ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Probability density function estimation using orthogonal forward regression

Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression technique is adopted to construct sparse kernel density estimates. The proposed algorithm incrementally minimises a leave-one-out test error score to select a sparse kernel model, and a local regularisation method is incorporated into the density construction process to further enforce sparsity. The kernel weights are finally updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size further. Except for the kernel width, the proposed algorithm has no other parameters that need tuning, and the user is not required to specify any additional criterion to terminate the density construction procedure. Two examples are used to demonstrate the ability of this regression-based approach to effectively construct a sparse kernel density estimate with comparable accuracy to that of the full-sample optimised Parzen window density estimate.

Using zero-norm constraint for sparse probability density function estimation

A new sparse kernel probability density function (pdf) estimator based on zero-norm constraint is constructed using the classical Parzen window (PW) estimate as the target function. The so-called zero-norm of the parameters is used in order to achieve enhanced model sparsity, and it is suggested to minimize an approximate function of the zero-norm. It is shown that under certain condition, the kernel weights of the proposed pdf estimator based on the zero-norm approximation can be updated using the multiplicative nonnegative quadratic programming algorithm. Numerical examples are employed to demonstrate the efficacy of the proposed approach.

Sparse probability density function estimation using the minimum integrated square error

We develop a new sparse kernel density estimator using a forward constrained regression framework, within which the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Our main contribution is to derive a recursive algorithm to select significant kernels one at time based on the minimum integrated square error (MISE) criterion for both the selection of kernels and the estimation of mixing weights. The proposed approach is simple to implement and the associated computational cost is very low. Specifically, the complexity of our algorithm is in the order of the number of training data N, which is much lower than the order of N2 offered by the best existing sparse kernel density estimators. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to those of the classical Parzen window estimate and other existing sparse kernel density estimators.

A fast algorithm for sparse probability density function construction

A new sparse kernel density estimator is introduced. Our main contribution is to develop a recursive algorithm for the selection of significant kernels one at time using the minimum integrated square error (MISE) criterion for both kernel selection. The proposed approach is simple to implement and the associated computational cost is very low. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

Binding of antioxidant flavone isovitexin to human serum albumin investigated by experimental and computational assays

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analytical form of the Probability Density Function of travel times in rectangular zone with Tchebyshev’s metric

Geometrical dependencies are being researched for analytical representation of the probability density function (pdf) for the travel time between a random, and a known or another random point in Tchebyshev’s metric. In the most popular case - a rectangular area of service - the pdf of this random variable depends directly on the position of the server. Two approaches have been introduced for the exact analytical calculation of the pdf: Ad-hoc approach – useful for a ‘manual’ solving of a specific case; by superposition – an algorithmic approach for the general case. The main concept of each approach is explained, and a short comparison is done to prove the faithfulness.

THE EFFECT OF GABAMIMETICS ON NEUROTRANSMITTER RECEPTOR BINDING AND FUNCTION IN RAT BRAIN

Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter in the central nervous system and alterations in central GABAergic transmission may contribute to the symptoms of a number of neurological and psychiatric disorders. Because of this relationship, numerous laboratories are attempting to develop agents which will selectively enhance GABA neurotransmission in brain. Due to these efforts, several promising compounds have recently been discovered. Should these drugs prove to be clinically effective, they will be used to treat chronic neuropsychiatric disabilities and, therefore, will be administered for long periods of time. Accordingly, the present investigation was undertaken to determine the neurochemical consequences of chronic activation of brain GABA systems in order to better define the therapeutic potential and possible side-effect liability of GABAmimetic compounds.^ Chronic (15 day) administration to rats of low doses of amino-oxyacetic acid (AOAA, 10 mg/kg, once daily), isonicotinic acid hydrazide (20 mg/kg, b.i.d.), two non-specific inhibitors of GABA-T, the enzyme which catabolizes GABA in brain, or (gamma)-acetylenic GABA (10 mg/kg, b.i.d.) a catalytic inhibitor of this enzyme, resulted in a significant elevation of brain and CSF GABA content throughout the course of treatment. In addition, chronic administration of these drugs, as well as the direct acting GABA receptor agonists THIP (8 mg/kg, b.i.d.) or kojic amine (18 mg/kg, b.i.d.) resulted in a significant increase in dopamine receptor number and a significant decrease in GABA receptor number in the corpus striatum of treated animals as determined by standard in vitro receptor binding techniques. Changes in the GABA receptor were limited to the corpus striatum and occurred more rapidly than did alterations in the dopamine receptor. The finding that dopamine-mediated stereotypic behavior was enhanced in animals treated chronically with AOAA suggested that the receptor binding changes noted in vitro have some functional consequence in vitro.^ Coadministration of atropine (a muscarinic cholinergic receptor antagonist) blocked the GABA-T inhibitor-induced increase in striatal dopamine receptors but was without effect on receptor alterations seen following chronic administration of direct acting GABA receptor agonists. Atropine administration failed to influence the drug-induced decreases in striatal GABA receptors.^ Other findings included the discovery that synaptosomal high affinity ('3)H-choline uptake, an index of cholinergic neuronal activity, was significantly increased in the corpus striatum of animals treated acutely, but not chronically, with GABAmimetics.^ It is suggested that the dopamine receptor supersensitivity observed in the corpus striatum of animals following long-term treatment with GABAmimetics is a result of the chronic inhibition of the nigrostriatal dopamine system by these drugs. Changes in the GABA receptor, on the other hand, are more likely due to a homospecific regulation of these receptors. An hypothesis based on the different sites of action of GABA-T inhibitors vis-a-vis the direct acting GABA receptor agonists is proposed to account for the differential effect of atropine on the response to these drugs.^ The results of this investigation provide new insights into the functional interrelationships that exist in the basal ganglia and suggest that chronic treatment with GABAmimetics may produce extrapyramidal side-effects in man. In addition, the constellation of neurochemical changes observed following administration of these drugs may be a useful guide for determining the GABAmimetic properties of neuropharmacological agents. ^

Intermittency reinjection probability density function with and without noise effects.

Intermittency phenomenon is a continuous route from regular to chaotic behaviour. Intermittency is an occurrence of a signal that alternates chaotic bursts between quasi-regular periods called laminar phases, driven by the so called reinjection probability density function (RPD). In this paper is introduced a new technique to obtain the RPD for type-II and III intermittency. The new RPD is more general than the classical one and includes the classical RPD as a particular case. The probabilities of the laminar length, the average laminar lengths and the characteristic relations are determined with and without lower bound of the reinjection in agreement with numerical simulations. Finally, it is analyzed the noise effect in intermittency. A method to obtain the noisy RPD is developed extending the procedure used in the noiseless case. The analytical results show a good agreement with numerical simulations.

Testing multiple mapping conditioning mixing for Monte Carlo probability density function simulations

Mitarai [Phys. Fluids 17, 047101 (2005)] compared turbulent combustion models against homogeneous direct numerical simulations with extinction/recognition phenomena. The recently suggested multiple mapping conditioning (MMC) was not considered and is simulated here for the same case with favorable results. Implementation issues crucial for successful MMC simulations are also discussed.

Low mannose-binding lectin function is associated with sepsis in adult patients

Mannose-binding lectin (MBL) is an innate immune system pattern recognition molecule that kills a wide range of pathogens via the lectin complement pathway. MBL deficiency is associated with severe infection but the best measure of this deficiency is undecided. We investigated the influence of MBL functional deficiency on the development of sepsis in 195 adult patients, 166 of whom had bloodstream infection and 35 had pneumonia. Results were compared with 236 blood donor controls. MBL function (C4b deposition) and levels were measured by enzyme-linked immunosorbent assay. Using receiver-operator characteristics of MBL function in healthy controls, we identified a level of < 0.2 U mu L-1 as a highly discriminative marker of low MBL2 genotypes. Median MBL function was lower in sepsis patients (0.18 U mu L-1) than in controls (0.48 U mu L-1, P < 0.001). MBL functional deficiency was more common in sepsis patients than controls (P < 0.001). MBL functional deficient patients had significantly higher sequential organ failure assessment (SOFA) scores and higher MBL function and levels were found in patients with SOFA scores predictive of good outcome. Deficiency of MBL function appears to be associated with bloodstream infection and the development of septic shock. High MBL levels may be protective against severe sepsis. © 2006 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved.