Learned helplessness in the rat: Effect of response topography in a within-subject design

Three experiments investigated learned helplessness in rats manipulating response topography within-subject and different intervals between treatment and tests among groups. In Experiment 1, rats previously exposed to inescapable shocks were tested under an escape contingency where either jumping or nose poking was required to terminate shocks: tests were run either 1, 14 or 28 days after treatment. Most rats failed to jump, as expected, but learned to nose poke, regardless of the interval between treatment and tests and order of testing. The same results were observed in male and female rats from a different laboratory (Experiment 2) and despite increased exposure to the escape contingencies using a within-subject design (Experiment 3). Furthermore, no evidence of helplessness reversal was observed, since animals failed to jump even after having learned to nose-poke in a previous test session. These results are not consistent with a learned helplessness hypothesis, which claims that shock (un)controllability is the key variable responsible for the effect. They are nonetheless consistent with the view that inescapable shocks enhance control by irrelevant features of the relationship between the environment and behavior. (C) 2010 Elsevier B.V. All rights reserved.

Clinical trial design in non-invasive brain stimulation psychiatric research

Major depressive disorder (MDD) trials - investigating either non-pharmacological or pharmacological interventions - have shown mixed results. Many reasons explain this heterogeneity, but one that stands out is the trial design due to specific challenges in the field. We aimed therefore to review the methodology of non-invasive brain stimulation (NIBS) trials and provide a framework to improve clinical trial design. We performed a systematic review for randomized, controlled MDD trials whose intervention was transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS) in MEDLINE and other databases from April 2002 to April 2008. We created an unstructured checklist based on CONSORT guidelines to extract items such as power analysis, sham method, blinding assessment, allocation concealment, operational criteria used for MDD, definition of refractory depression and primary study hypotheses. Thirty-one studies were included. We found that the main methodological issues can be divided in to three groups: (1) issues related to phase II/small trials, (2) issues related to MDD trials and, (3) specific issues of NIBS studies. Taken together, they can threaten study validity and lead to inconclusive results. Feasible solutions include: estimating the sample size a priori; measuring the degree of refractoriness of the subjects; specifying the primary hypothesis and statistical tests; controlling predictor variables through stratification randomization methods or using strict eligibility criteria; adjusting the study design to the target population; using adaptive designs and exploring NIBS efficacy employing biological markers. In conclusion, our study summarizes the main methodological issues of NIBS trials and proposes a number of alternatives to manage them. Copyright (C) 2011 John Wiley & Sons, Ltd.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): Objectives and Design

Although low- and middle-income countries still bear the burden of major infectious diseases, chronic noncommunicable diseases are becoming increasingly common due to rapid demographic, epidemiologic, and nutritional transitions. However, information is generally scant in these countries regarding chronic disease incidence, social determinants, and risk factors. The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) aims to contribute relevant information with respect to the development and progression of clinical and subclinical chronic diseases, particularly cardiovascular diseases and diabetes. In this report, the authors delineate the study's objectives, principal methodological features, and timeline. At baseline, ELSA-Brasil enrolled 15,105 civil servants from 5 universities and 1 research institute. The baseline examination (2008-2010) included detailed interviews, clinical and anthropometric examinations, an oral glucose tolerance test, overnight urine collection, a 12-lead resting electrocardiogram, measurement of carotid intima-media thickness, echocardiography, measurement of pulse wave velocity, hepatic ultrasonography, retinal fundus photography, and an analysis of heart rate variability. Long-term biologic sample storage will allow investigation of biomarkers that may predict cardiovascular diseases and diabetes. Annual telephone surveillance, initiated in 2009, will continue for the duration of the study. A follow-up examination is scheduled for 2012-2013.

Design of a Comb Generator for High Capacity Coherent-WDM Systems

This paper presents a theoretical model developed for estimating the power, the optical signal to noise ratio and the number of generated carriers in a comb generator, having as a reference the minimum optical signal do noise ratio at the receiver input, for a given fiber link. Based on the recirculating frequency shifting technique, the generator relies on the use of coherent and orthogonal multi-carriers (Coherent-WDM) that makes use of a single laser source (seed) for feeding high capacity (above 100 Gb/s) systems. The theoretical model has been validated by an experimental demonstration, where 23 comb lines with an optical signal to noise ratio ranging from 25 to 33 dB, in a spectral window of similar to 3.5 nm, are obtained.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

Describing the Situational Contexts of Sweetened Product Consumption in a Middle Eastern Canadian Community: Application of a Mixed Method Design

Little is known about the situational contexts in which individuals consume processed sources of dietary sugars. This study aimed to describe the situational contexts associated with the consumption of sweetened food and drink products in a Catholic Middle Eastern Canadian community. A two-stage exploratory sequential mixed-method design was employed with a rationale of triangulation. In stage 1 (n = 62), items and themes describing the situational contexts of sweetened food and drink product consumption were identified from semi-structured interviews and were used to develop the content for the Situational Context Instrument for Sweetened Product Consumption (SCISPC). Face validity, readability and cultural relevance of the instrument were assessed. In stage 2 (n = 192), a cross-sectional study was conducted and exploratory factor analysis was used to examine the structure of themes that emerged from the qualitative analysis as a means of furthering construct validation. The SCISPC reliability and predictive validity on the daily consumption of sweetened products were also assessed. In stage 1, six themes and 40-items describing the situational contexts of sweetened product consumption emerged from the qualitative analysis and were used to construct the first draft of the SCISPC. In stage 2, factor analysis enabled the clarification and/or expansion of the instrument's initial thematic structure. The revised SCISPC has seven factors and 31 items describing the situational contexts of sweetened product consumption. Initial validation of the instrument indicated it has excellent internal consistency and adequate test-retest reliability. Two factors of the SCISPC had predictive validity for the daily consumption of total sugar from sweetened products (Snacking and Energy demands) while the other factors (Socialization, Indulgence, Constraints, Visual Stimuli and Emotional needs) were rather associated to occasional consumption of these products.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Linear parameter varying control design for rotating systems supported by journal bearings

Linear parameter varying (LPV) control is a model-based control technique that takes into account time-varying parameters of the plant. In the case of rotating systems supported by lubricated bearings, the dynamic characteristics of the bearings change in time as a function of the rotating speed. Hence, LPV control can tackle the problem of run-up and run-down operational conditions when dynamic characteristics of the rotating system change significantly in time due to the bearings and high vibration levels occur. In this work, the LPV control design for a flexible shaft supported by plain journal bearings is presented. The model used in the LPV control design is updated from unbalance response experimental results and dynamic coefficients for the entire range of rotating speeds are obtained by numerical optimization. Experimental implementation of the designed LPV control resulted in strong reduction of vibration amplitudes when crossing the critical speed, without affecting system behavior in sub- or supercritical speeds. (C) 2012 Elsevier Ltd. All rights reserved.

Influence of temperature, light and nutrients on the growth rates of the macroalga Gracilaria domingensis in synthetic seawater using experimental design

In the present study, the daily relative growth rates (DRGR, in percent per day) of the red macroalga Gracilaria domingensis in synthetic seawater was investigated for the combined influence of five factors, i.e., light (L), temperature (T), nitrate (N), phosphate (P), and molybdate (M), using a statistical design method. The ranges of the experimental cultivation conditions were T, 18-26A degrees C; L, 74-162 mu mol photons m(-2) s(-1); N, 40-80 mu mol L-1; P, 8-16 mu mol L-1; and M, 1-5 nmol L-1. The optimal conditions, which resulted in a maximum growth rate of a parts per thousand yen6.4% d(-1) from 7 to 10 days of cultivation, were determined by analysis of variance (ANOVA) multivariate factorial analysis (with a 2(5) full factorial design) to be L, 74 mu mol photons m(-2) s(-1); T, 26A degrees C; N, 80 mu mol L-1; P, 8 mu mol L-1; and M, 1 nmol L-1. In additional, these growth rate values are close to the growth rate values in natural medium (von Stosch medium), i.e., 6.5-7.0% d(-1). The results analyzed by the ANOVA indicate that the factors N and T are highly significant linear terms, X (L), (alpha = 0.05). On the other hand, the only significant quadratic term (X (Q)) was that for L. Statistically significant interactions between two different factors were found between T vs. L and N vs. T. Finally, a two-way (linear/quadratic interaction) model provided a quite reasonable correlation between the experimental and predicted DRGR values (R (adjusted) (2) = 0.9540).

Design-based random permutation models with auxiliary information

We extend the random permutation model to obtain the best linear unbiased estimator of a finite population mean accounting for auxiliary variables under simple random sampling without replacement (SRS) or stratified SRS. The proposed method provides a systematic design-based justification for well-known results involving common estimators derived under minimal assumptions that do not require specification of a functional relationship between the response and the auxiliary variables.

Design, synthesis and the effect of 1,2,3-triazole sialylmimetic neoglycoconjugates on Trypanosoma cruzi and its cell surface trans-sialidase

This work describes the synthesis of a series of sialylmimetic neoglycoconjugates represented by 1,4-disubstituted 1,2,3-triazole-sialic acid derivatives containing galactose modified at either C-1 or C-6 positions, glucose or gulose at C-3 position, and by the amino acid derivative 1,2,3-triazole fused threonine-3-O-galactose as potential TcTS inhibitors and anti-trypanosomal agents. This series was obtained by Cu(I)-catalysed azide-alkyne cycloaddition reaction ('click chemistry') between the azido-functionalized sugars 1-N(3)-Gal (commercial), 6-N(3)-Gal, 3-N(3)-Glc and 3-N(3)-Gul with the corresponding alkyne-based 2-propynyl-sialic acid, as well as by click chemistry reaction between the amino acid N(3)-ThrOBn with 3-O-propynyl-GalOMe. The 1,2,3-triazole linked sialic acid-6-O-galactose and the sialic acid-galactopyranoside showed high Trypanosoma cruzi trans-sialidase (TcTS) inhibitory activity at 1.0 mM (approx. 90%), whilst only the former displayed relevant trypanocidal activity (IC(50) 260 mu M). These results highlight the 1,2,3-triazole linked sialic acid-6-O-galactose as a prototype for further design of new neoglycoconjugates against Chagas' disease. (C) 2011 Elsevier Ltd. All rights reserved.

Revisiting the Security of the ALRED Design and Two of Its Variants: Marvin and LetterSoup

The ALRED construction is a lightweight strategy for constructing message authentication algorithms from an underlying iterated block cipher. Even though this construction's original analyses show that it is secure against some attacks, the absence of formal security proofs in a strong security model still brings uncertainty on its robustness. In this paper, aiming to give a better understanding of the security level provided by different authentication algorithms based on this design strategy, we formally analyze two ALRED variants-the MARVIN message authentication code and the LETTERSOUP authenticated-encryption scheme,-bounding their security as a function of the attacker's resources and of the underlying cipher's characteristics.

The effect of implant design on insertion torque and immediate micromotion

Objectives: To evaluate the effect of insertion torque on micromotion to a lateral force in three different implant designs. Material and methods: Thirty-six implants with identical thread design, but different cutting groove design were divided in three groups: (1) non-fluted (no cutting groove, solid screw-form); (2) fluted (901 cut at the apex, tap design); and (3) Blossomt (Patent pending) (non-fluted with engineered trimmed thread design). The implants were screwed into polyurethane foam blocks and the insertion torque was recorded after each turn of 901 by a digital torque gauge. Controlled lateral loads of 10N followed by increments of 5 up to 100N were sequentially applied by a digital force gauge on a titanium abutment. Statistical comparison was performed with two-way mixed model ANOVA that evaluated implant design group, linear effects of turns and displacement loads, and their interaction. Results: While insertion torque increased as a function of number of turns for each design, the slope and final values increased (Po0.001) progressively from the Blossomt to the fluted to the non-fluted design (M +/- standard deviation [SD] = 64.1 +/- 26.8, 139.4 +/- 17.2, and 205.23 +/- 24.3 Ncm, respectively). While a linear relationship between horizontal displacement and lateral force was observed for each design, the slope and maximal displacement increased (Po0.001) progressively from the Blossomt to the fluted to the non-fluted design (M +/- SD 530 +/- 57.7, 585.9 +/- 82.4, and 782.33 +/- 269.4 mm, respectively). There was negligible to moderate levels of association between insertion torque and lateral displacement in the Blossomt, fluted and non-fluted design groups, respectively. Conclusion: Insertion torque was reduced in implant macrodesigns that incorporated cutting edges, and lesser insertion torque was generally associated with decreased micromovement. However, insertion torque and micromotion were unrelated within implant designs, particularly for those designs showing the least insertion torque.