Determination of corn stalk fibers' strength through modeling of the mechanical properties of its composites

Worldwide cultivation of corn is expanding, due in part to the increasing production of bioethanol. In consequence, huge amounts of corn stalks residues are been produced. Instead of incineration, we transformed the corn stalks into a semichemical pulp and successfully applied it as reinforcement in polypropylene composites. PP composites reinforced with 40% wt corn stalk single fibers were prepared, and their mechanical properties were evaluated. Through mechanical properties modeling of the composites, the intrinsic tensile strength of the cellulosic fibers that constitute the corn stalk have been determined

Reward networks in the brain as captured by connectivity measures

An assortment of human behaviors is thought to be driven by rewards including reinforcement learning, novelty processing, learning, decision making, economic choice, incentive motivation, and addiction. In each case the ventral tegmental area/ventral striatum (nucleus accumbens) (VTAVS) system has been implicated as a key structure by functional imaging studies, mostly on the basis of standard, univariate analyses. Here we propose that standard functional magnetic resonance imaging analysis needs to be complemented by methods that take into account the differential connectivity of the VTAVS system in the different behavioral contexts in order to describe reward based processes more appropriately. We fi rst consider the wider network for reward processing as it emerged from animal experimentation. Subsequently, an example for a method to assess functional connectivity is given. Finally, we illustrate the usefulness of such analyses by examples regarding reward valuation, reward expectation and the role of reward in addiction.

Assessing functional relations in single-case designs: Quantitative proposals in the context of the evidence-based movement

In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications.

Blocking and unblocking in a navigation task

Rodrigo, Chamizo, McLaren, & Mackintosh (1997) demonstrated the blocking effect in a navigational task using a swimming pool: rats initially trained to use three landmarks (ABC) to find an invisible platform learned less about a fourth landmark (X) added later than did rats trained from the outset with these four landmarks (ABCX). The aim of the experiment reported here was to demonstrate unblocking using a similar procedure as in the previous work. Three groups of rats were initially trained to find an invisible platfom in the presence of three landmarks: ABC for the Blocking and Unblocking groups and LMN for the Control group. Then, all animals were trained to find the platform in the presence of four landmarks, ABCX. In this second training, unlike animals in the Blocking group to which only a new landmark (X) was added in comparison to the first training, the animals in the Unblocking group also had a change in the platform position. In the Control group, both the four landmarks and the platform position were totally new at the beginning of this second training. As in Rodrigo et al. (1997) a blocking effect was found: rats in the Blocking group learned less with respect to the added landmark (X) than did animals in the Control group. However, rats in the Unblocking group learned about the added landmark (X) as well as did animals in the Control group. The results are interpreted as an unblocking effect due to a change in the platform position between the two phases of training, similarly to what is normal in classical conditioning experiments, in which a change in the conditions of reinforcement between the two training phases of a blocking design produce an attenuation or elimination of this effect. These results are explained within an error-correcting connectionist account of spatial navigation (McLaren, 2002).