The Modified Card Sorting Test: Test-retest stability and relationships with demographic variables in a healthy older adult sample

Objectives. To investigate the test-retest stability of a standardized version of Nelson's (1976) Modified Card Sorting Test (MCST) and its relationships with demographic variables in a sample of healthy older adults. Design. A standard card order and administration were devised for the MCST and administered to participants at an initial assessment, and again at a second session conducted a minimum of six months later in order to examine its test-retest stability. Participants were also administered the WAIS-R at initial assessment in order to provide a measure of psychometric intelligence. Methods. Thirty-six (24 female, 12 male) healthy older adults aged 52 to 77 years with mean education 12.42 years (SD = 3.53) completed the MCST on two occasions approximately 7.5 months (SD = 1.61) apart. Stability coefficients and test-retest differences were calculated for the range of scores. The effect of gender on MCST performance was examined. Correlations between MCST scores and age, education and WAIS-R IQs were also determined. Results. Stability coefficients ranged from .26 for the percent perseverative errors measure to .49 for the failure to maintain set measure. Several measures were significantly correlated with age, education and WAIS-R IQs, although no effect of gender on MCST performance was found. Conclusions. None of the stability coefficients reached the level required for clinical decision making. The results indicate that participants' age, education, and intelligence need to be considered when interpreting MCST performance. Normative studies of MCST performance as well as further studies with patients with executive dysfunction are needed.

Approach to designing rotating drum bioreactors for solid-state fermentation on the basis of dimensionless design factors

The development of large-scale solid-stale fermentation (SSF) processes is hampered by the lack of simple tools for the design of SSF bioreactors. The use of semifundamental mathematical models to design and operate SSF bioreactors can be complex. In this work, dimensionless design factors are used to predict the effects of scale and of operational variables on the performance of rotating drum bioreactors. The dimensionless design factor (DDF) is a ratio of the rate of heat generation to the rate of heat removal at the time of peak heat production. It can be used to predict maximum temperatures reached within the substrate bed for given operational variables. Alternatively, given the maximum temperature that can be tolerated during the fermentation, it can be used to explore the combinations of operating variables that prevent that temperature from being exceeded. Comparison of the predictions of the DDF approach with literature data for operation of rotating drums suggests that the DDF is a useful tool. The DDF approach was used to explore the consequences of three scale-up strategies on the required air flow rates and maximum temperatures achieved in the substrate bed as the bioreactor size was increased on the basis of geometric similarity. The first of these strategies was to maintain the superficial flow rate of the process air through the drum constant. The second was to maintain the ratio of volumes of air per volume of bioreactor constant. The third strategy was to adjust the air flow rate with increase in scale in such a manner as to maintain constant the maximum temperature attained in the substrate bed during the fermentation. (C) 2000 John Wiley & Sons, Inc.

The design of planar gradient coils. Part I: A winding path correction method

In this work a new approach for designing planar gradient coils is outlined for the use in an existing MRI apparatus. A technique that allows for gradient field corrections inside the diameter-sensitive volume is deliberated. These corrections are brought about by making changes to the wire paths that constitute the coil windings, and hence, is called the path correction method. The existing well-known target held method is used to gauge the performance of a typical gradient coil. The gradient coil design methodology is demonstrated for planar openable gradient coils that can be inserted into an existing MRI apparatus. The path corrected gradient coil is compared to the coil obtained using the target field method. It is shown that using a wire path correction with optimized variables, winding patterns that can deliver high magnetic gradient field strengths and large imaging regions can be obtained.

Impact of pressure profile and duration of recruitment maneuvers on morphofunctional and biochemical variables in experimental lung injury

Objective: To investigate the effects of the rate of airway pressure increase and duration of recruitment maneuvers on lung function and activation of inflammation, fibrogenesis, and apoptosis in experimental acute lung injury. Design: Prospective, randomized, controlled experimental study. Setting: University research laboratory. Subjects: Thirty-five Wistar rats submitted to acute lung injury induced by cecal ligation and puncture. Interventions: After 48 hrs, animals were randomly distributed into five groups (seven animals each): 1) nonrecruited (NR); 2) recruitment maneuvers (RMs) with continuous positive airway pressure (CPAP) for 15 secs (CPAP15); 3) RMs with CPAP for 30 secs (CPAP30); 4) RMs with stepwise increase in airway pressure (STEP) to targeted maximum within 15 secs (STEP15); and 5) RMs with STEP within 30 secs (STEP30). To perform STEP RMs, the ventilator was switched to a CPAP mode and positive end-expiratory pressure level was increased stepwise. At each step, airway pressure was held constant. RMs were targeted to 30 cm H(2)O. Animals were then ventilated for 1 hr with tidal volume of 6 mL/kg and positive end-expiratory pressure of 5 cm H(2)O. Measurements and Main Results: Blood gases, lung mechanics, histology (light and electronic microscopy), interleukin-6, caspase 3, and type 3 procollagen mRNA expressions in lung tissue. All RMs improved oxygenation and lung static elastance and reduced alveolar collapse compared to NR. STEP30 resulted in optimal performance, with: 1) improved lung static elastance vs. NR, CPAP15, and STEP15; 2) reduced alveolar-capillary membrane detachment and type 2 epithelial and endothelial cell injury scores vs. CPAP15 (p < .05); and 3) reduced gene expression of interleukin-6, type 3 procollagen, and caspase 3 in lung tissue vs. other RMs. Conclusions: Longer-duration RMs with slower airway pressure increase efficiently improved lung function, while minimizing the biological impact on lungs. (Crit Care Med 2011; 39:1074-1081)

Toward a better understanding of the influences on physical activity: The role of determinants, correlates, causal variables, mediators, moderators, and confounders

Background: For research on physical activity interventions to progress systematically, the mechanisms of action must be studied. In doing so, the research methods and their associated concepts and terminology become more complex. It is particularly important to clearly distinguish among determinants, correlates, mediators, moderators, and confounder variables used in physical activity research. This article examines the factors that are correlated with and that may have a causal relationship to physical activity. Methods and Results: We propose that the term correlate be used, instead of determinant, to describe statistical associations or correlations between measured variables and physical activity. Studies of the correlates of physical activity are reviewed. The findings of these studies can help to critique existing theories of health behavior change and can provide hypotheses to be tested in intervention studies from which it is possible to draw causal inferences. Mediator, moderator, and confounder variables can act to influence measured changes in physical activity. Intervening causal variables that are necessary to complete a cause-effect pathway between an intervention and physical activity are termed mediators. The relationship between an intervention and physical activity behaviors may vary for different groups; the strata by which they vary are levels of moderators of the relationship. Other factors may distort or affect the observed relationships between program exposure and physical activity, and are known as confounders. Conclusions: Consistent use of terms and additional research on mediators and moderators of intervention effects will improve our ability to understand and influence physical activity.

Effects of growth reducer and nitrogen fertilization on morphological variables, SPAD index, interception of radiation and productivity of wheat

ABSTRACT The objective of this study was to evaluate the effect of growth reducer and nitrogen fertilization on morphological variables, SPAD index, radiation interception, and grain yield of three cultivars of wheat. The experimental design was a randomized block in factorial scheme 3x5x2, with three cultivars (Mestre, Iguaçú and Itaipú), five nitrogen doses (0, 40, 80, 120, 160 Kg ha-1), and application or no application of a growth reducer, with three replications. The following characteristics were evaluated: plant height, SPAD index, leaf area index (LAI), Global Radiation Interception (GRI) and grain yield. The Tukey test (p < 0.05) was used for the comparison between the means of cultivar and growth reducer factors, and for a regression analysis to evaluate N levels. Increasing the dose of nitrogen promotes an increase in LAI of plants of wheat crops differently among cultivars, which leads to a greater degree of global radiation interception. At doses higher or equal to 120 Kg ha-1 of nitrogen, there are significant differences in grain yield between treatments with and without the application of the growth reducer. The significant interaction between growth reducer and nitrogen dose, showed that applications of growth reducer increase the GRI at doses above and below 80 Kg ha-1 of nitrogen. Nitrogen rates of 138 and 109 Kg ha-1 are responsible for maximum grain yields of wheat, which is 4235 and 3787 Kg ha-1 with and without the use of growth reducer, respectively.

Optimization of Cu(II) biosorption onto ascophyllum nodosum by factorial design methodology

A Box–Behnken factorial design coupled with surface response methodology was used to evaluate the effects of temperature, pH and initial concentration in the Cu(II) sorption process onto the marine macroalgae Ascophyllum nodosum. The effect of the operating variables on metal uptake capacitywas studied in a batch system and a mathematical model showing the influence of each variable and their interactions was obtained. Study ranges were 10–40ºC for temperature, 3.0–5.0 for pH and 50–150mgL−1 for initial Cu(II) concentration. Within these ranges, the biosorption capacity is slightly dependent on temperature but markedly increases with pH and initial concentration of Cu(II). The uptake capacities predicted by the model are in good agreement with the experimental values. Maximum biosorption capacity of Cu(II) by A. nodosum is 70mgg−1 and corresponds to the following values of those variables: temperature = 40ºC, pH= 5.0 and initial Cu(II) concentration = 150mgL−1.

Uncertainty propagation in inverse reliability-based design of composite structures

An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.

Soil sampling design and sampling techniques for soil properties monitoring – common difficulties related to forest soils

Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

Environmental indicator frameworks to design and assess environmental monitoring programs

Impact Assessment and Project Appraisal, vol. 22, n.1, March 2004, p. 47–62

Electro-Optical/Infrared sensor turret integration on an aircraft - structural im-pact on LOCKHEED MARTIN C-130H and design methodology

The growing need to patrol and survey large maritime and terrestrial areas increased the need to integrate external sensors on aircraft in order to accomplish those patrols at increasingly higher altitudes, longer range and not depending upon vehicle type. The main focus of this work is to elaborate a practical, simple, effective and efficient methodology for the aircraft modification procedure resulting from the integration of an Elec-tro-Optical/Infra-Red (EO/IR) turret through a support structure. The importance of the devel-opment of a good methodology relies on the correct management of project variables as time, available resources and project complexity. The key is to deliver a proper tool for a project de-sign team that will be used to create a solution that fulfils all technical, non-technical and certi-fication requirements present in this field of transportation. The created methodology is inde-pendent of two main inputs: sensor model and aircraft model definition, and therefore it is in-tended to deliver the results for different projects besides the one that was presented in this work as a case study. This particular case study presents the development of a structure support for FLIR STAR SAPHIRE III turret integration on the front lower fuselage bulkhead (radome) of the LOCKHEED MARTIN C-130 H. Development of the case study focuses on the study of local structural analysis through the use of Finite Element Method (FEM). Development of this Dissertation resulted in a cooperation between Faculty of Science and Technology - Universidade Nova de Lisboa and the company OGMA - Indústria Aeronáutica de Portugal

Development of a water-in-oil-in-water multiple emulsion system integrating biomimetic aqueous-core lipid nanodroplets for protein entity stabilization. Part I: experimental factorial design

Lipid nanoballoons integrating multiple emulsions of the type water-in-oil-in-water enclose, at least in theory, a biomimetic aqueous-core suitable for housing hydrophilic biomolecules such as proteins, peptides and bacteriophage particles. The research effort entertained in this paper reports a full statistical 23x31 factorial design study (three variables at two levels and one variable at three levels) to optimize biomimetic aqueous-core lipid nanoballoons for housing hydrophilic protein entities. The concentrations of protein, lipophilic and hydrophilic emulsifiers, and homogenization speed were set as the four independent variables, whereas the mean particle hydrodynamic size (HS), zeta potential (ZP) and polydispersity index (PI) were set as the dependent variables. The V23x31 factorial design constructed led to optimization of the higher (+1) and lower (-1) levels, with triplicate testing for the central (0) level, thus producing thirty three experiments and leading to selection of the optimized processing parameters as 0.015% (w/w) protein entity, 0.75% (w/w) lipophilic emulsifier (soybean lecithin) and 0.50% (w/w) hydrophilic emulsifier (poloxamer 188). In the present research effort, statistical optimization and production of protein derivatives encompassing full stabilization of their three-dimensional structure, has been attempted via housing said molecular entities within biomimetic aqueous-core lipid nanoballoons integrating a multiple (W/O/W) emulsion.

Rationale and design of a randomized, double-blind, placebo controlled multicenter trial to study efficacy, security, and long term effects of intermittent repeated levosimendan administration in patients with advanced heart failure: LAICA study.

BACKGROUND Advanced heart failure (HF) is associated with high morbidity and mortality; it represents a major burden for the health system. Episodes of acute decompensation requiring frequent and prolonged hospitalizations account for most HF-related expenditure. Inotropic drugs are frequently used during hospitalization, but rarely in out-patients. The LAICA clinical trial aims to evaluate the effectiveness and safety of monthly levosimendan infusion in patients with advanced HF to reduce the incidence of hospital admissions for acute HF decompensation. METHODS The LAICA study is a multicenter, prospective, randomized, double-blind, placebo-controlled, parallel group trial. It aims to recruit 213 out-patients, randomized to receive either a 24-h infusion of levosimendan at 0.1 μg/kg/min dose, without a loading dose, every 30 days, or placebo. RESULTS The main objective is to assess the incidence of admission for acute HF worsening during 12 months. Secondarily, the trial will assess the effect of intermittent levosimendan on other variables, including the time in days from randomization to first admission for acute HF worsening, mortality and serious adverse events. CONCLUSIONS The LAICA trial results could allow confirmation of the usefulness of intermittent levosimendan infusion in reducing the rate of hospitalization for HF worsening in advanced HF outpatients.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Experimental design on the simplex

Optimum experimental designs depend on the design criterion, the model andthe design region. The talk will consider the design of experiments for regressionmodels in which there is a single response with the explanatory variables lying ina simplex. One example is experiments on various compositions of glass such asthose considered by Martin, Bursnall, and Stillman (2001).Because of the highly symmetric nature of the simplex, the class of models thatare of interest, typically Scheff´e polynomials (Scheff´e 1958) are rather differentfrom those of standard regression analysis. The optimum designs are also ratherdifferent, inheriting a high degree of symmetry from the models.In the talk I will hope to discuss a variety of modes for such experiments. ThenI will discuss constrained mixture experiments, when not all the simplex is availablefor experimentation. Other important aspects include mixture experimentswith extra non-mixture factors and the blocking of mixture experiments.Much of the material is in Chapter 16 of Atkinson, Donev, and Tobias (2007).If time and my research allows, I would hope to finish with a few comments ondesign when the responses, rather than the explanatory variables, lie in a simplex.ReferencesAtkinson, A. C., A. N. Donev, and R. D. Tobias (2007). Optimum ExperimentalDesigns, with SAS. Oxford: Oxford University Press.Martin, R. J., M. C. Bursnall, and E. C. Stillman (2001). Further results onoptimal and efficient designs for constrained mixture experiments. In A. C.Atkinson, B. Bogacka, and A. Zhigljavsky (Eds.), Optimal Design 2000,pp. 225–239. Dordrecht: Kluwer.Scheff´e, H. (1958). Experiments with mixtures. Journal of the Royal StatisticalSociety, Ser. B 20, 344–360.1