E2N: Error Estimation Networks for Goal-Oriented Mesh Adaptation

Given a partial differential equation (PDE), goal-oriented error estimation allows us to understand how errors in a diagnostic quantity of interest (QoI), or goal, occur and accumulate in a numerical approximation, for example using the finite element method. By decomposing the error estimates into contributions from individual elements, it is possible to formulate adaptation methods, which modify the mesh with the objective of minimising the resulting QoI error. However, the standard error estimate formulation involves the true adjoint solution, which is unknown in practice. As such, it is common practice to approximate it with an 'enriched' approximation (e.g. in a higher order space or on a refined mesh). Doing so generally results in a significant increase in computational cost, which can be a bottleneck compromising the competitiveness of (goal-oriented) adaptive simulations. The central idea of this paper is to develop a "data-driven" goal-oriented mesh adaptation approach through the selective replacement of the expensive error estimation step with an appropriately configured and trained neural network. In doing so, the error estimator may be obtained without even constructing the enriched spaces. An element-by-element construction is employed here, whereby local values of various parameters related to the mesh geometry and underlying problem physics are taken as inputs, and the corresponding contribution to the error estimator is taken as output. We demonstrate that this approach is able to obtain the same accuracy with a reduced computational cost, for adaptive mesh test cases related to flow around tidal turbines, which interact via their downstream wakes, and where the overall power output of the farm is taken as the QoI. Moreover, we demonstrate that the element-by-element approach implies reasonably low training costs.Comment: 27 pages, 14 figure

Phosphorous application improves drought tolerance of Phoebe zhennan

Phoebe zhennan (Gold Phoebe) is a threatened tree species in China and a valuable and important source of wood and bioactive compounds used in medicine. Apart from anthropogenic disturbances, several biotic constraints currently restrict its growth and development. However, little attention has been given to building adaptive strategies for its conservation by examining its morphological and physio-biochemical responses to drought stress, and the role of fertilizers on these responses. A randomized experimental design was used to investigate the effects of two levels of irrigation (well-watered and drought-stressed) and phosphorous (P) fertilization treatment (with and without P) to assess the morphological and physio-biochemical responses of P. zhennan seedlings to drought stress. In addition, we evaluated whether P application could mitigate the negative impacts of drought on plant growth and metabolism. Drought stress had a significant negative effect on the growth and metabolic processes of P. zhennan. Despite this, reduced leaf area, limited stomatal conductance, reduced transpiration rate, increased water use efficiency, enhanced antioxidant enzymes activities, and osmolytes accumulation suggested that the species has good adaptive strategies for tolerating drought stress. Application of P had a significant positive effect on root biomass, signifying its improved water extracting capacity from the soil. Moreover, P fertilization significantly increased leaf relative water content, net photosynthetic rate, and maximal quantum efficiency of PSII under drought stress conditions. This may be attributable to several factors, such as enhanced root biomass, decreased malondialdehyde content, and the up-regulation of chloroplast pigments, osmolytes, and nitrogenous compounds. However, P application had only a slight or negligible effect on the growth and metabolism of well-watered plants. In conclusion, P. zhennan has a strong capability for drought resistance, while P application facilitates and improves drought tolerance mostly through physio-biochemical adjustments, regardless of water availability. It is imperative to explore the underlying metabolic mechanisms and effects of different levels of P fertilization on P. zhennan under drought conditions in order to design appropriate conservation and management strategies for this species, which is at risk of extinction.Instituto de Fisiología Vegeta

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a hold-out test set. Similarities in network segmentations were evaluated using pairwise Dice correlations. Articular cartilage thickness was computed per-scan and longitudinally. Correlation between thickness error and segmentation metrics was measured using Pearson's coefficient. Two empirical upper bounds for ensemble performance were computed using combinations of model outputs that consolidated true positives and true negatives. Results: Six teams (T1-T6) submitted entries for the challenge. No significant differences were observed across all segmentation metrics for all tissues (p=1.0) among the four top-performing networks (T2, T3, T4, T6). Dice correlations between network pairs were high (>0.85). Per-scan thickness errors were negligible among T1-T4 (p=0.99) and longitudinal changes showed minimal bias (<0.03mm). Low correlations (<0.41) were observed between segmentation metrics and thickness error. The majority-vote ensemble was comparable to top performing networks (p=1.0). Empirical upper bound performances were similar for both combinations (p=1.0). Conclusion: Diverse networks learned to segment the knee similarly where high segmentation accuracy did not correlate to cartilage thickness accuracy. Voting ensembles did not outperform individual networks but may help regularize individual models.Comment: Submitted to Radiology: Artificial Intelligence; Fixed typo

Phosphorous application improves drought tolerance of Phoebe zhennan

Phoebe zhennan (Gold Phoebe) is a threatened tree species in China and a valuable and important source of wood and bioactive compounds used in medicine. Apart from anthropogenic disturbances, several biotic constraints currently restrict its growth and development. However, little attention has been given to building adaptive strategies for its conservation by examining its morphological and physio-biochemical responses to drought stress, and the role of fertilizers on these responses. A randomized experimental design was used to investigate the effects of two levels of irrigation (well-watered and drought-stressed) and phosphorous (P) fertilization treatment (with and without P) to assess the morphological and physio-biochemical responses of P. zhennan seedlings to drought stress. In addition, we evaluated whether P application could mitigate the negative impacts of drought on plant growth and metabolism. Drought stress had a significant negative effect on the growth and metabolic processes of P. zhennan. Despite this, reduced leaf area, limited stomatal conductance, reduced transpiration rate, increased water use efficiency, enhanced antioxidant enzymes activities, and osmolytes accumulation suggested that the species has good adaptive strategies for tolerating drought stress. Application of P had a significant positive effect on root biomass, signifying its improved water extracting capacity from the soil. Moreover, P fertilization significantly increased leaf relative water content, net photosynthetic rate, and maximal quantum efficiency of PSII under drought stress conditions. This may be attributable to several factors, such as enhanced root biomass, decreased malondialdehyde content, and the up-regulation of chloroplast pigments, osmolytes, and nitrogenous compounds. However, P application had only a slight or negligible effect on the growth and metabolism of well-watered plants. In conclusion, P. zhennan has a strong capability for drought resistance, while P application facilitates and improves drought tolerance mostly through physio-biochemical adjustments, regardless of water availability. It is imperative to explore the underlying metabolic mechanisms and effects of different levels of P fertilization on P. zhennan under drought conditions in order to design appropriate conservation and management strategies for this species, which is at risk of extinction.Instituto de Fisiología Vegeta

Relationship between climatic conditions and the relative abundance of modern C<inf>3</inf> and C<inf>4</inf> plants in three regions around the North Pacific

Using -24‰ and -14‰ as the endpoints of stable carbon isotopic composition of total organic carbon (δ13CTOC) of surface soil under pure C3 and C4 vegetation, and surface soil δ13CTOC data from eastern China, Australia and the Great Plains of North America, we estimate the relative abundance of C3/C4 plants (i. e., the ratio of C3 or C4 biomass to local primary production) in modern vegetation for each region. The relative abundance of modern C3/C4 vegetation from each region is compared to the corresponding climatic parameters (mean annual temperature and precipitation) to explore the relationship between relative C4 abundance and climate. The results indicate that temperature controls the growth of C4 plants. However, even where temperature is high enough for the growth of C4 plants, they will only dominate the landscape when precipitation declines as temperatures increase. Our results are consistent with those of other investigations of the geographic distribution of modern C4 plant species. Therefore, our results provide an important reference for interpretation of past C3/C4 relative abundance records in these three regions. © 2010 Science China Press and Springer-Verlag Berlin Heidelberg

A Comprehensive Study of the Electrostatic Discharge Sensitivity and Chargeability of Tris(carbohydrazide)zinc Perchlorate

Abstract: Most primary explosives are non-conductors, easily accumulate charge when contacting with and separating from other materials, and are sensitive to electrostatic discharge (ESD). In order to reduce the number of accidents caused by ESD initiation of primary explosives, studies on their electrostatic hazards are necessary. This work presents comprehensive experimental results of electrostatic discharge sensitivity and chargeability of tris(carbohydrazide)zinc perchlorate (ZnCP) under different conditions. The influences of the testing conditions, of devices, particle size, ambient temperature and relative humidity on the electrostatic discharge sensitivity and chargeability have been investigated in detail, and the quantitative regression equations obtained

Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity

Functional connectivity of the brain fluctuates even in resting-state condition. It has been reported recently that fluctuations of global functional network topology and those of individual connections between brain regions expressed multifractal scaling. To expand on these findings, in this study we investigated if multifractality was indeed an inherent property of dynamic functional connectivity (DFC) on the regional level as well. Furthermore, we explored if local DFC showed region-specific differences in its multifractal and entropy-related features. DFC analyses were performed on 62-channel, resting-state electroencephalography recordings of twelve young, healthy subjects. Surrogate data testing verified the true multifractal nature of regional DFC that could be attributed to the presumed nonlinear nature of the underlying processes. Moreover, we found a characteristic spatial distribution of local connectivity dynamics, in that frontal and occipital regions showed stronger long-range correlation and higher degree of multifractality, whereas the highest values of entropy were found over the central and temporal regions. The revealed topology reflected well the underlying resting-state network organization of the brain. The presented results and the proposed analysis framework could improve our understanding on how resting-state brain activity is spatio-temporally organized and may provide potential biomarkers for future clinical research

Synthesis of core-shell Au-Pt nanodendrites with high catalytic performance via overgrowth of platinum on in situ gold nanoparticles

We present a simple and effective strategy for high yield synthesis of well-dispersed, core-shell Au-Pt nanodendrites (CS Au-Pt NDs) via overgrowth of platinum on in situ 5.5 nm gold nanoparticles in water at room temperature. The sizes of the resulting CS Au-Pt NDs are 14 nm, which should be the smallest so far to the best of our knowledge. The average dimensions of the small Pt branches on the Au nanoparticle surfaces are about 2.6 nm × 4.2 nm, which lead to a significantly increased electrochemically active surface area (up to 35.2 m2 g-1). It is found that the morphology of CS Au-Pt NDs is dependent on the reaction conditions such as the incubation time of citrate-HAuCl4 solution, the mixing time of citrate-HAuCl4-K2PtCl4 solution before AA addition, and Pt-to-Au and AA-to-Pt molar ratios. In comparison with commercial Pt black (0.12 A mgPd-1), the resulting Au-Pt5 NDs show a superior catalytic activity towards methanol oxidation (0.45 A mgPd-1) due to the electronic interaction between the Au cores and Pt branches in bimetallic Au-Pt NDs and the high fraction of atomic steps, kinks, and corner atoms on the surfaces of the Pt branches

Atmospheric Correction of Aisa Measurements Over the Florida Keys Optically Shallow Waters: Challenges in Radiometric Calibration and Aerosol Selection

An Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imager was deployed on a manned aircraft flown at 1305-m altitude to collect data over optically shallow waters in the Florida Keys with the ultimate goal of mapping water quality and benthic habitats. As a first step, we developed a practical atmospheric correction (AC) approach to derive surface remote-sensing reflectance ((Rrs) from AISA measurements using radiative transfer simulations and constraints obtained from field spectral Rrs measurements. Unlike previously published method, the AC approach removes the surface Fresnel reflection and accounts for aircraft altitude and nonzero near-infrared (NIR) reflectance through iteration over the pre-established look-up tables (LUTs) based on MODTRAN calculations. Simulations and comparison with concurrent in situRrs measurements show the feasibility of the approach in deriving surface Rrs with acceptable uncertainties. The possibility of errors in the radiometric calibration of AISA is demonstrated, although a definitive assessment cannot be made due to lack of enough concurrent in situ measurements. The need for noise reduction and the difficulty in carrying out a vicarious calibration are also discussed to help advance the design of future AISA missions