Evidence of oxidative stress responses of green turtles (Chelonia mydas) to differential habitat conditions in the Mexican Caribbean.

Important foraging and nesting habitats for Caribbean green sea turtles (Chelonia mydas) exist within the Mesoamerican Reef System in the Mexican Caribbean. During the last 25 years, urban development and touristic activities have drastically increased in Quintana Roo, Mexico. Moreover, in the last decade, massive pelagic sargasso blooms have also afflicted this region; however, information about the biochemical responses of Caribbean green turtles to these inputs is absent. This study aimed to assess if the oxidative stress indicators in the red blood cells of green turtles are valuable biomarkers of the extent of the anthropic impact in this region. Persistent organic pollutants (POPs) were also measured in the plasma of free-living green turtles during 2015-2018 to characterize these habitats further. As biochemical biomarkers, the production rate of superoxide radical (O2•-), carbonylated protein content, and lipid peroxidation (TBARS) levels, and the activities of superoxide dismutase, glutathione S-transferase (GST), catalase, glutathione peroxidase were measured in erythrocytes. A 15 % occurrence of fibropapillomatosis (FP) was revealed, with tumor size being positively correlated with CAT activity in the affected individuals. A multivariate analysis embracing all oxidative stress markers discriminated green turtles between years of capture (p < 0.001), with those sampled during 2015 presenting the highest production of O2•- (p = 0.001), activities of GST (p < 0.001), levels of TBARS (p < 0.001) and carbonylated proteins (p = 0.02). These local and temporal biochemical responses coincided with the first massive Sargassum spp. bloom reported in the region. The results of this study corroborate the utility of the oxidative stress indicators as biomarkers of environmental conditions (sargasso blooms and POPs) in the green turtle as sentinel species.

Individualized Prediction of SARS-CoV-2 Infection in Mexico City Municipality during the First Six Waves of the Pandemic.

After COVID-19 emerged, alternative methods to laboratory tests for the individualized prediction of SARS-CoV-2 were developed in several world regions. The objective of this investigation was to develop models for the individualized prediction of SARS-CoV-2 infection in a large municipality of Mexico. The study included data from 36,949 patients with suspected SARS-CoV-2 infection who received a diagnostic tested at health centers of the Alvaro Obregon Jurisdiction in Mexico City registered in the Epidemiological Surveillance System for Viral Respiratory Diseases (SISVER-SINAVE). The variables that were different between a positive test and a negative test were used to generate multivariate binary logistic regression models. There was a large variation in the prediction variables for the models of different pandemic waves. The models obtained an overall accuracy of 73% (63-82%), sensitivity of 52% (18-71%), and specificity of 84% (71-92%). In conclusion, the individualized prediction models of a positive COVID-19 test based on SISVER-SINAVE data had good performance. The large variation in the prediction variables for the models of different pandemic waves highlights the continuous change in the factors that influence the spread of COVID-19. These prediction models could be applied in early case identification strategies, especially in vulnerable populations.

TTS package: Computational tools for the application of the Time Temperature Superposition principle.

The TTS package has been developed in R software to predict the mechanical properties of viscoelastic materials, at short and long observation times/frequencies by applying the Time Temperature Superposition (TTS) principle. TTS is a physical principle used in material science to estimate mechanical properties beyond the experimental range of observed times/frequencies by shifting data curves obtained at other temperatures relative to a reference temperature in the dataset. It is a methodology related to accelerated life-tests and reliability, whereas the TTS library is one of the first open source computational tool to apply the TTS principle. This R package provides free computational tools to obtain master curves that characterize materials from a thermal-mechanical approach. The TTS package also proposes, implements and explains our own method to obtain the shift factors and the master curve in a TTS analysis, based on horizontal shifting of the first derivative function of viscoelastic properties. This procedure provides shift factors estimates and smooth master curve estimates using B-spline fitting, in a fully automatic way, without assuming any parametric expression. Williams-Landel-Ferry (WLF) and Arrhenius TTS parametric models are also implemented in the TTS package. They can be fitted from shifts obtained by the our first derivative based method.

A New Wavelet-Based Privatization Mechanism for Probability Distributions.

In this paper, we propose a new privatization mechanism based on a naive theory of a perturbation on a probability using wavelets, such as a noise perturbs the signal of a digital image sensor. Wavelets are employed to extract information from a wide range of types of data, including audio signals and images often related to sensors, as unstructured data. Specifically, the cumulative wavelet integral function is defined to build the perturbation on a probability with the help of this function. We show that an arbitrary distribution function additively perturbed is still a distribution function, which can be seen as a privatized distribution, with the privatization mechanism being a wavelet function. Thus, we offer a mathematical method for choosing a suitable probability distribution for data by starting from some guessed initial distribution. Examples of the proposed method are discussed. Computational experiments were carried out using a database-sensor and two related algorithms. Several knowledge areas can benefit from the new approach proposed in this investigation. The areas of artificial intelligence, machine learning, and deep learning constantly need techniques for data fitting, whose areas are closely related to sensors. Therefore, we believe that the proposed privatization mechanism is an important contribution to increasing the spectrum of existing techniques.

Predicting Blood Parasite Load and Influence of Expression of iNOS on the Effect Size of Clinical Laboratory Parameters in Acute Trypanosoma cruzi Infection With Different Inoculum Concentrations in C57BL/6 Mice.

In Chagas disease, the initial responses of phagocyte-mediated innate immunity are strongly associated with the control of Trypanosoma cruzi and are mediated by various signaling pathways, including the inducible nitric oxide synthetase (iNOS) pathway. The clinical and laboratory manifestations of Chagas disease depend on the parasite-host relationship, i.e., the responsive capacity of the host immune system and the immunogenicity of the parasite. Here, we evaluated effect sizes in clinical and laboratory parameters mediated by acute infection with different concentrations of T. cruzi inoculum in mice immunosuppressed via iNOS pathway inactivation. Infection was induced in C57BL/6 wild-type and iNOS-/- mice with the "Y" strain of T. cruzi at three inoculum concentrations (3 × 102, 3 × 103, and 3 × 104). Parasitemia and mortality in both mouse strains were monitored. Immunohistochemistry was performed to quantify amastigotes in cardiac tissues and cardiac musculature cells. Biochemical parameters, such as blood urea nitrogen, sodium, albumin, and globulin concentrations, among others, were measured, and cytokine concentrations were also measured. Effect sizes were determined by the eta squared formula. Compared with that in wild-type animals, mice with an absence of iNOS expression demonstrated a greater parasite load, with earlier infection and a delayed parasitemia peak. Inoculum concentration was positively related to death in the immunosuppressed subgroup. Nineteen parameters (hematological, biochemical, cytokine-related, and histopathological) in the immunocompetent subgroup and four in the immunosuppressed subgroup were associated with parasitemia. Parasitemia, biochemical parameters, and hematological parameters were found to be predictors in the knockout group. The impact of effect sizes on the markers evaluated based on T. cruzi inoculum concentration was notably high in the immunocompetent group (Cohen's d = 88.50%; p <.001). These findings contribute to the understanding of physiopathogenic mechanisms underlying T. cruzi infection and also indicate the influence of the concentration of T. cruzi during infection and the immunosuppression through the iNOS pathway in clinical laboratory heterogeneity reported in acute Chagas disease.

Arboles de Decisión como Metodología para Determinar el Rendimiento Académico en Educación Superior / Decision Trees as a Methodology to Determine Academic Performance in Higher Education / Árvores de Decisão como Metodologia para Determinar o Desempenho Acadêmico no Ensino Superior

Resumen Introducción. En este artículo se presentan los resultados finales de la investigación Árboles de decisión como metodología para determinar el rendimiento académico en educación superior. Objetivo. Explicar el rendimiento académico de los alumnos que cursan asignaturas relacionadas con la programación en una institución de nivel superior ubicada en la zona urbana de Pánuco, Veracruz, México. El rendimiento académico presenta una situación que no solamente preocupa a las instituciones educativas, sino también a los estudiantes, padres de familia, profesores y directores. Puede mencionarse que este presenta también una situación mundial y que es investigado en diferentes áreas de conocimiento. Materiales y Métodos. Se aplicó un cuestionario a 341 estudiantes repartidos en el segundo, cuarto y sexto semestre. Se utilizaron dos técnicas de modelado estadístico: árbol de decisión y regresión lineal múltiple, para definir qué variables independientes están asociadas al rendimiento académico. Resultados. Se ubica que las variables de aprendizaje en el aula y las tutorías externas están relacionadas con la variable de rendimiento académico y que el 48.1 % de los alumnos necesitan algún apoyo académico o capacitación externa para el reforzamiento de la programación. Conclusiones. Se recomienda implementar estrategias de mejora para reducir la sobrecarga de trabajo de los alumnos. También realizar una sensibilización antes de aplicar la encuesta y que los cuestionarios sean aplicados en fechas de exámenes ya que los alumnos se encuentran en niveles altos de estrés. En trabajos posteriores se tiene contemplado poder evaluar los efectos sobre el rendimiento académico, económico, social y cultural.

Abstract Introduction. This article presents the results of the Decision Trees research as a methodology to determine academic performance in higher education. Objective. Explain the academic performance of students taking subjects related to programming at a higher-level institution located in the urban area of Pánuco, Veracruz, Mexico. Academic performance presents a situation that not only concerns educational institutions, but also students, parents, teachers, and principals. It can be mentioned that this also presents a world situation and that it is investigated in different areas of knowledge. Materials and methods. A questionnaire was applied to 341 students distributed in the second, fourth and sixth semester. Two statistical modeling techniques were used: decision tree and multiple linear regression, to define which independent variables are associated with academic performance. Results. It is located that the learning variables in the classroom and the external tutorials are related to the academic performance variable and that 48.1 % of the students need some academic support or external training to reinforce the programming. Conclusions. It is recommended to implement improvement strategies to reduce the work overload of the students. Also make an awareness before applying the survey and that the questionnaires are applied on test dates since the students are at high levels of stress. Future research could evaluate the effect on academic, economic and cultural performance.

Resumo Introdução. Este artigo apresenta os resultados da pesquisa Árvores de Decisão como uma metodologia para determinar o desempenho acadêmico no ensino superior. Objetivo. Explique o desempenho acadêmico dos estudantes que cursam matérias relacionadas à programação em uma instituição de nível superior localizada na área urbana de Pánuco, Veracruz, México. O desempenho acadêmico apresenta uma situação que diz respeito não apenas às instituições de ensino, mas também a estudantes, pais, professores e diretores. Pode-se mencionar que isso também apresenta uma situação mundial e é investigada em diferentes áreas do conhecimento. Materiais e métodos. Foi aplicado um questionário a 341 alunos distribuídos no segundo, quarto e sexto semestre. Foram utilizadas duas técnicas de modelagem estatística: árvore de decisão e regressão linear múltipla, para definir quais variáveis independentes estão associadas ao desempenho acadêmico. Resultados. Fica localizado que as variáveis de aprendizagem em sala de aula e os tutoriais externos estão relacionados à variável desempenho acadêmico e que 48,1 % dos alunos precisam de algum apoio acadêmico ou treinamento externo para reforçar a programação. Conclusões. Recomenda-se implementar estratégias de melhoria para reduzir a sobrecarga de trabalho dos alunos. Lembre-se também antes de aplicar a pesquisa e que os questionários sejam aplicados nas datas dos testes, uma vez que os alunos estão em altos níveis de estresse.

Breakpoint Analysis for the COVID-19 Pandemic and Its Effect on the Stock Markets.

In this research, statistical models are formulated to study the effect of the health crisis arising from COVID-19 in global markets. Breakpoints in the price series of stock indexes are considered. Such indexes are used as an approximation of the stock markets in different countries, taking into account that they are indicative of these markets because of their composition. The main results obtained in this investigation highlight that countries with better institutional and economic conditions are less affected by the pandemic. In addition, the effect of the health index in the models is associated with their non-significant parameters. This is due to that the health index used in the modeling would not determine the different capacities of the countries analyzed to respond efficiently to the pandemic effect. Therefore, the contagion is the preponderant factor when analyzing the structural breakdown that occurred in the world economy.

Unsupervised Inference of Protein Fitness Landscape from Deep Mutational Scan.

The recent technological advances underlying the screening of large combinatorial libraries in high-throughput mutational scans deepen our understanding of adaptive protein evolution and boost its applications in protein design. Nevertheless, the large number of possible genotypes requires suitable computational methods for data analysis, the prediction of mutational effects, and the generation of optimized sequences. We describe a computational method that, trained on sequencing samples from multiple rounds of a screening experiment, provides a model of the genotype-fitness relationship. We tested the method on five large-scale mutational scans, yielding accurate predictions of the mutational effects on fitness. The inferred fitness landscape is robust to experimental and sampling noise and exhibits high generalization power in terms of broader sequence space exploration and higher fitness variant predictions. We investigate the role of epistasis and show that the inferred model provides structural information about the 3D contacts in the molecular fold.

Analysis of a dose-response assay in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) using the logistic regression model under the Bayesian approach

This paper shows the results of a dose-response study in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) exposed to the insecticide Fastac Duo. The aim was to evaluate the lethal concentration that causes the death of 50% of bees (LC50) and investigate the odd of mortality after exposure to different concentrations, using the logistic regression model under the Bayesian approach. In this approach, it is possible to incorporate a prior information and gives more accurate inferential results. Three independent dose-response experiments were analyzed, dissimilar in their lead time according to guidelines from the Organisation for Economic Co-operation and Development (OECD), in which each assay contained four replicates at the concentration levels investigated, including control. Observing exposure to the agrochemical, it was identified that the higher the concentration, the greater the odd of mortality. Regarding the estimated lethal concentrations for each experiment, the following values were found, 0.03 g a.i. L-1, for 24hours, 0.04 g a.i. L-1, for 48hoursand 0.06 g a.i. L-1for 72hours, showing that in experiments with longer exposure times there was an increase in LC50. Concluding, the study showed an alternative approach to classical methods for dose-response studies in Scaptotrigona bipunctatabees exposed to the insecticide Fastac Duo.(AU)

Analysis of a dose-response assay in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) using the logistic regression model under the Bayesian approach

This paper shows the results of a dose-response study in Scaptotrigona bipunctatabees, Lepeletier, 1836 (Hymenoptera: Apidae) exposed to the insecticide Fastac Duo. The aim was to evaluate the lethal concentration that causes the death of 50% of bees (LC50) and investigate the odd of mortality after exposure to different concentrations, using the logistic regression model under the Bayesian approach. In this approach, it is possible to incorporate a prior information and gives more accurate inferential results. Three independent dose-response experiments were analyzed, dissimilar in their lead time according to guidelines from the Organisation for Economic Co-operation and Development (OECD), in which each assay contained four replicates at the concentration levels investigated, including control. Observing exposure to the agrochemical, it was identified that the higher the concentration, the greater the odd of mortality. Regarding the estimated lethal concentrations for each experiment, the following values were found, 0.03 g a.i. L-1, for 24hours, 0.04 g a.i. L-1, for 48hoursand 0.06 g a.i. L-1for 72hours, showing that in experiments with longer exposure times there was an increase in LC50. Concluding, the study showed an alternative approach to classical methods for dose-response studies in Scaptotrigona bipunctatabees exposed to the insecticide Fastac Duo.

Examining land surface phenology in the tropical moist forest eco-zone of South America.

Using leaf area index (LAI) data from 1981 to 2014 in the tropical moist forest eco-zone of South America, we extracted start (SOS) and end (EOS) dates of the active growing season in forest and savanna at each pixel. Then, we detected spatiotemporal characteristics of SOS and EOS in the two vegetation types. Moreover, we analyzed relationships between interannual variations of SOS/EOS and climatic factors, and simulated SOS/EOS time series based on preceding mean air temperature and accumulated rainfall. Results show that mean SOS and EOS ranged from 260 to 330 day of year (DOY) and from 150 to 260 DOY across the study region, respectively. From 1981 to 2014, SOS advancement is more extensive than SOS delay, while EOS advancement and delay are similarly extensive. For most pixels of forest and savanna in tropical moist forest eco-zone, preceding rainfall correlates predominantly negatively with SOS but positively with EOS, while the relationship between preceding temperature and phenophases is location-specific. In addition, preceding rainfall is more extensive than preceding temperature in simulating SOS, while both preceding rainfall and temperature play an important role for simulating EOS. This study highlights the reliability of using LAI data for long-term phenological analysis in the tropical moist forest eco-zone.

Statistical modeling alongside observational data predicts long-term immunogenicity of one dose and two doses of pediatric hepatitis A vaccine in the Mendoza province of Argentina.

BACKGROUND: Follow-up for anti-hepatitis A (HA) antibody persistence up to 10 years was conducted after implementation of universal vaccination against HA virus (HAV) in Mendoza, Argentina. Based on these data, statistical modeling was used to predict the antibody persistence to 30 years. METHODS: A non-interventional study evaluated long-term immunogenicity (geometric mean concentrations [GMCs] and seroprotection rate) following routine vaccination with 1 dose (Group 1: N = 436) or 2 doses (Group 2: N = 108) of HA vaccine. Associated statistical modeling based on a Bayesian approach of mixed effects models on log transformed titers evaluated three models (linear, piecewise linear, and exponential decay, with and without a natural boosting effect). RESULTS: From the initial cohort, 9 participants (Group 1) and 1 participant (Group 2) showed antibody titers below the seroprotective threshold and received a booster. At Year 10, 190 (Group 1) and 51 (Group 2) participants remained in the study without a booster dose and all were seroprotected. Regarding statistical modeling, the piecewise linear model showed the best fit and demonstrated high and similar seroprotection for each schedule up to 30 years (89% [1-dose schedule], 85% [2-dose schedule]). The 2-dose schedule showed higher GMC (95% CI) than the 1-dose schedule (Year 10: 352 [271-456] versus 78 [69.8-87.6] mIU/mL) and Year 30 (predicted) (37 [13-97] versus 19 [11-34] mIU/mL). Natural boosting had little impact on predicted seroprotection rates at 30 years for the 1-dose schedule (89% [0.8-0.96] and 84% [0.73-0.94] with and without a natural booster, respectively). CONCLUSIONS: Long-term persistence of anti-HAV antibodies was observed up to 10 years with 1-dose and 2-dose vaccine schedules, supporting booster flexibility. Statistical modeling predicted good persistence of seroprotection for each schedule up to 30 years. Natural boosting had a limited impact on seroprotection rate predictions, enabling extrapolation of these results to non-endemic settings for traveler vaccination.

Toxicity of methylparaben to green microalgae species and derivation of a predicted no effect concentration (PNEC) in freshwater ecosystems.

Methylparaben (MeP) is one of the most used preservatives in the industry; however, the toxic effects on aquatic ecosystems are still poorly understood. Therefore, this study was conducted (1) to identify and compare the toxic effects of MeP on physiological parameters of different green microalgae species, using suitable mathematical models; and (2) to estimate a PNEC value for MeP in freshwater ecosystems, adopting either the deterministic or the probabilistic approaches. Toxicity tests were carried out with three green microalgae (Pseudopediastrum boryanum, Desmodesmus communis, Raphidocelis subcapitata), in which different endpoints such as growth rate, chlorophyll-a, and cell viability were measured and compared through the effective concentration which caused a response in x% of test organisms (ECx). ECx were obtained by adjusting different non-linear regression models for each microalgae dataset. Chlorophyll-a endpoint resulted in the lowest EC50 values, respectively 125, 81.2, 18.3 mg L-1 for D. communis, P. boryanum and R. subcapitata, showing R. subicapitata as the most sensitive, and D. communis as the most tolerant species to MeP (P < 0.05). PNEC was estimated from the present study and previous reports resulting in 5.7 and 65 µg L-1, respectively for the deterministic (PNECd) and the probabilistic (PNECp) approach. The development of chronic assays using test organisms from different ecological groups is encouraged to provide robust PNECp. In this meantime, we recommend the use of the estimated PNECd to support MeP risk assessments and policy formulation.

Predictors of Episodic Memory Performance Across Educational Strata: Multiple-Group Comparisons.

OBJECTIVES: Low educational attainment is a risk factor for more rapid cognitive aging, but there is substantial variability in cognitive trajectories within educational groups. The aim of this study was to determine the factors that confer resilience to memory decline within educational strata. METHODS: We selected 2573 initially nondemented White, African American, and Hispanic participants from the longitudinal community-based Washington Heights/Inwood Columbia Aging Project who had at least two visits. We estimated initial memory (intercept) and the rate of memory decline (slope) using up to five occasions of measurement. We classified groups according to the educational attainment groups as low (≤5 years), medium (6-11 years), and high (≥12 years). We used a multiple-group latent growth model to identify the baseline predictors of initial memory performance and rate of memory decline across groups. The model specification considered the influence of demographic, socioeconomic, biomedical, and cognitive variables on the intercept and the slope of memory trajectory. RESULTS: Our results indicated that the three educational groups do not benefit from the same factors. When allowed to differ across groups, the predictors were related to cognitive outcomes in the highly educated group, but we found no unique predictor of cognition for the low educated older adults. CONCLUSIONS: These findings highlight that memory-protective factors may differ across older adults with distinct educational backgrounds, and the need to evaluate a broader range of potential resilience factors for older adults with few years of school.

Survival Probability in Patients with Sickle Cell Anemia Using the Competitive Risk Statistical Model.

The clinical picture of patients with sickle cell anemia (SCA) is associated with several complications some of which could be fatal. The objective of this study is to analyze the causes of death and the effect of sex and age on survival of Brazilian patients with SCA. Data of patients with SCA who were seen and followed at HEMORIO for 15 years were retrospectively collected and analyzed. Statistical modeling was performed using survival analysis in the presence of competing risks estimating the covariate effects on a sub-distribution hazard function. Eight models were implemented, one for each cause of death. The cause-specific cumulative incidence function was also estimated. Males were most vulnerable for death from chronic organ damage (p = 0.0005) while females were most vulnerable for infection (p=0.03). Age was significantly associated (p ≤ 0.05) with death due to acute chest syndrome (ACS), infection, and death during crisis. The lower survival was related to death from infection, followed by death due to ACS. The independent variables age and sex were significantly associated with ACS, infection, chronic organ damage and death during crisis. These data could help Brazilian authorities strengthen public policies to protect this vulnerable population.

Passive acoustic monitoring of the decline of Mexico's critically endangered vaquita.

The vaquita (Phocoena sinus) is the world's most endangered marine mammal with approximately 245 individuals remaining in 2008. This species of porpoise is endemic to the northern Gulf of California, Mexico, and historically the population has declined because of unsustainable bycatch in gillnets. An illegal gillnet fishery for an endangered fish, the totoaba (Totoaba macdonaldi), has recently resurged throughout the vaquita's range. The secretive but lucrative wildlife trade with China for totoaba swim bladders has probably increased vaquita bycatch mortality by an unknown amount. Precise population monitoring by visual surveys is difficult because vaquitas are inherently hard to see and have now become so rare that sighting rates are very low. However, their echolocation clicks can be identified readily on specialized acoustic detectors. Acoustic detections on an array of 46 moored detectors indicated vaquita acoustic activity declined by 80% between 2011 and 2015 in the central part of the species' range. Statistical models estimated an annual rate of decline of 34% (95% Bayesian credible interval -48% to -21%). Based on results from 2011 to 2014, the government of Mexico enacted and is enforcing an emergency 2-year ban on gillnets throughout the species' range to prevent extinction, at a cost of US$74 million to compensate fishers. Developing precise acoustic monitoring methods proved critical to exposing the severity of vaquitas' decline and emphasizes the need for continual monitoring to effectively manage critically endangered species.

Análise dos fatores associados aos acidentes de trânsito envolvendo ciclistas atendidos nas capitais brasileiras / Analysis of factors associated with traffic accidents of cyclists attended in Brazilian state capitals

Resumo O Brasil possui a sexta maior frota de bicicletas do mundo, sendo esta o veículo de transporte individual mais utilizado no país. Porém, poucos estudos abordam a temática envolvendo os acidentes com ciclistas, bem como os fatores que colaboram ou evitam essa ocorrência. Utilizou-se amostragem complexa e posterior análise de dados por regressão logística multivariada e cálculo das respectivas razões de chance para estudar o Inquérito de delineamento transversal (VIVA), o qual compõe o Sistema de Vigilância de Violências e Acidentes do Ministério da Saúde. As razões de chance apontaram maiores chances de ocorrência de acidentes envolvendo ciclistas em indivíduos do sexo masculino, de menor escolaridade e que residem em área urbana e periurbana. Pessoas que não estavam utilizando a bicicleta para ir ao trabalho apresentaram maior chance de acidente. O perfil encontrado no presente estudo corrobora os achados de outros estudos, os quais consideram que a coexistência de ciclistas com os demais meios de transporte, no mesmo espaço urbano, acarreta em maior chance de acidentes. A construção de espaços exclusivos à circulação de bicicletas e a realização de campanhas educativas são preconizadas.

Abstract Introduction: Brazil has the sixth largest bicycles fleet in the world and bicycle is the most used individual transport vehicle in the country. Few studies address the issue of cyclists' accidents and factors that contribute to or prevent this event. Methodology: VIVA is a cross-sectional survey and is part of the Violence and Accidents Surveillance System, Brazilian Ministry of Health. We used complex sampling and subsequent data review through multivariate logistic regression and calculation of the respective odds ratios. Results: Odds ratios showed greater likelihood of cyclists' accidents in males, people with less schooling and living in urban and periurban areas. People who were not using the bike to go to work were more likely to suffer an accident. Discussion: The profile found in this study corroborates findings of other studies. They claim that the coexistence of cyclists and other means of transportation in the same urban space increases the likelihood of accidents. Conclusion: The construction of bicycle-exclusive spaces and educational campaigns are required.

Data driven performance evaluation of Wireless Sensor Networks.

Wireless Sensor Networks are presented as devices for signal sampling and reconstruction. Within this framework, the qualitative and quantitative influence of (i) signal granularity, (ii) spatial distribution of sensors, (iii) sensors clustering, and (iv) signal reconstruction procedure are assessed. This is done by defining an error metric and performing a Monte Carlo experiment. It is shown that all these factors have significant impact on the quality of the reconstructed signal. The extent of such impact is quantitatively assessed.