Local Decomposition Research Articles

In-situ local litter decomposition was mainly microbial and differed between pastures and mature forests but not along early succession in a tropical dry forest ecosystem

Organic matter decomposition in tropical dry forest ecosystems is poorly understood, especially under the diversity of land covers resulting from human activities and increasing predominance of secondary vegetation over primary vegetation. We hypothesized that 1) litter quality decreases progressively from pastures to successional forests and to mature forests as a result of increasing recalcitrant materials with increasing tree cover, 2) as a consequence of those litter quality differences, decomposition rates also decrease progressively from pastures to successional forests and to mature forests, and 3) bacteria dominate the microbial community in the first part of the process, consuming the most labile materials; fungi dominate afterwards, consuming the recalcitrant material; meso- and small macrofauna access to bags increases decomposition. Bags made from mesh of two opening sizes and containing bulk litter from the site were placed in each site when the rainy season started and removed after 1, 2, 4 and 9 months. Mass loss curves were remarkably similar in all sites despite being composed of different litter materials and exposed to different local environmental conditions in each site. Local litter in-situ decomposition showed a rapid decomposition phase during the first two months, in which close to half of the initial mass was lost, and virtually no further decomposition in the subsequent seven months. Half-life of the litter was approximately 3 months and the shape of the mass loss curves indicated the local bulk litters were rich in labile materials. Differences in litter quality were minor, were weakly related to decomposition and had no relation to the successional age of the sites. Decomposition rates were significantly higher as hypothesized, in pastures than in mature forests and intermediate in successional sites although the differences observed were of low magnitude. During the rapid decomposition period the fungi:bacteria abundance ratio decreased from four in initial bulk litters to one after the first two months. As predicted, bacteria proliferated in the initial stages whereas fungi decreased but we were not able to measure if fungi dominated the microbial community in the second, slow period. Allowing access of meso- and small macro-fauna to litter bags did not increase decomposition. These results suggest that decomposition is a resilient function in this ecosystem, as it is only slightly reduced in pastures and recovers rapidly through early succession.

A Local Coupling Multitrace Domain Decomposition Method for Electromagnetic Scattering From Multilayered Dielectric Objects

In this article, a local coupling multitrace domain decomposition method (LCMT-DDM) based on surface integral equation (SIE) formulations is proposed to analyze electromagnetic scattering from multilayered dielectric objects. Different from the traditional SIE-DDM, where the interactions between subdomains are accounted for using global radiation coupling, LCMT-DDM uses a local coupling scheme. The original multilayered object is decomposed into several independent domains, i.e., the exterior region (free space) and many homogeneous interior regions (dielectrics). The boundaries of subdomains are all touching faces, where only the Robin transmission conditions (RTCs) are enforced to ensure the field continuity. Hence, each subdomain only couples with its neighboring regions, which makes the DDM system a highly sparse matrix, especially when the number of subdomains is large. In each subdomain, the electric-field integral equation (EFIE) and the magnetic-field integral equation (MFIE) for dielectrics are used as the governing equations. By imposing RTCs, well-conditioned equations are formed in each subdomain without invoking the combined-field integral equation (CFIE), which usually causes accuracy issues in dielectric modeling. Since the subdomain matrices are diagonally dominant, the flexible generalized minimal residual (FGMRES) technique is used to accelerate the iterative solution of the whole DDM system. Moreover, an effective preconditioner that can be recursively constructed is proposed.

High-temperature toughening in ternary medium-entropy (Ta1/3Ti1/3Zr1/3)C carbide consolidated using spark-plasma sintering

ABSTRACT We report for the first time the effect of temperature on the mechanical properties of (Ta1/3Ti1/3Zr1/3)C carbide. Flexural strength and fracture toughness were investigated using the three-point bending technique in argon. Using commercially available carbide powders with an equimolar ratio and performing spark plasma consolidation at 1973°C, we obtained a bulk single-phase medium-entropy carbide ceramic with the lattice parameter a= 4.458 Å. The flexural strength and fracture toughness at room temperature reached on average 700 MPa and 3.2 MPa m1/2, respectively. At 1800°C, local decomposition of the medium-entropy carbide took place as a structure with a local chemical gradient was observed after high-temperature tests, which increased fracture toughness by 30% (to 4.4 MPa m1/2).

A Neural Network Decomposition Algorithm for Mapping on Crossbar-Based Computing Systems

Crossbar-based neuromorphic computing to accelerate neural networks is a popular alternative to conventional von Neumann computing systems. It is also referred as processing-in-memory and in-situ analog computing. The crossbars have a fixed number of synapses per neuron and it is necessary to decompose neurons to map networks onto the crossbars. This paper proposes the k-spare decomposition algorithm that can trade off the predictive performance against the neuron usage during the mapping. The proposed algorithm performs a two-level hierarchical decomposition. In the first global decomposition, it decomposes the neural network such that each crossbar has k spare neurons. These neurons are used to improve the accuracy of the partially mapped network in the subsequent local decomposition. Our experimental results using modern convolutional neural networks show that the proposed method can improve the accuracy substantially within about 10% extra neurons.

Multivariate statistical technique in the assessment of coastal water quality of Oman

Coastal water plays a significant role in the growth and productivity of marine organisms; and is the source of many important economic activities including fishery, coastal recreation and socio-economic development. Coastal water quality is highly influenced by the physical, chemical and biological processes in the ocean. The present study assessed 17 physico-chemical water quality parameters along the Omani coastline of Capital Muscat at Mina Al Fahal, Al Ghubrah, Barka and Quriyat. The results showed that the level of dissolved oxygen (O2) was lower than 5 mg/l at the Mina Al Fahal (2.24 mg/l) and Quriyat stations (3.68 mg/l), signifying a threat to coastal species. Relatively high total dissolved solids (>40 000 mg/l), total coliform (>500 most probable number (MPN)/100 ml) and Escherichia coli (>35 MPN/100 ml) at the Al Ghubrah and Barka stations indicated contamination from brine disposal, local run-offs, decomposition of organic waste and domestic effluent discharges. The higher phosphate–phosphorus level of 0.14 mg/l at Quriyat suggested pollution from local fish waste and sediment decomposition. The analysed parameters were further evaluated using multivariate statistical techniques such as cluster analysis (CA) and principal component analysis/factor analysis (PCA/FA). CA provided five clusters after grouping the parameters based on similarity. PCA/FA identified four main loading factors, with a total variance of 74.2%. The analysis showed contamination from desalination plants, domestic waste, local discharge and natural fish wastes and weathering of seabed rocks and sediments as the main contributors to the elevated concentrations affecting the water quality in the study locations.

Nonlinear sparse mode decomposition and its application in planetary gearbox fault diagnosis

Traditional time-frequency analysis methods, including empirical mode decomposition (EMD), local characteristic-scale decomposition (LCD) and variable mode decomposition (VMD), have some limitations in nonlinear signal analysis. When the signal has strong noise, traditional time-frequency analysis methods will force the signal to be decomposed into several inaccurate components, and the achieved components usually suffer from the end effect problem. Considering the above pressing challenge, a new signal decomposition algorithm, nonlinear sparse mode decomposition (NSMD), is proposed in this protocol. The core of NSMD is that the local narrowband signal disappears under the action of the singular local linear operator, so the singular local linear operator can be applied to extract the local narrowband component of the detected signal. Meanwhile, the obtained local narrowband signal can be superposed as the basic signal to close to the original signal, realizing the adaptive decomposition of the signal with good robustness and adaptability. The analysis results of simulation signals and planetary gearbox fault signals indicate that the proposed NSMD method is effective for raw vibration signals.

Angle-Based Contact Detection in Discontinuous Deformation Analysis

This study presents a novel angle-based contact detection method to address the concave contact problem of arbitrary polyhedra, including convex and concave polyhedra, those with cavities and/or holes, and likely their unions. First, the most important mathematical concept in this study, the angle, is introduced to represent a general polyhedron. Using angles, the topologies of the polyhedra can be far more complex and universal than those previously studied, allowing for the coplanarity of faces and collinearity of edges, and not limiting the polyhedra to simple homeomorphic to closed three-dimensional (3-D) spheres. Second, all the local entrances of two general angles, which are either vertex angle to half-space or crossing edge angle to edge angle entrances, are identified using the entrance formulas. Third, local convex decomposition (LCD) is proposed to decompose any arbitrarily concave angle into a set of convex subangles, making the method easy to implement and naturally compatible with detection of entrance angles. Fourth, the proposed entrance angle method (EAM) is implemented in 3-D discontinuous deformation analysis (DDA) to compute arbitrarily convex/concave contacts. Finally, the EAM-based 3-D DDA method is validated and then employed to investigate the discontinuous mechanical behaviors of complex polyhedral block systems. Overall, the extended 3-D DDA program is sufficiently developed to meet the analysis requirements of complex rock mass projects.

A hybridizable discontinuous Galerkin Generalized Multiscale Finite element method for highly heterogeneous linear elasticity problems

In this paper, we consider a multiscale hybridizable discontinuous Galerkin (HDG) for heterogeneous linear elasticity problem in a mixed formulation. Within the framework of HDG, the entire problem can be decomposed into a global problem defined in coarse interfaces and several local problems in coarse elements. Our goal here is to propose a multiscale basis space defined in the coarse interface. We will employ local snapshot spaces and local spectral decomposition following the concept of Generalized Multiscale Finite Element Methods (GMsFEM). Numerical experiments on highly heterogeneous material and nearly incompressible material are provided to verify the efficiency of the proposed method.

On Helmholtz–Hodge decomposition of inertia on a discrete local frame of reference

The notion of inertial reference frame is abandoned and I replaced it by a local reference frame on which the fundamental law of mechanics is expressed. The distant interactions of cause and effect are modeled by the propagation of waves from one local reference frame to another. The derivation of the equation of motion on a straight segment serves to express the proper acceleration as the sum of the accelerations imposed on it, in the form of an orthogonal local Helmholtz-Hodge decomposition, in one divergence-free and another curl-free contribution. I wrote the inertia term in the form of a gradient of a scalar potential and a dual curl of a vector potential. The adopted formalism opens the way to a reformulation of the material derivative in terms of potentials and allows me to remove the fictitious forces from continuum mechanics. The discrete equation of motion, invariant by rotation at constant angular velocity, is used to conserve the angular momentum per unit of mass, in addition to the conservation of energy per unit of mass and acceleration. All the variables in this equation are expressed only with two fundamental units, those of length and time.

How Simulations of the Land Carbon Sink Are Biased by Ignoring Fluvial Carbon Transfers: A Case Study for the Amazon Basin

Summary Land-surface models are important tools for simulation of the past, present, and future capacity of terrestrial ecosystems to absorb anthropogenic CO2 emissions. However, fluvial carbon (C) transfers are presently neglected in these models. Using the Amazon basin as a case study, we show that this negligence leads to significant underestimation of the net uptake of atmospheric C while terrestrial C storage changes are overestimated. These biases arise from the fact that C—in reality, leached from soils and exported through the river network—is instead represented as partly being respired and partly being stored in soils. Moreover, these biases scale mainly to the fluvial C export to the coast, despite aquatic CO2 emission to the atmosphere being the major pathway of riverine C exports. We further show that fluvial C transfers may change significantly in response to changes in either hydrology or in atmospheric C uptake by vegetation.

Solid solutions with coexisting ferroelectric and antiferroelectric phases for creation of new materials

The controlled decomposition of solid solutions in the vicinity of interphase boundaries separating domains of the coexisting antiferroelectric and ferroelectric phases opens new fields of applications for these materials. The lead zirconate–titanate based solid solutions are considered as an example of substances suitable for creation of materials with the negative refractive index. Manufactured composites constitute a dielectric antiferroelectric matrix with a structure of conducting interphase boundaries separating domains of the ferroelectric and antiferroelectric phases. The electric conductivity of the interphase boundaries occurs as a result of the local decomposition of the solid solutions in the vicinity of these boundaries. The decomposition process and consequently the conductivity of the interphase boundaries can be controlled by means of external influences.

Caracterización en línea de la dinámica temporal de señales para el monitoreo del sistema eléctrico de potencia

The characterization of dynamic phenomena is essential for monitoring the Electrical Power System subject to disturbances. This article proposes an On-line time systematic approach to analyze and characterize the temporal evolution of transient and nonlinear oscillations in these systems. Two methods are used; the first method is based on a local decomposition of the signal under study into orthogonal basis functions to obtain the dynamics of transient oscillations. Next, a second method is applied to those orthogonal basis functions to obtain analytical signals and characterize the instantaneous amplitude, phase and frequency attributes of the oscillations and determine a physical interpretation of the system’s behavior. The proposed methodology is a time-frequencyenergy analysis which can be applied to the timesynchronized Phasor Measurement Units measurements. The results demonstrate that the proposed methodology provide an accurate characterization of transient phenomena with non-stationary effects.

Local eigenvalue decomposition for embedded Riemannian manifolds

Local Principal Component Analysis can be performed over small domains of an embedded Riemannian manifold in order to relate the covariance analysis of the underlying point set with the local extrinsic and intrinsic curvature. We show that the volume of domains on a submanifold of general codimension, determined by the intersection with higher-dimensional cylinders and balls in the ambient space, have asymptotic expansions in terms of the mean and scalar curvatures. Moreover, we propose a generalization of the classical third fundamental form to general submanifolds and prove that the local eigenvalue decomposition (EVD) of the covariance matrices have asymptotic expansions that contain the curvature information encoded by the traces of this tensor. This proves the general correspondence between the local EVD integral invariants and differential-geometric curvature for arbitrary embedded Riemannian submanifolds, found so far for curves and hypersurfaces only. Thus, we establish a key theoretical bridge, via covariance matrices at scale, for potential applications in manifold learning relating the statistics of point clouds sampled from Riemannian submanifolds to the underlying geometry.

Local energy decomposition of coupled‐cluster interaction energies: Interpretation, benchmarks, and comparison with symmetry‐adapted perturbation theory

AbstractLocal energy decomposition analysis provides a breakdown of the domain‐based local pair natural orbital CCSD(T) [DLPNO‐CCSD(T)] energy into additive contributions representing the interaction between pairs of user‐defined fragments. Each of these fragment‐pairwise components can be further decomposed into a sum of physically meaningful terms, such as electrostatics, dispersion, and exchange. In this study, the dependence of such energy terms on the basis set size, the approximations used for the two‐electron integrals, and the localization scheme used for the virtual orbitals have been carefully evaluated on the interaction energies of the S66 benchmark set. A comparison with the energy components obtained at the SAPT2 + (3)δMP2 level of Symmetry‐Adapted Perturbation Theory is also provided.

Rolling element bearing weak fault diagnosis based on spatial correlation and ALIFD

Vibration signals of rolling element bearings during operation are always very complex, random strongly and broadband. Adaptive Local Iterative Filtering Decomposition (ALIFD) can overcome the smoothness and adaptive flaws of Iterative Filtering Decomposition (IFD), but it is so susceptible to random noise that it’s less effective. Here, spatial correlation was proposed. Firstly, the signal was denoised by spatial correlation and decomposed into several modes by ALIFD. Finally, the envelope demodulation was analyzed to extract fault feature. The simulating signal analysis and bearing fault simulator show that this method can be available for separating different frequencies of bearing fault vibration signals.

Spatiotemporal forecast with local temporal drift applied to weather patterns in Patagonia

Geostatistics was developed to generate maps or 3D models interpolating observed values in space. The so-called spatiotemporal geostatistic applies the same principles to estimate observed values that have both spatial and temporal distribution. Moreover, time series analysis can decompose and extrapolate its main trends and seasonality, preparing data for geostatistical assumptions. Using this principle, this study aims to decompose the time series of a spatiotemporal dataset as external drifts and estimate its residuals by spatiotemporal kriging. Since each observation point is a time series, it is possible to decompose its trend and seasonality locally and map its parameters, preferable, by traditional geostatistics. Aftermath, it is possible to extrapolate the trend and seasonality at each pixel. This procedure can achieve great long-term forecasting maps even in regions with poor sampling due to its time series analysis. As well as, the geostatistics guarantee that the spatio-temporal correlation is maintained. This method is especially good for prediction in regions that the time series pattern depends on its location, which is a common problem in large areas and the problem is worsened in poorly sampled regions. This study presents a 10 years map forecast (2008–2017) comparison by spatiotemporal geostatistics, the first with original data, with ARIMA Models Panels, then with global decomposition, finally, with the local decomposition approach. The target variable is temperature captured by the 18 active weather stations in Patagonia between 1973 and 2007. To validate the results, they are compared to Land Surface Temperature (LST), which is an image product MOD11C3 derived from the MODIS sensor onboard on Terra/Aqua satellites. The proposed method can make long-term forecasts with low error, low smoothing effect and similar spatiotemporal statistics (mean and variance) of the stations and the LST product. Finally, its results are comparable with the ARIMA Models Panels with the advantage that it can generate maps with spatiotemporal correlation and better than the often-used methods (st-kriging and global decomposition) to forecast large areas maps.

Unravelling the possibility of hydrogen storage on naphthalene dicarboxylate-based MOF linkers: a theoretical perspective

Post-synthetic modification of organic linkers embedded in a metal–organic framework (MOF) is a favourable strategy to improve the storage of hydrogen through physisorption at ambient conditions. Density functional and domain-based local pair natural orbital coupled cluster calculations are conducted to evaluate the feasibility of hydrogen adsorption on open metal sites of a Napthalene Dicarboxylate-based linker. Both alkaline metal ions like Ca2+ and Mg2+ and transition metal ions like Zn2+ and Cd2+ are chosen for this study. DFT and DLPNO-CCSD(T) energies reveal that the Napthalene Dicarboxylate systems with open magnesium, zinc and cadmium sites are capable of reversible H2 binding. However, the adsorption energy with calcium is rather low precluding build-up of H2 on CaNDC coordination site. Furthermore, local energy decomposition analysis reveals charge transfer interaction is dominant in small ions like magnesium while exchange interaction of same spin electrons governs the complexation energy in transition metals like zinc and cadmium.

Symmetry-preserving WENO-type reconstruction schemes in Lagrangian hydrodynamics

WENO (Weighted essentially non-oscillatory)-type reconstruction schemes are used to work as a limiter that preserves cylindrical symmetry for radial shock flows on an equal-angle polar mesh in Lagrangian hydrodynamics. These WENO-type limiters are tested with a high-order Lagrangian discontinuous Galerkin (DG) hydrodynamic method. In order to guarantee the compactness of the underlying DG methods, for strong shock problems, canonical WENO and Hermite WENO reconstructions are used for second-order DG(P1) and third-order DG(P2) respectively, using the known DG solution for the target cell as the central stencil. A salient feature of Hermite WENO lies in taking advantage of available information, namely the derivatives that are evolved with the DG method. With a local orthonormal basis or a local characteristic decomposition, the WENO-type reconstruction schemes can guarantee the cylindrical symmetry for Lagrangian hydrodynamics. A suite of challenging test problems are calculated to demonstrate the accuracy and robustness of these WENO-type schemes.

Local orbital-angular-momentum dependent surface states with topological protection.

Chiral surface states along the zigzag edge of a valley photonic crystal in the honeycomb lattice are demonstrated. By decomposing the local fields into orbital angular momentum (OAM) modes, we find that the chiral surface states present OAM-dependent unidirectional propagation characteristics. Particularly, the propagation directivities of the surface states are quantified by the local OAM decomposition and are found to depend on the chiralities of both the source and surface states. These findings allow for the engineering control of the unidirectional propagation of electromagnetic energy without requiring an ancillary cladding layer. Furthermore, we examine the propagation of the chiral surface states against sharp bends. It turns out that although only certain states successfully pass through the bend, the unidirectional propagation is well maintained due to the topology of the structure.

Exact Solution for Nonlinear Local Fractional Partial Differential Equations

In this work, we extend the existing local fractional Sumudu decomposition method to solve the nonlinear local fractional partial differential equations. Then, we apply this new algorithm to resolve the nonlinear local fractional gas dynamics equation and nonlinear local fractional Klein-Gordon equation, so we get the desired non-differentiable exact solutions. The steps to solve the examples and the results obtained, showed the flexibility of applying this algorithm, and therefore, it can be applied to similar examples.