Using the moving window incorporated neural network to forecast the population behavior of Nostocales spp. in the River Darling, Australia

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical populations of Nostocales spp. in the River Darling, Australia. Freshwater ecosystems are more likely to be nonstationary, instead of stationary. Nonstationarity implies that only the near past behaviors could forecast the near future for the system. However, nonstionarity was not considered seriously in previous research efforts for modeling and predicting algal population behaviors. Therefore the moving window technique was incorporated with radial basis function neural network (RBFNN) approach to deal with nonstationarity when modeling and forecasting the population behaviors of Nostocales spp. in the River Darling. The results showed that the RBFNN model could predict the timing and magnitude of algal blooms of Nostocales spp. with high accuracy. Moreover, a combined model based on individual RBFNN models was implemented, which showed superiority over the individual RBFNN models. Hence, the combined model was recommended for the modeling and forecasting of the phytoplankton populations, especially for the forecasting.

Modeling phytoplankton dynamics in the River Darling (Australia) using the radial basis function neural network

A radial basis function neural network was employed to model the abundance of cyanobacteria. The trained network could predict the populations of two bloom forming algal taxa with high accuracy, Nostocales spp. and Anabaena spp., in the River Darling, Australia. To elucidate the population dynamics for both Nostocales spp. and Anabaena spp., sensitivity analysis was performed with the following results. Total Kjeldahl nitrogen had a very strong influence on the abundance of the two algal taxa, electrical conductivity had a very strong negative relationship with the population of the two algal species, and flow was identified as one dominant factor influencing algal blooms after a scatter plot revealed that high flow could significantly reduce the algal biomass for both Nostocales spp. and Anabaena spp. Other variables such as turbidity, color, and pH were less important in determining the abundance and succession of the algal blooms.

Analysis of estrogens in environmental waters using polymer monolith in-polyether ether ketone tube solid-phase microextraction combined with high-performance liquid chromatography

A simple, rapid and sensitive on-line method for simultaneous determination of four endocrine disruptors (17 beta-estradiol, estriol, bisphenol A and 17 alpha-ethinylestradiol) in environmental waters was developed by coupling in-tube solid-phase microextraction (SPME) to high-performance liquid chromatography (HPLC) with fluorescence detection (FLD). A poly(acrylamide-vinylpyridine-NAP-methylene bisacrylamide) monolith, synthesized inside a polyether ether ketone (PEEK) tube, was selected as the extraction medium. To achieve optimum extraction performance, several parameters were investigated, including extraction flow-rate, extraction time, and pH value, inorganic salt and organic solvent content of the sample matrix. By simply filtered with nylon membrane filter and adjusting the pH of samples to 6.0 with phosphoric acid, the sample solution then could be directly injected into the device for extraction. Low detection limits (S/N = 3) and quantification limits (S/N = 10) of the proposed method were achieved in the range of 0.006-0.10 ng/mL and 0.02-0.35 ng/mL from spiked lake waters, respectively. The calibration curves of four endocrine disruptors showed good linearity ranging from quantification limits to 50 ng/mL with a linear coefficient R-2 value above 0.9913. Good method reproducibility was also found by intra- and inter-day precisions, yielding the RSDs less than 12 and 9.8%, respectively. Finally, the proposed method was successfully applied to the determination of these compounds in several environmental waters. (c) 2006 Elsevier B.V. All rights reserved.

Oxygen vacancy defects in Ta2O5 showing long-range atomic re-arrangements

The structure, formation energy, and energy levels of the various oxygen vacancies in Ta2O5 have been calculated using the λ phase model. The intra-layer vacancies give rise to unusual, long-range bonding rearrangements, which are different for each defect charge state. The 2-fold coordinated intra-layer vacancy is the lowest cost vacancy and forms a deep level 1.5 eV below the conduction band edge. The 3-fold intra-layer vacancy and the 2-fold inter-layer vacancy are higher cost defects, and form shallower levels. The unusual bonding rearrangements lead to low oxygen migration barriers, which are useful for resistive random access memory applications. © 2014 AIP Publishing LLC.

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Defects in gallium nitride nanowires: First principles calculations

Atomic configurations and formation energies of native defects in an unsaturated GaN nanowire grown along the [001] direction and with (100) lateral facets are studied using large-scale ab initio calculation. Cation and anion vacancies, antisites, and interstitials in the neutral charge state are all considered. The configurations of these defects in the core region and outermost surface region of the nanowire are different. The atomic configurations of the defects in the core region are same as those in the bulk GaN, and the formation energy is large. The defects at the surface show different atomic configurations with low formation energy. Starting from a Ga vacancy at the edge of the side plane of the nanowire, a N-N split interstitial is formed after relaxation. As a N site is replaced by a Ga atom in the suboutermost layer, the Ga atom will be expelled out of the outermost layers and leaves a vacancy at the original N site. The Ga interstitial at the outmost surface will diffuse out by interstitialcy mechanism. For all the tested cases N-N split interstitials are easily formed with low formation energy in the nanowires, indicating N-2 molecular will appear in the GaN nanowire, which agrees well with experimental findings.

First-principle study of native defects in CuScO2 and CuYO2

This paper studies the electronic structure and native defects intransparent conducting oxides CuScO2 and CuYO2 using the first-principle calculations. Some typical native copper-related and oxygen-related defects, such as vacancy, interstitials, and antisites in their relevant charge state are considered. The results of calculation show that, CuMO2 (M = Sc, Y) is impossible to shown-type conductivity ability. It finds that copper vacancy and oxygen interstitial have relatively low formation energy and they are the relevant defects in CuScO2 and CuYO2. Copper vacancy is the most efficient acceptor, and under O-rich condition oxygen antisite also becomes important acceptor and plays an important role in p-type conductivity.

First-principles study of defects in CuGaO2

Using the first-principles methods, we study the electronic structure, intrinsic and extrinsic defects doping in transparent conducting oxides CuGaO2. Intrinsic defects, acceptor-type and donor-type extrinsic defects in their relevant charge state are considered. The calculation result show that copper vacancy and oxygen interstitial are the relevant defects in CuGaO2. In addition, copper vacancy is the most efficient acceptor. Substituting Be for Ga is the prominent acceptor, and substituting Ca for Cu is the prominent donors in CuGaO2. Our calculation results are expected to be a guide for preparing n-type and p-type materials in CuGaO2.

First-principle study of extrinsic defects in CuScO2 and CuYO2

Using first-principles methods, we studied the extrinsic defects doping in transparent conducting oxides CuMO2 (M=Sc, Y). We chose Be, Mg, Ca, Si, Ge, Sn as extrinsic defects to substitute for M and Cu atoms. By systematically calculating the impurity formation energy and transition energy level, we find that Be-Cu is the most prominent extrinsic donor and Ca-M is the prominent extrinsic acceptor. In addition, we find that Mg atom substituting for Sc is the most prominent extrinsic acceptor in CuSCO2. Our calculation results are expected to be a guide for preparing n-type and p-type materials through extrinsic doping in CuMO2 (M=SC, y). (C) 2008 Elsevier B.V. All rights reserved.

Evolution of structural defects in SiOx films fabricated by electron cyclotron resonance plasma chemical vapour deposition upon annealing treatment

We study the structural defects in the SiOx film prepared by electron cyclotron resonance plasma chemical vapour deposition and annealing recovery evolution. The photoluminescence property is observed in the as-deposited and annealed samples. [-SiO3](2-) defects are the luminescence centres of the ultraviolet photoluminescence (PL) from the Fourier transform infrared spectroscopy and PL measurements. [-SiO3](2-) is observed by positron annihilation spectroscopy, and this defect can make the S parameters increase. After 1000 degrees C annealing, [-SiO3](2-) defects still exist in the films.

Annihilation of deep level defects in InP through high temperature annealing

Deep level transient spectroscopy (DLTS) and thermally stimulated current spectroscopy (TSC) have been used to investigate defects in semi-conducting and semi-insulating (SI) InP after high temperature annealing, respectively. The results indicate that the annealing in iron phosphide ambient has an obvious suppression effect of deep defects, when compared with the annealing in phosphorus ambient. A defect annihilation phenomenon has also been observed in Fe-doped SI-InP materials after annealing. Mechanism of defect formation and annihilation related to in-diffusion of iron and phosphorus is discussed. Nature of the thermally induced defects has been discussed based on the results. (c) 2007 Elsevier Ltd. All rights reserved.

First-principles study of native defects in rutile TiO2

Native point defects in the rutile TiO2 are studied via first-principles pseudopotential calculations. Except for the two antisite defects, all the native point defects have low formation energies. Under the Ti-rich growth condition, high concentrations of titanium interstitials and oxygen vacancies would form spontaneously in p-type samples; whereas high concentrations of titanium vacancies would form spontaneously in n-type samples regardless of the oxygen partial pressure. (c) 2007 Elsevier B.V. All rights reserved.

Single-electron tunneling depressing synapse for cellular neural networks

In this paper, a cellular neural network with depressing synapses for contrast-invariant pattern classification and synchrony detection is presented, starting from the impulse model of the single-electron tunneling junction. The results of the impulse model and the network are simulated using simulation program with integrated circuit emphasis (SPICE). It is demonstrated that depressing synapses should be an important candidate of robust systems since they exhibit a rapid depression of excitatory postsynaptic potentials for successive presynaptic spikes.

Investigation of native defects and property of bulk ZnO single crystal grown by a closed chemical vapor transport method

Hall effect, Raman scattering, photoluminescence spectroscopy (PL), optical absorption (OA), mass spectroscopy, and X-ray diffraction have been used to study bulk ZnO single crystal grown by a closed chemical vapor transport method. The results indicate that shallow donor impurities (Ga and Al) are the dominant native defects responsible for n-type conduction of the ZnO single crystal. PL and OA results suggest that the as-grown and annealed ZnO samples with poor lattice perfection exhibit strong deep level green photoluminescence and weak ultraviolet luminescence. The deep level defect in as-grown ZnO is identified to be oxygen vacancy. After high-temperature annealing, the deep level photoluminescence is suppressed in ZnO crystal with good lattice perfection. In contrast, the photoluminescence is nearly unchanged or even enhanced in ZnO crystal with grain boundary or mosaic structure. This result indicates that a trapping effect of the defect exists at the grain boundary in ZnO single crystal. (C) 2007 Elsevier B.V. All rights reserved.