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Although leisure constraints that individuals have to cope with can negatively affect their social inclusion and satisfaction with life, little research has addressed the link between these variables. Therefore, the current paper examined the moderator role of leisure constraints on the relationship between satisfaction with life and leisure constraints among adults living in five different European countries. The respondents were 1,382 women and 877 men adults. The findings of analysis revealed that all factors used in the study accounted for 15% of the variance in satisfaction with life and social inclusion had a significant and positive impact on satisfaction with life. As a result, it can be said that leisure constraints had a moderating effect on the relationship between satisfaction with life and social inclusion. The present research study recommends that social inclusion should be encouraged through decreasing to leisure constraints to increase the life satisfaction. [ABSTRACT FROM AUTHOR]

Purpose: This paper constitutes the first academic study to be made of Google Discover as applied to online journalism. Design/methodology/approach: This paper constitutes the first academic study to be made of Google Discover as applied to online journalism. The study involved conducting 61 semi-structured interviews with experts that are representative of a range of different professional profiles within the fields of journalism and search engine positioning (SEO) in Brazil, Spain and Greece. Based on the data collected, the authors created five semantic categories and compared the experts' perceptions in order to detect common response patterns. Findings: This study results confirm the existence of different degrees of convergence and divergence in the opinions expressed in these three countries regarding the main dimensions of Google Discover, including specific strategies using the feed, its impact on web traffic, its impact on both quality and sensationalist content and on the degree of responsibility shown by the digital media in its use. The authors are also able to propose a set of best practices that journalists and digital media in-house web visibility teams should take into account to increase their probability of appearing in Google Discover. To this end, the authors consider strategies in the following areas of application: topics, different aspects of publication, elements of user experience, strategic analysis and diffusion and marketing. Originality/value: Although research exists on the application of SEO to different areas, there have not, to date, been any studies examining Google Discover. Peer review: The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2022-0574 [ABSTRACT FROM AUTHOR]

The paper aimed to analyze the dynamics of livestock and milk and meat production in the top five EU countries growing sheep and goats: Spain, Romania, Greece, France and Italy. The empirical data from Eurostat and Faostat for the period 2012-2021 were processed using usual methods and procedures like fixed basis and structural indices, trend regression equation, determination coefficient and points method. The comparison between these five countries pointed out the decline of sheep number in four countries, except Romania and the decrease in goats number in Greece and Spain, but an increase in Romania, France and Italy. Ewe milk production increased in three countries, except Spain where it remained relatively constant and Romania where it declined. Goat milk production raised in three countries, except Greece and Romania. Sheep meat output increased in France and Spain, but in the other countries went down, while goat meat output increased only in Spain, the other four states recording a decline. In the year 2021, these five countries all together counted 46.1 million sheep, representing 76.% of the EU sheep livestock, and also they had 9.4 million goats, meaning 82.1% of the EU goats livestock. In 2020, all these countries produced 2.73 million tonnes sheep milk and 1.87 million tonnes goat milk, accounting for 1.7% and respectively 1.16% in the EU milk output. These counties also contributed by 85% to the EU sheep and goat meat production. This reflects the importance of small ruminants in the EU animal livestock and production. These species have to help the EU for greening agriculture, as they could valorize natural resources from the mountains and less favored areas and also could be grown in organic farming system, assuring jobs and income to the local population, food security and at the same time contributing to the biodiversity preservation and production of renewable energy. [ABSTRACT FROM AUTHOR]

Multi-Media applications are amongst the most demanding services, requiring high amounts of network capacity and computational resources for synchronous audio-visual streaming with high quality. Gaming streaming is one of the most demanding of these media applications. Recent technological advances in the 5G domain, precisely Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC), unlock media industries’ potential by offering high-quality media services through dynamic and efficient resource allocation with low latency. This work presents a multi-site gaming streaming use case implemented over an end-to-end 5G-enabled platform provided by the EU H2020 5G-PPP 5G EVE project. Furthermore, we present the executed use case experiment scenarios to validate the use case performance following a set of defined Quality of Experience(QoE)-related Key Performance Indicators (KPIs). In particular, this paper discusses the design workflow and orchestration of the multi-site gaming streaming use case across two 5G EVE sites (i.e., Spain and Greece), providing a detailed description of the network function applications and resources utilized for the use case. Subsequently, leveraging the 5G EVE monitoring platform, this paper elaborates on the executed experiment scenarios that provide the defined KPI metrics data. Finally, this paper presents, discusses, and analyzes the obtained KPI metrics data results and provides recommendations on future works for these kinds of use cases. [ABSTRACT FROM AUTHOR]

This paper aims to describe and discuss the significance of the social policy measures implemented in Southern European countries—Greece, Italy, Portugal and Spain—in response to the first wave of COVID‐19. Our analysis covers interventions from 1 March to June 30, 2020. Despite significant differences in how the COVID‐19 pandemic spread—with Italy and Spain experiencing much higher rates of infection and lethality—Southern European economies are among the most hard‐hit—and are likely to find themselves in the eye of the storm, once more. The paper shows that despite differences in how countries have countered the spread of COVID‐19, there are important commonalities in the actions governments took to counteract the economic impact of the pandemic. Foremost efforts were directed at wage subsidy schemes to contain mass job destruction, additional temporary benefits to compensate self‐employed and other non‐standard workers for the loss of earnings; the expansion of unemployment insurance; and finally, the introduction and/or strengthening of schemes to provide support to families with care responsibilities. The scale of the social policy and employment protection response has nevertheless been constrained by the fiscal position of each individual country in the post‐Euro crisis context. We argue that, in the long run, the response capacity of these governments and the social and economic consequences of this crisis will need to be contextualised against the backdrop of the deep and prolonged impact of austerity‐driven measures on public budgets, production and welfare regimes over the last decade. [ABSTRACT FROM AUTHOR]

SUMMARY: Advances in olive oil research have blossomed in recent years, and articles on olive oil have been widely recorded. However, a comprehensive and systematic bibliometric analysis of olive oil research has not been completed. Through a systematic literature search, we consolidated 7003 papers from the Web of Science Core Collection database. This bibliometric analysis was carried out to examine the article growth, geographical distribution, and analysis of journals/research areas/authors/keywords. The results revealed the following: (1) Exponential growth was shown in the annual number of publications (R2 = 0.9791). The geographical distribution is biased to a few countries, especially Spain, Italy, and Greece in the Mediterranean region, placing a larger focus on olive oil research. (2) Quality analysis‐related research acted as a link between keyword groups, the disease prevention and treatment‐related research of olive oil received decreasing interest, while authentication and quality analysis‐related research of olive oil showed the opposite trend, by‐products‐related research of olive oil got waving interests over the whole period. (3) Improvement is needed in the degree of olive oil with international collaboration. This is the first time that hotspots and trends in olive oil research have been shown. [ABSTRACT FROM AUTHOR]

The paper analyzed the trends and relationships in the EU ewes and goats livestock and milk output in the period 2010-2018 based on Eurostat Data using the fixed basis index, descriptive statistics, average yearly growth rate, Bravais- Pearson correlation coefficients, determination coefficient and regression models. The results attested the important contribution given by the two species to the EU milk sector in order to diversify cheese varieties and stimulate consumption and export. While sheep livestock declined in general, and the goats population increased, ewes and goats' milk delivered to dairy industry increased. In the decreasing order, the main EU countries raising sheep are Spain, Romania, Greece, Italy and France, and the main countries growing goats are Greece, Spain, Romania, France, Italy and Netherlands. Raw milk production increased in case of the both species in many countries. Ewe milk is mainly produced in Greece, Spain, Italy and France, while goat milk is especially produced in France, Spain, Netherlands and Greece. The diverse policies, management and marketing and production performance from a country to another pointed out the need to improve farmers skills in resources, livestock and production management, to encourage them to join in associations to benefit of low-price inputs and a direct access to market. The coupled aids financed by the EU are incentives to sustain sheep and goat farming and dairy sector, farmers' income, the valorization of the natural resources, the development of the disadvantaged rural and peri-urban areas, animal health and welfare, environment quality and biodiversity, and the offer of organic dairy products to consumers. [ABSTRACT FROM AUTHOR]

Background: The clinical and economic burden of type 2 diabetes mellitus on society is rising. Effective and efficient preventive measures may stop the increasing prevalence, given that type 2 diabetes mellitus is mainly a lifestyle-driven disease. The Feel4Diabetes-study aimed to tackle unhealthy lifestyle (unhealthy diet, lack of physical activity, sedentary behaviour, and excess weight) of families with a child in the first grades of elementary school. These schools were located in regions with a relatively low socio-economic status in Belgium, Bulgaria, Finland, Greece, Hungary and Spain. Special attention was paid to families with a high risk of developing type 2 diabetes mellitus. Methods: The aim of this paper is to describe the detailed methodology of the intervention's cost-effectiveness analysis. Based on the health economic evaluation of the Toybox-study, both a decision analytic part and a Markov model have been designed to assess the long-term (time horizon of 70 year with one-year cycles) intervention's value for money. Data sources used for the calculation of health state incidences, transition probabilities between health states, health state costs, and health state utilities are listed. Intervention-related costs were collected by questionnaires and diaries, and attributed to either all families or high risk families only. Conclusions: The optimal use of limited resources is pivotal. The future results of the health economic evaluation of the Feel4Diabetes-study will contribute to the efficient use of those resources. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

The Soil and Water Assessment Tool (SWAT) is a well-established eco-hydrological model that has been extensively applied to watersheds across the globe. This work reviews over two decades (2002–2022) of SWAT studies conducted on Mediterranean watersheds. A total of 260 articles have been identified since the earliest documented use of the model in a Mediterranean catchment back in 2002; of which 62% were carried out in Greece, Italy, or Spain. SWAT applications increased significantly in recent years since 86% of the reviewed papers were published in the past decade. A major objective for most of the reviewed works was to check the applicability of SWAT to specific watersheds. A great number of publications included procedures of calibration and validation and reported performance results. SWAT applications in the Mediterranean region mainly cover water resources quantity and quality assessment and hydrologic and environmental impacts evaluation of land use and climate changes. Nevertheless, a tendency towards a multi-purpose use of SWAT is revealed. The numerous examples of SWAT combined with other tools and techniques outline the model's flexibility. Several studies performed constructive comparisons between Mediterranean watersheds' responses or compared SWAT to other models or methods. The effects of inputs on SWAT outputs and innovative model modifications and improvements were also the focus of some of the surveyed articles. However, a significant number of studies reported difficulties regarding data availability, as these are either scarce, have poor resolution or are not freely available. Therefore, it is highly recommended to identify and develop accurate model inputs and testing data to optimize the SWAT performance. [Display omitted] • SWAT review on Mediterranean hydro-climatic studies. • Lack of SWAT assessment on Mediterranean catchments. • A comparison of data from different Mediterranean basins. • Enhancing data availability for SWAT applications. • Developing a comprehensive knowledge of Mediterranean watersheds. [ABSTRACT FROM AUTHOR]

The marginal role of social assistance and the absence of minimum income programmes have long been thought to constitute defining characteristics of the southern European model of welfare. Nevertheless, over the 1990s significant innovations in this field have taken place. The paper aims to contribute to the analysis of recent developments by critically examining the experience of anti-poverty policies in Greece, Italy, Portugal and Spain. It is argued that the “patchiness” of safety nets in southern Europe is due to a unique set of constraints, the most relevant of which are the role of families and the “softness” of state institutions. A review of national profiles reveals that new policies introduced in all four countries mark progress towards redressing some of the historical imbalances of that welfare model. In particular, fully fledged minimum income schemes now operate in Portugal and in certain Spanish regions, while an experiment involving a number of Italian municipalities is still in progress. In spite of this, the paper concludes that social safety nets in southern Europe remain frail in terms of institutional design as well as political support and legitimacy. [ABSTRACT FROM AUTHOR]

This paper focuses on the high rates of female full-time employment in Portugal and examines whether these are consistent with the familialistic features that typify the southern European social model. It employs a comparative methodology to investigate the extent to which recent policy developments and current social values in Portugal are aligned with the familialistic southern European tradition or whether they signal a departure from the model. The analysis reveals that the high rates of female employment are associated with particular features of the case of Portugal, namely, lower gender-based labour market segmentation and welfare state support for dual-earner families. However, this study also shows that the country still retains familialistic characteristics, which are particularly visible in the organization of care and in the persistence of traditional gender values. The article contributes to debates on the southern European social model and sheds light on how high female employment levels can be compatible with relatively high levels of familialism. [ABSTRACT FROM PUBLISHER]

This paper examines the global and structural forces facilitating the movement of female migrant domestic workers (FMDWs) from developing regions to southern Europe and the Levant. At the intersection of welfare state, childcare, gender and migration regimes, we can identify a cross-Mediterranean domestic worker model. It has important implications for the magnitude, composition (in terms of national background and live-in vs. live-out work), legal status and mobilization of the region's FMDWs. Their roles in global migration flows and national labour markets, as explained in the existing literature, are examined, followed by case comparison of Spain, Greece, Cyprus, Israel, Lebanon and Jordan. [ABSTRACT FROM PUBLISHER]

This paper focuses on analysis of public opinion towards European integration in Greece, Portugal and Spain, countries known for their positive attitudes toward integration. In particular, the article analyses how public attitudes towards Europe have been formed in these countries. Secondly, it examines the determining factors of citizens' positive attitudes toward integration and shows the types of variables that are essential to understanding the differences between Greeks, Spaniards and the Portuguese. It also examines traditional euro-optimism in these southern countries. The findings show the relevance of identity and the various impacts of party platforms and ideology in attitudes of support for European integration. [ABSTRACT FROM AUTHOR]

This paper focuses on the role of business networks, and especially on the ways in which formal and informal interactions among economic agents shape the tourist product. Local businesses are considered as agents who realize and/or create economic opportunities and develop new goals and strategies. Businesses are not viewed as independent entities, but as actors whose actions are embedded in structures of ongoing relations. As such, similar resources and activities based in rural tourism destinations do not necessarily have the same consequences at different times and places. Business networking is a crucial factor in organizing activities and resources at the local level, leading to spatially different levels of integration. Such differences are focused on here, using illustrative examples and findings from the case-study regions in the UK, Spain and Greece. [ABSTRACT FROM AUTHOR]

The aim of the paper lies in the identification of possible significant linear trends at monthly, seasonal and annual timescales in the Mediterranean during the second half of the 20th century. Monthly and daily records of 63 stations have been used to elaborate several precipitation indices: sum of daily precipitation (SDP) for rainfall >0.1 mm, >10 mm and >95th percentile, of number of rainy days (RD) >0.1 mm and >10 mm and of mean daily precipitation (MDP) >0.1 mm and >10 mm. For each index the stations have been gathered together by Rotated Principal Component Analyses to determine 8 sub-areas which can be considered as identical for all the timescales at the spatial scale of the research. Trends have been estimated from the scores of each eigenvector retained in all RPCAs. They are mainly non existant or non significant decreasing, even if a few monthly trends appear to be significantly diminishing, primarily during winter months, March in the Atlantic region, October in the Mediterranean Spain, December in the Lions and Genoa Gulfs, January, winter and the year in Greece, winter and the year in Italy and winter in the Near East and increasing in April in the two gulfs. Correlation coefficients between SDP>0.1 mm and other indices have been computed: the significant trends seem mainly related to RD>10 mm, which represents a high percentage of the total rainfall amount. Greece is remarkable: SDP>0.1 mm and >10 mm decrease significantly during January, winter, the rainy season and the entire year whereas SDP>95th percentile increases significantly, in accordance with the climatic change scenarios for the end of this century as does the decreasing of the total monthly and seasonal rainfall. [ABSTRACT FROM AUTHOR]

Market orientation is the evolutionary focus of EU food policy initiatives. In the context of this study, an example of this ethos is the legislative support framework for territorial food products. Whilst quantitative studies exist which examine the perceptual determinants of such products, exploratory research exposing the importance of symbolic connotations is largely the preserve of the qualitative literature. This paper seeks to generalise these tentative qualitative findings, whilst extending the dearth of quantitative literature by focusing in more detail on segment profiles, employing both an improved multivariate treatment and ‘pooled data’ from two Mediterranean countries to examine the significance of ‘citizenship’ on product perception. [ABSTRACT FROM AUTHOR]

Estimating demand functions for developing countries before and after the end of the Cold War, Dunne and Perlo-Freeman (2003) found little evidence of any change in the underlying relationship. One concern with their analysis was that the use of cross-section averages might have obscured important time series effects. This paper deals with this issue by analysing their data using static and dynamic panel data methods. This produces evidence of a change in relationship and suggests that the focus in the literature on cross-section analyses has indeed limited our understanding of important dynamic processes at work within countries. [ABSTRACT FROM AUTHOR]