Biomass decomposition and nutrient release from black oat and hairy vetch residues deposited in a vineyard

A significant quantity of nutrients in vineyards may return to the soil each year through decomposition of residues from cover plants. This study aimed to evaluate biomass decomposition and nutrient release from residues of black oats and hairy vetch deposited in the vines rows, with and without plastic shelter, and in the between-row areas throughout the vegetative and productive cycle of the plants. The study was conducted in a commercial vineyard in Bento Gonçalves, RS, Brazil, from October 2008 to February 2009. Black oat (Avena strigosa) and hairy vetch (Vicia villosa) residues were collected, subjected to chemical (C, N, P, K, Ca, and Mg) and biochemical (cellulose - Cel, hemicellulose - Hem, and lignin - Lig content) analyses, and placed in litter bags, which were deposited in vines rows without plastic shelter (VPRWS), in vines rows with plastic shelter (VPRS), and in the between-row areas (BR). We collected the residues at 0, 33, 58, 76, and 110 days after deposition of the litter bags, prepared the material, and subjected it to analysis of total N, P, K, Ca, and Mg content. The VPRS contained the largest quantities and percentages of dry matter and residual nutrients (except for Ca) in black oat residues from October to February, which coincides with the period from flowering up to grape harvest. This practice led to greater protection of the soil surface, avoiding surface runoff of the solution derived from between the rows, but it retarded nutrient cycling. The rate of biomass decomposition and nutrient release from hairy vetch residues from October to February was not affected by the position of deposition of the residues in the vineyard, which may especially be attributed to the lower values of the C/N and Lig/N ratios. Regardless of the type of residue, black oat or hairy vetch, the greatest decomposition and nutrient release mainly occurred up to 33 days after deposition of the residues on the soil surface, which coincided with the flowering of the grapevines, which is one of the phenological stages of greatest demand for nutrients.

Analysis of an iterative deconvolution approach for estimating the source wavelet during waveform inversion of crosshole ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole georadar data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a time-domain waveform inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little-to-no trade-off between the wavelet estimation and the tomographic imaging procedures.

Space and momentum representation analysis of Hartman's effect in wave packet transmission

The Hartman effect is analyzed in both the position and momentum representations of the problem. The importance of Wigner tunneling and deep tunneling is singled out. It is shown quantitatively how the barrier acts as a filter for low momenta (quantum speed up) as the width increases, and a detailed mechanism is proposed. Superluminal transmission is also discussed.

Socio-economic inequalities in reported depression in Spain : a decomposition approach

Recent evidence questions some conventional view on the existence of income-related inequalities in depression suggesting in turn that other determinants might be in place, such as activity status and educational attainment. Evidence of socio-economic inequalities is especially relevant in countries such as Spain that have a limited coverage of mental health care and are regionally heterogeneous. This paper aims at measuring and explaining the degree of socio-economic inequality in reported depression in Spain. We employ linear probability models to estimate the concentration index and its decomposition drawing from 2003 edition of the Spanish National Health Survey, the most recent representative health survey in Spain. Our findings point towards the existence of avoidable inequalities in the prevalence of reported depression. However, besides ¿pure income effects¿ explaining 37% of inequality, economic activity status (28%), education (15%) and demographics (15%) play also a key encompassing role. Although high income implies higher resources to invest and cure (mental) illness, environmental factors influencing in peoples perceived social status act as indirect path as explaining the prevalence of depression. Finally, we find evidence of a gender effect, gender social-economic inequality in income is mainly avoidable.

Iowa Earth Year 2000 : partner packet, 2000

This packet gives information on how to preserve, conserve, and protect Iowa's rich natural resources by working together in communities, staying committed to bettering Iowa's future, encouraging volunteerism, enlisting support from a variety of sources, setting environmental examples ourselves and developing positive awareness programs.

MM-GBSA binding free energy decomposition and T cell receptor engineering.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by class I major histocompatibility complexes (MHC) is the key event in the immune response against virus infected cells or tumor cells. The major determinant of T cell activation is the affinity of the TCR for the peptide-MHC complex, though kinetic parameters are also important. A study of the 2C TCR/SIYR/H-2Kb system using a binding free energy decomposition (BFED) based on the MM-GBSA approach had been performed to assess the performance of the approach on this system. The results showed that the TCR-p-MHC BFED including entropic terms provides a detailed and reliable description of the energetics of the interaction (Zoete and Michielin, 2007). Based on these results, we have developed a new approach to design sequence modifications for a TCR recognizing the human leukocyte antigen (HLA)-A2 restricted tumor epitope NY-ESO-1. NY-ESO-1 is a cancer testis antigen expressed not only in melanoma, but also on several other types of cancers. It has been observed at high frequencies in melanoma patients with unusually positive clinical outcome and, therefore, represents an interesting target for adoptive transfer with modified TCR. Sequence modifications of TCR potentially increasing the affinity for this epitope have been proposed and tested in vitro. T cells expressing some of the proposed TCR mutants showed better T cell functionality, with improved killing of peptide-loaded T2 cells and better proliferative capacity compared to the wild type TCR expressing cells. These results open the door of rational TCR design for adoptive transfer cancer therapy.

Decomposition of Ruppia cirrhosa (Petagna) Grande in the sediment of a coastal lagoon

The decomposition process of Ruppia cirrhosa was studied in a Mediterranean coastal lagoon in the Delta of the River Ebro (NE Spain). Leaves and shoots of Ruppia were enclosed in 1 mm-mesh and 100 pm-mesh litter bags to ascertain the effect of detritivores, macroinvertebrates, and bacteria and fungi, respectively. Changes in biomass and carbon, and, nitrogen and phosphorus concentrations in the detritus were studied at the sediment-water interface and in the sediment. Significant differences in biomass decay were observed between the two bag types. Significant differences in decomposition were observed between the two experimental conditions studied using 100 pm-mesh bags. These differences were not significant when using the 1 mm-mesh bags. The carbon content in the detritus remained constant during the decomposition process. The percentage of nitrogen increased progressively from an initial 2.4 % to 3 %. The percentage of phosphorus decreased rapidly during the first two days of decomposition from an initial 0.26 % to 0.17 %. This loss is greater in the sediment than in the water column or at the sediment-water interface. From these results we deduce that the activity of microorganisms seems to be more important in the sediment than in the water-sediment interface, and that grazing by macroinvertebrates has less importance in the sediment than in the water column.

Source-wavelet estimation during full-waveform inversion of ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole ground-penetrating radar (GPR) data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a recently published time-domain inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity of both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little to no trade-off between the wavelet estimation and the tomographic imaging procedures.

MMPBSA decomposition of the binding energy throughout a molecular dynamics simulation of Amyloid-Beta (Aß10-35) aggregation

Recent experiments with amyloid-beta (Aß) peptides indicate that the formation of toxic oligomers may be an important contribution to the onset of Alzheimer's disease. The toxicity of Aß oligomers depend on their structure, which is governed by assembly dynamics. However, a detailed knowledge of the structure of at the atomic level has not been achieved yet due to limitations of current experimental techniques. In this study, replica exchange molecular dynamics simulations are used to identify the expected diversity of dimer conformations of Aß10-35 monomers. The most representative dimer conformation has been used to track the dimer formation process between both monomers. The process has been characterized by means of the evolution of the decomposition of the binding free energy, which provides an energetic profile of the interaction. Dimers undergo a process of reorganization driven basically by inter-chain hydrophobic and hydrophilic interactions and also solvation/desolvation processes.

Empirics of the international inequality in CO2 emissions intensity: explanatory factors according to complementary decomposition methodologies

This paper analyses the international inequalities in CO2 emissions intensity for the period 1971–2009 and assesses explanatory factors. Multiplicative, group and additive methodologies of inequality decomposition are employed. The first allows us to clarify the separated role of the carbonisation index and the energy intensity in the pattern observed for inequalities in CO2 intensities; the second allows us to understand the role of regional groups; and the third allows us to investigate the role of different fossil energy sources (coal, oil and gas). The results show that, first, the reduction in global emissions intensity has coincided with a significant reduction in international inequality. Second, the bulk of this inequality and its reduction are attributed to differences between the groups of countries considered. Third, coal is the main energy source explaining these inequalities, although the growth in the relative contribution of gas is also remarkable. Fourth, the bulk of inequalities between countries and its decline are explained by differences in energy intensities, although there are significant differences in the patterns demonstrated by different groups of countries. JEL codes: D39; Q43; Q56. Key words: CO2 international distribution, inequality decomposition, CO2 emissions intensity

Real-time monitoring of the silicidation process of tungsten filaments at high temperature used as catalysers for silane decomposition

The scope of this work is the systematic study of the silicidation process affecting tungsten filaments at high temperature (1900ºC) used for silane decomposition in the hot-wire chemical vapour deposition technique (HWCVD). The correlation between the electrical resistance evolution of the filaments, Rfil(t), and the different stages of the their silicidation process is exposed. Said stages correspond to: the rapid formation of two WSi2 fronts at the cold ends of the filaments and their further propagation towards the middle of the filaments; and, regarding the hot central portion of the filaments: a initial stage of silicon dissolution into the tungsten bulk, with a random duration for as-manufactured filaments, followed by the inhomogeneous nucleation of W5Si3 (which is later replaced by WSi2) and its further growth towards the filaments core. An electrical model is used to obtain real-time information about the current status of the filaments silicidation process by simply monitoring their Rfil(t) evolution during the HWCVD process. It is shown that implementing an annealing pre-treatment to the filaments leads to a clearly repetitive trend in the monitored Rfil(t) signatures. The influence of hydrogen dilution of silane on the filaments silicidation process is also discussed.

Decomposition of Arachis pintoi and Hyparrhenia rufa litters in monoculture and intercropped systems under lowland soil

Tropical grasslands under lowland soils are generally underutilized and the litter of forage legumes may be used to recover these degraded pastures. The objective of this work was to study the dynamics of litter decomposition of Arachis pintoi (pinto peanut), Hyparrhenia rufa (thatching grass) and a mixture of both species in a lowland soil. These treatments were analyzed in three areas: grass monoculture, legume monoculture and legume intercropped with the grass during the dry and wet seasons. Litter bags containing the legume, grass or a mixture of both species were incubated to estimate the decomposition rate and microorganism colonization. Decomposition constants (K) and litter half-lives (T1/2) were estimated by an exponential model whereas number of microorganisms in specific media were determined by plate dilution. The decomposition rate, release of nutrients and microorganisms number, especially bacteria, increased when pinto peanut was added to thatching grass, influenced by favorable lignin/N and C/N ratios in legume litter. When pinto peanut litter was incubated in the grass plots, 50% N and P was released within about 135 days in the dry season and in the wet season, the equivalent release occurred within 20 days. These results indicate that A. pintoi has a great potential for nutrient recycling via litter and can be used to recover degraded areas.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9).

Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.