COMPARISON BETWEEN LINEAR AND DAILY UNDULATING PERIODIZED RESISTANCE TRAINING TO INCREASE STRENGTH

Prestes, J, Frollini, AB, De Lima, C, Donatto, FF, Foschini, D, de Marqueti, RC, Figueira Jr, A, and Fleck, SJ. Comparison between linear and daily undulating periodized resistance training to increase strength. J Strength Cond Res 23(9): 2437-2442, 2009-To determine the most effective periodization model for strength and hypertrophy is an important step for strength and conditioning professionals. The aim of this study was to compare the effects of linear (LP) and daily undulating periodized (DUP) resistance training on body composition and maximal strength levels. Forty men aged 21.5 +/- 8.3 and with a minimum 1-year strength training experience were assigned to an LP (n = 20) or DUP group (n = 20). Subjects were tested for maximal strength in bench press, leg press 45 degrees, and arm curl (1 repetition maximum [RM]) at baseline (T1), after 8 weeks (T2), and after 12 weeks of training (T3). Increases of 18.2 and 25.08% in bench press 1 RM were observed for LP and DUP groups in T3 compared with T1, respectively (p <= 0.05). In leg press 45 degrees, LP group exhibited an increase of 24.71% and DUP of 40.61% at T3 compared with T1. Additionally, DUP showed an increase of 12.23% at T2 compared with T1 and 25.48% at T3 compared with T2. For the arm curl exercise, LP group increased 14.15% and DUP 23.53% at T3 when compared with T1. An increase of 20% was also found at T2 when compared with T1, for DUP. Although the DUP group increased strength the most in all exercises, no statistical differences were found between groups. In conclusion, undulating periodized strength training induced higher increases in maximal strength than the linear model in strength-trained men. For maximizing strength increases, daily intensity and volume variations were more effective than weekly variations.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.

Effect of repeated torque/mechanical loading cycles on two different abutment types in implants with internal tapered connections: an in vitro study

Internal tapered connections were developed to improve biomechanical properties and to reduce mechanical problems found in other implant connection systems. The purpose of this study was to evaluate the effects of mechanical loading and repeated insertion/removal cycles on the torque loss of abutments with internal tapered connections. Sixty-eight conical implants and 68 abutments of two types were used. They were divided into four groups: groups 1 and 3 received solid abutments, and groups 2 and 4 received two-piece abutments. In groups 1 and 2, abutments were simply installed and uninstalled; torque-in and torque-out values were measured. In groups 3 and 4, abutments were installed, mechanically loaded and uninstalled; torque-in and torque-out values were measured. Under mechanical loading, two-piece abutments were frictionally locked into the implant; thus, data of group 4 were catalogued under two subgroups (4a: torque-out value necessary to loosen the fixation screw; 4b: torque-out value necessary to remove the abutment from the implant). Ten insertion/removal cycles were performed for every implant/abutment assembly. Data were analyzed with a mixed linear model (P <= 0.05). Torque loss was higher in groups 4a and 2 (over 30% loss), followed by group 1 (10.5% loss), group 3 (5.4% loss) and group 4b (39% torque gain). All the results were significantly different. As the number of insertion/removal cycles increased, removal torques tended to be lower. It was concluded that mechanical loading increased removal torque of loaded abutments in comparison with unloaded abutments, and removal torque values tended to decrease as the number of insertion/removal cycles increased. To cite this article:Ricciardi Coppede A, de Mattos MdaGC, Rodrigues RCS, Ribeiro RF. Effect of repeated torque/mechanical loading cycles on two different abutment types in implants with internal tapered connections: an in vitro study.Clin. Oral Impl. Res. 20, 2009; 624-632.doi: 10.1111/j.1600-0501.2008.01690.x.

Study of some physical properties of biodegradable films based on blends of gelatin and poly(vinyl alcohol) using a response-surface methodology

The aim of this work was to study the effect of the hydrolysis degree (HD) and the concentration (C(PVA)) Of two types of poly(vinyl alcohol) (PVA) and of the type (glycerol and sorbitol) and the concentration (C(P)) of plasticizers on some physical properties of biodegradable films based on blends of gelatin and PVA Using a response-surface methodology. The films were prepared with a film forming solutions (FFS) with 2 g of macromolecules (gelatin+PVA)/100 g de FFS. The responses analyzed were the mechanical properties, the solubility, the moisture Content. the color difference and the opacity. The linear model was statistically significant and predictive for puncture force and deformation. elongation at break, solubility in water, Moisture content and opacity. The CPVA affected strongly the elongation at break of the films. The interaction of the HD and the C(P) affected this property. Moreover. the puncture force was affected slightly by the C(PVA). Concerning the Solubility in water, the reduction of the HD increased it and this effect was greater for high CPVA Values. In general. the most important effect observed in the physical properties of the films was that of the plasticizer type and concentration. The PVA hydrolysis degree and concentration have an important effect only for the elongation at break, puncture deformation and solubility in water. (C) 2008 Elsevier B.V. All rights reserved.

Fluctuating abundance of humpback whales (Megaptera novaeangliae) in a calving ground off coastal Brazil

The humpback whale (Megaptera novaeangliae) population that uses Abrolhos Bank, off the east coast of Brazil as a breeding ground is increasing. To describe temporal changes in the relative abundance of humpback whales around Abrolhos, seven years (1998-2004) of whale count data were collected during July through to November. During one-hour-scans, observers determined group size within 9.3 km (5 n.m.) of a land-based observing station. A total Of 930 scans, comprising 7996 sightings of adults and 2044 calves were analysed using generalized linear models that included variables for time of day, day of the season, years and two-way interactions as possible predictors. The pattern observed was the gradual build-up and decline in whale counts within seasons. Patterns and peaks of adult and calf counts varied among years. Although fluctuation was observed, there was generally an increasing trend in adult counts among years. Calf counts increased only in 2004. These fluctuations may have been caused by some environmental conditions in humpback whales` summering grounds and also by changes in spatial-temporal concentrations in Abrolhos Bank. The general pattern observed within the study area mirrored what was observed in the whole Abrolhos Bank. Knowledge of the consistency with which humpback whales use this important nursing area should prove beneficial for designing future monitoring programmes especially related to whale watching activities around Abrolhos Archipelago.

The constrained compartmentalized knapsack problem: mathematical models and solution methods

The constrained compartmentalized knapsack problem can be seen as an extension of the constrained knapsack problem. However, the items are grouped into different classes so that the overall knapsack has to be divided into compartments, and each compartment is loaded with items from the same class. Moreover, building a compartment incurs a fixed cost and a fixed loss of the capacity in the original knapsack, and the compartments are lower and upper bounded. The objective is to maximize the total value of the items loaded in the overall knapsack minus the cost of the compartments. This problem has been formulated as an integer non-linear program, and in this paper, we reformulate the non-linear model as an integer linear master problem with a large number of variables. Some heuristics based on the solution of the restricted master problem are investigated. A new and more compact integer linear model is also presented, which can be solved by a branch-and-bound commercial solver that found most of the optimal solutions for the constrained compartmentalized knapsack problem. On the other hand, heuristics provide good solutions with low computational effort. (C) 2011 Elsevier BM. All rights reserved.

Job rotation in assembly lines employing disabled workers

In this paper we consider the programming of job rotation in the assembly line worker assignment and balancing problem. The motivation for this study comes from the designing of assembly lines in sheltered work centers for the disabled, where workers have different task execution times. In this context, the well-known training aspects associated with job rotation are particularly desired. We propose a metric along with a mixed integer linear model and a heuristic decomposition method to solve this new job rotation problem. Computational results show the efficacy of the proposed heuristics. (C) 2009 Elsevier B.V. All rights reserved.

Transformed symmetric models

For the first time, we introduce a class of transformed symmetric models to extend the Box and Cox models to more general symmetric models. The new class of models includes all symmetric continuous distributions with a possible non-linear structure for the mean and enables the fitting of a wide range of models to several data types. The proposed methods offer more flexible alternatives to Box-Cox or other existing procedures. We derive a very simple iterative process for fitting these models by maximum likelihood, whereas a direct unconditional maximization would be more difficult. We give simple formulae to estimate the parameter that indexes the transformation of the response variable and the moments of the original dependent variable which generalize previous published results. We discuss inference on the model parameters. The usefulness of the new class of models is illustrated in one application to a real dataset.

Cutpoint selection for discretizing a continuous covariate for generalized estimating equations

We consider consider the problem of dichotomizing a continuous covariate when performing a regression analysis based on a generalized estimation approach. The problem involves estimation of the cutpoint for the covariate and testing the hypothesis that the binary covariate constructed from the continuous covariate has a significant impact on the outcome. Due to the multiple testing used to find the optimal cutpoint, we need to make an adjustment to the usual significance test to preserve the type-I error rates. We illustrate the techniques on one data set of patients given unrelated hematopoietic stem cell transplantation. Here the question is whether the CD34 cell dose given to patient affects the outcome of the transplant and what is the smallest cell dose which is needed for good outcomes. (C) 2010 Elsevier BM. All rights reserved.

Asymptotic Skewness in Exponential Family Nonlinear Models

In this article, we give an asymptotic formula of order n(-1/2), where n is the sample size, for the skewness of the distributions of the maximum likelihood estimates of the parameters in exponencial family nonlinear models. We generalize the result by Cordeiro and Cordeiro ( 2001). The formula is given in matrix notation and is very suitable for computer implementation and to obtain closed form expressions for a great variety of models. Some special cases and two applications are discussed.

Birnbaum-Saunders nonlinear regression models

We introduce, for the first time, a new class of Birnbaum-Saunders nonlinear regression models potentially useful in lifetime data analysis. The class generalizes the regression model described by Rieck and Nedelman [Rieck, J.R., Nedelman, J.R., 1991. A log-linear model for the Birnbaum-Saunders distribution. Technometrics 33, 51-60]. We discuss maximum-likelihood estimation for the parameters of the model, and derive closed-form expressions for the second-order biases of these estimates. Our formulae are easily computed as ordinary linear regressions and are then used to define bias corrected maximum-likelihood estimates. Some simulation results show that the bias correction scheme yields nearly unbiased estimates without increasing the mean squared errors. Two empirical applications are analysed and discussed. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

A linear optimization approach to the combined production planning model

Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Effects of Synthesis Conditions on the Nanostructure of Hybrid Sols Produced by the Hydrolytic Condensation of (3-Methacryloxypropyl)trimethoxysilane

Polysilsesquioxanes containing methacrylate pendant groups were prepared by the sol-gel process through hydrolysis and condensation of (3-methacryloxypropyl)trimethoxysilane (MPTS) dissolved in a methanol/methyl methacrylate (MMA) mixture. The effects of different water, MMA, and methanol contents, as well as of pH, on the nanoscopic and local structures of the system, at advanced stages of the condensation reaction, were studied by small-angle X-ray scattering (SAXS) and (29)Si nuclear magnetic resonance (NMR) spectroscopy, respectively. SAXS results indicate that the nanoscopic features of the hybrid sol could be described by a hierarchical model composed of two levels, namely (i) silsesquioxane (SSQO) nanoparticles Surrounded by the methacrylate pendant groups and the methanol/MMA mixture. and (ii) aggregation zones or islands containing correlated SSQO nanoparticles, embedded in the liquid medium. The (29)Si NMR results Show that the inner Structures of SSQO nanoparticles produced at pH 1 and 3 were built Up of polyhedral structures. mainly cagelike octamers and small linear oligomers, respectively. Irrespective of MMA and methanol contents, for a [H(2)O]/[MPTS] ratio higher than or equal to 1, the SSQO nailoparticles produced at pH I exhibit an average condensation degree (CD approximate to 69-87%) and average radius of gyration (R(g) approximate to 2.5 angstrom) larger than those produced at pH 3 (CD approximate to 48-67% and R(g) approximate to 1.5 angstrom). Methanol appears to act as a redispersion agent, by decreasing the number of particles inside the aggregation zones, while the addition of MMA induces a swelling of the aggregation zones.