Complete Series Research Articles

Characteristics and Clinical Outcomes of Vaccine-Eligible US Children Under-5 Years Hospitalized for Acute COVID-19 in a National Network.

In June 2022, the mRNA COVID-19 vaccination was recommended for young children. We examined clinical characteristics and factors associated with vaccination status among vaccine-eligible young children hospitalized for acute COVID-19. We enrolled inpatients 8 months to <5 years of age with acute community-acquired COVID-19 across 28 US pediatric hospitals from September 20, 2022 to May 31, 2023. We assessed demographic and clinical factors, including the highest level of respiratory support, and vaccination status defined as unvaccinated, incomplete, or complete primary series [at least 2 (Moderna) or 3 (Pfizer-BioNTech) mRNA vaccine doses ≥14 days before hospitalization]. Among 597 children, 174 (29.1%) patients were admitted to the intensive care unit and 75 (12.6%) had a life-threatening illness, including 51 (8.5%) requiring invasive mechanical ventilation. Children with underlying respiratory and neurologic/neuromuscular conditions more frequently received higher respiratory support. Only 4.5% of children hospitalized for COVID-19 (n = 27) had completed their primary COVID-19 vaccination series and 7.0% (n = 42) of children initiated but did not complete their primary series. Among 528 unvaccinated children, nearly half (n = 251) were previously healthy, 3 of them required extracorporeal membrane oxygenation for acute COVID-19 and 1 died. Most young children hospitalized for acute COVID-19, including most children admitted to the intensive care unit and with life-threatening illness, had not initiated COVID-19 vaccination despite being eligible. Nearly half of these children had no underlying conditions. Of the small percentage of children who initiated a COVID-19 primary series, most had not completed it before hospitalization.

Digitization of the Built Cultural Heritage: An Integrated Methodology for Preservation and Accessibilization of an Art Nouveau Museum

The emergence of new technologies has dynamized the way in which cultural heritage is documented, preserved, and passed on to new generations; something that determines a paradigm shift in terms of research in this field. Most operations now also have access to the virtual component. In this context, the current study aimed to make accessible through virtual and augmented reality one of the most interesting objectives belonging to the Jewish cultural heritage built in Art Nouveau style in the municipality of Oradea (Romania), which currently functions as a La Belle Epoque Museum. In the study, the techniques of terrestrial, aerial photogrammetry, and terrestrial laser scanning were used to remodel, in a three-dimensional format, as faithful as possible and usable in different applications, the special architecture of the exterior of the monument. This information was doubled by making the interior of the monument accessible through a complete and complex series of panoramic images interconnected within a virtual tour that will be made available to tourists interested in discovering the Darvas-La Roche House. The virtual tour, which includes both graphic, textual, and audio information, represents an innovative approach for the buildings built in Art Nouveau style in the municipality of Oradea, representing a virtual bridge for better promotion of the tourist destination and for the awareness of the local people regarding the importance of preserving and appreciating the local cultural heritage. This is all the more important as this is the first initiative to make the Art Nouveau buildings in Oradea Municipality accessible to the general public in an innovative way.

2081. COVID-19 mRNA Vaccine Effectiveness against Hospitalizations among U.S. Children and Adolescents During Omicron Variant Predominance

Abstract Background SARS-CoV-2 Omicron variants have increased vaccine-induced immune evasion and their emergence coincided with waning COVID-19 vaccine effectiveness (VE). The duration of immunity from the primary series and VE of booster doses against pediatric COVID-19 (Omicron)-associated hospitalizations has not been characterized in the United States. Methods Using a case-control design, we examined VE against laboratory-confirmed COVID-19-associated hospitalizations, enrolling case-patients hospitalized for COVID-19 and SARS-CoV-2 test-negative controls with COVID-like illness from 31 hospitals in 23 states. VE was estimated through multivariable logistic regression by comparing the odds of antecedent primary series or booster COVID-19 mRNA vaccination within and beyond 60 days prior to hospitalization. Results were analyzed by age group (5–11 and 12–18 years) among patients admitted December 19, 2021–March 30, 2023. Results We enrolled 1,242 case-patients (972 [78%] of whom were unvaccinated, 164 [13%] of whom received life support, and 11 of whom died) and 1,309 controls. Among children aged 5-18 years, VE of 2 mRNA doses (complete primary series) against pediatric COVID-19 hospitalization was 64% (95% confidence interval [CI]: 44–76%) at 14-60 days after dose 2 (median time since dose 2, 38 days); VE waned to 38% (95% CI: 23–50%) at ≥60 days (median time since vaccination, 213 days). Within 60 days of a monovalent booster dose, VE was 52% (95% CI: -3–77%); among children aged 5-11 years, VE of a bivalent booster dose was 79% (95% CI: 25-94%). Among case-patients who required life support or died, 122/164 (74%) were unvaccinated and only 3 (2%) had received a bivalent booster dose.Figure 1.Vaccine effectiveness against COVID-19-related hospitalizations, by age group, vaccine dose, and time since last dose. VE estimates were only plotted if confidence interval width was &amp;lt;200. Adjusted models included ≥1 underlying medical condition (yes/no), age in years, census region, biweekly date of hospital admission, and social vulnerability index (SVI) score. Sex and race/ethnicity were tested as confounders in the full model but were dropped for absence of evidence of confounding.Table 1.Critical outcomes among enrolled COVID-19 case-patients ages 5-18 years, by vaccine dose and time since last vaccine dose. Abbreviations: ICU, intensive care unit; ECMO, extracorporeal membrane oxygenation Conclusion COVID-19 mRNA vaccination reduced the likelihood of pediatric COVID-19 hospitalization by &amp;gt;60%; VE waned but remained protective, even at a median of 213 days after dose 2. Although not reaching statistical significance due to limited power, monovalent boosters appeared to temporarily restore protection, and bivalent booster doses among 5–11-year-olds were nearly 80% protective against hospitalization. Nearly three quarters of children requiring life support or who died were unvaccinated. Disclosures Regina Simeone, PhD, Pfizer: Stocks/Bonds Natasha B. Halasa, MD, MPH, Merck: Grant/Research Support|Quidell: Grant/Research Support|Quidell: donation of kits|Sanofi: Grant/Research Support|Sanofi: vaccine support

Synthesis, structure–activity relationship studies using density functional theory and in silico molecular docking on substituted benzohydrazide derivatives

The present study demonstrates the utility of benzohydrazide derivatives based on an approach to identify potential targets for a series of synthesized compounds that show potent anticancer activities against four cancer cell lines compared to other structurally related molecules. Benzohydrazide compounds have been synthesized effectively by the condensation of aldehyde and hydrazide at a 1:1 molar ratio. The complete series of compounds 1a-j were characterized by FT-IR, NMR, and one of them by single-crystal X-ray diffraction. The crystal structure of compound 1a shows a trans configuration around the CN bond and crystallized in a monoclinic system with C 2/c space group. All compounds exhibited good anticancer activity against four cancer cell lines such as A375 (human malignant melanoma), A549 (human lung adenocarcinoma), HT-29 (human epithelial intestinal) and MDA-MB-232(human metastatic breast). Among them, compound 1e shows the highest cytotoxic effect against the HT29 (IC50 = 0.47 µM) and A375 (IC50 = 0.80 µM) cell lines. Other compounds also exhibited promising anticancer activity. In addition, the nontoxic action was verified using the cytocompatibility assay on the L929 normal cell line and the hemolysis assay on human red blood cells. Parameters such as HOMO-LUMO energies, Hirshfeld surface analysis, and Molecular Electrostatic Potential (MEP) surface have been calculated using DFT and compared to experimental values of compounds 1a-c. In silico molecular docking studies revealed that the compound 1 h interacted very strongly with the 1T46 protein, with a docking score of −9.7 kcal/mol and very good binding via π–π, π-alkyl and π–σ interactions as compared to the standard drug. As a result of their potent cytotoxicity activities and computational analysis, these can be considered promising anticancer agents.

Unravelling the Impacts of Climate Variability on Surface Runoff in the Mouhoun River Catchment (West Africa)

This study assesses the impacts of climate variability on surface runoff generation in the Mouhoun River Catchment (MRC) in Burkina Faso, in the West African Sahel. The study uses a combination of observed and reanalysis data over the period 1983–2018 to develop a SWAT model (KGE = 0.77/0.89 in calibration/validation) further used to reconstitute the complete time series for surface runoff. Results show that annual rainfall and surface runoff follow a significant upward trend (rainfall: 4.98 mm·year−1, p-value = 0.029; runoff: 0.45 m3·s−1·year−1, p-value = 0.013). Also, rainfall appears to be the dominant driver of surface runoff (Spearman’s ρ = 0.732, p-value &lt; 0.0001), leading surface runoff at all timescales. Surface runoff is further modulated by potential evapotranspiration with quasi-decadal timescales fluctuations, although being less correlated to surface runoff (Spearman’s ρ = −0.148, p-value = 0.386). The study highlights the added value of the coupling of hydrological modeling and reanalysis datasets to analyze the rainfall–runoff relationship in data-scarce and poorly gauged environments and therefore raises pathways to improve knowledge and understanding of the impacts of climate variability in Sahelian hydrosystems.

Rockfall monitoring with a Doppler radar on an active rockslide complex in Brienz/Brinzauls (Switzerland)

Abstract. We present and analyze a rockfall catalog from an active landslide complex in Brienz/Brinzauls of the Swiss Alps, collected with a new Doppler radar system. This radar system provides a complete and continuous time series of rockfall events with volumes of 1 m3 and greater since 2018 and serves as automatic traffic control for an important main road. In the period between January 2018 and October 2022, 6743 events were detected, which is 2 orders of magnitude higher activity than in stable continental cliffs. A few percent of all rockfall events reached the shadow area, which hosts an important road and agricultural area. The Doppler radar data set allows us to investigate the triggering factors quantitatively. We found that the background rockfall activity is controlled by seasonal climatic triggers. In winter, more rockfalls are observed during thawing periods, whereas in summer the rockfall activity increases with hourly rainfall intensity. We also found that, due to the geological setting in an active landslide complex, increased rockfall activity occurs clustered in space and time, triggered by local displacement hotspots. Thus, monitoring spatial and temporal variations of slope displacement velocity is crucial for detailed rockfall hazard assessment in similar geological settings.

Cross-Frame Resource Allocation With Context-Aware QoE Estimation for 360° Video Streaming in Wireless Virtual Reality

Wireless virtual reality (VR), aiming to provide an untethered immersive experience through 360° videos, could be facilitated by viewport-guided streaming with the help of viewport prediction. Although many recent viewport predictors can output a series of predictions over upcoming frames, most existing work on video streaming does not fully utilize the capability of these predictors. In this paper, we investigate the problem of 360° video streaming by incorporating the complete series of viewport predictions for maximizing the quality of experience (QoE) through cross-frame resource allocation. To address the problem of viewport prediction errors that could result in erroneous estimation of QoE contribution of tiles in upcoming frames, we develop a novel approach based on contextual multi-armed bandit (CMAB) to “learn” <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">online</i> the viewing behavior of the user and the capability of the predictor such that resource can be preferentially allocated to tiles with significant QoE contribution. Further, to address the problem of transmission failures during wireless streaming, we formulate a constrained Markov decision process (CMDP) and apply model predictive control (MPC) to account for resource competition among reactive and proactive transmissions as well as retransmissions of tiles. The performance of the proposed streaming system is evaluated using a real-world VR dataset, state-of-the-art viewport predictors, and realistic mmWave channel models. An improvement of 10.2% in QoE and a reduction of 18.7% in resource waste are achieved across various videos, users, and predictors. Simulation results substantiate that the context-aware QoE learned by the proposed CMAB effectively addresses prediction errors for tiles with different temporal and spatial contexts, and the proposed CMDP can achieve the desired performance even under tight bandwidth constraint and severe channel condition.

Employing higher density lower reliability weather data from the Global Historical Climatology Network monitors to generate serially complete weather data for watershed modelling

AbstractHydrological models require complete and accurate weather data time series to represent watershed‐scale responses adequately. The Global Historical Climatology Network (GHCN) is the most comprehensive weather database used in hydrological modelling studies globally. Since higher‐density, lower‐reliability precipitation measurements from private citizens collected by the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network data were integrated into the GHCN, hydrological modellers in the United States have access to a much greater amount of weather data. However, the benefit of using CoCoRaHS data has not been assessed. The objectives of this work were to develop a method for generating a complete weather data time series based on the combination of data from multiple GHCN monitors and to assess several methods for the estimation of missing weather data. Weather data from GHCN monitors located within a specific radius of a watershed were obtained and interpolated using three estimation methods (Inverse Distance Weighting (IDW), Inverse Distance and Elevation Weighting (IDEW) and Closest Station), creating a seamless time series of weather observations. To evaluate the performance of the methodologies, weather data obtained from each estimation method was used to force the Soil and Water Assessment Tool (SWAT) and Thornthwaite‐Mather models for 21 US Department of Agriculture‐Conservation Effects Assessment Project watersheds in different climate regions to simulate daily streamflow for 2010–2021. Except for three watersheds, all of the SWAT models had Nash‐Sutcliffe Efficiency above 0.5, the ratio of the root mean square error to the standard deviation of observations below 0.7, and percent bias from −25% to 25% with a satisfactory performance rating. IDEW and IDW performed similarly, and the Closest Station method resulted in the poorest streamflow simulation. A comparison with published SWAT model results further corroborated improved model performance using novel combined GHCN data with all Closest Station, IDW and IDEW methods.

High-pressure Raman spectroscopy study of α-quartz-like Si1-xGexO2 solid solution

Spontaneous α-Si1-xGexO2 single crystals were synthesized using the set of crystal growth techniques: hydrothermal (XGe = 0.09, 0.20), flux (XGe = 0.45, 0.70) and recycling (XGe = 0.96). The XRD and spectroscopic studies with non-negative matrix factorization show linear dependences of structural parameters and Raman shift on germanium content and confirmed the existence of a complete series of α-Si1-xGexO2 solid solution. The synthesized samples of the solid solution were studied by Raman spectroscopy at the ambient conditions and for the first time at high pressures up to ∼30 GPa. The obtained results suggest a phase transition “α-quartz → post-quartz” for Si1-xGexO2 in the examined pressure range. The formation of the possible intermediate phase (quartz-II) was detected for Si1-xGexO2 with XGe = 0.09, 0.20 and 0.45 at 11, 10 and 7.5 GPa, respectively. The linear dependences of the pressure value of phase transitions on germanium content were observed. At decompression, the post-quartz phase remained stable that was determined by Raman spectra for all compositions of solid solution. Obtained experimental results revealed the correlation of the chemical composition, spectroscopic characteristics, and structural deformations at ambient conditions and at high pressures.

Machine learning models to complete rainfall time series databases affected by missing or anomalous data

In recent years, artificial intelligence in geosciences is spreading more and more, thanks to the availability of a large amount of data. In particular, the development of automatic raingauges networks allows to get rainfall data and makes these techniques effective, even if the performance of artificial intelligence models is a consequence of the coherency and quality of the input data. In this work, we intended to provide machine learning models capable of predicting rainfall data starting from the values of the nearest raingauges at one historic time point. Moreover, we investigated the influence of the anomalous input data on the prediction of rainfall data. We pursued these goals by applying machine learning models based on Linear Regression, LSTM and CNN architectures to several raingauges in Tuscany (central Italy). More than 75% of the cases show an R2 higher than 0.65 and a MAE lower than 4 mm. As expected, we emphasized a strong influence of the input data on the prediction capacity of the models. We quantified the model inaccuracy using the Pearson's correlation. Measurement anomalies in time series cause major errors in deep learning models. These anomalous data may be due to several factors such as temporary malfunctions of raingauges or weather conditions. We showed that, in both cases, the data-driven model features could highlight these situations, allowing a better management of the raingauges network and rainfall databases.

Restructuring and serving web-accessible streamflow data from the NOAA National Water Model historic simulations

In 2016, the National Oceanic and Atmospheric Administration deployed the first iteration of an operational National Water Model (NWM) to forecast the water cycle in the continental United States. With many versions, an hourly, multi-decadal historic simulation is made available to the public. In all released to date, the files containing simulated streamflow contain a snapshot of model conditions across the entire domain for a single timestep which makes accessing time series a technical and resource-intensive challenge. In the most recent release, extracting a complete streamflow time series for a single location requires managing 367,920 files (~16.2 TB). In this work we describe a reproducible process for restructuring a sequential set of NWM steamflow files for efficient time series access and provide restructured datasets for versions 1.2 (1993–2018), 2.0 (1993–2020), and 2.1 (1979–2022). These datasets have been made accessible via an OPeNDAP enabled THREDDS data server for public use and a brief analysis highlights the latest version of the model should not be assumed best for all locations. Lastly we describe an R package that expedites data retrieval with examples for multiple use-cases.

The effect of homogenization when constructing long‐term gridded monthly precipitation and temperature data

AbstractWhen assessing long‐term climate trends and variability, it is important to analyse data that are not disturbed by external factors that might lead to misleading trends. It is also urgent to analyse consistent series that cover the entire time period. Since observation networks are continuously changing not too many complete series are available for a centennial long analysis. In this paper an approach to construct long‐term homogenized climate series to be used to derive a long‐term gridded dataset is presented. A gridded dataset of monthly climate anomalies based on all available observations was used to construct 165 raw temperature series and 323 raw precipitation series covering the entire period 1901–2020. These series are homogenized by using the automatic procedure in the R‐package climatol. The gridded data based on the homogenized data show the same regional trends and variability as the data derived from non‐homogenized data. The local spatial variance is smaller in the gridded data based on homogenized series than those based on the raw data series. Both the construction and homogenization of data series to provide spatial and temporal consistent data for gridding lead to better and more reliable gridded datasets for analysing climate trends and variability.

The sum of four squares over real quadratic number fields

Well-known results of Lagrange and Jacobi prove that every [Formula: see text] can be expressed as a sum of four integer squares, and the number [Formula: see text] of such representations can be given by an explicit formula in [Formula: see text]. In this paper, we prove that the only real quadratic number field for which the sum of four squares is universal is [Formula: see text]. We provide explicit formulas for [Formula: see text] for [Formula: see text] and [Formula: see text]. We then consider the theta series of the sum of four squares over any real quadratic number field, providing explicit upper and lower bounds for the Eisenstein coefficients. Last, we include examples of the complete theta series decomposition of the sum of four squares over [Formula: see text], [Formula: see text] and [Formula: see text].

Unstructured citizen science reduces the perception of butterfly local extinctions: the interplay between species traits and user effort

The detection of local extinctions is often hindered by the lack of long-term monitoring schemes, and thus relies on time series of presence data. Recently, citizen science has repeatedly shown its value in documenting species occurrences. We investigated the effectiveness of unstructured citizen science records in reducing the perception of local extinctions in butterfly populations across Italian National Parks. We addressed three research questions: (i) the ability of citizen science data to supplement existing knowledge to complete time series of occurrences, (ii) the impact on data collection of three species features (species size, distribution and length of flight period) determining their appearance, and (iii) the interplay between participant effort and species appearance in the amount of diversity recorded on the iNaturalist platform. Our analysis of 98,922 records of Italian butterflies (39,929 from literature and 58,993 from iNaturalist of which 7427 from National Parks) showed that the addition of iNaturalist data filled many recent gaps in time series, thus reducing the perception of potential local extinctions. Records from more engaged users encompassed a higher fraction of local biodiversity and were more likely to reduce the perception of local extinctions. User effort strongly interacted with species features in determining the frequency of records for individual species. In particular, more engaged users were less affected by species size. We provided updated butterfly checklists for Italian National Parks and a R package to calculate potential extinction upon time series. These results offer guidance for protected areas, conservationists, policymakers, and citizen scientists to optimize monitoring of local populations.

Ontogenetic variation in the cranium of Mixosaurus cornalianus, with implications for the evolution of ichthyosaurian cranial development

Relatively complete ontogenetic series are comparatively rare in the vertebrate fossil record. This can create biases in our understanding of morphology and evolution, since immaturity can represent a source of unrecognized intraspecific variation in both skeletal anatomy and ecology. In the extinct marine reptile clade Ichthyopterygia, ontogenetic series were widely studied only in some Jurassic genera, while the ontogeny of the oldest and most basal members of the clade is very poorly understood. Here, we investigate cranial ontogeny in Mixosaurus cornalianus, from the Middle Triassic Besano Formation of the Swiss and Italian Alps. This small-bodied taxon is represented by a wealth of material from multiple size classes, including fetal material. This allows us to assess ontogenetic changes in cranial morphology, and identify stages in the ontogenetic trajectory where divergence with more derived ichthyosaurs has occurred. Early ontogenetic stages of Mixosaurus show developmental patterns that are reminiscent of the presumed ancestral (early diverging sauropsid) condition. This is prominently visible in the late fetal stage in both the basioccipital, which shows morphology akin to basal tubera, and in the postorbital, which has a triradiate head. The ontogenetic trajectory of at least some of the cranial elements of Mixosaurus is therefore likely still very akin to the ancestral condition, even though the adult cranium diverges from the standard diapsid morphology.

Floods and Diarrhea Risk in Young Children in Low- and Middle-Income Countries

Climate change is associated with more frequent and intense floods. Current research on the association between flood exposure and diarrhea risk is limited mainly to short-term and event-specific analyses. Moreover, how prior drought or water, sanitation, and hygiene (WaSH) practices influence this association remains largely unknown. To examine the association between flood exposure and diarrhea risk among children younger than 5 years and to evaluate the compounding influence of prior drought and effect modification by WaSH. This cross-sectional study included multicluster surveys conducted by the Demographic and Health Surveys Program in 43 low- and middle-income countries during 2009 through 2019. This study included children younger than 5 years in all households from each survey cluster. Collected data were analyzed between September 1 and December 31, 2022. Historical flood events during 2009 through 2019 were obtained from the Dartmouth Flood Observatory. The main outcome was diarrhea prevalence among children younger than 5 years in the 2 weeks before the survey was conducted. Results were analyzed by binomial generalized linear mixed-effects logistic regression models with nested random intercepts for country and survey cluster. Among 639 250 children making up the complete data series (excluding 274 847 children with missing values for diarrhea or baseline characteristics), 6365 (mean [SD] age, 28.9 [17.2] months; 3214 boys [50.5%]; 3151 girls [49.5%]) were exposed to floods during the 8 weeks after a flood started. The prevalence of diarrhea was 13.2% (n = 839) among exposed children and 12.7% (n = 80 337) among unexposed children. Exposure to floods was associated with increased diarrhea risk, with the highest odds ratio (OR) observed during the second to fourth weeks after floods started (OR, 1.35; 95% CI, 1.05-1.73). When floods were stratified by severity and duration, significant associations were observed only for extreme floods (OR during the third to fifth weeks, 2.07; 95% CI, 1.37-3.11) or floods lasting more than 2 weeks (OR during the second to fourth weeks, 1.47; 95% CI, 1.13-1.92), with significantly stronger associations than for less extreme floods or shorter-duration floods, respectively. The OR during the first 4 weeks after the start of floods was significantly higher for floods preceded by a 6-month or longer drought (12-month drought OR, 1.96; 95% CI, 1.53-2.52) than for floods not preceded by a 6-month or longer drought (12-month drought OR, 1.00; 95% CI, 0.79-1.27). These findings suggest that floods, especially severe floods, long-duration floods, and floods preceded by drought, are associated with an increased risk of diarrhea among children younger than 5 years living in low- and middle-income countries. With the projected increasing frequency and intensity of floods and drought under climate change, greater collective efforts are needed to protect children's health from these compounding events.

Missing interpolation model for wind power data based on the improved CEEMDAN method and generative adversarial interpolation network

Randomness and fluctuations in wind power output may cause changes in important parameters (e.g., grid frequency and voltage), which in turn affect the stable operation of a power system. However, owing to external factors (such as weather), there are often various anomalies in wind power data, such as missing numerical values and unreasonable data. This significantly affects the accuracy of wind power generation predictions and operational decisions. Therefore, developing and applying reliable wind power interpolation methods is important for promoting the sustainable development of the wind power industry. In this study, the causes of abnormal data in wind power generation were first analyzed from a practical perspective. Second, an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) method with a generative adversarial interpolation network (GAIN) network was proposed to preprocess wind power generation and interpolate missing wind power generation sub-components. Finally, a complete wind power generation time series was reconstructed. Compared to traditional methods, the proposed ICEEMDAN-GAIN combination interpolation model has a higher interpolation accuracy and can effectively reduce the error impact caused by wind power generation sequence fluctuations

A palaeohydrological record of a complete Eemian series from Żabieniec Ża-19 (Garwolin Plain, Central Poland) with reference to palaeoclimate data

The aim of this study was to reconstruct the evolution of the Eemian palaeolake in the Żabieniec site (Garwolin Plain, Central Poland); it identifies changes in the water level and the trophic status of the lake resulting from panregional factors, including climate changes occurring during individual phases of the last interglacial, and local geologic-geomorphological factors shaping the palaeoenvironment using multi-proxy methods (palaeobotanical analyses, subfossil Cladocera and diatoms analyses as well as determinations of the stable isotopes). A record was obtained of all seven Regional Pollen Assemblage Zones (RPAZs) according to Mamakowa’s description of the Eemian pollen succession (1989), and of the changes in microfossil assemblages and isotopes in palaeolake sediments associated with lake evolution. Special attention was paid to the Middle Eemian RPAZ 4 (i.e. hazel phase) of the climatic optimum; all proxies associate this with the highest water level and a warm humid climate. During the E5/E6 RPAZs, the eutrophic lake transformed very quickly, and a transitional peatbog was formed. The higher humidity of the late Eemian resulted in another increase in water level. The multi-proxy record of the Żabieniec palaeolake which we obtained was compared to those of other Eemian water bodies in the Garwolin Plain and in Central Poland that exhibit sedimentation gaps especially during the younger part of the E5 RPAZ.

Bone histology of the Late Pleistocene Prolagus sardus (Lagomorpha: Mammalia) provides further insights into life-history strategy of insular giant small mammals

Abstract Fossils provide an excellent opportunity to study and understand the evolution of insular environments free of human-made perturbations. Here, we evaluated the life-history traits and strategy of the extinct insular giant Prolagus sardus (Mammalia: Lagomorpha) by examining microscopically its fossilized bone tissues (osteohistology, skeletochronology, and quantitative geometry). For this task, a complete ontogenetic series of femora retrieved from the Late Pleistocene Grotta della Medusa (NW Sardinia, Italy) were analysed. Our results reveal that: (i) P. sardus’ pups were weaned at large size; (ii) the species’ maturation was delayed in its life cycle; and (iii) P. sardus lived longer than expected for its size. Hence, the giant P. sardus should have a slow pace of life triggered by the low levels of extrinsic mortality of the insular habitat. On the other hand, bone tissue differences between P. sardus and Ochotona were found in the vascularization, slow- growing bone presence, and cortical and medullary growth trajectories. The results obtained in this study concur with the eco-evolutionary responses described to date in extinct insular lagomorphs, as well as provide new empirical evidence about the phenomenon known as ‘insular gigantism’ as a pattern of evolution of small-sized mammals in genuine insular ecosystems.

Asteroseismology and Spectropolarimetry of the Exoplanet Host Star λ Serpentis

The bright star λ Ser hosts a hot Neptune with a minimum mass of 13.6 M ⊕ and a 15.5 day orbit. It also appears to be a solar analog, with a mean rotation period of 25.8 days and surface differential rotation very similar to the Sun. We aim to characterize the fundamental properties of this system and constrain the evolutionary pathway that led to its present configuration. We detect solar-like oscillations in time series photometry from the Transiting Exoplanet Survey Satellite, and we derive precise asteroseismic properties from detailed modeling. We obtain new spectropolarimetric data, and we use them to reconstruct the large-scale magnetic field morphology. We reanalyze the complete time series of chromospheric activity measurements from the Mount Wilson Observatory, and we present new X-ray and ultraviolet observations from the Chandra and Hubble space telescopes. Finally, we use the updated observational constraints to assess the rotational history of the star and estimate the wind braking torque. We conclude that the remaining uncertainty on the stellar age currently prevents an unambiguous interpretation of the properties of λ Ser, and that the rate of angular momentum loss appears to be higher than for other stars with a similar Rossby number. Future asteroseismic observations may help to improve the precision of the stellar age.