Surface coverage in wireless sensor networks based on delaunay tetrahedralization

In this work is presented a new method for sensor deployment on 3D surfaces. The method was structured on different steps. The first one aimed discretizes the relief of interest with Delaunay algorithm. The tetrahedra and relative values (spatial coordinates of each vertex and faces) were input to construction of 3D Voronoi diagram. Each circumcenter was calculated as a candidate position for a sensor node: the corresponding circular coverage area was calculated based on a radius r. The r value can be adjusted to simulate different kinds of sensors. The Dijkstra algorithm and a selection method were applied to eliminate candidate positions with overlapped coverage areas or beyond of surface of interest. Performance evaluations measures were defined using coverage area and communication as criteria. The results were relevant, once the mean coverage rate achieved on three different surfaces were among 91% and 100%.

Effect of different solutions on color stability of acrylic resin-based dentures

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

Protein Hydrolysates Are Avoided by Herbivores but Not by Omnivores in Two-Choice Preference Tests

Background: The negative sensory properties of casein hydrolysates (HC) often limit their usage in products intended for human consumption, despite HC being nutritious and having many functional benefits. Recent, but taxonomically limited, evidence suggests that other animals also avoid consuming HC when alternatives exist. Methodology/Principal Findings: We evaluated ingestive responses of five herbivorous species (guinea pig, mountain beaver, gopher, vole, and rabbit) and five omnivorous species (rat, coyote, house mouse, white-footed mouse, and deer mouse; N = 16–18/species) using solid foods containing 20% HC in a series of two-choice preference tests that used a nonprotein, cellulose-based alternative. Individuals were also tested with collagen hydrolysate (gelatin; GE) to determine whether it would induce similar ingestive responses to those induced by HC. Despite HC and GE having very different nutritional and sensory qualities, both hydrolysates produced similar preference score patterns. We found that the herbivores generally avoided the hydrolysates while the omnivores consumed them at similar levels to the cellulose diet or, more rarely, preferred them (HC by the white-footed mouse; GE by the rat). Follow-up preference tests pairing HC and the nutritionally equivalent intact casein (C) were performed on the three mouse species and the guinea pigs. For the mice, mean HC preference scores were lower in the HC v C compared to the HC v Cel tests, indicating that HC’s sensory qualities negatively affected its consumption. However, responses were species-specific. For the guinea pigs, repeated exposure to HC or C (4.7-h sessions; N = 10) were found to increase subsequent HC preference scores in an HC v C preference test, which was interpreted in the light of conservative foraging strategies thought to typify herbivores. Conclusions/Significance: This is the first empirical study of dietary niche-related taxonomic differences in ingestive responses to protein hydrolysates using multiple species under comparable conditions. Our results provide a basis for future work in sensory, physiological, and behavioral mechanisms of hydrolysate avoidance and on the potential use of hydrolysates for pest management.

JVM-based Techniques for Improving Java Observability

Observability measures the support of computer systems to accurately capture, analyze, and present (collectively observe) the internal information about the systems. Observability frameworks play important roles for program understanding, troubleshooting, performance diagnosis, and optimizations. However, traditional solutions are either expensive or coarse-grained, consequently compromising their utility in accommodating today’s increasingly complex software systems. New solutions are emerging for VM-based languages due to the full control language VMs have over program executions. Existing such solutions, nonetheless, still lack flexibility, have high overhead, or provide limited context information for developing powerful dynamic analyses. In this thesis, we present a VM-based infrastructure, called marker tracing framework (MTF), to address the deficiencies in the existing solutions for providing better observability for VM-based languages. MTF serves as a solid foundation for implementing fine-grained low-overhead program instrumentation. Specifically, MTF allows analysis clients to: 1) define custom events with rich semantics ; 2) specify precisely the program locations where the events should trigger; and 3) adaptively enable/disable the instrumentation at runtime. In addition, MTF-based analysis clients are more powerful by having access to all information available to the VM. To demonstrate the utility and effectiveness of MTF, we present two analysis clients: 1) dynamic typestate analysis with adaptive online program analysis (AOPA); and 2) selective probabilistic calling context analysis (SPCC). In addition, we evaluate the runtime performance of MTF and the typestate client with the DaCapo benchmarks. The results show that: 1) MTF has acceptable runtime overhead when tracing moderate numbers of marker events; and 2) AOPA is highly effective in reducing the event frequency for the dynamic typestate analysis; and 3) language VMs can be exploited to offer greater observability.

A computer-controlled color vision test for children based on the Cambridge Colour Test

The present study aimed at providing conditions for the assessment of color discrimination in children using a modified version of the Cambridge Colour Test (CCT, Cambridge Research Systems Ltd., Rochester, UK). Since the task of indicating the gap of the Landolt C used in that test proved counterintuitive and/or difficult for young children to understand, we changed the target Stimulus to a patch of color approximately the size of the Landolt C gap (about 7 degrees Of Visual angle at 50 cm from the monitor). The modifications were performed for the CCT Trivector test which measures color discrimination for the protan, deutan and tritan confusion lines. Experiment I Sought to evaluate the correspondence between the CCT and the child-friendly adaptation with adult subjects (n = 29) with normal color vision. Results showed good agreement between the two test versions. Experiment 2 tested the child-friendly software with children 2 to 7 years old (n = 25) using operant training techniques for establishing and maintaining the subjects` performance. Color discrimination thresholds were progressively lower as age increased within the age range tested (2 to 30 years old), and the data-including those obtained for children-fell within the range of thresholds previously obtained for adults with the CCT. The protan and deutan thresholds were consistently lower than tritan thresholds, a pattern repeatedly observed in adults tested with the CCT. The results demonstrate that the test is fit for assessment of color discrimination in young children and may be a useful tool for the establishment of color vision thresholds during development.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

A stable liquid-liquid extraction system for clavulanic acid using polymer-based aqueous two-phase systems

The partitioning of Clavulanic Acid (CA) in a novel inexpensive and stable aqueous two-phase system (ATPS) composed by poly(ethylene glycol) (PEG) and sodium polyacrylate (NaPA) has been studied. The aqueous two-phase systems are formed by mixing both polymers with a salt (NaCl or Na2SO4) and an aqueous solution of CA. The stability of CA on the presence of both polymers was investigated and it was observed that these polymers do not degrade the biomolecule. The effect of PEG-molecular size, polymer concentrations on the commercial CA partitioning has been studied, at 25 degrees C. The data showed that commercial CA was preferentially partitioned for the PEG-rich phase with a partition coefficient (K-CA) between 1 and 12 in the PEG/NaPA aqueous two phase systems supplemented with NaCl and Na2SO4. The partition to the PEG phase was increased in the systems with high polymer concentrations. Furthermore, Na2SO4 caused higher CA preference for the PEG-phase than NaCl. The systems having a composition with 10 wt.% of PEG4000, 20 wt.% of NaPA8000 and 6 wt.% of Na2SO4 were selected as the optimal ones in terms of recovery of CA from fermented broth of Streptomyces clavuligerus. The partitioning results (K-CA = 9.15 +/- 1.06) are competitive with commercial extraction methods of CA (K-CA = 11.91 +/- 2.08) which emphasizes that the system PEG/NaPA/Na2SO4 can be used as a new process to CA purification/concentration from fermented broth. (C) 2012 Elsevier B.V. All rights reserved.

Capillary bioreactors based on human purine nucleoside phosphorylase: A new approach for ligands identification and characterization

The enzyme purine nucleoside phosphorylase (PNP) is a target for the discovery of new lead compounds employed on the treatment severe T-cell mediated disorders. Within this context, the development of new, direct, and reliable methods for ligands screening is an important task. This paper describes the preparation of fused silica capillaries human PNP (HsPNP) immobilized enzyme reactor (IMER). The activity of the obtained IMER is monitored on line in a multidimensional liquid chromatography system, by the quantification of the product formed throughout the enzymatic reaction. The Km value for the immobilized enzyme was about twofold higher than that measured for the enzyme in solution (255 +/- 29.2 mu M and 133 +/- 114.9 mu M, respectively). A new fourth-generation immucillin derivative (DI4G: IC50 = 40.6 +/- 0.36 nM), previously identified and characterized in HsPNP free enzyme assays, was used to validate the IMER as a screening method for HsPNP ligands. The validated method was also used for mechanistic studies with this inhibitor. This new approach is a valuable tool to PNP ligand screening, since it directly measures the hypoxanthine released by inosine phosphorolysis, thus furnishing more reliable results than those one used in a coupled enzymatic spectrophotometric assay. (C) 2011 Elsevier B.V. All rights reserved.

Towards global consensus on outcome measures for atopic eczema research: results of the HOME II meeting

The use of nonstandardized and inadequately validated outcome measures in atopic eczema trials is a major obstacle to practising evidence-based dermatology. The Harmonising Outcome Measures for Eczema (HOME) initiative is an international multiprofessional group dedicated to atopic eczema outcomes research. In June 2011, the HOME initiative conducted a consensus study involving 43 individuals from 10 countries, representing different stakeholders (patients, clinicians, methodologists, pharmaceutical industry) to determine core outcome domains for atopic eczema trials, to define quality criteria for atopic eczema outcome measures and to prioritize topics for atopic eczema outcomes research. Delegates were given evidence-based information, followed by structured group discussion and anonymous consensus voting. Consensus was achieved to include clinical signs, symptoms, long-term control of flares and quality of life into the core set of outcome domains for atopic eczema trials. The HOME initiative strongly recommends including and reporting these core outcome domains as primary or secondary endpoints in all future atopic eczema trials. Measures of these core outcome domains need to be valid, sensitive to change and feasible. Prioritized topics of the HOME initiative are the identification/development of the most appropriate instruments for the four core outcome domains. HOME is open to anyone with an interest in atopic eczema outcomes research.

Relationship Between Regional Brain Volumes and Cognitive Performance in the Healthy Aging: An MRI Study Using Voxel-Based Morphometry

The presence of cognitive impairment is a frequent complaint among elderly individuals in the general population. This study aimed to investigate the relationship between aging-related regional gray matter (rGM) volume changes and cognitive performance in healthy elderly adults. Morphometric magnetic resonance imaging (MRI) measures were acquired in a community-based sample of 170 cognitively-preserved subjects (66 to 75 years). This sample was drawn from the "Sao Paulo Ageing and Health" study, an epidemiological study aimed at investigating the prevalence and risk factors for Alzheimer's disease in a low income region of the city of Sao Paulo. All subjects underwent cognitive testing using a cross-culturally battery validated by the Research Group on Dementia 10/66 as well as the SKT (applied on the day of MRI scanning). Blood genotyping was performed to determine the frequency of the three apolipoprotein E allele variants (APOE epsilon 2/epsilon 3/epsilon 4) in the sample. Voxelwise linear correlation analyses between rGM volumes and cognitive test scores were performed using voxel-based morphometry, including chronological age as covariate. There were significant direct correlations between worse overall cognitive performance and rGM reductions in the right orbitofrontal cortex and parahippocampal gyrus, and also between verbal fluency scores and bilateral parahippocampal gyral volume (p < 0.05, familywise-error corrected for multiple comparisons using small volume correction). When analyses were repeated adding the presence of the APOE epsilon 4 allele as confounding covariate or excluding a minority of APOE epsilon 2 carriers, all findings retained significance. These results indicate that rGM volumes are relevant biomarkers of cognitive deficits in healthy aging individuals, most notably involving temporolimbic regions and the orbitofrontal cortex.

Effect of Nintendo Wii (TM)-based motor and cognitive training on activities of daily living in patients with Parkinson's disease: A randomised clinical trial

Objectives To investigate the effect of Nintendo Wii (TM)-based motor cognitive training versus balance exercise therapy on activities of daily living in patients with Parkinson's disease. Design Parallel, prospective, single-blind, randomised clinical trial. Setting Brazilian Parkinson Association. Participants Thirty-two patients with Parkinson's disease (Hoehn and Yahr stages 1 and 2). Interventions Fourteen training sessions consisting of 30 minutes of stretching, strengthening and axial mobility exercises, plus 30 minutes of balance training. The control group performed balance exercises without feedback or cognitive stimulation, and the experimental group performed 10 Wii Fit (TM) games. Main outcome measure Section II of the Unified Parkinson's Disease Rating Scale (UPDRS-II). Randomisation Participants were randomised into a control group (n = 16) and an experimental group (n = 16) through blinded drawing of names. Statistical analysis Repeated-measures analysis of variance (RM-ANOVA). Results Both groups showed improvement in the UPDRS-II with assessment effect (RM-ANOVA P < 0.001, observed power = 0.999). There was no difference between the control group and the experimental group before training {8.9 [standard deviation (SD) 2.9] vs 10.1 (SD 3.8)}, after training [7.6 (SD 2.9) vs 8.1 (SD 3.5)] or 60 days after training [8.1 (SD 3.2) vs 8.3 (SD 3.6)]. The mean difference of the whole group between before training and after training was -0.9 (SD 2.3, 95% confidence interval -1.7 to -0.6). Conclusion Patients with Parkinson's disease showed improved performance in activities of daily living after 14 sessions of balance training, with no additional advantages associated with the Wii-based motor and cognitive training. Registered on http://www.clinicaltrials.gov (identifier: NCT01580787). (C) 2012 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Trends of the genetic connectedness measures among Nelore beef cattle herds

Validity of comparisons between expected breeding values obtained from best linear unbiased prediction procedures in genetic evaluations is dependent on genetic connectedness among herds. Different cattle breeding programmes have their own particular features that distinguish their database structure and can affect connectedness. Thus, the evolution of these programmes can also alter the connectedness measures. This study analysed the evolution of the genetic connectedness measures among Brazilian Nelore cattle herds from 1999 to 2008, using the French Criterion of Admission to the group of Connected Herds (CACO) method, based on coefficients of determination (CD) of contrasts. Genetic connectedness levels were analysed by using simple and multiple regression analyses on herd descriptors to understand their relationship and their temporal trends from the 19992003 to the 20042008 period. The results showed a high level of genetic connectedness, with CACO estimates higher than 0.4 for the majority of them. Evaluation of the last 5-year period showed only a small increase in average CACO measures compared with the first 5 years, from 0.77 to 0.80. The percentage of herds with CACO estimates lower than 0.7 decreased from 27.5% in the first period to 16.2% in the last one. The connectedness measures were correlated with percentage of progeny from connecting sires, and the artificial insemination spread among Brazilian herds in recent years. But changes in connectedness levels were shown to be more complex, and their complete explanation cannot consider only herd descriptors. They involve more comprehensive changes in the relationship matrix, which can be only fully expressed by the CD of contrasts.

Work Precariousness and Risk of Accidents in Civil Construction: A study based on the Collective Work Analysis

This paper aims to describe the construction workers' activities, as well as their perceptions about risks and workload. The study, based on the Collective Work Analysis, is part of a broader public policies project for the improvement of SIVAT (Surveillance System of Work Accidents) - in the city of Piracicaba (Southeastern Brazil). Civil construction was prioritized given the epidemiological magnitude of the occurrence of work accidents and the limited efficacy of traditional surveillance initiatives in this sector due to informal employment practices, outsourcing, high staff turnover, etc. The workers have a high level of awareness concerning the risk of accidents, but they believe that the main preventive measures hinder or even make it impossible for them to carry out the tasks. Our findings question the efficacy of traditional training for adherence to safety practices, thus highlighting the need for a transformative pedagogy for preventive practices and the health promotion of workers.

Linear and nonlinear measures of fetal heart rate patterns evaluated on very short fetal magnetocardiograms

We analyzed the effectiveness of linear short- and long-term variability time domain parameters, an index of sympatho-vagal balance (SDNN/RMSSD) and entropy in differentiating fetal heart rate patterns (fHRPs) on the fetal heart rate (fHR) series of 5, 3 and 2 min duration reconstructed from 46 fetal magnetocardiograms. Gestational age (GA) varied from 21 to 38 weeks. FHRPs were classified based on the fHR standard deviation. In sleep states, we observed that vagal influence increased with GA, and entropy significantly increased (decreased) with GA (SDNN/RMSSD), demonstrating that a prevalence of vagal activity with autonomous nervous system maturation may be associated with increased sleep state complexity. In active wakefulness, we observed a significant negative (positive) correlation of short-term (long-term) variability parameters with SDNN/RMSSD. ANOVA statistics demonstrated that long-term irregularity and standard deviation of normal-to-normal beat intervals (SDNN) best differentiated among fHRPs. Our results confirm that short-and long-term variability parameters are useful to differentiate between quiet and active states, and that entropy improves the characterization of sleep states. All measures differentiated fHRPs more effectively on very short HR series, as a result of the fMCG high temporal resolution and of the intrinsic timescales of the events that originate the different fHRPs.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.