Zero-non-zero patterned vector error correction modeling for I(2) cointegrated time series with applications in testing PPP and stock market relationships

Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

Exploring Relationships Between Vector-Borne Diseases and Landscape Architecture: Aedes aegypti, Aedes albopictus and Landscape Architecture

Thesis (Master's)--University of Washington, 2016-06

Characterization of electrical penetration graphs of Bucephalogonia xanthophis, a vector of Xylella fastidiosa in citrus

The sharpshooter Bucephalogonia xanthophis (Berg) (Homoptera: Cicadellidae) is a vector of the xylem-limited bacterium, Xylella fastidiosa (Wells, Raju, Hung, Weisburg, Mandelco-Paul, and Brenner), which causes citrus variegated chlorosis. Despite the importance of citrus variegated chlorosis, the probing behavior of vectors on citrus and its implications for transmission of X. fastidiosa have not been studied. Here we studied electrical penetration graph (EPG-DC system) waveforms produced by B. xanthophis on Citrus sinensis (L.) Osbeck (Rutaceae), and their relationships with stylet activities and xylem ingestion. Electrical penetration graph waveforms were described based on amplitude, frequency, voltage level, and electrical origin of the observed traces during stylet penetration on plant tissues. The main waveforms were correlated with histological observations of salivary sheaths in plant tissues and excretion analysis, in order to determine stylet activities and their precise position. Six waveforms and associated activities are described: (S) secretion of salivary sheath and intracellular stylet pathway, (R) resting during stylet pathway, (Xc) contact of stylets with xylem vessels, (Xi) active xylem ingestion, (N) interruption within the xylem phase (during Xc or Xi), and (W) withdrawal of stylet from the plant. The sharpshooter spent 91.8% of its probing time with its stylet in the xylem, where the main activity was ingestion (Xi: 97.5%). During a probe, the most likely sequence of events is secretion of salivary sheath and pathway (S) through epidermal and parenchyma cells (all individuals), followed by contact with xylem (Xc) (67.6% of all individuals) and ingestion (Xi) (88.3% of those that exhibit waveform Xc). The mean time to contact the xylem (Xc) and initiate ingestion (Xi) after onset of the first probe was 27.8 and 34.2 min, respectively. However, sustained xylem ingestion (Xi > 5 min) was established after 39.8 min, on average. This information is basic for future studies on the transmission mechanisms of X. fastidiosa and in order to establish control strategies aimed at interfering with this process.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

Phylogenetic relationships of Hepatozoon (Haemogregarina) boigae Hepatozoon sp. Haemogregarina clelandi and Haemoproteus chelodina from Australian reptiles to other Apicomplexa based on cladistic analyses of ultrastructural and life-cycle characters

The phylogeny of representative haemozoan species of the phylum Apicomplexa was reconstructed by cladistic analyses of ultrastructural and life-cycle characteristics. The analysis incorporated 4 apicomplexans previously not included in phylogenetic reconstructions: Haemogregarina clelandi from the Brisbane River tortoise (Emydura signata), Hepatozoon sp. from the slaty grey snake (Stegonotus cucullatus), Hepatozoon (Haemogregarina) boigae from the brown tree snake (Boiga irregularis), and Haemoproteus chelodina from the saw-shelled tortoise (Elseya latisternum). There was no apparent correlation between parasite phylogeny and that of their vertebrate hosts, but there appeared to be some relationship between parasites and their intermediate hosts, suggestive of parasite/vector co-evolution.

Fecundity, parity, and adult feeding relationships among Nyssorhynchus malaria vectors from Venezuela

Relative to their pre-engorgement weights, nulliparous Anopheles nuneztovari consumed significantly smaller blood meals than A. marajoara, A. triannulatus or A. aquasalis. When females were deprived of sugar before blood feeding, only one-quarter of A. nuneztovari, but more than two-thirds of A. marajoara, A. triannulatus and A. aquasalis matured eggs. Sugar feeding before blood, or two sucessive blood meals by sugar-deprived females, increased the proportion of nulliparous a. nuneztovari which developed eggs, but not significantly so. Nearly all individuals of nulliparous, sugar-fed A. marajoara, A. triannulatus and A. aquasalis matured eggs after one blood feeding. Among A. nuneztovari, A. marajoara and A. aquasalis that matured some eggs in the laboratory, there were no positive correlations between the number of eggs developed and relative vlood mealsize. However, blood meals larger than the mean size significantly increased the chance that A. nuneztovari would develop some eggs. Mean fecundities of gravid A. nuneztovari and A. marajoara reared in the laboratory were significantly lower than those of the same species captured at human bait in nature. Post-engorgement access to sugar by A. nuneztovari (captured at human bait) did not influence fecundity, but significantly enhanced survivorship and the proporticon of individuals which retained eggs. Release-recapture experiments revealed that relatively small blood meals are typical of A. nuneztovari only during the first gonotrophic cycle. We suggest that multiple blood feeding, seemingly necessary for most A. nuneztovari to develop a first clutch of eggs, may increase the probability of infection with Plasmodium vivax where this mosquito species is a primary vector.

Biological rhythms and vector insects

The adjustment of all species, animals and plants, to the Earth’s cyclic environments is ensured by their temporal organisation. The relationships between parasites, vectors and hosts rely greatly upon the synchronisation of their biological rhythms, especially circadian rhythms. In this short note, parasitic infections by Protozoa and by microfilariae have been chosen as examples of the dependence of successful transmission mechanisms on temporal components.

Bayesian estimation and selection of nonlinear vector error correction models: The case of the sugar-ethanol-oil nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

Phylogenetic relationships among species of Anopheles (Nyssorhynchus) (Diptera, Culicidae) based on nuclear and mitochondrial gene sequences

Phylogenetic relationships among 21 species of mosquitoes in subgenus Nyssorhynchus were inferred from the nuclear white and mitochondrial NADH dehydrogenase subunit 6 (ND6) genes. Bayestan phylogenetic methods found that none of the three Sections within Nyssorhynchus (Albimanus, Argyritarsis, Myzorhynchella) were supported in all analyses, although Myzorhynchella was found to be monophyletic at the combined genes Within the Albimanus Section the monophyly of the Stroder Subgroup was strongly supported and within the Myzorhynchella Section Anopheles anrunesi and An lutzu formed a strongly supported monophyletic group The epidemiologically significant Albitarsis Complex showed evidence of paraphyly (relative to An lanet-Myzorhynchella) and discordance across gene trees, and the previously synonomized species of An. dunhami and An goeldii were recovered as sister species Finally, there was evidence of complexes in several species, including An antunesi, An deaneorum, and An. strodei (c) 2010 Elsevier B.V. All rights reserved

The relationships of alternative energies with the technology sector and non-renewable energies

Este trabalho tem como objectivo compreender de que forma os investidores veem as energias renováveis: se as veem como parte do sector tecnológico, à espera de novos desenvolvimentos, ou como uma alternativa aos métodos existentes de produção de energia. Para responder a esta questão, foi desenvolvido um modelo de vectores autoregressivos com quatro variáveis de forma a se poder aplicar um Granger causality test e Impulse Response function. Os resultados sugerem que para o período de 2002-2007 à escala global ambas as hipóteses se confirmam, porém de 2009-2014 os resultados sugerem que os investidores não reconhecem as energias renováveis como um ramo do sector tecnológico, neste período. Para além disso, durante o período de 2009-2014, e quando comparados investidores Americanos com Europeus, os resultados sugerem que apenas o último identifica as energias renováveis como uma fonte viável para a produção energética.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Ontology-based protein-protein interactions extraction from literature using the hidden vector state model

This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

LRD : Latent Relation Discovery for vector space expansion and information retrieval

In this paper, we propose a text mining method called LRD (latent relation discovery), which extends the traditional vector space model of document representation in order to improve information retrieval (IR) on documents and document clustering. Our LRD method extracts terms and entities, such as person, organization, or project names, and discovers relationships between them by taking into account their co-occurrence in textual corpora. Given a target entity, LRD discovers other entities closely related to the target effectively and efficiently. With respect to such relatedness, a measure of relation strength between entities is defined. LRD uses relation strength to enhance the vector space model, and uses the enhanced vector space model for query based IR on documents and clustering documents in order to discover complex relationships among terms and entities. Our experiments on a standard dataset for query based IR shows that our LRD method performed significantly better than traditional vector space model and other five standard statistical methods for vector expansion.

Development And Characterization Of A Cationic Lipid Nanocarrier As Non-viral Vector For Gene Therapy.

The aim of the present work was to produce a cationic solid lipid nanoparticle (SLN) as non-viral vector for protein delivery. Cationic SLN were produced by double emulsion method, composed of softisan(®) 100, cetyltrimethylammonium bromide (CTAB), Tween(®) 80, Span(®) 80, glycerol and lipoid(®) S75 loading insulin as model protein. The formulation was characterized in terms of mean hydrodynamic diameter (z-ave), polydispersity index (PI), zeta potential (ZP), stability during storage time, stability after lyophilization, effect of toxicity and transfection ability in HeLa cells, in vitro release profile and morphology. SLN were stable for 30days and showed minimal changes in their physicochemical properties after lyophilization. The particles exhibited a relatively slow release, spherical morphology and were able to transfect HeLa cells, but toxicity remained an obstacle. Results suggest that SLN are nevertheless promising for delivery of proteins or nucleic acids for gene therapy.

Reference Values For High-density Lipoprotein Particle Size And Volume By Dynamic Light Scattering In A Brazilian Population Sample And Their Relationships With Metabolic Parameters.

Current data indicate that the size of high-density lipoprotein (HDL) may be considered an important marker for cardiovascular disease risk. We established reference values of mean HDL size and volume in an asymptomatic representative Brazilian population sample (n=590) and their associations with metabolic parameters by gender. Size and volume were determined in HDL isolated from plasma by polyethyleneglycol precipitation of apoB-containing lipoproteins and measured using the dynamic light scattering (DLS) technique. Although the gender and age distributions agreed with other studies, the mean HDL size reference value was slightly lower than in some other populations. Both HDL size and volume were influenced by gender and varied according to age. HDL size was associated with age and HDL-C (total population); non- white ethnicity and CETP inversely (females); HDL-C and PLTP mass (males). On the other hand, HDL volume was determined only by HDL-C (total population and in both genders) and by PLTP mass (males). The reference values for mean HDL size and volume using the DLS technique were established in an asymptomatic and representative Brazilian population sample, as well as their related metabolic factors. HDL-C was a major determinant of HDL size and volume, which were differently modulated in females and in males.