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This study evaluates machine learning (ML) classifiers for diagnosing Parkinson’s disease (PD) using subcortical brain region data from 3D T1 magnetic resonance imaging (MRI) Parkinson’s Progression Markers Initiative (PPMI database). We aim to identify top-performing algorithms and assess gender-related differences in accuracy.

Multiple ML algorithms will be compared for their ability to classify PD vs healthy controls using MRI scans of the brain structures like the putamen, thalamus, brainstem, accumbens, amygdala, caudate, hippocampus and pallidum. Analysis will include gender-specific performance comparisons.

The study reveals that ML classifier performance in diagnosing PD varies across subcortical brain regions and shows gender differences. The Extra Trees classifier performed best in men (86.36% accuracy in the putamen), while Naive Bayes performed best in women (69.23%, amygdala). Regions like the accumbens, hippocampus and caudate showed moderate accuracy (65–70%) in men and poor performance in women. The results point out a significant gender-based performance gap, highlighting the need for gender-specific models to improve diagnostic precision across complex brain structures.

This study highlights the significant impact of gender on machine learning diagnosis of PD using data from subcortical brain regions. Our novel focus on these regions uncovers their diagnostic potential, improves model accuracy and emphasizes the need for gender-specific approaches in medical AI. This work could ultimately lead to earlier PD detection and more personalized treatment.

The purpose of this paper is to explore the prospect of using neurophenomenology to understand, design and test phygital consumer experiences. It aims to clarify interpretivist approaches to consumer neuroscience, wherein theoretical models of individual phenomenology can be combined with modern neuroimaging techniques to detect and interpret the first-person accounts of phygital experiences.

The argument is conceptual in nature, building its position through synthesizing insights from phenomenology, phygital marketing, theoretical neuroscience and other related fields.

Ultimately, the paper presents the argument that interpretivist neuroscience in general, and neurophenomenology specifically, provides a valuable new perspective on phygital marketing experiences. In particular, we argue that the approach to studying first-personal experiences within the phygital domain can be significantly refined by adopting this perspective.

One of the primary goals of this paper is to stimulate a novel approach to interpretivist phygital research, and in doing so, provide a foundation by which the impact of phygital interventions can be empirically tested through neuroscience, and through which future research into this topic can be developed. As such, the success of such an approach is yet untested.

Phygital marketing is distinguished by its focus on the quality of subjective first-personal consumer experiences, but few papers to date have explored how neuroscience can be used as a tool for exploring these inner landscapes. This paper addresses this lacuna by providing a novel perspective on “interpretivist neuroscience” and proposes ways that current neuroscientific models can be used as a practical methodology for addressing these questions.

Accurate diagnosis of brain tumors is crucial for effective treatment and improved patient outcomes. Magnetic resonance imaging (MRI) is a common method for detecting brain malignancies, but interpreting MRI data can be challenging and time-consuming for healthcare professionals.

An innovative method is presented that combines deep learning (DL) models with natural language processing (NLP) from ChatGPT to enhance the accuracy of brain tumor detection in MRI scans. The method generates textual descriptions of brain tumor regions, providing clinicians with valuable insights into tumor characteristics for informed decision-making and personalized treatment planning.

The evaluation of this approach demonstrates promising outcomes, achieving a notable Dice coefficient score of 0.93 for tumor segmentation, outperforming current state-of-the-art methods. Human validation of the generated descriptions confirms their precision and conciseness.

While the method showcased advancements in accuracy and understandability, ongoing research is essential for refining the model and addressing limitations in segmenting smaller or atypical tumors.

These results emphasized the potential of this innovative method in advancing neuroimaging practices and contributing to the effective detection and management of brain tumors.

Since 2011, the Extremism Risk Guidance (ERG 22+) has been the primary risk assessment framework used for terrorist and violent extremist offenders in England and Wales. The aim of this study was to conduct a rapid evidence assessment to examine the research literature on the ERG22+ factors and to identify possible significant new and emerging knowledge around potential new factors.

Searches were conducted of the Google Scholar database to identify relevant literature published between 2012 and 2020. In total, 29 documents were identified, which examined new radicalisation models and frameworks, 339 were identified, which explored to some extent one or more of the current ERG factors, and a further 138 articles were identified, which focused on potentially relevant additional issues/factors.

Most of the ERG factors were the focus of substantial research activity between 2012 and 2020. Six factors, however, received very little research attention. Potential implications of these trends are considered. Ten research themes were identified with the potential to either form new factors or which could play a significant role in the updating or revision of some existing factors.

This paper is the first rapid evidence assessment on the ERG22+ risk factors. It provides an important picture of the published scientific research of potential relevance in this area and helps to inform the review process for the ERG22+.

Internationalisation in higher education (HE) has always been romanticised and idealised but there has been limited focus on the internationalisation of gender equality and Equality, Diversity and Inclusion (EDI) certification and the role of international partnerships. Certification and Award Schemes (CAS), such as the Athena Swan Charter, can promote gender equality, best practices exchanges and foster institutional changes. Nevertheless, simply transferring strategies or frameworks without careful consideration of the nuances of the destination context can inadvertently lead to the perpetuation or exacerbation of gender inequalities and reproduce hierarchical relations between the Global South and North. Brazil's cultural and political context highlights the need for adapting the CAS framework to align with the unique conditions of the country, as well as institutional transformations in order to accommodate such a framework. This study aims to critically explore how gender equality and EDI certification can be internationalised in the Global South and how international partnerships can play a role in this process.

Building on a collaborative UK–Brazil funded project on advancing gender equality in Brazilian academia, we critically reflect on the assumptions of the funding call for operationalising international collaborations, and how we built solidarity – informed by our positionalities – against underlying colonial patterns. As part of our partnership, we were consulted to provide feedback on the introduction of an Athena SWAN framework in Brazil. We reflect on how the Athena Swan framework was “internationalised” in Brazil, especially in relation to its focus, the challenges of implementing gender equality and EDI efforts and the conditions required for such efforts to be meaningful in the Brazilian context. Thus, we assess and critically reflect on the current situation in Brazil, the role that certification can play for EDI and which conditions are required to enact change. In addition, we reflect on our positionalities and working practices as part of this collaboration as feminist researchers from different disciplinary and geographical backgrounds.

We trace colonial logics in the operationalisation of the funding scheme on setting international collaborations valorising the UK system and reinforcing geopolitical production of knowledge hierarchies between the Global North and Global South. Furthermore, reflecting on the Brazilian political, cultural context with a focus on HE we find similar challenges – to the UK – in implementing gender and EDI efforts. However, there are particular nuances in the Brazilian context that exacerbate these obstacles and make the implementation of an EDI certification framework in Brazil particularly challenging. Overcoming these barriers requires a collective effort from government, funding bodies, scientific associations and HE institutions, for the implementation of impactful and sustainable initiatives beyond mere rhetoric. Finally, while we had a positive collaboration, we felt ambivalent towards certain dimensions of the way the partnerships and the EDI internationalisation were operationalised.

We provide insights and practical recommendations that enhance the understanding of the issues surrounding the implementation of EDI efforts internationally such as CAS in the Brazilian context.

Reflecting on the internationalisation of EDI can lead to more tailored context-sensitive frameworks and activities that have the potential to influence societal attitudes and expectations towards gender roles and inclusivity, contributing to a more equitable and just society at large. It also touches upon the dynamics of international partnerships and collaborations across different contexts that can have implications for how such partnerships should be developed and funded beyond a mainstream colonial approach of “mentoring less advanced institutions”.

We reflect and critically discuss the internationalisation of EDI certification in HE and the role of international collaborations towards this process, a topic that has not been often examined within the literature on the internationalisation of HE as a romanticised and positive discourse. From our experience, we explore how such efforts can bring up ambivalence in the way they are operationalised and have the potential to both reinforce and disrupt colonial hierarchies.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

This paper aims to draw on values theory, associative network theory and schema congruity theory to examine how consumers attribute human-like values to product categories and products, and how these attributions affect product evaluations.

Study 1 randomly assigned 925 respondents to one of three product categories (cars, mobile phones and vacations). They were asked about their values and to attribute values to an assigned product category. Study 2 randomly assigned 919 respondents to one of the four value-expressive car conditions. They were asked to attribute values to the car, and then about their attitudes and purchase intentions.

Respondents attributed human-like values to product categories and products that were distinct and reflected the motivational compatibilities and conflicts inherent in the circular structure of human values. Moreover, multifaceted value congruity effects were found to positively influence attitudes and intentions to purchase a car, including congruity with product category values-schema, consumers’ personal values-schema and the structure of human values.

The authors demonstrate how a cognitive memory-based view can be used to better understand the complexities of the attribution of human-like values to products and product categories. Moving beyond the attribution of brand personality, this study shows the importance of not only understanding the attributions of values to a product but also considering how these attributions interact with the more abstract product category values to influence evaluations.

The COVID-19 pandemic has contributed to making workers more uncompromising with respect to issues such as quality of workplace relations and work-life balance. Hence, motivation and leadership style assume a key relevance for keeping the workforce engaged. We hypothesize that individuals may exhibit different preferences for motivational drivers and for leadership style, and that these two sets of preferences might be correlated with each other and with employees’ personality traits.

Here, we empirically investigate the relationship between leadership style and motivation, by also hypothesizing the possible contribution of personality traits. An online survey was developed and distributed to 150 employees or interns/trainees to collect measures related to their preference for leadership, their motivational drivers, as well as their personality traits. The data were analyzed by means of mediation and moderation analyses to disentangle the three-level relationship existing between these constructs.

Our results suggest that indeed there exists a relationship between preferences for leadership style and motivational drivers. Furthermore, one of these relationships appears to be critically mediated by specific personality traits.

This work is the first, to our knowledge, empirically testing the existence of a three-level relationship between leadership preferences, motivation and personality traits of employees and to contribute to disentangle their reciprocal influences.

There is an emerging interest in understanding the cognitive, emotional and motivational processes that drive tourists' behaviour using neuroscientific research methods. This chapter briefly reviews the main methods of interest to tourism researchers, to then focuses on electroencephalography, which reflects electrical activity from the brain. Event-related potentials or electroencephalography oscillations reflect cognitive and affective processes. Components of the former can index emotional brain responses, and alpha oscillations are related to attention and approach/withdrawal. Existing tourism literature/using electroencephalography are reviewed. This is a promising tool for studying a range of phenomena that are of interest to tourism scholars, but require careful use of methods and interpretation.

This paper aims to develop a comprehensive model on intra- and interpersonal emotion regulation (ER) in hospitality and tourism (H&T) service encounters.

A critical review and reflection of ER research from multiple disciplines was conducted. Methodologies appropriate for investigating ER were also reviewed.

A comprehensive framework was proposed to outline key influential factors, processes and consequences of intra- and interpersonal ER in service encounters in the H&T industry. Methodologies integrating advanced tools were suggested to measure complex and dynamic emotion generation and regulation processes in social interactions from a multimodal perspective.

The researchers developed a comprehensive conceptual model on both intra- and interpersonal ER based on a critical review of the most recent psychological research on ER. Various theoretical and methodological considerations are discussed, offering H&T scholars a solid starting point to explore dynamic emotion generation and regulation processes in complex social settings. Moreover, the model provides future directions for the expansion of ER theories, which have been mostly developed and tested based on laboratory research.

The proposed model addresses two critical issues identified in emotion research in the H&T field: the lack of a dynamic perspective and the neglect of the social nature of emotions. Moreover, the model provides a roadmap for future research.