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This study aims to improve the control accuracy and antidisturbance performance of the manipulator with the flexible link, a combined controller, which combines the novel backstepping sliding mode controller based on the extended state observer (ESO) and super-twisting sliding mode controller.

First, the dynamic of the system is constructed by Lagrange method and assumed mode method, and then the dynamic is decoupled by the singular perturbation theory to obtain the slow-varying subsystem and fast-varying subsystem. For the slow-varying subsystem, the novel backstepping sliding mode controller based on ESO is used to achieve joint tracking. For the fast-varying subsystem, the super-twisting sliding mode controller is used for vibration suppression. At the same time, to suppress chattering, the tanh function is used to replace the sign function in the reaching law.

The simulation results show that the combined control has better trajectory tracking performance, antiinterference performance and vibration suppression performance than traditional sliding mode control (SMC).

A novel backstepping sliding mode controller based on ESO is designed to guarantee the performance of the tracking trajectory. The new controller improves the converge rate. A super-twisting sliding mode controller, which can stabilize the fast-varying subsystem, is used to suppress the vibration of flexible link.

This paper aims to identify aspects of how work-life interaction has changed in the post-pandemic situations and propose strategies of the security concept for living-working patterns in the post-pandemic interior as future disease prevention.

We conducted a systematic literature search and review to select previous research systematically and relate concepts by coding the data and synthesising the data critically. The systematic literature search and review considered 90 papers (35 were studied).

The findings identify three strategies: hybrid activity patterns, new layout for hybrid and changing behaviour and culture. Each strategy demonstrates the connection between the hybrid living-working interior spaces in the post-pandemic period and security-pandemic variables. The results on security design factors focused on interior control, detection and deterrence; connection to nature creates a safer environment to prevent further variables; and hybrid activity requires more elements to govern users' behaviour and culture.

Limitations of this study are as follows: excluded papers that are not written in English/Bahasa or do not have gold/green open access; some aspects were not discussed (such as social distancing); the articles included in this review are up to April 2023 (and there is the possibility of recent papers). Future studies can be developed to update building certification for post-pandemic interiors or research with psychological, social equity or family vitality issues.

The study offers strategies and the holistic relationship between the post-pandemic concept and security-pandemic design variables within the built environment, especially in the users' culture and behaviour context.

This study aims to examine the connection between scholars' research performance and the multidisciplinary nature of their collaborative research. Furthermore, in response to mixed results regarding the effects of multidisciplinarity on research performance, this study explores how human resource management (HRM) practices may moderate this link.

The authors built a model based on the theoretical arguments and empirical evidence found in the review of diversity and HRM literature. The authors also performed a quantitative study based on a sample of scholars in the field of management. Different econometric estimations were used to test the proposed model.

The results of this empirical analysis suggest that multidisciplinary research has a non-linear effect on research performance. Certain HRM practices, such as development and collaboration, moderated the curvilinear relationship between multidisciplinarity and performance, displacing the optimum to allow higher performance at higher levels of multidisciplinary research.

The paper provides advances on previous works studying the curvilinear relationship between multidisciplinarity and the researchers' performance, confirming that multidisciplinarity is beneficial up to a threshold beyond which these benefits are attenuated. In addition, the findings shed light on important issues related to team-oriented HRM practices associated with the outcomes of multidisciplinary research.

Artificial Intelligence (AI) has revolutionized teaching and learning methods in higher education, especially in English language teaching and learning. This chapter contributes to the existing knowledge by exploring how AI has developed within the framework of teaching and learning of English, highlighting the challenges, dangers, and moral issues associated with its application. The typical classroom environment has significantly changed because of the integration of AI-powered tools and platforms in English instruction. Chatbots, automated grading systems, and language learning apps driven by AI have streamlined language education, increasing its effectiveness and accessibility. But these benefits accompany a variety of challenges and worries. Ethical concerns about data privacy, algorithmic biases, and the depersonalization of education arise as AI becomes more deeply ingrained in educational methods. Reliance on AI may inadvertently exacerbate educational disparities as long as learners' access to technology and its advantages remain unequal. In addition, significant thought must be given to the ethical ramifications of AI-generated content as well as the possible loss of human connection in language learning settings. This chapter examines these dangers and challenges and makes the case for a well-rounded strategy that maximizes AI's benefits while minimizing any potential downsides. Together, educators and legislators need to create moral guidelines that balance the potential of AI with human-centered learning experiences. To ensure responsible and fair AI integration and promote an inclusive learning environment that prioritizes students' holistic development while exploiting technology breakthroughs, comprehensive assessment of the associated obstacles, risks, and ethical issues is necessary.

Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.

Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.

Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.

In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.

This study aims to examine the extent and quality of biodiversity reporting within publicly traded companies in Italy during 2022, amidst growing calls worldwide for enhanced corporate environmental responsibility.

The study proposes a framework derived from existing biodiversity reporting literature and international guidelines on the topic. Using data from companies’ non-financial reports, the voluntary biodiversity disclosure index is quantified on disclosed information. Various quality reporting characteristics are also deepened. Sector-specific analysis is conducted across 11 industries.

Approximately 30% of companies in the sample release information on their biodiversity practices/initiatives regarding biodiversity and extinction loss risks. Quantitative analysis reveals a general commitment to disclosure yet falls short of optimal standards. Qualitative insights suggest a genuine intention towards reporting exists, with notable gaps in future orientation, double materiality and mitigation strategies. The quality analysis underscores that the reporting is mainly generalised, narrative and disaggregated concerning actions to restore habitats and ecosystems.

A limitation of this study is the observation of annual reports during one reporting period. Future studies of longer duration would provide cross-period insights into corporate behaviour.

Policymakers should implement regulations and guidelines specifically tailored to biodiversity reporting, providing clear frameworks and standards for companies. Collaborative initiatives between governments, businesses and environmental organisations offer potential to develop best practices and facilitate knowledge-sharing in biodiversity reporting.

Collaborative initiatives between governments, businesses and environmental organisations offer potential to develop best practices and facilitate knowledge sharing in biodiversity reporting.

The study contributes to future biodiversity disclosure research by introducing a comprehensive framework that fosters stakeholder trust and environmental accountability. It also sheds light on biodiversity stewardship among Italian companies, under EU directives.

According to G20, ‘Inclusiveness basically signifies the accessibility of the various resources (goods, services, and livelihoods) on a commercially viable basis to the economically vulnerable section of the society through making them part of the organizations' value chain as customers, retailers, distributors, and suppliers’. With the increased application of digital technology in every sphere of life, the concept of inclusiveness has moved to e-inclusiveness. So, the present chapter tried to investigate the conceptual journey from inclusiveness to e-inclusiveness from business and financial system aspects. Further, it presents an insight into how the e-inclusiveness aspect impacts the poverty level mainly from the developing country's perspective. The study also suggests that from the perspective of developed as well as developing economies, the public and private sector players strive to develop an effective financial system incorporating an inclusiveness aspect.

This study aims to evaluate the behavioral predictors that affect tourists’ intentions to visit silver screen destinations.

The survey questionnaire was composed of multi-item measures, and a total of 432 questionnaires were collected by purposive sampling technique. Participants were asked about sensory stimuli, social stimuli, naturalistic stimuli, cultural stimuli, hospitality culture stimuli, cognitive responses, affective responses and behavior approach, which were evaluated using a seven-point Likert scale.

The authors discovered that cognitive and affective responses positively influence the tourists’ intention toward destinations with film-induced tourism, because tourists highly value unique and refreshing symbolic connotations of silver screen destinations, which are commonly predisposed to nostalgia and poetic on the scene.

The originality of this study and the theoretical value of the present research lies with revealing specific relations within the film-induced experienscape constructs that are based on the multistakeholder and multidisciplinary approach. Moreover, this study puts forward constructive suggestions for destination stakeholders in regard to how to market film-induced tourism that uses a multidisciplinary approach that is encompassed by experienscape constructs, which thereby reinforces the film-induced tourists’ experience and their behavior approach.

This study proposes a deep learning algorithm-based model to predict the repair and maintenance costs of apartment buildings, by collecting repair and maintenance cost data that were incurred in an actual apartment complex. More specifically, a long short-term memory (LSTM) algorithm was adopted to develop the prediction model, while the robustness of the model was verified by recurrent neural networks (RNN) and gated recurrent units (GRU) models.

Repair and maintenance cost data incurred in actual apartment complexes is collected, along with various input variables, such as repair and maintenance timing (calendar year), usage types, building ages, temperature, precipitation, wind speed, humidity and solar radiation. Then, the LSTM algorithm is employed to predict the costs, while two other learning models (RNN and GRU) are taught to validate the robustness of the LSTM model based on R-squared values, mean absolute errors and root mean square errors.

The LSTM model’s learning is more accurate and reliable to predict repair and maintenance costs of apartment complex, compared to the RNN and GRU models’ learning performance. The proposed model provides a valuable tool that can contribute to mitigating financial management risks and reducing losses in forthcoming apartment construction projects.

Gathering a real-world high-quality data set of apartment’s repair and maintenance costs, this study provides a highly reliable prediction model that can respond to various scenarios to help apartment complex managers plan resources more efficiently, and manage the budget required for repair and maintenance more effectively.

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.