Blending Bathymetry: Combination of image-derived parametric approximations and celerity data sets for nearshore bathymetry estimation

Estimation of nearshore bathymetry is important for accurate prediction of nearshore wave conditions. However, direct data collection is expensive and time-consuming while accurate airborne lidar-based survey is limited by breaking waves and decreased light penetration affected by water turbidity. Instead, tower-based platforms or Unmanned Aircraft System (UAS) can provide indirect video-based observations. The video-based time-series imagery provides wave celerity information and time-averaged (timex) or variance enhanced (var) images identify persistent regions of wave breaking. In this work, we propose a rapid and improved bathymetry estimation method that takes advantage of image-derived wave celerity and a first-order bathymetry estimate from Parameter Beach Tool (PBT), software that fits parameterized sandbar and slope forms to the timex or var images. Two different sources of the data, PBT and wave celerity, are combined or blended optimally based on their assumed accuracy in a statistical framework. The PBT-derived bathymetry serves as "prior" coarse-scale background information and then is updated and corrected with the imagery-derived wave data through the dispersion relationship, which results in a better bathymetry estimate that is consistent with imagery-based wave data. To illustrate the accuracy of our proposed method, imagery data sets collected in 2017 at the US Army EDRC's Field Research Facility in Duck, NC under different weather and wave height conditions are tested. Estimated bathymetry profiles are remarkably close to the direct survey data. The computational time for the estimation from PBT-based bathymetry and imagery-derived wave celerity is only about five minutes on a free Google Cloud node with one CPU core. These promising results indicate the feasibility of reliable real-time bathymetry imaging during a single flight of UAS.Comment: 21 pages, 14 figures, preprint

Development, Validation, and Limits of Freezing of Gait Detection Using a Single Waist-Worn Device

Objective: Freezing of Gait (FOG) often described as the sensation of “the feet being glued to the ground” is prevalent in people with Parkinson's disease (PD) and severely disturbs mobility. In addition to tracking disease progression, precise detection of the exact boundaries for each FOG episode may enable new technologies capable of “breaking” FOG in real time. This study investigates the limits of sensitivity and performance for automatic device-based FOG detection. Methods: Eight machine-learning classifiers (including Neural Networks, Ensemble & Support Vector Machine) were developed using (i) accelerometer and (ii) accelerometer and gyroscope data from a waist-worn device. While wearing the device, 107 people with PD completed a walking and mobility task designed to elicit FOG. Two clinicians independently annotated the precise FOG episodes using synchronized video according to international guidelines, which were incorporated into a flowchart algorithm developed for this study. Device-detected FOG episodes were compared to the annotated FOG episodes using 10-fold cross-validation to determine accuracy and with Interclass Correlation Coefficients (ICC) to assess level of agreement. Results: Development used 50,962 windows of data representing over 10 hours of data and annotated activities. Very strong agreement between clinicians for precise FOG episodes was observed (90% sensitivity, 92% specificity and ICC 1,1 = 0.97 for total FOG duration). Device-based performance varied by method, complexity and cost matrix. The Neural Network that used only 67 accelerometer features provided a good balance between high sensitivity to FOG (89% sensitivity, 81% specificity and ICC 1,1 = 0.83) and solution stability (validation loss ≤ 5%). Conclusion: The waist-worn device consistently reported accurate detection of precise FOG episodes and compared well to more complex systems. The superior agreement between clinicians indicates there is room to improve future device-based FOG detection by using larger and more varied data sets. Significance: This study has clinical implications with regard to improving PD care by reducing reliance on clinical FOG assessments and time-consuming visual inspection. It shows high sensitivity to automatically detect FOG is possible

Development, Validation, and Limits of Freezing of Gait Detection Using a Single Waist-Worn Device

Objective: Freezing of Gait (FOG) often described as the sensation of “the feet being glued to the ground” is prevalent in people with Parkinson's disease (PD) and severely disturbs mobility. In addition to tracking disease progression, precise detection of the exact boundaries for each FOG episode may enable new technologies capable of “breaking” FOG in real time. This study investigates the limits of sensitivity and performance for automatic device-based FOG detection. Methods: Eight machine-learning classifiers (including Neural Networks, Ensemble & Support Vector Machine) were developed using (i) accelerometer and (ii) accelerometer and gyroscope data from a waist-worn device. While wearing the device, 107 people with PD completed a walking and mobility task designed to elicit FOG. Two clinicians independently annotated the precise FOG episodes using synchronized video according to international guidelines, which were incorporated into a flowchart algorithm developed for this study. Device-detected FOG episodes were compared to the annotated FOG episodes using 10-fold cross-validation to determine accuracy and with Interclass Correlation Coefficients (ICC) to assess level of agreement. Results: Development used 50,962 windows of data representing over 10 hours of data and annotated activities. Very strong agreement between clinicians for precise FOG episodes was observed (90% sensitivity, 92% specificity and ICC 1,1 = 0.97 for total FOG duration). Device-based performance varied by method, complexity and cost matrix. The Neural Network that used only 67 accelerometer features provided a good balance between high sensitivity to FOG (89% sensitivity, 81% specificity and ICC 1,1 = 0.83) and solution stability (validation loss ≤ 5%). Conclusion: The waist-worn device consistently reported accurate detection of precise FOG episodes and compared well to more complex systems. The superior agreement between clinicians indicates there is room to improve future device-based FOG detection by using larger and more varied data sets. Significance: This study has clinical implications with regard to improving PD care by reducing reliance on clinical FOG assessments and time-consuming visual inspection. It shows high sensitivity to automatically detect FOG is possible

Optimising the timing of renal replacement therapy in acute kidney injury

The optimal timing of renal replacement therapy (RRT) in critically ill patients with acute kidney injury (AKI) has been much debated. Over the past five years several studies have provided new guidance for evidence-based decision-making. High-quality evidence now supports an approach of expectant management in critically ill patients with AKI, where RRT may be deferred up to 72 h unless a life-threatening indication develops. Nevertheless, physicians’ judgment still plays a central role in identifying appropriate patients for expectant management

Rivastigmine for gait stability in patients with Parkinson's disease (ReSPonD): a randomised, double-blind, placebo-controlled, phase 2 trial

Background Falls are a frequent and serious complication of Parkinson's disease and are related partly to an underlying cholinergic deficit that contributes to gait and cognitive dysfunction in these patients. Gait dysfunction can lead to an increased variability of gait from one step to another, raising the likelihood of falls. In the ReSPonD trial we aimed to assess whether ameliorating this cholinergic deficit with the acetylcholinesterase inhibitor rivastigmine would reduce gait variability. Methods We did this randomised, double-blind, placebo-controlled, phase 2 trial at the North Bristol NHS Trust Hospital, Bristol, UK, in patients with Parkinson's disease recruited from community and hospital settings in the UK. We included patients who had fallen at least once in the year before enrolment, were able to walk 18 m without an aid, had no previous exposure to an acetylcholinesterase inhibitor, and did not have dementia. Our clinical trials unit randomly assigned (1:1) patients to oral rivastigmine or placebo capsules (both taken twice a day) using a computer-generated randomisation sequence and web-based allocation. Rivastigmine was uptitrated from 3 mg per day to the target dose of 12 mg per day over 12 weeks. Both the trial team and patients were masked to treatment allocation. Masking was achieved with matched placebo capsules and a dummy uptitration schedule. The primary endpoint was difference in step time variability between the two groups at 32 weeks, adjusted for baseline age, cognition, step time variability, and number of falls in the previous year. We measured step time variability with a triaxial accelerometer during an 18 m walking task in three conditions: normal walking, simple dual task with phonemic verbal fluency (walking while naming words beginning with a single letter), and complex dual task switching with phonemic verbal fluency (walking while naming words, alternating between two letters of the alphabet). Analysis was by modified intention to treat; we excluded from the primary analysis patients who withdrew, died, or did not attend the 32 week assessment. This trial is registered with ISRCTN, number 19880883. Findings Between Oct 4, 2012 and March 28, 2013, we enrolled 130 patients and randomly assigned 65 to the rivastigmine group and 65 to the placebo group. At week 32, compared with patients assigned to placebo (59 assessed), those assigned to rivastigmine (55 assessed) had improved step time variability for normal walking (ratio of geometric means 0·72, 95% CI 0·58–0·88; p=0·002) and the simple dual task (0·79; 0·62–0·99; p=0·045). Improvements in step time variability for the complex dual task did not differ between groups (0·81, 0·60–1·09; p=0·17). Gastrointestinal side-effects were more common in the rivastigmine group than in the placebo group (p<0·0001); 20 (31%) patients in the rivastigmine group versus three (5%) in the placebo group had nausea and 15 (17%) versus three (5%) had vomiting

Differential Growth Responses of Soil Bacterial Taxa to Carbon Substrates of Varying Chemical Recalcitrance

Soils are immensely diverse microbial habitats with thousands of co-existing bacterial, archaeal, and fungal species. Across broad spatial scales, factors such as pH and soil moisture appear to determine the diversity and structure of soil bacterial communities. Within any one site however, bacterial taxon diversity is high and factors maintaining this diversity are poorly resolved. Candidate factors include organic substrate availability and chemical recalcitrance, and given that they appear to structure bacterial communities at the phylum level, we examine whether these factors might structure bacterial communities at finer levels of taxonomic resolution. Analyzing 16S rRNA gene composition of nucleotide analog-labeled DNA by PhyloChip microarrays, we compare relative growth rates on organic substrates of increasing chemical recalcitrance of >2,200 bacterial taxa across 43 divisions/phyla. Taxa that increase in relative abundance with labile organic substrates (i.e., glycine, sucrose) are numerous (>500), phylogenetically clustered, and occur predominantly in two phyla (Proteobacteria and Actinobacteria) including orders Actinomycetales, Enterobacteriales, Burkholderiales, Rhodocyclales, Alteromonadales, and Pseudomonadales. Taxa increasing in relative abundance with more chemically recalcitrant substrates (i.e., cellulose, lignin, or tannin–protein) are fewer (168) but more phylogenetically dispersed, occurring across eight phyla and including Clostridiales, Sphingomonadalaes, Desulfovibrionales. Just over 6% of detected taxa, including many Burkholderiales increase in relative abundance with both labile and chemically recalcitrant substrates. Estimates of median rRNA copy number per genome of responding taxa demonstrate that these patterns are broadly consistent with bacterial growth strategies. Taken together, these data suggest that changes in availability of intrinsically labile substrates may result in predictable shifts in soil bacterial composition

Quantum Hall Effect in a Holographic Model

We consider a holographic description of a system of strongly coupled fermions in 2+1 dimensions based on a D7-brane probe in the background of D3-branes, and construct stable embeddings by turning on worldvolume fluxes. We study the system at finite temperature and charge density, and in the presence of a background magnetic field. We show that Minkowski-like embeddings that terminate above the horizon describe a family of quantum Hall states with filling fractions that are parameterized by a single discrete parameter. The quantization of the Hall conductivity is a direct consequence of the topological quantization of the fluxes. When the magnetic field is varied relative to the charge density away from these discrete filling fractions, the embeddings deform continuously into black-hole-like embeddings that enter the horizon and that describe metallic states. We also study the thermodynamics of this system and show that there is a first order phase transition at a critical temperature from the quantum Hall state to the metallic state.Comment: v2: 27 pages, 12 figures. There is a major revision in the quantitative analysis. The qualitative results and conclusions are unchanged, with one exception: we show that the quantum Hall state embeddings, which exist for discrete values of the filling fraction, deform continuously into metallic state embeddings away from these filling fraction

Analysis of sloppiness in model simulations: unveiling parameter uncertainty when mathematical models are fitted to data

This work introduces a Bayesian approach to assess the sensitivity of model outputs to changes in parameter values, constrained by the combination of prior beliefs and data. This novel approach identifies stiff parameter combinations that strongly affect the quality of the model-data fit while simultaneously revealing which of these key parameter combinations are informed primarily from the data or are also substantively influenced by the priors. We focus on the very common context in complex systems where the amount and quality of data are low compared to the number of model parameters to be collectively estimated, and showcase the benefits of our technique for applications in biochemistry, ecology, and cardiac electrophysiology. We also show how stiff parameter combinations, once identified, uncover controlling mechanisms underlying the system being modeled and inform which of the model parameters need to be prioritized in future experiments for improved parameter inference from collective model-data fitting

Single-crystal to cingle-crystal addition of H2to [Ir(iPr-PONOP)(propene)][BArF4] and comparison between solid-state and solution reactivity

The EPSRC (EP/M024210/2, EP/T019867/1), SCG Chemicals, The Clarendon Trust, The Leverhulme Trust (RPG-2020-184), Diamond Light Source for funding (PhD studentship to AM).The reactivity of the Ir(I) PONOP pincer complex [Ir(iPr-PONOP)(η2-propene)][BArF4], 6, [iPr-PONOP = 2,6-(iPr2PO)2C6H3N, ArF= 3,5-(CF3)2C6H3] was studied in solution and the solid state, both experimentally, using molecular density functional theory (DFT) and periodic-DFT computational methods, as well as in situ single-crystal to single-crystal (SC-SC) techniques. Complex 6 is synthesized in solution from sequential addition of H2and propene, and then the application of vacuum, to [Ir(iPr-PONOP)(η2-COD)][BArF4], 1, a reaction manifold that proceeds via the Ir(III) dihydrogen/dihydride complex [Ir(iPr-PONOP)(H2)H2][BArF4], 2, and the Ir(III) dihydride propene complex [Ir(iPr-PONOP)(η2-propene)H2][BArF4], 7, respectively. In solution (CD2Cl2) 6 undergoes rapid reaction with H2to form dihydride 7 and then a slow (3 d) onward reaction to give dihydrogen/dihydride 2 and propane. DFT calculations on the molecular cation in solution support this slow, but productive, reaction, with a calculated barrier to rate-limiting propene migratory insertion of 24.8 kcal/mol. In the solid state single-crystals of 6 also form complex 7 on addition of H2in an SC-SC reaction, but unlike in solution the onward reaction (i.e., insertion) does not occur, as confirmed by labeling studies using D2. The solid-state structure of 7 reveals that, on addition of H2to 6, the PONOP ligand moves by 90° within a cavity of [BArF4]-anions rather than the alkene moving. Periodic DFT calculations support the higher barrier to insertion in the solid state (ΔG‡= 26.0 kcal/mol), demonstrating that the single-crystal environment gates onward reactivity compared to solution. H2addition to 6 to form 7 is reversible in both solution and the solid state, but in the latter crystallinity is lost. A rare example of a sigma amine-borane pincer complex, [Ir(iPr-PONOP)H2(η1-H3B·NMe3)][BArF4], 5, is also reported as part of these studies.Peer reviewe

Continental-scale animal tracking reveals functional movement classes across marine taxa

Acoustic telemetry is a principle tool for observing aquatic animals, but coverage over large spatial scales remains a challenge. To resolve this, Australia has implemented the Integrated Marine Observing System's Animal Tracking Facility which comprises a continental-scale hydrophone array and coordinated data repository. This national acoustic network connects localized projects, enabling simultaneous monitoring of multiple species over scales ranging from 100 s of meters to 1000 s of kilometers. There is a need to evaluate the utility of this national network in monitoring animal movement ecology, and to identify the spatial scales that the network effectively operates over. Cluster analyses assessed movements and residency of 2181 individuals from 92 species, and identified four functional movement classes apparent only through aggregating data across the entire national network. These functional movement classes described movement metrics of individuals rather than species, and highlighted the plasticity of movement patterns across and within populations and species. Network analyses assessed the utility and redundancy of each component of the national network, revealing multiple spatial scales of connectivity influenced by the geographic positioning of acoustic receivers. We demonstrate the significance of this nationally coordinated network of receivers to better reveal intra-specific differences in movement profiles and discuss implications for effective management