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This paper aims to successfully synthesize three-dimensional spindle-like Au functionalized Co₃O₄-ZnO nanocomposites; characterize the structure, morphology and surface chemical properties of the products; study the effect of Au NPs doping concentration, operating temperature different gas to, sensing properties; and introduce an attractive gas sensor for acetone detection.

Au NPs functionalized Co₃O₄-ZnO nanocomposite was prepared by coprecipitation and impregnation methods; the structure and surface chemical property of the products were characterized by XRD, SEM, TEM, UV-Vis, BET and XPS. The sensing ability of Au@Co₃O₄-ZnO for acetone and mechanism was analyzed systematically.

The results of gas sensing tests show that the unique component structure, Schottky junction and catalytic effect of Au functionalization make it have low operating temperature, excellent selectivity, high response (10 ppm, 56) and rapid response recovery time.

All the characterization and test data of the prepared materials are provided in this paper and reveals the gas sensing mechanism of the gas sensor.

The detection limit is 2.92–100 ppb acetone. It is promising to be applied in low-power, micro detection and miniature acetone gas sensors.

The gas sensor prepared has a lower working temperature and low detection limit, so it has promising application prospects in low-concentration acetone detection and early warning.

The unique component structure, Schottky junction and catalytic effect of Au functionalization Co₃O₄-ZnO make it have low operating temperature, excellent selectivity and rapid response recovery time.

The purpose of this paper is to study the effect of doping, annealing temperature and visible optical excitation on CuO-ZnO nanocomposites’ acetone sensing properties and introduce an attractive candidate for acetone detection at about room temperature.

ZnO nanoparticles doped with CuO were prepared by sol-gel method, and the structure and morphology were characterized via X-ray diffraction, scanning electron microscope, energy dispersive spectroscopy and Brunauer-Emmett-Teller. The photoelectric responses of CuO-ZnO nanocomposites to cetone under the irradiation of visible light were investigated at about 30°C. The photoelectric response mechanism was also discussed with the model of double Schottky.

The doping of CuO enhanced performance of ZnO nanoparticles in terms of the photoelectric responses and the gas response and selectivity to acetone of ZnO nanoparticles, in addition, decreasing the operating temperature to about 30ºC. The optimum performance was obtained by 4.17% CuO-ZnO nanocomposites. Even at the operating temperature, about 30ºC, the response to 1,000 ppm acetone was significantly increased to 579.24 under the visible light irradiation.

The sensor fabricated by 4.17% CuO-ZnO nanocomposites exhibited excellent acetone-sensing characteristics at about 30ºC. It is promising to be applied in low power and miniature acetone gas sensors.

In the present research, a new nanocomposite material of CuO-ZnO was prepared by Sol-gel method. The optimum gas sensing properties to acetone were obtained by 4.17% CuO-ZnO nanocomposites at about 30ºC operating temperature when it was irradiated by visible light with the wavelength more than 420 nm.

The purpose of this research is to synthesize Al₂O₃-ZnO thick films, study the effect of doping and optical excitation on their sensing properties and introduce an attractive candidate for acetone detection in practice.

ZnO nanoparticles doped with Al₂O₃ were prepared by sol-gel method and characterized via X-ray diffraction and field-emission scanning electron microscopy. The sensing properties to acetone were investigated with an irradiation of UV. The sensing mechanism was also discussed with UV-Vis spectroscopy.

The doping of Al₂O₃ promoted the sensing response and stability of ZnO nanoparticles. The optimum performance was obtained by 4.96 Wt.% Al₂O₃-ZnO. The response to acetone (1,000 ppm) was significantly increased to 241.81, even just at an operating temperature of 64°C. It was also demonstrated that optical excitation with UV irradiation greatly enhanced the sensing response and the sensitivity can reach up to 305.14.

The sensor fabricated from 4.96 Wt.% Al₂O₃-ZnO exhibited excellent acetone-sensing characteristics. It is promising to be applied in low power and miniature acetone gas sensors.

In the present research, the optimum performance was obtained by 4.96 Wt.% Al₂O₃-ZnO at a low operating temperature of 64°C. The sensing properties were enhanced significantly with optical excitation, and the sensing mechanism was discussed with UV-Vis spectroscopy which has been reported rarely before.

The awareness of Eastern Europe within China is mostly tied to the shared notion of Communist control. During the last half century, educational and cultural links were established which often resonated in the minds and desired experiences of many Chinese tourists. This chapter explores the meaning of these Asian-European links for Croatia by using economic data and archival evidence. The analysis is framed within the context of China’s policy toward Central and Eastern Europe. The work seeks to offer a better understanding of the politico-economic decisions that shape contemporary tourism flows and interests, not only in relation to Croatia, but also to similarly placed countries.

The purpose of this paper is to describe the tribological characteristics with different area density of concave-convex micro-texture on the mold surface. It is a new technology to improve the quality of the workpiece to control the tribological properties through the application of concave-convex micro-texture on the mold surface.

Five groups of laser micro-texture with different area density (ratio of the concave-convex micro-texture area to the all-area) were processed on the surface of the mold steel, and the tribological properties were compared with the smooth surface of the reference sample.

The time of the running-in stage in different experimental groups was about 300 s. The fluctuation amplitude of concave-convex micro-texture friction coefficient is much larger than that of smooth plane specimen in the running-in stage. After the running-in stage, the friction coefficients were lower than that in the smooth condition and decreased with the increase of the concave-convex micro-texture area density. When the area density reached 25%, the friction coefficients no longer decreased significantly. In addition, the wear of concave-convex micro-texture surface is much lower than that of smooth surface and decreases with the increase of concave-convex micro-texture area density.

Domestic and foreign scholars have done a lot of research on the relationship between concave micro-texture and tribological properties. However, the object of this paper is a new concave-convex micro-texture, which is rarely studied in the field of tribology.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2020-0081/

This paper aims to provide an understanding of how accounting systems have changed across four distinct periods of hegemonic leadership in China.

Using Gramsci's concept of hegemony, periods of leadership and accounting change throughout Chinese history are examined, including the Confucian tradition, the rise of the socialist system followed by the Cultural Revolution in the Maoist era, and the move towards the socialist‐market system in the Dengist era.

This paper shows how political leaders in these different time periods effectively achieved leadership by destroying an existing hegemony, creating a new ideology, and implanting this into people's daily lives in order to successfully mobilise their ideological systems. Consistent with changes in leadership, Chinese accounting systems are shown to have responded to hegemonic shifts across these periods.

This paper contributes to understandings of Gramsci's concept of hegemony, explanations of, and motivations for, accounting change, and provides an insight into the evolution of accounting systems throughout time in the context of China.

Music sentiment analysis helps to promote the diversification of music information retrieval methods. Traditional music emotion classification tasks suffer from high manual workload and low classification accuracy caused by difficulty in feature extraction and inaccurate manual determination of hyperparameter. In this paper, the authors propose an optimized convolution neural network-random forest (CNN-RF) model for music sentiment classification which is capable of optimizing the manually selected hyperparameters to improve the accuracy of music sentiment classification and reduce labor costs and human classification errors.

A CNN-RF music sentiment classification model is designed based on quantum particle swarm optimization (QPSO). First, the audio data are transformed into a Mel spectrogram, and feature extraction is conducted by a CNN. Second, the music features extracted are processed by RF algorithm to complete a preliminary emotion classification. Finally, to select the suitable hyperparameters for a CNN, the QPSO algorithm is adopted to extract the best hyperparameters and obtain the final classification results.

The model has gone through experimental validations and achieved a classification accuracy of 97 per cent for different sentiment categories with shortened training time. The proposed method with QPSO achieved 1.2 and 1.6 per cent higher accuracy than that with particle swarm optimization and genetic algorithm, respectively. The proposed model had great potential for music sentiment classification.

The dual contribution of this work comprises the proposed model which integrated two deep learning models and the introduction of a QPSO into model optimization. With these two innovations, the efficiency and accuracy of music emotion recognition and classification have been significantly improved.