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.

Semiotics of Communication: From Semiosis of Nature to Culture

Communication Studies currently undergoes a crisis of paradigms that requires an ontological review that must begin with a debate about the conditions of possibility of every communicational phenomena. In this article we argue that semiosis offers a conceptual framework that allows for the study of communication as qualitative action. Semiosis, or the action of the sign, is here defined as a fundamental process based on perception that models the world of species, creating cognition and culture. At the core of semiosis are dynamic structures that the authors have defined as 'ontological diagrams'. The first purpose of Semiotics of Communication is to understand how these modeling systems evolve ontologically and phylogenically, producing, in the case of human culture, means of communication ever more varied and technologically advanced.

Anti-Aversive Effects of Cannabidiol on Innate Fear-Induced Behaviors Evoked by an Ethological Model of Panic Attacks Based on a Prey vs the Wild Snake Epicrates cenchria crassus Confrontation Paradigm

Several pharmacological targets have been proposed as modulators of panic-like reactions. However, interest should be given to other potential therapeutic neurochemical agents. Recent attention has been given to the potential anxiolytic properties of cannabidiol, because of its complex actions on the endocannabinoid system together with its effects on other neurotransmitter systems. The aim of this study was to investigate the effects of cannabidiol on innate fear-related behaviors evoked by a prey vs predator paradigm. Male Swiss mice were submitted to habituation in an arena containing a burrow and subsequently pre-treated with intraperitoneal administrations of vehicle or cannabidiol. A constrictor snake was placed inside the arena, and defensive and non-defensive behaviors were recorded. Cannabidiol caused a clear anti-aversive effect, decreasing explosive escape and defensive immobility behaviors outside and inside the burrow. These results show that cannabidiol modulates defensive behaviors evoked by the presence of threatening stimuli, even in a potentially safe environment following a fear response, suggesting a panicolytic effect. Neuropsychopharmacology (2012) 37, 412-421; doi:10.1038/npp.2011.188; published online 14 September 2011

Structure- and ligand-based drug design approaches for neglected tropical diseases

Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.

Longitudinal brain volumetric changes during one year in non-elderly healthy adults: a voxel-based morphometry study

Previous cross-sectional magnetic resonance imaging (MRI) studies of healthy aging in young adults have indicated the presence of significant inverse correlations between age and gray matter volumes, although not homogeneously across all brain regions. However, such cross-sectional studies have important limitations and there is a scarcity of detailed longitudinal MRI studies with repeated measures obtained in the same individuals in order to investigate regional gray matter changes during short periods of time in non-elderly healthy adults. In the present study, 52 healthy young adults aged 18 to 50 years (27 males and 25 females) were followed with repeated MRI acquisitions over approximately 15 months. Gray matter volumes were compared between the two times using voxel-based morphometry, with the prediction that volume changes would be detectable in the frontal lobe, temporal neocortex and hippocampus. Voxel-wise analyses showed significant (P < 0.05, family-wise error corrected) relative volume reductions of gray matter in two small foci located in the right orbitofrontal cortex and left hippocampus. Separate comparisons for males and females showed bilateral gray matter relative reductions in the orbitofrontal cortex over time only in males. We conclude that, in non-elderly healthy adults, subtle gray matter volume alterations are detectable after short periods of time. This underscores the dynamic nature of gray matter changes in the brain during adult life, with regional volume reductions being detectable in brain regions that are relevant to cognitive and emotional processes.

A semi-supervised classification technique based on interacting forces

Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.

Molecular origin of charge traps in polyfluorene-based semiconductors

The comprehensive control of morphology and structure is of extreme importance in semiconducting polymers when used as active layers in optoelectronic devices. In the work reported here, a systematic investigation of the structural and dynamical properties of poly(9,9-di-n-octyl-fluorene-alt-benzothiadiazole), known as F8BT, and their correlation with electrical properties is presented when the material is used as an active layer in optoelectronic devices. By means of X-ray diffraction, one observes that in thick layer films (thickness of about 4 μm) grown by drop-cast deposition, a solvent induced crystalline phase exists which evolves to a stable phase as the temperature is raised. This was not observed in thin films (thickness of about 250 nm) prepared by spin-coating within the investigated temperature range. By modeling the current-voltages characteristics of both thick and thin film devices, important information on the influence of crystallization on the trapping states could be drawn. Furthermore, the temperature dependence of the charge carrier mobility was found to be closely related to that of the molecular relaxation processes. The understanding of the nature of such molecular relaxations, measured by solid-state nuclear magnetic resonance methods, allows one to understand the importance of molecular relaxations and microstructure changes on the trap states of the system.