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This paper aims to provide an overview of the current manufacturing methods for three-dimensional textile preforms while providing experimental data on the emerging techniques of combining yarn interlocking with yarn interlooping.

The paper describes the key textile technologies used for composite manufacture: braiding, weaving and knitting. The various textile preforming methods are suited to different applications; their capabilities and end performance characteristics are analysed.

Such preforms are used in composites in a wide range of industries, from aerospace to medical and automotive to civil engineering. The paper highlights how the use of knitting technology for preform manufacture has gained wider acceptance due to its flexibility in design and shaping capabilities. The tensile properties of glass fibre knit structures containing inlay yarns interlocked between knitted loops are given, highlighting the importance of reinforcement yarns.

The future trends of reinforcement yarns in knitted structures for improved tensile properties are discussed, with initial experimental data.

This case study aims to shed light on what went wrong with the introduction of new surgical suture in a Dutch hospital operating theatre following a tender. Transition to working with new surgical suture was organized in accordance with legal and contractual provisions, and basic principles of change management were applied, but resistance from surgeons led to cancellation of supplies of the new suture.

Researchers had access to all documents relevant to the tendering procedure and crucial correspondence between stakeholders. Seventeen in-depth, 1 h interviews were conducted with key informants who were targeted through maximum variation sampling. Patients were not interviewed. The interviews were recorded, transcribed and analysed by discourse analysis. A trial session and workshop were participatively observed. A cultural psychological perspective was adopted to gain an understanding of why certain practices appear to be resistant to change.

For the cardiothoracic surgeons, suture was more than just stitching material. Suture as a tactile element in their day-to-day work environment is embedded within a social arrangement that ties elements of professional accountability, risk avoidance and direct patient care together in a way that makes sense and feels secure. This arrangement is not to be fumbled with by outsiders.

By understanding the practical and emotional stakes that medical professionals have in their work, lessons can be learned to prevent failure of future change initiatives.

The cultural psychological perspective adopted in this study has never been applied to understanding failed change in a hospital setting.

The operating wagon records were produced from distinct railway information systems, which resulted in the wagon routing record with the same oriental destination (OD) was different. This phenomenon has brought considerable difficulties to the railway wagon flow forecast. Some were because of poor data quality, which misled the actual prediction, while others were because of the existence of another actual wagon routings. This paper aims at finding all the wagon routing locus patterns from the history records, and thus puts forward an intelligent recognition method for the actual routing locus pattern of railway wagon flow based on SST algorithm.

Based on the big data of railway wagon flow records, the routing metadata model is constructed, and the historical data and real-time data are fused to improve the reliability of the path forecast results in the work of railway wagon flow forecast. Based on the division of spatial characteristics and the reduction of dimension in the distributary station, the improved Simhash algorithm is used to calculate the routing fingerprint. Combined with Squared Error Adjacency Matrix Clustering algorithm and Tarjan algorithm, the fingerprint similarity is calculated, the spatial characteristics are clustering and identified, the routing locus mode is formed and then the intelligent recognition of the actual wagon flow routing locus is realized.

This paper puts forward a more realistic method of railway wagon routing pattern recognition algorithm. The problem of traditional railway wagon routing planning is converted into the routing locus pattern recognition problem, and the wagon routing pattern of all OD streams is excavated from the historical data results. The analysis is carried out from three aspects: routing metadata, routing locus fingerprint and routing locus pattern. Then, the intelligent recognition SST-based algorithm of railway wagon routing locus pattern is proposed, which combines the history data and instant data to improve the reliability of the wagon routing selection result. Finally, railway wagon routing locus could be found out accurately, and the case study tests the validity of the algorithm.

Before the forecasting work of railway wagon flow, it needs to know how many kinds of wagon routing locus exist in a certain OD. Mining all the OD routing locus patterns from the railway wagon operating records is helpful to forecast the future routing combined with the wagon characteristics. The work of this paper is the basis of the railway wagon routing forecast.

As the basis of the railway wagon routing forecast, this research not only improves the accuracy and efficiency for the railway wagon routing forecast but also provides the further support of decision-making for the railway freight transportation organization.

The purpose of this study is the introduction and validation of a new technique for process monitoring during electron beam melting (EBM).

In this study, a backscatter electron detector inside the building chamber is used for image acquisition during EBM process. By systematic variation of process parameters, the ability of displaying different topographies, especially pores, is investigated. The results are evaluated in terms of porosity and compared with optical microscopy and X-ray computed tomography.

The method is capable of detecting major flaws (e.g. pores) and gives information about the quality of the resulting component.

Image acquisition by evaluating backscatter electrons during EBM process is a new approach in process monitoring which avoids disadvantages restricting previously investigated techniques.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

The paper aims to investigate the comfort-related performances of an innovative solar shading solution based on a new composite patented material that consists of a cement-based matrix coupled with a stretchable three-dimensional textile. The paper’s aim is, through a performance-based generative design approach, to develop a high-performance static shading system able to guarantee adequate daylit spaces, a connection with the outdoors and a glare-free environment in the view of a holistic and occupant-centric daylight assessment.

The paper describes the design and simulation process of a complex static shading system for digital manufacturing purposes. Initially, the optical material properties were characterized to calibrate radiance-based simulations. The developed models were then implemented in a multi-objective genetic optimization algorithm to improve the shading geometries, and their performance was assessed and compared with traditional external louvres and overhangs.

The system developed demonstrates, for a reference office space located in Milan (Italy), the potential of increasing useful daylight illuminance by 35% with a reduced glare of up to 70%–80% while providing better uniformity and connection with the outdoors as a result of a topological optimization of the shape and position of the openings.

The paper presents the innovative nature of a new composite material that, coupled with the proposed performance-based optimization process, enables the fabrication of optimized shading/cladding surfaces with complex geometries whose formability does not require ad hoc formworks, making the process fast and economic.

Under the unique context of COVID-19, this paper aims to analyze how the Government of Pakistan (GoP) provides financial and non-financial support to women entrepreneurs in Pakistan. Drawing on the resource-based theory of entrepreneurship (RBTE), the study advances the understanding of resources and grants offered by GoP to women entrepreneurs to help them in business survival.

The study adopts qualitative research method to address the questions: how does the Pakistani government respond to issues faced by women entrepreneurs during the COVID-19 pandemic, and what assistance and initiatives were implemented by GoP? Semi-structured interviews were conducted with twenty on-job government officials related to the entrepreneurial sector in Pakistan.

The paper reveals that during the pandemic, GoP keenly communicated with women entrepreneurial representatives to comprehend their business challenges. In addition, waivers and incentives were provided to support their business activities. GoP further invited women entrepreneurs to contribute their knowledge and give suggestions in policy making.

Lots of research have been conducted to identify the issues faced by women entrepreneurs during the pandemic. However, the specific strategies, policies, and support provided by the governments to address these issues have often been overlooked. This paper fills such gap with focus on the governing bodies and policymakers in Pakistan towards women entrepreneurship during the COVID-19 crisis.

The Group of Twenty (G20) has substantial influence in global economic policy but has been peripheral in global education governance. There is intensification of education policy-relevant engagement within the Think 20 (T20), the “ideas bank” and official engagement group of the G20. The authors analyse the evolution of education as a policy domain within the T20, the ideas and discursive framing of education and global education policy “solutions” and assumptions about the G20 in education policy engagement.

The authors view the T20 as an external actor that can mobilise policy-relevant ideas to G20 actors responsible for internal policy selection and translation. The analysis covers the period 2018–2021 when education became an explicit T20 policy area. The authors screened all 461 T20 policy briefs across all domains. Of these, 32 briefs and four final T20 Summit communiqués were reviewed using critical discourse analysis. Data were supplemented via organisational websites and tacit professional knowledge.

Three assumptions on the G20 as an actor prevailed: (1) policymaker, (2) policy shaper and (3) knowledge mobiliser. The framing ideas on education were linked to assumptions on drivers of education system reform as intertwined with, or to enable: (1) economic adaptation, (2) technical adaptation and (3) socio-political adaptation of individuals and societies.

Accelerated education engagement within the T20 and its direct reach to G20 leaders makes it, and the G20, analytically unique and new unexamined actors of potential influence. The authors conclude that the T20 is positioned as a unique actor, both that can mobilise education policy-relevant ideas to G20 leaders, and legitimised as the actor from which G20 leaders and policymakers should adopt ideas.

This study investigates the relationships between team dynamics and performance in healthcare operations. Specifically, it explores, through wearable sensors, how team coordination mechanisms can influence the likelihood of surgical glitches during routine surgery.

Breast surgeries of a large Italian university hospital were monitored using Sociometric Badges – wearable sensors developed at MIT Media Lab – for collecting objective and systematic measures of individual and group behaviors in real time. Data retrieved were used to analyze team coordination mechanisms, as it evolved in the real settings, and finally to test the research hypotheses.

Findings highlight that a relevant portion of glitches in routine surgery is caused by improper team coordination practices. In particular, results show that the likelihood of glitches decreases when practitioners adopt implicit coordination mechanisms rather than explicit ones. In addition, team cohesion appears to be positively related with the surgical performance.

For the first time, direct, objective and real time measurements of team behaviors have enabled an in-depth evaluation of the team coordination mechanisms in surgery and the impact on surgical glitches. From a methodological perspective, this research also represents an early attempt to investigate coordination behaviors in dynamic and complex operating environments using wearable sensor tools.

After knee replacement surgery, rehabilitation is needed to recover to normal levels of mobility. A continuous passive motion (CPM) machine is usually introduced at this stage to aid rehabilitation. However, the redundant structure and complex mechanism of the existing machine has resulted in irregular use. The purpose of this paper is to redesign the current machine.

The mechanical and electrical systems of the current machine were studied alongside interviews with stakeholders. Problems with the existing machine were identified. Related information was gathered in both the engineering and medical aspects. The redesign concept of the equipment was specified following engineering analyses to develop the final model. Finite element analysis was performed to ensure the appropriate size and dimension of the equipment. The prototype of the redesigned CPM was manufactured in-house. Product testing was conducted with 40 volunteers including experienced therapists, nurses, university students and working-age people.

Compared to the previous machine, the newly designed model was improved in both functioning and manufacturing costs. The redesigned machine is more durable and consists of a less complex structure.

The redesigned machine introduces some new features and removes unnecessary functions. As a result, the model costs less and hence, is considered beneficial to the general public. More utilization is expected which could eventually reduce the therapists’ workload at the hospital. This research provides well-defined processes of the product development starting from the users’ requirement analysis to the prototype testing stage.