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A new luminescence erosion meter has huge potential for inferring erosion rates on sub-millennial scales for both steady and transient states of erosion, which is not currently possible with any existing techniques capable of measuring erosion. This study applies new rock luminescence techniques to a well-constrained scenario provided by the Beinn Alligin rock avalanche, NW Scotland. Boulders in this deposit are lithologically consistent and have known cosmogenic nuclide ages and independently derived Holocene erosion rates. We find that luminescence-derived exposure ages for the Beinn Alligin rock avalanche were an order of magnitude younger than existing cosmogenic nuclide exposure ages, suggestive of high erosion rates (as supported by field evidence of quartz grain protrusions on the rock surfaces). Erosion rates determined by luminescence were consistent with independently derived rates measured from boulder edge roundness. Inversion modelling indicates a transient state of erosion reflecting the stochastic nature of erosional processes over the last ∼4.5 kyr in the wet, temperate climate of NW Scotland. Erosion was likely modulated by known fluctuations in moisture availability and to a lesser extent temperature, which controlled the extent of chemical weathering of these highly lithified rocks prior to erosion. The use of a multi-elevated temperature, post-infra-red, infra-red stimulated luminescence (MET-pIRIR) protocol (50, 150 and 225 ∘C) was advantageous as it identified samples with complexities that would not have been observed using only the standard infra-red stimulated luminescence (IRSL) signal measured at 50 ∘C, such as that introduced by within-sample variability (e.g. surficial coatings). This study demonstrates that the luminescence erosion meter can infer accurate erosion rates on sub-millennial scales and identify transient states of erosion (i.e. stochastic processes) in agreement with independently derived erosion rates for the same deposit.

Strong winds may uproot and break trees and represent a major natural disturbance for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the effects of climate change. Despite the importance of such natural disturbances, there are currently no spatially explicit databases of wind-related impact at a pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND is comprised of more than 80 000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018 and describes them in a harmonized and consistent geographical vector format. The database includes all major windstorms that occurred over the observational period (e.g. Gudrun, Kyrill, Klaus, Xynthia and Vaia) and represents approximately 30 % of the reported damaging wind events in Europe. Correlation analyses between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p value < 0.05). When recorded forest areas are rescaled based on their damage degree, correlation increases to 0.54. Wind-damaged growing stock volumes reported in national inventories (FORESTORM dataset) are generally higher than analogous metrics provided by FORWIND in combination with satellite-based biomass and country-scale statistics of growing stock volume. The potential of FORWIND is explored for a range of challenging topics and scientific fields, including scaling relations of wind damage, forest vulnerability modelling, remote sensing monitoring of forest disturbance, representation of uprooting and breakage of trees in large-scale land surface models, and hydrogeological risks following wind damage. Overall, FORWIND represents an essential and open-access spatial source that can be used to improve the understanding, detection and prediction of wind disturbances and the consequent impacts on forest ecosystems and the land–atmosphere system. Data sharing is encouraged in order to continuously update and improve FORWIND. The dataset is available at https://doi.org/10.6084/m9.figshare.9555008 (Forzieri et al., 2019).

Following the general warming trend in Greenland, an increase in calving rates, retreat and ice flow has been observed at ocean-terminating outlet glaciers. These changes contribute substantially to the current mass loss of the Greenland Ice Sheet. In order to constrain models of ice dynamics as well as estimates of mass change, detailed knowledge of geometry and ice flow is needed, in particular on the rapidly changing tongues of ocean-terminating outlet glaciers. In this study, we validate velocity estimates and spatial patterns close to the calving terminus of such an outlet derived from an iterative offset-tracking method based on synthetic aperture radar (SAR) intensity data with a collection of three independent reference measurements of glacier flow. These reference datasets are comprised of measurements from differential GPS, a terrestrial radar interferometer (TRI) and repeated unmanned aerial vehicle (UAV) surveys. Our approach to SAR velocity processing aims at achieving a relatively fine grid spacing and a high temporal resolution in order to best resolve the steep velocity gradients in the terminus area and aims to exploit the 12 d repeat interval of the single-satellite Sentinel-1A sensor. Results from images of the medium-sized ocean-terminating outlet glacier Eqip Sermia acquired by Sentinel-1A and RADARSAT-2 exhibit a mean difference of 11.5 % when compared to the corresponding GPS measurements. An areal comparison of our SAR velocity fields with independently generated velocity maps from TRI and UAV surveys showed good agreement in magnitude and spatial patterns, with mean differences smaller than 0.7 m d−1. In comparison with existing operational velocity products, our SAR-derived velocities show an improved spatial velocity pattern near the margins and calving front. There 8 % to 30 % higher surface ice velocities are produced, which has implications on ice fluxes and on mass budget estimates of similarly sized outlet glaciers. Further, we show that offset tracking from SAR intensity data at relatively low spatio-temporal sampling intervals is a valid method to derive glacier flow fields for fast-flowing glacier termini of outlet glaciers and, given the repeat period of 12 d of the Sentinel-1A sensor (6 d with Sentinel-1B), has the potential to be applied operationally in a quasi-continuous mode.

Earth's extant ice sheets are of great societal importance given their ongoing and potential future contributions to sea-level rise. Numerical models of ice sheets are designed to simulate ice-sheet behaviour in response to climate changes but to be improved require validation against observations. The direct observational record of extant ice sheets is limited to a few recent decades, but there is a large and growing body of geochronological evidence spanning millennia constraining the behaviour of palaeo-ice sheets. Hindcasts can be used to improve model formulations and study interactions between ice sheets, the climate system and landscape. However, ice-sheet modelling results have inherent quantitative errors stemming from parameter uncertainty and their internal dynamics, leading many modellers to perform ensemble simulations, while uncertainty in geochronological evidence necessitates expert interpretation. Quantitative tools are essential to examine which members of an ice-sheet model ensemble best fit the constraints provided by geochronological data. We present the Automated Timing Accordance Tool (ATAT version 1.1) used to quantify differences between model results and geochronological data on the timing of ice-sheet advance and/or retreat. To demonstrate its utility, we perform three simplified ice-sheet modelling experiments of the former British–Irish ice sheet. These illustrate how ATAT can be used to quantify model performance, either by using the discrete locations where the data originated together with dating constraints or by comparing model outputs with empirically derived reconstructions that have used these data along with wider expert knowledge. The ATAT code is made available and can be used by ice-sheet modellers to quantify the goodness of fit of hindcasts. ATAT may also be useful for highlighting data inconsistent with glaciological principles or reconstructions that cannot be replicated by an ice-sheet model.

Before applying change detection, high resolution SAR (Synthetic Aperture Radar) imagery benefits from advanced denoising mechanisms to preserve details and minimize speckle. We propose a change detector based on a MCA (Morphological Components Analysis) of a difference image (DI). With MCA, the data is decomposed into image features utilizing sparse representations of the image content. By introducing a priori knowledge of the content of the scenes, and exploiting shape information corresponding to the changes provided by MCA, we can significantly improve performance under adverse conditions, such as inconsistent acquisition geometries.

The phase estimation of cross-track multibaseline synthetic aperture interferometric data is usually thought to be very efficiently achieved using the maximum likelihood (ML) method. The suitability of this method is investigated here as applied to airborne single pass multibaseline data. Experimental interferometric data acquired with a Ka-band sensor were processed using (a) a ML method that fuses the complex data from all receivers and (b) a coarse-to-fine method that only uses the intermediate baselines to unwrap the phase values from the longest baseline. The phase noise was analyzed for both methods: in most cases, a small improvement was found when the ML method was used.

In this paper, we describe a unified algorithm for locating and computing hyperbolic trajectories, and then computing their stable and unstable manifolds, for finite time velocity fields in the form of a data set defined on a space-time grid. The algorithm is applied to a turbulent regime of a quasigeostrophic wind-driven double gyre in a rectangular domain.

In this paper we develop analytical and numerical methods for finding special hyperbolic trajectories that govern geometry of Lagrangian structures in time-dependent vector fields. The vector fields (or velocity fields) may have arbitrary time dependence and be realized only as data sets over finite time intervals, where space and time are discretized. While the notion of a hyperbolic trajectory is central to dynamical systems theory, much of the theoretical developments for Lagrangian transport proceed under the assumption that such a special hyperbolic trajectory exists. This brings in new mathematical issues that must be addressed in order for Lagrangian transport theory to be applicable in practice, i.e. how to determine whether or not such a trajectory exists and, if it does exist, how to identify it in a sequence of instantaneous velocity fields. We address these issues by developing the notion of a distinguished hyperbolic trajectory (DHT). We develop an existence criteria for certain classes of DHTs in general time-dependent velocity fields, based on the time evolution of Eulerian structures that are observed in individual instantaneous fields over the entire time interval of the data set. We demonstrate the concept of DHTs in inhomogeneous (or "forced") time-dependent linear systems and develop a theory and analytical formula for computing DHTs. Throughout this work the notion of linearization is very important. This is not surprising since hyperbolicity is a "linearized" notion. To extend the analytical formula to more general nonlinear time-dependent velocity fields, we develop a series of coordinate transforms including a type of linearization that is not typically used in dynamical systems theory. We refer to it as Eulerian linearization, which is related to the frame independence of DHTs, as opposed to the Lagrangian linearization, which is typical in dynamical systems theory, which is used in the computation of Lyapunov exponents. We present the numerical implementation of our method which can be applied to the velocity field given as a data set. The main innovation of our method is that it provides an approximation to the DHT for the entire time-interval of the data set. This offers a great advantage over the conventional methods that require certain regions to converge to the DHT in the appropriate direction of time and hence much of the data at the beginning and end of the time interval is lost.

Introduction Chronic pain affects 19% of adults in the United States, with increasing prevalence in active and aging populations. Pain can limit physical activity and activities of daily living (ADLs), resulting in declined mental and social health. Nutritional interventions for pain currently target inflammation or joint health, but few influence both. Collagen, the most abundant protein in the human body and constituent of the extra cellular matrix, is such a nutraceutical. While there have been reports of reductions in pain with short-term collagen peptide (CP) supplementation, there are no long-term studies specifically in healthy middle-aged active adults. Purpose To determine the effects of daily CP consumption over 3, 6, and 9 months on survey measures of pain, function, and physical and mental health using The Knee Injury & Osteoarthritis Outcomes Score (KOOS) and Veterans Rand 12 (VR-12) in middle-aged active adults. Methods This study was a double-blind randomized control trial with three treatment groups (Placebo, 10 g/d CP, and 20 g/d CP). Results Improvements in ADLs (p = .031, ηp2 = .096) and pain (p = .037, ηp2 = .164) were observed with 10 g/d CP over 6 months, although pain only improved in high frequency exercisers (>180 min/week). Additionally, VR-12 mental component scores (MCS) improved with 10 g/d of CP over 3–9 months (p = .017, ηp2 = .309), while physical component scores (PCS) improved with 20 g/d of CP over 3-9 months, but only in females (p = .013, ηp2= .582). Conclusion These findings suggest 10 to 20 g/d of CP supplementation over 6 to 9 months may improve ADLs, pain, MCS, and PCS in middle-aged active adults.

Rationale and objectives: Determine in cardiac amyloid (CA) patients, whether cardiac CT derived extracellular volume (ECV) correlates with that obtained by MRI. Perform this correlation with single (SECT) versus dual energy (DECT) CT and evaluate whether a single sample volume ECV-measure was as reliable as a global (16 segment) assessment. Materials and methods: CA patients who had undergone a clinical cardiac MRI (CMR) were recruited prospectively. SECT and DECT cardiac scans were performed. Three ECG-triggered prospective SECT scans were acquired: non-contrast, arterial-phase contrast and 5-minute delayed images. A DECT scan was performed at 7 min. Post processing was used to determine ECV. Analyses of SECT or DECT global ECV versus CMR were performed using the Pearson correlation coefficient, Bland Altman analysis and Intraclass correlation coefficient (ICC). Similar analyses were performed to examine the performance of single-segment sampling by SECT or DECT versus CMR. Results: 25 patients were recruited, mean age was 80.0 ± 7.1 years, 80 % were male, 21 patients had transthyretin- CA, 4 had light chain- CA. Correlations were close with both SECT or DECT global ECV versus CMR (r = 0.79 and 0.88 respectively, p

Pentatricopeptide repeat (PPR) proteins are considered a potential tool for manipulating organelle gene expression in plants because they can recognise a wide range of different RNA sequences, and the molecular basis for this sequence recognition is partially known and understood. A library of redesigned PPR proteins related to restorer-of-fertility proteins was created and transformed into plants in order to target mitochondrial transcripts. Ninety different variants tested in vivo showed a wide range of phenotypes. One of these lines, which displayed slow growth and downward curled leaves, showed a clear reduction in complex V. The phenotype was due to a specific cleavage of atp1 transcripts induced by a modified PPR protein from the library, validating the use of this library as a source of mitochondrial ‘mutants’. This study is a step towards developing specific RNA targeting tools using PPR proteins that can be aimed at desired targets.

Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ∼350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ∼100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.

Boundary layer and turbulent characteristics (surface fluxes, turbulent kinetic energy – TKE, turbulent kinetic energy dissipation rate – ϵ), along with synoptic-scale changes in these properties over time, are examined using data collected from 18 research flights made with the CIRPAS Twin Otter Aircraft. Data were collected during the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) at Point Alpha (20∘ S, 72∘ W) in October and November 2008 off the coast of South America. The average boundary layer depth is found to be 1148 m, with 28 % of the boundary layer profiles analyzed displaying decoupling. Analysis of correlation coefficients indicates that as atmospheric pressure decreases, the boundary layer height (zi) increases. As has been shown previously, the increase in zi is accompanied by a decrease in turbulence within the boundary layer. As zi increases, cooling near cloud top cannot sustain mixing over the entire depth of the boundary layer, resulting in less turbulence and boundary layer decoupling. As the latent heat flux (LHF) and sensible heat flux (SHF) increase, zi increases, along with the cloud thickness decreasing with increasing LHF. This suggests that an enhanced LHF results in enhanced entrainment, which acts to thin the cloud layer while deepening the boundary layer. A maximum in TKE on 1 November (both overall average and largest single value measured) is due to sub-cloud precipitation acting to destabilize the sub-cloud layer while acting to stabilize the cloud layer (through evaporation occurring away from the surface, primarily confined between a normalized boundary layer height, z/zi, of 0.40 to 0.60). Enhanced moisture above cloud top from a passing synoptic system also acts to reduce cloud-top cooling, reducing the potential for mixing of the cloud layer. This is observed in both the vertical profiles of the TKE and ϵ, in which it is found that the distributions of turbulence for the sub-cloud and in-cloud layer are completely offset from one another (i.e., the range of turbulent values measured have slight or no overlap for the in-cloud and sub-cloud regions), with the TKE in the sub-cloud layer maximizing for the analysis period, while the TKE in the in-cloud layer is below the average in-cloud value for the analysis period. Measures of vertical velocity variance, TKE, and the buoyancy flux averaged over all 18 flights display a maximum near cloud middle (between normalized in-cloud height, Z*, values of 0.25 and 0.75). A total of 10 of the 18 flights display two peaks in TKE within the cloud layer, one near cloud base and another near cloud top, signifying evaporative and radiational cooling near cloud top and latent heating near cloud base. Decoupled boundary layers tend to have a maximum in turbulence in the sub-cloud layer, with only a single peak in turbulence within the cloud layer.

Sea fog is a societally relevant phenomenon that occurs under the influence of specific oceanic and atmospheric conditions including aerosol conditions. The Yellow Sea region in China regularly experiences sea fog events, of varying intensity, that impact coastal regions and maritime activities. The occurrence and structure of fog are impacted by the concentration of aerosols in the air where the fog forms. Along with industrial development, air pollution has become a serious environmental problem in Northeastern China. These higher pollution levels are confirmed by various satellite remote sensing instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite that observes aerosol and cloud properties. These observations show a clear influence of aerosol loading over the Yellow Sea region, which can impact regional sea fog. In this study, high-resolution data sets from MODIS Aqua L2 are used to investigate the relationships between cloud properties and aerosol features. Using a bi-variate comparison method, we find that, for most cases, larger values of COT (cloud optical thickness) are related to both a smaller DER (droplet effective radius) and higher CTH (cloud top height). However, in the cases where fog is thinner with many zero values in CTH, the larger COT is related to both a smaller DER and CTH. For fog cases where the aerosol type is dominated by smoke (e.g., confirmed fire activities in the East China Plain), the semi-direct effect is indicated and may play a role in determining fog structure such that a smaller DER corresponds with thinner fog and smaller COT values. [ABSTRACT FROM AUTHOR]

Exercise-based, multimodal rehabilitation programming similar to that used in the existing models of cardiac or pulmonary rehabilitation or prehabilitation is a holistic potential solution to address the range of physical, psychological, and existential (e.g., as their diagnosis relates to potential death) stressors associated with a cancer diagnosis and subsequent treatment. The purpose of this study was to systematically evaluate the structure and format of any type of exercise-based, multimodal rehabilitation programs used in individuals with cancer and the evidence base for their real-world effectiveness on metrics of physical (e.g., cardiorespiratory fitness, blood pressure) and psychological (e.g., health-related quality of life) health. Very few of the 33 included exercise-based, multimodal rehabilitation programs employed intervention components, education topics, and program support staff that were multi-disciplinary or cancer-specific. In particular, a greater emphasis on nutrition care, and the evaluation and management of psychosocial distress and CVD risk factors, with cancer-specific adaptations, would broaden and maximize the holistic health benefits of exercise-based rehabilitation. Despite these opportunities for improvement, exercise-based, multimodal rehabilitation programs utilized under real-world settings in individuals with cancer produced clinically meaningful and large effect sizes for cardiorespiratory fitness (VO2peak, ±2.9 mL/kg/min, 95% CI = 2.6 to 3.3) and 6-minute walk distance (+47 meters, 95% CI = 23 to 71), and medium effect sizes for various measures of cancer-specific, health-related quality of life. However, there were no changes to blood pressure, body mass index, or lung function. Overall, these findings suggest that exercise-based, multimodal rehabilitation is a real-world therapy that improves physical and psychological health among individuals with cancer, but the holistic health benefits of this intervention would likely be enhanced by addressing nutrition, psychosocial concerns, and risk factor management through education and counselling with consideration of the needs of an individual with cancer.

Herein, the UV light photocatalytic activity of an Au101NC-AlSrTiO3-rGO nanocomposite comprising 1 wt% rGO, 0.05 wt% Au101(PPh3)21Cl5 (Au101NC), and AlSrTiO3 evaluated for H2 production. The synthesis of Au101NC-AlSrTiO3-rGO nanocomposite followed two distinct routes: (1) Au101NC was first mixed with AlSrTiO3 followed by the addition of rGO (Au101NC-AlSrTiO3:rGO) and (2) Au101NC was first mixed with rGO followed by the addition of AlSrTiO3 (Au101NC-rGO:AlSrTiO3). Both prepared samples were annealed in air at 210 °C for 15 min. Inductively coupled plasma mass spectrometry and high-resolution scanning transmission electron microscopy showed that the Au101NC adhered almost exclusively to the rGO in the nanocomposite and maintained a size less than 2 nm. Under UV light irradiation, the Au101NC-AlSrTiO3:rGO nanocomposite produced H2 at a rate 12 times greater than Au101NC-AlSrTiO3 and 64 times greater than AlSrTiO3. The enhanced photocatalytic activity is attributed to the small particle size and high loading of Au101NC, which is achieved by non-covalent binding to rGO. These results show that significant improvements can be made to AlSrTiO3-based photocatalysts that use cluster co-catalysts by the addition of rGO as an electron mediator to achieve high cluster loading and limited agglomeration of the clusters.

BACKGROUND:. Continuous electroencephalogram monitoring is associated with lower mortality in critically ill patients; however, it is underused due to the resource-intensive nature of manually interpreting prolonged streams of continuous electroencephalogram data. Here, we present a novel real-time, machine learning–based alerting and monitoring system for epilepsy and seizures that dramatically reduces the amount of manual electroencephalogram review. METHODS:. We developed a custom data reduction algorithm using a random forest and deployed it within an online cloud-based platform, which streams data and communicates interactively with caregivers via a web interface to display algorithm results. We developed real-time, machine learning–based alerting and monitoring system for epilepsy and seizures on continuous electroencephalogram recordings from 77 patients undergoing routine scalp ICU electroencephalogram monitoring and tested it on an additional 20 patients. RESULTS. We achieved a mean seizure sensitivity of 84% in cross-validation and 85% in testing, as well as a mean specificity of 83% in cross-validation and 86% in testing, corresponding to a high level of data reduction. This study validates a platform for machine learning–assisted continuous electroencephalogram analysis and represents a meaningful step toward improving utility and decreasing cost of continuous electroencephalogram monitoring. We also make our high-quality annotated dataset of 97 ICU continuous electroencephalogram recordings public for others to validate and improve upon our methods.

Abstract In this paper, we introduce a theoretical framework for optical trapping that integrates nonlinear polarization within the dipole approximation. This theory represents the most comprehensive analytic model to date capable of resolving the discrepancies between the observed and simulated trapping of plasmonic nanoparticles. Our theory elucidates how two-photon absorption can account for the stable trapping of gold nanoparticles, including their longitudinal stability, especially near their plasmon resonance. Furthermore, the experimentally observed split potential wells in the transverse plane, which are attributed to two-photon absorption, are in close agreement with our model’s predictions. Finally, this study provides new insights into the mechanism of optical trapping under conditions of intense light–matter interactions.