Richards growth model and viability indicators for populations subject to interventions

In this work we study the problem of modeling identification of a population employing a discrete dynamic model based on the Richards growth model. The population is subjected to interventions due to consumption, such as hunting or farming animals. The model identification allows us to estimate the probability or the average time for a population number to reach a certain level. The parameter inference for these models are obtained with the use of the likelihood profile technique as developed in this paper. The identification method here developed can be applied to evaluate the productivity of animal husbandry or to evaluate the risk of extinction of autochthon populations. It is applied to data of the Brazilian beef cattle herd population, and the the population number to reach a certain goal level is investigated.

Enzyme kinetics, structural analysis and molecular modeling studies on a series of Schistosoma mansoni PNP inhibitors

The enzyme purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive molecular target for the development of novel drugs against schistosomiasis, a neglected tropical disease that affects about 200 million people worldwide. In the present work, enzyme kinetic studies were carried out in order to determine the potency and mechanism of inhibition of a series of SmPNP inhibitors. In addition to the biochemical investigations, crystallographic and molecular modeling studies revealed important molecular features for binding affinity towards the target enzyme, leading to the development of structure-activity relationships (SAR).

Structural and chemical basis for anticancer activity of a series of 'beta'-tubulin ligands: molecular modeling and 3D QSAR studies

An important approach to cancer therapy is the design of small molecule modulators that interfere with microtubule dynamics through their specific binding to the ²-subunit of tubulin. In the present work, comparative molecular field analysis (CoMFA) studies were conducted on a series of discodermolide analogs with antimitotic properties. Significant correlation coefficients were obtained (CoMFA(i), q² =0.68, r²=0.94; CoMFA(ii), q² = 0.63, r²= 0.91), indicating the good internal and external consistency of the models generated using two independent structural alignment strategies. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the 3D contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of discodermolide analogs, and should be useful for the design of new specific ²-tubulin modulators with potent anticancer activity.

Spectroscopic characterization and investigation of the dynamic of charge compensation process of supramolecular films derived from tetra-2-pyridyl-1,4-pyrazine ligand

This work describes the infrared spectroscopy characterization and the charge compensation dynamics in supramolecular film FeTPPZFeCN derived from tetra-2-pyridyl-1,4-pyrazine (TPPZ) with hexacyanoferrate, as well as the hybrid film formed by FeTPPZFeCN and polypyrrole (PPy). For supramolecular film, it was found that anion flux is greater in a K+ containing solution than in Li+ solution, which seems to be due to the larger crystalline ionic radius of K+. The electroneutralization process is discussed in terms of electrostatic interactions between cations and metallic centers in the hosting matrix. The nature of the charge compensation process differs from others modified electrodes based on Prussian blue films, where only cations such as K+ participate in the electroneutralization process. In the case of FeTPPZFeCN/PPy hybrid film, the magnitude of the anions’s flux is also dependent on the identity of the anion of the supporting electrolyte.

Body Mass Index, Cigarette Smoking, and Alcohol Consumption and Cancers of the Oral Cavity, Pharynx, and Larynx: Modeling Odds Ratios in Pooled Case-Control Data

study-specific results, their findings should be interpreted with caution

Modeling of the Barkhausen jump in low carbon steel

This work presents a model for the magnetic Barkhausen jump in low carbon content steels. The outcomes of the model evidence that the Barkhausen jump height depends on the coercive field of the pinning site and on the mean free path of the domain wall between pinning sites. These results are used to deduce the influence of the microstructural features and of the magnetizing parameters on the amplitude and duration of the Barkhausen jumps. In particular, a theoretical expression, establishing the dependence of the Barkbausen jump height on the carbon content and grain size, is obtained. The model also reveals the dependence of the Barkhausen jump on the applied frequency and amplitude. Theoretical and experimental results are presented and compared, being in good agreement. (C) 2008 American Institute of Physics.

Multidisciplinary optimization of a catamaran's hydrofoil design with dynamic response surface and distributive processing

This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.

FILTERING TECHNIQUES APPLIED ON RAW CARRIER PHASE FOR GPS DETECTING SMALL DYNAMIC DISPLACEMENTS

This work is part of a research under construction since 2000, in which the main objective is to measure small dynamic displacements by using L1 GPS receivers. A very sensible way to detect millimetric periodic displacements is based on the Phase Residual Method (PRM). This method is based on the frequency domain analysis of the phase residuals resulted from the L1 double difference static data processing of two satellites in almost orthogonal elevation angle. In this article, it is proposed to obtain the phase residuals directly from the raw phase observable collected in a short baseline during a limited time span, in lieu of obtaining the residual data file from regular GPS processing programs which not always allow the choice of the aimed satellites. In order to improve the ability to detect millimetric oscillations, two filtering techniques are introduced. One is auto-correlation which reduces the phase noise with random time behavior. The other is the running mean to separate low frequency from the high frequency phase sources. Two trials have been carried out to verify the proposed method and filtering techniques. One simulates a 2.5 millimeter vertical antenna displacement and the second uses the GPS data collected during a bridge load test. The results have shown a good consistency to detect millimetric oscillations.

Active Dendrites Enhance Neuronal Dynamic Range

Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the past decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of an active dendritic tree is a highly non-linear function of its afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease in dynamic range.

Modeling the risk of malaria for travelers to areas with stable malaria transmission

Background: Malaria is an important threat to travelers visiting endemic regions. The risk of acquiring malaria is complex and a number of factors including transmission intensity, duration of exposure, season of the year and use of chemoprophylaxis have to be taken into account estimating risk. Materials and methods: A mathematical model was developed to estimate the risk of non-immune individual acquiring falciparum malaria when traveling to the Amazon region of Brazil. The risk of malaria infection to travelers was calculated as a function of duration of exposure and season of arrival. Results: The results suggest significant variation of risk for non-immune travelers depending on arrival season, duration of the visit and transmission intensity. The calculated risk for visitors staying longer than 4 months during peak transmission was 0.5% per visit. Conclusions: Risk estimates based on mathematical modeling based on accurate data can be a valuable tool in assessing risk/benefits and cost/benefits when deciding on the value of interventions for travelers to malaria endemic regions.

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 1: Model description and evaluation

We introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and from biomass burning aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostics include the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between the simulated biomass burning aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM(2.5)) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosondes and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained.

Modeling Two-Oscillator Circadian Systems Entrained by Two Environmental Cycles

Several experimental studies have altered the phase relationship between photic and non-photic environmental, 24 h cycles (zeitgebers) in order to assess their role in the synchronization of circadian rhythms. To assist in the interpretation of the complex activity patterns that emerge from these ""conflicting zeitgeber'' protocols, we present computer simulations of coupled circadian oscillators forced by two independent zeitgebers. This circadian system configuration was first employed by Pittendrigh and Bruce (1959), to model their studies of the light and temperature entrainment of the eclosion oscillator in Drosophila. Whereas most of the recent experiments have restricted conflicting zeitgeber experiments to two experimental conditions, by comparing circadian oscillator phases under two distinct phase relationships between zeitgebers (usually 0 and 12 h), Pittendrigh and Bruce compared eclosion phase under 12 distinct phase relationships, spanning the 24 h interval. Our simulations using non-linear differential equations replicated complex non-linear phenomena, such as ""phase jumps'' and sudden switches in zeitgeber preferences, which had previously been difficult to interpret. Our simulations reveal that these phenomena generally arise when inter-oscillator coupling is high in relation to the zeitgeber strength. Manipulations in the structural symmetry of the model indicated that these results can be expected to apply to a wide range of system configurations. Finally, our studies recommend the use of the complete protocol employed by Pittendrigh and Bruce, because different system configurations can generate similar results when a ""conflicting zeitgeber experiment'' incorporates only two phase relationships between zeitgebers.

Modeling the skin pattern of fishes

Complicated patterns showing various spatial scales have been obtained in the past by coupling Turing systems in such a way that the scales of the independent systems resonate. This produces superimposed patterns with different length scales. Here we propose a model consisting of two identical reaction-diffusion systems coupled together in such a way that one of them produces a simple Turing pattern of spots or stripes, and the other traveling wave fronts that eventually become stationary. The basic idea is to assume that one of the systems becomes fixed after some time and serves as a source of morphogens for the other system. This mechanism produces patterns very similar to the pigmentation patterns observed in different species of stingrays and other fishes. The biological mechanisms that support the realization of this model are discussed.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 2: Model sensitivity to the biomass burning

We describe an estimation technique for biomass burning emissions in South America based on a combination of remote-sensing fire products and field observations, the Brazilian Biomass Burning Emission Model (3BEM). For each fire pixel detected by remote sensing, the mass of the emitted tracer is calculated based on field observations of fire properties related to the type of vegetation burning. The burnt area is estimated from the instantaneous fire size retrieved by remote sensing, when available, or from statistical properties of the burn scars. The sources are then spatially and temporally distributed and assimilated daily by the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) in order to perform the prognosis of related tracer concentrations. Three other biomass burning inventories, including GFEDv2 and EDGAR, are simultaneously used to compare the emission strength in terms of the resultant tracer distribution. We also assess the effect of using the daily time resolution of fire emissions by including runs with monthly-averaged emissions. We evaluate the performance of the model using the different emission estimation techniques by comparing the model results with direct measurements of carbon monoxide both near-surface and airborne, as well as remote sensing derived products. The model results obtained using the 3BEM methodology of estimation introduced in this paper show relatively good agreement with the direct measurements and MOPITT data product, suggesting the reliability of the model at local to regional scales.