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Green innovation provides powerful incentives to achieve sustained social progress. However, the available research examines the financial drivers of green innovation, overlooking the impact of digital government development and the institutional environment. The integration of digital government construction with the institutional environment, and the coupling of the two with green innovation, will paint a picture of the future that promotes sustainable social progress and the modernization of governance. This research utilizes data from 31 provinces in China from 2018 to 2022 to study the impact of digital government construction and the institutional environment on the provincial green innovation efficiency. An empirical analysis is conducted on the basis of analyzing the spatiotemporal evolution and pattern of digital government construction, the institutional environment and the provincial green innovation efficiency. Firstly, digital government construction emphasizes data openness and sharing, and data become a key link between those inside and outside the government. The digital platform becomes an important carrier connecting the government and multiple subjects in collaborative innovation to continuously shape a new digital governance ecology. The netting of digital ecology is conducive to the institutional environment, serving to break the path dependence and create a more open, inclusive and synergistic institutional environment. Based on this, we consider that digital government construction positively affects the institutional environment, and this is verified. Secondly, a good government–market relationship, mature market development, a large market service scale, a complete property rights system and a fair legal system brought about by the improved institutional environment provide macro-external environmental support for enhanced innovation dynamics. Based on this, it is proposed that the institutional environment positively affects the provincial green innovation efficiency. Meanwhile, building on embeddedness theory, the industrial embeddedness of the institutional environment for green innovation highlights the scattered distribution of innovation components. Geographical embeddedness stresses indigenous resource distribution grounded in space vicinity and clustering. The better the institutional environment, the greater the forces of disempowerment at the industrial tier and the easier it is for resources to flow out. This may potentially have a detrimental role in improving the local green innovation efficiency. In view of this, it is proposed that the institutional environment negatively affects the provincial green innovation efficiency, and this is verified. Thirdly, digital government construction, as an important aspect of constructing a digital governance system and implementing the strategy of a strong network state, can effectively release the multiplier effect of digital technology in ecological environment governance and green innovation, continuously enhancing the provincial green innovation efficiency. In view of this, it is proposed that digital government construction positively affects the provincial green innovation efficiency, and this is verified. When the institutional environment is used as a mediating variable, digital government construction will have a certain non-linear impact in terms of provincial green innovation efficiency improvement. Building on the evidence-based analysis results, it is found that the institutional environment plays a competitive mediating role. This study integrates digital government construction, the institutional environment and the provincial green innovation efficiency under a unified analytical structure, offering theoretical inspiration and operational directions to enhance the provincial green innovation efficiency. Full article

In the current era, the economic model that measures the dependence of the training offered by companies to their employees on certain variables allows for identifying the steps taken on account of digital transformations, given the fact that companies want to be competitive, to develop sustainably and the positive effect to it spreads globally. However, how digital transformation contributes remains unclear in both the literature and practice. Five descriptors of information on the economy in relation to the digital economy were extracted from the Eurostat database, and data on eight Eastern European countries in the period 2012–2020 served as primary data in the analysis. A generalized linear model was used as a statistical tool to infer the data series. Following the statistical regression analysis, it was found that the variable measuring the share of companies that offered training for the development/improvement of information and communication technology (ICT) skills is influenced by the combined effect of several other variables: ‘country’, ‘country × year’, ‘country × share of ICT personnel in total employees’, year × “share of ICT sector in GDP”. Based on the results, we noticed that the studied countries are included in two groups with distinct features, which influence the obtained GLZ model, showing the increase in the dependency effect or, on the contrary, the decrease in this effect. Full article

The cultures and religious beliefs of Taiwanese indigenous peoples are deeply rooted in ecological protection and environmental ethics. Indigenous peoples emphasize reverence for nature, ecological diversity, sustainable living, resource sharing, and sanctity of nature. Integrating environmental education with indigenous culture can promote biodiversity and ecological conservation while preserving indigenous traditions and fostering sustainable development. This study combined Virtual Reality 360-degree (VR360) technology with indigenous culture to develop a virtual ecological system as a learning tool for environmental education in indigenous elementary schools. The VR360 system simulates the ecological environments of Chichiawan Creek and the Atayal Nanshan Tribe in the mountainous regions of northern Taiwan to provide students with immersive experiences that enhance their learning interest and motivation. Through interactive operations, they can observe the appearance, characteristics, and habitual behaviors of Formosan Landlocked Salmon and other conservation animals to understand the relationship between maintaining biodiversity and ecological balance. The VR360 ecological system enhances learning effectiveness and motivation using low-cost cardboard glasses, making it suitable for promoting indigenous culture and environmental education while reducing the digital divide in remote tribal areas. Full article

Individual physiotherapy is crucial in treating patients with various pain and health issues, and significantly impacts abdominal surgical outcomes and further medical problems. Recent technological and artificial intelligent advancements have equipped healthcare professionals with innovative tools, such as sensor systems and telemedicine equipment, offering groundbreaking opportunities to monitor and analyze patients’ physical activity. This paper investigates the potential applications of mobile accelerometers in evaluating the symmetry of specific rehabilitation exercises using a dataset of 1280 tests on 16 individuals in the age range between 8 and 75 years. A comprehensive computational methodology is introduced, incorporating traditional digital signal processing, feature extraction in both time and transform domains, and advanced classification techniques. The study employs a range of machine learning methods, including support vector machines, Bayesian analysis, and neural networks, to evaluate the balance of various physical activities. The proposed approach achieved a high classification accuracy of 90.6% in distinguishing between left- and right-side motion patterns by employing features from both the time and frequency domains using a two-layer neural network. These findings demonstrate promising applications of precise monitoring of rehabilitation exercises to increase the probability of successful surgical recovery, highlighting the potential to significantly enhance patient care and treatment outcomes. Full article

This study examines how digital technologies can improve a company’s overall sustainability. It also explores whether lean manufacturing practices can mediate the connection between digital technologies and sustainability. Data were collected from 319 senior managers, production managers, and general managers at Egyptian manufacturing companies and examined using the software Smart-PLS 4. The results show that digital technologies (i.e., blockchain, the Internet of Things, big data analytics, cloud computing, and the digital twins) have a positive impact on all three aspects of sustainability: environmental, social, and economic. Additionally, lean manufacturing was found to play a key role in this relationship. The model explained 34.3% of lean manufacturing practices, 59.7% of sustainable economic performance, 40.3% of sustainable social performance, and 40.6% of sustainable environmental performance. The findings of this study have some implications for companies, investors, and policymakers regarding how to improve economic, social, and environmental performance through fostering LMP and proper implementation of Digital Technologies (DTs). The current investigation extends the discourse on the role of digital technologies and new manufacturing techniques like lean manufacturing and how they can lead to sustainable performance. Positioned as one of the initial studies to examine the mediating role of lean manufacturing in the association between digital technologies and sustainable performance, this study provides insights within an emerging market context. Full article

In the context of digital construction, responsibility management in smart city building information modeling (BIM) projects spans the entire building lifecycle. The involvement of numerous BIM designers in project management and frequent data exchanges pose significant challenges for the traceability, immutability, and responsibility attribution of BIM models. To address these issues, this study proposes a blockchain-based responsibility management and collaboration framework for BIM projects using non-fungible tokens (NFTs), aiming to enhance the management of responsibilities and accountability in BIM projects. This research adopts a design science methodology, strictly adhering to scientific research procedures to ensure rigor. First, NFTs based on blockchain technology were developed to generate corresponding digital signatures for BIM model files. This approach ensures that each BIM model file has a unique digital identity, enhancing transparency and traceability in responsibility management. Next, the interplanetary file system (IPFS) was used to generate digital fingerprints, with the content identifier generated by IPFS uploaded to the blockchain to ensure the immutability of BIM model files. This method guarantees the integrity and security of BIM model files throughout their lifecycle. Finally, the proposed methods were validated through a blockchain network. The experimental results indicate that the proposed framework is theoretically highly feasible and demonstrates good applicability and efficiency in practical production. The constructed blockchain network meets the actual needs of responsibility management in smart city BIM projects, enhancing the transparency and reliability of project management. Full article

This study comprises a systematic literature review of 68 articles published between 2010 and 2024, identifying and coherently grouping the wine tourism sector’s adoption of technological innovation practices. The articles were analyzed using a framework developed from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The selection criteria included peer-reviewed, full-length articles in English emphasizing technological innovations in the wine tourism sector. The results highlight several key trends in technological innovation applied to wine tourism. The innovations were categorized into five areas: digital marketing and promotion, sustainability and innovation, immersive technologies (AR/VR), e-commerce and distribution models, and smart technologies for winery management. The review reveals a growing interest in digital marketing and immersive technologies in promoting wine tourism through digital platforms and creating engaging tourist experiences through virtual and augmented reality. The review focuses only on peer-reviewed studies published in English, which may limit its global scope. Books and non-peer-reviewed articles may have introduced further developments in technological innovation that are not captured in this review. This study is a post-COVID-19 review of technological innovation in wine tourism. The findings provide significant implications for researchers and policymakers, suggesting future research areas and offering insights on how public funds can support wine tourism’s digital transformation and sustainability Full article

This study proposes incorporating generative artificial intelligence large language models (LLMs) into the Master of Science (M.Sc.) curriculum on digitization in construction. The aim was to help students generate computer code to solve, automate, and streamline practical challenges in advanced construction engineering and management (CEM). To this end, a host of problem-based learning (PBL) individual assignments and collaborative team projects were developed, alongside a combination of flipped classroom models and blended learning lessons, in order to teach effective interactions with LLMs and mitigate concerns, such as bias and hallucination. The effective interaction with LLMs not only facilitated code generation, which would otherwise be complex without additional formal training, but also provided a platform for strengthening basic project management skills, such as departmentalization, work breakdown structuring, modularization, activity delegation, and defining key performance indicators. The effectiveness of this approach was quantitatively and qualitatively evaluated within two new modules, Digital Engineering and Construction and Digital Technologies in Field Information Modeling. These modules were offered over three semesters each as part of a new M.Sc. program in Technology and Management in Construction at the Karlsruhe Institute of Technology. It was observed that 86.4% of students fully completed the PBL projects, while the remaining 13.6% achieved over 50% completion across all six semesters. Furthermore, anonymous student surveys indicated a teaching quality index of 100% in five semesters and 96.4% in one semester. These preliminary results suggest that the proposed strategy can be used to effectively integrate LLMs to support students in code generation for open-ended projects in CEM. Further research was, however, found to be necessary to ensure the sustainable revision and redesign of the problems as LLM capabilities evolve. Full article

Sentiment analysis is a crucial tool for measuring public opinion and understanding human communication across digital social media platforms. However, due to linguistic complexities and limited data or computational resources, it is under-represented in many African languages. While state-of-the-art Afrocentric pre-trained language models (PLMs) have been developed for various natural language processing (NLP) tasks, their applications in eXplainable Artificial Intelligence (XAI) remain largely unexplored. In this study, we propose a novel approach that combines Afrocentric PLMs with XAI techniques for sentiment analysis. We demonstrate the effectiveness of incorporating attention mechanisms and visualization techniques in improving the transparency, trustworthiness, and decision-making capabilities of transformer-based models when making sentiment predictions. To validate our approach, we employ the SAfriSenti corpus, a multilingual sentiment dataset for South African under-resourced languages, and perform a series of sentiment analysis experiments. These experiments enable comprehensive evaluations, comparing the performance of Afrocentric models against mainstream PLMs. Our results show that the Afro-XLMR model outperforms all other models, achieving an average F1-score of 71.04% across five tested languages, and the lowest error rate among the evaluated models. Additionally, we enhance the interpretability and explainability of the Afro-XLMR model using Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP). These XAI techniques ensure that sentiment predictions are not only accurate and interpretable but also understandable, fostering trust and reliability in AI-driven NLP technologies, particularly in the context of African languages. Full article

Based on city-level data from 287 Chinese prefecture-level administrative units spanning 2011 to 2021, this study employs text analysis to quantify FinTech development and applies a double machine learning model to empirically assess the impact of FinTech on Inclusive Green Growth, along with its underlying mechanisms. The key findings are as follows: (1) FinTech significantly promotes Inclusive Green Growth, particularly in the areas of payment systems, lending and capital raising, and investment management. This conclusion holds across a range of robustness checks, including alternative measurement indicators, different machine learning models, and tests for endogeneity. (2) Mechanism analysis demonstrates that FinTech drives Inclusive Green Growth by fostering financial employment, expanding financial supply, and facilitating green technological innovation. (3) Heterogeneity analysis reveals that while China still faces elements of the resource curse, the positive impact of FinTech on Inclusive Green Growth is more pronounced in regions with higher levels of digital infrastructure, environmental regulation, and green finance. These findings provide valuable insights into leveraging FinTech’s potential to support China’s high-quality economic development. Full article

Yunnan Dendrocalamus sinicus Chia et J. L. Sun (YDS) is a giant bamboo species with a diameter at breast height of up to nearly 40 cm. It is endemic to Yunnan, China, and only a very small portion of it is directly used as load-bearing beams and columns in the dwellings of ethnic minorities, such as in Dai architecture. Due to the structural characteristics of its hollow and thin walls, systematic physical and mechanical property testing of this species faces significant challenges in terms of methods and means. This issue has become one of the main barriers to the realization of its large-scale industrial use. Therefore, this paper systematically tests and studies YDS’s three kinds of strength (tension, compression, and shear), modulus of elasticity, and six Poisson’s ratios with the help of digital image correlation (DIC) technology and self-created material testing methods. The (1) tensile, compressive, and shear strengths and moduli in longitudinal, radial, and chordal directions; (2) tensile strengths and moduli of bamboo green, flesh, and yellow layers in the thickness direction of the bamboo wall; and (3) six Poisson’s ratios under tensile and compressive stresses were obtained for YDS. It was also found that the tensile strength (378.8 MPa) of the green layer of YDS exceeded the yield strength (355 MPa) of 45# steel, making it a potential high-strength engineering material or fiber-reinforced material. Full article

In the later stages of oilfield development, the decline in oil well production and the increase in development costs, attributed to issues such as insufficient liquid supply, necessitate the implementation of intermittent pumping measures. However, current methods for selecting these wells lack comprehensiveness in the decision-making process. This article proposes a novel method for selecting intermittent pumping wells utilizing the analytic network process (ANP) and fuzzy logic. Initial surveys identified the main factors influencing intermittent pumping effectiveness. The ANP was employed to screen and integrate six core factors, including submergence depth and water cut. Subsequently, a fuzzy-logic-based model was developed, incorporating trapezoidal and rectangular membership functions to establish detailed correlations among the factors. The model’s efficacy was validated and tested using real-world data from the oilfield. Results indicate that the model’s assessments of intermittent pumping wells align closely with professional engineering judgments. This approach not only provides clear guidance for well selection but also demonstrates high scalability and adaptability across different oilfields by adjusting membership functions, thereby showcasing significant practical value. Full article

The evaluation of smartphone camera technology for close-range photogrammetry includes assessing captured photos for 3D measurement. In this work, experiments are conducted on many smartphones to study distortion levels and accuracy performance in close-range photogrammetry applications. Analytical methods and specialized digital tools are employed to evaluate the results. OpenCV functions estimate the distortions introduced by the lens. Diagrams, evaluation images, statistical quantities, and indicators are utilized to compare the results among sensors. The accuracy achieved in photogrammetry is examined using the photogrammetric bundle adjustment in a real-world application. In the end, generalized conclusions are drawn regarding this technology’s use in close-range photogrammetry applications. Full article

In a rapidly evolving technological landscape, manufacturers are increasingly pressured to undertake digital transformation, with smart manufacturing serving as a crucial milestone in this process. This study investigates the key factors influencing the implementation of smart manufacturing from a supply chain perspective, employing the analytical hierarchy process (AHP) to analyze collected data from senior managers of manufacturing firms. The findings highlight several critical factors, including the commitment of senior executives, the recruitment of skilled professionals, interdepartmental collaboration, and financial support. Moreover, this study reveals differing priorities between large and small manufacturers: large firms emphasize the importance of the Industrial Internet of Things (IIoT), while smaller firms prioritize understanding end-consumer needs and product trends. This study emphasizes that smart manufacturing is not only for optimizing the operational efficiency of manufacturing firms but also for supporting sustainability efforts through more effective use of resources and reduced environmental impact of work processes. Full article

Background: The following case report presents the treatment of a patient with severe maxillary atrophy and failing residual dentition. The patient has been diagnosed with stage IV grade C periodontitis, making this case challenging from the very beginning. Methods: The treatment plan was based on collecting and merging digital data: CBCT, a face scan, and an intraoral scan. Due to the advancement of the periodontal disease, the treatment was divided into three stages. The entire process was conducted in a digital manner, based on the concept of prosthetically driven implantology. Additionally, all prosthetic temporaries were planned via digital smile design. Stage I included extracting the residual dentition, placing four implants in the mandible, and the delivery of a 3D-printed upper removable denture. Stage II included placing two zygomatic implants, two anchored piriform rims, and one midline implant. Both arches were immediately loaded with the intraoral welding of abutments screwed to multiunit abutments and 3D-printed shells. Subsequently, in stage III, two milled ceramic superstructures combined with a titanium milled bar were delivered as a final screw-retained restoration with the application of scan flags (horizontal scan bodies) for intraoral scanning. Results: The aforementioned technologies can all be implemented and merged into one complex treatment plan combining high predictability, successful esthetics, and a reliable and accurate end result. Even though the concept of scan flags is relatively new, this case shows its potential and merit. Conclusions: This case represents the power of the digital approach as a helpful tool in the recreation of functional and esthetic smiles in compromised conditions in periodontal patients. Full article