Service Design to promote a systemic and dynamic perspective of well-being in dementia care

With the population aging, the number of people with dementia in Europe is projected to rise from 9.95 million in 2010 to 18.65 million in 2050 (WHO, 2017). Due to a cluster of behavioural and psychological symptoms, people with dementia often show high dependent on others, resulting in a wide range of complex care needs for performing normal activities of daily living (WHO, 2017). However, the current focus of the healthcare systems is mainly on diagnosis, yet people living with dementia require and depend on their own care partners for support in their daily lives (Burgdorf et al., 2019). Dementia not only poses a burden on those afflicted, but also directly impacts their care partners (Köhler et al., 2021). In the 20th century, there has been a shift towards promoting the well-being of both people with dementia as well as their care partners (Burley et al., 2020), which emphasizes the importance of understanding the interactions and experiences of various actors involved in dementia care, including dyadic relationships (Watson, 2019; Podgorski et al., 2021), networks (Köhler et al., 2021), and other social care factors (Cho et al., 2016). But in most of these studies, they tend to focus on individual subjective well-being (Kitwood, 1993; Dröes et al., 2017) rather than examining their interrelationships or how the dynamic experiences and interactions contribute to reach a better care condition at the collective level. Based on research gaps, my PhD research questions are: (1) How to understand well-being from a systemic perspective in dementia care and what are their interrelations in existing care models? (2) How is the systemic perspective of well-being currently approached in designing for dementia care? (3) How can service design introduce and foster a systemic perspective of well-being for dementia care? This research aims to explore how Service Design should change in order to adopt and reach toward a systemic and dynamic perspective of well-being in the context of dementia care. While acknowledging the need to focus on improving the well-being of people with dementia and their caregivers, this research will explore the influence of relational dynamics involving multiple actors on the experiences of caregiving or living with dementia. The research will draw on both empirical and theoretical knowledge to create a more holistic understanding of dementia care, well-being, and the challenges associated with it. The interdisciplinary nature of this research will involve collaboration with healthcare professionals, designers, and other stakeholders from nursing, psychology, health science, and transformative service research

Service Design for a systemic and dynamic understanding on well-being

As the world has become more interconnected and complex, there is an increasing awareness of the importance of considering well-being collectively. This paper aims to explore how service design can contribute to the shift from an individual well-being perspective to a more systemic and dynamic understanding. The authors first conducted literature reviews about three key well-being constructs: resource- challenges equilibrium (individual well-being), balanced centricity in value networks (network well-being), and actor ecosystems (community well-being). Using these constructs as lenses, the authors have then selected three service design interventions to describe service design approaches and contributions at different well-being levels. Finally, the authors suggested developing a holistic and integrated service design approach to link individuals with network and community well-being for a growing service ecosystem

A systemic perspective on designing for well-being in dementia care: learning from the case of Dementia Friendly Communities

This paper aims to analyse the potential contributions of design from a systemic perspective of well-being in dementia care and to identify areas for intervention. Specifically, the authors first provide a systemic perspective of well-being in dementia care from three levels: individual, network, and community. Then using Dementia Friendly Communities as a case study, the authors summarise three contributions areas: (1) Involving - shifting the focus from deficits and burdens to remaining capacities and contributions; (2) Connecting - enhancing service inclusivity and building care service network; and (3) Fostering - activating resources within and beyond the community. The authors then explore what we can learn from Dementia Friendly Communities about design for well-being and the potential contribution of service design in promoting well-being for people with dementia, their care partners, and the community as a whole. The paper concludes with future steps for research in service design in this area

Five-S-isotope evidence of two distinct mass-independent sulfur isotope effects and implications for the modern and Archean atmospheres.

The signature of mass-independent fractionation of quadruple sulfur stable isotopes (S-MIF) in Archean rocks, ice cores, and Martian meteorites provides a unique probe of the oxygen and sulfur cycles in the terrestrial and Martian paleoatmospheres. Its mechanistic origin, however, contains some uncertainties. Even for the modern atmosphere, the primary mechanism responsible for the S-MIF observed in nearly all tropospheric sulfates has not been identified. Here we present high-sensitivity measurements of a fifth sulfur isotope, stratospherically produced radiosulfur, along with all four stable sulfur isotopes in the same sulfate aerosols and a suite of chemical species to define sources and mechanisms on a field observational basis. The five-sulfur-isotope and multiple chemical species analysis approach provides strong evidence that S-MIF signatures in tropospheric sulfates are concomitantly affected by two distinct processes: an altitude-dependent positive 33S anomaly, likely linked to stratospheric SO2 photolysis, and a negative 36S anomaly mainly associated with combustion. Our quadruple stable sulfur isotopic measurements in varying coal samples (formed in the Carboniferous, Permian, and Triassic periods) and in SO2 emitted from combustion display normal 33S and 36S, indicating that the observed negative 36S anomalies originate from a previously unknown S-MIF mechanism during combustion (likely recombination reactions) instead of coal itself. The basic chemical physics of S-MIF in both photolytic and thermal reactions and their interplay, which were not explored together in the past, may be another ingredient for providing deeper understanding of the evolution of Earth's atmosphere and life's origin

Conditional Positional Encodings for Vision Transformers

We propose a conditional positional encoding (CPE) scheme for vision Transformers. Unlike previous fixed or learnable positional encodings, which are pre-defined and independent of input tokens, CPE is dynamically generated and conditioned on the local neighborhood of the input tokens. As a result, CPE can easily generalize to the input sequences that are longer than what the model has ever seen during training. Besides, CPE can keep the desired translation-invariance in the image classification task, resulting in improved classification accuracy. CPE can be effortlessly implemented with a simple Position Encoding Generator (PEG), and it can be seamlessly incorporated into the current Transformer framework. Built on PEG, we present Conditional Position encoding Vision Transformer (CPVT). We demonstrate that CPVT has visually similar attention maps compared to those with learned positional encodings. Benefit from the conditional positional encoding scheme, we obtain state-of-the-art results on the ImageNet classification task compared with vision Transformers to date. Our code will be made available at https://github.com/Meituan-AutoML/CPVT .Comment: A general purpose conditional position encoding for vision transformer

SegViT: Semantic Segmentation with Plain Vision Transformers

We explore the capability of plain Vision Transformers (ViTs) for semantic segmentation and propose the SegVit. Previous ViT-based segmentation networks usually learn a pixel-level representation from the output of the ViT. Differently, we make use of the fundamental component -- attention mechanism, to generate masks for semantic segmentation. Specifically, we propose the Attention-to-Mask (ATM) module, in which the similarity maps between a set of learnable class tokens and the spatial feature maps are transferred to the segmentation masks. Experiments show that our proposed SegVit using the ATM module outperforms its counterparts using the plain ViT backbone on the ADE20K dataset and achieves new state-of-the-art performance on COCO-Stuff-10K and PASCAL-Context datasets. Furthermore, to reduce the computational cost of the ViT backbone, we propose query-based down-sampling (QD) and query-based up-sampling (QU) to build a Shrunk structure. With the proposed Shrunk structure, the model can save up to $40\%$ computations while maintaining competitive performance.Comment: 9 Pages, NeurIPS 202

Magnetic field induced discontinuous spin reorientation in ErFeO3 single crystal

The spin reorientation of ErFeO3 that spontaneously occurs at low temperature has been previously determined to be a process involving the continuous rotation of Fe3þ spins. In this work, the dynamic process of spin reorientation in ErFeO3 single crystal has been investigated by AC susceptibility measurements at various frequencies and static magnetic fields. Interestingly, two completely discontinuous steps are induced by a relatively large static magnetic field due to the variation in the magnetic anisotropy during this process. It provides deeper insights into the intriguing magnetic exchange interactions which dominate the sophisticated magnetic phase transitions in the orthoferrite systems