Background: Despite trends towards greater professionalisation of the nursing profession and an improved public image in certain countries, studies also show that large proportions of the public still do not fully appreciate nurses’ competencies. Mapping differences in the societal and professional recognition of nurses allows for benchmarking among countries. Aim: To investigate the level of societal recognition of the nursing profession in nine European countries, and the level of professional recognition perceived by European nurses themselves; to compare levels of recognition between countries; and to identify influencing factors. Methods: A cross-sectional study was conducted. Through an online survey, the study surveyed both the general public and nurses from various healthcare settings across nine countries between December 2022 and June 2023. The instrument used was a combination of self-developed questions on societal and professional recognition, the Work Motivation Scale and an adapted version of the Multidimensional Work Motivation Scale. Data were analysed using SPSS v.29.0, with socioeconomic prestige scores for the public and work environment/work motivation scores for nurses calculated accordingly. Results: A total of 1618 adult citizens and 2335 nurses participated. The public predominantly characterised nurses with attributes such as friendliness, warmth, empathy and compassion. The mean socioeconomic prestige score assigned to nurses was 7.2/10 (SD 1.9), with Portugal having the highest score (M 7.5/10, SD 2.0) and Norway the lowest (M 5.8/10, SD 1.4; p < 0.001). Professional recognition experienced by nurses was generally low (54% indicated rather low, 17% very low). Slovenia, the Netherlands and Belgium had slightly higher mean scores (all M 1.4/3) compared to other countries (p < 0.001). High professional recognition could be predicted for 33% by work environment score (OR = 1.21; 95% CI [1.19–1.24]), work motivation score (OR = 1.02; 95%CI[1.01–1.02]), expertise outside the hospital (OR = 1.57; 95% CI [1.25–1.97]) and work experience (OR = 1.01; 95% CI [1.00–1.02]) corrected for country. Conclusion: The study highlights the need for targeted interventions to improve the professional and public image of the nursing profession while addressing disparities in professional recognition between countries. Longitudinal studies are recommended to monitor changes in public perception and professional recognition among nurses.
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This article deals with automatic object recognition. The goal is that in a certain grey-level image, possibly containing many objects, a certain object can be recognized and localized, based upon its shape. The assumption is that this shape has no special characteristics on which a dedicated recognition algorithm can be based (e.g. if we know that the object is circular, we could use a Hough transform or if we know that it is the only object with grey level 90, we can simply use thresholding). Our starting point is an object with a random shape. The image in which the object is searched is called the Search Image. A well known technique for this is Template Matching, which is described first.
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Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology which uses strong electric fields to manipulate liquid atomization. Among many other areas, electrospray is currently used as an important tool for biomedical applications (droplet encapsulation), water technology (thermal desalination and metal recovery) and material sciences (nanofibers and nano spheres fabrication, metal recovery, selective membranes and batteries). A complete review about the particularities of this technology and its applications was recently published in a special edition of the Journal of Aerosol Sciences [1]. Even though EHDA is already applied in many different industrial processes, there are not many controlling tools commercially available which can be used to remotely operate the system as well as identify some spray characteristics, e.g. droplet size, operational mode, droplet production ratio. The AECTion project proposes the development of an innovative controlling system based on the electrospray current, signal processing & control and artificial intelligence to build a non-visual tool to control and characterize EHDA processes.
A continuation and update of the first ALT-ER project, which produced an app for early-years students that allowed them to express their feelings and tell stories related to pro-social and important developmental themes. This follow-up project will expand the software and themes, particularly in light of the COVID-19 pandemic, to reflect a wider range of experiences for young people.
