Decomposition of the environmental Kuznets curve : scale, technique, and composition effects

This study decomposed the determinants of environmental quality into scale, technique, and composition effects. We applied a semiparametric method of generalized additive models, which enabled us to use flexible functional forms and include several independent variables in the model. The differences in the technique effect were found to play a crucial role in reducing pollution. We found that the technique effect was sufficient to reduce sulfur dioxide emissions. On the other hand, its effect was not enough to reduce carbon dioxide (CO2) emissions and energy use, except for the case of CO2 emissions in high-income countries.

Insight into the thermal decomposition of kaolinite intercalated with potassium acetate : an evolved gas analysis

The thermal decomposition process of kaolinite–potassium acetate intercalation complex has been studied using simultaneous thermogravimetry coupled with Fourier-transform infrared spectroscopy and mass spectrometry (TG-FTIR-MS). The results showed that the thermal decomposition of the complex took place in four temperature ranges, namely 50–100, 260–320, 320–550, and 650–780 °C. The maximal mass losses rate for the thermal decomposition of the kaolinite–potassium acetate intercalation complex was observed at 81, 296, 378, 411, 486, and 733 °C, which was attributed to (a) loss of the adsorbed water, (b) thermal decomposition of surface-adsorbed potassium acetate (KAc), (c) the loss of the water coordinated to potassium acetate in the intercalated kaolinite, (d) the thermal decomposition of intercalated KAc in the interlayer of kaolinite and the removal of inner surface hydroxyls, (e) the loss of the inner hydroxyls, and (f) the thermal decomposition of carbonate derived from the decomposition of KAc. The thermal decomposition of intercalated potassium acetate started in the range 320–550 °C accompanied by the release of water, acetone, carbon dioxide, and acetic acid. The identification of pyrolysis fragment ions provided insight into the thermal decomposition mechanism. The results showed that the main decomposition fragment ions of the kaolinite–KAc intercalation complex were water, acetone, carbon dioxide, and acetic acid. TG-FTIR-MS was demonstrated to be a powerful tool for the investigation of kaolinite intercalation complexes. It delivers a detailed insight into the thermal decomposition processes of the kaolinite intercalation complexes characterized by mass loss and the evolved gases.

Family tree

Artist's Statement: These suspended shipping floats symbolise the artist's grandfather's home on Keriri (Hammond Island), where the trees are decorated with floats of all colours that have washed up on the beach. Across the entire Torres Strait, these floats, often from Asia, wash ashore and become decorative objects, strung from trees and hung from island shacks. Their vivid colours, and sometimes reflective glass surfaces, play against the lush tropical setting, while their re-use reflects the innovative character of island life. This arrangement of the floats represents the artist's family tree, which he has traced back six generations to Mer (Murray Island) and Keriri. The strings of orange floats represent his immediate family and direct lineage, each member of which is named on a float, with the totem of the family painted on the base. The remaining floats trace additional ancestry and spread further back through time and space, spanning the Torres Strait from west to east.

Child's body in tree adds to Lockyer Valley death toll

"Two more bodies, including a that of child discovered in a tree, were retrieved in the Lockyer Valley at the weekend, reinforcing the grisly complexity of the search for the missing."

Injury narrative text classification : a preliminary study

Description of a patient's injuries is recorded in narrative text form by hospital emergency departments. For statistical reporting, this text data needs to be mapped to pre-defined codes. Existing research in this field uses the Naïve Bayes probabilistic method to build classifiers for mapping. In this paper, we focus on providing guidance on the selection of a classification method. We build a number of classifiers belonging to different classification families such as decision tree, probabilistic, neural networks, and instance-based, ensemble-based and kernel-based linear classifiers. An extensive pre-processing is carried out to ensure the quality of data and, in hence, the quality classification outcome. The records with a null entry in injury description are removed. The misspelling correction process is carried out by finding and replacing the misspelt word with a soundlike word. Meaningful phrases have been identified and kept, instead of removing the part of phrase as a stop word. The abbreviations appearing in many forms of entry are manually identified and only one form of abbreviations is used. Clustering is utilised to discriminate between non-frequent and frequent terms. This process reduced the number of text features dramatically from about 28,000 to 5000. The medical narrative text injury dataset, under consideration, is composed of many short documents. The data can be characterized as high-dimensional and sparse, i.e., few features are irrelevant but features are correlated with one another. Therefore, Matrix factorization techniques such as Singular Value Decomposition (SVD) and Non Negative Matrix Factorization (NNMF) have been used to map the processed feature space to a lower-dimensional feature space. Classifiers with these reduced feature space have been built. In experiments, a set of tests are conducted to reflect which classification method is best for the medical text classification. The Non Negative Matrix Factorization with Support Vector Machine method can achieve 93% precision which is higher than all the tested traditional classifiers. We also found that TF/IDF weighting which works well for long text classification is inferior to binary weighting in short document classification. Another finding is that the Top-n terms should be removed in consultation with medical experts, as it affects the classification performance.

Turbulence measurements in a shallow tidal estuary : analysis based on triple decomposition

In an estuary, mixing and dispersion are the result of the combination of large scale advection and small scale turbulence which are both complex to estimate. A field study was conducted in a small sub-tropical estuary in which high frequency (50 Hz) turbulent data were recorded continuously for about 48 hours. A triple decomposition technique was introduced to isolate the contributions of tides, resonance and turbulence in the flow field. A striking feature of the data set was the slow fluctuations which exhibited large amplitudes up to 50% the tidal amplitude under neap tide conditions. The triple decomposition technique allowed a characterisation of broader temporal scales of high frequency fluctuation data sampled during a number of full tidal cycles.

Analysing the similarity of proteins based on a new approach to empirical mode decomposition

The function of a protein can be partially determined by the information contained in its amino acid sequence. It can be assumed that proteins with similar amino acid sequences normally have closer functions. Hence analysing the similarity of proteins has become one of the most important areas of protein study. In this work, a layered comparison method is used to analyze the similarity of proteins. It is based on the empirical mode decomposition (EMD) method, and protein sequences are characterized by the intrinsic mode functions (IMFs). The similarity of proteins is studied with a new cross-correlation formula. It seems that the EMD method can be used to detect the functional relationship of two proteins. This kind of similarity method is a complement of traditional sequence similarity approaches which focus on the alignment of amino acids

Perturbed Lignification Impacts Tree Growth in Hybrid Poplar-A Function of Sink Strength, Vascular Integrity, and Photosynthetic Assimilation

The effects of reductions in cell wall lignin content, manifested by RNA interference suppression of coumaroyl 3'-hydroxylase, on plant growth, water transport, gas exchange, and photosynthesis were evaluated in hybrid poplar trees (Populus alba 3 grandidentata). The growth characteristics of the reduced lignin trees were significantly impaired, resulting in smaller stems and reduced root biomass when compared to wild-type trees, as well as altered leaf morphology and architecture. The severe inhibition of cell wall lignification produced trees with a collapsed xylem phenotype, resulting in compromised vascular integrity, and displayed reduced hydraulic conductivity and a greater susceptibility to wall failure and cavitation. In the reduced lignin trees, photosynthetic carbon assimilation and stomatal conductance were also greatly reduced, however, shoot xylem pressure potential and carbon isotope discrimination were higher and water-use efficiency was lower, inconsistent with water stress. Reductions in assimilation rate could not be ascribed to increased stomatal limitation. Starch and soluble sugars analysis of leaves revealed that photosynthate was accumulating to high levels, suggesting that the trees with substantially reduced cell wall lignin were not carbon limited and that reductions in sink strength were, instead, limiting photosynthesis.

A model-framed evaluation of elephant effects on tree and fire dynamics in African savannas

There is a concern that high densities of elephants in southern Africa could lead to the overall reduction of other forms of biodiversity. We present a grid-based model of elephant-savanna dynamics, which differs from previous elephant-vegetation models by accounting for woody plant demographics, tree-grass interactions, stochastic environmental variables (fire and rainfall), and spatial contagion of fire and tree recruitment. The model projects changes in height structure and spatial pattern of trees over periods of centuries. The vegetation component of the model produces long-term tree-grass coexistence, and the emergent fire frequencies match those reported for southern African savannas. Including elephants in the savanna model had the expected effect of reducing woody plant cover, mainly via increased adult tree mortality, although at an elephant density of 1.0 elephant/km2, woody plants still persisted for over a century. We tested three different scenarios in addition to our default assumptions. (1) Reducing mortality of adult trees after elephant use, mimicking a more browsing-tolerant tree species, mitigated the detrimental effect of elephants on the woody population. (2) Coupling germination success (increased seedling recruitment) to elephant browsing further increased tree persistence, and (3) a faster growing woody component allowed some woody plant persistence for at least a century at a density of 3 elephants/km2. Quantitative models of the kind presented here provide a valuable tool for exploring the consequences of management decisions involving the manipulation of elephant population densities. © 2005 by the Ecological Society of America.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

A Monte-Carlo tree search in argumentation

Monte-Carlo Tree Search (MCTS) is a heuristic to search in large trees. We apply it to argumentative puzzles where MCTS pursues the best argumentation with respect to a set of arguments to be argued. To make our ideas as widely applicable as possible, we integrate MCTS to an abstract setting for argumentation where the content of arguments is left unspecified. Experimental results show the pertinence of this integration for learning argumentations by comparing it with a basic reinforcement learning.

Micromorphology and anatomy of leaves of Syzygium floribundum (Myrtaceae: Syzygieae), a rainforest tree endemic to eastern Australia

Although species of Syzygium are abundant components of the rainforests in Queensland and New South Wales, little is known about the anatomy of the Australian taxa. Here we describe the foliar anatomy and micromorphology of Syzygium floribundum (syn: Waterhousea floribunda) using standard protocols for scanning electron microscopy (SEM) and light microscopy. Syzygium floribundum possesses dorsiventral leaves with cyclo-staurocytic stomata, single epidermis, internal phloem, rhombus-shaped calcium oxalate crystals and complex-open midrib. In general, leaf anatomical and micromorphological characters are common with some species of the tribe Syzygieae. However, this particular combination of leaf characters has not been reported in a species of the genus. The anatomy of the species is typical of mesophytic taxa.

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%).