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It is widely reported that the productivity-richness relation (PRR) is highly variable, and several field studies suggest that the PRR varies with observational scale. Here we provide the first experimental study to test whether the PRR is scale-dependent when all replicate ecosystems have similar initial conditions. We also test the relation between productivity and compositional dissimilarity, and whether the PRR varies with ecosystem size. Moderately complex replicated microcosms were assembled consisting of a range of protozoa, algae, and a diverse bacterial flora. We found that the PRR of protozoan and algal communities varied with observational scale, but was unrelated to ecosystem size. Specifically, protozoan and algal richness increased monotonically with productivity at the local scale, but became flattened at the regional scale. This varying PRR at different scales occurred because dissimilarity among replicates decreased with productivity. Thus, in this model system, our experimental approach found a different form of scale dependence than previous field research. We speculate that this difference results from different processes governing extinctions at low levels of productivity.

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Abstract  

A modified NiS fire-assay neutron activation method is developed for the determination of all platinum-group elements (PGEs) in mantle-derived xenoliths. This method is characterized by sub-ppb detection limits, <0.1~0.002 ppb procedural blanks and 7~15% analytical precision for PGEs. Analyses of PGE standard rocks indicate that this modified NiS fire-assay neutron activation method is as reliable as the method previously proposed for a large scale of samples. The capability of the method for the measurement of PGEs in the upper mantle is also illustrated by some exciting results obtained from mantle-derived xenoliths of Eastern China.

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This investigation is one of the first to adopt quantile regression (QR) technique to examine covariance risk dynamics in international stock markets. Feasibility of the proposed model is demonstrated in G7 stock markets. Additionally, two conventional random-coefficient frameworks, including time-varying betas derived from GARCH models and state-varying betas implied by Markov-switching models, are employed and subjected to comparative analysis. The empirical findings of this work are consistent with the following notions. First, the beta smile (beta skew) curve for the Italian, U.S. and U.K. (Canadian, French and German) markets. That is, covariance risk among global stock markets in extremely bull and/or bear market states is significantly higher than in stable periods. Additionally, the Japanese market provides a special case, and its beta estimate at extremely bust state is significantly lower, not higher than that at the middle region. Second, the quantile-varying betas are identified as possessing two key advantages. Specifically, the comparison of the system with quantile-varying betas against that with time-varying betas implied by GARCH models provides meaningful implications for correlation-volatility relationship among international stock markets. Furthermore, the quantile-varying beta design in this study relaxes a simple dual beta setting implied by Markov-switching models of Ramchand — Susmel (1998) and can identify dynamics of asymmetry in betas.

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SOFM (self-organizing feature map) clustering is powerful in analyzing and solving complicated and non-linear problems. This method was used and compared with fuzzy C-means clustering and TWINSPAN, the most common classification methods, in analysis of plant communities in the Guancen Mts., China. The dataset consisted of importance values of 112 species in 53 quadrats of 10 m × 20 m. All the three methods classified the 53 quadrats into eight groups, representing eight associations of vegetation. They were all effective in the analysis of ecological data. The consistency of SOFM clustering with fuzzy C-means clustering (FCM) and TWINSPAN classification was 81.1% and 94.3%, respectively. SOFM clustering has some advantages and more potentiality in application to studies of ecology.

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Crystallization, morphology and mechanical properties of a spodumene-diopside glass ceramics with adding different amount of CaO and MgO in Li2O-Al2O3-2SiO2 were investigated. With CaO and MgO addition, the crystallization temperature (T p) decreased, the value of Avrami constant (n) decreased from 3.2±0.3 to 1.4±0.2, the activation energy (E) increased from 299±3 kJ mol−1 to 537±5 kJ mol−1. The crystalline phases precipitated were h-quartz solid solution, β-spodumene and diopside. The mechanism of crystallization of the glass ceramics changed from bulk crystallization to surface crystallization. The grain sizes and thermal expansion coefficients increased while flexural strength and fracture toughness of the glass-ceramics increased first, and then decreased. The mechanical properties were correlated with crystallization and morphology of glass ceramics.

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An efficient method used to separate five bioactive compounds from Gelidium amansii was optimized by the HCI software. The optimum composition of mobile phase for high-performance liquid chromatographic (HPLC) separation was obtained. The elution profiles were calculated by the polynomial theory based on the retention factor ln k = A + BF + CF 2 (F was the volume percentage of acetonitrile with 1.0% acetic acid); then, the theory was applied to calculate the elution profile in both isocratic and gradient modes by modifying different mobile phase conditions with HCI program. The calculated results of mobile phase condition suggested that acetonitrile-water (containing 1.0% acetic acid) with a linear gradient elution of 0∼30 min from 15:85 to 50:50 (v/v) was the optimized component. In the experimental conditions, the agreement between the experimental elution profiles and the calculated values of eluted concentration was relatively good.

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TG and DTA experiments were performed to investigate the biomass tar combustion behavior in coexistence of dolomite and mayenite at two different heating rates as 5 and 15°C min−1. Different reaction kinetic mechanisms with the classical Arrhenius model were used to treat TG data, and showed that the first-order combustion model fitted the data well. Three stages combustion model was proposed and applied for the calculation of kinetics parameters successfully. The starting temperature of high temperature combustion stage moved up near 100°C because of the coexistence catalysts, and the combustion amount of biomass of the stage also improved nearly 10 mass%. By calculation a uniform trend of decreasing activation energies was observed with the addition of dolomite and mayenite, and also greatly improved the amount and speed of tar combustion process.

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The decomposition kinetics of reference calcite and three ultra-fine samples with different morphologies are investigated. The kinetic parameters and rate equation are obtained according to the methods reported in our previous studies. Compared with the reference calcite, a considerable diminution of the activation energy E a up to 70–80 kJ mol−1 is observed in the case of three ultra-fine samples. There are also some distinct differences concerning the activation energy of each of the ultra-fine sample. This may have something to do with the particle morphology revealed by TEM and SEM measurements. XRD measurements of four calcite samples show that large strain exists in the crystal lattice in the case of ultra-fine calcite samples. This may give a reason to their abnormal decomposition behavior.

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A simple direct labeling method was used to synthesize the iodinated ultrafine polystyrene particles. The assay of X-ray photoelectron spectroscopy (XPS) as well as Fourier-transform infrared (FT-IR) spectroscopy indicated the formation of stable covalent bond to aryl group of the polymer particles. The purified radioiodinated product was incubated with serum of rat, and then evaluated by in vitro stability test. The result showed that these synthesized ultrafine polystyrene particles were unmetabolized at 2 hours post-exposure, indicating the potential useful application of this labeled polymer particles as a promising probe in biomedical sciences.

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