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The aim of this paper is to prepare, describe and discuss the models of the current and future distribution of Phthiracarus longulus (Koch, 1841) (Acari: Oribatida: Euptyctima), the oribatid mite species widely distributed within the Palearctic. We used the maximum entropy (MAXENT) method to predict its current and future (until the year 2100) distribution based on macroclimatic bio-variables. To our best knowledge, this is the first-ever prediction of distribution in mite species using environmental niche modelling. The main thermal variables that shape the current distribution of P. longulus are the temperature annual range, mean temperature of the coldest quarter and the annual mean temperature, while for precipitation variables the most important is precipitation of the driest quarter. Regardless of the climatic change scenario (SSP1-2.6, SSP2-4.5, SSP5-8.5) our models show generally the northward shift of species range, and in Southern Europe the loss of most habitats with parallel upslope shift. According to our current model, the most of suitable habitats for P. longulus are located in the European part of Palearctic. In general, the species range is mostly affected in Europe. The most stable areas of P. longulus distribution were the Jutland with surrounding southern coasts of Scandinavia, islands of the Danish Straits and the region of Trondheim Fjord., (© 2024. The Author(s).)

Predicting epidemic evolution is essential for making informed decisions and guiding the implementation of necessary countermeasures. Computational models are vital tools that provide insights into illness progression and enable early detection, proactive intervention, and targeted preventive measures. This paper introduces Sybil, a framework that integrates machine learning and variant-aware compartmental models, leveraging a fusion of data-centric and analytic methodologies. To validate and evaluate Sybil's forecasts, we employed COVID-19 data from several European and U.S. states. The dataset included the number of new and recovered cases, fatalities, and variant presence over time. We evaluate the forecasting precision of Sybil in periods in which there is a change in the trend of the pandemic evolution or a new variant appears. Results demonstrate that Sybil outperforms conventional data-centric approaches, being able to forecast accurately the changes in the trend, the magnitude of these changes, and the future prevalence of new variants., (© 2024. The Author(s).)

The process of implementation of the UN Sustainable Development Goals (SDGs) which were approved by the UN General Assembly in 2015 has not been simple, being influenced by variety of social, economic, and logistical problems. It has also been negatively affected by the COVID-19 pandemic. There are to date no specific studies aimed at assessing the extent to which higher universities institutions in Europe are active in the SDGs implementation process. Departing from this research need, this paper reports on a study aimed at examining the current degree of engagement of European universities in the implementing the SDGs. By using a multi-methods approach, which entails a review of existing documents, a survey involving participants from 22 countries and case studies, the paper maps, documents and disseminates examples of what European universities are doing to implement the SDGs, the challenges they face, and the solutions being deployed to overcome them., (© 2024. The Author(s).)

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.)

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).)

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).)

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).)

Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO 2 , O 3 , PM 2.5 , and PM 10 levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO 2 compared to PM 2.5 and PM 10 concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe., (© 2022. The Author(s).)

Comparison of COVID-19 trends in space and over time is essential to monitor the pandemic and to indirectly evaluate non-pharmacological policies aimed at reducing the burden of disease. Given the specific age- and sex- distribution of COVID-19 mortality, the underlying sex- and age-distribution of populations need to be accounted for. The aim of this paper is to present a method for monitoring trends of COVID-19 using adjusted mortality trend ratios (AMTRs). Age- and sex-mortality distribution of a reference European population (N = 14,086) was used to calculate age- and sex-specific mortality rates. These were applied to each country to calculate the expected deaths. Adjusted Mortality Trend Ratios (AMTRs) with 95% confidence intervals (C.I.) were calculated for selected European countries on a daily basis from 17th March 2020 to 29th April 2021 by dividing observed cumulative mortality, by expected mortality, times the crude mortality of the reference population. These estimated the sex- and age-adjusted mortality for COVID-19 per million population in each country. United Kingdom experienced the highest number of COVID-19 related death in Europe. Crude mortality rates were highest Hungary, Czech Republic, and Luxembourg. Accounting for the age-and sex-distribution of the underlying populations with AMTRs for each European country, four different patterns were identified: countries which experienced a two-wave pandemic, countries with almost undetectable first wave, but with either a fast or a slow increase of mortality during the second wave; countries with consistently low rates throughout the period. AMTRs were highest in Eastern European countries (Hungary, Czech Republic, Slovakia, and Poland). Our methods allow a fair comparison of mortality in space and over time. These might be of use to indirectly estimating the efficacy of non-pharmacological health policies. The authors urge the World Health Organisation, given the absence of age and sex-specific mortality data for direct standardisation, to adopt this method to estimate the comparative mortality from COVID-19 pandemic worldwide., (© 2021. The Author(s).)

Mobility restrictions have been identified as key non-pharmaceutical interventions to limit the spread of the SARS-COV-2 epidemics. However, these interventions present significant drawbacks to the social fabric and negative outcomes for the real economy. In this paper we propose a real-time monitoring framework for tracking the economic consequences of various forms of mobility reductions involving European countries. We adopt a granular representation of mobility patterns during both the first and second waves of SARS-COV-2 in Italy, Germany, France and Spain to provide an analytical characterization of the rate of losses of industrial production by means of a nowcasting methodology. Our approach exploits the information encoded in massive datasets of human mobility provided by Facebook and Google, which are published at higher frequencies than the target economic variables, in order to obtain an early estimate before the official data becomes available. Our results show, in first place, the ability of mobility-related policies to induce a contraction of mobility patterns across jurisdictions. Besides this contraction, we observe a substitution effect which increases mobility within jurisdictions. Secondly, we show how industrial production strictly follows the dynamics of population commuting patterns and of human mobility trends, which thus provide information on the day-by-day variations in countries' economic activities. Our work, besides shedding light on how policy interventions targeted to induce a mobility contraction impact the real economy, constitutes a practical toolbox for helping governments to design appropriate and balanced policy actions aimed at containing the SARS-COV-2 spread, while mitigating the detrimental effect on the economy. Our study reveals how complex mobility patterns can have unequal consequences to economic losses across countries and call for a more tailored implementation of restrictions to balance the containment of contagion with the need to sustain economic activities.

Traditional morphological diagnoses of taxonomic status remain widely used while an increasing number of studies show that one morphospecies might hide cryptic diversity, i.e. lineages with unexpectedly high molecular divergence. This hidden diversity can reach even tens of lineages, i.e. hyper cryptic diversity. Even well-studied model-organisms may exhibit overlooked cryptic diversity. Such is the case of the freshwater crustacean amphipod model taxon Gammarus fossarum. It is extensively used in both applied and basic types of research, including biodiversity assessments, ecotoxicology and evolutionary ecology. Based on COI barcodes of 4926 individuals from 498 sampling sites in 19 European countries, the present paper shows (1) hyper cryptic diversity, ranging from 84 to 152 Molecular Operational Taxonomic Units, (2) ancient diversification starting already 26 Mya in the Oligocene, and (3) high level of lineage syntopy. Even if hyper cryptic diversity was already documented in G. fossarum, the present study increases its extent fourfold, providing a first continental-scale insight into its geographical distribution and establishes several diversification hotspots, notably south-eastern and central Europe. The challenges of recording hyper cryptic diversity in the future are also discussed.

In the beginning of April 2020, large fires that started in the Chernobyl Exclusion Zone (CEZ) established after the Chernobyl accident in 1986 caused media and public concerns about the health impact from the resuspended radioactivity. In this paper, the emissions of previously deposited radionuclides from these fires are assessed and their dispersion and impact on the population is examined relying on the most recent data on radioactive contamination and emission factors combined with satellite observations. About 341 GBq of 137 Cs, 51 GBq of 90 Sr, 2 GBq of 238 Pu, 33 MBq of 239 Pu, 66 MBq of 240 Pu and 504 MBq of 241 Am were released in 1st-22nd April 2020 or about 1,000,000,000 times lower than the original accident in 1986 and mostly distributed in Central and East Europe. The large size of biomass burning particles carrying radionuclides prevents long-range transport as confirmed by concentrations reported in Europe. The highest cumulative effective doses (> 15 μSv) were calculated for firefighters and the population living in the CEZ, while doses were much lower in Kiev (2-5 μSv) and negligible in Belarus, Russia and Europe. All doses are radiologically insignificant and no health impact on the European population is expected from the April 2020 fires.

In this paper, the early Pleistocene small vertebrate sequence of Quibas-Sima (Quibas karstic complex, Murcia, SE Spain) is presented. The available magnetostratigraphic information together with the small vertebrate association, allow to reliably constrain the age of the different units. The basal unit of the section has recorded a reversed polarity assigned to the pre-Jaramillo Matuyama (C1r.2r, i.e., between 1.2 and 1.07 Ma). The intermediate units have recorded a normal polarity correlated directly with the Jaramillo subchron (C1r.1n, between 1.07 and 0.99 Ma), while the upper units record the post-Jaramillo reverse polarity (C1r.1r, i.e., between 0.99 and 0.78). Jaramillo subchron is especially significant regarding the earliest hominin dispersal in Western Europe. However, vertebrate faunas unambiguously correlatable with Jaramillo subchron are extremely rare in Europe. Thereby, the study of the Quibas-Sima sequence allows to characterize the vertebrate association synchronous to this paleomagnetic episode in southern Iberian Peninsula, and contributes to increase knowledge of the biotic and climatic events that took place in southern Europe at the beginning of the Early-Middle Pleistocene transition, prior to the Matuyama-Brunhes boundary. A continuous small vertebrate succession has been reported, including representatives of the families Bufonidae, Pelodytidae, Testudinidae, Gekkonidae, Blanidae, Lacertidae, Colubridae, Viperidae, Soricidae, Erinaceidae, Rhinolophidae, Vespertilionidae, Muridae, Gliridae, Sciuridae, Leporidae and Ochotonidae The ecological affinities of the faunal association suggest a progressive reduction in forest cover in the onset of the Jaramillo subchron.

Globally, maternal birth season affects fertility later in life. The purpose of this systematic literature review is to comprehensively investigate the birth season and female fertility relationship. Using PubMed, we identified a set of 282 relevant fertility/birth season papers published between 1972 and 2018. We screened all 282 studies and removed 131 non-mammalian species studies on fertility and 122 studies that were on non-human mammals. Our meta-analysis focused on the remaining 29 human studies, including twelve human datasets from around the world (USA, Europe, Asia). The main outcome was change in female fertility as observed by maternal birth month and whether this change was correlated with either temperature or rainfall. We found that temperature was either strongly correlated or anti-correlated in studies, indicating that another factor closely tied to temperature may be the culprit exposure. We found that rainfall only increases fertility in higher altitude locations (New Zealand, Romania, and Northern Vietnam). This suggests the possibility of a combined or multi-factorial mechanism underlying the female fertility - birth season relationship. We discuss other environmental and sociological factors on the birth season - female fertility relationship. Future research should focus on the role of birth season and female fertility adjusting for additional factors that modulate female fertility as discussed in this comprehensive review.

Truffles are edible mushrooms with similar morphological characteristics, that make it difficult to distinguish between highly prized truffles (such as the Périgord black T. melanosporum) and inexpensive truffles (such as the Asian Black T. indicum). These biological and economic features have led to several misidentifications and/or fraudulent profit in the truffle markets. In this paper, we investigate Matrix-assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) biotyping to identify 34 commercial fresh truffles from Europe and Asia. The MALDI-TOF MS clustering rapidly distinguished seven Tuber species identified by ITS phylogenetic analysis. The tasty T. melanosporum was clearly differentiated from the Chinese and less expensive truffles. These cheaper mushrooms were marketed as T. indicum but corresponded to a mix of three species. In total, the method confirmed misidentifications in 26% of commercial specimens. Several unknown blind-coded truffles were rapidly identified, with scores >= 2, using the Bruker Biotyper algorithm against MS databases. This study demonstrates that MALDI-TOF MS is a reliable, rapid and cheaper new tool compared with molecular methods for the identification of truffle species and could be used to control frauds in the truffle markets. It could also be useful for the certification of truffle-inoculated seedlings and/or diversity in forest ecosystems.

Carex buekii is a tall sedge, forming large stands in wetlands, particularly in river floodplains across Central Europe and thus on many sites determining the typical appearance of riverine habitats. Our paper aims at increasing the knowledge on ecology of C. buekii and its role in the wetlands. Field data were collected in Poland, the Czech Republic, Slovakia, Hungary, and Italy. Carex buekii usually occurs in nutrient rich habitats, but is also capable of colonising relatively nutrient-poor ones; it grows on both acidic and alkaline soils (pH 3.3-7.4) with diverse concentrations of assimilable elements (Ca, Mg, P, K). One of the most important ecological characteristics of C. buekii is its relationship to the floodplains of watercourses. It seems to be dependent on, or at least very tolerant to regular disturbances by streaming, floods and transport of sediments. Carex buekii usually forms relatively uniform stands of its own association, Caricetum buekii. The species most frequently accompanying C. buekii are Urtica dioica, Calystegia sepium, Galium aparine, Rubus caesius, Phalaris arundinacea, and Cirsium arvense. The sedge also occurs in the understorey of forests with e.g. Alnus glutinosa, Salix fragilis, Padus avium, and Quercus robur. Carex buekii is able to colonise man-made or man-changed habitats such as railway embankments and roadsides or regulated river banks. Taking into account the IUCN Red List Criteria we propose to regard C. buekii as a least-concern (LC).