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This study aims to address the challenge of training a detection model for the robot to detect the abnormal samples in the industrial environment, while abnormal patterns are very rare under this condition.

The authors propose a new model with double encoder–decoder (DED) generative adversarial networks to detect anomalies when the model is trained without any abnormal patterns. The DED approach is used to map high-dimensional input images to a low-dimensional space, through which the latent variables are obtained. Minimizing the change in the latent variables during the training process helps the model learn the data distribution. Anomaly detection is achieved by calculating the distance between two low-dimensional vectors obtained from two encoders.

The proposed method has better accuracy and F1 score when compared with traditional anomaly detection models.

A new architecture with a DED pipeline is designed to capture the distribution of images in the training process so that anomalous samples are accurately identified. A new weight function is introduced to control the proportion of losses in the encoding reconstruction and adversarial phases to achieve better results. An anomaly detection model is proposed to achieve superior performance against prior state-of-the-art approaches.

This study aims to explore the relationship between the degree of state-owned enterprises’ (SOEs) mixed reform and the environmental response of enterprises, against the background of actively promoting the reform of mixed ownership in China.

The study is conducted on a sample of A-share listed manufacturing companies in Shanghai and Shenzhen of China, investigated for the period 2015 to 2020. The baseline regression results are robust to a series of robustness and endogeneity tests. To deal with the issue of endogeneity, the technique of instrumental variable method has been applied.

The study confirms the U-shaped effect of the depth and restriction of mixed ownership on SOEs’ environmentally responsive behaviour in the manufacturing industry, especially for lower environmental regulation and higher level of risk-taking firms. The findings indicate that the government, shareholders and other stakeholders of enterprises should not simply consider that the mixed reform is directly promoting or reducing the environmental response behaviour of enterprises.

SOEs should improve their shareholding structures to undermine performance enhancement at the expense of the environment and increase environmentally beneficial behaviours. Regulators and governments should improve the institutional mechanism of environmental regulation and make efforts to promote corporate awareness of the environment.

Although the adoption and implementation of environmentally friendly policies are costly, improved environmental response and other social responsibilities are helpful to corporate long-term growth and reputation and obtain more capital market attention. Therefore, firms would benefit from improving their environmental response to protect nature, as well as to enjoy the economic and social benefits of a better environmental response.

To the best of the authors’ knowledge, there is a lack of studies focussing on the environmental behaviour of SOEs of mixed reform. As the mixed reform in China has come to a climax phase in recent several years, SOEs of mixed reform is an ideal environment for research. The study focusses on manufacturing firms as these firms are more susceptible to contribute to environmental pollution, exploitation of natural resources and labour concerns.

Shape memory polymers (SMPs) are classified as smart materials owing to their inherent stimulus-induced response. SMPs are capable of recovering partially or totally to its original shape after a high degree of deformation by external stimulus. The most used stimuli are thermal, light, magnetic field and electricity. This research aims to characterize the toughness property of thermo-responsive SMP specimens fabricated by the material extrusion (ME) process and to investigate the impact of ME parameters on specimen maximum load and load-displacement curves. Moreover, to investigate the recovery efficiency based on the initial and post toughness generated by the compact tension test.

A design of experiments with three parameters (temperature, velocity and layer height) defined the ME settings to fabricate the specimens. The ME raster orientation factor was also evaluated separately. In addition, one more specimen group assisted by a clamp during the recovery process was compared with a specimen control group. After fabrication, specimens were submitted to a thermo-mechanical cycle that encompasses a compact tension test and a thermo-recovery process. Comparison studies of load-displacement, toughness and recovery efficiency of the specimens were carried out to determine the optimized fabrication parameters.

It was found that ME parameters and raster orientation impacted the test results. Samples with the clamp support during recovery returned a higher toughness than samples without support. Finally, results showed that the shape memory effect can contribute with up to 43 per cent recovery efficiency in a first recovery and up to 23 per cent in a second recovery of damaged specimens.

This paper is a reference for toughness and recovery properties of SMP parts produced by the ME fabrication process.

Shape memory polymer (SMP) is capable of recovering its original shape from a high degree of deformation by applying an external stimulus such as thermal energy. This research presents an integration of two commercial SMP materials (DiAPLEX and Tecoflex) and a material extrusion (ME) printer to fabricate SMP parts and specimens. The material properties such as Young’s modulus of the specimens was examined as a process output. Furthermore, stress-strain curve, strain recovery, instant shape-fixity ratio, long-term shape-fixity ratio and recovery ratio of SMP specimens during a thermo-mechanical cycle were investigated.

The ME fabrication settings for the SMP specimens were defined by implementing a design of experiments with temperature, velocity and layer height as process variables.

It was found, according to main effect and iteration plots, that fabrication parameters have an impact on Young’s modulus and exist minimum iteration among variables. In addition, Young’s modulus variation of DiAPLEX and Tecoflex specimens was mostly caused by velocity and layer height parameters, respectively. Moreover, results showed that SMP specimens were able to recover high levels of deformation.

This paper is a reference for process control and for rheological properties of SMP parts produced by ME fabrication process.

This paper aims to develop a feasible visual weld detection method to solve the problems in multi-layer welding detection (e.g. cover pass welding detection) for seam tracking and non-destructive testing. It seeks for an adaptive and accurate way to determine the edge between the seam and the base metal in the grayscale image of weld automatically. This paper tries to contribute to next-generation real-time robotic welding systems for multi-layer welding.

This paper opted for invariant moments to characterize the seam and the base metal for classification purposes. The properties of invariant moments, such as high degree of self-similarity and separation, affine invariance and repetition invariance, were discussed to verify the adaptability of the invariant moment in weld detection. Then, a weld detection method based on invariant moments was proposed to extract the edge between the seam and the base metal, including image division, invariant moment features extraction, K-Means adaptive thresholding, maximum connected domain detection and edge position extraction.

This paper highlights the significance of high degree of self-similarity and separation, affine invariance and repetition invariance of the invariant moment for weld detection. An adaptive, effective and accurate method is proposed to detect the edge between the seam and the base metal based on invariant moments.

It is necessary to verify the applicability of the proposed method in variable welding conditions further. Further works will focus on the establishment of a real-time seam tracking system during the whole multi-layer/multi-pass welding process based on such adaptive visual features.

This paper includes the implications for development of an adaptive and real-time weld detection method, which is expected to be applied to online seam tracking in multi-layer welding.

This paper presents an accurate weld detection method in multi-layer welding, overcoming difficulties in effectiveness, adaptability and efficiency of existing weld detection methods.

The significance of this research lies in providing an understanding of how economic conditions, including financial development, informal economic activities and economic uncertainty, influence carbon emissions and tries to offer valuable insights for policymakers to promote sustainable development.

The Panel-ARDL method is employed for a group of 30 developing countries from 1990 to 2018. This study analyzes the data obtained from the World bank, International Monetary Fund and World Uncertainty databases.

Based on the empirical results of the extended model, an increase in GDP and energy intensity is associated with an 83 and 14% increase in carbon emissions, respectively. Conversely, a 1% increase in financial development and economic uncertainty is linked to significant decrease in carbon emissions (about 47 and 23%, respectively). Finally, an increase in the informal economy can lead to a negligible yet significant decrease in carbon emissions. These results reveal that financial development plays an effective role in reducing CO₂ emissions. Moreover, while economic uncertainty and informal economy are among unfavorable economic conditions, they contribute in CO₂ reduction.

Therefore, fostering financial development and addressing economic uncertainty are crucial for mitigating carbon emissions, while the impact of informal economy on emissions, though present, is relatively negligible. Accordingly, policies to control uncertainty and reduce the informal economy should be accompanied by environmental policies to avoid increase in emissions.

The originality of this paper lies in its focus on fundamental changes in the economic environment such as financial development, economic uncertainty, and informal activities as determinants of carbon emissions. This perspective opens up new avenues for understanding the intricate relationship between carbon emissions and economic factors, offering unique insights previously unexplored in the literature.