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.

DNA Barcoding em Utricularia (Lentibulariaceae)

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Discrimination of production environments of specialty coffees by means of stable isotopes and discriminant model

The south of Minas Gerais, Brazil stands out among various regions through its capacity for production of specialty coffees. Its potential, manifested through being one of the most award-winning Brazilian regions in recent years, has been recognized by the Cup of Excellence (COE). With the evident relationship between product quality and the environment in mind, the need arises for scientific studies to provide a foundation for discrimination of product origin, creating new methods for combating possible fraud. The aim of this study was to evaluate the use of carbon and nitrogen isotopes in discrimination of production environments of specialty coffees from the Serra da Mantiqueira of Minas Gerais by means of the discriminant model. Coffee samples were composed of ripe yellow and red fruits collected manually at altitudes below 1,000 m, from 1,000 to 1,200 m and above 1,200 m. The yellow and red fruits were subjected to dry processing and wet processing, with five replications. A total of 119 samples were used for discrimination of specialty coffee production environments by means of stable isotopes and statistical modeling. The model generated had an accuracy rate of 89% in discrimination of environments and was composed of the isotope variables of δ15N, δ13C, %C, %N, δD, δ18O (meteoric water) and sensory analysis scores. In addition, for the first time, discrimination of environments on a local geographic scale, within a single municipality, was proposed and successfully concluded. This shows that isotope analysis is an effective method in verifying geographic origin for specialty coffees.

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.

Chromatic discrimination losses in multiple sclerosis patients with and without optic neuritis using the Cambridge Colour Test

We assessed chromatic discrimination in multiple sclerosis (MS) patients both with (ON) and without (no ON) a history of optic neuritis using the Cambridge color test (CCT). Our goal was to determine the magnitude and chromatic axes of any color vision losses in both patient groups, and to evaluate age-related changes in chromatic discrimination in both patient groups compared to normals. Using the CCT, we measured chromatic discrimination along the protan, deutan and tritan axes in 35 patients with MS (17 ON eyes) and 74 age matched controls. Color thresholds for both patient groups were significantly higher than controls` along the protan and tritan axes (P < 0.001). In addition, the ON and no-ON groups differed significantly along all three-color axes (p < 0.001). MS patients presented a progressive color discrimination impairment with age (along the deutan and tritan axes) that was almost two times faster than controls, even in the absence of ON. These findings suggest that demyelinating diseases reduce sensitivity to color vision in both red-green and blue-yellow axes, implying impairment in both parvocellular and koniocellular visual pathways. The CCT is a useful tool to help characterize vision losses in MS and the relationship between these losses and degree of optic nerve involvement.

Hausdorff Distance evaluation of orthodontic accessories' streaking artifacts in 3D model superimposition

The aim of this study was to determine whether image artifacts caused by orthodontic metal accessories interfere with the accuracy of 3D CBCT model superimposition. A human dry skull was subjected three times to a CBCT scan: at first without orthodontic brackets (T1), then with stainless steel brackets bonded without (T2) and with orthodontic arch wires (T3) inserted into the brackets' slots. The registration of image surfaces and the superimposition of 3D models were performed. Within-subject surface distances between T1-T2, T1-T3 and T2-T3 were computed and calculated for comparison among the three data sets. The minimum and maximum Hausdorff Distance units (HDu) computed between the corresponding data points of the T1 and T2 CBCT 3D surface images were 0.000000 and 0.049280 HDu, respectively, and the mean distance was 0.002497 HDu. The minimum and maximum Hausdorff Distances between T1 and T3 were 0.000000 and 0.047440 HDu, respectively, with a mean distance of 0.002585 HDu. In the comparison between T2 and T3, the minimum, maximum and mean Hausdorff Distances were 0.000000, 0.025616 and 0.000347 HDu, respectively. In the current study, the image artifacts caused by metal orthodontic accessories did not compromise the accuracy of the 3D model superimposition. Color-coded maps of overlaid structures complemented the computed Hausdorff Distances and demonstrated a precise fusion between the data sets.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners

Bertuzzi, R, Bueno, S, Pasqua, LA, Acquesta, FM, Batista, MB, Roschel, H, Kiss, MAPDM, Serrao, JC, Tricoli, V, and Ugrinowitsch, C. Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners. J Strength Cond Res 26(8): 2096-2102, 2012-The purpose of this study was to investigate the main bioenergetics and neuromuscular determinants of the time to exhaustion (T-lim) at the velocity corresponding to maximal oxygen uptake in recreational long-distance runners. Twenty runners performed the following tests on 5 different days: (a) maximal incremental treadmill test, (b) 2 submaximal tests to determine running economy and vertical stiffness, (c) exhaustive test to measured the T-lim, (d) maximum dynamic strength test, and (e) muscle power production test. Aerobic and anaerobic energy contributions during the T-lim test were also estimated. The stepwise multiple regression method selected 3 independent variables to explain T-lim variance. Total energy production explained 84.1% of the shared variance (p = 0.001), whereas peak oxygen uptake ((V) over dotO(2)peak) measured during T-lim and lower limb muscle power ability accounted for the additional 10% of the shared variance (p = 0.014). These data suggest that the total energy production, (V) over dotO(2)peak, and lower limb muscle power ability are the main physiological and neuromuscular determinants of T-lim in recreational long-distance runners.

Effect of surface area and air-drying distance on shear bond strength of etch-and-rinse adhesive

We evaluated the effects of air-drying distance and bond surface area on the shear bond strength of a 2-step etch-and-rinse adhesive. A total of 120 bovine anterior teeth were equally divided into 6 main groups based on bonding surface area. The main groups were divided into sub-groups (n = 5) according to air-drying distance. The shear strength was determined using a universal testing machine at a crosshead speed of 0.5 mm/min. The averaged results were subjected to two-way ANOVA and Tukey's test (alpha = 0.05). Two-way ANOVA testing identified no significant cross-product interactions (p > 0.05), but the main factors of area (p < 0.0001) and air-drying distance (p < 0.00001) significantly affected the mean bond strength. Shorter air-drying distances improved bond strength, and increased surface area decreased the bond strength.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

MRKAd5 HIV-1 Gag/Pol/Nef Vaccine-Induced T-Cell Responses Inadequately Predict Distance of Breakthrough HIV-1 Sequences to the Vaccine or Viral Load

Background: The sieve analysis for the Step trial found evidence that breakthrough HIV-1 sequences for MRKAd5/HIV-1 Gag/Pol/Nef vaccine recipients were more divergent from the vaccine insert than placebo sequences in regions with predicted epitopes. We linked the viral sequence data with immune response and acute viral load data to explore mechanisms for and consequences of the observed sieve effect. Methods: Ninety-one male participants (37 placebo and 54 vaccine recipients) were included; viral sequences were obtained at the time of HIV-1 diagnosis. T-cell responses were measured 4 weeks post-second vaccination and at the first or second week post-diagnosis. Acute viral load was obtained at RNA-positive and antibody-negative visits. Findings: Vaccine recipients had a greater magnitude of post-infection CD8+ T cell response than placebo recipients (median 1.68% vs 1.18%; p = 0.04) and greater breadth of post-infection response (median 4.5 vs 2; p = 0.06). Viral sequences for vaccine recipients were marginally more divergent from the insert than placebo sequences in regions of Nef targeted by pre-infection immune responses (p = 0.04; Pol p = 0.13; Gag p = 0.89). Magnitude and breadth of pre-infection responses did not correlate with distance of the viral sequence to the insert (p. 0.50). Acute log viral load trended lower in vaccine versus placebo recipients (estimated mean 4.7 vs 5.1) but the difference was not significant (p = 0.27). Neither was acute viral load associated with distance of the viral sequence to the insert (p>0.30). Interpretation: Despite evidence of anamnestic responses, the sieve effect was not well explained by available measures of T-cell immunogenicity. Sequence divergence from the vaccine was not significantly associated with acute viral load. While point estimates suggested weak vaccine suppression of viral load, the result was not significant and more viral load data would be needed to detect suppression.