In our society, sustainability has emerged as a major concept in our daily lives and activities, e.g. from reducing the environmental impact of our foods to corporate social responsibility in doing business, and social impact of our activities. The original idea of sustainability was to address human development within social, ecological, and economic boundaries. Nowadays, however, sustainability is more and more extended to other areas of our lives, including aspects of a good life and well-being. The aim here was to compare sustainability, a good life, and well-being and determine their overlap, differentiations, and indefinite or undecided overlap when considering the original definitions. Following from the definition of sustainability, a good life, and well-being, I analyze the overlap, differentiations, and indefinite overlap of these concepts. With this comparison, I show that sustainability is clearly adapting to include more aspects of a good life and well-being (approximately 26% overlap), but is limited to do so from its original definition. I conclude that overlap between concepts exists and by being relatively different they are fundamentally supportive to one another and need to be applied accordingly to further support sustainable development.
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Given the growing number of older people, society as a whole should ideally provide a higher quality of life (QoL) for its ageing citizens through the concept of personalised ageing. Information and communication technologies (ICT) are subject to constant and rapid development, and can contribute to the goal of an improved QoL for older adults. In order to utilise future ICT solutions as a part of an age-friendly smart environment that helps achieve personalised ageing with an increased QoL, one must first determine whether the existing ICT solutions are satisfying the needs of older people. In order to accomplish that, this study contributes in three ways. First, it proposes a framework for the QoL of older adults, in order to provide a systematic review of the state-of-the-art literature and patents in this field. The second contribution is the finding that selected ICT solutions covered by articles and patents are intended for older adults and are validated by them. The third contribution of the study are the six recommendations that are derived from the review of the literature and the patents which would help move the agenda concerning the QoL of older people and personalised ageing with the use of ICT solutions forward. Original article at MDPI; DOI: http://dx.doi.org/10.3390/ijerph17082940 (This article belongs to the Special Issue Feature Papers "Age-Friendly Cities & Communities: State of the Art and Future Perspectives")
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Intergenerational continuity in family behaviors partly results from socialization processes in the parental home. However, socialization is a multidimensional process. This article tests hypotheses about the relative importance of value transmission and modeling in explaining expectations of adolescence concerning the timing of leaving home, and entry into cohabitation, marriage, and parenthood. Structural equation modeling on multiactor data from over 1,000 parent–adolescent child couples in the Netherlands is used to test hypotheses. Results suggest that, in general, both value transmission and modeling are important predictors of adolescents’ expectations concerning the timing of major family events. Moreover, no differences between mothers and fathers and between boys and girls are observed in the strength of the intergenerational relationships studied.
Multiple sclerosis (MS) is a severe inflammatory condition of the central nervous system (CNS) affecting about 2.5 million people globally. It is more common in females, usually diagnosed in their 30s and 40s, and can shorten life expectancy by 5 to 10 years. While MS is rarely fatal; its effects on a person's life can be profound, which signifies comprehensive management and support. Most studies regarding MS focus on how lymphocytes and other immune cells are involved in the disease. However, little attention has been given to red blood cells (erythrocytes), which might also be important in developing MS. Artificial intelligence (AI) has shown significant potential in medical imaging for analyzing blood cells, enabling accurate and efficient diagnosis of various conditions through automated image analysis. The project aims to implement an AI pipeline based on Deep Learning (DL) algorithms (e.g., Transfer Learning approach) to classify MS and Healthy Blood cells.
The postdoc candidate, Sondos Saad, will strengthen connections between research groups Asset Management(AM), Data Science(DS) and Civil Engineering bachelor programme(CE) of HZ. The proposed research aims at deepening the knowledge about the complex multidisciplinary performance deterioration prediction of turbomachinery to optimize cleaning costs, decrease failure risk and promote the efficient use of water &energy resources. It targets the key challenges faced by industries, oil &gas refineries, utility companies in the adoption of circular maintenance. The study of AM is already part of CE curriculum, but the ambition of this postdoc is that also AM principles are applied and visible. Therefore, from the first year of the programme, the postdoc will develop an AM material science line and will facilitate applied research experiences for students, in collaboration with engineering companies, operation &maintenance contractors and governmental bodies. Consequently, a new generation of efficient sustainability sensitive civil engineers could be trained, as the labour market requires. The subject is broad and relevant for the future of our built environment being more sustainable with less CO2 footprint, with possible connections with other fields of study, such as Engineering, Economics &Chemistry. The project is also strongly contributing to the goals of the National Science Agenda(NWA), in themes of “Circulaire economie en grondstoffenefficiëntie”,”Meten en detecteren: altijd, alles en overall” &”Smart Industry”. The final products will be a framework for data-driven AM to determine and quantify key parameters of degradation in performance for predictive AM strategies, for the application as a diagnostic decision-support toolbox for optimizing cleaning &maintenance; a portfolio of applications &examples; and a new continuous learning line about AM within CE curriculum. The postdoc will be mentored and supervised by the Lector of AM research group and by the study programme coordinator(SPC). The personnel policy and job function series of HZ facilitates the development opportunity.