Efficient Emulation of Radiative Transfer Codes Using Gaussian Processes and Application to Land Surface Parameter Inferences

There is an increasing need to consistently combine observations from different sensors to monitor the state of the land surface. In order to achieve this, robust methods based on the inversion of radiative transfer (RT) models can be used to interpret the satellite observations. This typically results in an inverse problem, but a major drawback of these methods is the computational complexity. We introduce the concept of Gaussian Process (GP) emulators: surrogate functions that accurately approximate RT models using a small set of input (e.g., leaf area index, leaf chlorophyll, etc.) and output (e.g., top-of-canopy reflectances or at sensor radiances) pairs. The emulators quantify the uncertainty of their approximation, and provide a fast and easy route to estimating the Jacobian of the original model, enabling the use of e.g., efficient gradient descent methods. We demonstrate the emulation of widely used RT models (PROSAIL and SEMIDISCRETE) and the coupling of vegetation and atmospheric (6S) RT models targetting particular sensor bands. A comparison with the full original model outputs shows that the emulators are a viable option to replace the original model, with negligible bias and discrepancies which are much smaller than the typical uncertainty in the observations. We also extend the theory of GP to cope with models with multivariate outputs (e.g., over the full solar reflective domain), and apply this to the emulation of PROSAIL, coupled 6S and PROSAIL and to the emulation of individual spectral components of 6S. In all cases, emulators successfully predict the full model output as well as accurately predict the gradient of the model calculated by finite differences, and produce speed ups between 10,000 and 50,000 times that of the original model. Finally, we use emulators to invert leaf area index ( L A I ), leaf chlorophyll content ( C a b ) and equivalent leaf water thickness ( C w ) from a time series of observations from Sentinel-2/MSI, Sentinel-3/SLSTR and Proba-V observations. We use sophisticated Hamiltonian Markov Chain Monte Carlo (MCMC) methods that exploit the speed of the emulators as well as the gradient estimation, a variational data assimilation (DA) method that extends the problem with temporal regularisation, and a particle filter using a regularisation model. The variational and particle filter approach appear more successful (meaning parameters closer to the truth, and smaller uncertainties) than the MCMC approach as a result of using the temporal regularisation mode. These work therefore suggests that GP emulators are a practical way to implement sophisticated parameter retrieval schemes in an era of increasing data volumes

Results of a Case Study on Quantifying Fuel Use and Emissions for a Bridge Replacement Project

ABSTRACT As the nation moves toward more sustainable energy and environmental standards, it is important to examine all sources of fuel consumption and pollution, including heavy-duty diesel (HDD) construction equipment. In order to quantify these sources at the project level, they must be identified with their respective activities. A case study was performed on an Oklahoma Department of Transportation (ODOT) bridge replacement project in order to establish a baseline of real-world activity, equipment, fuel use, and emissions data. This data was collected on a daily basis via jobsite visits and included specific information such as the equipment's model year, engine horsepower, and hours worked. These data were used to estimate fuel use and emissions based on calculations from the EPA's NONROAD model. Using these estimates, traditional project management techniques were expanded to evaluate the energy and environmental impacts of the project, in addition to the economic impacts. Histograms and cumulative frequency diagrams (s-curves) were created to summarize fuel use and emissions on a daily and project total basis. These results were combined with the preliminary and final ODOT pay items and quantities to define new fuel use and emission factors based on quantity of work completed, dollars of work completed, and specific activities. Recommendations include using the new fuel use and emission factors to identify activities with high energy and environmental impacts as well as evaluating various mitigation strategies. INTRODUCTION In order to build new, demolish old, or refurbish existing infrastructure, heavy duty diesel (HDD) equipment must be used. This equipment requires fossil fuel for energy and emits air pollutants that are harmful to the environment and human health. HDD equipment is a substantial contributor to this growing problem. New ways to quantify and characterize this pollution problem must be found in order to reduce and mitigate it. Diesel exhaust (DE) poses risks for humans and the environment (EPA 2003). For example, tiny particles found in DE, known as particulate matter (PM), may cause lung damage as well as aggravate existing respiratory diseases. DE also contains nitrogen oxides (NO x ) and hydrocarbons (HC) which are precursors to ozone. Carbon monoxide (CO) is another air pollutant found in DE that adversely affects human health and may even cause death in high concentrations, althoug

Characterization of the near-Earth Asteroid 2002NY40

In August 2002, the near-Earth asteroid 2002 NY40, made its closest approach to the Earth. This provided an opportunity to study a near-Earth asteroid with a variety of instruments. Several of the telescopes at the Maui Space Surveillance System were trained at the asteroid and collected adaptive optics images, photometry and spectroscopy. Analysis of the imagery reveals the asteroid is triangular shaped with significant self-shadowing. The photometry reveals a 20-hour period and the spectroscopy shows that the asteroid is a Q-type

Effects of local hypothermia-rewarming on physiology, metabolism and inflammation of acutely injured human spinal cord.

In five patients with acute, severe thoracic traumatic spinal cord injuries (TSCIs), American spinal injuries association Impairment Scale (AIS) grades A-C, we induced cord hypothermia (33 °C) then rewarming (37 °C). A pressure probe and a microdialysis catheter were placed intradurally at the injury site to monitor intraspinal pressure (ISP), spinal cord perfusion pressure (SCPP), tissue metabolism and inflammation. Cord hypothermia-rewarming, applied to awake patients, did not cause discomfort or neurological deterioration. Cooling did not affect cord physiology (ISP, SCPP), but markedly altered cord metabolism (increased glucose, lactate, lactate/pyruvate ratio (LPR), glutamate; decreased glycerol) and markedly reduced cord inflammation (reduced IL1β, IL8, MCP, MIP1α, MIP1β). Compared with pre-cooling baseline, rewarming was associated with significantly worse cord physiology (increased ICP, decreased SCPP), cord metabolism (increased lactate, LPR; decreased glucose, glycerol) and cord inflammation (increased IL1β, IL8, IL4, IL10, MCP, MIP1α). The study was terminated because three patients developed delayed wound infections. At 18-months, two patients improved and three stayed the same. We conclude that, after TSCI, hypothermia is potentially beneficial by reducing cord inflammation, though after rewarming these benefits are lost due to increases in cord swelling, ischemia and inflammation. We thus urge caution when using hypothermia-rewarming therapeutically in TSCI

A Compromise between Neutrino Masses and Collider Signatures in the Type-II Seesaw Model

A natural extension of the standard $SU(2)_{\rm L} \times U(1)_{\rm Y}$ gauge model to accommodate massive neutrinos is to introduce one Higgs triplet and three right-handed Majorana neutrinos, leading to a $6\times 6$ neutrino mass matrix which contains three $3\times 3$ sub-matrices $M_{\rm L}$, $M_{\rm D}$ and $M_{\rm R}$. We show that three light Majorana neutrinos (i.e., the mass eigenstates of $\nu_e$, $\nu_\mu$ and $\nu_\tau$) are exactly massless in this model, if and only if $M_{\rm L} = M_{\rm D} M_{\rm R}^{-1} M_{\rm D}^T$ exactly holds. This no-go theorem implies that small but non-vanishing neutrino masses may result from a significant but incomplete cancellation between $M_{\rm L}$ and $M_{\rm D} M_{\rm R}^{-1} M_{\rm D}^T$ terms in the Type-II seesaw formula, provided three right-handed Majorana neutrinos are of ${\cal O}(1)$ TeV and experimentally detectable at the LHC. We propose three simple Type-II seesaw scenarios with the $A_4 \times U(1)_{\rm X}$ flavor symmetry to interpret the observed neutrino mass spectrum and neutrino mixing pattern. Such a TeV-scale neutrino model can be tested in two complementary ways: (1) searching for possible collider signatures of lepton number violation induced by the right-handed Majorana neutrinos and doubly-charged Higgs particles; and (2) searching for possible consequences of unitarity violation of the $3\times 3$ neutrino mixing matrix in the future long-baseline neutrino oscillation experiments.Comment: RevTeX 19 pages, no figure

Identification of autoantigens and their potential post-translational modification in EGPA and severe eosinophilic asthma.

BACKGROUND: The chronic airway inflammation in severe eosinophilic asthma (SEA) suggests potential autoimmune aetiology with unidentified autoantibodies analogous to myeloperoxidase (MPO) in ANCA-positive EGPA (eosinophilic granulomatosis with polyangiitis). Previous research has shown that oxidative post-translational modification (oxPTM) of proteins is an important mechanism by which autoantibody responses may escape immune tolerance. Autoantibodies to oxPTM autoantigens in SEA have not previously been studied. METHODS: Patients with EGPA and SEA were recruited as well as healthy control participants. Autoantigen agnostic approach: Participant serum was incubated with slides of unstimulated and PMA-stimulated neutrophils and eosinophils, and autoantibodies to granulocytes were identified by immunofluorescence with anti-human IgG FITC antibody. Target autoantigen approach: Candidate proteins were identified from previous literature and FANTOM5 gene set analysis for eosinophil expressed proteins. Serum IgG autoantibodies to these proteins, in native and oxPTM form, were detected by indirect ELISA. RESULTS: Immunofluorescence studies showed that serum from patients with known ANCA stained for IgG against neutrophils as expected. In addition, serum from 9 of 17 tested SEA patients stained for IgG to PMA-stimulated neutrophils undergoing NETosis. Immunofluorescent staining of eosinophil slides was evident with serum from all participants (healthy and with eosinophilic disease) with diffuse cytoplasmic staining except for one SEA individual in whom subtle nuclear staining was evident. FANTOM5 gene set analysis identified TREM1 (triggering receptor expressed on myeloid cells 1) and IL-1 receptor 2 (IL1R2) as eosinophil-specific targets to test for autoantibody responses in addition to MPO, eosinophil peroxidase (EPX), and Collagen-V identified from previous literature. Indirect ELISAs found high concentrations of serum autoantibodies to Collagen-V, MPO, and TREM1 in a higher proportion of SEA patients than healthy controls. High concentrations of serum autoantibodies to EPX were evident in serum from both healthy and SEA participants. The proportion of patients with positive autoantibody ELISAs was not increased when examining oxPTM compared to native proteins. DISCUSSION: Although none of the target proteins studied showed high sensitivity for SEA, the high proportion of patients positive for at least one serum autoantibody shows the potential of more research on autoantibody serology to improve diagnostic testing for severe asthma. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier, NCT04671446

Tidal stream resource characterisation in progressive versus standing wave systems

© 2018 The Author(s) Characterisations of the tidal stream resource and its variability over various timescales are crucial for the development of the tidal stream energy industry. To date, no research has compared resource sensitivity in standing wave (when peak currents occur midway between high and low water) and progressive wave (where peak currents occur at high and low water) tidal systems. Here, we compare the flow regimes of standing wave versus progressive wave systems and the associated variations in tidal stream power with applications to device deployment options (floating-platform turbines versus bottom-mounted turbines). We use a validated 3D numerical model (ROMS) of a globally-significant tidal energy shelf sea region (Irish Sea), to test the hypotheses that the influence on potential extractable energy, and suitability for different devices, may be markedly different between these contrasting systems. Power density was also calculated and compared for floating versus bottom-mounted devices using in-situ current data (ADCPs) obtained from a standing wave site and a progressive wave site. We show that progressive wave systems are characterised by velocity-asymmetry over a tidal cycle (i.e. stronger peak flows at high water than at low water), leading to power-asymmetry. Such power asymmetry was shown to have more of an effect on floating device technology, where an assumed turbine depth tracks the sea surface, in contrast to bottom-mounted technology, where the hub height is fixed at a certain position above the sea bed. Shallow, high-flow regions where tidal range is large contained up to 2.5% more power density from bottom-mounted compared with floating turbines; however, there were areas where floating devices were exposed to higher mean currents over a tidal cycle. Standing wave systems, where flow asymmetry is minimised, did not particularly favour either technology. The results highlight the requirement for detailed resource assessments to consider the vertical plane, and are applicable to all potential tidal stream energy sites

Testing for Network and Spatial Autocorrelation

Testing for dependence has been a well-established component of spatial statistical analyses for decades. In particular, several popular test statistics have desirable properties for testing for the presence of spatial autocorrelation in continuous variables. In this paper we propose two contributions to the literature on tests for autocorrelation. First, we propose a new test for autocorrelation in categorical variables. While some methods currently exist for assessing spatial autocorrelation in categorical variables, the most popular method is unwieldy, somewhat ad hoc, and fails to provide grounds for a single omnibus test. Second, we discuss the importance of testing for autocorrelation in data sampled from the nodes of a network, motivated by social network applications. We demonstrate that our proposed statistic for categorical variables can both be used in the spatial and network setting