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ABSTRACT: Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH4]:[CO2], in breath from individual animals (the so-called “sniffer technique”) and estimated CO2 production can be used to estimate CH4 production, provided that CO2 production can be reliably calculated. This would allow CH4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH4 production might become possible and their values could be used for breeding of low CH4-emitting animals. Estimates of CO2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO2 production directly from milk production, dietary, and animal variables, and furthermore to develop different models to be used for different scenarios, depending on available data. An international dataset with 2,244 records from individual lactating cows including CO2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk, and days pregnant, was compiled to constitute the training dataset. Research location and experiment nested within research location were included as random intercepts. The method of CO2 production measurement (respiration chamber [RC] or GreenFeed [GF]) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training dataset: model 1 (“best model”), where all significant traits were included; model 2 (“on-farm model”), where DMI was excluded; and model 3 (“reduced on-farm model”), where both DMI and BW were excluded. Evaluation on test dat sets with either RC data (n = 103), GF data without additives (n = 478), or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (−0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic overprediction and underprediction of CO2 production when the models were evaluated on the GF and the RC test datasets, respectively. To address this bias, the 3 models were evaluated on a modified test dataset, where the CO2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test datasets. With this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO2 production from lactating dairy cows.

The Global Navigation Satellite System (GNSS) is a key asset for tropospheric monitoring. Currently, GNSS meteorology relies primarily on geodetic-grade stations. However, such stations are too costly to be densely deployed, which limits the contribution of GNSS to tropospheric monitoring. In 2016, Google released the raw GNSS measurement application programming interface for smartphones running on Android version 7.0 and higher. Given that nowadays there are billions of Android smartphones worldwide, utilizing those devices for atmospheric monitoring represents a remarkable scientific opportunity. In this study, smartphone GNSS data collected in Germany as part of the Application of Machine Learning Technology for GNSS IoT Data Fusion (CAMALIOT) crowdsourcing campaign in 2022 were utilized to investigate this idea. Approximately 20 000 raw GNSS observation files were collected there during the campaign. First, a dedicated data processing pipeline was established that consists of two major parts: machine learning (ML)-based data selection and ionosphere-free precise point positioning (PPP)-based zenith total delay (ZTD) estimation. The proposed method was validated with a dedicated smartphone data collection experiment conducted on the rooftop of the ETH campus. The results confirmed that ZTD estimates of millimeter-level precision could be achieved with smartphone data collected in an open-sky environment. The impacts of observation time span and utilization of multi-GNSS observations on ZTD estimation were also investigated. Subsequently, the crowdsourced data from Germany were processed by PPP with the ionospheric delays interpolated using observations from surrounding satellite positioning service of the German National Survey (SAPOS) GNSS stations. The ZTDs derived from ERA5 and an ML-based ZTD product served as benchmarks. The results revealed that an accuracy of better than 10 mm can be achieved by utilizing selected high-quality crowdsourced smartphone data. This study demonstrates high-precision ZTD determination with crowdsourced smartphone GNSS data and reveals success factors and current limitations.

The presence of a ski resort modifies the snow cover at the local scale, due to snow management practices on ski pistes, especially grooming and snowmaking. Snow management exerts 2-fold effects on the local hydrological cycle, through (i) abstraction and transfer of water used for snowmaking, and (ii) changes in water runoff due to added snow mass through snowmaking and/or delayed melting of the snowpack due to snow grooming. This induces a local pressure on water resources, which has seldom been addressed in scientific studies hitherto. Here we introduce a method to compute the hydrological effects of snow management on ski pistes and we apply and illustrate its results for the case study of the La Plagne ski resort in the Northern French Alps. The approach mainly relies on snow cover modelling using the Crocus snow cover driven by SAFRAN reanalysis and climate projections. Model results are evaluated against in-situ hydrological observations and show that the modelling approach, although very simplified for many hydrological processes, provides relevant information and insights in terms of the influence of snow-related processes on water resources. Our study shows a visible impact of grooming, virtually eliminating snowmelt in winter, thus delaying the onset of snowmelt. This results is a lower snowmelt flux during the wintertime, low flow period, on the order of −10 % to −20 %, compensated by higher amounts when snow melts. While about 10 % of the water used for snowmaking is estimated to be lost by evaporation through the ice formation process from the liquid water droplets, we find that, in the case studied, the annual scale alteration of water resources is limited and estimated to be on the order of 1 % to 2 %. This is due to the fact that the amount of water used for snowmaking on ski pistes represents a fraction of 10 % to 20 % of total annual precipitation, that ski pistes cover typically 10 % of the surface area of catchments within which ski resorts are located, and that snowmaking equipment covers, in the case of La Plagne, 40 % of the surface area of ski pistes. Therefore, in this case, snowmaking mainly leads to a moderate shift in snow cover formation and snowmelt processes and plays, for example, a smaller role than the influence of future climate change on mountain hydrology. This study provides an initial overview of the influence of grooming and snowmaking on river flows in a mountain catchment, which can inform future studies on water management and climate change adaptation in areas with ski tourism facilities. This study does not discuss long-term sustainability challenges of ski tourism and other aspects of the local environmental impacts (landscape, biodiversity) of snow management, such as the construction and use of mountain water reservoirs and other earthworks in ski resorts.

Remote sensing of water vapour using the Global Navigation Satellite System (GNSS) is a well-established technique and reliable data source for numerical weather prediction (NWP). However, one of the phenomena rarely studied using GNSS are foehn winds. Since foehn winds are associated with significant humidity gradients between two sides of a mountain range, tropospheric estimates from GNSS are also affected by their occurrence. Time series reveal characteristic features like distinctive minima and maxima as well as a significant decrease in the correlation between the stations. However, detecting such signals becomes increasingly difficult for large datasets. Therefore, we suggest the application of machine learning algorithms for the detection and prediction of foehn events by means of GNSS troposphere products. This initial study develops a new, machine learning-based method for detection and prediction of foehn events at the Swiss station Altdorf by utilising long-term time series of high-quality GNSS troposphere products. Data from the Automated GNSS Network Switzerland (AGNES) and various GNSS sites from neighbouring countries as well as records of an operational foehn index are used to investigate the performance of several different classification algorithms based on appropriate statistical metrics. The two best-performing algorithms are fine tuned and tested in four dedicated experiments using different feature setups. The results are promising, especially when reprocessed GNSS products are utilised and the most dense station setup is used. Detection- and alarm-based measures reach levels between 66 %–80 % for both tested algorithms and thus are comparable to those from studies using data from meteorological stations and NWP. For operational prediction, limitations due to the availability and quality of GNSS products in near-real time (NRT) exist. However, they might be mitigated to a significant extent by provision of additional NRT products and improved data processing in the future. Results also outline benefits for the results when including geographically relevant stations (e.g. high-altitude stations) in the utilised datasets.

Background: Alzheimer's Disease (AD) and Type 2 Diabetes Mellitus (T2DM), two prevalent diseases related to ageing, often share common pathologies including increased inflammation, endoplasmic reticulum (ER) stress, and impaired metabolic homeostasis predominantly affecting different organs. Therefore, it was unexpected to find in a previous study that neuronal hBACE1 knock-in (PLB4 mouse) leads to both an AD- and T2DM- like phenotype. The complexity of this co-morbidity phenotype required a deeper systems approach to explore the age-related changes in AD and T2DM-like pathologies of the PLB4 mouse. Therefore, we here analysed key neuronal and metabolic tissues comparing associated pathologies to those of normal ageing. Methods: Glucose tolerance, insulin sensitivity and protein turnover were assessed in 5-h fasted 3- and 8-month-old male PLB4 and wild-type mice. Western Blot and quantitative PCR were performed to determine regulation of homeostatic and metabolic pathways in insulin-stimulated brain, liver and muscle tissue. Results: Neuronal hBACE1 expression caused early pathological cleavage of APP (increased monomeric Aβ (mAβ) levels at 3 months), in parallel with brain ER stress (increased phosphorylation of the translation regulation factor (p-eIF2α) and the chaperone binding immunoglobulin protein (BIP)). However, APP processing shifted over time (higher full-length APP and secreted APPβ levels, alongside lower mAβ and secreted APPα at 8 months), together with increased ER stress (phosphorylated/total inositol-requiring enzyme 1α (IRE1α)) in brain and liver. Metabolically, systemic glucose intolerance was evident from 3 months, yet metabolic signalling varied greatly between tissues and ages, and was confined to the periphery (increased muscle insulin receptors (IR), dipeptidyl-peptidase-4 (DPP4) levels, and decreased phosphorylated protein Kinase B (p-Akt), alongside increased liver DPP4 and fibroblast growth factor 21 (FGF21)), all of which normalised to wild-type levels at 8 months. Conclusion: Our data suggest that the murine nervous system is affected early by APP misprocessing as a result of hBACE1 introduction, which coincided with ER stress, but not IR changes, and was alleviated with age. Peripheral metabolic alterations occurred early and revealed tissue-specific (liver vs. muscle) adaptations in metabolic markers but did not correlate with neuronal APP processing. Compensatory vs. contributory neuronal mechanisms associated with hBACE1 expression at different ages may explain why mice intrinsically do not develop AD pathologies and may offer new insights for future interventions.

Several single-platform satellite missions have been designed during the past decades in order to retrieve the atmospheric concentrations of anthropogenic greenhouse gases (GHG), initiating worldwide efforts towards better monitoring of their sources and sinks. To set up a future operational system for anthropogenic GHG emission monitoring, both revisit frequency and spatial resolution need to be improved. The Space Carbon Observatory (SCARBO) project aims at significantly increasing the revisit frequency of spaceborne GHG measurements, while reaching state-of-the-art precision requirements, by implementing a concept of small satellite constellation. It would accommodate a miniaturised GHG sensor named NanoCarb coupled with an aerosol instrument, the multi-angle polarimeter SPEXone. More specifically, the NanoCarb sensor is a static Fabry–Pérot imaging interferometer with a 2.3×2.3 km2 spatial resolution and 200 km swath. It samples a truncated interferogram at optical path differences (OPDs) optimally sensitive to all the geophysical parameters necessary to retrieve column-averaged dry-air mole fractions of CO2 and CH4 (hereafter XCO2 and XCH4). In this work, we present the Level 2 performance assessment of the concept proposed in the SCARBO project. We perform inverse radiative transfer to retrieve XCO2 and XCH4 directly from synthetic NanoCarb truncated interferograms and provide their systematic and random errors, column vertical sensitivities, and degrees of freedom as a function of five scattering-error-critical atmospheric and observational parameters. We show that NanoCarb XCO2 and XCH4 systematic retrieval errors can be greatly reduced with SPEXone posterior outputs used as improved prior aerosol constraints. For two-thirds of the soundings, located at the centre of the 200 km NanoCarb swath, XCO2 and XCH4 random errors span 0.5–1 ppm and 4–6 ppb, respectively, compliant with their respective 1 ppm and 6 ppb precision objectives. Finally, these Level 2 performance results are parameterised as a function of the explored scattering-error-critical atmospheric and observational parameters in order to time-efficiently compute extensive L2 error maps for future CO2 and CH4 flux estimation performance studies.

A climatic anomaly can potentially affect the hydrological behaviour of a catchment for several years. This article presents a new approach to quantifying this multi-year hydrological memory, using exclusively streamflow and climate data. Rather than providing a single value of catchment memory, we aim to describe how this memory fades over time. The precipitation–runoff relationship is analyzed through the concept of elasticity. Elasticity quantifies the change in one quantity caused by the change in another quantity. We analyze the elasticity of the relation between the annual anomalies of runoff yield and humidity index. We identify Catchment Forgetting Curves (CFC) to quantify multi-year catchment memory, considering not only the current year's humidity anomaly but also the anomalies of the preceding years. The variability of CFCs is investigated on a set of 158 Swedish and 527 French catchments. As expected, French catchments overlying large aquifers exhibit a long memory, i.e., with the impact of climate anomalies detected over several years. In Sweden, the expected effect of the lakes is less clear. For both countries, a relatively strong relationship between the humidity index and memory is identified, with drier regions exhibiting longer memory. Taking into account the multi-year memory has significantly improved the elasticity analysis for 15 % of the catchments. Our work thus underlines the need to account for catchment memory in order to produce meaningful and geographically coherent elasticity indices.

UK-based national surveys and international longitudinal studies have shown that around a third of parents experience chronic or persistent loneliness. There is limited research about the experience of loneliness in parenthood, however blogs authored by parents, sharing their personal experiences about loneliness offer a potential rich data source. The purpose of this study was to identify and analyse blog narratives written by parents who had experienced loneliness to increase understanding of their experiences. One hundred and ninety-six relevant blog posts were identified, of which 157 had contact details to request permission to use the blog post in the study. Twenty-two parent bloggers gave their permission. Thematic network analysis was used to open code the blogs and 4 organising themes and subthemes emerged, which centred on a global theme of disconnection. Disconnection underpinned themes relating to a sense that being a parent was overwhelming, changes in identity linked to becoming a parent, difficulties in sharing feelings of loneliness with others, and a need for social connection. Findings point to parents being unprepared for the transition to parenthood, with implications for perinatal education and support, including further opportunities for parents to connect to reduce social isolation.

Ventricular Assist Devices (VAD) are enabling children experiencing severe heart failure, who would have otherwise died, to be bridged to transplant or recovery. Donated Paediatric hearts are in short supply, so the use of VAD is likely to continue to support paediatric patients for the foreseeable future. This study explored the experiences of children and young people (CYP) being supported by VAD and their families. Semi-structured interviews were undertaken with 24 families after transplant (either parents only, parents and CYP together, or CYP only), and two participant observations with families currently living with a child on VAD. This study was conducted at one of two UK Paediatric Heart Transplantation Centres. The data suggest that families adjust to a ‘new normal’ that the heart failure and subsequent medical intervention brings. This involves adjusting to the initial diagnosis and need for VAD implantation; establishing a new life on VAD; the emotional roller coaster that comes with this highly invasive treatment option; and, adapting to a new way of life following transplant. This research adds to the limited available research on the experience of families with a CYP being supported by VAD. The family viewpoint raises important issues about highly invasive treatment, the lived realities of VAD implantation and subsequent transplant, and the forever changed lives post discharge. These perspectives are of great importance when considering the growth of both VAD implantation and paediatric heart transplantations as established therapeutic treatment options.

Climate models' outputs are affected by biases that need to be detected and adjusted to model climate impacts. Many climate hazards and climate-related impacts are associated with the interaction between multiple drivers, i.e. by compound events. So far climate model biases are typically assessed based on the hazard of interest, and it is unclear how much a potential bias in the dependence of the hazard drivers contributes to the overall bias and how the biases in the drivers interact. Here, based on copula theory, we develop a multivariate bias-assessment framework, which allows for disentangling the biases in hazard indicators in terms of the underlying univariate drivers and their statistical dependence. Based on this framework, we dissect biases in fire and heat stress hazards in a suite of global climate models by considering two simplified hazard indicators: the wet-bulb globe temperature (WBGT) and the Chandler burning index (CBI). Both indices solely rely on temperature and relative humidity. The spatial pattern of the hazard indicators is well represented by climate models. However, substantial biases exist in the representation of extreme conditions, especially in the CBI (spatial average of absolute bias: 21 ∘C) due to the biases driven by relative humidity (20 ∘C). Biases in WBGT (1.1 ∘C) are small compared to the biases driven by temperature (1.9 ∘C) and relative humidity (1.4 ∘C), as the two biases compensate for each other. In many regions, also biases related to the statistical dependence (0.85 ∘C) are important for WBGT, which indicates that well-designed physically based multivariate bias adjustment procedures should be considered for hazards and impacts that depend on multiple drivers. The proposed compound-event-oriented evaluation of climate model biases is easily applicable to other hazard types. Furthermore, it can contribute to improved present and future risk assessments through increasing our understanding of the biases' sources in the simulation of climate impacts.

Probabilistic seasonal forecasts are important for many water-intensive activities requiring long-term planning. Among the different techniques used for seasonal forecasting, the ensemble streamflow prediction (ESP) approach has long been employed due to the singular dependence on past meteorological records. The Swedish Meteorological and Hydrological Institute is currently extending the use of long-range forecasts within its operational warning service, which requires a thorough analysis of the suitability and applicability of different methods with the national S-HYPE hydrological model. To this end, we aim to evaluate the skill of ESP forecasts over 39 493 catchments in Sweden, understand their spatio-temporal patterns, and explore the main hydrological processes driving forecast skill. We found that ESP forecasts are generally skilful for most of the country up to 3 months into the future but that large spatio-temporal variations exist. Forecasts are most skilful during the winter months in northern Sweden, except for the highly regulated hydropower-producing rivers. The relationships between forecast skill and 15 different hydrological signatures show that forecasts are most skilful for slow-reacting, baseflow-dominated catchments and least skilful for flashy catchments. Finally, we show that forecast skill patterns can be spatially clustered in seven unique regions with similar hydrological behaviour. Overall, these results contribute to identifying in which areas and seasons and how long into the future ESP hydrological forecasts provide an added value, not only for the national forecasting and warning service, but also, most importantly, for guiding decision-making in critical services such as hydropower management and risk reduction.

Recent improvements in initialization procedures and representation of large-scale hydrometeorological processes have contributed to advancing the accuracy of hydroclimatic forecasts, which are progressively more skillful over seasonal and longer timescales. These forecasts are potentially valuable for informing strategic multisector decisions, including irrigated agriculture, for which they can improve crop choices and irrigation scheduling. In this operational context, the accuracy associated with the forecast system setup does not necessarily yield proportional marginal benefit, as this is also affected by how forecasts are employed by end users. This paper aims at quantifying the value of hydroclimatic forecasts in terms of potential economic benefit to the end users, which allows for the inference of a relation between gains in forecast skill and gains in end user profit. We also explore the sensitivity of this benefit to both forecast system setup and end user behavioral factors. These analyses are supported by an evaluation framework demonstrated on the Lake Como system (Italy), a regulated lake operated for flood protection and irrigation supply. Our framework relies on an integrated modeling chain composed of three building blocks: bias-adjusted seasonal meteorological forecasts are used as input to the continentally calibrated E-HYPE hydrological model; predicted lake inflows are used for conditioning the daily lake operations; and the resulting lake releases feed an agricultural model to estimate the net profit of the farmers in a downstream irrigation district. Results suggest that despite the gain in average conditions being negligible, informing the operations of Lake Como based on seasonal hydrological forecasts during intense drought episodes allows about 15 % of the farmers' profit to be gained with respect to a baseline solution not informed by any forecast. Moreover, our analysis suggests that behavioral factors capturing different perceptions of risk and uncertainty significantly impact the quantification of the benefit to the end users, whereby the estimated forecast value is potentially undermined by different levels of end user risk aversion. Lastly, our results show an intricate skill-to-value relation modulated by the underlying hydrologic conditions, which is well aligned over an exponential function in dry years, while the gains in profit are almost insensitive to the improvements in forecast skill in wet years.

We present a single-electron device for the manipulation of charge states via quantum interference in nanostructured electrodes. Via self-inductance effects, we induce two independent magnetic fluxes in the electrodes and we demonstrate sensitivity to single charge states and magnetic field at variable temperature. Moreover, our approach allows us to demonstrate local and independent control of the single-particle conductance between nano-engineered tunnel junctions in a fully superconducting quantum interference single-electron transistor, thereby increasing the flexibility of our single-electron transistors. Our devices show a robust modulation of the current-to-flux transfer function via control currents while exploiting the single-electron filling of a mesoscopic superconducting island. Further applications of the device concept to single charge manipulation and magnetic-flux sensing are also discussed.

Recent advancements in catchment hydrology (such as understanding catchment similarity, accessing new data sources, and refining methods for parameter constraints) make it possible to apply catchment models for ungauged basins over large domains. Here we present a cutting-edge case study applying catchment-modelling techniques with evaluation against river flow at the global scale for the first time. The modelling procedure was challenging but doable, and even the first model version showed better performance than traditional gridded global models of river flow. We used the open-source code of the HYPE model and applied it for >130 000 catchments (with an average resolution of 1000 km2), delineated to cover the Earth's landmass (except Antarctica). The catchments were characterized using 20 open databases on physiographical variables, to account for spatial and temporal variability of the global freshwater resources, based on exchange with the atmosphere (e.g. precipitation and evapotranspiration) and related budgets in all compartments of the land (e.g. soil, rivers, lakes, glaciers, and floodplains), including water stocks, residence times, and the pathways between various compartments. Global parameter values were estimated using a stepwise approach for groups of parameters regulating specific processes and catchment characteristics in representative gauged catchments. Daily and monthly time series (>10 years) from 5338 gauges of river flow across the globe were used for model evaluation (half for calibration and half for independent validation), resulting in a median monthly KGE of 0.4. However, the World-Wide HYPE (WWH) model shows large variation in model performance, both between geographical domains and between various flow signatures. The model performs best (KGE >0.6) in the eastern USA, Europe, South-East Asia, and Japan, as well as in parts of Russia, Canada, and South America. The model shows overall good potential to capture flow signatures of monthly high flows, spatial variability of high flows, duration of low flows, and constancy of daily flow. Nevertheless, there remains large potential for model improvements, and we suggest both redoing the parameter estimation and reconsidering parts of the model structure for the next WWH version. This first model version clearly indicates challenges in large-scale modelling, usefulness of open data, and current gaps in process understanding. However, we also found that catchment modelling techniques can contribute to advance global hydrological predictions. Setting up a global catchment model has to be a long-term commitment as it demands many iterations; this paper shows a first version, which will be subjected to continuous model refinements in the future. WWH is currently shared with regional/local modellers to appreciate local knowledge.

In recent years, several forensic laboratories have noted an increase in the number of sexual assault cases submitted for testing, often leading to longer turnaround times. In that context, forensic laboratories may be interested in reviewing their procedures to increase productivity. Here, we present two different strategies that were put in place in our laboratory. First, we changed the way sexual assault evidence kits (SAEK) are processed by implementing an optimized workflow that prioritizes the internal samples (vaginal, anal, and oral). This new procedure allowed for a drastic decrease in turnaround time, while maintaining a similar investigative power.Secondly, we used data from casework to target cases and samples that were likely to yield biological material from the perpetrator, in an attempt to avoid dedicating time and effort to cases for which there is a very low probability of obtaining foreign DNA evidence. Among other things, we looked at the likelihood of obtaining DNA from the perpetrator when the complainant reported the use of a condom, has showered after the assault or when the complainant has no memory of the assault. Results show that those circumstances do not dramatically decrease the probability of finding DNA from the perpetrator.

Abstract Background Intubation is a lifesaving procedure that is often performed in intensive care unit (ICU) patients, but leads to serious adverse events in 20–40% of cases. Recent trials aimed to provide guidance about which medications, devices, and modalities maximize patient safety. Videolaryngoscopes are being offered in an increasing range of options and used in broadening indications (from difficult to unremarkable intubation). The objective of this study was to describe intubation practices and device availability in French ICUs. Materials and methods We conducted an online nationwide survey by emailing an anonymous 26-item questionnaire to physicians in French ICUs. A single questionnaire was sent to either the head or the intubation expert at each ICU. Results Of 257 ICUs, 180 (70%) returned the completed questionnaire. The results showed that 43% of intubators were not fully proficient in intubation; among them, 18.8% had no intubation training or had received only basic training (lectures and observation at the bedside). Among the participating ICUs, 94.4% had a difficult intubation trolley, 74.5% an intubation protocol, 92.2% a capnography device (used routinely to check tube position in 69.3% of ICUs having the device), 91.6% a laryngeal mask, 97.2% front-of-neck access capabilities, and 76.6% a videolaryngoscope. In case of difficult intubation, 85.6% of ICUs used a bougie (154/180) and 7.8% switched to a videolaryngoscope (14/180). Use of a videolaryngoscope was reserved for difficult intubation in 84% of ICUs (154/180). Having a videolaryngoscope was significantly associated with having an intubation protocol (P = 0.043) and using capnography (P = 0.02). Airtraq® was the most often used videolaryngoscope (39.3%), followed by McGrath®Mac (36.9%) then by Glidescope® (14.5%). Conclusion Nearly half the intubators in French ICUs are not fully proficient with OTI. Access to modern training methods such as simulation is inadequate. Most ICUs own a videolaryngoscope, but reserve it for difficult intubations.

Neogene deposits of the lower Colorado River valley, especially the Miocene(?) and early Pliocene Bouse Formation, have been the focus of intense debate regarding the early paleoenvironmental history of this important continental-scale river system in southwestern North America and its integration with the proto-Gulf of California. Fine-grained units within these Neogene deposits also hold a promising archive of Pliocene paleoclimate history for this part of the world. Because the depocenter deposits of the Bouse Formation and the deposits that overlie and underlie it are poorly exposed and highly weathered, the formation is ripe for study through collection of drill cores. A workshop was held 28 February–3 March 2019 in Parker, AZ, USA, to discuss how scientific drilling might be employed to help resolve the Bouse controversies and improve our understanding of paleoclimate history in the region.

Objectives: Type 2 diabetes (T2D) is associated with chronic, low grade inflammation. Activation of the NLRP3 inflammasome and secretion of its target interleukin-1β (IL-1β) have been implicated in pancreatic β cell failure in T2D. Specific targeting of the NLRP3 inflammasome to prevent pancreatic β cell death could allow for selective T2D treatment without compromising all IL-1β-associated immune responses. We hypothesized that treating a mouse model of T2D with MCC950, a compound that specifically inhibits NLRP3, would prevent pancreatic β cell death, thereby preventing the onset of T2D. Methods: Diabetic db/db mice were treated with MCC950 via drinking water for 8 weeks from 6 to 14 weeks of age, a period over which they developed pancreatic β cell failure. We assessed metabolic parameters such as body composition, glucose tolerance, or insulin secretion over the course of the intervention. Results: MCC950 was a potent inhibitor of NLRP3-induced IL-1β in vitro and was detected at high levels in the plasma of treated db/db mice. Treatment of pre-diabetic db/db mice with MCC950, however, did not prevent pancreatic dysfunction and full onset of the T2D pathology. When examining the NLRP3 pathway in the pancreas of db/db mice, we could not detect an activation of this pathway nor increased levels of its target IL-1β. Conclusions: NLRP3 driven-pancreatic IL-1β inflammation does not play a key role in the pathogenesis of the db/db murine model of T2D. Keywords: Type 2 diabetes, Inflammasome, Interleukin-1β, MCC950, db/db mice

The Southern Ocean is experiencing rapid and relentless change in its physical and biogeochemical properties. The rate of warming of the Antarctic Circumpolar Current exceeds that of the global ocean, and the enhanced uptake of carbon dioxide is causing basin-wide ocean acidification. Observational data suggest that these changes are influencing the distribution and composition of pelagic plankton communities. Long-term and annual field observations on key environmental variables and organisms are a critical basis for predicting changes in Southern Ocean ecosystems. These observations are particularly needed, since high-latitude systems have been projected to experience the most severe impacts of ocean acidification and invasions of allochthonous species. Coccolithophores are the most prolific calcium-carbonate-producing phytoplankton group playing an important role in Southern Ocean biogeochemical cycles. Satellite imagery has revealed elevated particulate inorganic carbon concentrations near the major circumpolar fronts of the Southern Ocean that can be attributed to the coccolithophore Emiliania huxleyi. Recent studies have suggested changes during the last decades in the distribution and abundance of Southern Ocean coccolithophores. However, due to limited field observations, the distribution, diversity and state of coccolithophore populations in the Southern Ocean remain poorly characterised. We report here on seasonal variations in the abundance and composition of coccolithophore assemblages collected by two moored sediment traps deployed at the Antarctic zone south of Australia (2000 and 3700 m of depth) for 1 year in 2001–2002. Additionally, seasonal changes in coccolith weights of E. huxleyi populations were estimated using circularly polarised micrographs analysed with C-Calcita software. Our findings indicate that (1) coccolithophore sinking assemblages were nearly monospecific for E. huxleyi morphotype B/C in the Antarctic zone waters in 2001–2002; (2) coccoliths captured by the traps experienced weight and length reduction during summer (December–February); (3) the estimated annual coccolith weight of E. huxleyi at both sediment traps (2.11 ± 0.96 and 2.13 ± 0.91 pg at 2000 and 3700 m) was consistent with previous studies for morphotype B/C in other Southern Ocean settings (Scotia Sea and Patagonian shelf); and (4) coccolithophores accounted for approximately 2–5 % of the annual deep-ocean CaCO3 flux. Our results are the first annual record of coccolithophore abundance, composition and degree of calcification in the Antarctic zone. They provide a baseline against which to monitor coccolithophore responses to changes in the environmental conditions expected for this region in coming decades.

Coupling compartmentalisation and molecular replication is essential for the development of evolving chemical systems. Here the authors show an oil-in-water droplet containing a self-replicating amphiphilic imine that can undergo repeated droplet division.

Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.

Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful, which has the potential to benefit streamflow forecasting. Seasonal streamflow forecasts can help to take anticipatory measures for a range of applications, such as water supply or hydropower reservoir operation and drought risk management. This study assesses the skill of seasonal precipitation and streamflow forecasts in France to provide insights into the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. We apply eight variants of bias correction approaches to the precipitation forecasts prior to generating the streamflow forecasts. The approaches are based on the linear scaling and the distribution mapping methods. A daily hydrological model is applied at the catchment scale to transform precipitation into streamflow. We then evaluate the skill of raw (without bias correction) and bias-corrected precipitation and streamflow ensemble forecasts in 16 catchments in France. The skill of the ensemble forecasts is assessed in reliability, sharpness, accuracy and overall performance. A reference prediction system, based on historical observed precipitation and catchment initial conditions at the time of forecast (i.e. ESP method) is used as benchmark in the computation of the skill. The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are often more skilful than the conventional ESP method in terms of sharpness. However, they are not significantly better in terms of reliability. Forecast skill is generally improved when applying bias correction. Two bias correction methods show the best performance for the studied catchments, each method being more successful in improving specific attributes of the forecasts: the simple linear scaling of monthly values contributes mainly to increasing forecast sharpness and accuracy, while the empirical distribution mapping of daily values is successful in improving forecast reliability.

Bronchiolitis obliterans syndrome (BOS), the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group), and 26 samples at or after BOS diagnosis (diagnosis group). An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group). We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1), T-cell leukemia/lymphoma protein 1A (TCL1A), and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p

Measurement of sediment deposition and erosion in coastal areas is a challenge due to soft shifting sediments, but is critical to assessing loss or restoration of coastal sediments and wetlands. The aim of this project was to design and construct a semi-autonomous boat with water depth measuring capabilities. It was intended to map the depth of coastal wetlands to determine erosion rates and assess coastal restoration effects. Depth-measuring equipment was incorporated into an autonomous pontoon boat powered by solar panels. The propulsion system consisted of two paddlewheels and two-way motors to allow movement and positioning for measurements. Modifications included a lightweight, hard coating on the pontoons and powder-coating the frame to extend their usable life. A microcontroller controlled the boat and captured depth data from sensors and location data with a GPS system. The depth measuring system consisted of a pulley and counter system that completed each measurement in less than 45 seconds. This allowed the boat to take approximately 400 measurements per day. Net accuracy was approximately 3 cm in the tested configuration. The boat can continually measure the depth of specified areas in the wetlands; with this data, the change in depth can be monitored to see the effects of restoration projects.

Ankle sprains are reportedly the most common lower limb injury amongst active individuals.

No abstract available.

Shellfish are recognized as a potential vehicle of viral diseases. However, according to European Regulations, only bacteriological parameters (Salmonella and E. coli) are used to establish their microbiological quality. Because of the lack of a standard reference method for the detection of viruses, data on the incidence of enteric viruses in European production areas are still limited. Aim of the present study was the evaluation of the Norovirus (NoV) contamination in shellfish from different harvesting areas (both class A and B) and from registered and not- registered retails of the Campania region (Tyrrhenian Sea, Italy). Seventy shellfish (Mytilus galloprovincialis) were collected from 15 harvesting areas, one authorized and two not authorized retails and were examined for virus presence (NoV genogroups I and II) by Real Time PCR. Ten harvesting areas (66%) showed presence of viral contamination, with three of them belonging to A areas and seven to B areas. The shellfish collected from the registered retail tested positive for Norovirus presence, whereas the shellfish collected from not-authorized retails didn’t show viral contamination. Twenty-nine samples were positive for genogroup II, ten of which tested positive also for NoV genogroup I.

To date no studies have been published on preoperative education for patients who had lumbar surgery. The aim of this study was to determine if there is a demand for preoperative education for patients who had lumbar surgery for radiculopathy. A convenience sample of 47 patients who had lumbar surgery and a random sample of 141 physiotherapists involved in treating patients who had lumbar surgery completed a newly developed spinal surgery questionnaire. The data were analyzed using descriptiveand inferential statistical tests. Results showed that 100% of the patients and 99% of therapists view preoperative education to be an important component for lumbar surgery for radiculopathy. The most important factors identified for inclusion in preoperative educational programs were reason for surgery, risks associated with surgery, limitations following surgery and more education regarding pain. The preferred method of education delivery was verbal one-on-one education. This study demonstrates that there is a demand for preoperative education for patients who had lumbar surgery.

In the recent years, structural monitoring of large infrastructures (buildings, dams, bridges) or more generally man-made structures has raised an increased attention due to the growing interest about safety and security issues and risk assessment through early detection. In this framework, aim of the paper is to introduce a new integrated approach which combines two sensing techniques acting on different spatial and temporal scales. The first one is a distributed optic fiber sensor based on the Brillouin scattering phenomenon, which allows a spatially and temporally continuous monitoring of the structure with a "low" spatial resolution (meter). The second technique is based on the use of Ground Penetrating Radar (GPR), which can provide detailed images of the inner status of the structure (with a spatial resolution less then tens centimetres), but does not allow a temporal continuous monitoring. The paper describes the features of these two techniques and provides experimental results concerning preliminary test cases.

In many applications of microwave imaging, there is the need of confining the device in order to shield it from environmental noise as well as to host the targets and the medium used for impedance matching purposes. For instance, in MWI for biomedical diagnostics a coupling medium is typically adopted to improve the penetration of the probing wave into the tissues. From the point of view of quantitative imaging procedures, that is aimed at retrieving the values of the complex permittivity in the domain under test, the presence of a confining structure entails an increase of complexity of the underlying modelling. This entails a further difficulty in achieving real-time imaging results, which are obviously of interest in practice. To address this challenge, we propose the application of a recently proposed inversion method that, making use of a suitable preprocessing of the data and a scenario-oriented field approximation, allows obtaining quantitative imaging results by means of quasi-real-time linear inversion, in a range of cases which is much broader than usual linearized approximations. The assessment of the method is carried out in the scalar 2D configuration and taking into account enclosures of different shapes and, to show the method’s flexibility different shapes, embedding nonweak targets.

We present a case of arrhythmogenic cardiomyopathy with biventricular involvement and strong arrhythmic substrate, highlighting the need to consider more than a single diagnostic option when facing arrhythmic presentations in young patients and the growing contribution provided by the genetic laboratory and contrast CMR to clinical management.

This paper deals with the possibility of adopting microwave imaging to continuously monitor a patient after the onset of a brain stroke, with the aim to follow the evolution of the disease, promptly counteract its uncontrolled growth, and possibly support decisions in the clinical treatment. In such a framework, the assessed techniques for brain stroke diagnosis are indeed not suitable to pursue this goal. Conversely, microwave imaging can provide a diagnostic tool able to follow up the disease’s evolution, while relying on a relatively low cost and portable apparatus. The proposed imaging procedure is based on a differential approach which requires the processing of scattered field data measured at different time instants. By means of a numerical analysis dealing with synthetic data generated for realistic anthropomorphic phantoms, we address some crucial issues for the method’s effectiveness. In particular, we discuss the role of patient-specific information and the effect of inaccuracies in the measurement procedure, such as an incorrect positioning of the probes between two different examinations. The observed results show that the proposed technique is indeed feasible, even when a simple, nonspecific model of the head is exploited and is robust against the above mentioned inaccuracies.

This works examines the influence of mating on ovarian follicle development in Triatoma infestans. The observations were carried out on both virgin and mated females, wich were killed at various times after their emergence. There was no difference in the ovarian development of both experimental groups during the first gonadotrofic cycle. By the 7th day mated females as well as virgn females showed vitellogenic oocytes. The coriogenesis and ovulation process began on the 13th day after imaginal moulting. However we could observe that egg-laying was dependent on mating. Mated females laid eggs whereas virgin females did not lay eggs. However ovarian production was significantly greater in the mated females. It is suggested that in T. infestans mating stimulates egg-laying but it does not influence the oogenesis and ovulation process.