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This study examined the impact of school leadership on teacher professional collaboration, with collective teacher innovativeness and teacher self-efficacy (TSE) playing the mediating role. Two most commonly used leadership styles, instructional leadership (IL) and distributed leadership (DL), were analyzed using a multilevel design, i.e. teachers are nested within schools.

The proposed model was validated using data of Taiwan TALIS 2018 collected from both teachers and principals and analyzed using hierarchical linear modeling.

Results showed that IL and DL influence teacher professional collaboration through different paths. IL had a significant direct impact on teacher professional collaboration alone, while DL had a significant direct impact on both teachers' collective innovativeness and their professional collaboration. While TSE had a direct effect on collective teacher innovativeness, TSE and collective teacher innovativeness had a direct effect on teacher professional collaboration.

This study highlights the significant impact of principal leadership as both principals and teachers work in the same environment and culture co-shaped through the interaction and collaboration. Research evidence regarding the effects of IL and DL on teacher professional collaboration is limited; this is even less evidential when the indirect effects of variables mediating between school leadership and teacher outcomes, including teacher collective innovativeness and TSE, are added to the total effects. The present findings provide useful references for principals and teachers when promoting professional collaboration to achieve desired outcomes in school and student improvement.

Constant or decreasing returns and increasing returns to scale are two kinds of mechanism in economic growth. The goal of supply-side structural reform is to promote the establishment of the mechanism with increasing returns to scale. The paper aims to discuss this issue.

This paper argues that the overall economic structure of the developing economy has been divided into the sector of constant or decreasing returns to scale and the sector of increasing returns to scale due to the dual economic structure. Among them, the supply-side structural reform is mainly to reduce the sector of decreasing returns to scale and increase the sector of increasing returns to scale. Based on the hypothesis of such two-sector economic structure in the supply side of developing economies and on the industrial data, this paper empirically tests the returns to scale of China’s supply structure. The result suggests that so far the sector of constant or decreasing returns to scale dominates the supply structure of China’s economic growth, which results in the state of decreasing returns to scale in China’s overall economy.

Therefore, to realize the long-term sustained growth and transformation of the development pattern of China’s economy, the authors must carry out the supply-side structural reform, vigorously develop the modern industrial sectors characterized by modern knowledge and technology, and promote the development of an innovation-driven economy.

Besides, the authors must accelerate the transformation from traditional industrial sectors to modern industrial sectors, actively promote China’s industrial structure toward rationalization and high gradation, as well as build a modern industrial system so as to facilitate the formation of the mechanism of increasing returns to scale and accelerate the transformation of the driving force of China’s economic growth.

The purpose of this paper is to demonstrate the impact of the welding sequence on the substrate plate distortion during the wire and arc additive manufacturing (WAAM) process. This paper also aims to show the capability of finite element simulations in the prediction of those thermally induced distortions.

An experiment was conducted in which solid aluminum blocks were manufactured using two different welding sequences. The distortion of the substrates was measured at predefined positions and converted into bending and torsion values. Subsequently, a weakly coupled thermo-mechanical finite element model was created using the Abaqus simulation software. The model was calibrated and validated with data gathered from the experiments.

The results of this paper showed that the welding sequence of a part significantly affects the formation of thermally induced distortions of the final part. The calibrated simulation model was able to capture the different distortion behavior attributed to the welding sequences.

Within this work, a simulation model was developed capable of predicting the distortion of WAAM parts in advance. The findings of this paper can be used to improve the design of WAAM welding sequences while avoiding high experimental efforts.

The purpose of this paper is to explore the actual walking distance to public transport (PuT) stations and to report passenger perceptions on route choice.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). It can determine the interrelation between the accessibility of the transit service and evaluation on walking distance acceptance. Statistical analysis and geo-spatial approach were completed for obtaining major findings.

Statistical and geo-spatial analysis shows that respondents living in low-density areas walk longer than residents living in nearby inner city areas. In terms of PuT modes, residents walk longer for suburban train and subway/metro (U-Bahn) than for bus/tram services. Transit users accept a longer walking distance to reach a train station than other PuT modes and they choose the most direct and quickest route to reach PuT stations.

Findings of this study would help to formulate future strategies and standards for the sustainable planning of public transportation systems in the context of Munich and many other cities around the globe with similar conditions. However, future research should be conducted using a large-scale survey for evaluating the comprehensive picture of walking patterns to PuT stations. Accessibility to PuT stations can also be modeled and evaluated by adopting open data and voluntary social media information. Unfortunately, this study only presents a partial evaluation of walking focused on accessibility at selected PuT stations in different settings of the urban fabric.

This empirical study can be considered as an initial finding in the favor of the city transport authority to provide a design scale for improved accessibility of transit users; however, further investigation should be conducted using a large-scale survey for evaluating the comprehensive walking patterns.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). Findings of this study would help to formulate future strategies and standard for the sustainable planning of the public transportation system in the context of Munich and many other cities in the globe with similar conditions.

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

Climate change and variability present different challenges to the livelihoods of forest-dependent communities. This paper aims to determine climate variability/change and its effects on the livelihoods of the Buyangu community, which depends on Kakamega tropical rain forest in Kenya.

Rainfall and temperature trends were analysed using Mann–Kendall tests and Sen’s slope estimator. The effects of climate variability on the community were determined using household survey questionnaires, focus group discussions and in-depth interviews with key stakeholders.

Temperature trend analyses represent statistically significant trends for the period of 1980-2015. Results reveal a warming trend for both mean annual maximum temperatures and mean annual minimum temperatures by 0.04°C/year and 0.02°C/year, respectively. Moreover, analysis of annual precipitation (1923-2015) indicated an increase of 0.068 mm/year; however, the mean monthly rainfall showed a decreasing trend. As a result, crop production and livestock rearing are negatively affected. Although there is a high level of awareness of climate variability and its related effects on livelihoods, a majority of the Buyangu community still do not understand the influence of climate change on forests and the provision of forest products. Lack of knowledge on this subject will consequently limit adaptation responses.

This research fulfills the need to study climate variability and its effects on the livelihoods of forest-dependent communities. The study calls for all-round stakeholder participation of local and national players in formulating coherent adaptation strategies that will enhance the resilience of forest-dependent communities to a changing climate.

In this exploratory multiple case study, we aim to compare the internationalization of two state-owned enterprises (SOEs) owned by subnational governments with three owned by central governments in Latin America. This study provides a contextualized answer to the question: What are the differences in the internationalization of subnationally owned SOEs compared to central SOEs? This study finds that the speed and diversification of these two types of SOEs’ internationalization differ because they have a different expansion logic. Subnationally owned SOEs have a gradual and diversified expansion following market rules. Central government’s SOEs are specialized and take more drastic steps in their internationalization, which relates to non-market factors.

This study builds an exploratory qualitative comparative case analysis that uses multiple sources of data and information to develop a comprehensive understanding of SOEs through process tracing.

The study posits some assumptions that are confirmed in the case analysis. This study finds relevant differences between sub-national (SSOEs) and central authority (CSOEs’) strategies. SSOEs’ fewer resources and needs to increase income push them to follow a gradual market-driven internationalization and to diversify abroad. CSOEs non-gradual growth is justified by non-market factors (i.e. national politics). CSOEs do not diversify abroad due to the broader set of constituencies they have to face.

Given the exploratory comparative case study of this research, the findings are bounded by the particularities of the cases and their region (Latin America). This paper and its findings can be useful for theory building but it does not claim any generalization capacity.

This study adds complexity into the SOEs phenomenon by distinguishing between different types of SOEs. This paper contributes to the study of subnational phenomena and its effect in SOEs’ internationalization process, which is an understudied topic. To the authors’ best knowledge, this is among the first studies that explore subnational SOEs in Latin America.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

This research aims at analyzing the antecedents of absorptive capacity (ACAP) in the companies incubated in the State of Rio Grande do Norte, Brazil. In this context, 111 incubated companies took part in the research.

The methodology used the confirmatory factor analysis and the multiple linear regression to analyze the relationship of the dependent variables (ACAP) with the dependent variables (interaction with other companies, professionals' knowledge (PK), knowledge use (KU) and knowledge acquisition).

The results highlight that external KU was the construct that most influences the ACAP. Among the dependent variables suggested, only the construct concerning the incubators' PK presented no model significance, which shows that the PK is not an antecedent of ACAP in the incubated companies.

This study is relevant due to pointing out that the incubators may not be providing their professionals with knowledge properly, or that this knowledge is not being accessed by the incubated companies, which allows actions turned to encouraging businesses in this context.

The decarbonization of power generation is key to achieving carbon neutrality in China by the end of 2060. This paper aims to examine how green finance influences China’s low-carbon transition of power generation. Using a provincial panel data set as an empirical study example, green finance is assessed first, then empirically analyses the influences of green finance on the low-carbon transition of power generation, as well as intermediary mechanisms at play. Finally, this paper makes relevant recommendations for peak carbon and carbon neutrality in China.

To begin with, an evaluation index system with five indicators is constructed with entropy weighting method. Second, this paper uses the share of coal-fired power generation that takes in total power generation as an inverse indicator to measure the low-carbon transition in power generation. Finally, the authors perform generalized method of moments (GMM) econometric model to examine how green finance influences China’s low-carbon transition of power generation by taking advantage of 30 provincial panel data sets, spanning the period of 2007–2019. Meanwhile, the implementation of the 2016 Guidance on Green Finance is used as a turning point to address endogeneity using difference-in-difference method (DID).

The prosperity of green finance can markedly reduce the share of thermal power generation in total electricity generation, which implies a trend toward China’s low-carbon transformation in the power generation industry. Urbanization and R&D investment are driving forces influencing low-carbon transition, while economic development hinders the low-carbon transition. The conclusions remain robust after a series of tests such as the DID method, instrumental variable method and replacement indicators. Notably, the results of the mechanism analysis suggest that green finance contributes to low-carbon transformation in power generation by reducing secondary sectoral share, reducing the production of export products, promoting the advancement of green technologies and expanding the proportion of new installed capacity of renewable energy.

This paper puts forward relevant suggestions for promoting the green finance development with countermeasures such as allowing low interest rate for renewable energy power generation, facilitating market function and using carbon trade market. Additional policy implication is to promote high quality urbanization and increase R&D investment while pursuing high quality economic development. The last implication is to develop mechanism to strengthen the transformation of industrial structure, to promote high quality trade from high carbon manufactured products to low-carbon products, to stimulate more investment in green technology innovation and to accelerate the greening of installed structure in power generation industry.

This paper first attempts to examine the low-carbon transition in power generation from a new perspective of green finance. Second, this paper analyses the mechanism through several aspects: the share of secondary industry, the output of exported products, advances in green technology and the share of renewable energy in new installed capacity, which has not yet been done. Finally, this study constructs a system of indicators to evaluate green finance, including five indicators with entropy weighting method. In conclusion, this paper provides scientific references for sustainable development in China, and meanwhile for other developing countries with similar characteristics.