THE MAPPING IN THE CONTINUING EDUCATION OF TEACHERS: AN EXPERIENCE THROUGH DISTANCE LEARNING

In this work, we show the experience of continuing teacher education in Cartography in the period from 03/11/2009 to 03/11/2010, it was held by the Center for Continuing Education in Mathematics Education, Science and Environment (CECEMCA) - UNESP - Rio Claro, in DL (Distance Learning). This experience was through the extension course set in TelEduc platform. The course was titled Introduction to Cartography and aimed primarily: Present concepts of systematic and thematic mapping and its potential application in teaching practices, increase knowledge in the areas of Geography, Cartography and Environment; Offer alternatives for implementing content mapping in the classroom.

Patch size, shape and edge distance influences seed predation in a keystone palm in tropical rainforests

Pós-graduação em Ciências Biológicas (Zoologia) - IBRC

Online distance mathematics education in Brazil: research, practice and policy

In this article, we address online distance mathematics education research and practice in Brazil, which are relative newcomers to the educational scene. We present the national context of education in Brazil, highlighting the organization of the educational system, and also a summary of national legislation on distance education and an overview of digital inclusion in the country. We outline the potential and relevance of distance education for the Brazilian educational system and show how it could intervene in the system. With respect to research and practice in online mathematics education, we present support for research, examples of studies and highlight different aspects being addressed, including its essential components. In addition, we discuss the synergy between distance education and teacher education, and mathematics distance education and modeling, as well as other initiatives in the national scenario.

Distance exercised during submaximal training on race winnings for Thoroughbred racehorses

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

The effect of gastrointestinal nematode infection level on grazing distance from dung

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.

Short distance QCD contribution to the electroweak mass difference of pions

It is known that the short distance QCD contribution to the mass difference of pions is quadratic on the quark masses, and irrelevant with respect to the long distance part. It is also considered in the literature that its calculation contains infinities, which should be absorbed by the quark mass renormalization. Following a prescription by Craigie, Narison, and Riazuddin of a renormalization-group-improved perturbation theory to deal with the electromagnetic mass shift problem in QCD, we show that the short distance QCD contribution to the electroweak pion mass difference (with mu=md≠0) is finite and, of course, its value is negligible compared to other contributions.

Soybean yield in relation to distance from the Itaipu reservoir

Crops close to small water bodies may exhibit changes in yield if the water mass causes significant changes in the microclimate of areas near the reservoir shoreline. The scientific literature describes this effect as occurring gradually, with higher intensity in the sites near the shoreline and decreasing intensity with distance from the reservoir. Experiments with two soybean cultivars were conducted during four crop seasons to evaluate soybean yield in relation to distance from the Itaipu reservoir and determine the effect of air temperature and water availability on soybean crop yield. Fifteen experimental sites were distributed in three transects perpendicular to the Itaipu reservoir, covering an area at approximately 10 km from the shoreline. The yield gradient between the site closest to the reservoir and the sites farther away in each transect did not show a consistent trend, but varied as a function of distance, crop season, and cultivar. This finding indicates that the Itaipu reservoir does not affect the yield of soybean plants grown within approximately 10 km from the shoreline. In addition, the variation in yield among the experimental sites was not attributed to thermal conditions because the temperature was similar within transects. However, the crop water availability was responsible for higher differences in yield among the neighboring experimental sites related to water stress caused by spatial variability in rainfall, especially during the soybean reproductive period in January and February.

A recepção de Machado de Assis por jovens leitores do século XXI

Pós-graduação em Letras - FCLAS

Repeated sprint ability tests and intensity-time curvature constant to predict short-distance running performances

Anaerobic efforts are commonly required through repeated sprint during efforts in many sports, making the anaerobic pathway a target of training. Nevertheless, to identify improvements on such energetic way it is necessary to assess anaerobic capacity or power, which is usually complex. For this purpose, authors have postulated the use of short running performances to anaerobic ability assessment. Thus, the aim of this study was to find a relationship between running performances on anaerobic power, anaerobic capacity or repeated sprint ability. Methods Thirteen military performed maximal running of 50 (P50), 100 (P100) and 300 (P300) m on track, beyond of running-based anaerobic sprint test (RAST; RSA and anaerobic power test), maximal anaerobic running test (MART; RSA and anaerobic capacity test) and the W′ from critical power model (anaerobic capacity test). Results By RAST variables, peak and average power (absolute and relative) and maximum velocity were significantly correlated with P50 (r = −0.68, p = 0.03 and −0.76, p = 0.01; −0.83, p < 0.01 and −0.83, p < 0.01; and −0.78, p < 0.01), respectively. The maximum intensity of MART was negatively and significantly correlated with P100 (r = −0.59) and W′ was not statistically correlated with any of the performances. Conclusion MART and W′ were not correlated with short running performances, having a weak performance predicting probably due to its longer duration in relation to assessed performances. Observing RAST outcomes, we postulated that such a protocol can be used during daily training as short running performance predictor.

Is Drosera meristocaulis a pygmy sundew? evidence of a long-distance dispersal between Western Australia and northern South America

Background and aims South America and Oceania possess numerous floristic similarities, often confirmed by morphological and molecular data. The carnivorous Drosera meristocaulis (Droseraceae), endemic to the Neblina highlands of northern South America, was known to share morphological characters with the pygmy sundews of Drosera sect. Bryastrum, which are endemic to Australia and New Zealand. The inclusion of D. meristocaulis in a molecular phylogenetic analysis may clarify its systematic position and offer an opportunity to investigate character evolution in Droseraceae and phylogeographic patterns between South America and Oceania. Methods Drosera meristocaulis was included in a molecular phylogenetic analysis of Droseraceae, using nuclear internal transcribed spacer (ITS) and plastid rbcL and rps16 sequence data. Pollen of D. meristocaulis was studied using light microscopy and scanning electron microscopy techniques, and the karyotype was inferred from root tip meristem. Key Results The phylogenetic inferences (maximum parsimony, maximum likelihood and Bayesian approaches) substantiate with high statistical support the inclusion of sect. Meristocaulis and its single species, D. meristocaulis, within the Australian Drosera clade, sister to a group comprising species of sect. Bryastrum. A chromosome number of 2n = approx. 32–36 supports the phylogenetic position within the Australian clade. The undivided styles, conspicuous large setuous stipules, a cryptocotylar (hypogaeous) germination pattern and pollen tetrads with aperture of intermediate type 7–8 are key morphological traits shared between D. meristocaulis and pygmy sundews of sect. Bryastrum from Australia and New Zealand. Conclusions The multidisciplinary approach adopted in this study (using morphological, palynological, cytotaxonomic and molecular phylogenetic data) enabled us to elucidate the relationships of the thus far unplaced taxon D. meristocaulis. Long-distance dispersal between southwestern Oceania and northern South America is the most likely scenario to explain the phylogeographic pattern revealed.

Availability and Use of Audiovisual and Electronic Resources by Distance Learning Students in Nigerian Universities: a Case Study of National Open University of Nigeria (NOUN), Ibadan Study Centre

This study investigated the availability and use of audiovisual and electronic resources by distance learning students at the National Open University of Nigeria (NOUN). A questionnaire was administered tothe distance learning students selected across the various departments of the NOUN. The findings revealed that even though NOUN made provision for audiovisual and electronic resources for students' use, a majority of the audiovisual and electronic resources are available through personal provision by the students.The study also revealed regular use of audiovisual and electronic resources by the distance learning students. Constraints on use include poor power supply, poor infrastructure, lack of adequate skill, and high cost of access.

Spatial statistical models that use flow and stream distance

We develop spatial statistical models for stream networks that can estimate relationships between a response variable and other covariates, make predictions at unsampled locations, and predict an average or total for a stream or a stream segment. There have been very few attempts to develop valid spatial covariance models that incorporate flow, stream distance, or both. The application of typical spatial autocovariance functions based on Euclidean distance, such as the spherical covariance model, are not valid when using stream distance. In this paper we develop a large class of valid models that incorporate flow and stream distance by using spatial moving averages. These methods integrate a moving average function, or kernel, against a white noise process. By running the moving average function upstream from a location, we develop models that use flow, and by construction they are valid models based on stream distance. We show that with proper weighting, many of the usual spatial models based on Euclidean distance have a counterpart for stream networks. Using sulfate concentrations from an example data set, the Maryland Biological Stream Survey (MBSS), we show that models using flow may be more appropriate than models that only use stream distance. For the MBSS data set, we use restricted maximum likelihood to fit a valid covariance matrix that uses flow and stream distance, and then we use this covariance matrix to estimate fixed effects and make kriging and block kriging predictions.

Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.