Ethical preferences for influencing superiors: A 41-society study

With a 41-society sample of 9990 managers and professionals, we used hierarchical linear modeling to investigate the impact of both macro-level and micro-level predictors on subordinate influence ethics. While we found that both macro-level and micro-level predictors contributed to the model definition, we also found global agreement for a subordinate influence ethics hierarchy. Thus our findings provide evidence that developing a global model of subordinate ethics is possible, and should be based upon multiple criteria and multilevel variables. Journal of International Business Studies (2009) 40, 1022-1045. doi:10.1057/jibs.2008.109

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

A Statistical Study of the Association of Seven Dental Anomalies in the Brazilian Population

The objective of this study was to show the association patterns among seven types of dental anomalies (second pre-molar agenesis, upper side incisive reduced in size, lower first molar infra-ochlesis, enamel hypoplasia, first molar ectopic eruption, supra numerous teeth and upper canine ectopic eruption) in a population sample without dental treatment ranging in age from 7 to 14. A total of 172 patients were attended and underwent the clinical examination at the Clinica Infantil da Fundacao Educacional de Barretos. Eleven patients from this total were selected according to a first dental anomaly diagnosis and submitted to panoramic radiography. A significant association (p < 0.05) was detected among six pairs of anomalies (second pre-molar agenesis x first pre-molar ectopic eruption; second pre-molar agenesis x lower first molar infra-ochlesis; second pre-molar agenesis x upper side incisive reduced in size; supra numerous teeth x reduced size upper side incisive; first pre-molar ectopic eruption x enamel hypoplasia; lower first molar infra-ochlesis x upper side incisive reduced in size) suggesting a common genetic origin for these conditions. The association was not significant in only one case where there was anomaly sharing by the patients. The existence of an anomaly is clinically relevant for early diagnosis of a possible association and an anomaly can indicate an increased risk of other anomalies.

Modeling volatile organic compounds (voc`s) adsorption onto cup-stacked carbon nanotubes (cscnt) using the linear driving force model

Modeling volatile organic compounds (voc`s) adsorption onto cup-stacked carbon nanotubes (cscnt) using the linear driving force model. Volatile organic compounds (VOC`s) are an important category of air pollutants and adsorption has been employed in the treatment (or simply concentration) of these compounds. The current study used an ordinary analytical methodology to evaluate the properties of a cup-stacked nanotube (CSCNT), a stacking morphology of truncated conical graphene, with large amounts of open edges on the outer surface and empty central channels. This work used a Carbotrap bearing a cup-stacked structure (composite); for comparison, Carbotrap was used as reference (without the nanotube). The retention and saturation capacities of both adsorbents to each concentration used (1, 5, 20 and 35 ppm of toluene and phenol) were evaluated. The composite performance was greater than Carbotrap; the saturation capacities for the composite was 67% higher than Carbotrap (average values). The Langmuir isotherm model was used to fit equilibrium data for both adsorbents, and a linear driving force model (LDF) was used to quantify intraparticle adsorption kinetics. LDF was suitable to describe the curves.

Local delivery of EGF-liposome mediated bone modeling in orthodontic tooth movement by increasing RANKL expression

Aims: It has long been demonstrated that epidermal growth factor (EGF) has catabolic effects oil bone. Thus. we examined the role of EGF in regulating mechanically induced bone modeling in a rat model of orthodontic tooth movement. Main methods: The maxillary first molars of rats were moved mesially using an orthodontic appliance attached to the maxillary incisor teeth. Rats were randomly divided into 4 groups: (G1) administration of PBS (Phosphate buffer saline Solution (n = 24); (G2) administration of empty liposomes (it = 24): (Q) administration 20 rig of EGF Solution (n = 24): and (G4) 20 ng of EGF-liposomes Solution (it = 24). Each Solution was injected in the mucosa of the left first molar adjacent to the appliance. At days 5, 10, 14 and 2 1 after drug administration. 6 animals of each group were sacrificed. Histomorphometric analysis was used to quantify osteoclasts (Tartrate-resistant acid phosphatase (TRAP) + cells) and tooth movement. Using immunohistochemistry assay we evaluated the RANKL (receptor activator of nuclear factor kappa B ligand) and epidermal growth factor receptor (EGFR) expression. Key findings: The EGF-liposome administration showed an increased tooth movement and osteoclast numbers compared to controls (p<0.05). This was correlated with intense RANKL expression. Both osteoblasts and osteoclasts expressed EGFR. Significance: Local delivery of EGF-liposome stimulates, osteoclastogenesis and tooth movement. (C) 2009 Elsevier Inc. All rights reserved.

Modeling of columnar-to-equiaxed transition in solidified Al-Si alloys

A Cellular-Automaton Finite-Volume-Method (CAFVM) algorithm has been developed, coupling with macroscopic model for heat transfer calculation and microscopic models for nucleation and growth. The solution equations have been solved to determine the time-dependent constitutional undercooling and interface retardation during solidification. The constitutional undercooling is then coupled into the CAFVM algorithm to investigate both the effects of thermal and constitutional undercooling on columnar growth and crystal selection in the columnar zone, and formation of equiaxed crystals in the bulk liquid. The model cannot only simulate microstructures of alloys but also investigates nucleation mechanisms and growth kinetics of alloys solidified with various solute concentrations and solidification morphologies.

Tooth loss in Brazilian middle-aged adults: multilevel effects

Objective. To examine the link between tooth loss and multilevel factors in a national sample of middle-aged adults in Brazil. Material and methods. Analyses were based on the 2003 cross-sectional national epidemiological survey of the oral health of the Brazilian population, which covered 13 431 individuals (age 35-44 years). Multistage cluster sampling was used. The dependent variable was tooth loss and the independent variables were classified according to the individual or contextual level. A multilevel negative binomial regression model was adopted. Results. The average tooth loss was 14 (standard deviation 9.5) teeth. Half of the individuals had lost 12 teeth. The contextual variables showed independent effects on tooth loss. It was found that having 9 years or more of schooling was associated with protection against tooth loss (means ratio range 0.68-0.76). Not having visited the dentist and not having visited in the last >= 3 years accounted for increases of 33.5% and 21.3%, respectively, in the risk of tooth loss (P < 0.05). The increase in tooth extraction ratio showed a strong contextual effect on increased risk of tooth loss, besides changing the effect of protective variables. Conclusions. Tooth loss in middle-aged adults has important associations with social determinants of health. This study points to the importance of the social context as the main cause of oral health injuries suffered by most middle-aged Brazilian adults.

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Race modeling: An effective cognitive strategy for the 100 m sprinter?

The purpose of this study was to investigate the effects of a specific cognitive race plan on 100 m sprint performance, Twelve elite sprinters (11 male and 1 female) performed 100 m time trials under normal (control) conditions and then under experimental conditions (use of race cues). In the experimental condition, participants were asked to think about specific thought content in each of three segments of the 100 m. A multiple baseline design was employed. A mean improvement of 0.26 s was found. Eleven of the 12 participants showed improvement using the specific cognitive race plan (p < .005). Participants also produced more consistent sprint performances when using the cues (p < .01). Subjective evaluations made by the participants unanimously supported the use of the race plan for optimizing sprint performance. Environmental conditions, effort, and practice effects were considered as possible influences on the results.

Modeling the optical constants of solids using acceptance-probability-controlled simulated annealing with an adaptive move generation procedure

The acceptance-probability-controlled simulated annealing with an adaptive move generation procedure, an optimization technique derived from the simulated annealing algorithm, is presented. The adaptive move generation procedure was compared against the random move generation procedure on seven multiminima test functions, as well as on the synthetic data, resembling the optical constants of a metal. In all cases the algorithm proved to have faster convergence and superior escaping from local minima. This algorithm was then applied to fit the model dielectric function to data for platinum and aluminum.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Simulated-annealing-based genetic algorithm for modeling the optical constants of solids

We propose a simulated-annealing-based genetic algorithm for solving model parameter estimation problems. The algorithm incorporates advantages of both genetic algorithms and simulated annealing. Tests on computer-generated synthetic data that closely resemble optical constants of a metal were performed to compare the efficiency of plain genetic algorithms against the simulated-annealing-based genetic algorithms. These tests assess the ability of the algorithms to and the global minimum and the accuracy of values obtained for model parameters. Finally, the algorithm with the best performance is used to fit the model dielectric function to data for platinum and aluminum. (C) 1997 Optical Society of America.

Modeling of subcutaneous absorption kinetics of infusion solutions in the elderly using technetium

Absorption kinetics of solutes given with the subcutaneous administration of fluids is ill-defined. The gamma emitter, technitium pertechnetate, enabled estimates of absorption rate to be estimated independently using two approaches. In the first approach, the counts remaining at the site were estimated by imaging above the subcutaneous administration site, whereas in the second approach, the plasma technetium concentration-time profiles were monitored up to 8 hr after technetium administration. Boluses of technetium pertechnetate were given both intravenously and subcutaneously on separate occasions with a multiple dosing regimen using three doses on each occasion. The disposition of technetium after iv administration was best described by biexponential kinetics with a V-ss of 0.30 +/- 0.11 L/kg and a clearance of 30.0 +/- 13.1 ml/min. The subcutaneous absorption kinetics was best described as a single exponential process with a half-life of 18.16 +/- 3.97 min by image analysis and a half-life of 11.58 +/- 2.48 min using plasma technetium time data. The bioavailability of technetium by the subcutaneous route was estimated to be 0.96 +/- 0.12. The absorption half-life showed no consistent change with the duration of the subcutaneous infusion. The amount remaining at the absorption site with time was similar when analyzed using image analysis, and plasma concentrations assuming multiexponential disposition kinetics and a first-order absorption process. Profiles of fraction remaining at the absorption sire generated by deconvolution analysis, image analysis, and assumption of a constant first-order absorption process were similar. Slowing of absorption from the subcutaneous administration site is apparent after the last bolus dose in three of the subjects and can De associated with the stopping of the infusion. In a fourth subject, the retention of technetium at the subcutaneous site is more consistent with accumulation of technetium near the absorption site as a result of systemic recirculation.