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.

Influence of pattern gradation on the design of piezocomposite energy harvesting devices using topology optimization

Piezoelectric materials can be used to convert oscillatory mechanical energy into electrical energy. Energy harvesting devices are designed to capture the ambient energy surrounding the electronics and convert it into usable electrical energy. The design of energy harvesting devices is not obvious, requiring optimization procedures. This paper investigates the influence of pattern gradation using topology optimization on the design of piezocomposite energy harvesting devices based on bending behavior. The objective function consists of maximizing the electric power generated in a load resistor. A projection scheme is employed to compute the element densities from design variables and control the length scale of the material density. Examples of two-dimensional piezocomposite energy harvesting devices are presented and discussed using the proposed method. The numerical results illustrate that pattern gradation constraints help to increase the electric power generated in a load resistor and guides the problem toward a more stable solution. (C) 2012 Elsevier Ltd. All rights reserved.

Symmetry insights for design of supercomputer network topologies: roots and weights lattices

We present a family of networks whose local interconnection topologies are generated by the root vectors of a semi-simple complex Lie algebra. Cartan classification theorem of those algebras ensures those families of interconnection topologies to be exhaustive. The global arrangement of the network is defined in terms of integer or half-integer weight lattices. The mesh or torus topologies that network millions of processing cores, such as those in the IBM BlueGene series, are the simplest member of that category. The symmetries of the root systems of an algebra, manifested by their Weyl group, lends great convenience for the design and analysis of hardware architecture, algorithms and programs.

Determination of Opiates in Whole Blood and Vitreous Humor: A Study of the Matrix Effect and an Experimental Design to Optimize Conditions for the Enzymatic Hydrolysis of Glucuronides

Faculty of Medicine University of Sao Paulo

Optimized Duration of Clopidogrel Therapy Following Treatment with the Endeavor Zotarolimus-Eluting Stent in Real-World Clinical Practice (OPTIMIZE) Trial: Rationale and design of a large-scale, randomized, multicenter study

Background Current recommendations for antithrombotic therapy after drug-eluting stent (DES) implantation include prolonged dual antiplatelet therapy (DAPT) with aspirin and clopidogrel >= 12 months. However, the impact of such a regimen for all patients receiving any DES system remains unclear based on scientific evidence available to date. Also, several other shortcomings have been identified with prolonged DAPT, including bleeding complications, compliance, and cost. The second-generation Endeavor zotarolimus-eluting stent (E-ZES) has demonstrated efficacy and safety, despite short duration DAPT (3 months) in the majority of studies. Still, the safety and clinical impact of short-term DAPT with E-ZES in the real world is yet to be determined. Methods The OPTIMIZE trial is a large, prospective, multicenter, randomized (1: 1) non-inferiority clinical evaluation of short-term (3 months) vs long-term (12-months) DAPT in patients undergoing E-ZES implantation in daily clinical practice. Overall, 3,120 patients were enrolled at 33 clinical sites in Brazil. The primary composite endpoint is death (any cause), myocardial infarction, cerebral vascular accident, and major bleeding at 12-month clinical follow-up post-index procedure. Conclusions The OPTIMIZE clinical trial will determine the clinical implications of DAPT duration with the second generation E-ZES in real-world patients undergoing percutaneous coronary intervention. (Am Heart J 2012;164:810-816.e3.)

What is Missing for Traditional Design-Centric Engineering Education to Better Prepare Newly Graduated Engineers for the Global Era?

This paper presents an analysis of the capacity of design centric methodologies to prepare engineering students to succeed in the market. Gaps are brainstormed and analyzed with reference to their importance. Reasons that may lead the newly graduated engineers not to succeed right from the beginning of their professional lives have also been evaluated. A comparison among the two subjects above was prepared, reviewed and analyzed. The influence of multidisciplinary, multicultural and complex environmental influences created in the current global business era is taken into account. The industry requirements in terms of what they expect to 'receive' from their engineers are evaluated and compared to the remaining of the study above. An innovative approach to current engineering education that utilizes traditional design-centric methodologies is then proposed, aggregating new disciplines to supplement the traditional engineering education. The solution encompasses the inclusion of disciplines from Human Sciences and Emotional Intelligence fields willing to better prepare the engineer of tomorrow to work in a multidisciplinary, globalized, complex and team working environment. A pilot implementation of such an approach is reviewed and conclusions are drawn from this educational project.