Photo luminescent polymer electrolyte based on agar and containing europium picrate for electrochemical devices

Dispersion of photoluminescent rare earth metal complexes in polymer matrices is of great interest due to the possibility of avoiding the saturation of the photoluminescent signal. The possibility of using a natural ionic conducting polymer matrix was investigated in this study. Samples of agar-based electrolytes containing europium picrate were prepared and characterized by physical and chemical analyses. The FTIR spectra indicated strong interaction of agar O-H and 3.6-anhydro-galactose C-O groups with glycerol and europium picrate. The DSC analyses revealed no glass transition temperature of the samples in the -60 to 250 degrees C range. From the thermogravimetry (TG), a thermal stability of the samples of up to 180 degrees C was stated. The membranes were subjected to ionic conductivity measurement, which provided the values of 2.6 x 10(-6) S/cm for the samples with acetic acid and 1.6 x 10(-5) S/cm for the samples without acetic acid. Moreover, the temperature-dependent ionic conductivity measurements revealed both Arrhenius and VTF models of the conductivity depending on the sample. Surface visualization through scanning electron microscopy (SEM) demonstrated good uniformity. The samples were also applied in small electrochromic devices and showed good electrochemical stability. The present work confirmed that these materials may perform as satisfactory multifunctional component layers in the field of electrochemical devices. (C) 2012 Elsevier B.V. All rights reserved.

Validation of the 2000 Bernstein-Parsonnet and EuroSCORE at the Heart Institute - USP

Objective: To validate the 2000 Bernstein Parsonnet (2000BP) and additive EuroSCORE (ES) to predict mortality in patients who underwent coronary bypass surgery and/or heart valve surgery at the Heart Institute, University of Sao Paulo (InCor/HC-FMUSP). Methods:A prospective observational design. We analyzed 3000 consecutive patients who underwent coronary bypass surgery and/or heart valve surgery, between May 2007 and July 2009 at the InCor/HC-FMUSP. Mortality was calculated with the 2000BP and ES models. The correlation between estimated mortality and observed mortality was validated by calibration and discrimination tests. Results: There were significant differences in the prevalence of risk factors between the study population, 2000BP and ES. Patients were stratified into five groups for 2000BP and three for the ES. In the validation of models, the ES showed good calibration (P = 0396), however, the 2000BP (P = 0.047) proved inadequate. In discrimination, the area under the ROC curve proved to be good for models, ES (0.79) and 2000BP (0.80). Conclusion: In the validation, 2000BP proved questionable and ES appropriate to predict mortality in patients who underwent coronary bypass surgery and/or heart valve surgery at the InCor/HC-FMUSP.

Within-plant isoprene oxidation confirmed by direct emissions of oxidation products methyl vinyl ketone and methacrolein

Isoprene is emitted from many terrestrial plants at high rates, accounting for an estimated 1/3 of annual global volatile organic compound emissions from all anthropogenic and biogenic sources combined. Through rapid photooxidation reactions in the atmosphere, isoprene is converted to a variety of oxidized hydrocarbons, providing higher order reactants for the production of organic nitrates and tropospheric ozone, reducing the availability of oxidants for the breakdown of radiatively active trace gases such as methane, and potentially producing hygroscopic particles that act as effective cloud condensation nuclei. However, the functional basis for plant production of isoprene remains elusive. It has been hypothesized that in the cell isoprene mitigates oxidative damage during the stress-induced accumulation of reactive oxygen species (ROS), but the products of isoprene-ROS reactions in plants have not been detected. Using pyruvate-2-13C leaf and branch feeding and individual branch and whole mesocosm flux studies, we present evidence that isoprene (i) is oxidized to methyl vinyl ketone and methacrolein (iox) in leaves and that iox/i emission ratios increase with temperature, possibly due to an increase in ROS production under high temperature and light stress. In a primary rainforest in Amazonia, we inferred significant in plant isoprene oxidation (despite the strong masking effect of simultaneous atmospheric oxidation), from its influence on the vertical distribution of iox uptake fluxes, which were shifted to low isoprene emitting regions of the canopy. These observations suggest that carbon investment in isoprene production is larger than that inferred from emissions alone and that models of tropospheric chemistry and biotachemistryclimate interactions should incorporate isoprene oxidation within both the biosphere and the atmosphere with potential implications for better understanding both the oxidizing power of the troposphere and forest response to climate change.

DengueTools: innovative tools and strategies for the surveillance and control of dengue

Dengue fever is a mosquito-borne viral disease estimated to cause about 230 million infections worldwide every year, of which 25,000 are fatal. Global incidence has risen rapidly in recent decades with some 3.6 billion people, over half of the world's population, now at risk, mainly in urban centres of the tropics and subtropics. Demographic and societal changes, in particular urbanization, globalization, and increased international travel, are major contributors to the rise in incidence and geographic expansion of dengue infections. Major research gaps continue to hamper the control of dengue. The European Commission launched a call under the 7th Framework Programme with the title of 'Comprehensive control of Dengue fever under changing climatic conditions'. Fourteen partners from several countries in Europe, Asia, and South America formed a consortium named 'DengueTools' to respond to the call to achieve better diagnosis, surveillance, prevention, and predictive models and improve our understanding of the spread of dengue to previously uninfected regions (including Europe) in the context of globalization and climate change. The consortium comprises 12 work packages to address a set of research questions in three areas: Research area 1: Develop a comprehensive early warning and surveillance system that has predictive capability for epidemic dengue and benefits from novel tools for laboratory diagnosis and vector monitoring. Research area 2: Develop novel strategies to prevent dengue in children. Research area 3: Understand and predict the risk of global spread of dengue, in particular the risk of introduction and establishment in Europe, within the context of parameters of vectorial capacity, global mobility, and climate change. In this paper, we report on the rationale and specific study objectives of 'DengueTools'. DengueTools is funded under the Health theme of the Seventh Framework Programme of the European Community, Grant Agreement Number: 282589 Dengue Tools.

Secondary production of sandy beach macrofauna: An evaluation of predictive models

During the last three decades, several predictive models have been developed to estimate the somatic production of macroinvertebrates. Although the models have been evaluated for their ability to assess the production of macrobenthos in different marine ecosystems, these approaches have not been applied specifically to sandy beach macrofauna and may not be directly applicable to this transitional environment. Hence, in this study, a broad literature review of sandy beach macrofauna production was conducted and estimates obtained with cohort-based and size-based methods were collected. The performance of nine models in estimating the production of individual populations from the sandy beach environment, evaluated for all taxonomic groups combined and for individual groups separately, was assessed, comparing the production predicted by the models to the estimates obtained from the literature (observed production). Most of the models overestimated population production compared to observed production estimates, whether for all populations combined or more specific taxonomic groups. However, estimates by two models developed by Cusson and Bourget provided best fits to measured production, and thus represent the best alternatives to the cohort-based and size-based methods in this habitat. The consistent performance of one of these Cusson and Bourget models, which was developed for the macrobenthos of sandy substrate habitats (C&B-SS), shows that the performance of a model does not depend on whether it was developed for a specific taxonomic group. Moreover, since some widely used models (e.g., the Robertson model) show very different responses when applied to the macrofauna of different marine environments (e.g., sandy beaches and estuaries), prior evaluation of these models is essential.

A rationale for long-lived quarks and leptons at the LHC: low energy flavour theory

In the framework of gauged flavour symmetries, new fermions in parity symmetric representations of the standard model are generically needed for the compensation of mixed anomalies. The key point is that their masses are also protected by flavour symmetries and some of them are expected to lie way below the flavour symmetry breaking scale(s), which has to occur many orders of magnitude above the electroweak scale to be compatible with the available data from flavour changing neutral currents and CP violation experiments. We argue that, actually, some of these fermions would plausibly get masses within the LHC range. If they are taken to be heavy quarks and leptons, in (bi)-fundamental representations of the standard model symmetries, their mixings with the light ones are strongly constrained to be very small by electroweak precision data. The alternative chosen here is to exactly forbid such mixings by breaking of flavour symmetries into an exact discrete symmetry, the so-called proton-hexality, primarily suggested to avoid proton decay. As a consequence of the large value needed for the flavour breaking scale, those heavy particles are long-lived and rather appropriate for the current and future searches at the LHC for quasi-stable hadrons and leptons. In fact, the LHC experiments have already started to look for them.

Pion, Kaon, and Proton Production in Central Pb-Pb Collisions at root s(NN)=2.76 TeV

In this Letter we report the first results on pi(+/-), K-+/-, p, and (p) over bar production at midrapidity (vertical bar y vertical bar < 0.5) in central Pb-Pb collisions at root s(NN) = 2.76 TeV, measured by the ALICE experiment at the LHC. The p(T) distributions and yields are compared to previous results at root s(NN) = 200 GeV and expectations from hydrodynamic and thermal models. The spectral shapes indicate a strong increase of the radial flow velocity with root s(NN), which in hydrodynamic models is expected as a consequence of the increasing particle density. While the K/pi ratio is in line with predictions from the thermal model, the p/pi ratio is found to be lower by a factor of about 1.5. This deviation from thermal model expectations is still to be understood.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Independent predictors and a prognostic model for surgical outcome in refractory frontal lobe epilepsy

Purpose: Refractory frontal lobe epilepsy (FLE) remains one of the most challenging surgically remediable epilepsy syndromes. Nevertheless, definition of independent predictors and predictive models of postsurgical seizure outcome remains poorly explored in FLE. Methods: We retrospectively analyzed data from 70 consecutive patients with refractory FLE submitted to surgical treatment at our center from July 1994 to December 2006. Univariate results were submitted to logistic regression models and Cox proportional hazards regression to identify isolated risk factors for poor surgical results and to construct predictive models for surgical outcome in FLE. Results: From 70 patients submitted to surgery, 45 patients (64%) had favorable outcome and 37 (47%) became seizure free. Isolated risk factors for poor surgical outcome are expressed in hazard ratio (H.R.) and were time of epilepsy (H.R.=4.2; 95% C.I.=.1.5-11.7; p=0.006), ictal EEG recruiting rhythm (H.R. = 2.9; 95% C.I. = 1.1-7.7; p=0.033); normal MRI (H.R. = 4.8; 95% C.I. = 1.4-16.6; p = 0.012), and MRI with lesion involving eloquent cortex (H.R. = 3.8; 95% C.I. = 1.2-12.0; p = 0.021). Based on these variables and using a logistic regression model we constructed a model that correctly predicted long-term surgical outcome in up to 80% of patients. Conclusion: Among independent risk factors for postsurgical seizure outcome, epilepsy duration is a potentially modifiable factor that could impact surgical outcome in FLE. Early diagnosis, presence of an MRI lesion not involving eloquent cortex, and ictal EEG without recruited rhythm independently predicted favorable outcome in this series. (C) 2011 Elsevier B.V. All rights reserved.

Organization Performance Evaluation Using System Thinking: A Study in Brazilian Chemical Organizations Models

System thinking allows companies to use subjective constructs indicators like recursiveness, cause-effect relationships and autonomy to performance evaluation. Thus, the question that motivates this paper is: Are Brazilian companies searching new performance measurement and evaluation models based on system thinking? The study investigates models looking for system thinking roots in their framework. It was both exploratory and descriptive based on a multiple four case studies strategy in chemical sector. The findings showed organizational models have some characteristics that can be related to system thinking as system control and communication. Complexity and autonomy are deficiently formalized by the companies. All data suggest, inside its context, that system thinking seems to be adequate to organizational performance evaluation but remains distant from the management proceedings.

Bagging k-dependence probabilistic networks: An alternative powerful fraud detection tool

Fraud is a global problem that has required more attention due to an accentuated expansion of modern technology and communication. When statistical techniques are used to detect fraud, whether a fraud detection model is accurate enough in order to provide correct classification of the case as a fraudulent or legitimate is a critical factor. In this context, the concept of bootstrap aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the adjusted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper, for the first time, we aim to present a pioneer study of the performance of the discrete and continuous k-dependence probabilistic networks within the context of bagging predictors classification. Via a large simulation study and various real datasets, we discovered that the probabilistic networks are a strong modeling option with high predictive capacity and with a high increment using the bagging procedure when compared to traditional techniques. (C) 2012 Elsevier Ltd. All rights reserved.

Tracking the impact of translational research in psychiatry: state of the art and perspectives

Personalized treatments have become a primary goal in translational psychiatric research. They include the identification of neural circuits associated with psychiatric disorders and definition of treatment according to individual characteristics. Many new tools and technologies have been developed but further efforts are required to provide clues on how these scientific advances in psychiatry may be translated into more effective therapeutic approaches. Obstacles to the progress of translational psychiatry also involve numerous scientific, financial, ethical, logistics and regulatory aspects. Also, the goal of DSM-5 to expand “signs and symptoms” classification to incorporate biological measures may help the development of new multifactorial and dimensional models able to better understand the pathophysiology of psychiatric disorders and develop improved treatments. Finally, a better understanding on the significant response variability, cognitive functioning, role of comorbidities and treatment-resistant cases are critical for the development of prevention and intervention strategies that are more effective.

Fidelity and game-based technology in management education

This study explores educational technology and management education by analyzing fidelity in game-based management education interventions. A sample of 31 MBA students was selected to help answer the research question: To what extent do MBA students tend to recognize specific game-based academic experiences, in terms of fidelity, as relevant to their managerial performance? Two distinct game-based interventions (BG1 and BG2) with key differences in fidelity levels were explored: BG1 presented higher physical and functional fidelity levels and lower psychological fidelity levels. Hypotheses were tested with data from the participants, collected shortly after their experiences, related to the overall perceived quality of game-based interventions. The findings reveal a higher overall perception of quality towards BG1: (a) better for testing strategies, (b) offering better business and market models, (c) based on a pace that better stimulates learning, and (d) presenting a fidelity level that better supports real world performance. This study fosters the conclusion that MBA students tend to recognize, to a large extent, that specific game-based academic experiences are relevant and meaningful to their managerial development, mostly with heightened fidelity levels of adopted artifacts. Agents must be ready and motivated to explore the new, to try and err, and to learn collaboratively in order to perform.

Development of a supplier and purchase order management product/service under the 4PL logistics concept: a case study

Supply chain starts with a demand arisen and ends with material transport and delivery at its final destination. With this in mind, most of manufacturing, processors or distribution companies of consumer goods, spare parts and components for production, processing and finished goods, within national or international markets, may not have information and control over its supply chain performance. This article presents concept and logistics models evolution, purchase order and international supplier management, control tower and its logistics information systems. This also presents a real process implementation for a global high tech manufacturer company.

Phage display identification of CD100 in human atherosclerotic plaque macrophages and foam cells

Atherosclerosis is a complex disease in which vessels develop plaques comprising dysfunctional endothelium, monocyte derived lipid laden foam cells and activated lymphocytes. Considering that humans and animal models of the disease develop quite distinct plaques, we used human plaques to search for proteins that could be used as markers of human atheromas. Phage display peptide libraries were probed to fresh human carotid plaques, and a bound phage homologous to plexin B1, a high affinity receptor for CD100, was identified. CD100 is a member of the semaphorin family expressed by most hematopoietic cells and particularly by activated T cells. CD100 expression was analyzed in human plaques and normal samples. CD100 mRNA and protein were analyzed in cultured monocytes, macrophages and foam cells. The effects of CD100 in oxLDL-induced foam cell formation and in CD36 mRNA abundance were evaluated. Human atherosclerotic plaques showed strong labeling of CD100/SEMA4D. CD100 expression was further demonstrated in peripheral blood monocytes and in in vitro differentiated macrophages and foam cells, with diminished CD100 transcript along the differentiation of these cells. Incubation of macrophages with CD100 led to a reduction in oxLDL-induced foam cell formation probably through a decrease of CD36 expression, suggesting for the first time an atheroprotective role for CD100 in the human disease. Given its differential expression in the numerous foam cells and macrophages of the plaques and its capacity to decrease oxLDL engulfment by macrophages we propose that CD100 may have a role in atherosclerotic plaque development, and may possibly be employed in targeted treatments of these atheromas.