Modeling the age-specific per capita growth and reproduction of Rhizobius lophanthae (Col: Coccinellidae)

A per capita model for the growth, development and reproduction of the coccinellid predator Rhizobius lophanthae (Blaisd) feeding on the oleander scale (Aspidiotus nerii Bouche (Homoptera: Diaspididae)) was developed. A thermal threshold for development of 9.4 degrees C was found. Under conditions of unlimited food, the relationship of mass at time t+1 to that at t (in days at 25 degrees C) suggests an 8.7 percent growth rate per mg larvae per day at 25 degrees C. An adult female beetle produces approximately 20 eggs per day while consuming an average of 8.5 scales/day. This is approximately 2.16 eggs per scale consumed above the maintenance level of 1.88 scales per day. More precisely, this compensation point is 0.12 mg of prey/mg of predator/day at 25 degrees C and the egestion rate is 1 - beta = 0.63.

Photoluminescence of crystalline and disordered BTO : Mn powder: Experimental and theoretical modeling

Disordered and crystalline Mn-doped BaTiO3 (BTO:Mn) powders were synthesized by the polymeric precursor method. After heat treatment, the nature of visible photoluminescence (PL) at room temperature in amorphous BTO:Mn was discussed, considering results of experimental and theoretical studies. X-ray diffraction (XRD), PL, and UV-vis were used to characterize this material. Rietveld refinement of the BTO:Mn from XRD data was used to built two models, which represent the crystalline BTO:Mn (BTO:Mn,) and disordered BTO:Mn (BTO:Mn-d) structures. Theses models were analyzed by the periodic ab initio quantum mechanical calculations using the CRYSTAL98 package within the framework of density functional theory at the B3LYP level. The experimental and theoretical results indicated that PL is related with the degree of disorder in the BTO:Mn powders and also suggests the presence of localized states in the disordered structure. (c) 2006 Elsevier B.V. All rights reserved.

Voltage regulator modeling for the three-phase power flow in distribution networks

In this paper a three-phase power flow for electrical distribution systems considering different models of voltage regulators is presented. A voltage regulator (VR) is an equipment that maintains the voltage level in a predefined value in a distribution line in spite of the load variations within its nominal power. Three different types of connections are analyzed: 1) wye-connected regulators, 2) open delta-connected regulators and 3) closed delta-connected regulators. To calculate the power flow, the three-phase backward/forward sweep algorithm is used. The methodology is tested on the IEEE 34 bus distribution system. ©2008 IEEE.

Enterprise systems modeling: The ERP5 development process

The design and implementation of an ERP system involves capturing the information necessary for implementing the system's structure and behavior that support enterprise management. This process should start on the enterprise modeling level and finish at the coding level, going down through different abstraction layers. For the case of Free/Open Source ERP, the lack of proper modeling methods and tools jeopardizes the advantages of source code availability. Moreover, the distributed, decentralized decision-making, and source-code driven development culture of open source communities, generally doesn't rely on methods for modeling the higher abstraction levels necessary for an ERP solution. The aim of this paper is to present a model driven development process for the open source ERP ERP5. The proposed process covers the different abstraction levels involved, taking into account well established standards and common practices, as well as new approaches, by supplying Enterprise, Requirements, Analysis, Design, and Implementation workflows. Copyright 2008 ACM.

Transaction scheduling using dynamic conflict avoidance

Software transaction memory (STM) systems have been used as an approach to improve performance, by allowing the concurrent execution of atomic blocks. However, under high-contention workloads, STM-based systems can considerably degrade performance, as transaction conflict rate increases. Contention management policies have been used as a way to select which transaction to abort when a conflict occurs. In general, contention managers are not capable of avoiding conflicts, as they can only select which transaction to abort and the moment it should restart. Since contention managers act only after a conflict is detected, it becomes harder to effectively increase transaction throughput. More proactive approaches have emerged, aiming at predicting when a transaction is likely to abort, postponing its execution. Nevertheless, most of the proposed proactive techniques are limited, as they do not replace the doomed transaction by another or, when they do, they rely on the operating system for that, having little or no control on which transaction to run. This article proposes LUTS, a lightweight user-level transaction scheduler. Unlike other techniques, LUTS provides the means for selecting another transaction to run in parallel, thus improving system throughput. We discuss LUTS design and propose a dynamic conflict-avoidance heuristic built around its scheduling capabilities. Experimental results, conducted with the STAMP and STMBench7 benchmark suites, running on TinySTM and SwissTM, show how our conflict-avoidance heuristic can effectively improve STM performance on high contention applications. © 2012 Springer Science+Business Media, LLC.

Basic ingredients for mathematical modeling of tumor growth in vitro: Cooperative effects and search for space

Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.

Estimating the concentration of gold nanoparticles incorporated on natural rubber membranes using multi-level starlet optimal segmentation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fuzzy rule-based system for evaluation of uncertainty transaction in cassava chain

A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

Modeling amino acid requirements of poultry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling spatial distribution of cancer incidence in Cordoba, Argentina

Background: Cancer is the second leading cause of death in Argentina, and there is little knowledge about its incidence. The first study based on population-based cancer registry described spatial incidence and indicated that there existed at least county-level aggregation. The aim of the present work is to model the incidence patterns for the most incidence cancer in Córdoba Province, Argentina, using information from the Córdoba Cancer Registry by performing multilevel mixed model approach to deal with dependence and unobserved heterogeneity coming from the geo-reference cancer occurrence. Methods: Standardized incidence rates (world standard population) (SIR) by sex based on 5-year age groups were calculated for 109 districts nested on 26 counties for the most incidence cancers in Cordoba using 2004 database. A Poisson twolevel random effect model representing unobserved heterogeneity between first level-districts and second level-counties was fitted to assess the spatial distribution of the overall and site specific cancer incidence rates. Results: SIR cancer at Córdoba province shown an average of 263.53±138.34 and 200.45±98.30 for men and women, respectively. Considering the ratio site specific mean SIR to the total mean, breast cancer ratio was 0.25±0.19, prostate cancer ratio was 0.12±0.10 and lower values for lung and colon cancer for both sexes. The Poisson two-level random intercepts model fitted for SIR data distributed with overdispersion shown significant hierarchical structure for the cancer incidence distribution. Conclusions: a strong spatial-nested effect for the cancer incidence in Córdoba was observed and will help to begin the study of the factors associated with it.

Development and evolution of caste dimorphism in honeybees - a modeling approach

The difference in phenotypes of queens and workers is a hallmark of the highly eusocial insects. The caste dimorphism is often described as a switch-controlled polyphenism, in which environmental conditions decide an individual's caste. Using theoretical modeling and empirical data from honeybees, we show that there is no discrete larval developmental switch. Instead, a combination of larval developmental plasticity and nurse worker feeding behavior make up a colony-level social and physiological system that regulates development and produces the caste dimorphism. Discrete queen and worker phenotypes are the result of discrete feeding regimes imposed by nurses, whereas a range of experimental feeding regimes produces a continuous range of phenotypes. Worker ovariole numbers are reduced through feeding-regime-mediated reduction in juvenile hormone titers, involving reduced sugar in the larval food. Based on the mechanisms identified in our analysis, we propose a scenario of the evolutionary history of honeybee development and feeding regimes.

ESTIMATING REACTION CONSTANTS BY AB INITIO MOLECULAR MODELING: A STUDY ON THE OXIDATION OF PHENOL TO CATECHOL AND HYDROQUINONE IN ADVANCED OXIDATION PROCESSES

Molecular modeling is growing as a research tool in Chemical Engineering studies, as can be seen by a simple research on the latest publications in the field. Molecular investigations retrieve information on properties often accessible only by expensive and time-consuming experimental techniques, such as those involved in the study of radical-based chain reactions. In this work, different quantum chemical techniques were used to study phenol oxidation by hydroxyl radicals in Advanced Oxidation Processes used for wastewater treatment. The results obtained by applying a DFT-based model showed good agreement with experimental values available, as well as qualitative insights into the mechanism of the overall reaction chain. Solvation models were also tried, but were found to be limited for this reaction system within the considered theoretical level without further parameterization.

Modeling the Emergence of Circadian Rhythms in a Clock Neuron Network

Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.

Modeling the gluon propagator in Landau gauge: Lattice estimates of pole masses and dimension-two condensates

We present an analytic description of numerical results for the Landau-gauge SU(2) gluon propagator D(p(2)), obtained from lattice simulations (in the scaling region) for the largest lattice sizes to date, in d = 2, 3 and 4 space-time dimensions. Fits to the gluon data in 3d and in 4d show very good agreement with the tree-level prediction of the refined Gribov-Zwanziger (RGZ) framework, supporting a massive behavior for D(p(2)) in the infrared limit. In particular, we investigate the propagator's pole structure and provide estimates of the dynamical mass scales that can be associated with dimension-two condensates in the theory. In the 2d case, fitting the data requires a noninteger power of the momentum p in the numerator of the expression for D(p(2)). In this case, an infinite-volume-limit extrapolation gives D(0) = 0. Our analysis suggests that this result is related to a particular symmetry in the complex-pole structure of the propagator and not to purely imaginary poles, as would be expected in the original Gribov-Zwanziger scenario.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.