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The implementation of reverse logistics (RL) as a strategic decision has gained significant attention amongst organisations due to its benefits to sustainable development. The purpose of this paper is to provide a comprehensive review of the literature to evaluate the performance of the RL process based on the three dimensions of sustainability including environmental, economic and social aspects.

Content analysis was adopted to collect and analyse the information.

The findings of this research show that most of the studies have focused on the performance evaluation of RL by considering the factors associated with economic and environmental performance. The social aspect of RL has been overlooked and requires investigation due to its contribution to positive social outcomes. In addition, no research has been conducted to assess the impact of each of the disposition options on the triple-bottom-line sustainability performance in one study.

Although RL can make a significant contribution to improving the sustainability performance of firms, little research has been undertaken on exploring the relationship between RL and sustainability performance. This paper provides practitioners, academics and researchers a broad and complete view of the relationship between RL and sustainability performance with suggestion for future research.

The electrical properties of piezoelectric vibrators have a crucial influence on the operating state of ultrasonic motors. In order to solve the problem that the current piezoelectric vibrator generates a large amount of heat during vibration to degrade its performance, which in turn affects the normal operation of ultrasonic motors, this paper prepares a novel piezoelectric vibrator and tests its maximum vibration velocity under the working condition, which is more than twice as much as that of the current commercial PZT-8.

The crystal structures of the samples were analyzed by using an X-ray diffractometer. For microstructure observation, samples were observed by scanning electron microscope (SEM). The quasi-static piezoelectric coefficient meter (ZJ-3AN) was used for piezoelectric measurement. Dielectric properties were measured by utilizing an impedance analyzer (Agilent 4294A) with a laboratory heating unit. Ferroelectric hysteresis loops were obtained using a ferroelectric analyzer (Radiant, Multiferroic 100). A Doppler laser vibrometer (Polytec PSV-300F, Germany) and a power amplifier were used for piezoelectric vibration measurements, during which the temperature rise was determined by an infrared radiation thermometer (Victor 303, China).

The ceramics exhibit enhanced piezoelectric performance at 0.1–0.4 mol% of Yb doping contents. The ceramic of 0.4 mol% Yb reaches the maximal internal bias field and presents a larger mechanical quality factor of 1,692 compared with that of 0.2 mol% Yb-doped ceramic, in spite of a slightly decreased dielectric constant of 439 pC/N, the unit of the piezoelectric constant, which is the ratio of the local charge (pC) to the frontal force (N) and electromechanical coupling coefficient of 0.63. The vibrator with this large mechanical quality factor ceramic displays a vibration velocity of up to 0.81 m/s under the constraint of 20 °C temperature rising, which is much higher than commercial high-power piezoelectric ceramics PZT-8.

The enhanced high-power properties of the piezoelectric vibrator by Yb doping may provide a potential application for the high-performance USM and offer the possibility of long-term stable operation under high power for special equipment like USM. In the subsequent phase of research, the novel PZT-based high-power piezoelectric vibrator can be utilized in the USM, and the motor's performance will be evaluated under aerospace conditions to objectively assess the reliability of the piezoelectric vibrator.

The paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter rate and fleet development as the main influencing factors for the market analysis.

The paper used the vector error correction model to evaluate the degree of impact of each influencing factor on Suezmax tanker freight rates, as well as the interplay between these factors.

The conclusion and results were tested using the 20-year data from 1999 to 2019, and the methodology and theory of this paper were proved to be effective. Results of this study provide effective reference for scholars to find the law of fluctuations in Suezmax tanker freight rates.

This paper provides a decision-making support tool for tanker operators to cope with fluctuation risks in the tanker shipping market.

The purpose of this paper is to explore the internal interaction mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth from a systematic perspective, based on which this work forecasts their future development trends.

In this study, a multivariate grey model is applied to the prediction of marine scientific research and education, industrial structure upgrading and marine economic growth. Considering the impact of the COVID-19 on marine development, this paper introduces the weakening buffer operator into MGM(1,m) and constructs the AWBO-MGM(1,m) model. To verify the validity and accuracy of the new model, this paper uses AWBO-MGM(1,m), MGM(1,m), GM(1,N), GM(1,1), back propagation neural network and linear regression models for simulation and prediction based on the data from 2010 to 2021, respectively.

From the theoretical perspective, the development of marine scientific research and education can accelerate industrial upgrading and promote marine economic growth by providing high-quality talents, promoting marine science and technology progress and reducing transaction costs; while the upgrading of marine industrial structure and marine economic growth can promote the development of marine scientific research and education by guiding social capital, enhancing talent demand and stimulating market vitality. From the empirical analysis, the AWBO-MGM(1,m) model can effectively deal with epidemic shocks and has higher fitting and prediction accuracy than the other five comparative models.

The government should pay attention to the construction of marine scientific research and education, so as to provide high-quality talents and advanced scientific research results for the high-quality development of marine economy. On the basis of using science and technology to firmly build the primary and secondary marine industries, the government should actively guide the labor, capital and other factors of production to the tertiary industry, thereby promoting the optimization and upgrading of marine industrial structure.

On the one hand, the interplay mechanism of marine scientific research and education, industrial structure upgrading and marine economic growth is analyzed from a systematic perspective; on the other hand, the enhanced AWBO-MGM(1,m) possesses higher forecasting performance and is applicable to the systemic multivariate forecasting problem in the presence of outstanding external shocks.

The purpose of the study is to obtain and analyze vibro-acoustic characteristics.

A unified analysis model for the rotary composite laminated plate and conical–cylindrical double cavities coupled system is established. The related parameters of the unified model are determined by isoparametric transformation. The modified Fourier series are applied to construct the admissible displacement function and the sound pressure tolerance function of the coupled systems. The energy functional of the structure domain and acoustic field domain is established, respectively, and the structure–acoustic coupling potential energy is introduced to obtain the energy functional. Rayleigh–Ritz method was used to solve the energy functional.

The displacement and sound pressure response of the coupled systems are acquired by introducing the internal point sound source excitation, and the influence of relevant parameters of the coupled systems is researched. Through research, it is found that the impedance wall can reduce the amplitude of the sound pressure response and suppress the resonance of the coupled systems. Besides, the composite laminated plate has a good noise reduction effect.

This study can provide the theoretical guidance for vibration and noise reduction.

This paper aims to build a scientific evaluation index system for regional low-carbon circular economic development. Taking Sichuan Province as the empirical research object, the paper evaluates its low-carbon circular economy (LCCE) development level and proposes policy recommendations for climate change improvement based on the evaluation results.

This paper, first, built an evaluation index system with 30 indicators within six subsystems, namely, economic development, social progress, energy consumption, low-carbon emissions, carbon sink capacity and environmental carrying capacity. Second, develop an “entropy weight-grey correlation” evaluation method. Finally, from a practical point of view, measure the development level of LCCE in Sichuan Province, China, from 2008 to 2018.

It was found that Sichuan LCCE development had a general downward trend from 2008 to 2012 and a steady upward trend from 2012 to 2018; however, the overall level was low. The main factors affecting the LCCE development are lagging energy consumption and environmental carrying capacity subsystem developments.

This paper puts forward relevant suggestions for improving the development of a low-carbon economy and climate change for the reference of policymakers.

This paper built an evaluation index system with 30 indicators for regional low carbon circular economic development. The evaluation method of “entropy weight-grey correlation” is used to measure the development level of regional LCCE in Sichuan Province, China.

The purpose of the paper is to predict mapping of areas vulnerable to flooding in the Ourika watershed in the High Atlas of Morocco with the aim of providing a useful tool capable of helping in the mitigation and management of floods in the associated region, as well as Morocco as a whole.

Four machine learning (ML) algorithms including k-nearest neighbors (KNN), artificial neural network, random forest (RF) and x-gradient boost (XGB) are adopted for modeling. Additionally, 16 predictors divided into categorical and numerical variables are used as inputs for modeling.

The results showed that RF and XGB were the best performing algorithms, with AUC scores of 99.1 and 99.2%, respectively. Conversely, KNN had the lowest predictive power, scoring 94.4%. Overall, the algorithms predicted that over 60% of the watershed was in the very low flood risk class, while the high flood risk class accounted for less than 15% of the area.

There are limited, if not non-existent studies on modeling using AI tools including ML in the region in predictive modeling of flooding, making this study intriguing.