Graph Theoretical Measures of Fast Ripple Networks Improve the Accuracy of Post-operative Seizure Outcome Prediction

Fast ripples (FR) are a biomarker of epileptogenic brain, but when larger portions of FR generating regions are resected seizure freedom is not always achieved. To evaluate and improve the diagnostic accuracy of FR resection for predicting seizure freedom we compared the FR resection ratio (RR) with FR network graph theoretical measures. In 23 patients FR were semi-automatically detected and quantified in stereo EEG recordings during sleep. MRI normalization and co-registration localized contacts and relation to resection margins. The number of FR, and graph theoretical measures, which were spatial (i.e., FR rate-distance radius) or temporal correlational (i.e., FR mutual information), were compared with the resection margins and with seizure outcome We found that the FR RR did not correlate with seizure-outcome (p \u3e 0.05). In contrast, the FR rate-distance radius resected difference and the FR MI mean characteristic path length RR did correlate with seizure-outcome (p \u3c 0.05). Retesting of positive FR RR patients using either FR rate-distance radius resected difference or the FR MI mean characteristic path length RR reduced seizure-free misclassifications from 44 to 22% and 17%, respectively. These results indicate that graph theoretical measures of FR networks can improve the diagnostic accuracy of the resection of FR events for predicting seizure freedom

Direct Visualization of Laser-Driven Electron Multiple Scattering and Tunneling Distance in Strong-Field Ionization

Using a simple model of strong-field ionization of atoms that generalizes the well-known 3-step model from 1D to 3D, we show that the experimental photoelectron angular distributions resulting from laser ionization of xenon and argon display prominent structures that correspond to electrons that pass by their parent ion more than once before strongly scattering. The shape of these structures can be associated with the specific number of times the electron is driven past its parent ion in the laser field before scattering. Furthermore, a careful analysis of the cutoff energy of the structures allows us to experimentally measure the distance between the electron and ion at the moment of tunnel ionization. This work provides new physical insight into how atoms ionize in strong laser fields and has implications for further efforts to extract atomic and molecular dynamics from strong-field physics

Milky Way Tomography with the SkyMapper Southern Survey. II. Photometric Recalibration of SMSS DR2

We apply the spectroscopy-based stellar-color regression (SCR) method to perform an accurate photometric recalibration of the second data release from the SkyMapper Southern Survey (SMSS DR2). From comparison with a sample of over 200,000 dwarf stars with stellar atmospheric parameters taken from GALAH+ DR3 and with accurate, homogeneous photometry from Gaia DR2, zero-point offsets are detected in the original photometric catalog of SMSS DR2, in particular for the gravity- and metallicity-sensitive uv bands. For the uv bands, the zero-point offsets are close to zero at very low extinction, and then steadily increase with E(B - V), reaching as large as 0.174 and 0.134 mag respectively, at E(B - V) ∼ 0.5 mag. These offsets largely arise from the adopted dust term in the transformations used by SMSS DR2 to construct photometric calibrators from the ATLAS reference catalog. For the gr bands, the zero-point offsets exhibit negligible variations with the E(B - V) of Schlegel et al. due to their tiny coefficients on the dust term in the transformation. Our study also reveals small but significant spatial variations of the zero-point offsets in all uvgr bands. External checks using Strömgren photometry, WD loci, and the SDSS Stripe 82 standard-star catalog independently confirm the zero-points found by our revised SCR method.The national facility capability for SkyMapper has been funded through ARC LIEF grant LE130100104 from the Australian Research Council, awarded to the University of Sydney, the Australian National University, Swinburne University of Technology, the University of Queensland, the University of Western Australia, the University of Melbourne, Curtin University of Technology, Monash University, and the Australian Astronomical Observatory. SkyMapper is owned and operated by The Australian National University’s Research School of Astronomy and Astrophysics. The survey data were processed and provided by the SkyMapper Team at ANU. The SkyMapper node of the AllSky Virtual Observatory (ASVO) is hosted at the National Computational Infrastructure (NCI). Development and support of the SkyMapper node of the ASVO has been funded in part by Astronomy Australia Limited (AAL) and the Australian Government through the Commonwealth’s Education Investment Fund (EIF) and National Collaborative Research Infrastructure Strategy (NCRIS), particularly the National eResearch Collaboration Tools and Resources (NeCTAR) and the Australian National Data Service Projects (ANDS). Parts of this research were supported by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013

Responses of soil respiration and its components to drought stress

Climate change is likely to increase both intensity and frequency of drought stress. The responses of soil respiration (Rs) and its components (root respiration, Rr; mycorrhizal respiration, Rm; and heterotrophic respiration, Rh) to drought stress can be different. This work aims to review the recent and current literature about the variations in Rs during the period of drought stress, to explore potential coupling processes and mechanisms between Rs and driving factors in the context of global climate change

Automatic estimation of soil biochar quantity via hyperspectral imaging

Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil. © 2019 by IGI Global

Automatic estimation of soil biochar quantity via hyperspectral imaging

Biochar soil amendment is globally recognized as an emerging approach to mitigate CO2 emissions and increase crop yield. Because the durability and changes of biochar may affect its long term functions, it is important to quantify biochar in soil after application. In this chapter, an automatic soil biochar estimation method is proposed by analysis of hyperspectral images captured by cameras that cover both visible and infrared light wavelengths. The soil image is considered as a mixture of soil and biochar signals, and then hyperspectral unmixing methods are applied to estimate the biochar proportion at each pixel. The final percentage of biochar can be calculated by taking the mean of the proportion of hyperspectral pixels. Three different models of unmixing are described in this chapter. Their experimental results are evaluated by polynomial regression and root mean square errors against the ground truth data collected in the environmental labs. The results show that hyperspectral unmixing is a promising method to measure the percentage of biochar in the soil

Peanut shell biochar improves soil properties and peanut kernel quality on a red Ferrosol

Purpose Biochar has excellent potential to improve crop yield and quality, but its effects vary depending on soil type and agronomic inputs (e.g., irrigation and fertiliser). In this study, we investigate the effects of biochar on peanut productivity and crop quality under different irrigation and fertilisation regime in red Ferrosols. Materials and methods We applied peanut shell biochar (9.2 t ha−1) on a red Ferrosol under field conditions to examine the effects of biochar, irrigation, fertiliser and their interactions on soil properties and yield and kernel quality of the peanut variety ‘Middleton’. Results and discussion Biochar application improved kernel quality by increasing the fraction of the highest commercial grade kernels (grade ‘Jumbo’) but did not affect photosynthesis and yield of peanut. Biochar application also increased soil total C (TC), total nitrogen (TN) and C/N ratio, and changed soil C and N stable isotope composition. Soil K and Zn content was higher in biochar treatments, which partially explains the observed kernel grade improvement. Fertilisation did not improve peanut performance, and irrigation generally had a negative effect on crop yield and physiology, but these data were compromised by high rainfall during cropping. There were few interactions among biochar, irrigation and fertiliser treatments. Conclusions Peanut shell biochar improves soil organic C, nutrient availability and peanut kernel quality under different irrigation and fertiliser rate regimes in field conditions

The relative importance of genetic diversity and phenotypic plasticity in determining invasion success of a clonal weed in the USA and China

Phenotypic plasticity has been proposed as an important adaptive strategy for clonal plants in heterogeneous habitats. Increased phenotypic plasticity can be especially beneficial for invasive clonal plants, allowing them to colonize new environments even when genetic diversity is low. However, the relative importance of genetic diversity and phenotypic plasticity for invasion success remains largely unknown. Here, we performed molecular marker analyses and a common garden experiment to investigate the genetic diversity and phenotypic plasticity of the globally important weed Alternanthera philoxeroides in response to different water availability (terrestrial vs. aquatic habitats). This species relies predominantly on clonal propagation in introduced ranges. We therefore expected genetic diversity to be restricted in the two sampled introduced ranges (the USA and China) when compared to the native range (Argentina), but that phenotypic plasticity may allow the species’ full niche range to nonetheless be exploited. We found clones from China had very low genetic diversity in terms of both marker diversity and quantitative variation when compared with those from the USA and Argentina, probably reflecting different introduction histories. In contrast, similar patterns of phenotypic plasticity were found for clones from all three regions. Furthermore, despite the different levels of genetic diversity, bioclimatic modeling suggested that the full potential bioclimatic distribution had been invaded in both China and USA. Phenotypic plasticity, not genetic diversity, was therefore critical in allowing A. philoxeroides to invade diverse habitats across broad geographic areas