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This study describes a method that combines synthetic aperture radar (SAR) data with shallow-water modeling to estimate flood hazards at a local level. The method uses particle filtering to integrate flood probability maps derived from SAR imagery with simulated flood maps for various flood return periods within specific river sub-catchments. We tested this method in a section of the Severn River basin in the UK. Our research involves 11 SAR flood observations from ENVISAT ASAR images, an ensemble of 15 particles representing various pre-computed flood scenarios, and 4 masks of spatial units corresponding to different river segmentations. Empirical results yield maps of maximum flood extent with associated return periods, reflecting the local characteristics of the river. The results are validated through a quantitative comparison approach, demonstrating that our method improves the accuracy of flood extent and scenario estimation. This provides spatially distributed return periods in sub-catchments, making flood hazard monitoring effective at a local scale. [ABSTRACT FROM AUTHOR]

Coastal sediment grain size is an important factor in determining coastal morphodynamics. In this study, we explore a novel approach for retrieving the median sediment grain size (D50) of gravel-dominated beaches using Synthetic Aperture Radar (SAR) spaceborne imagery. We assessed this by using thirty-six Sentinel-1 (C-band SAR) satellite images acquired in May and June 2022 and 2023, and three NovaSAR (S-band SAR) satellite images acquired in May and June 2022, for three different training sites and one test site across England (the UK). The results from the Sentinel-1 C-band data show strong positive correlations (R2 ≥ 0.75 ) between the D50 and the backscatter coefficients for 15/18 of the resultant models. The models were subsequently used to derive predictions of D50 for the test site, with the models which exhibited the strongest correlations resulting in Mean Absolute Errors (MAEs) in the range 2.26–5.47 mm. No correlation (R2 = 0.04) was found between the backscatter coefficients from the S-band NovaSAR data and D50. These results highlight the potential to derive near-real time estimates of coastal sediment grain size for gravel beaches to better inform coastal erosion and monitoring programs. [ABSTRACT FROM AUTHOR]

Tidal flats are some of the most dynamic coastal environments in the world, where traditional coastal mapping and monitoring provide insufficient temporal resolution to reliably map channels and sand flats. Satellite-based Synthetic Aperture Radar (SAR) enables regular cloud-penetrating detection of water flowing through channels within the tidal flats, referred to as tidal channels. This paper presents a method for detecting a path through tidal channels, using satellite imagery, that supports our understanding and safe exploitation of this valuable coastal environment. This approach is the first proposed to identify navigable paths in all conditions, with SAR images susceptible to variation due to weather and tidal conditions. Tidal channels are known to vary in SAR presentation, and we find that tidal flat presentation is also influenced by conditions. The most influential factor is the wind, with high winds causing an inversion in how both tidal flats and tidal channels present in SAR images. The presented method for the automatic detection of tidal channels accounts for this variability by using previous channel paths as a reference to reliably correct imagery and detect the latest path. The final algorithm produces paths with minor errors in 17.6% of images; the error rate increases to 71.7%, with an almost tenfold increase in errors, when the SAR image and paths are not adjusted to account for conditions. This capability has been used to support the Nith Inshore Rescue in attending call-outs from their base in Glencaple, UK, while the insights from monitoring tidal channels for a year demonstrate how periods of high river flow preceded major changes in the channel path. [ABSTRACT FROM AUTHOR]

Background: Disease recurrence remains one of the biggest concerns in patients after resection of pancreatic ductal adenocarcinoma (PDAC). Despite (neo)adjuvant systemic therapy, most patients experience local and/or distant PDAC recurrence within 2 years. High-level evidence regarding the benefits of recurrence-focused surveillance after PDAC resection is missing, and the impact of early detection and treatment of recurrence on survival and quality of life is unknown. In most European countries, recurrence-focused follow-up after surgery for PDAC is currently lacking. Consequently, guidelines regarding postoperative surveillance are based on expert opinion and other low-level evidence. The recent emergence of more potent local and systemic treatment options for PDAC recurrence has increased interest in early diagnosis. To determine whether early detection and treatment of recurrence can lead to improved survival and quality of life, we designed an international randomized trial. Methods: This randomized controlled trial is nested within an existing prospective cohort in pancreatic cancer centers in the Netherlands (Dutch Pancreatic Cancer Project; PACAP) and the United Kingdom (UK) (Pancreas Cancer: Observations of Practice and survival; PACOPS) according to the "Trials within Cohorts" (TwiCs) design. All PACAP/PACOPS participants with a macroscopically radical resection (R0-R1) of histologically confirmed PDAC, who provided informed consent for TwiCs and participation in quality of life questionnaires, are included. Participants randomized to the intervention arm are offered recurrence-focused surveillance, existing of clinical evaluation, serum cancer antigen (CA) 19–9 testing, and contrast-enhanced computed tomography (CT) of chest and abdomen every three months during the first 2 years after surgery. Participants in the control arm of the study will undergo non-standardized clinical follow-up, generally consisting of clinical follow-up with imaging and serum tumor marker testing only in case of onset of symptoms, according to local practice in the participating hospital. The primary endpoint is overall survival. Secondary endpoints include quality of life, patterns of recurrence, compliance to and costs of recurrence-focused follow-up, and the impact on recurrence-focused treatment. Discussion: The RADAR-PANC trial will be the first randomized controlled trial to generate high level evidence for the current clinical equipoise regarding the value of recurrence-focused postoperative surveillance with serial tumor marker testing and routine imaging in patients after PDAC resection. The Trials within Cohort design allows us to study the acceptability of recurrence-focused surveillance among cohort participants and increases the generalizability of findings to the general population. While it is strongly encouraged to offer all trial participants treatment at time of recurrence diagnosis, type and timing of treatment will be determined through shared decision-making. This might reduce the potential survival benefits of recurrence-focused surveillance, although insights into the impact on patients' quality of life will be obtained. Trial registration: Clinicaltrials.gov, NCT04875325. Registered on May 6, 2021. [ABSTRACT FROM AUTHOR]

Background: Disease recurrence remains one of the biggest concerns in patients after resection of pancreatic ductal adenocarcinoma (PDAC). Despite (neo)adjuvant systemic therapy, most patients experience local and/or distant PDAC recurrence within 2 years. High-level evidence regarding the benefits of recurrence-focused surveillance after PDAC resection is missing, and the impact of early detection and treatment of recurrence on survival and quality of life is unknown. In most European countries, recurrence-focused follow-up after surgery for PDAC is currently lacking. Consequently, guidelines regarding postoperative surveillance are based on expert opinion and other low-level evidence. The recent emergence of more potent local and systemic treatment options for PDAC recurrence has increased interest in early diagnosis. To determine whether early detection and treatment of recurrence can lead to improved survival and quality of life, we designed an international randomized trial. Methods: This randomized controlled trial is nested within an existing prospective cohort in pancreatic cancer centers in the Netherlands (Dutch Pancreatic Cancer Project; PACAP) and the United Kingdom (UK) (Pancreas Cancer: Observations of Practice and survival; PACOPS) according to the "Trials within Cohorts" (TwiCs) design. All PACAP/PACOPS participants with a macroscopically radical resection (R0-R1) of histologically confirmed PDAC, who provided informed consent for TwiCs and participation in quality of life questionnaires, are included. Participants randomized to the intervention arm are offered recurrence-focused surveillance, existing of clinical evaluation, serum cancer antigen (CA) 19–9 testing, and contrast-enhanced computed tomography (CT) of chest and abdomen every three months during the first 2 years after surgery. Participants in the control arm of the study will undergo non-standardized clinical follow-up, generally consisting of clinical follow-up with imaging and serum tumor marker testing only in case of onset of symptoms, according to local practice in the participating hospital. The primary endpoint is overall survival. Secondary endpoints include quality of life, patterns of recurrence, compliance to and costs of recurrence-focused follow-up, and the impact on recurrence-focused treatment. Discussion: The RADAR-PANC trial will be the first randomized controlled trial to generate high level evidence for the current clinical equipoise regarding the value of recurrence-focused postoperative surveillance with serial tumor marker testing and routine imaging in patients after PDAC resection. The Trials within Cohort design allows us to study the acceptability of recurrence-focused surveillance among cohort participants and increases the generalizability of findings to the general population. While it is strongly encouraged to offer all trial participants treatment at time of recurrence diagnosis, type and timing of treatment will be determined through shared decision-making. This might reduce the potential survival benefits of recurrence-focused surveillance, although insights into the impact on patients' quality of life will be obtained. Trial registration: Clinicaltrials.gov, NCT04875325. Registered on May 6, 2021. [ABSTRACT FROM AUTHOR]

Differential reflectivity (ZDR$$ {Z}_{\mathrm{DR}} $$) columns were observed using a Met Office three‐dimensional radar composite. An algorithm for automatic detection of ZDR$$ {Z}_{\mathrm{DR}} $$ columns was developed, based on ZDR≥1.0$$ {Z}_{\mathrm{DR}}\ge 1.0 $$ dB and ZH≥10$$ {Z}_{\mathrm{H}}\ge 10 $$ dBZ. Across three case days, detected ZDR$$ {Z}_{\mathrm{DR}} $$ columns were found to precede severe convection in tracked convective cells with a range of lead times from 0 to 20 min depending on the case day. Requiring maxima above 1.4 dB and 30 dBZ of ZDR$$ {Z}_{\mathrm{DR}} $$ and ZH$$ {Z}_{\mathrm{H}} $$ respectively was an appropriate second condition for all three cases although the skill in the early detection of severe convection varied across case days. Despite the high probability of detections, the high false alarm rate accompanied by low critical success index and data latency limit performance based on the three cases considered in this study. Nevertheless, the ability to detect ZDR$$ {Z}_{\mathrm{DR}} $$ columns in operational radar data with a useful lead time prior to severe convection in certain conditions is a promising development towards advancing nowcasting of severe convection in the United Kingdom. [ABSTRACT FROM AUTHOR]

Individuals with rare kidney diseases account for 5–10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure. People aged 0–96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan–Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1·73 m2 or more to first eGFR of less than 30 mL/min per 1·73 m2 (the therapeutic trial window). Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9·6 years (IQR 5·9–16·7). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2·81 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0·0001), but better survival rates (standardised mortality ratio 0·42 [95% CI 0·32–0·52]; p<0·0001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases. Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3–5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand. RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity. [ABSTRACT FROM AUTHOR]

Object-based radar rainfall nowcasting is a widely used technique for convective storm prediction. Currently, most existing object-based nowcasting methods primarily focus on predicting cell movements, neglecting the temporal evolution of cell properties such as size, shape, and intensity. Incorporating this evolution is critical for improving predictability in convective storms. While previous studies have used three-dimensional (3D) radar observations to capture vertical changes during convective cell formation, these efforts often analyse or reconstruct specific convective events. Integrating 3D radar information into operational object-based radar rainfall nowcasting remains an open challenge. This research addresses this challenge using deep learning (DL) techniques. More specifically, a DL-based prediction model is developed, which uses 2D and 3D cells' properties retrieved from 3D radar reflectivity data at the current time and across the past 15 min to predict the evolution of these properties over the next 15 min. This model could eventually be integrated into existing object-based nowcasting models. A total of 4708 cell lifecycles, extracted from high-resolution (5-min, 1-km, 24 levels at 0.5 km intervals) 3D radar data across the UK, are used to train the model, and a total of 1177 lifecycles are used for testing. The proposed model is shown to predict the evolution of single-core convective cells effectively, including changes in 2D projected geometry and mean 2D and 3D reflectivity. In particular, by incorporating information on the vertical evolution of convective cores, the prediction errors of mean reflectivity (in both 2D and 3D) can be reduced by approximately 50% at 15-min forecast lead time, as compared to a persistence forecast. Keywords: radar, tracking, convective cell, nowcasting, 3D, deep learning, lstm. • A deep-learning model that predicts single-core convective cell evolution. • Convective core altitudes aid cell mean reflectivity prediction. • Prediction errors of cell reflectivity are reduced by 50% at 15-min lead time. [ABSTRACT FROM AUTHOR]

Radar networks hold great promise for monitoring population trends of migrating insects. However, it is important to elucidate the nature of responses to environmental cues. We use data from a mini-network of vertical-looking entomological radars in the southern UK to investigate changes in nightly abundance, flight altitude and behaviour of insect migrants, in relation to meteorological and celestial conditions. Abundance of migrants showed positive relationships with air temperature, indicating that this is the single most important variable influencing the decision to initiate migration. In addition, there was a small but significant effect of moonlight illumination, with more insects migrating on full moon nights. While the effect of nocturnal illumination levels on abundance was relatively minor, there was a stronger effect on the insects' ability to orientate close to downwind: flight headings were more tightly clustered on nights when the moon was bright and when cloud cover was sparse. This indicates that nocturnal illumination is important for the navigational mechanisms used by nocturnal insect migrants. Further, our results clearly show that environmental conditions such as air temperature and light levels must be considered if long-term radar datasets are to be used to assess changing population trends of migrants. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'. [ABSTRACT FROM AUTHOR]

Background: End-of-life (EoL) care volunteers in hospitals are a novel approach to support patients and their close ones. The iLIVE Volunteer Study supported hospital volunteer coordinators from five European countries to design and implement an EoL care volunteer service on general wards in their hospitals. This study aimed to identify and explore barriers and facilitators to the implementation of EoL care volunteer services in the five hospitals. Methods: Volunteer coordinators (VCs) from the Netherlands (NL), Norway (NO), Slovenia (SI), Spain (ES) and United Kingdom (UK) participated in a focus group interview and subsequent in-depth one-to-one interviews. A theory-inspired framework based on the five domains of the Consolidated Framework for Implementation Research (CFIR) was used for data collection and analysis. Results from the focus group were depicted in radar charts per hospital. Results: Barriers across all hospitals were the COVID-19 pandemic delaying the implementation process, and the lack of recognition of the added value of EoL care volunteers by hospital staff. Site-specific barriers were struggles with promoting the service in a highly structured setting with many stakeholders (NL), negative views among nurses on hospital volunteering (NL, NO), a lack of support from healthcare professionals and the management (SI, ES), and uncertainty about their role in implementation among VCs (ES). Site-specific facilitators were training of volunteers (NO, SI, NL), involving volunteers in promoting the service (NO), and education and awareness for healthcare professionals about the role and boundaries of volunteers (UK). Conclusion: Establishing a comprehensive EoL care volunteer service for patients in non-specialist palliative care wards involves multiple considerations including training, creating awareness and ensuring management support. Implementation requires involvement of stakeholders in a way that enables medical EoL care and volunteering to co-exist. Further research is needed to explore how trust and equal partnerships between volunteers and professional staff can be built and sustained. Trial registration: NCT04678310. Registered 21/12/2020. [ABSTRACT FROM AUTHOR]

Ten cases are identified of an unusual type of mesoscale windstorm in the United Kingdom between 2006 and 2021. The windstorms, which occurred in association with frontal rainbands, produced wind damage swaths no more than 20–30km wide, but sometimes extending for several hundred kilometres, often with embedded tornadoes. Storm structure and evolution are explored for two cases using radar data, surface observations, a 1.5‐km gridlength model and damage reports obtained from social media platforms and post‐event damage surveys. Findings are summarised in the form of a conceptual model, and some questions are posed for future research. [ABSTRACT FROM AUTHOR]

Background: End-of-life (EoL) care volunteers in hospitals are a novel approach to support patients and their close ones. The iLIVE Volunteer Study supported hospital volunteer coordinators from five European countries to design and implement an EoL care volunteer service on general wards in their hospitals. This study aimed to identify and explore barriers and facilitators to the implementation of EoL care volunteer services in the five hospitals. Methods: Volunteer coordinators (VCs) from the Netherlands (NL), Norway (NO), Slovenia (SI), Spain (ES) and United Kingdom (UK) participated in a focus group interview and subsequent in-depth one-to-one interviews. A theory-inspired framework based on the five domains of the Consolidated Framework for Implementation Research (CFIR) was used for data collection and analysis. Results from the focus group were depicted in radar charts per hospital. Results: Barriers across all hospitals were the COVID-19 pandemic delaying the implementation process, and the lack of recognition of the added value of EoL care volunteers by hospital staff. Site-specific barriers were struggles with promoting the service in a highly structured setting with many stakeholders (NL), negative views among nurses on hospital volunteering (NL, NO), a lack of support from healthcare professionals and the management (SI, ES), and uncertainty about their role in implementation among VCs (ES). Site-specific facilitators were training of volunteers (NO, SI, NL), involving volunteers in promoting the service (NO), and education and awareness for healthcare professionals about the role and boundaries of volunteers (UK). Conclusion: Establishing a comprehensive EoL care volunteer service for patients in non-specialist palliative care wards involves multiple considerations including training, creating awareness and ensuring management support. Implementation requires involvement of stakeholders in a way that enables medical EoL care and volunteering to co-exist. Further research is needed to explore how trust and equal partnerships between volunteers and professional staff can be built and sustained. Trial registration: NCT04678310. Registered 21/12/2020. [ABSTRACT FROM AUTHOR]

• High resolution E. coli data from a mixed UK catchment with field and sewer inputs. • New model for acute impacts using travel times from spatially distributed sources. • Sewer overflow sensors and radar rainfall used to characterize source loadings. • Application for forecasting arrival time of elevated E. coli levels. • Disaggregation of model output shows E.coli source is a function of the rainfall. Surface water quality is frequently impacted by acute rainfall driven pollutant sources such as sewer overflows. Understanding the risk of exposure from faecal pollution from short term impacts is challenging due to a paucity of high-resolution data from river systems. This paper proposes practical modelling approach for forecasting arrival time and durations of elevated E. coli levels based on hydrological routing of catchment source loadings, characterized by distributed and remote sensing techniques (including sewer overflow monitoring). The model is calibrated and validated using new high resolution E. coli datasets from a UK catchment featuring both diffuse field runoff and storm overflow impacts. Hourly/Bihourly sampling of E. coli was undertaken in the river following different rainfall events across a range of seasonal conditions. The model provides a good estimate of arrival times and durations of elevated E. coli periods following rainfall events. Model simulations suggest that key sources in the catchment are event specific, with sewer overflow spills being more significant following short, intense rainfall events. [Display omitted] [ABSTRACT FROM AUTHOR]