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Abstract Objective The maturation of neural network-based techniques in combination with the availability of large sleep datasets has increased the interest in alternative methods of sleep monitoring. For unobtrusive sleep staging, the most promising algorithms are based on heart rate variability computed from inter-beat intervals (IBIs) derived from ECG-data. The practical application of these algorithms is even more promising when alternative ways of obtaining IBIs, such as wrist-worn photoplethysmography (PPG) can be used. However, studies validating sleep staging algorithms directly on PPG-based data are limited. Results We applied an automatic sleep staging algorithm trained and validated on ECG-data directly on inter-beat intervals derived from a wrist-worn PPG sensor, in 389 polysomnographic recordings of patients with a variety of sleep disorders. While the algorithm reached moderate agreement with gold standard polysomnography, the performance was significantly lower when applied on PPG- versus ECG-derived heart rate variability data (kappa 0.56 versus 0.60, p

Long-term, reliable datasets of satellite-based vegetation condition are essential for understanding terrestrial ecosystem responses to global environmental change, particularly in Australia, which is characterised by diverse ecosystems and strong interannual climate variability. We comprehensively evaluate several existing global Advanced Very High Resolution Radiometer (AVHRR) normalised-difference vegetation index (NDVI) products for their suitability for long-term vegetation monitoring in Australia. Comparisons with the MODIS NDVI highlight significant deficiencies, particularly over densely vegetated regions. Moreover, all the assessed products failed to adequately reproduce the interannual variability in the pre-MODIS era as indicated by Landsat NDVI anomalies. To address these limitations, we propose a new approach to calibrating and harmonising NOAA's Climate Data Record of AVHRR NDVI to the MODIS MCD43A4 NDVI for Australia using a gradient-boosting decision tree ensemble method. Two versions of the datasets are developed, one incorporating climate data in the predictors (“AusENDVI-clim”: Australian Empirical NDVI-climate) and another that is independent of climate data (“AusENDVI-noclim”). These datasets, spanning 1982–2013 at a spatial resolution of 0.05° and with a monthly time step, exhibit strong correlations (r2=0.89–0.94) and low mean errors compared with MODIS MCD43A4 NDVI (mean absolute error (MAE) = 0.014–0.028, RMSE = 0.021–0.046), accurately reproducing seasonal cycles over densely vegetated regions. Furthermore, they closely replicate the interannual variability in vegetation condition in the pre-MODIS era. A reliable method for gap-filling the AusENDVI record is also developed that leverages climate, atmospheric CO2 concentration, and woody-cover fraction predictors. The resulting synthetic NDVI dataset shows excellent agreement with the MODIS MCD43A4 NDVI and the recalibrated AVHRR NDVI time series (r2=0.82–0.95, MAE = 0.016–0.029, RMSE = 0.039–0.041). Finally, we provide a complete 41-year dataset where the gap-filled AusENDVI-clim from January 1982 to February 2000 is joined with the MODIS MCD43A4 NDVI from March 2000 to December 2022. Analysing 40-year per-pixel trends in Australia's annual maximum NDVI revealed increasing values, and shifts in the timing, of the annual peak NDVI across most of the continent, underscoring the dataset's potential to address crucial questions regarding the changing vegetation phenology and its drivers. The AusENDVI dataset can be used for studying Australia's changing vegetation dynamics and downstream impacts on the terrestrial carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change. AusENDVI is open access and available at https://doi.org/10.5281/zenodo.10802703 (Burton et al., 2024).

Abstract Understanding climate variability across interannual to centennial timescales is critical, as it encompasses the natural range of climate fluctuations that early human agricultural societies had to adapt to. Deviations from the long-term mean climate are often associated with both societal collapse and periods of prosperity and expansion. Here, we show that contrary to what global paleoproxy reconstructions suggest, the mid to late-Holocene was not a period of climate stability. We use mid- to late-Holocene Earth System Model simulations, forced by state-of-the-art reconstructions of external climate forcing to show that eleven long-lasting cold periods occurred in the Northern Hemisphere during the past 8000 years. These periods correlate with enhanced volcanic activity, where the clustering of volcanic eruptions induced a prolonged cooling effect through gradual ocean-sea ice feedback. These findings challenge the prevailing notion of the Holocene as a period characterized by climate stability, as portrayed in multi-proxy climate reconstructions. Instead, our simulations provide an improved representation of amplitude and timing of temperature variations on sub-centennial timescales.

The 2015–2016 Amazon drought was characterized by below-average regional precipitation for an entire year, which distinguishes it from the dry-season-only droughts in 2005 and 2010. Studies of vegetation indices (VIs) derived from optical remote sensing over the Amazonian forests indicated three stages in canopy response during the 2015–2016 drought, with below-average greenness during the onset and end of the drought, and above-average greenness during the intervening months. To date, a satisfactory explanation for this broad temporal pattern has not been found. A better understanding of rainforest behaviors during this unusually long drought should help predict their response to future droughts. We hypothesized that negative VI anomalies could be caused by water and heat stress exceeding the tolerance ranges of the rainforest. To test our hypothesis, based on monthly observations of terrestrial water storage (TWS), land surface temperature (LST), and vapor pressure deficit (VPD) for January 2003 to December 2016, we proposed an approach to categorize regions into two groups: (1) those exceeding normal hydrological and thermal ranges and (2) those within normal ranges. Accordingly, regions exceeding normal ranges during different stages of the 2015–2016 event were delineated. The results showed a gradual southward shift in these regions: from the northeastern Amazon during August to October 2015 to the north–central part during November 2015 to February 2016 and finally to the southern Amazon in July 2016. Over these regions exceeding normal ranges during droughts, negative VI anomalies were expected, irrespective of radiation anomalies. Over the regions within normal ranges, VI anomalies were assumed to respond positively to radiation anomalies, as is expected under normal conditions. We found that our proposed approach can explain more than 70 % of the observed spatiotemporal patterns in VI anomalies during the 2015–2016 drought. These results suggest that our “exceeding normal ranges”-based approach combining (i) water storage, (ii) temperature, and (iii) atmospheric moisture demand drivers can reasonably identify the most likely drought-affected regions at monthly to seasonal timescales. Using observation-based hydrological and thermal condition thresholds can help with interpreting the response of the Amazon rainforest to future drought events.

Measuring the spatiotemporal dynamics of lake and reservoir water storage is fundamental for assessing the influence of climate variability and anthropogenic activities on water quantity and quality. Previous studies estimated relative water volume changes for lakes where both satellite-derived extent and radar altimetry data are available. This approach is limited to only a few hundred lakes worldwide and cannot estimate absolute (i.e. total volume) water storage. We increased the number of measured lakes by a factor of 300 by using high-resolution Landsat and Sentinel-2 optical remote sensing and ICESat-2 laser altimetry, in addition to radar altimetry from the Topex/Poseidon; Jason-1, Jason-2 and Jason-3; and Sentinel-3 and Sentinel-6 instruments. Historical time series (1984–2020) of water storage could be derived for more than 170 000 lakes globally with a surface area of at least 1 km2, representing 99 % of the total volume of all water stored in lakes and reservoirs globally. Specifically, absolute lake volumes are estimated based on topographic characteristics and lake properties that can be observed by remote sensing. In addition to that, we also generated relative lake volume changes solely based on satellite-derived heights and extents if both were available. Within this dataset, we investigated how many lakes can be measured in near real time (2020–current) in basins worldwide. We developed an automated workflow for near-real-time global lake monitoring of more than 27 000 lakes. The GloLakes historical and near-real-time lake storage dynamics data from 1984 to current are publicly available through https://doi.org/10.25914/K8ZF-6G46 (Hou et al., 2022c) and a web-based data explorer (http://www.globalwater.online, last access: 12 December 2023).

A novel concept is described concerning the possible effect of right ventricular pacing stimulation being detected by the cardiac autonomic nervous system and through its afferent neuronal connection to the central autonomic nervous system (spinal cord) causing reversal or attenuation of the vasovagal reflex. This could be a direct effect of electrical stimulation or may occur by the known adverse consequences on ventricular synchrony induced by stimulation which could be right ventricular site and timing in the evolution of the vasovagal reflex dependent.

Abstract We introduce Version 2 of our widely used 1-km Köppen-Geiger climate classification maps for historical and future climate conditions. The historical maps (encompassing 1901–1930, 1931–1960, 1961–1990, and 1991–2020) are based on high-resolution, observation-based climatologies, while the future maps (encompassing 2041–2070 and 2071–2099) are based on downscaled and bias-corrected climate projections for seven shared socio-economic pathways (SSPs). We evaluated 67 climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and kept a subset of 42 with the most plausible CO2-induced warming rates. We estimate that from 1901–1930 to 1991–2020, approximately 5% of the global land surface (excluding Antarctica) transitioned to a different major Köppen-Geiger class. Furthermore, we project that from 1991–2020 to 2071–2099, 5% of the land surface will transition to a different major class under the low-emissions SSP1-2.6 scenario, 8% under the middle-of-the-road SSP2-4.5 scenario, and 13% under the high-emissions SSP5-8.5 scenario. The Köppen-Geiger maps, along with associated confidence estimates, underlying monthly air temperature and precipitation data, and sensitivity metrics for the CMIP6 models, can be accessed at www.gloh2o.org/koppen .

We develop high-resolution (1 km) estimates of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) over the Australian continent for the period January 2003 to June 2022 by empirical upscaling of flux tower measurements. We compare our estimates with nine other products that cover the three broad categories that define current methods for estimating the terrestrial carbon cycle and assess if consiliences between datasets can point to the correct dynamics of Australia's carbon cycle. Our results indicate that regional empirical upscaling greatly improves upon the existing global empirical upscaling efforts, outperforms process-based models, and agrees much better with the dynamics of CO2 flux over Australia as estimated by two regional atmospheric inversions. Our nearly 20-year estimates of terrestrial carbon fluxes revealed that Australia is a strong net carbon sink of −0.44 PgC yr−1 (interquartile range, IQR = 0.42 PgC yr−1) on average, with an inter-annual variability of 0.18 PgC yr−1 and an average seasonal amplitude of 0.85 PgC yr−1. Annual mean carbon uptake estimated from other methods ranged considerably, while carbon flux anomalies showed much better agreement between methods. NEE anomalies were predominately driven by cumulative rainfall deficits and surpluses, resulting in larger anomalous responses from GPP than ER. In contrast, we show that the long-term average seasonal cycle is dictated more by the variability in ER than GPP, resulting in peak carbon uptake typically occurring during the cooler, drier austral autumn and winter months. This new estimate of Australia's terrestrial carbon cycle provides a benchmark for assessment against land surface model simulations and a means for monitoring of Australia's terrestrial carbon cycle at an unprecedented high resolution. We call this new estimate of Australia's terrestrial carbon cycle “AusEFlux” (Australian Empirical Fluxes).

Abstract Background Syncope management is fraught with unnecessary tests and frequent failure to establish a diagnosis. We evaluated the potential of implementing the 2018 European Society of Cardiology (ESC) Syncope Guidelines regarding diagnostic yield, accuracy and costs. Methods A multicentre pre-post study in five Dutch hospitals comparing two groups of syncope patients visiting the emergency department: one before intervention (usual care; from March 2017 to February 2019) and one afterwards (from October 2017 to September 2019). The intervention consisted of the simultaneous implementation of the ESC Syncope Guidelines with quick referral routes to a syncope unit when indicated. The primary objective was to compare diagnostic accuracy using logistic regression analysis accounting for the study site. Secondary outcome measures included diagnostic yield, syncope-related healthcare and societal costs. One-year follow-up data were used to define a gold standard reference diagnosis by applying ESC criteria or, if not possible, evaluation by an expert committee. We determined the accuracy by comparing the treating physician’s diagnosis with the reference diagnosis. Results We included 521 patients (usual care, n = 275; syncope guidelines intervention, n = 246). The syncope guidelines intervention resulted in a higher diagnostic accuracy in the syncope guidelines group than in the usual care group (86% vs.69%; risk ratio 1.15; 95% CI 1.07 to 1.23) and a higher diagnostic yield (89% vs. 76%, 95% CI of the difference 6 to 19%). Syncope-related healthcare costs did not differ between the groups, yet the syncope guideline implementation resulted in lower total syncope-related societal costs compared to usual care (saving €908 per patient; 95% CI €34 to €1782). Conclusions ESC Syncope Guidelines implementation in the emergency department with quick referral routes to a syncope unit improved diagnostic yield and accuracy and lowered societal costs. Trial registration Netherlands Trial Register, NTR6268

Abstract Background The Observable Movement Quality scale for patients with low back pain (OMQ-LBP) is a newly developed measurement instrument for use in primary care settings of physical and exercise therapists to assess movement quality (MQ) of patients with low back pain (LBP). Objective This study aims to determine validity, reliability and feasibility of the OMQ-LBP. The OMQ-LBP consists of a standardized movement circuit (performed twice) consisting of five daily activities problematic for LBP patients, which are scored with an 11-item observation list. Methods Construct validity was determined by testing seven hypotheses on associations between constructs (n = 85 patients with LBP) and four hypotheses on known group differences (n = 85 patients with LBP and n = 63 healthy controls; n = 35 matched participant-patients having VAS-pain ≥ 20 mm during and/or after both circuits and healthy controls). Internal consistency was analyzed with Cronbach’s alpha (n = 85 patients with LBP). For inter- and intra-rater reliability Intraclass Correlation Coefficient (ICC) values were examined (n = 14 therapists: seven primary care physical therapists and seven exercise therapists). Additionally, content validity and feasibility were determined using thematic analysis of a brief interview with participants, patients (n = 38) and therapists (n = 14). Results After Bonferroni correction 2/7 associations between constructs and 2/4 significant group differences were confirmed. Cronbach’s alpha was 0,79. The ICC-values of interrater reliability of the OMQ-LBP total score and the duration score were 0.56 and 0.99 and intra-rater reliability 0.82 and 0,93, respectively. Thematic analysis revealed five themes. Three themes elucidate that both patients and therapists perceived the content of the OMQ-LBP as valid. The fourth theme exhibits that OMQ-LBP provides a clear and unambiguous language for MQ in patients with LBP. Theme 5 depicts that the OMQ-LBP seems feasible, but video recording is time-consuming. Conclusions The OMQ-LBP is a promising standardized observational assessment of MQ during the five most problematic daily activities in patients with LBP. It is expected that uniform and objective description and evaluation of MQ add value to clinical reasoning and facilitate uniform communication with patients and colleagues.

Introduction Acute mesenteric ischaemia (AMI) is a life-threatening condition with short-term mortality of up to 80%. The diagnosis of AMI has remained troublesome due to the non-specific clinical presentation, symptoms and laboratory findings. Early unambiguous diagnosis of AMI is critical to prevent progression from reversible to irreversible transmural intestinal damage, thereby decreasing morbidity and improving survival. The present study aims to validate a panel of plasma biomarkers and investigate volatile organic compound (VOC) profiles in exhaled air as a tool to timely and accurately diagnose AMI.Methods and analysis In this international multicentre prospective observational study, 120 patients (>18 years of age) will be recruited with clinical suspicion of AMI. Clinical suspicion is based on: (1) clinical manifestation, (2) physical examination, (3) laboratory measurements and (4) the physician’s consideration to perform a CT scan. The patient’s characteristics, repetitive blood samples and exhaled air will be prospectively collected. Plasma levels of mucosal damage markers intestinal fatty acid-binding protein and villin-1, as well as transmural damage marker smooth muscle protein 22-alpha, will be assessed by ELISA. Analysis of VOCs in exhaled air will be performed by gas chromatography time-of-flight mass spectrometry. Diagnosis of AMI will be based on CT, endovascular and surgical reports, clinical findings, and (if applicable) verified by histopathological examination.Ethics and dissemination The study protocol was approved by the Medical Research Ethics Committee (METC) of Maastricht University Medical Centre+ and Maastricht University (METC azM/UM), the Netherlands (METC19-010) and the Ethics Committee Research UZ/KU Leuven, Belgium (S63500). Executive boards and local METCs of other Dutch participating centres Gelre Ziekenhuizen (Apeldoorn), Medisch Spectrum Twente (Enschede), and University Medical Centre Groningen have granted permission to carry out this study. Study results will be disseminated via open-access peer-reviewed scientific journals and national/international conferences.Trial registration number NCT05194527.

Rainfall interception loss remains one of the most uncertain fluxes in the global water balance, hindering water management in forested regions and precluding an accurate formulation in climate models. Here, a synthesis of interception loss data from past field experiments conducted worldwide is performed, resulting in a meta-analysis comprising 166 forest sites and 17 agricultural plots. This meta-analysis is used to constrain a global process-based model driven by satellite-observed vegetation dynamics, potential evaporation and precipitation. The model considers sub-grid heterogeneity and vegetation dynamics and formulates rainfall interception for tall and short vegetation separately. A global, 40-year (1980–2019), 0.1∘ spatial resolution, daily temporal resolution dataset is created, analysed and validated against in situ data. The validation shows a good consistency between the modelled interception and field observations over tall vegetation, both in terms of correlations and bias. While an underestimation is found in short vegetation, the degree to which it responds to in situ representativeness errors and difficulties inherent to the measurement of interception in short vegetated ecosystems is unclear. Global estimates are compared to existing datasets, showing overall comparable patterns. According to our findings, global interception averages to 73.81 mm yr−1 or 10.96 × 103 km3 yr−1, accounting for 10.53 % of continental rainfall and approximately 14.06 % of terrestrial evaporation. The seasonal variability of interception follows the annual cycle of canopy cover, precipitation, and atmospheric demand for water. Tropical rainforests show low intra-annual vegetation variability, and seasonal patterns are dictated by rainfall. Interception shows a strong variance among vegetation types and biomes, supported by both the modelling and the meta-analysis of field data. The global synthesis of field observations and the new global interception dataset will serve as a benchmark for future investigations and facilitate large-scale hydrological and climate research.

Many thousands of large dam reservoirs have been constructed worldwide during the last 70 years to increase reliable water supplies and support economic growth. Because reservoir storage measurements are generally not publicly available, so far there has been no global assessment of long-term dynamic changes in reservoir water volumes. We overcame this by using optical (Landsat) and altimetry remote sensing to reconstruct monthly water storage for 6695 reservoirs worldwide between 1984 and 2015. We relate reservoir storage to resilience and vulnerability and investigate interactions between precipitation, streamflow, evaporation, and reservoir water storage. This is based on a comprehensive analysis of streamflow from a multi-model ensemble and as observed at ca. 8000 gauging stations, precipitation from a combination of station, satellite and forecast data, and open water evaporation estimates. We find reservoir storage has diminished substantially for 23 % of reservoirs over the three decades, but increased for 21 %. The greatest declines were for dry basins in southeastern Australia (−29 %), southwestern USA (−10 %), and eastern Brazil (−9 %). The greatest gains occurred in the Nile Basin (+67 %), Mediterranean basins (+31 %) and southern Africa (+22 %). Many of the observed reservoir changes could be explained by changes in precipitation and river inflows, emphasizing the importance of multi-decadal precipitation changes for reservoir water storage. Uncertainty in the analysis can come from, among others, the relatively low Landsat imaging frequency for parts of the Earth and the simple geo-statistical bathymetry model used. Our results also show that there is generally little impact from changes in net evaporation on storage trends. Based on the reservoir water balance, we deduce it is unlikely that water release trends dominate global trends in reservoir storage dynamics. This inference is further supported by different spatial patterns in water withdrawal and storage trends globally. A more definitive conclusion about the impact of changes in water releases at the global or local scale would require data that unfortunately are not publicly available for the vast majority of reservoirs globally.

Plants interact with a multitude of microorganisms and insects, both below- and above ground, which might influence plant metabolism. Despite this, we lack knowledge of the impact of natural soil communities and multiple aboveground attackers on the metabolic responses of plants, and whether plant metabolic responses to single attack can predict responses to dual attack. We used untargeted metabolic fingerprinting (gas chromatography-mass spectrometry, GC-MS) on leaves of the pedunculate oak, Quercus robur, to assess the metabolic response to different soil microbiomes and aboveground single and dual attack by oak powdery mildew (Erysiphe alphitoides) and the common oak aphid (Tuberculatus annulatus). Distinct soil microbiomes were not associated with differences in the metabolic profile of oak seedling leaves. Single attacks by aphids or mildew had pronounced but different effects on the oak leaf metabolome, but we detected no difference between the metabolomes of healthy seedlings and seedlings attacked by both aphids and powdery mildew. Our findings show that aboveground attackers can have species-specific and non-additive effects on the leaf metabolome of oak. The lack of a metabolic signature detected by GC-MS upon dual attack might suggest the existence of a potential negative feedback, and highlights the importance of considering the impacts of multiple attackers to gain mechanistic insights into the ecology and evolution of species interactions and the structure of plant-associated communities, as well as for the development of sustainable strategies to control agricultural pests and diseases and plant breeding.

Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo (Merged soil Moisture) and six estimates from the HBV (Hydrologiska Byråns Vattenbalansavdelning) model with three precipitation inputs (ERA5, IMERG, and MSWEP) with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5 cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. We found that application of the Soil Wetness Index (SWI) smoothing filter resulted in improved performance for all satellite products. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3ESWI, SMOSSWI, AMSR2SWI, and ASCATSWI, with the L-band-based SMAPL3ESWI (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCISWI), MeMo performed better on average (median R of 0.72 versus 0.67), probably due to the inclusion of SMAPL3ESWI. The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale.

There is a growing interest globally in the spatial distribution and temporal dynamics of intermittently flowing streams and rivers, and how this varies in relation to climatic and other environmental factors. However, biases in the distribution of stream gauges may give a misleading impression of spatial-temporal variations in streamflow intermittency within river networks. Here, we developed an approach to quantify catchment-wide streamflow intermittency over long time frames and in a spatially explicit manner, using readily accessible and spatially contiguous daily runoff data from a national-scale water balance model. We examined the ability of the water balance model to simulate streamflow in two hydro-climatically distinctive (subtropical and temperate) regions in Australia, with a particular focus on low-flow simulations. We also evaluated the effect of model time step (daily vs. monthly) on flow intermittency estimation to inform future model selection. The water balance model showed better performance in the temperate region characterised by steady baseflow than in the subtropical region with flashy hydrographs and frequent cease-to-flow periods. The model tended to overestimate low-flow magnitude mainly due to overestimation of gains (e.g. groundwater release to baseflow) during low-flow periods. Modelled patterns of flow intermittency revealed highly dynamic behaviour in space and time, with cease-to-flow events affecting between 29 and 80 % of the river network over the period of 1911–2016, using a daily streamflow model. The daily flow model did not perform better than the monthly flow model in quantifying flow intermittency at a monthly time step, and model selection should depend on the intended application of the model outputs. Our general approach to quantifying spatio-temporal patterns of flow intermittency is transferable to other parts of the world, and it can inform hydro-ecological understanding and management of intermittent streams where limited gauging data are available.

BackgroundMany cardiocirculatory mechanisms are involved in the adaptation to orthostatic stress. While these mechanisms may be impaired in Fontan patients. However, it is yet unclear how Fontan patients, who exhibit a critical fluid balance, respond to orthostatic stress. Angiotensin converting enzyme inhibitors are often prescribed to Fontan patients, but they may negatively influence orthostatic tolerance. Therefore, we evaluated the response to orthostatic stress in pediatric Fontan patients before and after treatment with enalapril.MethodsThirty-five Fontan patients (aged 14 years) with moderate-good systolic ventricular function without pre-existent enalapril treatment were included. Before and after a three-month enalapril treatment period, the hemodynamic response to head-up tilt test was evaluated by various parameters including cardiac index, blood pressure, cerebral blood flow, aortic stiffness and cardiac autonomous nervous activity. Thirty-four healthy subjects (aged 13 years) served as controls.ResultsFontan patients had a decreased cerebral blood flow and increased aortic stiffness in the supine position compared to controls, while all other factors did not differ. Patients and controls showed a comparable response to head-up tilt test for most parameters. Twenty-seven patients completed the enalapril study with a mean dosage of 0.3±0.1mg/kg/day. Most parameters were unaffected by enalapril, only the percent decrease in cardiac index to tilt was higher after treatment, but the cardiac index during tilt was not lower (3.0L/min/m2 pre-enalapril versus 2.8L/min/m2 after treatment; P = 0.15).ConclusionPediatric Fontan patients adequately respond to orthostasis with maintenance of blood pressure and cerebral blood flow and sufficient autonomic response. Enalapril treatment did not alter the response.Clinical trial informationScientific title: ACE inhibition in Fontan patients: its effect on body fluid regulation (sAFE-study). The Netherlands National Trial Register: Trail NL6415. Registered 2017-07-20. Trial information: https://www.trialregister.nl/trial/6415.

Studies using remote sensing data for fire danger prediction have primarily relied on fire ignitions data to develop fire danger indices (FDIs). However, these data may only represent conditions suitable for ignition but may not represent fire danger conditions causing escalating fire size. The fire-related response variable’s scalability is a key factor that forms a basis for an FDI to include a broader range of fire danger conditions. Remote sensing derived fire size is a scalable fire characteristic encapsulating all possible fire sizes that previously occurred in the landscape, including extreme fire events. Consequently, we propose a new FDI that uses remote sensing derived fire size as a response variable. We computed fire sizes from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument burned area. We applied random forest (RF) and logistic regression (LR) to develop the FDI for Australia. RF models performed better than LR, and the higher predicted probabilities demonstrated higher chances for ignited fires to be escalated to larger fire sizes at a regional scale across Australia. However, the predicted probabilities cannot be related to the specific range of fire sizes due to data limitations. Further research with higher temporal and spatial resolution data of both the response and predictor variables can help establish a better relationship between a specific range of fire sizes and the predicted probabilities.

Background and Objectives: Early identification of child mental health problems (MHPs) is important to provide adequate, timely treatment. Dutch preventive youth healthcare monitors all aspects of a child's healthy development. We explored the usefulness of their electronic health records (EHRs) in scientific research and aimed to develop prediction models for child MHPs.Methods: Population-based cohort study with anonymously extracted electronic healthcare data from preventive youth healthcare centers in the Leiden area, the Netherlands, from the period 2005–2015. Data was analyzed with respect to its continuity, percentage of cases and completeness. Logistic regression analyses were conducted to develop prediction models for the risk of a first recorded concern for MHPs in the next scheduled visit at age 3/4, 5/6, 10/11, and 13/14 years.Results: We included 26,492 children. The continuity of the data was low and the number of concerns for MHPs varied greatly. A large number of determinants had missing data for over 80% of the children. The discriminatory performance of the prediction models were poor.Conclusions: This is the first study exploring the usefulness of EHRs from Dutch preventive youth healthcare in research, especially in predicting child MHPs. We found the usefulness of the data to be limited and the performance of the developed prediction models was poor. When data quality can be improved, e.g., by facilitating accurate recording, or by data enrichment from other available sources, the analysis of EHRs might be helpful for better identification of child MHPs.

Forecasting drought and its impact on agriculture and ecosystems is challenged by a lack of knowledge of vegetation access to deep moisture. Here the authors show that combining vegetation and water storage remote sensing can be used to infer this knowledge, allowing drought impact forecasts months in advance.

Access to water is a critical aspect of livestock production, although the relationship between livestock weight gain and water quality remains poorly understood. Previous work has shown that water quality of poorly managed farm dams can be improved by fencing and constructing hardened watering points to limit stock access to the dam, and revegetation to filter contaminant inflow. Here we use cattle weight gain data from three North American studies to develop a cost-benefit analysis for the renovation of farm dams to improve water quality and, in turn, promote cattle weight gain on farms in south-eastern Australia. Our analysis indicated a strong likelihood of positive results and suggested there may be substantial net economic benefit from renovating dams in poor condition to improve water quality. The average per-farm Benefit-Cost Ratios based on deterministic assumptions was 1.5 for New South Wales (NSW) and 3.0 for Victoria in areas where rainfall exceeds 600mm annually. Our analyses suggested that cattle on farms in NSW and Victoria would need to experience additional weight gain from switching to clean water of at least 6.5% and 1.8% per annum respectively, to break even in present value terms. Monte Carlo simulation based on conservative assumptions indicated that the probability of per-farm benefits exceeding costs was greater than 70%. We recommend localised experiments to assess the impact of improved water quality on livestock weight gain in Australian conditions to confirm these expectations empirically.

Abstract This work introduces a methodology for optimizing neural network models using a combination of continuous and categorical binary indices in the context of precipitation forecasting. Probability of detection and false alarm rate are popular metrics used in the verification of precipitation models. However, machine learning models trained using gradient descent cannot be optimized based on these metrics, as they are not differentiable. We propose an alternative formulation for these categorical indices that are differentiable and we demonstrate how they can be used to optimize the skill of precipitation neural network models defined as a multiobjective optimization problem. To our knowledge, this is the first proposal of a methodology for optimizing weather neural network models based on categorical indices.

Vasovagal syncope (VVS) is the most common cause of syncope across all age groups. Nonetheless, despite its clinical importance and considerable research effort over many years, the pathophysiology of VVS remains incompletely understood. In this regard, numerous studies have been undertaken in an attempt to improve insight into the evolution of VVS episodes and many of these studies have examined neurohormonal changes that occur during the progression of VVS events primarily using the head-up tilt table testing model. In this regard, the most consistent finding is a marked increase in epinephrine (Epi) spillover into the circulation beginning at an early stage as VVS evolves. Reported alterations of circulating norepinephrine (NE), on the other hand, have been more variable. Plasma concentrations of other vasoactive agents have been reported to exhibit more variable changes during a VVS event, and for the most part change somewhat later, but in some instances the changes are quite marked. The neurohormones that have drawn the most attention include arginine vasopressin [AVP], adrenomedullin, to a lesser extent brain and atrial natriuretic peptides (BNP, ANP), opioids, endothelin-1 (ET-1) and serotonin. However, whether some or all of these diverse agents contribute directly to VVS pathophysiology or are principally a compensatory response to an evolving hemodynamic crisis is as yet uncertain. The goal of this communication is to summarize key reported neurohumoral findings in VVS, and endeavor to ascertain how they may contribute to observed hemodynamic alterations during VVS.

Soil moisture affects the partitioning of water and energy and is recognized as an essential climate variable. Soil moisture estimates derived from passive microwave remote sensing can improve model estimates through data assimilation, but the relative effectiveness of microwave retrievals in different frequencies is unclear. Land Parameter Retrieval Model (LPRM) satellite soil moisture derived from L-, C-, and X-band frequency remote sensing were assimilated in the Australian Water Resources Assessment landscape hydrology model (AWRA-L) using an ensemble Kalman filter approach. Two sets of experiments were performed. First, each retrieval was assimilated individually for comparison. Second, each possible combination of two retrievals was assimilated jointly. Results were evaluated against field-measured top-layer and root-zone soil moisture at 24 sites across Australia. Assimilation generally improved the coefficient of correlation (r) between modeled and field-measured soil moisture. L- and X-band retrievals were more informative than C-band retrievals, improving r by an average of 0.11 and 0.08 compared to 0.04, respectively. Although L-band retrievals were more informative for top-layer soil moisture in most cases, there were exceptions, and L- and X-band were equally informative for root-zone soil moisture. The consistency between L- and X-band retrievals suggests that they can substitute for each other, for example when transitioning between sensors and missions. Furthermore, joint assimilation of retrievals resulted in a model performance that was similar to or better than assimilating either retrieval individually. Comparison of model estimates obtained with global precipitation data and with higher-quality, higher-resolution regional data, respectively, demonstrated that precipitation data quality does determine the overall benefit that can be expected from assimilation. Further work is needed to assess the potentially complementary spatial information that can be derived from retrievals from different frequencies.

The carbon balance in Southeast Asia is highly uncertain. Here, the authors show that land use changes and occurrence of strong El Niño control decadal shifts in the carbon balance of this region.

Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of large-scale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human–water interface in hydrological models.

Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979–2015 with a 3-hourly temporal and 0.25° spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44–0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (2) across the globe. Specifically, we calibrated the simple conceptual hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) against daily Q observations with P from each of the different datasets. For the 1058 sparsely gauged catchments, representative of 83.9 % of the global land surface (excluding Antarctica), MSWEP obtained a median calibration NSE of 0.52 vs. 0.29–0.39 for the other P datasets. MSWEP is available via http://www.gloh2o.org.

This study presents an "Earth observation-based" method for estimating root zone storage capacity – a critical, yet uncertain parameter in hydrological and land surface modelling. By assuming that vegetation optimises its root zone storage capacity to bridge critical dry periods, we were able to use state-of-the-art satellite-based evaporation data computed with independent energy balance equations to derive gridded root zone storage capacity at global scale. This approach does not require soil or vegetation information, is model independent, and is in principle scale independent. In contrast to a traditional look-up table approach, our method captures the variability in root zone storage capacity within land cover types, including in rainforests where direct measurements of root depths otherwise are scarce. Implementing the estimated root zone storage capacity in the global hydrological model STEAM (Simple Terrestrial Evaporation to Atmosphere Model) improved evaporation simulation overall, and in particular during the least evaporating months in sub-humid to humid regions with moderate to high seasonality. Our results suggest that several forest types are able to create a large storage to buffer for severe droughts (with a very long return period), in contrast to, for example, savannahs and woody savannahs (medium length return period), as well as grasslands, shrublands, and croplands (very short return period). The presented method to estimate root zone storage capacity eliminates the need for poor resolution soil and rooting depth data that form a limitation for achieving progress in the global land surface modelling community.

Внешние эксперты: Haruhiko Abe (Япония), David G. Benditt (США), Wyatt W. Decker (США), Blair P. Grubb (США), Horacio Kaufmann9 (США), Carlos Morillo (Канада), Brian Olshansky (США), Steve W. Parry (Великобритания), Robert Sheldon (Канада), Win K. Shen (США)Члены Комитета Европейского общества кардиологов по практическим рекомендациям (ESC Committee for Practice Guidelines: CPG): Alec Vahanian (Председатель) (Франция), Angelo Auricchio (Швейцария),Jeroen Bax (Нидерланды), Claudio Ceconi (Италия), Veronica Dean (Франция), Gerasimos Filippatos (Греция), Christian Funck-Brentano (Франция), Richard Hobbs (Великобритания), Peter Kearney (Ирландия), Theresa McDonagh (Великобритания), Keith McGregor (Франция), Bogdan A. Popescu (Румыния), Zeljko Reiner (Хорватия), Udo Sechtem (Германия), Per Anton Sirnes (Норвегия), Michal Tendera (Польша), Panos Vardas (Греция), Petr Widimsky (Чехия)Рецензенты: Angelo Auricchio (Координатор от CPG) (Швейцария), Esmeray Acarturk (Турция), Felicita Andreotti (Италия), Riccardo Asteggiano (Италия), Urs Bauersfeld (Швейцария), Abdelouahab Bellou4 (Франция), Athanase Benetos6 (Франция), Johan Brandt (Швеция), Mina K. Chung3 (США), Pietro Cortelli 8 (Италия), Antoine Da Costa (Франция), Fabrice Extramiana (Франция), Jose´ Ferro7 (Португалия), Bulent Gorenek (Турция), Antti Hedman (Финляндия), Rafael Hirsch (Израиль), Gabriela Kaliska (Словакия), Rose Anne Kenny6 (Ирландия), Keld Per Kjeldsen (Дания), Rachel Lampert 3 (USA), Henning Mølgard (Denmark), Rain Paju (Эстония), Aras Puodziukynas (Литва), Antonio Raviele (Италия), Pilar Roman5 (Испания), Martin Scherer (Германия), Ronald Schondorf 9 (Канада), Rosa Sicari (Италия), Peter Vanbrabant 4 (Бельгия), Christian Wolpert1 (Германия), Jose Luis Zamorano (Испания).

Advanced oxidation with O3 / H2O2 (peroxone) was conducted on pilot plant scale on pre-treated Meuse river water to investigate the conversion of organic micropollutants (OMPs) and the formation of bromate. Fourteen selected model compounds were dosed to the pre-treated river water on a regular basis to assess the efficiency of the peroxone process and to establish the influence of the water matrix. The ozone dose was the main factor in the conversion of the model compounds, however, the ozone dose was limited because of bromate formation. The hydrogen peroxide dosage had only a minor effect on the conversion, but it limited the bromate formation effectively. In terms of limited chemical consumption, maximal conversion and to comply the strict Dutch drinking water act for bromate of 1 μg L−1, a practical peroxone setting was 6 mg L−1 hydrogen peroxide and 1.5 mg L−1 ozone. During the investigation period, the average conversion of the model compounds was 78.9 %. The conversion of OMPs was higher at higher water temperatures and lower concentrations of DOC and bicarbonate. The bromate formation also was higher at higher water temperature and lower bicarbonate concentration and proportional with the bromide concentration, above a threshold of about 32 μg L−1 bromide. The peroxone process can be controlled on basis of the (derived) parameters water temperature, bicarbonate and DOC.

Drinking water companies (are intending to) implement advanced oxidation processes (AOP) in their treatment schemes to increase the barrier against organic micropollutants (OMPs). It is necessary to decompose the excessive hydrogen peroxide after applying AOP to avoid negative effects in the following, often biological, treatment steps. A drinking water company in the western part of the Netherlands investigated decomposition of about 5.75 mg L−1 hydrogen peroxide in pre-treated Meuse river water with different catalysts on pilot scale. In down flow operation, the necessary reactor empty bed contact time (EBCT) with the commonly used granulated activated carbon (GAC) and waste ground water filter gravel (MCFgw) were found equal with 149 s, corresponding with a conversion rate constant r of 0.021 s−1. The EBCT of the fine coating of ground water filter gravel (MC) was significantly shorter with a little more than 10 s (r = 0.30 s−1). In up flow operation, with a flow rate of 20 m h−1, the EBCT of coating MC increased till about 100 s (r = 0.031 s−1), from which can be concluded, that the performance of this waste material is better compared with GAC, in both up and down flow operation. The necessary EBCT at average filtration rate of full scale dual layer filter material (MCFsw) amounted to 209 s (r= 0.015 s−1). Regarding the average residence time in the full scale filters of 700 s, applying AOP in front of the filters could be an interesting alternative which makes a separate decomposition installation superfluous, on the condition that the primary functions of the filters are not affected.

We present a global water cycle reanalysis that merges water balance estimates derived from the Gravity Recovery And Climate Experiment (GRACE) satellite mission, satellite water level altimetry and off-line estimates from several hydrological models. Error estimates for the sequential data assimilation scheme were derived from available uncertainty information and the triple collocation technique. Errors in four GRACE storage products were estimated to be 11–12 mm over land areas, while errors in monthly storage changes derived from five global hydrological models were estimated to be 17–28 mm. Prior and posterior water storage estimates were evaluated against independent observations of river water level and discharge, snow water storage and glacier mass loss. Data assimilation improved or maintained agreement overall, although results varied regionally. Uncertainties were greatest in regions where glacier mass loss and subsurface storage decline are both plausible but poorly constrained. We calculated a global water budget for 2003–2012. The main changes were a net loss of polar ice caps (−342 Gt yr−1) and mountain glaciers (−230 Gt yr−1), with an additional decrease in seasonal snowpack (−18 Gt yr−1). Storage increased due to new impoundments (+16 Gt yr−1), but this was compensated by decreases in other surface water bodies (−10 Gt yr−1). If the effect of groundwater depletion (−92 Gt yr−1) is considered separately, subsurface water storage increased by +202 Gt yr−1 due particularly to increased wetness in northern temperate regions and in the seasonally wet tropics of South America and southern Africa. The reanalysis results are publicly available via www.wenfo.org/wald/.

The new German standard on the calculation of calcite saturation in drinking water, DIN 38404-10, 2012 (DIN), marks a change in drinking water standardization from using simplified equations applicable for nomographs and simple calculators to using extensive chemical modeling requiring computer programs. The standard outlines the chemical modeling and presents a dataset with 10 water samples for validating used computer programs. The DIN standard, as well as the Standard Methods 2330 (SM) and NEN 6533 (NEN) for calculation of calcium carbonate saturation in drinking water were translated into chemical databases for use in PHREEQC (USGS, 2013). This novel approach gave the possibility to compare the calculations as defined in the standards with calculations using widely used chemical databases provided with PHREEQC. From this research it is concluded that the computer program PHREEQC with the developed chemical database din38404-10_2012.dat complies with the DIN standard for calculating Saturation Index (SI) and Calcite Dissolution Capacity (Calcitlösekapazität) or Calcium Carbonate Precipitation Potential (CCPP). This compliance is achieved by assuming equal values for molarity as used in DIN (obsolete) and molality as used in PHREEQC. From comparison with widely used chemical databases it is concluded that the use of molarity limits the use of DIN to a maximum temperature of 45 °C. For current practical applications in water treatment and drinking water applications, the PHREEQC database stimela.dat was developed within the Stimela platform of Delft University of Technology. This database is an extension of the chemical database phreeqc.dat and thus in compliance with SM. The database stimela.dat is also applicable for hot and boiling water, which is important in drinking water supply with regard to scaling of calcium carbonate in in-house drinking water practices. SM and NEN proved to be not accurate enough to comply with DIN, because of their simplifications. The differences in calculation results for DIN, SM and NEN illustrate the need for international unification of the standard for calcium carbonate saturation in drinking water.

Four pilot (biological) granular activated carbon ((B)GAC) filters were operated to quantify the effects of ozonation and water temperature on the biodegradation of natural organic matter (NOM) in (B)GAC filters. The removal of dissolved organic carbon (DOC), assimilable organic carbon (AOC) and oxygen and the production of carbon dioxide were taken as indicators for NOM biodegradation. Ozonation stimulated DOC and AOC removal in the BGAC filters, but had no significant effect on oxygen consumption or carbon dioxide production. The temperature had no significant effect on DOC and AOC removal, while it had a positive effect on oxygen consumption and carbon dioxide production. Multivariate linear regression was used to quantify these relationships. In summer, the ratio between oxygen consumption and DOC removal was approximately 2 times the theoretical maximum of 2.6 g O2 g C−1 and the ratio between carbon dioxide production and DOC removal was approximately 1.5 times the theoretical maximum of 3.7 g CO2 g C−1. The production and loss of biomass, the degassing of (B)GAC filters, the decrease in the NOM reduction degree and the temperature effects on NOM adsorption could only partly explain these excesses and the non-correlation between DOC and AOC removal and oxygen consumption and carbon dioxide production. It was demonstrated that bioregeneration of NOM could explain the excesses and the non-correlation. Therefore, it was likely that bioregeneration of NOM did occur in the (B)GAC pilot filters.

In drinking water production, river bank filtration has the advantages of dampening peak concentrations of many dissolved components, substantially removing many micropollutants and removing, virtually completely, the pathogens and suspended solids. The production aquifer is not only fed by the river bank infiltrate but also by water percolating through covering layers. In the polder areas, these top layers consist of peat and deposits from river sediments and sea intrusions. This paper discusses the origin and fate of macro components in river bank filtrate, based on extensive full-scale measurements in well fields and treatment systems of the Drinking Water Company Oasen in the Netherlands. First, it clarifies and illustrates redox reactions and the mixing of river bank filtrate and PW as the dominant processes determining the raw water quality for drinking water production. Next, full-scale results are elaborated on to evaluate trickling filtration as an efficient and proven one-step process to remove methane, iron, ammonium and manganese. The interaction of methane and manganese removal with nitrification in these systems is further analyzed. Methane is mostly stripped during trickling filtration and its removal hardly interferes with nitrification. Under specific conditions, microbial manganese removal may play a dominant role.

An "all pipes" hydraulic model of a drinking water distribution system was constructed with two types of demand allocations. One is constructed with the conventional top-down approach, i.e. a demand multiplier pattern from the booster station is allocated to all demand nodes with a correction factor to account for the average water demand on that node. The other is constructed with a bottom-up approach of demand allocation, i.e., each individual home is represented by one demand node with its own stochastic water demand pattern. This was done for a drinking water distribution system of approximately 10 km of mains and serving ca. 1000 homes. The system was tested in a real life situation. The stochastic water demand patterns were constructed with the end-use model SIMDEUM on a per second basis and per individual home. Before applying the demand patterns in a network model, some temporal aggregation was done. The flow entering the test area was measured and a tracer test with sodium chloride was performed to determine travel times. The two models were validated on the total sum of demands and on travel times. The study showed that the bottom-up approach leads to realistic water demand patterns and travel times, without the need for any flow measurements or calibration. In the periphery of the drinking water distribution system it is not possible to calibrate models on pressure, because head losses are too low. The study shows that in the periphery it is also difficult to calibrate on water quality (e.g. with tracer measurements), as a consequence of the high variability between days. The stochastic approach of hydraulic modelling gives insight into the variability of travel times as an added feature beyond the conventional way of modelling.

The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations) in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log Kow), solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal. Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values for most solutes.

A new treatment concept for drinking water production from surface water has been investigated on a pilot scale. The treatment concept consists of fluidized ion exchange (FIEX), ultrafiltration (UF), nanofiltration (NF), and granular activated carbon filtration (GAC). The FIEX process removed calcium and other divalent cations; the UF membrane removed particles and micro-organisms; and the NF membrane and GAC removed natural organic matter (NOM) and micro-pollutants. This study focused on the prevention of fouling of the UF and scaling of the NF and investigated the overall removal of micro-pollutants by the treatment concept. The results of the experiments showed that in 14 days of continuous operation at a flux of 65 l/h m2 the UF performance was stable with the FIEX pre-treated feed water without the aid of a coagulant. The scaling of the NF was also not observed even at 97% recovery. Different micro-pollutants were spiked in the NF feed water and their concentrations in the effluent of NF and GAC were measured. The combination of NF and GAC removed most of the micro-pollutants successfully, except for the very polar substances with a molecular weight lower than 100 Daltons.

For more than a decade it has been known that shallow tube wells in Bangladesh are frequently contaminated with arsenic concentrations at a level that is harmful to human health. By now it is clear that a disaster of an unheard magnitude is going on: the World Health Organization has estimated that long-term exposure to arsenic in groundwater, at concentrations over 500 μg L−1, causes death in 1 in 10 adults. Other studies show that problems with arsenic in groundwater/drinking water occur in many more countries worldwide, such as in the USA and China. In Europe the focus on arsenic problems is currently confined to countries with high arsenic levels in their groundwater, such as Serbia, Hungary and Italy. In most other European countries, the naturally occurring arsenic concentrations are mostly lower than the European drinking water standard of 10 μg L−1. However, from the literature review presented in this paper, it is concluded that at this level health risks cannot be excluded. As consumers in European countries expect the drinking water to be of impeccable quality, it is recommended that water supply companies optimize arsenic removal to a level of −1, which is technically feasible.

The Netherlands is one of the few countries where chlorine is not used at all, neither for primary disinfection nor to maintain a residual disinfectant in the distribution network. The Dutch approach that allows production and distribution of drinking water without the use of chlorine while not compromising microbial safety at the tap, can be summarized as follows: 1. Use the best source available, in order of preference: – microbiologically safe groundwater, – surface water with soil passage such as artificial recharge or bank filtration, – direct treatment of surface water in a multiple barrier treatment; 2. Use a preferred physical process treatment such as sedimentation, filtration and UV-disinfection. If absolutely necessary, also oxidation by means of ozone or peroxide can be used, but chlorine is avoided; 3. Prevent ingress of contamination during distribution; 4. Prevent microbial growth in the distribution system by production and distribution of biologically stable (biostable) water and the use of biostable materials; 5. Monitor for timely detection of any failure of the system to prevent significant health consequences. New developments in safe drinking water in the Netherlands include the adaptation of the Dutch drinking water decree, implementation of quantitative microbial risk assessment (QMRA) by water companies and research into source water quality, drinking water treatment efficacy, safe distribution and biostability of drinking water during distribution and Legionella. This paper summarizes how the Dutch water companies warrant the safety of the drinking water without chlorine.

Today, there is a growing interest in network water quality modelling. The water quality issues of interest relate to both dissolved and particulate substances. For dissolved substances the main interest is in residual chlorine and (microbiological) contaminant propagation; for particulate substances it is in sediment leading to discolouration. There is a strong influence of flows and velocities on transport, mixing, production and decay of these substances in the network. This imposes a different approach to demand modelling which is reviewed in this article. For the large diameter lines that comprise the transport portion of a typical municipal pipe system, a skeletonised network model with a top-down approach of demand pattern allocation, a hydraulic time step of 1 h, and a pure advection-reaction water quality model will usually suffice. For the smaller diameter lines that comprise the distribution portion of a municipal pipe system, an all-pipes network model with a bottom-up approach of demand pattern allocation, a hydraulic time step of 1 min or less, and a water quality model that considers dispersion and transients may be needed. Demand models that provide stochastic residential demands per individual home and on a one-second time scale are available. A stochastic demands based network water quality model needs to be developed and validated with field measurements. Such a model will be probabilistic in nature and will offer a new perspective for assessing water quality in the drinking water distribution system.

ObjectiveTo establish whether severe obstetric brachial plexus palsy (OBPP) can be identified reliably at or before three months of age.MethodsSevere OBPP was defined as neurotmesis or avulsion of spinal nerves C5 and C6 irrespective of additional C7-T1 lesions, assessed during surgery and confirmed by histopathological examination. We first prospectively studied a derivation group of 48 infants with OBPP with a minimal follow-up of two years. Ten dichotomous items concerning active clinical joint movement and needle electromyography of the deltoid, biceps and triceps muscles were gathered at one week, one month and three months of age. Predictors for a severe lesion were identified using a two-step forward logistic regression analysis. The results were validated in two independent cohorts of OBPP infants of 60 and 13 infants.ResultsPrediction of severe OBPP at one month of age was better than at one week and at three months. The presence of elbow extension, elbow flexion and of motor unit potentials in the biceps muscle correctly predicted whether lesions were mild or severe in 93.6% of infants in the derivation group (sensitivity 1.0, specificity 0.88), in 88.3% in the first validation group (sensitivity 0.97, specificity 0.76) and in 84.6% in the second group (sensitivity of 1.0, specificity 0.66).InterpretationInfants with OBPP with severe lesions can be identified at one month of age by testing elbow extension, elbow flexion and recording motor unit potentials (MUPs) in the biceps muscle. The decision rule implies that children without active elbow extension at one month should be referred to a specialized center, while children with active elbow extension as well as active flexion should not. When there is active elbow extension, but no active elbow flexion an EMG is needed; absence of MUPs in the biceps muscle is an indication for referral.

Many efforts have been directed at negating the influence of electromyographic (EMG) activity on the EEG, especially in elderly demented patients. We wondered whether these “artifacts” might reflect cognitive and behavioural aspects of dementia. In this pilot study, 11 patients with probable Alzheimer's disease (AD), 13 with amnestic mild cognitive impairment (MCI) and 13 controls underwent EEG registration. As EMG measures, we used frontal and temporal 50–70 Hz activity. We found that the EEGs of AD patients displayed more theta activity, less alpha reactivity, and more frontal EMG than controls. Interestingly, increased EMG activity indicated more cognitive impairment and more depressive complaints. EEG variables on the whole distinguished better between groups than EMG variables, but an EMG variable was best for the distinction between MCI and controls. Our results suggest that EMG activity in the EEG could be more than noise; it differs systematically between groups and may reflect different cerebral functions than the EEG.