality and effectiveness.

The entrepreneurial process often cannot be explained by a single entrepreneurial theory. Instead, it is more likely the result of the interaction between various entrepreneurial behavior patterns and different environmental conditions. However, existing research has frequently overlooked the complexity inherent in the entrepreneurial phenomenon. Building on a configurational perspective, this study aims to examine how new ventures can use different behavioral configurations to achieve high performance amid various uncertain environments.

Based on the survey data from 143 new start-ups in China’s software industry, this study uses fuzzy-set qualitative comparative analysis (fsQCA).

This study jointly considers multiple entrepreneurial behaviors − causation, effectuation and entrepreneurial bricolage and different types of environmental uncertainty − state uncertainty, effect uncertainty and response uncertainty. The findings reveal three behavioral configurations for high/nonhigh new venture performance.

This study expands previous insights into the relationship between entrepreneurial behaviors and new venture performance from the perspective of configurational theory. Moreover, it offers new insights into the types of uncertainty, further refining our understanding of the uncertainties inherent in entrepreneurial activities.

The purpose of this paper is to present the design and implementation of a blended problem-based learning (PBL) teaching model and corresponding teaching materials for a university-level bioinformatics course. The effects of this teaching model on student performance in terms of problem solving and learning attitudes were investigated.

Students in both groups completed assessments of problem-solving attitudes and learning attitudes both one week both before and after experimental instruction. Collected data were analyzed using one-way ANCOVA. Group discussions and student interviews were recorded and treated as part of the data analysis.

The study produced the following findings: the experimental group was found to perform better than the control group in terms of learning attitudes, but the results were not statistically significant; the experimental group was found to outperform the control group in terms of problem-solving attitudes, and the difference was statistically significant; lesson plan contents need to be designed based on problem-based learning theory, and reflect real-world conditions; participants in the experimental group approved of the blended PBL and group discussion approach.

Results are expected to provide a useful reference for educators and researchers. These findings can be applied to relevant instructional fields to enhance learner motivation and engagement, thus improving learning outcomes.

This study explores configurations that promote the development of collective economies in China's rural villages and reveals the multiple development pathways that otherwise remain relatively unexamined in the literature.

The authors obtained first-hand representative case data from 20 villages in 12 counties in 5 provinces in East, West and Central China via fieldwork and applied fuzzy set qualitative comparative analysis (fsQCA) to conduct a configurational comparative study of the development of village collective economies.

This paper identifies five factors in the current literature that affect the development of village collectives, based on an “entrepreneur–situation” analytical framework. Using the fsQCA method, this study further obtains two main configurations of conditions that culminate in the growth of rural collective economies in China. The first solution is the “top-down path”: When entrepreneurial leadership (EL), resource endowment (RE) and government assistance (GA) are present, a village collective economy will experience a high level of development, irrespective of policy support (PS) and villagers' participation (VP). The second solution is the “bottom-up path”: When EL, VP and PS are present and GA is not present, a village collective economy will experience a high level of development, irrespective of RE. In both situations, EL stands out as the core condition for the development of village collective economies, implying the need for the government to vigorously cultivate the entrepreneurial skills and aspirations of village cadres.

Taking a configurational perspective and using an fsQCA approach, this research constructs an “entrepreneur–situation” analytical framework to investigate the key combinations of factors and pathways involved in the high level of development of Chinese village collective economies.

The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

This paper aims to implement quality of service(QoS) dynamic optimization for the integrated satellite-terrestrial network(STN) of the fifth-generation Inmarsat system(Inmarsat-5).

The structure and operational logic of Inmarsat-5 STN are introduced to build the graphic evaluation and review technique(GERT) model. Thus, the equivalent network QoS metrics can be derived from the analytical algorithm of GERT. The center–point mixed possibility functions of average delay and delay variation are constructed considering users' experiences. Then, the grey clustering evaluation of link QoS is obtained combined with the two-stage decision model to give suitable rewards for the agent of GERT-Q-learning, which realizes the intelligent optimization mechanism under real-time monitoring data.

A case study based on five time periods of monitoring data verifies the adaptability of the proposed method. On the one hand, grey clustering based on possibility function enables a more effective measurement of link QoS from the users' perspective. On the other hand, the method comparison intuitively shows that the proposed method performs better.

With the development trend of integrated communication, STN has become an important research object in satellite communications. This paper establishes a modular and extensible optimization framework whose loose coupling structure and flexibility facilitate management and development. The grey-clustering-based GERT-Q-Learning model has the potential to maximize design and application benefits of STN throughout its life cycle.

The purpose of this study is to use polybenzoxazine (Pbz) functionalized ZrO₂ nanoparticles to synthesize polyurethane (PU)-PbZ/ZrO₂ nanocomposite. The results derived from the electrochemical impedance spectroscopy (EIS) and polarization studies indicated the superior anticorrosive activity of PU-Pbz/ZrO₂ nanocomposite coatings compared to those of plain PU coatings. The decreased corrosion current was detected on the scratch of the PU-Pbz/ZrO₂ nanocomposite-coated mild steel surface by scanning electrochemical microscopy (SECM) compared to other studied coatings. The superior anticorrosive and mechanical properties of the proposed nanocomposite coatings provide a new horizon in the development of high-performance anticorrosive coatings for various industries.

The Pbz functionalized ZrO₂ nanoparticles were characterized by Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM) with energy dispersive X-ray analysis (EDX) and thermogravimetric analysis (TGA) in terms of the structural, morphological and thermal properties of these coatings. A different formulation of coatings such as PU, PU-Pbz, PU-ZrO₂ and PU-Pbz/ZrO₂ were prepared and investigated for their corrosion protection performance on mild steel in natural seawater by electrochemical techniques. The surface morphological studies were done by SEM/EDX and XRD analysis.

The superior anticorrosive property of the proposed nanocomposite coatings provides a new horizon in the development of high-performance anticorrosive coatings for various industries. Addition of Pbz wrapped ZrO₂ nanoparticles into the PU coating resulted in the blockage of charge transfer at the metal/electrolyte interface, which reduced the dissolution of mild steel. It was revealed from the SEM/EDX analysis that the formation of the corrosion products at the metal/electrolyte interface behaved as the passive layer which reduced the dissolution of steel.

The inclusion of polybenzoxazine functionalized ZrO₂ nanoparticles to the polyurethane coating reinforces the barrier and mechanical properties of PU-Pbz/ZrO₂ nanocomposite, which is due to the synergistic effect of ZrO₂ and Pbz.

Injecting drug use is a global concern, with an estimated 16 million people who inject drugs (PWIDs) in over 148 countries. A number of Asian countries detain PWIDs for compulsory treatment. The paper aims to discuss this issue.

The authors reviewed the literature on compulsory drug treatment in seven Asian countries.

The authors identified 1,269 closed settings which held over 600,000 drug users in eight countries. The average detainee was aged from 20 to 30 years and was predominantly male. HIV risk behaviour continued in detention in some countries. In most countries treatment comprised physical labour, military drills. Methadone maintenance treatment and antiretroviral therapy were rarely available. No data were located to show detention in a closed setting treated drug dependency. Issues of concern were; no due legal process for the detention of drug users, lack of evidence-based drug treatment, lack of HIV prevention and treatment, abusive conditions, forced labour and exercise, arbitrary exit procedures and very high relapse rates.

The review of compulsory treatment of drug users failed to find any evaluation of effective drug treatment for detainees. Instead serious breaches in human rights conditions were evident. Prominent international organisations have called for the compulsory treatment of drug users to cease.

Many countries are spending vast amounts of funding on ineffective treatments for drug users.

Funding should be directed to community-based drug treatments that have been shown to work.

This is the largest review of compulsory treatment of drug users to date.