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Therapeutic landscapes can be beneficial for patients recovering from cognitive and behavioural impairments. The therapeutic garden in the Royal Talbot rehabilitation centre (RTRC) located in Kew, Melbourne is a precedent for its nature design outdoor spaces and horticultural therapy (HT) program for patients with cognitive impairments due to brain and spinal cord injuries. There have been no studies into the physical design of the RTRC therapeutic garden.

This case study unveils the critical design themes, and dominant physical elements of the RTRC therapeutic garden through site observation and analysis over the course of two months, a semi-structured interview with a key staff, and graphical representations using integrated photography and collaborative digital tools of AutoCAD and Adobe Photoshop.

Seven critical design themes are identified for the RTRC garden: (1) space layout and organization, (2) physical and visual access, (3) pathway and facility, (4) multisensory vegetation, (5) amenity, wayfinding and seasonal interest, (6) cognitive stimulation, (7) utility and HT. Qualitative and quantitative data analysed in visual and descriptive format reveal multisensory vegetation, amenity, wayfinding and seasonal interest, and utility and HT are the top three most pivotal critical design themes in the RTRC therapeutic garden.

The findings of this case study can be used to impart knowledge about the design of therapeutic landscape settings for cognitive impairments to design professionals and the public.

There is no case study has been conducted for this precedent of therapeutic garden in the Royal Talbot rehabilitation centre that targets for cognitive impairment patients. With the increasing awareness in medical and healthcare environments, this case study would help to inject mutual understanding, generate knowledge and design awareness among design professionals and public, and to cultivate more good quality healthcare settings.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The United National Convention on the Rights of Persons with Disabilities (UNCRPD) emphasises the need for those with disabilities to be guaranteed full access to participation in society (United Nations, 2006). This rights-based approach in higher education foregrounds the importance of removing practical and attitudinal barriers within how institutions, or staff, interact with students with traumatic brain injury (TBI) that facilitate their access. This chapter summarises the key findings of my PhD thesis where I use my unique positioning as a TBI survivor and status as a PhD student to gain deeper understanding of the experience of access for neurodiverse students in higher education. I contend that we can be marginalised in these settings. In this chapter, I argue for the importance of student voice in decision and policymaking processes in higher education, aligning with ‘nothing about us, without us’ (Charlton, 2000). A blended methodology of autoethnography and phenomenology was used in my scholarship, which meant listening to the perspectives of students with TBI who often navigate the educational environment differently. Loss, change of identity and care are significant factors in shaping experiences. This research has much to offer as it uses the researcher's and participant's voices to transform rather than maintain the status quo regarding access for students with TBI. Inclusive education must place flexibility and diversity at its core and consider the person when putting academic programmes and support in place.

This article reports on a study that explored how the Tanzanian government can support the development of research-intensive universities in its higher education system.

Data were collected through document analysis and in-depth semi-structured interviews with participants obtained from national higher education departments, senior university leadership offices and academic staff in both public and private universities.

The study identified four essential systemic elements for developing research-intensive universities (RIUs): diversification of universities based on their core functions, allocation of financial resources according to research performance, relaxation of university governing systems and accrediting universities based on research outcomes.

The study identified essential systemic elements that could address the issue of developing RIUs in low- and middle-income countries (LMICs). These elements present a potential solution for developing a diverse higher education system capable of sustaining RIUs, offering opportunities to produce innovative knowledge, develop diverse skills and meet the needs of a range of students, employers and businesses.

This study adds to the body of knowledge on how LMICs can develop well-functioning RIUs. The study also contributes to the ongoing debates among higher education stakeholders, including governments, academics, students and the community, on the changing dynamics of higher education and its role in national and regional development.

The study examines potential differences in socioeconomic status (SES) and emigration patterns between Greek international students (IS) and non-international students (non-IS) and their relationship to the brain drain from Greece.

The study draws on a unique database including all the Greek PhD holders and provides detailed information on their SES and mobility patterns. Furthermore, an individual-level SES index is constructed including both human capital and socioeconomic indicators to estimate the magnitude of the brain drain in terms of the SES that emigrated abroad between 1,985 and 2,018.

First, Greek IS have a higher educational, professional and economic status compared to Greek non-IS. Moreover, they exhibit a more international profile, inasmuch as they are more likely to remain abroad after graduation to seek employment. Second, the magnitude of the brain drain in terms of SES emigrated abroad (22.5% of the total) is greater than in terms of individuals who moved abroad (13.4% of the total). Specifically, the SES that outflows with an additional Greek skilled emigrant (that is, an additional IS and non-IS residing abroad) is 1.1 times greater than the SES that remains in Greece with an additional non-IS residing in Greece.

The study contributes to the scientific discussion that relates the SES of IS and highly skilled migrants to brain drain and fills the gap in the relevant literature.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0607.

The purpose of this study is to explore the intersection of mindfulness practices and ethical decision-making within organisational leadership. Drawing from ancient Buddhist principles and contemporary neuroscience, this study aims to illuminate how mindfulness can enhance cognitive and emotional regulation, thereby fostering ethical behaviour and improved decision-making among leaders and employees. By examining the theoretical and practical implications of mindfulness in the context of organisational behaviour, this research seeks to contribute to the development of more compassionate, ethical and effective leadership practices, ultimately promoting a more mindful and sustainable business environment.

This concept paper explores the integration of mindfulness meditation practices with decision-making, particularly its influence on ethical choices, through a comparative study of modern techniques and the ancient teachings of the Tripitaka. Using a methodology that spans literature review in organisational behaviour and leadership, alongside in-depth analysis of the Tripitaka and contributions from scholars like Bhikkhu Bodhi, the paper examines the potential of mindfulness in enhancing ethical decision-making. It incorporates a range of sources, including peer-reviewed journals and seminal books across various disciplines, to underscore the transformative potential of mindfulness in addressing contemporary challenges and guiding leadership practices.

This discussion explores how mindfulness, rooted in ancient Buddhist philosophy and aligned with modern neuroscience, can significantly enhance managerial decision-making by fostering a balance between cognitive and emotional factors. It delves into the transformative potential of mindfulness in refining thought processes, promoting ethical decision-making and mitigating cognitive biases. By bridging traditional wisdom with contemporary scientific insights, the analysis underscores mindfulness as an active, dynamic process crucial for personal growth and effective leadership in complex environments.

One limitation of this research is its reliance on theoretical frameworks and literature reviews, which may not capture the full range of practical challenges in implementing mindfulness practices within organisations. Additionally, the diversity in mindfulness methodologies and the subjective nature of mindfulness experiences may affect the generalisability of the findings. Future research should include empirical studies to validate the proposed benefits of mindfulness in organisational settings and explore the most effective strategies for integrating mindfulness practices into leadership and decision-making processes. This would help in understanding how mindfulness can be tailored to suit different organisational cultures and individual preferences.

The practical implications of applying mindfulness in organisational settings include enhanced decision-making abilities, improved leadership effectiveness and increased employee well-being. Mindfulness training can equip leaders and employees with the skills to manage stress, navigate complex ethical decisions and maintain focus amidst distractions, leading to more thoughtful and responsible business practices. Organisations might see a reduction in conflict, enhanced creativity and better teamwork, contributing to a more harmonious and productive workplace. Implementing mindfulness programmes could also support talent retention and attraction by promoting a workplace culture that values mental health and ethical behaviour.

The social implications of integrating mindfulness into organisational decision-making and leadership, as suggested by the document, include promoting ethical behaviour, enhancing emotional regulation and improving team dynamics. Mindfulness practices can lead to more informed and conscious decision-making, reducing cognitive biases and fostering a culture of ethical awareness within organisations. This shift towards mindful leadership could potentially transform organisational cultures, encouraging greater compassion, ethical responsibility and collective well-being, thereby contributing positively to broader societal values and norms.

The originality and value of this research lie in its novel integration of mindfulness concepts derived from ancient Buddhist teachings with contemporary neuroscience and organisational behaviour studies. By exploring the deep-rooted philosophical underpinnings of mindfulness and their applicability to modern ethical decision-making and leadership practices, this work offers a unique perspective that bridges historical wisdom with current scientific understanding. It provides a comprehensive framework for understanding the transformative potential of mindfulness in organisational settings, highlighting its capacity to foster ethical leadership, enhance decision-making processes and contribute to a more mindful, compassionate and sustainable business environment.

This study aims to discuss the mathematical modelling of a compliance-assisted flapping mechanism and morphable structures for an UAV.

A compliance-assisted flapping wing was designed and modelled mathematically, and signals for the corresponding curves were calculated. The actual wing tip trace of a hummingbird was taken, and variables a, b, h and k were calculated from the image. This data was given to the mathematical model for plotting the graph, and the curve was compared with the input curve. The wing frame and mechanism for control surfaces using morphing is modelled along with single pivoted spine for centre of gravity augmentation and flight orientation control.

The model efficiently approximates the 2D path of the wing using line segments using the muscle and compliance mechanism.

Using a compliance-assisted flapping mechanism offers practical advantages. It allows us to synchronize the flapping frequency with the input signal frequency, ensuring efficient operation. Additionally, the authors can enhance the torque output by using multiple muscle strands, resulting in a substantial increase in the system’s torque-to-weight ratio. This approach proves to be more favourable when compared to conventional methods involving motors or servos, ultimately offering a more efficient and robust solution for practical application.

This model focuses on creating a flexible and tunable mechanism that can at least trace four types of wing traces from the same design, for shifting from one mode of flight to another.

Conventional ornithopter flapping mechanisms are gear or servo driven and cannot trace a wing tip, but some can trace complicated curves, but only one at a time. This model can trace multiple curves using the same hardware, allowing the user to program the curve based on their needs or bird. The authors may vary the shape of the wing tip trace to switch between forward flight, hovering, backward flying, etc., which is not conceivable with any traditional flapping mechanism.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

The internal (farmer-controlled) and external (non-farmer-controlled) factors affect crop yield. However, not a single study has identified and analyzed yield predictors in India using effective predictive models. Thus, this study aims to investigate how internal and external predictors impact pearl millet yield and Stover yield.

Descriptive analytics and artificial neural network are used to investigate the impact of predictors on pearl millet yield and Stover yield. From descriptive analytics, 473 valid responses were collected from semi-arid zone, and the predictors were categorized into internal and external factors. Multi-layer perceptron-neural network (MLP-NN) model was used in Statistical Package for the Social Sciences version 25 to model them.

The MLP-NN model reveals that rainfall has the highest normalized importance, followed by irrigation frequency, crop rotation frequency, fertilizers type and temperature. The model has an acceptable goodness of fit because the training and testing methods have average root mean square errors of 0.25 and 0.28, respectively. Also, the model has R² values of 0.863 and 0.704, respectively, for both pearl millet and Stover yield.

To the best of the authors’ knowledge, the current study is first of its kind related to impact of predictors of both internal and external factors on pearl millet yield and Stover yield.

The literature reveals that most studies have estimated crop yield using limited parameters and forecasting approaches. However, this research will examine the impact of various predictors such as internal and external of both yields. The outcomes of the study will help policymakers in developing strategies for stakeholders. The current work will improve pearl millet yield literature.

The selection of sensitive temperature measurement points is the premise of thermal error modeling and compensation. However, most of the sensitive temperature measurement point selection methods do not consider the influence of the variability of thermal sensitive points on thermal error modeling and compensation. This paper considers the variability of thermal sensitive points, and aims to propose a sensitive temperature measurement point selection method and thermal error modeling method that can reduce the influence of thermal sensitive point variability.

Taking the truss robot as the experimental object, the finite element method is used to construct the simulation model of the truss robot, and the temperature measurement point layout scheme is designed based on the simulation model to collect the temperature and thermal error data. After the clustering of the temperature measurement point data is completed, the improved attention mechanism is used to extract the temperature data of the key time steps of the temperature measurement points in each category for thermal error modeling.

By comparing with the thermal error modeling method of the conventional fixed sensitive temperature measurement points, it is proved that the method proposed in this paper is more flexible in the processing of sensitive temperature measurement points and more stable in prediction accuracy.

The Grey Attention-Long Short Term Memory (GA-LSTM) thermal error prediction model proposed in this paper can reduce the influence of the variability of thermal sensitive points on the accuracy of thermal error modeling in long-term processing, and improve the accuracy of thermal error prediction model, which has certain application value. It has guiding significance for thermal error compensation prediction.