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Providing public healthcare to people is a major challenge for governments. In this sector, public-funded systems are grossly inadequate in India, and excessive commercialization and exploitation by the private sector are a stark reality. The cooperative healthcare model is emerging as an alternate system in Kerala with its strong service objective to challenge the woes of private healthcare. The cooperative hospitals in the state worked round the clock to serve the poor and needy during the devastating COVID-19 pandemic. The pandemic has also badly exposed the weakness of our healthcare system in the wake of challenges posed by an increase in demand for health services, especially in rural areas. The resultant rise in the cost of treatment has put severe strains on the people at a time when even their day to day jobs were in peril. India has a strong cooperative movement and world-class institutions to serve as models in each sector. The Thrikkakara Municipal Co-operative Hospital, located at Cochin in the Kerala State of India on which this case study is written was established by the Hospital Society Ltd. in 1999, as a project under the People’s Planning Programme of the Government. Today, it has grown into a medium-sized healthcare establishment with the prime objective ‘Modern healthcare to all at affordable costs’ and cater to an average of 700 outpatients a day. This case study reveals the inception, development over years, facilities available, operations, management, public interface, and outlook for the hospital to become a modern healthcare institution to serve the people still better.

This study aims to predict the effect of cultural distance, perceived risk and electronic word of mouth (eWOM) on higher education institutes' students' destination image. In addition, it examines the mediating role of destination image in relation to students' travel intentions.

An online survey was employed to collect data from 200 graduate and postgraduate students. The partial least squares was employed to analyse the hypothesised relationships.

The results of this study found support for the positive effect of cultural distance and eWOM on destination image. Additionally, the mediating effect of destination image was also supported.

This research confirms the vital role of destination image as an antecedent of students' future intention to visit the destination. Moreover, this study contributes to marketing theory by predicting the critical drivers of higher education students' destination image and discussing their applications in the education sector.

The purpose of this study is to develop a magnetic resonance imaging (MRI)-safe iron-free electrical actuator for MR-guided surgical interventions.

The paper deals with the design of an MRI compatible electrical actuator. Three-dimensional electromagnetic and thermal analytical models have been developed to design the actuator. These models have been validated through 3D finite element (FE) computations. The analytical models have been inserted in an optimization procedure that uses genetic algorithms to find the optimal parameters of the actuator.

The analytical models are very fast and precise compared to the FE models. The computation time is 0.1 s for the electromagnetic analytical model and 3 min for the FE one. The optimized actuator does not perturb imaging sequence even if supplied with a current 10 times higher than its rated one. Indeed, the actuator’s magnetic field generated in the imaging area does not exceed 1 ppm of the B₀ field generated by the MRI scanner. The actuator can perform up to 25 biopsy cycles without any risk to the actuator or the patient since he maximum temperature rise of the actuator is about 20°C. The actuator is compact and lightweight compared to its pneumatic counterpart.

The MRI compatible actuator uses the B₀ field generated by scanner as inductor. The design procedure uses magneto-thermal coupled models that can be adapted to the design of a variety actuation systems working in MRI environment.

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

The aim of this research is to analyze the territorialization strategy developed by the Spanish brewing company Cruzcampo through its campaign #ConMuchoAcento (#With a strong accent) launched in January 2021.

The work is framed within the case study methodology. Semiotics will be the discipline used to establish the set of cultural units or signs that the company puts into play in its campaign #ConMuchoAcento.

Cruzcampo beer makes use of place branding by highlighting the Andalusian accent as a way of creating a unique positioning strategy. By doing so, the brewing company faces the issue of being associated with the negative Andalusian stereotype, sometimes regarded as if it were uneducated and low class. The use of dialectic must be seen as a step further in place branding strategy since it brings locality to the commercial message.

The social effects of the cultural units brought into play by the #ConMuchoAcento campaign remain to be analyzed, that is, the political dimension of this exercise of signifying agency of Andalusian culture. In other words, it remains to be seen how the accent represents that romantic Andalusian ideal of “authenticity” as that form of subjectivity at the margins of the cultural and rational organization of modern global capitalism.

This study is one of the first to be conducted on the multi-award-winning #ConMuchoAcento campaign. Furthermore, it will analyze the place branding strategy carried out by the brand from a semiotic perspective.

Administrative processes play a crucial role in various sectors, often contributing to cost overruns and delays. While lean concept has been extensively applied in many industries, there is a recognized need for further research on the integration of lean in administrative processes. To address this research gap, this study aims to systematically analyse the implementation of lean in administrative processes, providing a sector-wise comparison to explore its prospects for the construction industry.

A systematic literature review was conducted by adapting the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. Eighty-six research papers are subjected to descriptive and content analysis on different tools applied in lean integrated administrative processes in health care, education, public administration and other sectors.

The research study reveals common lean tools irrespective of sector. Moreover, specific tools used for a particular sector are analysed. Out of the various lean tools and techniques, value stream mapping, 5S and Kaizen are highly acknowledged tools in every sector of lean intervention. Furthermore, ECRS is applied explicitly in the education sector. Furthermore, it is noted that Suppliers, Inputs, Process, Outputs and Customers (SIPOC), 5whys, load levelling and control charts are identical to administrative processes in lean health care. Furthermore, Spaghetti charts and Kaikaku are only adapted to administrative processes in the public administration sector, and causal loop diagrams are used explicitly in administrative processes in the construction sector.

This study contributes to research by developing a guideline to design lean intervention for a lean-integrated administrative process in any sector which still needs to be transformed into lean. Hence, this study will be a cornerstone for incorporating lean principles for administrative processes in construction sector.

Diagnosing brain tumors is a process that demands a significant amount of time and is heavily dependent on the proficiency and accumulated knowledge of radiologists. Over the traditional methods, deep learning approaches have gained popularity in automating the diagnosis of brain tumors, offering the potential for more accurate and efficient results. Notably, attention-based models have emerged as an advanced, dynamically refining and amplifying model feature to further elevate diagnostic capabilities. However, the specific impact of using channel, spatial or combined attention methods of the convolutional block attention module (CBAM) for brain tumor classification has not been fully investigated.

To selectively emphasize relevant features while suppressing noise, ResNet50 coupled with the CBAM (ResNet50-CBAM) was used for the classification of brain tumors in this research.

The ResNet50-CBAM outperformed existing deep learning classification methods like convolutional neural network (CNN), ResNet-CBAM achieved a superior performance of 99.43%, 99.01%, 98.7% and 99.25% in accuracy, recall, precision and AUC, respectively, when compared to the existing classification methods using the same dataset.

Since ResNet-CBAM fusion can capture the spatial context while enhancing feature representation, it can be integrated into the brain classification software platforms for physicians toward enhanced clinical decision-making and improved brain tumor classification.

This research has not been published anywhere else.

This research is located at the intersection of communication, memetics, and the study of the imaginary. As a presupposition, we put forward the existence of a communicational imaginary, in which the contemporary person functions through their competencies in social networks, by meeting the demands of the public and the private, managing the obsessiveness of the sharing of intimacy and the exorbitant number of images. Considering memes as a significant aspect of this communicational imaginary, we seek to understand the dynamics and path of memes in the midst of this plethora of images. From the concept of iconophagy, we deal with the exacerbated multiplication of the images and the path of memes starting from a marginalized environment until it is integrated into social roles and a rational level of thought. Thus, it is the general objective of this research to understand the dynamics and the path of memes amidst the plethora of images in the context of communicational imagery and to investigate the multiplication of memes as representative of the myriad images in contemporary imagery.