Organic material decomposition and nutrient dynamics in a mulch system enriched with leguminous trees in the Amazon

As novas técnicas propostas para a agricultura na Amazônia incluem sistema de rotação de capoeira enriquecido com árvores leguminosas e transformando a queima da biomassa em cobertura morta sobre o solo. A decomposição e a liberação de nutrientes da cobertura morta foram estudadas usando sacos de liteira com malha fina que continham cinco tratamentos com diferentes espécies de leguminosas em comparação a um tratamento-controle com vegetação natural. As amostras para cada tratamento foram analisadas para conteúdos de C total, N, P, K, Ca, Mg, lignina, celulose e polifenóis solúveis em diferentes tempos de amostragem durante um ano. A razão constante de decomposição variou com a espécie e com o tempo. A perda de massa nos sacos de decomposição foi de 30,1 % para Acacia angustissima, de 32,7 % para Sclerolobium paniculatum, de 33,9 % para Inga edulis e para a vegetação secundária, de 45,2 % para Acacia mangium e de 63,6 % para Clitoria racemosa. Foi observada imobilização de N e P em todos os tratamentos, sendo a mineralização do N negativamente correlacionada com o fenol, razão C/N, razão (lignina + fenol)/N, razão fenol/P e o conteúdo de N nos sacos de liteira. Depois de 362 dias de incubação no campo, 3,3 % de K, 32,2 % de Ca e 22,4 % de Mg permaneceram no material em decomposição. Os resultados evidenciaram que a baixa qualidade mineral e a alta quantidade de carbono orgânico e aplicado como cobertura morta podem limitar a quantidade de energia disponível para os microrganismos resultando em uma competição por nutrientes com as plantas agrícolas.

Effect of added nitrogen on plant litter decomposition depends on initial soil carbon and nitrogen stoichiometry

Increasing organic carbon inputs to agricultural soils through the use of pastures or crop residues has been suggested as a means of restoring soil organic carbon lost via anthropogenic activities, such as land use change. However, the decomposition and retention of different plant residues in soil, and how these processes are affected by soil properties and nitrogen fertiliser application, is not fully understood. We evaluated the rate and extent of decomposition of 13C-pulse labelled plant material in response to nitrogen addition in four pasture soils of varying physico-chemical characteristics. Microbial respiration of buffel grass (Cenchrus ciliaris L.), wheat (Triticum aestivum L.) and lucerne (Medicago sativa L.) residues was monitored over 365-days. A double exponential model fitted to the data suggested that microbial respiration occurred as an early rapid and a late slow stage. A weighted three-compartment mixing model estimated the decomposition of both soluble and insoluble plant 13C (mg C kg−1 soil). Total plant material decomposition followed the alkyl C: O-alkyl C ratio of plant material, as determined by solid-state 13C nuclear magnetic resonance spectroscopy. Urea-N addition increased the decomposition of insoluble plant 13C in some soils (≤0.1% total nitrogen) but not others (0.3% total nitrogen). Principal components regression analysis indicated that 26% of the variability of plant material decomposition was explained by soil physico-chemical characteristics (P = 0.001), which was primarily described by the C:N ratio. We conclude that plant species with increasing alkyl C: O-alkyl C ratio are better retained as soil organic matter, and that the C:N stoichiometry of soils determines whether N addition leads to increases in soil organic carbon stocks.

Simultaneous material and structural optimization by multiscale topology optimization

Acknowledgments The authors acknowledge the support from Engineering and Physical Sciences Research Council, grant number EP/M002322/1. The authors would also like to thank Numerical Analysis Group at the Rutherford Appleton Laboratory for their FORTRAN HSL packages (HSL, a collection of Fortran codes for large-scale scientific computation. See http://www.hsl.rl.ac.uk/).

Damage accumulation in gallium nitride irradiated with various energetic heavy ions

In this work a study of damage production in gallium nitride via elastic collision process (nuclear energy deposition) and inelastic collision process (electronic energy deposition) using various heavy ions is presented. Ordinary low-energy heavy ions (Fe+ and Mo+ ions of 110 keV), swift heavy ions (Pb-208(27+) ions of 1.1 MeV/u) and slow highly-charged heavy ions (Xen+ ions of 180 keV) were employed in the irradiation. Damage accumulation in the GaN crystal films as a function of ion fluence and temperature was studied with RBS-channeling technique, Raman scattering technique, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). For ordinary low-energy heavy ion irradiation, the temperature dependence of damage production is moderate up to about 413 K resulting in amorphization of the damaged layer. Enhanced dynamic annealing of defects dominates at higher temperatures. Correlation of amorphization with material decomposition and nitrogen bubble formation was found. In the irradiation of swift heavy ions, rapid damage accumulation and efficient erosion of the irradiated layer occur at a rather low value of electronic energy deposition (about 1.3 keV/nm(3)),. which also varies with irradiation temperature. In the irradiation of slow highly-charged heavy ions (SHCI), enhanced amorphization and surface erosion due to potential energy deposition of SHCI was found. It is indicated that damage production in GaN is remarkably more sensitive to electronic energy loss via excitation and ionization than to nuclear energy loss via elastic collisions.

Study on thermodynamic properties of polypyromellitimide molding powder

Polypyromellitimide molding powder has been prepared. In the 78-370 K range, the dependence of the specific heat capacity (c(p)) on the temperature (T) is given by the polynomial: c(p)=0.8163+0.4592X+0.02468X(2)+0.1192X(3)+0.05659X(4) (J K-1 g(-1)) where X=(T-225.5)/144.5. Thermal decomposition in air starts at 716 K, and is complete at 1034 K. The standard combustion enthalpy is Delta(c)H=-26.442 kJ g(-1). (C) 2000 Elsevier Science B.V. All rights reserved.

Spectrotemporal CT data acquisition and reconstruction at low dose.

PURPOSE: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D+dual energy+time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. METHODS: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer. RESULTS: Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol. CONCLUSIONS: Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time.

Consorciação de braquiárias com milho outonal em plantio direto sob pivô central

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effect of the modifier ion on the properties of MgFe2O4 and ZnFe2O4 pigments

Magnesium and zinc ferrites have been prepared by the polymeric precursor method. The organic material decomposition was studied by thermogravimetry (TG) and differential thermal analysis (DTA). The variation of crystalline phases and particle morphology with calcination temperature were investigated using X-ray diffraction (XRD) and scanning electronic microscopy (SEM), respectively. The colors of the ferrites were evaluated using colorimetry. Magnesium ferrite crystallizes above 800 degrees C, presenting a yellow-orange color with a reflectance peak at the 600-650 nm range, while zinc ferrite crystallizes at 600 degrees C, with a reflectance peak between 650-700 nm, corresponding to the red-brick color.

Machine Learning-based Techniques to Address Spectral Distortions in Photon Counting X-ray Computed Tomography

Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables full spectrum CT in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical eects in the detector and are very noisy due to photon starvation. In this work, we proposed two methods based on machine learning to address the spectral distortion issue and to improve the material decomposition. This rst approach is to model distortions using an articial neural network (ANN) and compensate for the distortion in a statistical reconstruction. The second approach is to directly correct for the distortion in the projections. Both technique can be done as a calibration process where the neural network can be trained using 3D printed phantoms data to learn the distortion model or the correction model of the spectral distortion. This replaces the need for synchrotron measurements required in conventional technique to derive the distortion model parametrically which could be costly and time consuming. The results demonstrate experimental feasibility and potential advantages of ANN-based distortion modeling and correction for more accurate K-edge imaging with a PCXD. Given the computational eciency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.

Acoustic feature extraction using perceptual wavelet packet decomposition for frog call classification

Frog protection has become increasingly essential due to the rapid decline of its biodiversity. Therefore, it is valuable to develop new methods for studying this biodiversity. In this paper, a novel feature extraction method is proposed based on perceptual wavelet packet decomposition for classifying frog calls in noisy environments. Pre-processing and syllable segmentation are first applied to the frog call. Then, a spectral peak track is extracted from each syllable if possible. Track duration, dominant frequency and oscillation rate are directly extracted from the track. With k-means clustering algorithm, the calculated dominant frequency of all frog species is clustered into k parts, which produce a frequency scale for wavelet packet decomposition. Based on the adaptive frequency scale, wavelet packet decomposition is applied to the frog calls. Using the wavelet packet decomposition coefficients, a new feature set named perceptual wavelet packet decomposition sub-band cepstral coefficients is extracted. Finally, a k-nearest neighbour (k-NN) classifier is used for the classification. The experiment results show that the proposed features can achieve an average classification accuracy of 97.45% which outperforms syllable features (86.87%) and Mel-frequency cepstral coefficients (MFCCs) feature (90.80%).

Synthesis of nanoparticles of the giant dielectric material, CaCu3Ti4O12 from a precursor route

A complex oxalate precursor, CaCu3(TiO)(4)(C2O4)(8)center dot 9H(2)O, (CCT-OX), was synthesized and the precipitate that obtained was confirmed to be monophasic by the wet chemical analyses, X-ray diffraction, FTIR absorption and TG/DTA analyses. The thermal decomposition of this oxalate precursor led to the formation of phase-pure calcium copper titanate, CaCu3Ti4O12, (CCTO) at a parts per thousand yen680A degrees C. The bright-field TEM micrographs revealed that the size of the as synthesized crystallites to be in the 30-80 nm range. The powders so obtained had excellent sinterability resulting in high density ceramics which exhibited giant dielectric constants upto 40000 (1 kHz) at 25A degrees C, accompanied by low dielectric losses.

Defect Sensitization of Combustion and Thermal Decomposition of Ammonium Perchlorate: Effect of Pelletizing Pressure and Dwell Time

A systematic study was undertaken on the combustion and thermal decomposition of pelletized Ammonium Perchlorate (AP) to investigate the effects of pelletizing pressure and dwell time. At constant pressure, increasing the dwell time results in an increase in the burning rate up to a maximum and thereafter decreases it. The dwell time required for the pellets to have maximum burning rate is a function of pressure. The maximum burning rate is the same for all the pressures used and is also unaffected by increasing, to the range 90-250 μ, the particle size of AP used. In order to explain the occurrence of a maximum in burning rate, pellets were examined for their thermal sensitivities, physical nature and the changes occurring during pelletization with dwell time and pressure. The variations are argued in terms of increasing density, formation of defects such as dislocations leading to an increase in the number of reactive sites, followed by their partial annihilation at longer dwell times due to flow of material during pelletization.

Rapid synthetic routes to prepare LiNi1/3Mn1/3Co1/3O2 as a high voltage, high-capacity Li-ion battery cathode material

LiNi1/3Mn1/3Co1/3O2, a high voltage and high-capacity cathode material for Li-ion batteries, has been synthesized by three different rapid synthetic methods. viz. nitrate-melt decomposition, combustion and sol-gel methods. The first two methods are ultra rapid and a time period as small as 15 min is sufficient to prepare nano-crystalline LiNi1/3Mn1/3Co1/3O2. The processing parameters in obtaining the best performing materials are optimized for each process and their electrochemical performance is evaluated in Li-ion cells. The combustion-derived LiNi1/3Mn1/3Co1/3O2 sample exhibits large extent of cation mixing (10%) while the other two methods yield LiNi1/3Mn1/3Co1/3O2 with cation mixing <5%. LiNi1/3Mn1/3Co1/3O2 prepared by nitrate-melt decomposition method exhibits superior performance as Li-ion battery cathode material.

Direct Writing of Copper Film Patterns by Laser-Induced Decomposition of Copper Acetate

Direct writing of patterns is being widely attempted in the field of microelectronic circuit/device manufacture. Use of this technique eliminates the need for employing photolithographic process. Laser induced direct writing can be achieved by (i) Photochemical reaction [i] , (ii) Evaporation from target material [2], and (iii) decomposition.Micron size features of palladium and copper through decomposition of palladium acetate and copper formate respectively on quartz and silicon using Argon ion laser have been reported [3,4] .In this commuication we report a technique for both single line and large area depositon of copper through decomposition of copper acetate,(CH3COO)2Cu, on alumina substrates.Nd:YAG laser known for its reliability and low maintenance cost as compared to excimer and other gas lasers is used. This technique offers an attractive and economical alternative for manufacture of thin film microcircuits.