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 4,687 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

In NW Spain, a European region with very high fire incidence and erosion risks, the effects on soils of a medium-to-high severity wildfire and two emergency stabilization techniques were studied. In burned plots (control, BS; seeded with cereal, BSS; straw mulched, BSM) and adjacent unburned plots (US), the topsoil (0-2 cm) pH and thirteen NH4Ac-DTPA extractable elements were evaluated at t = 0, 4, 8 and 12 months after the fire. Compared to US, fire increased by 0.3-0.5 units the soil pH which decrease slowly over time, but remaining significantly higher at t = 12 (BS, BSM, BSS>US). Ammonium nitrogen (N) levels were higher (p<0.05) in burned plots than in US, difference decreasing progressively from 48-fold (t = 0) to 25-fold (t = 12). Although no significant effect of fire was immediately observed, the extractable sodium (Na) and potassium (K) were higher (p<0.05) in burned plots than in US at t = 4 and t = 8, probably due to cation leaching from the overlying ash. Fire did not modify the extractable magnesium (Mg), but at t = 0 the extractable calcium (Ca) and phosphorous (P) were transiently and significantly higher in burned plots than in US. Extractable aluminum (Al), iron (Fe), copper (Cu), cobalt (Co) and zinc (Zn) were lower and manganese (Mn) was higher in burned plots than in US. Neither seeding nor mulching significantly modified the topsoil concentrations of the elements considered. The PCA revealed that BS, BSM and BSS became more similar to US over the study period due to a rapid decrease in extractable Ca and Mg and a slow decrease in extractable Mn and NH4(+)-N. At t = 12, the most notable differences between burned plots and US were in the concentrations of extractable Al and Zn. Data suggest that at least another 4-8 months will be required for full recovery of the burned plots to unburned conditions.
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PMID:Short and medium-term effects of a wildfire and two emergency stabilization treatments on the availability of macronutrients and trace elements in topsoil. 2495 Apr 98

In the analysis of functional Near-Infrared Spectroscopy (fNIRS) signals from real-world scenarios, artifact rejection is essential. However, currently there exists no gold-standard. Although a plenitude of methodological approaches implicitly assume the presence of latent processes in the signals, elaborate Blind-Source-Separation methods have rarely been applied. A reason are challenging characteristics such as Non-instantaneous and non-constant coupling, correlated noise and statistical dependencies between signal components. We present a novel suitable BSS framework that tackles these issues by incorporating A) Independent Component Analysis methods that exploit both higher order statistics and sample dependency, B) multimodality, i.e., fNIRS with accelerometer signals, and C) Canonical-Correlation Analysis with temporal embedding. This enables analysis of signal components and rejection of motion-induced physiological hemodynamic artifacts that would otherwise be hard to identify. We implement a method for Blind Source Separation and Accelerometer based Artifact Rejection and Detection (BLISSA2RD). It allows the analysis of a novel n-back based cognitive workload paradigm in freely moving subjects, that is also presented in this manuscript. We evaluate on the corresponding data set and simulated ground truth data, making use of metrics based on 1st and 2nd order statistics and SNR and compare with three established methods: PCA, Spline and Wavelet-based artifact removal. Across 17 subjects, the method is shown to reduce movement induced artifacts by up to two orders of magnitude, improves the SNR of continuous hemodynamic signals in single channels by up to 10dB, and significantly outperforms conventional methods in the extraction of simulated Hemodynamic Response Functions from strongly contaminated data. The framework and methods presented can serve as an introduction to a new type of multivariate methods for the analysis of fNIRS signals and as a blueprint for artifact rejection in complex environments beyond the applied paradigm.
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PMID:A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy. 3120 24