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Accurately predicting population mortality rates is crucial for effective retirement insurance and economic policy formulation. Recent advancements in deep learning time series forecasting (DLTSF) have led to improved mortality rate predictions compared to traditional models like Lee-Carter (LC). This study focuses on mortality rate prediction in large clusters across Europe. By utilizing PCA dimensionality reduction and statistical clustering techniques, we integrate age features from high-dimensional mortality data of multiple countries, analyzing their similarities and differences. To capture the heterogeneous characteristics, an adaptive adjustment matrix is generated, incorporating sequential variation and spatial geographical information. Additionally, a combination of graph neural networks and a transformer network with an adaptive adjustment matrix is employed to capture the spatiotemporal features between different clusters. Extensive numerical experiments using data from the Human Mortality Database validate the superiority of the proposed GT-A model over traditional LC models and other classic neural networks in terms of prediction accuracy. Consequently, the GT-A model serves as a powerful forecasting tool for global population studies and the international life insurance field., (© 2024. The Author(s).)

The European healthcare sector faces a significant shortage of healthcare workers. Assessing the prevalence of this issue and understanding its direct and indirect determinants are essential for formulating effective recruitment programs and enhancing job retention strategies for physicians and nurses. A multicentric cross-sectional study was conducted, involving 381 physicians and 1351 nurses recruited from eight European hospitals in Belgium, the Netherlands, Italy, and Poland. The study focused on assessing turnover intentions among healthcare workers based on the Job Demands-Resources model, using an online questionnaire. Structural equation models were employed to test the data collection questionnaires' construct validity and internal consistency. The turnover intention was assessed by agreement with the intention to leave either the hospital or the profession. Among physicians, 17% expressed an intention to leave the hospital, while 9% intended to leave the profession. For nurses, the figures were 8.9% and 13.6%, respectively. The internal consistency of the questionnaires exceeded 0.90 for both categories of health workers. Depersonalization and job dissatisfaction were identified as direct determinants of turnover intention, with work engagement being particularly relevant for nurses. We found a higher intention to leave the hospital among physicians, while nurses were more prone to leave their profession. To mitigate turnover intentions, it is recommended to focus on improving job satisfaction, work engagement and fostering a positive working climate, thereby addressing depersonalisation and promoting job retention., (© 2024. The Author(s).)

The fans' importance in sports is acknowledged by the term 'the 12th man', a figurative extra player for the home team. Sport teams are indeed more successful when they play in front of their fans than when they play away. The supposed mechanism behind this phenomenon, termed Home Advantage (HA), is that fans' support spurs home players to better performance and biases referees, which in turn determines the outcome. The inference about the importance of fans' support is, however, indirect as there is normally a 12th man of this kind, even if it is an opponent's. The current pandemic, which forced sporting activities to take place behind closed doors, provides the necessary control condition. Here we employ a novel conceptual HA model on a sample of over 4000 soccer matches from 12 European leagues, some played in front of spectators and some in empty stadia, to demonstrate that fans are indeed responsible for the HA. However, the absence of fans reduces the HA by a third, as the home team's performance suffers and the officials' bias disappears. The current pandemic reveals that the figurative 12th man is no mere fan hyperbole, but is in fact the most important player in the home team., (© 2021. The Author(s).)

Faunal provincialism between the North and South parts of Eastern Asia is shown to have been in place since the late Eocene. This provincialism structured the mammalian dispersals across Eurasia for millions of years and provides insights into both palaeonvironments and palaeoclimate zonation. In addition, this study reveals the oldest record of a crown ruminant (Iberomeryx from Shinao, China). Ecologically, as well as economically, ruminant artiodactyls are one of the most important large mammal groups today. The revision of the ruminants from the Shinao Formation, from the Caijiachong marls and Xiaerhete, resulted in two new taxa and shows that the different provinces were populated by distinct taxa living in different environments, dominated by the monsoon in the South and drier conditions in the North. Evaluating this result in a Eurasian context demonstrates that the dispersals from Asia to Europe was complex. These results confirm that there were at least two dispersal events, distinct in space and time: the Grande-Coupure from Northern and Central Asia along the North ca. 34 Mya and the Bachitherium dispersal event from the Southern province along a southerly route ca. 31 Mya., (© 2021. The Author(s).)

The invasive Asian date mussel (Arcuatula senhousia) inhabits diverse global coastal environments, in some circumstances posing significant ecological and economic risks. Recently recorded in the Greater North Sea ecoregion, an established population has not previously been confirmed. Combining historical and field data, we provided baseline information from the UK and recorded colonisation in a variety of habitats. Gonadal development was assessed using the gonadosomatic index (GSI) to determine if an intertidal soft-sediment population is self-sustaining. Arcuatula senhousia records from subtidal muddy/mixed-sediment within a major estuarine system from 2007 to 2016 were also analysed. First detected in 2011, spatial distribution was variable across the years within the subtidal, with individuals found at 4-9 out of 25 sites, and densities per site varying from 10 to 290 individuals per m 2 . The intertidal population was, in part, associated with seagrass (Zostera spp.) and attached to bivalves. In marinas, individuals were attached to concrete tiles, associated with live Mytilus edulis, and to dead Ostrea edulis. Mean GSI from the intertidal population differed across months, peaking in July before declining in September/October, but with high inter-individual variability. Arcuatula senhousia is reproducing and maintaining viable populations. Using a natural capital approach, we identify the potential impacts on Europe's functionally important habitats, fisheries and aquaculture if its spread continues.

The age determination in fast-growing short-living species, such as European anchovy (Engraulis encrasicolus), has been widely recognized as a difficult task and bias introduced by readers leads to bias in reconstructing the population age structure. In this context, it is worth to note that age structure of fish population represents key information in fishery ecology and for stock assessment models. The uncertainty in estimating the age of the European anchovy by otolith reading is linked to the number of false-growth increments (checks) laid down before the annulus formation. While direct validation methods (e.g. mark-recapture, rearing, radiochemical dating) are difficult to implement specially for this short living species, the use of different indirect methods, supported by a coherent statistical approach, represents a robust and easier validation tool. A statistical modeling approach has been here adopted to assess the coherence of two well-known methods, namely Edge Analysis and Marginal Increment Analysis, in order to validate the first annulus formation in European anchovy. Both methodologies in two different yearly cycles converged toward the same result, thus confirming the annulus identification for the first year class. In addition, the completion dates of the checks and the first annulus were computed in order to gain a better insight into otolith growth dynamic. According to the species spawning period, the completion date of the first annulus falls in the summer period, while the first and second checks completion dates were mostly found in summer and winter respectively. General additive models using marginal increments as dependent variable showed a significant effect of the month, highlighting the presence of only one clear minimum in July/August, as well as specific relationships with condition factor and gonadosomatic index. Modeling the otolith edge morphology, the probability to find a hyaline band displayed in both years a similar shape, characterized by a minimum in July/August and higher values between November and January. The obtained results evidenced temporally coherent patterns providing a better insight in the otolith growth dynamic as well as a more robust validation of the first annulus formation in the European anchovy.

Until now, the genus Robsonomyia was represented by two extant species: R. reducta Matile & Vockeroth, 1980 from North America and R. sciaraeformis (Okada, 1939) from Asia. This paper presents the first fossil members of the genus Robsonomyia, which is also the first record from Europe. Two new fossil species from Baltic amber are described: R. baltica Pełczyńska, Krzemiński & Blagoderov, sp. nov. and R. henningseni Pełczyńska, Krzemiński & Blagoderov, sp. nov.. The presence of fossil Robsonomyia spp. on the European continent suggests Holarctic distribution of the genus in the past. We also discuss possible pathways of its intercontinental dispersion., (© 2024. The Author(s).)

The Health Silk Road plays a crucial role in the Belt and Road Initiative, and comprehending the health status within the participating countries is fundamental for fostering cooperation in public health. This paper collected five health indicators to represent the health status of the Belt and Road countries. Employing spatial statistics, the spatial patterns of health indicators and the associations with influencing factors were investigated. The utilized spatial statistics encompass spatial autocorrelation methods, geographical detector and spatial lag model. The results revealed obvious disparities and significant positive spatial autocorrelation of health indicators within the Belt and Road countries. Specifically, countries in Sub-Saharan Africa exhibited significant clustering of limited health indicators, while countries in Europe and Central Asia demonstrated significant clustering of robust health indicators. Furthermore, the health indicators exhibited significant spatial heterogeneity and association with the influencing factors. Universal health coverage, household air pollution, and the prevalence of undernourishment emerge as influential factors affecting health indicators. Overall, our findings highlighted complex influencing factors that contributed to the profound health inequalities across the Belt and Road countries. These factors should be duly considered in public health collaborations within the Belt and Road Initiative., (© 2024. The Author(s).)

This paper explores the nature and extent of conflict in Late Neolithic Europe based on expanded skeletal evidence for violence from the San Juan ante Portam Latinam rockshelter in present-day Spain (ca. 3380-3000 cal. BC). The systematic osteological re-examination has identified 65 unhealed and 89 healed traumas-of which 77 were previously undocumented-consistent with aggression. They affect 23.1% of the 338 individuals represented. Adolescent and adult males are particularly affected (44.9% of the 107 identified), comprising 97.6% of unhealed trauma and 81.7% of healed trauma recorded in individuals whose sex could be estimated and showing higher frequencies of injuries per individual than other demographic subgroups. Results suggest that many individuals, essentially men, were exposed to violence and eventually killed in battle and raids, since warriorship is mainly restricted to this demographic in many societies. The proportion of casualties is likely to have been far greater than indicated by the 10.1% individuals exhibiting unhealed trauma, given the presence of isolated cases of unhealed postcranial trauma and of arrowheads potentially having impacted into soft tissues. This, together with skeletal indicators of poor health and the possible socioeconomic outcomes evidenced in the region, suggest wider social impacts, which may relate to a more sophisticated and formalized way of warfare than previously appreciated in the European Neolithic record., (© 2023. Springer Nature Limited.)

Air transport has been identified as one of the primary means whereby COVID-19 spread throughout Europe during the early stages of the pandemic. In this paper we analyse two categories of methods - dynamic network markers (DNMs) and network analysis-based methods - as potential early warning signals for detecting and anticipating COVID-19 outbreaks in Europe on the basis of accuracy regarding the daily confirmed cases. The analysis was carried out from 15 February 2020, around two weeks before the first COVID-19 cases appeared in Europe, and 1 May 2020, approximately two weeks after all the air traffic in Europe had been shut down. Daily European COVID-19 information sourced from the World Health Organization was used, whereas air traffic data from Flightradar24 has been incorporated into the analyses by means of four alternative adjacency matrices. Some DNMs have been discarded since they output multiple time series, which makes it very difficult to interpret their results. The only DNM outputting a single time series does not emulate the COVID-19 trend: it does not detect all the main peaks, which means that peak heights do not match up with the increase in the number of infected people. However, many combinations of network analysis based methods and adjacency matrices output good results (with high accuracy and 20-day advance forecasts), with only minor differences from one to another. The number of edges and the network density methods are slightly better when dynamic flight frequency information is used., (© 2023. Springer Nature Limited.)

Using a unique harmonized real-time data set from the COME-HERE longitudinal survey that covers five European countries (France, Germany, Italy, Spain, and Sweden) and applying a non-parametric machine learning model, this paper identifies the main individual and macro-level predictors of self-protecting behaviors against the coronavirus disease 2019 (COVID-19) during the first wave of the pandemic. Exploiting the interpretability of a Random Forest algorithm via Shapely values, we find that a higher regional incidence of COVID-19 triggers higher levels of self-protective behavior, as does a stricter government policy response. The level of individual knowledge about the pandemic, confidence in institutions, and population density also ranks high among the factors that predict self-protecting behaviors. We also identify a steep socioeconomic gradient with lower levels of self-protecting behaviors being associated with lower income and poor housing conditions. Among socio-demographic factors, gender, marital status, age, and region of residence are the main determinants of self-protective measures., (© 2023. The Author(s).)

This paper seeks to reconstruct the management of food resources in the early Neolithic site of Cabecicos Negros in southeastern Spain. For this purpose, we have studied 29 potsherds from Cabecicos Negros (Andalusia, Spain). Applying the methods of gas chromatography and mass spectrometry we were able to recompose the daily use of the sherds related to the consumption and storage of food products. Among the results obtained in this work, we were able to show new evidence of the exploitation of dairy products in the south of the Iberian Peninsula, as well as provide information on the exploitation and management of the early domestic animals herds. To improve the archaeological results obtained, isotopic results were compared with a modern reference of 53 fat samples from the adipose tissue of domestic pigs and wild boars., (© 2023. The Author(s).)

The perennial western ragweed (Ambrosia psilostachya DC.) arrived from North America to Europe in the late nineteenth century and behaves invasive in its non-native range. Due to its efficient vegetative propagation via root suckers, A. psilostachya got naturalized in major parts of Europe forming extensive populations in Mediterranean coastal areas. The invasion history, the spreading process, the relationships among the populations as well as population structuring is not yet explored. This paper aims to give first insights into the population genetics of A. psilostachya in its non-native European range based on 60 sampled populations and 15 Simple Sequence Repeats (SSR). By AMOVA analysis we detected 10.4% of genetic variation occurring among (pre-defined) regions. These regions represent important harbors for trading goods from America to Europe that might have served as source for founder populations. Bayesian Clustering revealed that spatial distribution of genetic variation of populations is best explained by six groups, mainly corresponding to regions around important harbors. As northern populations show high degrees of clonality and lowest levels of within-population genetic diversity (mean H o  = 0.40 ± 0.09), they could preserve the initial genetic variation levels by long-lived clonal genets. In Mediterranean populations A. psilostachya expanded to millions of shoots. Some of those were obviously spread by sea current along the coast to new sites, where they initiated populations characterized by a lower genetic diversity. For the future, the invasion history in Europe might get clearer after consideration of North American source populations of western ragweed., (© 2023. The Author(s).)

Social insects are very successful invasive species, and the continued increase of global trade and transportation has exacerbated this problem. The yellow-legged hornet, Vespa velutina nigrithorax (henceforth Asian hornet), is drastically expanding its range in Western Europe. As an apex insect predator, this hornet poses a serious threat to the honey bee industry and endemic pollinators. Current suppression methods have proven too inefficient and expensive to limit its spread. Gene drives might be an effective tool to control this species, but their use has not yet been thoroughly investigated in social insects. Here, we built a model that matches the hornet's life history and modelled the effect of different gene drive scenarios on an established invasive population. To test the broader applicability and sensitivity of the model, we also incorporated the invasive European paper wasp Polistes dominula. We find that, due to the haplodiploidy of social hymenopterans, only a gene drive targeting female fertility is promising for population control. Our results show that although a gene drive can suppress a social wasp population, it can only do so under fairly stringent gene drive-specific conditions. This is due to a combination of two factors: first, the large number of surviving offspring that social wasp colonies produce make it possible that, even with very limited formation of resistance alleles, such alleles can quickly spread and rescue the population. Second, due to social wasp life history, infertile individuals do not compete with fertile ones, allowing fertile individuals to maintain a large population size even when drive alleles are widespread. Nevertheless, continued improvements in gene drive technology may make it a promising method for the control of invasive social insects in the future., (© 2023. The Author(s).)

Chronic Venous Disorders (CVD) of the lower limbs are one of the most prevalent medical conditions, affecting 35% of adults in Europe and North America. Due to the exponential growth of the aging population and the worsening of CVD with age, it is expected that the healthcare costs and the resources needed for the treatment of CVD will increase in the coming years. The early diagnosis of CVD is fundamental in treatment planning, while the monitoring of its treatment is fundamental to assess a patient's condition and quantify the evolution of CVD. However, correct diagnosis relies on a qualitative approach through visual recognition of the various venous disorders, being time-consuming and highly dependent on the physician's expertise. In this paper, we propose a novel automatic strategy for the joint segmentation and classification of CVDs. The strategy relies on a multi-task deep learning network, denominated VENet, that simultaneously solves segmentation and classification tasks, exploiting the information of both tasks to increase learning efficiency, ultimately improving their performance. The proposed method was compared against state-of-the-art strategies in a dataset of 1376 CVD images. Experiments showed that the VENet achieved a classification performance of 96.4%, 96.4%, and 97.2% for accuracy, precision, and recall, respectively, and a segmentation performance of 75.4%, 76.7.0%, 76.7% for the Dice coefficient, precision, and recall, respectively. The joint formulation increased the robustness of both tasks when compared to the conventional classification or segmentation strategies, proving its added value, mainly for the segmentation of small lesions., (© 2023. The Author(s).)

Hominin footprints were recently discovered at Matalascañas (Huelva; South of Iberian Peninsula). They were dated thanks to a previous study in deposits of the Asperillo cliff to 106 ± 19 ka, Upper Pleistocene, making Neandertals the most likely track-makers. In this paper, we report new Optically Stimulated Luminescence dating that places the hominin footprints surface in the range of 295.8 ± 17 ka (MIS 9-MIS 8 transition, Middle Pleistocene). This new age implies that the possible track-makers are individuals more likely from the Neandertal evolutionary lineage. Regardless of the taxon attributed to the Matalascañas footprints, they supplement the existing partial fossil record for the European Middle Pleistocene Hominins being notably the first palaeoanthropological evidence (hominin skeleton or footprints) from the MIS 9 and MIS 8 transition discovered in the Iberian Peninsula, a moment of climatic evolution from warm to cool. Thus, the Matalascañas footprints represent a crucial record for understanding human occupations in Europe in the Pleistocene., (© 2022. The Author(s).)

Although globalization has left its mark on economic dynamism, causing conditionalities among various aspects (market openness, production networks, technological and information developments, migratory flows, international cooperation, humanitarian support, etc.), the less pleasant side of it should not be omitted, i.e. the emergence of the framework for the faster diffusion of epidemiological diseases. Thus, with the onset of the SARS-CoV-2 virus, its widespread circulation is a serious challenge for the provision of efficient solutions to combat it, especially in countries with fragile health systems, poor institutional quality and lack of resources. In this paper we aim to investigate the implications of globalization on the COVID-19 vaccination of the population. The period under analysis is January 1, 2021-January 1, 2022, using montly data, and the object of our study are 48 European states. To capture the relationship between globalization and the vaccination rate, we applied regression models, including a number of factors that may influence the progress of vaccination. In order to test the robustness of the results, the two-stage least squares (2SLS) regressions was used. The regression models developed underlined that globalization impacts the degree of vaccination. More globalized economies are more competitive in COVID-19 management, and the significance of this effect comes from better interconnection in global markets and easier access to medical discoveries. At the same time, countries with a higher vaccination rate are associated with higher levels of development. Based on the results obtained, we proposed some policy recommendations to increase the propensity to vaccinate, ensure equity in the distribution of vaccines and provide financial support to developing countries., (© 2022. The Author(s).)

A better understanding of various patterns in the coronavirus disease 2019 (COVID-19) spread in different parts of the world is crucial to its prevention and control. Motivated by the previously developed Global Epidemic and Mobility (GLEaM) model, this paper proposes a new stochastic dynamic model to depict the evolution of COVID-19. The model allows spatial and temporal heterogeneity of transmission parameters and involves transportation between regions. Based on the proposed model, this paper also designs a two-step procedure for parameter inference, which utilizes the correlation between regions through a prior distribution that imposes graph Laplacian regularization on transmission parameters. Experiments on simulated data and real-world data in China and Europe indicate that the proposed model achieves higher accuracy in predicting the newly confirmed cases than baseline models., (© 2022. The Author(s).)

Air pollution is one of the leading causes of death globally, and continues to have a detrimental effect on our health. In light of these impacts, an extensive range of statistical modelling approaches has been devised in order to better understand air pollution statistics. However, the time-varying statistics of different types of air pollutants are far from being fully understood. The observed probability density functions (PDFs) of concentrations depend very much on the spatial location and on the pollutant substance. In this paper, we analyse a large variety of data from 3544 different European monitoring sites and show that the PDFs of nitric oxide (NO), nitrogen dioxide ([Formula: see text]) and particulate matter ([Formula: see text] and [Formula: see text]) concentrations generically exhibit heavy tails and are asymptotically well approximated by q-exponential distributions with a given width parameter [Formula: see text]. We observe that the power-law parameter q and the width parameter [Formula: see text] vary widely for the different spatial locations. For each substance, we find different patterns of parameter clouds in the [Formula: see text] plane. These depend on the type of pollutants and on the environmental characteristics (urban/suburban/rural/traffic/industrial/background). This means the effective statistical physics description of air pollution exhibits a strong degree of spatial heterogeneity., (© 2022. The Author(s).)

Precipitation in Europe shows natural fluctuations that differ considerably between seasons and geographical regions. A number of studies have linked local or seasonal rainfall variability to various long-distance air pressure differences in north-south or west-east direction. This paper presents the first continent-wide analysis of European rainfall variability on a month-by-month and country-by-country basis. We calculated Pearson r values for unsmoothed monthly rainfall data of 39 European countries over the period 1950-2019 with five potential climatic drivers, namely the North Atlantic Oscillation (NAO), the Arctic Oscillation (AO), the North Sea Caspian Pattern (NCP), and two indices of Mediterranean Oscillation (MOI2, WeMOI). For a variety of countries and months we found substantial and statistically significant r values of up to r = 0.7 and more. The dynamic temporal-spatial evolution of the Pearson correlations was mapped out across the continent, tracking the gradual or abrupt expansion, displacement and subsequent waning of the various effects over the course of the year. The correlation analysis was complemented by best subset multiple regression, controlling for intercorrelation of the potential drivers. Our results may help to improve short- to midterm rainfall prognoses in Europe and provide important calibration data for the further refinement of climate models., (© 2022. The Author(s).)