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Meta's AI attribution models enhancing customer experience in digital ads
No full textMeta's AI-driven Multi-Touch Attribution system addresses the shortcomings of conventional models like last-click by better representing intricate consumer paths across multiple platforms. Meta evaluates the actual incremental effects of ad interactions using Shapley value analysis and counterfactual modelling combined with federated learning while maintaining user privacy protections. The new methods enable higher return on ad spend (ROAS), allow for dynamic budget adjustments in real time and facilitate customization for different platforms. Even though there have been quantifiable improvements in performance results algorithmic transparency issues along with regulatory compliance and bias mitigation challenges persist. The chapter promotes ethical use of artificial intelligence and highlights the critical role humans and AI must play together when planning media strategies. The conclusion calls for established attribution frameworks that are both standardized and interpretable to maintain responsible and effective marketing within the fast-changing digital environment.<br/
An analysis of AI technology-based service encounters:repercussions for hospitality and tourism operations
No full textThis chapter focuses on AI in hospitality and tourism service encounters, where we discuss employee-customer interactions across four types of AI service: augmented, generated, mediated, and facilitated service encounters (Li et al., 2021). It then considers the preference between Japan’s fully automated, robot-staffed services and China’s AI-enhanced human encounters. In Japan, the first robot-staffed hotel, the Fedal, is used as a case example, where we review the increasing use of AI and its benefits (efficiency, speed) and drawbacks (depersonalization, machine learning to generate new products and service offerings). We also discuss the increasing use of hybrid service models that combine data-driven efficiency at reducing cost, while remaining competitive and providing a more warm, human, and attentive service. The chapter concludes by offering recommendations on the design and use of AI in service, how to redress job losses, and identify areas for future research – the impact on customer loyalty and the ethical questions faced by AI.<br/
3+1 beam laser interference lithography for preparing 3D nanostructures
No full textTargeting the demand for three-dimensional (3D) micro/nanostructure fabrication, we systematically investigate the optical field formation mechanism in non-coplanar 3+1 beams interference. It specifically elucidates the governing role of the coherent beams' incidence angle in controlling the aspect ratio of the interference patterns. Based on this theoretical framework, the 3+1 beam laser interference lithography system was constructed for studying the 3D periodic nanostructures.</p
Exploration of rapid adaptation of first contact physiotherapy services during the COVID-19 pandemic:a three-phase sequential mixed-methods study protocol
Full text linkBackground: The COVID-19 pandemic significantly disrupted primary care and emergency departments globally, including the UK and Australia respectively, affecting services within these settings, such as first contact physiotherapy services (FCPS) for patients with musculoskeletal conditions. This disruption necessitated rapid adaptation to ensure continuity of care. Before this study, comprehensive adaptations across both primary care and emergency departments FCPS had not been documented. Additionally, the specific adaptation processes, strategies used, and experiences of both staff and patients during the COVID-19 pandemic were unclear. Variations in responses between the UK and Australia also remained unknown. Documenting these rapid adaptations and experiences is crucial for future preparedness, as it provides valuable insights to guide FCPS and similar services, preventing future disruptions and promoting continuity of care. Moreover, findings will contribute significant knowledge to the existing literature. Aim: This study explores rapid adaptation of FCPS for patients with musculoskeletal conditions during the COVID-19 pandemic in the UK and Australia. Methods: This is an ongoing three-phase sequential mixed-methods study. Phase 1 utilises a cross-sectional survey of physiotherapists in FCPS role in the UK and Australia to assess changes in healthcare delivery during the pandemic, as well as levels of readiness and responsiveness, highlighting similarities and differences. Phase 2 employs a case-study approach, including semi-structured interviews and a review of documents produced to direct the management and implementation of proposed changes in FCPS, to further understand the findings from Phase 1. In phase 3, mixed-methods integration facilitates the development of context specific recommendations for the rapid adaptation of FCPS and similar contexts. These recommendations will be presented to experts for feedback and further refinement. Discussion: The mixed-methods research will provide contextually rich account of FCPS rapid adaptation, providing key learnings that could be applied to implement evidence-informed rapid adaptation in FCPS during public health emergencies.</p
Comment on “Effectiveness of Mind–Body Exercise in Older Adults With Sarcopenia and Frailty:A Systematic Review and Meta-Analysis” by Wan et al.
Full text linkHealth psychology theories and models of behaviour
Full text linkTheories, models, and their application are a crucial part of the development and growth of health psychology. This chapter contextualises health psychology in its foundations of the biopsychosocial model and discusses, non-exhaustively, key theories, models, and concepts used in the field relating to behaviour. The development of theories and models over the decades will be presented, showcasing the movement from cognitive to socio-cognitive, self-regulation to whole systems approaches, and where they are applied, to include individuals, populations, environments, behaviours, and conditions. This chapter will help to situate health psychology in the health and social care system, and critically discuss its contribution to science, education, policy, and practice
Targeting TRPC-5 channel inhibition to improve penile vascular function in erectile dysfunction
Full text linkCanonical transient receptor potential (TRPC) channels contribute to calcium homeostasis, which is involved in penile vascular contractility and erectile dysfunction (ED) pathophysiology. We evaluated the impact of TRPC5 inhibition on endothelial function in penile vascular tissue from aging rats and ED patients and its effect on the relaxant efficacy of PDE5 inhibitors. TRPC inhibitor-induced endothelial and neurogenic relaxations were evaluated in corpus cavernosum (RCC) from a rat model of aging-related ED and in human penile resistance arteries (HPRAs) and corpus cavernosum (HCC) from ED patients and organ donors (NoED). The TRPC5 inhibitor, AC1903, was more effective than TRPC3 and TRPC4 inhibitors in relaxing aged RCC and HCC and HPRA from ED patients. In addition to enhancing endothelial and neurogenic relaxations in RCC from aged animals, AC1903 improved endothelium-dependent relaxation in both HCC and HPRA from ED patients but not in tissues from NoED. Cavernosal expression of TRPC5 was not different between ED and NoED subjects. AC1903 potentiated relaxations to the PDE5 inhibitor, tadalafil, in HCC/HPRA from ED patients. TRPC5 inhibition improved penile vascular function in aged rats and patients with ED. TRPC5 inhibition could be a potential therapeutic target for ED, particularly when combined with PDE5 inhibitors to enhance treatment outcomes.</p
Navigating dementia care:a systematic review of young and young adult carers′ needs and support solutions
Full text linkObjectives: This systematic review aimed to explore the available support and identify the unique needs of young and young adult carers of individuals with dementia. Method: A systematic review following PRISMA guidelines was conducted. Electronic databases, including PubMed, Web of Science, PsycINFO, CINAHL, and Ovid, along with Google Scholar for grey literature, were searched. A narrative synthesis approach was used to analyse the findings of the included studies. The quality of the articles was assessed using the Mixed Methods Appraisal Tool (MMAT). Results: Seven studies met the predefined inclusion criteria and were included in the narrative synthesis. Findings revealed that young and young adult carers often lack knowledge of available support services and face challenges navigating the healthcare system. Caregiving responsibilities were found to hinder educational and career aspirations, leading to social isolation and strained relationships. The support received from family, friends, and teachers was often inconsistent and inadequate. A significant finding was the lack of differentiation between young and young adult carers in the existing research, despite their distinct social care support needs. Conclusion: The limited research highlights a critical gap in the literature regarding the support and needs of young and young adult carers of people with dementia. The lack of distinction between these two groups, who receive different social care support, emphasises the need for further research to better understand their unique experiences. There is an urgent need for targeted education and support programmes that address the distinct developmental needs and challenges of this population, promoting their well-being and safeguarding their personal and educational aspirations.</p
Supporting health and social care students stay and stay well: a conceptual framework for implementing integrated care into higher education
Full text linkIntegrated care demands a workforce that is confident, capable and compassionate. This is dependent on a willingness to work inter-professionally and understand the roles, standards and values of other professional groups. However, there are few examples of integrated care initiatives within higher education that aim to build the knowledge and skills required to support effective integrated, people-centred care. While satisfying, working in the helping professions is emotionally challenging and for students’ these challenges are often underestimated. Some students struggle through their studies with many failing to complete and others drop out in the early years of their careers. Understanding what supports students to thrive in their professional roles is essential to retention of a highly skilled integrated workforce. To address this challenge, this paper outlines a conceptual framework designed to promote a pedagogical environment focused on creating the conditions for integrated working. The framework is based on the “student lifecycle”, from starting to see the benefits of a career in the helping professions, developing a sense of belonging through to thriving and succeeding as future practitioners. It outlines how students are supported to develop emotional resilience, inter-professional empathy and reflexivity to help them stay and stay well in their careers
Comprehensive review on the use of machine learning techniques applied to the ultrasound data for the characterisation of porosity across carbon fibre reinforced polymer layers
Full text linkCarbon fibre reinforced polymers (CFRP) are increasingly being used in different industries, including the Automotive and aerospace sectors. One important reason for this is because they have interesting structural and mechanical properties compared to metallic materials. Their high strength-to-weight ratio makes them a preferred choice for high-stress applications. However, CFRPs are often subjected to various defects during their manufacturing that can significantly alter their structural integrity and durability. Amongst these defects, the occurrence of void formation (known as porosity) is the most common. Many methods have been developed for the characterisation of porosity including the ones based on the use of ultrasound data. The present work aims at providing a comprehensive review of the application of machine learning (ML) techniques to the mapping and characterisation of porosity across CFRP composites. The types of ML used, and their potentials for improving the accuracy of porosity detection are presented and discussed. It is particularly noted that ML techniques can extract unique features from CFRP complex ultrasound data with a relatively good level of accuracy. This result suggests that these techniques, particularly the convolutional neural network (CNN), would overcome the limitations of traditional signal processing techniques
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