内蒙古草原凋落物分解对生物多样性变化的响应

生物多样性与生态系统功能紧密相关，而凋落物分解是生态系统主要功能之一，同时凋落物的分解反过来又影响了物种的组成和多样性。本研究在内蒙古草原应用分解网袋法，通过功能群去除产生不同的多样性梯度。研究了草原生态系统的生物多样性变化对凋落物分解过程的影响。实验分为相互补充的三个部分，（一）、分解微环境实验研究了功能群多样性变化引起的分解微环境变化对凋落物分解的影响；（二）、凋落物组成实验研究四个功能群的优势物种羊草（Leymus chinensis）、大针茅（Stipa grandis）、细叶葱（Allium tenuissimum）、刺穗藜（Chenopodium aristatum）的15种不同组合方式的单种或混合凋落物在相同的分解微环境下物种间的相互作用对凋落物分解的影响；（三）、综合分解微环境和凋落物组成两种影响凋落物分解的因素，从15种多样性组合的去除样方中收集的单种或混合凋落物放回原样方分解。研究结果表明，功能群多样性，相应地物种多样性高的样方中，其微环境有利于凋落物的分解，两个生物特性差异较大的物种木地肤（Kochia prostrata）和二裂委陵菜（Potentilla bifurca）在功能群多样性高的样方中与多样性低的样方相比均表现出高的分解速率；混合凋落物的分解具有非加和性效应。混合凋落物的分解速率与其初始碳含量呈负相关关系，与其初始氮、磷含量呈正相关；当混合凋落物在功能群多样性不同的环境中分解时，重量降解速率与环境中的功能群多样性没有显著的相关关系，氮流失与功能多样性成正相关。我们的研究表明，群落中凋落物组成和凋落物多样性相比，前者是影响凋落物分解的决定性因素；与地上存活植株的生物学过程相比，凋落物分解受生物多样性的影响较小；在生物多样性更高的区域，可以显著地增加氮的循环过程，有利于提高群落生产力。

Dust emissions from a tunnel-ventilated broiler poultry shed with fresh and partially reused litter

Dust emissions from large-scale, tunnel-ventilated poultry sheds could have negative health and environmental impacts. Despite this fact, the literature concerning dust emissions from tunnel-ventilated poultry sheds in Australia and overseas is relatively scarce. Dust measurements were conducted during two consecutive production cycles at a single broiler shed on a poultry farm near Ipswich, Queensland. Fresh litter was employed during the first cycle and partially reused litter was employed during the second cycle. This provided an opportunity to study the effect that partial litter reuse has on dust emissions. Dust levels were characterised by the number concentration of suspended particles having diameter between 0.5–20 μm and by the mass concentration of dust particles below 10 μm diameter (PM10) and 2.5 μm diameter (PM2.5). In addition, we measured the number size distributions of dust particles. The average concentration and emission rate of dust was higher when partially reused litter was used in the shed than when fresh litter was used. In addition we found that dust particles emitted from the shed with partially reused litter were finer than the particles emitted with fresh litter. Although the change in litter properties is certainly contributing to this observed variability, other factors such as ventilation rate and litter moisture content are also likely to be involved.

Probabilistic subgroup identification using Bayesian finite mixture modelling : a case study in Parkinson’s disease phenotype identification

This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).

Optical and microscopic study of a polymer-nanotube mixture for organic photovoltaic applications

Organic solar cells based on bulk heterojunction between a conductive polymer and a carbon nanostructure offer potential advantages compared to conventional inorganic cells. Low cost, light weight, flexibility and high peak power per unit weight are all features that can be considered a reality for organic photovoltaics. Although polymer/carbon nanotubes solar cells have been proposed, only low power conversion efficiencies have been reached without addressing the mechanisms responsible for this poor performance. The purpose of this work is therefore to investigate the basic interaction between carbon nanotubes and poly(3-hexylthiophene) in order to demonstrate how this interaction affects the performance of photovoltaic devices. The outcomes of this study are the contributions made to the knowledge of the phenomena explaining the behaviour of electronic devices based on carbon nanotubes and poly(3-hexylthiophene). In this PhD, polymer thin films with the inclusion of uniformly distributed carbon nanotubes were deposited from solution and characterised. The bulk properties of the composites were studied with microscopy and spectroscopy techniques to provide evidence of higher degrees of polymer order when interacting with carbon nanotubes. Although bulk investigation techniques provided useful information about the interaction between the polymer and the nanotubes, clear evidence of the phenomena affecting the heterojunction formed between the two species was investigated at nanoscale. Identifying chirality-driven polymer assisted assembly on the carbon nanotube surface was one of the major achievements of this study. Moreover, the analysis of the electrical behaviour of the heterojunction between the polymer and the nanotube highlighted the charge transfer responsible for the low performance of photovoltaic devices. Polymer and carbon nanotube composite-based devices were fabricated and characterised in order to study their electronic properties. The carbon nanotube introduction in the polymer matrix evidenced a strong electrical conductivity enhancement but also a lower photoconductivity response. Moreover, the extension of pristine polymer device characterisation models to composites based devices evidenced the conduction mechanisms related to nanotubes. Finally, the introduction of carbon nanotubes in the polymer matrix was demonstrated to improve the pristine polymer solar cell performance and the spectral response even though the power conversion efficiency is still too low.

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

Pyrolysing poultry litter reduces N2O and CO2 fluxes

Application of poultry litter (PL) to soil can lead to substantial nitrous oxide (N2O) emissions due to the co-application of labile carbon (C) and nitrogen (N). Slow pyrolysis of PL to produce biochar may mitigate N2O emissions from this source, whilst still providing agronomic benefits. In a corn crop on ferrosol with similarly matched available N inputs of ca. 116 kg N/ha, PL-biochar plus urea emitted significantly less N2O (1.5 kg N2O-N/ha) compared to raw PL at 4.9 kg N2O-N/ha. Urea amendment without the PL-biochar emitted 1.2 kg N2O-N/ha, and the PL-biochar alone emitted only 0.35 kg N2O-N/ha. Both PL and PL-biochar resulted in similar corn yields and total N uptake which was significantly greater than for urea alone. Using stable isotope methodology, the majority (~ 80%) of N2O emissions were shown to be from non-urea sources. Amendment with raw PL significantly increased C mineralisation and the quantity of permanganate oxidisable organic C. The low molar H/C (0.49) and O/C (0.16) ratios of the PL-biochar suggest its higher stability in soil than raw PL. The PL-biochar also had higher P and K fertiliser value than raw PL. This study suggests that PL-biochar is a valuable soil amendment with the potential to significantly reduce emissions of soil greenhouse gases compared to the raw product. Contrary to other studies, PL-biochar incorporated to 100 mm did not reduce N2O emissions from surface applied urea, which suggests that further field evaluation of biochar impacts, and methods of application of both biochar and fertiliser, are needed.

Regional contingencies in the relationship between aboveground biomass and litter in the world’s grasslands

Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.

Fast re-parameterisation of Gaussian mixture models for robotics applications

Autonomous navigation and picture compilation tasks require robust feature descriptions or models. Given the non Gaussian nature of sensor observations, it will be shown that Gaussian mixture models provide a general probabilistic representation allowing analytical solutions to the update and prediction operations in the general Bayesian filtering problem. Each operation in the Bayesian filter for Gaussian mixture models multiplicatively increases the number of parameters in the representation leading to the need for a re-parameterisation step. A computationally efficient re-parameterisation step will be demonstrated resulting in a compact and accurate estimate of the true distribution.

Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model

This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000-2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. © 2012 Elsevier B.V.