Abstract
Luxembourg, known for its immigration history, attracts immigrants to work. This study analyses different immigrant groups in the labour market from 2014 to 2022 by using Labor Force Survey (LFS) data, Symbolic Data Analysis (SDA), and the Monitoring the Evolution of Clusters (MEC) framework.Based on the birthplace and length of residence in Luxembourg, in each year, microdata were aggregated into 21 symbolic objects. They were primarily described by 16 modal variables which are multi-valued variables with a frequency attached to each category. Moreover, clustering using complete linkage and the Chernoff's distance was applied. The Heuristic Identification of Noisy Variables (HINoV) suggested that with just six variables, objects may be grouped homogeneously. The MEC framework traced temporal relations and transitions between the clusters, revealing some movements across the different years.Results indicate that people from the European Union (EU) and Neighbouring countries have similar profiles while the Portuguese have opposite characteristics. The Luxembourgers are somewhere in between. Profiling people from non-EU countries was challenging.The data and methodology used make it easy to replicate the work in other nations, enabling comparison of results and monitoring to continue in the future.

Abstract

Abstract
The R/G approach to the development of interfering programs was initiated by the pioneering work of Cliff Jones (1981) on a relational basis. R/G has been the subject of much research since then, most of it deviating from the original relational set-up. This paper looks at such early work from a historical perspective and shows how it can be approached and extended using state-of-the-art relational algebra. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
Digital images from orbital platforms are the main source of information for mapping and decision-making. Their use has become increasingly popular over the years and has expanded into various areas. Feature extraction in digital images has been widely researched in Image Analysis, Photogrammetry, and Computer Vision. Works related to feature extraction for the generation and updating of GISs are generally divided into anthropic features such as buildings and/or highways and natural features such as vegetation areas or bodies of water. One attractive methodology for feature extraction, especially for rivers and bodies of water, is based on active contours, formulated based on the evolution of curves, which can have parametric models (Snakes) or geometric models (Level set). In this context, this work intends to identify and compare some characteristics of parametric and geometric active contour methods and apply them to orbital images from the OLI and PAN sensors of the LANDSAT 8 and CBERS 4 satellites for feature extraction, correlating these characteristics with the parameters required in the mathematical models of active contours. The present work makes use of Digital Image Processing (DIP) methods, with the first processing stage known as pre-processing, consisting of interconnected tasks that can be used to extract some information about the objects present in the scene. Subsequently, in the processing stage, the features of interest are extracted with the help of the Fiji and Icy software using Level Set and Snake, respectively. Regardless of the method used, the results presented in this work show an extraction time compatible with application needs, as they are developed semi-automatically.

Abstract
As the global community transitions towards decarbonization and sustainable energy, green hydrogen is emerging as a key clean energy carrier. This paper addresses the role of hydrogen in transportation, emphasizing the European Union's additionality principle for renewable energy sources in green hydrogen production. It introduces a model for optimally designing hydrogen fueling stations, considering electrolyzers, hydrogen storage, fuel cells, PV systems, and batteries. This model also considers the participation in electricity (energy and secondary reserve), hydrogen, and oxygen markets, and it is evaluated under different additionality policy scenarios. Results indicate that stricter additionality policies reduce the internal rate of return. However, participation in secondary reserve markets significantly boosts operational revenues and compensates for higher investment costs.

Abstract
Purpose - The purpose of this paper is to explore the challenges, interplay and potential directions for future service research to address the first three Sustainable Development Goals (SDGs) of no poverty, zero hunger and good health and well-being. Design/methodology/approach - This commentary examines how service research has addressed these SDGs in the literature, and through the development of a theory of change, the authors propose an agenda for service research going beyond serving, to enabling and transforming service systems, expanding the current focus on individual to community and population well-being through promotion and prevention.Findings - Service research has increasingly advocated human-centered approaches but requires a shift towards an all of humanity perspective. Individual and collective well-being have gained attention in service research, emphasizing the importance of considering collective well-being.Research limitations/implications - The commentary underscores the need for a comprehensive approach to develop services that contribute to the well-being of the human species. It calls for research that transcends dyadic interactions, considers systemic dynamics and broadens the focus from individual to collective and population well-being. Social implications - This paper discusses important societal issues of poverty, hunger and good health and well-being and the need for integrated and ecosystem approaches to develop equitable and sustainable solutions for collective well-being.Originality/value - While SDGs 1, 2 and 3 address individual goals, they collectively underpin the well-being of communities and societies.