Self-Organizing Maps of Molecular Descriptors for Sesquiterpene Lactones and Their Application to the Chemotaxonomy of the Asteraceae Family

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Tank experiments with borehole self-potential data

Despite their importance in the evaluation of petroleum and gas reservoirs, measurements of self-potential data under borehole conditions (well-logging) have found only minor applications in aquifer and waste-site characterization. This can be attributed to lower signals from the diffusion fronts in near-surface environments because measurements are made long after the drilling of the well, when concentration fronts are already disappearing. Proportionally higher signals arise from streaming potentials that prevent using simple interpretation models that assume signals from diffusion only. Our laboratory experiments found that dual-source self-potential signals can be described by a simple linear model, and that contributions (from diffusion and streaming potentials) can be isolated by slightly perturbing the borehole conditions. Perturbations are applied either by changing the concentration of the borehole-filling solution or its column height. Parameters useful for formation evaluation can be estimated from data measured during perturbations, namely, pore water resistivity, pressure drop across the borehole wall, and electrokinetic coupling parameter. These are important parameters to assess, respectively, water quality, aquifer lateral continuity, and interfacial properties of permeable formations.

Integration of spatial and temporal models to predict extreme water table depths

The objective of this work was to evaluate extreme water table depths in a watershed, using methods for geographical spatial data analysis. Groundwater spatio-temporal dynamics was evaluated in an outcrop of the Guarani Aquifer System. Water table depths were estimated from monitoring of water levels in 23 piezometers and time series modeling available from April 2004 to April 2011. For generation of spatial scenarios, geostatistical techniques were used, which incorporated into the prediction ancillary information related to the geomorphological patterns of the watershed, using a digital elevation model. This procedure improved estimates, due to the high correlation between water levels and elevation, and aggregated physical sense to predictions. The scenarios showed differences regarding the extreme levels - too deep or too shallow ones - and can subsidize water planning, efficient water use, and sustainable water management in the watershed.

A novel self consistent calculation approach for the capacitance-voltage characteristics of semiconductor quantum wire transistors based on a split-gate configuration

Purpose - The purpose of this paper is to develop an efficient numerical algorithm for the self-consistent solution of Schrodinger and Poisson equations in one-dimensional systems. The goal is to compute the charge-control and capacitance-voltage characteristics of quantum wire transistors. Design/methodology/approach - The paper presents a numerical formulation employing a non-uniform finite difference discretization scheme, in which the wavefunctions and electronic energy levels are obtained by solving the Schrodinger equation through the split-operator method while a relaxation method in the FTCS scheme ("Forward Time Centered Space") is used to solve the two-dimensional Poisson equation. Findings - The numerical model is validated by taking previously published results as a benchmark and then applying them to yield the charge-control characteristics and the capacitance-voltage relationship for a split-gate quantum wire device. Originality/value - The paper helps to fulfill the need for C-V models of quantum wire device. To do so, the authors implemented a straightforward calculation method for the two-dimensional electronic carrier density n(x,y). The formulation reduces the computational procedure to a much simpler problem, similar to the one-dimensional quantization case, significantly diminishing running time.

DIGITAL LIBRARIES AND LEARNING OBJECTS REPOSITORIES

Discusses the technological changes that affects learning organizations as well as the human, technical, legal and sustainable aspects regarding learning objects repositories creation, maintenance and use. It presents concepts of information objects and learning objects, the functional requirements needed to their storage at Learning Management Systems. The role of Metadata is reviewed concerning learning objects creation and retrieval, followed by considerations about learning object repositories models, community participation/collaborative strategies and potential derived metrics/indicators. As a result of this desktop research, it can be said that not only technical competencies are critical to any learning objects repository implementation, but it urges that an engaged community of interest be establish as a key to support a learning object repository project. On that matter, researchers are applying Activity Theory (Vygostky, Luria y Leontiev) in order to seek joint perceptions and actions involving learning objects repository users, curators and managers, perceived as critical assets to a successful proposal.

Complex network classification using partially self-avoiding deterministic walks

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

Income inequality and elderly self-rated health in Sao Paulo, Brazil

Purpose: To test the association between income inequality and elderly self-rated health and to propose a pathway to explain the relationship. Methods: We analyzed a sample of 2143 older individuals (60 years of age and over) from 49 distritos of the Municipality of Sao Paulo, Brazil. Bayesian multilevel logistic models were performed with poor self-rated health as the outcome variable. Results: Income inequality (measured by the Gini coefficient) was found to be associated with poor self-rated health after controlling for age, sex, income and education (odds ratio, 1.19; 95% credible interval, 1.01-1.38). When the practice of physical exercise and homicide rate were added to the model, the Gini coefficient lost its statistical significance (P>.05). We fitted a structural equation model in which income inequality affects elderly health by a pathway mediated by violence and practice of physical exercise. Conclusions: The health of older individuals may be highly susceptible to the socioeconomic environment of residence, specifically to the local distribution of income. We propose that this association may be mediated by fear of violence and lack of physical activity. (C) 2012 Elsevier Inc. All rights reserved.

Benchmarking sustainable urban mobility: The case of Curitiba, Brazil

Transportation planning is currently being confronted with a broader planning view, which is given by the concept of mobility. The Index of Sustainable Urban Mobility (I_SUM) is among the tools developed for supporting this new concept implementation. It is a tool to assess the current mobility conditions of any city, which can also be applied for policy formulation. This study focus on the application of I_SUM in the city of Curitiba, Brazil. Considering that the city is known worldwide as a reference of successful urban and transportation planning, the index application must confirm it. An additional objective of the study was to evaluate the index itself, or the subjacent assessment method and reference values. A global I_SUM value of 0.747 confirmed that the city has indeed very positive characteristics regarding sustainable mobility policies. However, some deficiencies were also detected, particularly with respect to non-motorized transport modes. The application has also served to show that a few I_SUM indicators were not able to capture some of the positive aspects of the city, what may suggest the need of changes in their formulation. Finally, the index application in parts of the city suggests that the city provides fair and equitable mobility conditions to all citizens throughout the city. This is certainly a good attribute for becoming a benchmark of sustainable mobility, even if it is not yet the ideal model. (C) 2012 Elsevier Ltd. All rights reserved.

Models of passive and active dendrite motoneuron pools and their differences in muscle force control

Motoneuron (MN) dendrites may be changed from a passive to an active state by increasing the levels of spinal cord neuromodulators, which activate persistent inward currents (PICs). These exert a powerful influence on MN behavior and modify the motor control both in normal and pathological conditions. Motoneuronal PICs are believed to induce nonlinear phenomena such as the genesis of extra torque and torque hysteresis in response to percutaneous electrical stimulation or tendon vibration in humans. An existing large-scale neuromuscular simulator was expanded to include MN models that have a capability to change their dynamic behaviors depending on the neuromodulation level. The simulation results indicated that the variability (standard deviation) of a maintained force depended on the level of neuromodulatory activity. A force with lower variability was obtained when the motoneuronal network was under a strong influence of PICs, suggesting a functional role in postural and precision tasks. In an additional set of simulations when PICs were active in the dendrites of the MN models, the results successfully reproduced experimental results reported from humans. Extra torque was evoked by the self-sustained discharge of spinal MNs, whereas differences in recruitment and de-recruitment levels of the MNs were the main reason behind torque and electromyogram (EMG) hysteresis. Finally, simulations were also used to study the influence of inhibitory inputs on a MN pool that was under the effect of PICs. The results showed that inhibition was of great importance in the production of a phasic force, requiring a reduced co-contraction of agonist and antagonist muscles. These results show the richness of functionally relevant behaviors that can arise from a MN pool under the action of PICs.