Age and metallicity of star clusters in the Small Magellanic Cloud from integrated spectroscopy

Context. Analysis of ages and metallicities of star clusters in the Magellanic Clouds provide information for studies on the chemical evolution of the Clouds and other dwarf irregular galaxies. Aims. The aim is to derive ages and metallicities from integrated spectra of 14 star clusters in the Small Magellanic Cloud, including a few intermediate/old age star clusters. Methods. Making use of a full-spectrum fitting technique, we compared the integrated spectra of the sample clusters to three different sets of single stellar population models, using two fitting codes available in the literature. Results. We derive the ages and metallicities of 9 intermediate/old age clusters, some of them previously unstudied, and 5 young clusters. Conclusions. We point out the interest of the newly identified as intermediate/old age clusters HW1, NGC 152, Lindsay 3, Lindsay 11, and Lindsay 113. We also confirm the old ages of NGC 361, NGC 419, Kron 3, and of the very well-known oldest SMC cluster, NGC 121.

Optimization and validation of a LIBS method for the determination of macro and micronutrients in sugar cane leaves

Laser induced breakdown spectrometry (LIBS) was applied for the determination of macro (P, K, Ca, Mg) and micronutrients (B, Cu, Fe, Mn and Zn) in sugar cane leaves, which is one of the most economically important crops in Brazil. Operational conditions were previously optimized by a neuro-genetic approach, by using a laser Nd:YAG at 1064 nm with 110 mJ per pulse focused on a pellet surface prepared with ground plant samples. Emission intensities were measured after 2.0 mu s delay time, with 4.5 mu s integration time gate and 25 accumulated laser pulses. Measurements of LIBS spectra were based on triplicate and each replicate consisted of an average of ten spectra collected in different sites (craters) of the pellet. Quantitative determinations were carried out by using univariate calibration and chemometric methods, such as PLSR and iPLS. The calibration models were obtained by using 26 laboratory samples and the validation was carried out by using 15 test samples. For comparative purpose, these samples were also microwave-assisted digested and further analyzed by ICP OES. In general, most results obtained by LIBS did not differ significantly from ICP OES data by applying a t-test at 95% confidence level. Both LIBS multivariate and univariate calibration methods produced similar results, except for Fe where better results were achieved by the multivariate approach. Repeatability precision varied from 0.7 to 15% and 1.3 to 20% from measurements obtained by multivariate and univariate calibration, respectively. It is demonstrated that LIBS is a powerful tool for analysis of pellets of plant materials for determination of macro and micronutrients by choosing calibration and validation samples with similar matrix composition.

Incidence of dementia and cause of death in elderly Japanese emigrants to Brazil before World War II

In 1997 we examined the prevalence of dementia among the Japanese elderly immigrants living in the Sao Paulo metropolitan area (n = 166). Herein, we followed up on these subjects for causes of death and dementia incidence. We were able to contact 108 subjects: 54 were already dead. The most common cause of death was cardiac disease. For dementia, 31.6% of the dead subjects were found to have developed dementia before they died, and 20.8% of the living subjects were demented. As for the baseline the clinical dementia rating (CDR), 20.8% of CDR 0 and 50.0% of CDR 0.5 subjects developed dementia in the dead group; whereas in the living group, 23.9% of CDR 0 and 52.6% of CDR 0.5 developed dementia. As a whole, the incidence was 34.2% per 1000 person-years. Cardiac disease as the most common cause of death was probably due to the higher prevalence of diabetes mellitus. Compared with the previous study, the lower incidence of dementia from the CDR 0.5 group may have been due to a higher mortality rate. This is the first study on the incidence of dementia in elderly Japanese immigrants in Brazil. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Treatment of Obese Adolescents: The Influence of Periodization Models and ACE Genotype

The aims of the present study were to compare the effects of two periodization models on metabolic syndrome risk factors in obese adolescents and verify whether the angiotensin-converting enzyme (ACE) genotype is important in establishing these effects. A total of 32 postpuberty obese adolescents were submitted to aerobic training (AT) and resistance training (RT) for 14 weeks. The subjects were divided into linear periodization (LP, n = 16) or daily undulating periodization (DUP, n = 16). Body composition, visceral and subcutaneous fat, glycemia, insulinemia, homeostasis model assessment of insulin resistance (HOMA-IR), lipid profiles, blood pressure, maximal oxygen consumption (VO(2max)), resting metabolic rate (RMR), muscular endurance were analyzed at baseline and after intervention. Both groups demonstrated a significant reduction in body mass, BMI, body fat, visceral and subcutaneous fat, total and low-density lipoprotein cholesterol, blood pressure and an increase in fat-free mass, VO(2max), and muscular endurance. However, only DUP promoted a reduction in insulin concentrations and HOMA-IR. It is important to emphasize that there was no statics difference between LP and DUP groups; however, it appears that there may be bigger changes in the DUP than LP group in some of the metabolic syndrome risk factors in obese adolescents with regard to the effect size (ES). Both periodization models presented a large effect on muscular endurance. Despite the limitation of sample size, our results suggested that the ACE genotype may influence the functional and metabolic characteristics of obese adolescents and may be considered in the future strategies for massive obesity control.

Modeling and Analysis of Piezoelectric Energy Harvesting From Aeroelastic Vibrations Using the Doublet-Lattice Method

Multifunctional structures are pointed out as an important technology for the design of aircraft with volume, mass, and energy source limitations such as unmanned air vehicles (UAVs) and micro air vehicles (MAVs). In addition to its primary function of bearing aerodynamic loads, the wing/spar structure of an UAV or a MAV with embedded piezoceramics can provide an extra electrical energy source based on the concept of vibration energy harvesting to power small and wireless electronic components. Aeroelastic vibrations of a lifting surface can be converted into electricity using piezoelectric transduction. In this paper, frequency-domain piezoaeroelastic modeling and analysis of a canti-levered platelike wing with embedded piezoceramics is presented for energy harvesting. The electromechanical finite-element plate model is based on the thin-plate (Kirchhoff) assumptions while the unsteady aerodynamic model uses the doublet-lattice method. The electromechanical and aerodynamic models are combined to obtain the piezoaeroelastic equations, which are solved using a p-k scheme that accounts for the electromechanical coupling. The evolution of the aerodynamic damping and the frequency of each mode are obtained with changing airflow speed for a given electrical circuit. Expressions for piezoaeroelastically coupled frequency response functions (voltage, current, and electrical power as well the vibratory motion) are also defined by combining flow excitation with harmonic base excitation. Hence, piezoaeroelastic evolution can be investigated in frequency domain for different airflow speeds and electrical boundary conditions. [DOI:10.1115/1.4002785]

Rotifer abundance, biomass, and secondary production after the recovery of hydrologic connectivity between a river and two marginal lakes (Sao Paulo, Brazil)

Rotifera density, biomass, and secondary production on two marginal lakes of Paranapanema River were compared after the recovery of hydrologic connectivity with the river (Sao Paulo State, Brazil). Daily samplings were performed in limnetic zone of both lakes during the rainy season immediately after lateral inflow of water and, in the dry period, six months after hydrologic connectivity recovery. In order to identify the factors that affect rotifer population dynamics, lake water level, volume, depth, temperature, transparency, dissolved oxygen, pH, alkalinity, conductivity, suspended solids, nutrients, and chlorophyll-a were determined. Variations of water physical and chemical factors that affect rotifer population were related to the lake-river degree of connection and to water level rising after drought. The water lateral inflow from the river resulted in an increase in lake water volume, depth, and transparency and a decrease in water pH, alkalinity, and suspended solids. The lake with the wider river connection, more frequent biota exchange, and larger amount of particulate and dissolved materials was richer and more diverse, while rotifer density, biomass, and productivity were lower in both periods studied. Density, biomass, and secondary production were higher in the lake with the smaller river connection and the higher physical and chemical stability. Our results show that the connectivity affects the limnological stability, associated to seasonality. Stable conditions, caused by low connectivity in dry periods, were related with high density, biomass and secondary production. Conversely, instability conditions in rainy periods were associated to elevated richness and diversity values, caused by exchange biota due to higher connectivity. (C) 2008 Elsevier GmbH. All rights reserved.

Acoustic Simulation of a Special Switched Reluctance Drive by Means of Field-Circuit Coupling and Multiphysics Simulation

The approach presented in this paper consists of an energy-based field-circuit coupling in combination with multi-physics simulation of the acoustic radiation of electrical machines. The proposed method is applied to a special switched reluctance motor with asymmetric pole geometry to improve the start-up torque. The pole shape has been optimized, subject to low torque ripple, in a previous study. The proposed approach here is used to analyze the impact of the optimization on the overall acoustic behavior. The field-circuit coupling is based on a temporary lumped-parameter model of the magnetic part incorporated into a circuit simulation based on the modified nodal analysis. The harmonic force excitation is calculated by means of stress tensor computation, and it is transformed to a mechanical mesh by mapping techniques. The structural dynamic problem is solved in the frequency domain using a finite-element modal analysis and superposition. The radiation characteristic is obtained from boundary element acoustic simulation. Simulation results of both rotor types are compared, and measurements of the drive are presented.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

alpha-Arylation and Alkynylation of Cyclic alpha-Iodoenones Using Palladium-Catalyzed Cross-Coupling Reactions with Trifluoroborate Salts

An expeditious synthesis of alpha-aryl- and alpha-alkynylcyclo-hexenones is described and illustrated by palladium-catalyzed cross-coupling reaction of cyclic alpha-iodoenones with potassium aryltrifluoroborate salts. This procedure offers easy access to alpha-arylated and alkynylated cyclohexenones functionalized with electrondonor and -acceptor substituents in good yields.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Familial hyperaldosteronism type II: Description of a large kindred and exclusion of the aldosterone synthase (CYP11B2) gene

Familial hyperaldosteronism type II (FH-II) is characterized by autosomal dominant inheritance and hypersecretion of aldosterone due to adrenocortical hyperplasia or an aldosterone-producing adenoma; unlike FH type I (FH-I), hyperaldosteronism in FH-II is not suppressible by dexamethasone. Of a total of 17 FH-II families with 44 affected members, we studied a large kindred with 7 affected members that was informative for linkage analysis. Family members were screened with the aldosterone/PRA ratio test; patients with aldosterone/PRA ratio greater than 25 underwent fludrocortisone/salt suppression testing for confirmation of autonomous aldosterone secretion. Postural testing, adrenal gland imaging, and adrenal venous sampling were also performed. Individuals affected by FH-II demonstrated lack of suppression of plasma A levels after 4 days of dexamethasone treatment (0.5 mg every 6 h). All patients had neg ative genetic testing for the defect associated with FH-I, the CYP11B1/CYP11B2 hybrid gene. Genetic linkage was then examined between FH-II and aldosterone synthase (the CYP11B2 gene) on chromosome 8q. A polyadenylase repeat within the 5'-region of the CYP11B2 gene and 9 other markers covering an approximately 80-centimorgan area on chromosome 8q21-8qtel were genotyped and analyzed for linkage. Two-point logarithm of odds scores were negative and ranged from -12.6 for the CYP11B2 polymorphic marker to -0.98 for the D8S527 marker at a recombination distance (theta) of 0. Multipoint logarithm of odds score analysis confirmed the exclusion of the chromosome 8q21-8qtel area as a region harboring the candidate gene for FH-II in this family. We conclude that FH-II shares autosomal dominant inheritance and hyperaldosteronism with FH-I, but, as demonstrated by the large kindred investigated in this report, it is clinically and genetically distinct. Linkage analysis demonstrated that the CYP11B2 gene is not responsible for FH-II in this family; furthermore, chromosome 8q21-8qtel most likely does not harbor the genetic defect in this kindred.

Subgroup relations: A comparison of mutual intergroup differentiation and common ingroup identity models of prejudice reduction

Two studies examined relations between groups (humanities and math-science students) that implicitly or explicitly share a common superordinate category (university student). In Experiment 1, 178 participants performed a noninteractive decision-making task during which category salience was manipulated in a 2 (superordinate category salience) x 2 (subordinate category salience) between-groups design. Consistent with the mutual intergroup differentiation model, participants for whom both categories were salient exhibited the lowest levels of bias, whereas bias was strongest when the superordinate category alone was made salient. This pattern of results was replicated in Experiment 2 (N = 135). In addition, Experiment 2 demonstrated that members of subgroups that are nested within a superordinate category are more sensitive to how the superordinate category is represented than are members of subgroups that extend beyond the boundaries of the superordinate category.

Swapping space for time and unfair tests of ecological models

Testing ecological models for management is an increasingly important part of the maturation of ecology as an applied science. Consequently, we need to work at applying fair tests of models with adequate data. We demonstrate that a recent test of a discrete time, stochastic model was biased towards falsifying the predictions. If the model was a perfect description of reality, the test falsified the predictions 84% of the time. We introduce an alternative testing procedure for stochastic models, and show that it falsifies the predictions only 5% of the time when the model is a perfect description of reality. The example is used as a point of departure to discuss some of the philosophical aspects of model testing.